diff --git a/backend/config.yaml b/backend/config.yaml new file mode 100644 index 0000000..32b9823 --- /dev/null +++ b/backend/config.yaml @@ -0,0 +1,13 @@ +redis: + address: + port: + DB: + protocol: + password: +database: + address: + port: + user: + password: + + diff --git a/backend/src/go.mod b/backend/src/go.mod new file mode 100644 index 0000000..78788ed --- /dev/null +++ b/backend/src/go.mod @@ -0,0 +1,31 @@ +module backend + +go 1.24.2 + +replace signin => ./session_processing + +require ( + github.com/spf13/viper v1.20.1 + signin v0.0.0-00010101000000-000000000000 +) + +require ( + github.com/cespare/xxhash/v2 v2.3.0 // indirect + github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f // indirect + github.com/fsnotify/fsnotify v1.8.0 // indirect + github.com/go-viper/mapstructure/v2 v2.2.1 // indirect + github.com/pelletier/go-toml/v2 v2.2.3 // indirect + github.com/redis/go-redis/v9 v9.7.3 // indirect + github.com/sagikazarmark/locafero v0.7.0 // indirect + github.com/sourcegraph/conc v0.3.0 // indirect + github.com/spf13/afero v1.12.0 // indirect + github.com/spf13/cast v1.7.1 // indirect + github.com/spf13/pflag v1.0.6 // indirect + github.com/subosito/gotenv v1.6.0 // indirect + go.uber.org/atomic v1.9.0 // indirect + go.uber.org/multierr v1.9.0 // indirect + golang.org/x/crypto v0.36.0 // indirect + golang.org/x/sys v0.31.0 // indirect + golang.org/x/text v0.23.0 // indirect + gopkg.in/yaml.v3 v3.0.1 // indirect +) diff --git a/backend/src/go.sum b/backend/src/go.sum new file mode 100644 index 0000000..4fd6df8 --- /dev/null +++ b/backend/src/go.sum @@ -0,0 +1,64 @@ +github.com/bsm/ginkgo/v2 v2.12.0 h1:Ny8MWAHyOepLGlLKYmXG4IEkioBysk6GpaRTLC8zwWs= +github.com/bsm/ginkgo/v2 v2.12.0/go.mod h1:SwYbGRRDovPVboqFv0tPTcG1sN61LM1Z4ARdbAV9g4c= +github.com/bsm/gomega v1.27.10 h1:yeMWxP2pV2fG3FgAODIY8EiRE3dy0aeFYt4l7wh6yKA= +github.com/bsm/gomega v1.27.10/go.mod h1:JyEr/xRbxbtgWNi8tIEVPUYZ5Dzef52k01W3YH0H+O0= +github.com/cespare/xxhash/v2 v2.3.0 h1:UL815xU9SqsFlibzuggzjXhog7bL6oX9BbNZnL2UFvs= +github.com/cespare/xxhash/v2 v2.3.0/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs= +github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c= +github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f h1:lO4WD4F/rVNCu3HqELle0jiPLLBs70cWOduZpkS1E78= +github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f/go.mod h1:cuUVRXasLTGF7a8hSLbxyZXjz+1KgoB3wDUb6vlszIc= +github.com/frankban/quicktest v1.14.6 h1:7Xjx+VpznH+oBnejlPUj8oUpdxnVs4f8XU8WnHkI4W8= +github.com/frankban/quicktest v1.14.6/go.mod h1:4ptaffx2x8+WTWXmUCuVU6aPUX1/Mz7zb5vbUoiM6w0= +github.com/fsnotify/fsnotify v1.8.0 h1:dAwr6QBTBZIkG8roQaJjGof0pp0EeF+tNV7YBP3F/8M= +github.com/fsnotify/fsnotify v1.8.0/go.mod h1:8jBTzvmWwFyi3Pb8djgCCO5IBqzKJ/Jwo8TRcHyHii0= +github.com/go-viper/mapstructure/v2 v2.2.1 h1:ZAaOCxANMuZx5RCeg0mBdEZk7DZasvvZIxtHqx8aGss= +github.com/go-viper/mapstructure/v2 v2.2.1/go.mod h1:oJDH3BJKyqBA2TXFhDsKDGDTlndYOZ6rGS0BRZIxGhM= +github.com/google/go-cmp v0.6.0 h1:ofyhxvXcZhMsU5ulbFiLKl/XBFqE1GSq7atu8tAmTRI= +github.com/google/go-cmp v0.6.0/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY= +github.com/kr/pretty v0.3.1 h1:flRD4NNwYAUpkphVc1HcthR4KEIFJ65n8Mw5qdRn3LE= +github.com/kr/pretty v0.3.1/go.mod h1:hoEshYVHaxMs3cyo3Yncou5ZscifuDolrwPKZanG3xk= +github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY= +github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE= +github.com/pelletier/go-toml/v2 v2.2.3 h1:YmeHyLY8mFWbdkNWwpr+qIL2bEqT0o95WSdkNHvL12M= +github.com/pelletier/go-toml/v2 v2.2.3/go.mod h1:MfCQTFTvCcUyyvvwm1+G6H/jORL20Xlb6rzQu9GuUkc= +github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM= +github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4= +github.com/redis/go-redis/v9 v9.7.3 h1:YpPyAayJV+XErNsatSElgRZZVCwXX9QzkKYNvO7x0wM= +github.com/redis/go-redis/v9 v9.7.3/go.mod h1:bGUrSggJ9X9GUmZpZNEOQKaANxSGgOEBRltRTZHSvrA= +github.com/rogpeppe/go-internal v1.9.0 h1:73kH8U+JUqXU8lRuOHeVHaa/SZPifC7BkcraZVejAe8= +github.com/rogpeppe/go-internal v1.9.0/go.mod h1:WtVeX8xhTBvf0smdhujwtBcq4Qrzq/fJaraNFVN+nFs= +github.com/sagikazarmark/locafero v0.7.0 h1:5MqpDsTGNDhY8sGp0Aowyf0qKsPrhewaLSsFaodPcyo= +github.com/sagikazarmark/locafero v0.7.0/go.mod h1:2za3Cg5rMaTMoG/2Ulr9AwtFaIppKXTRYnozin4aB5k= +github.com/sourcegraph/conc v0.3.0 h1:OQTbbt6P72L20UqAkXXuLOj79LfEanQ+YQFNpLA9ySo= +github.com/sourcegraph/conc v0.3.0/go.mod h1:Sdozi7LEKbFPqYX2/J+iBAM6HpqSLTASQIKqDmF7Mt0= +github.com/spf13/afero v1.12.0 h1:UcOPyRBYczmFn6yvphxkn9ZEOY65cpwGKb5mL36mrqs= +github.com/spf13/afero v1.12.0/go.mod h1:ZTlWwG4/ahT8W7T0WQ5uYmjI9duaLQGy3Q2OAl4sk/4= +github.com/spf13/cast v1.7.1 h1:cuNEagBQEHWN1FnbGEjCXL2szYEXqfJPbP2HNUaca9Y= +github.com/spf13/cast v1.7.1/go.mod h1:ancEpBxwJDODSW/UG4rDrAqiKolqNNh2DX3mk86cAdo= +github.com/spf13/pflag v1.0.6 h1:jFzHGLGAlb3ruxLB8MhbI6A8+AQX/2eW4qeyNZXNp2o= +github.com/spf13/pflag v1.0.6/go.mod h1:McXfInJRrz4CZXVZOBLb0bTZqETkiAhM9Iw0y3An2Bg= +github.com/spf13/viper v1.20.1 h1:ZMi+z/lvLyPSCoNtFCpqjy0S4kPbirhpTMwl8BkW9X4= +github.com/spf13/viper v1.20.1/go.mod h1:P9Mdzt1zoHIG8m2eZQinpiBjo6kCmZSKBClNNqjJvu4= +github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME= +github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI= +github.com/stretchr/testify v1.10.0 h1:Xv5erBjTwe/5IxqUQTdXv5kgmIvbHo3QQyRwhJsOfJA= +github.com/stretchr/testify v1.10.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY= +github.com/subosito/gotenv v1.6.0 h1:9NlTDc1FTs4qu0DDq7AEtTPNw6SVm7uBMsUCUjABIf8= +github.com/subosito/gotenv v1.6.0/go.mod h1:Dk4QP5c2W3ibzajGcXpNraDfq2IrhjMIvMSWPKKo0FU= +go.uber.org/atomic v1.9.0 h1:ECmE8Bn/WFTYwEW/bpKD3M8VtR/zQVbavAoalC1PYyE= +go.uber.org/atomic v1.9.0/go.mod h1:fEN4uk6kAWBTFdckzkM89CLk9XfWZrxpCo0nPH17wJc= +go.uber.org/multierr v1.9.0 h1:7fIwc/ZtS0q++VgcfqFDxSBZVv/Xo49/SYnDFupUwlI= +go.uber.org/multierr v1.9.0/go.mod h1:X2jQV1h+kxSjClGpnseKVIxpmcjrj7MNnI0bnlfKTVQ= +golang.org/x/crypto v0.36.0 h1:AnAEvhDddvBdpY+uR+MyHmuZzzNqXSe/GvuDeob5L34= +golang.org/x/crypto v0.36.0/go.mod h1:Y4J0ReaxCR1IMaabaSMugxJES1EpwhBHhv2bDHklZvc= +golang.org/x/sys v0.31.0 h1:ioabZlmFYtWhL+TRYpcnNlLwhyxaM9kWTDEmfnprqik= +golang.org/x/sys v0.31.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k= +golang.org/x/text v0.23.0 h1:D71I7dUrlY+VX0gQShAThNGHFxZ13dGLBHQLVl1mJlY= +golang.org/x/text v0.23.0/go.mod h1:/BLNzu4aZCJ1+kcD0DNRotWKage4q2rGVAg4o22unh4= +gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0= +gopkg.in/check.v1 v1.0.0-20190902080502-41f04d3bba15 h1:YR8cESwS4TdDjEe65xsg0ogRM/Nc3DYOhEAlW+xobZo= +gopkg.in/check.v1 v1.0.0-20190902080502-41f04d3bba15/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0= +gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA= +gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM= diff --git a/backend/src/main.go b/backend/src/main.go new file mode 100644 index 0000000..4c5641e --- /dev/null +++ b/backend/src/main.go @@ -0,0 +1,48 @@ +package main + +import ( + "fmt" + "signin" + + "github.com/spf13/viper" +) + +func setupConfig() { + viper.SetConfigName("config") + viper.SetConfigType("yaml") + viper.AddConfigPath("..") + viper.AddConfigPath(".") + + if err := viper.ReadInConfig(); err != nil { + if _, ok := err.(viper.ConfigFileNotFoundError); ok { + // Config file not found; ignore error if desired + } else { + // Config file was found but another error was produced + } + } +} + +func main() { + // fmt.Println("hi") + // params := signin.DefaultArgon2Params + + // test, _ := params.GeneratePassEncoding("hello") + // fmt.Println(test) + + // fmt.Println(signin.CheckPasswordAgainstEncoding("hello", test)) + // fmt.Println(signin.CheckPasswordAgainstEncoding("hello1", test)) + + // authenticate.test2() + setupConfig() + + // fmt.Println(viper.AllKeys()) + // redis := viper.GetStringMapString("redis") + // fmt.Println(viper.Get("redis")) + // fmt.Println(redis["address"]) + + err := signin.InitializeRedis(viper.GetStringMapString("redis")) + fmt.Println(err) + // fmt.Println(rs) + // fmt.Println(map[string]int{"a": 1, "b": 2, "c": 3}) + +} diff --git a/backend/src/session_processing/go.mod b/backend/src/session_processing/go.mod new file mode 100644 index 0000000..c2d3e51 --- /dev/null +++ b/backend/src/session_processing/go.mod @@ -0,0 +1,14 @@ +module signin + +go 1.24.2 + +require ( + github.com/redis/go-redis/v9 v9.7.3 + golang.org/x/crypto v0.36.0 +) + +require ( + github.com/cespare/xxhash/v2 v2.2.0 // indirect + github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f // indirect + golang.org/x/sys v0.31.0 // indirect +) diff --git a/backend/src/session_processing/go.sum b/backend/src/session_processing/go.sum new file mode 100644 index 0000000..2622b04 --- /dev/null +++ b/backend/src/session_processing/go.sum @@ -0,0 +1,14 @@ +github.com/bsm/ginkgo/v2 v2.12.0 h1:Ny8MWAHyOepLGlLKYmXG4IEkioBysk6GpaRTLC8zwWs= +github.com/bsm/ginkgo/v2 v2.12.0/go.mod h1:SwYbGRRDovPVboqFv0tPTcG1sN61LM1Z4ARdbAV9g4c= +github.com/bsm/gomega v1.27.10 h1:yeMWxP2pV2fG3FgAODIY8EiRE3dy0aeFYt4l7wh6yKA= +github.com/bsm/gomega v1.27.10/go.mod h1:JyEr/xRbxbtgWNi8tIEVPUYZ5Dzef52k01W3YH0H+O0= +github.com/cespare/xxhash/v2 v2.2.0 h1:DC2CZ1Ep5Y4k3ZQ899DldepgrayRUGE6BBZ/cd9Cj44= +github.com/cespare/xxhash/v2 v2.2.0/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs= +github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f h1:lO4WD4F/rVNCu3HqELle0jiPLLBs70cWOduZpkS1E78= +github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f/go.mod h1:cuUVRXasLTGF7a8hSLbxyZXjz+1KgoB3wDUb6vlszIc= +github.com/redis/go-redis/v9 v9.7.3 h1:YpPyAayJV+XErNsatSElgRZZVCwXX9QzkKYNvO7x0wM= +github.com/redis/go-redis/v9 v9.7.3/go.mod h1:bGUrSggJ9X9GUmZpZNEOQKaANxSGgOEBRltRTZHSvrA= +golang.org/x/crypto v0.36.0 h1:AnAEvhDddvBdpY+uR+MyHmuZzzNqXSe/GvuDeob5L34= +golang.org/x/crypto v0.36.0/go.mod h1:Y4J0ReaxCR1IMaabaSMugxJES1EpwhBHhv2bDHklZvc= +golang.org/x/sys v0.31.0 h1:ioabZlmFYtWhL+TRYpcnNlLwhyxaM9kWTDEmfnprqik= +golang.org/x/sys v0.31.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k= diff --git a/backend/src/session_processing/hash_and_check.go b/backend/src/session_processing/hash_and_check.go new file mode 100644 index 0000000..2e80aeb --- /dev/null +++ b/backend/src/session_processing/hash_and_check.go @@ -0,0 +1,128 @@ +package signin + +// credit to https://www.alexedwards.net/blog/how-to-hash-and-verify-passwords-with-argon2-in-go + +import ( + "fmt" + "runtime" + "strings" + + "golang.org/x/crypto/argon2" + + "crypto/rand" + "crypto/subtle" + "encoding/base64" + "errors" +) + +// PUBLIC METHODS AND STRUCTURES + +// argon2 parameter struct +type Argon2params struct { + Memory uint32 + Iterations uint32 + Parallelism uint8 + SaltLength uint32 + KeyLength uint32 +} + +var DefaultArgon2Params = &Argon2params{ + Memory: 64 * 1024, + Iterations: 1, + Parallelism: uint8(runtime.NumCPU()), + SaltLength: 16, + KeyLength: 32, +} + +func (p *Argon2params) GeneratePassEncoding(password string) (encoding string, err error) { + salt, err := generateRandomBytes(p.SaltLength) + if err != nil { + return "", err + } + + hash := argon2.IDKey([]byte(password), salt, p.Iterations, p.Memory, p.Parallelism, p.KeyLength) + + // Base64 encode the salt and hashed password. + b64Salt := base64.RawStdEncoding.EncodeToString(salt) + b64Hash := base64.RawStdEncoding.EncodeToString(hash) + + // Return a string using the standard encoded hash representation. + encoding = fmt.Sprintf("$argon2id$v=%d$m=%d,t=%d,p=%d$%s$%s", argon2.Version, p.Memory, p.Iterations, p.Parallelism, b64Salt, b64Hash) + + return encoding, nil +} + +func CheckPasswordAgainstEncoding(password string, encodedHash string) (match bool, err error) { + p, salt, hash, err := decodeHash(encodedHash) + if err != nil { + return false, err + } + + // Derive the key from the other password using the same parameters. + otherHash := argon2.IDKey([]byte(password), salt, p.Iterations, p.Memory, p.Parallelism, p.KeyLength) + + // Check that the contents of the hashed passwords are identical. Note + // that we are using the subtle.ConstantTimeCompare() function for this + // to help prevent timing attacks. + if subtle.ConstantTimeCompare(hash, otherHash) == 1 { + return true, nil + } + return false, nil +} + +// PRIVATE STUFF + +// error statements +var ErrInvalidHash = errors.New("the encoded hash is not in the correct format") +var ErrIncompatibleVersion = errors.New("incompatible version of argon2") + +func decodeHash(encodedHash string) (p *Argon2params, salt []byte, hash []byte, err error) { + + vals := strings.Split(encodedHash, "$") + if len(vals) != 6 { + return nil, nil, nil, ErrInvalidHash + } + + var version int + _, err = fmt.Sscanf(vals[2], "v=%d", &version) + if err != nil { + return nil, nil, nil, err + } + if version != argon2.Version { + return nil, nil, nil, ErrIncompatibleVersion + } + + p = &Argon2params{} + _, err = fmt.Sscanf(vals[3], "m=%d,t=%d,p=%d", &p.Memory, &p.Iterations, &p.Parallelism) + if err != nil { + return nil, nil, nil, err + } + + salt, err = base64.RawStdEncoding.Strict().DecodeString(vals[4]) + if err != nil { + return nil, nil, nil, err + } + p.SaltLength = uint32(len(salt)) + + hash, err = base64.RawStdEncoding.Strict().DecodeString(vals[5]) + if err != nil { + return nil, nil, nil, err + } + p.KeyLength = uint32(len(hash)) + + return p, salt, hash, nil + +} + +func generateRandomBytes(saltLen uint32) ([]byte, error) { + + var bytes []byte = make([]byte, saltLen) + + _, err := rand.Read(bytes) + + if err != nil { + return nil, err + } + + return bytes, nil +} diff --git a/backend/src/session_processing/session_check.go b/backend/src/session_processing/session_check.go new file mode 100644 index 0000000..2b0e666 --- /dev/null +++ b/backend/src/session_processing/session_check.go @@ -0,0 +1,101 @@ +package signin + +import ( + "errors" + "strconv" + "time" + + "github.com/redis/go-redis/v9" +) + +// implement a periodic function to clean up the redis database of old tokens + +var redis_client *redis.Client = nil + +type session_data struct { + token string + username string + expiresAt time.Time +} + +type redisSettings struct { + host string + port uint16 + password string + db uint64 + protocol uint64 +} + +var ( + ErrInvalidRedisPort = errors.New("Invalid Redis Port") + ErrInvalidRedisDB = errors.New("Invalid Redis DB mode") + ErrInvalidRedisProtocol = errors.New("Invalid Redis Protocol") +) + +func processSettingsMap(settings map[string]string, setting_struct *redisSettings) error { + for key, val := range settings { + if val == "" { + continue + } + switch key { + case "host": + setting_struct.host = val + case "port": + s, err := strconv.ParseUint(val, 10, 16) + if s < 3000 || err != nil { + return ErrInvalidRedisPort + } + setting_struct.port = uint16(s) + case "password": + setting_struct.password = val + case "db": + s, err := strconv.ParseUint(val, 10, 64) + if err != nil { + return ErrInvalidRedisDB + } + setting_struct.db = s + case "protocol": + s, err := strconv.ParseUint(val, 10, 64) + if err != nil { + return ErrInvalidRedisProtocol + } + setting_struct.db = s + } + } + return nil +} + +func Login() { // add entry into + +} + +func ValidateSession(token string) bool { // check if it's a valid session against the redis database + return false +} + +func InitializeRedis(settings map[string]string) error { + + // pulling settings from env map + redis_setup := &redisSettings{ + host: "localhost", + port: 6379, + password: "", + db: 0, + protocol: 2, + } + + err := processSettingsMap(settings, redis_setup) + if err != nil { + return err + } + + // initializing redis connection + redis_client = redis.NewClient(&redis.Options{ + Addr: string(strconv.AppendUint([]byte(redis_setup.host+":"), uint64(redis_setup.port), 10)), + Password: redis_setup.password, + DB: int(redis_setup.db), + Protocol: int(redis_setup.protocol), + }) + + return nil +} diff --git a/code/autocropper/.vscode/c_cpp_properties.json b/code/autocropper/.vscode/c_cpp_properties.json deleted file mode 100644 index 8e82922..0000000 --- a/code/autocropper/.vscode/c_cpp_properties.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "configurations": [ - { - "name": "Linux", - "includePath": [ - "${workspaceFolder}/**" - ], - "defines": [], - "compilerPath": "/usr/bin/gcc", - // "cStandard": "c17", - // "cppStandard": "gnu++17", - "intelliSenseMode": "linux-gcc-x64", - "configurationProvider": "ms-vscode.cmake-tools" - } - ], - "version": 4 -} \ No newline at end of file diff --git a/code/autocropper/.vscode/settings.json b/code/autocropper/.vscode/settings.json deleted file mode 100644 index 613752d..0000000 --- a/code/autocropper/.vscode/settings.json +++ /dev/null @@ -1,65 +0,0 @@ -{ - "C_Cpp.errorSquiggles": "enabled", - "files.associations": { - "array": "cpp", - "atomic": "cpp", - "bit": "cpp", - "*.tcc": "cpp", - "cctype": "cpp", - "chrono": "cpp", - "clocale": "cpp", - "cmath": "cpp", - "compare": "cpp", - "complex": "cpp", - "concepts": "cpp", - "condition_variable": "cpp", - "cstdarg": "cpp", - "cstddef": "cpp", - "cstdint": "cpp", - "cstdio": "cpp", - "cstdlib": "cpp", - "cstring": "cpp", - "ctime": "cpp", - "cwchar": "cpp", - "cwctype": "cpp", - "deque": "cpp", - "list": "cpp", - "map": "cpp", - "set": "cpp", - "string": "cpp", - "unordered_map": "cpp", - "vector": "cpp", - "exception": "cpp", - "algorithm": "cpp", - "functional": "cpp", - "iterator": "cpp", - "memory": "cpp", - "memory_resource": "cpp", - "numeric": "cpp", - "random": "cpp", - "ratio": "cpp", - "string_view": "cpp", - "system_error": "cpp", - "tuple": "cpp", - "type_traits": "cpp", - "utility": "cpp", - "fstream": "cpp", - "initializer_list": "cpp", - "iomanip": "cpp", - "iosfwd": "cpp", - "iostream": "cpp", - "istream": "cpp", - "limits": "cpp", - "mutex": "cpp", - "new": "cpp", - "numbers": "cpp", - "ostream": "cpp", - "semaphore": "cpp", - "sstream": "cpp", - "stdexcept": "cpp", - "stop_token": "cpp", - "streambuf": "cpp", - "thread": "cpp", - "typeinfo": "cpp" - }, -} \ No newline at end of file diff --git a/code/autocropper/CMakeLists.txt b/code/autocropper/CMakeLists.txt deleted file mode 100644 index 2225b5a..0000000 --- a/code/autocropper/CMakeLists.txt +++ /dev/null @@ -1,24 +0,0 @@ -cmake_minimum_required(VERSION 3.22) -project(autocropper - VERSION 0.1 - DESCRIPTION "Autocrops Receipt Pictures" - LANGUAGES CXX) - -#GLOBING -file(GLOB_RECURSE SOURCE_FILES src/*.cpp) -add_executable(CropperEx main.cpp ${SOURCE_FILES}) - -# add_executable(CropperEx main.cpp -# src/dog.cpp -# src/operations.cpp) - -target_compile_features(CropperEx PRIVATE cxx_std_20) - -find_package(OpenCV REQUIRED) - -target_link_libraries(CropperEx ${OpenCV_LIBS}) - -target_include_directories(CropperEx - PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/include - PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../externallibraries/stbimagehelpers - PRIVATE ${OpenCV_INCLUDE_DIRS}) diff --git a/code/autocropper/houghlinedevspace.ipynb b/code/autocropper/houghlinedevspace.ipynb deleted file mode 100644 index 3321130..0000000 --- a/code/autocropper/houghlinedevspace.ipynb +++ /dev/null @@ -1,721 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n" - ] - } - ], - "source": [ - "import cv2\n", - "import myfunctions as mf\n", - "import numpy as np\n", - "import math\n", - "import scipy.stats as st" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import pathlib\n", - "import time\n", - "\n", - "def removeextensionandnumeric(filename):\n", - " suffix = pathlib.Path(filename).suffix\n", - " num = filename[:-len(suffix)]\n", - " numint = int(num)\n", - " return numint\n", - " \n", - "\n", - "def testondataset(pathtodataset, function):\n", - " imagefileextensions = [\".jpg\", \".png\"]\n", - " filenames = next(os.walk(pathtodataset), (None, None, []))[2]\n", - " \n", - " filenames.sort(key=removeextensionandnumeric)\n", - " # print(filenames)\n", - " outs = []\n", - " tdiffs = []\n", - " for filename in filenames:\n", - " suffix = pathlib.Path(filename).suffix\n", - " if (suffix not in imagefileextensions):\n", - " print(\"Not a valid image \"+filename)\n", - " continue\n", - " img = cv2.imread(pathtodataset+filename)\n", - " t1 = time.time()\n", - " outs.append(function(img))\n", - " tdiffs.append(time.time() - t1)\n", - " tdiffs = np.array(tdiffs)\n", - " print(\"average time: \" + str(np.mean(tdiffs))+\"(s)\")\n", - " return outs\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def showimgs(imgs):\n", - " if (isinstance(imgs, np.ndarray)):\n", - " if (imgs.shape[0] > imgs.shape[1]):\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(imgs, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(imgs, width=1000))\n", - " else:\n", - " for i, out in enumerate(imgs):\n", - " if (out.shape[0] > out.shape[1]):\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, width=1000))\n", - " cv2.waitKey(0)\n", - " cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "def writeimgs(directorypath, imgs):\n", - " if (isinstance(imgs, np.ndarray)):\n", - " cv2.imwrite(directorypath+\"test.png\", imgs)\n", - " else:\n", - " for i, out in enumerate(imgs):\n", - " cv2.imwrite(directorypath+\"test\"+str(i)+\".png\", out)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "img = cv2.imread('/mnt/dataset/baseimages/12.jpg')\n", - "# img = cv2.imread('/mnt/code/autocropper/test_images/IMG_7605.jpg')\n", - "testall = False" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "## NEED TO FIX THE EARLIER PARTS SO THAT IT DOESN'T HAVE THOSE BLACK SECTIONS AFTER THE ROTATION\n", - "\n", - "\n", - "def whiteoutbackground(image):\n", - " ogshape = image.shape\n", - " shrunkdim=1000\n", - " if (image.shape[1] > image.shape[0]):\n", - " shrunkimg, scaler = mf.ResizeWithAspectRatio(image, width=shrunkdim, retscale=True)\n", - " else:\n", - " shrunkimg, scaler = mf.ResizeWithAspectRatio(image, height=shrunkdim, retscale=True)\n", - " \n", - " mainimage = shrunkimg\n", - " \n", - " sdim = int(min(mainimage.shape[0], mainimage.shape[1])/5)\n", - " srkernel = cv2.getStructuringElement(cv2.MORPH_RECT, (sdim, sdim))\n", - " skernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (sdim, sdim))\n", - " \n", - " \n", - " lab = cv2.cvtColor(mainimage, cv2.COLOR_BGR2LAB)\n", - " \n", - " imglist = []\n", - " # imglist.append(mainimage)\n", - " \n", - " labl = lab[:,:,0]\n", - " # imglist.append(labl)\n", - " # imglist.append(cv2.cvtColor(image, cv2.COLOR_BGR2GRAY))\n", - " laba = lab[:,:,1]\n", - " # imglist.append(laba)\n", - " labb = lab[:,:,2]\n", - " # imglist.append(labb)\n", - " \n", - " \n", - " # canny = cv2.Canny(labl, 0, 500)\n", - " threshl = cv2.threshold(labl, 0, 255, cv2.THRESH_OTSU)[1]\n", - " # return threshl\n", - " \n", - " \n", - " dim = int(min(mainimage.shape[0], mainimage.shape[1])/100)\n", - " # dim = 2\n", - " # dim = dotsize\n", - " kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (dim, dim))\n", - " kernelell = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dim, dim))\n", - " \n", - " paddedl = mf.padWithColour(threshl, sdim*2, sdim*2, fill=0)\n", - " # return paddedl\n", - " \n", - " \n", - " # morphedl = 255-cv2.morphologyEx(255-threshl, cv2.MORPH_OPEN, kernel, iterations=3)\n", - " morphedl = paddedl\n", - " # morphedl = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernel, iterations=1)\n", - " morphed1l = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernelell, iterations=1)\n", - "\n", - " # return morphedl\n", - " \n", - " contours, heirarchy = cv2.findContours(morphed1l, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " biggestcontour = max(contours, key=cv2.contourArea)\n", - " \n", - " \n", - " blank = np.full(labl.shape, 255, dtype=np.uint8)\n", - " mask1 = blank.copy()\n", - " mask1 = mf.padWithColour(mask1, sdim*2, sdim*2, fill=255)\n", - " mask1 = cv2.drawContours(mask1, [biggestcontour], -1, 0, thickness=cv2.FILLED)\n", - " \n", - " \n", - " mask1 = cv2.morphologyEx(mask1, cv2.MORPH_DILATE, kernelell, iterations=2)\n", - " \n", - " \n", - " # mask1 = mask1[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " # return mask1\n", - " \n", - " # morphed2l = mf.padWithColour(morphedl, sdim*2, sdim*2, fill=255)\n", - " morphed2l = cv2.morphologyEx(morphedl, cv2.MORPH_OPEN, kernel, iterations=1)\n", - " # morphed2l = morphed2l[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " \n", - " # return morphed2l\n", - " # print(mask1.shape)\n", - " # print(morphed2l.shape)\n", - " morphed2l = cv2.bitwise_or(morphed2l, 255-mask1)\n", - " # return morphed2l\n", - " \n", - " morphed2l = morphed2l[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " temp_final = cv2.bitwise_or(threshl, 255-morphed2l)\n", - " return temp_final\n", - " \n", - " canny = cv2.Canny(morphed2l, 0, 500)\n", - " # return canny\n", - "\n", - " vminlength = mainimage.shape[0]//10\n", - " vmaxgap = mainimage.shape[0]//50\n", - " vlinesP = cv2.HoughLinesP(canny, 1, np.pi / 180, 10, None, vminlength, vmaxgap)\n", - " \n", - " hminlength = mainimage.shape[1]//15\n", - " hmaxgap = mainimage.shape[1]//40\n", - " hlinesP = cv2.HoughLinesP(canny, 1, np.pi / 180, 10, None, hminlength, hmaxgap)\n", - " # print(linesP)\n", - " \n", - " vmarginlines = mf.WithinXDegrees(vlinesP, 15)\n", - " hmarginlines = mf.WithinXDegrees(hlinesP, 15, baseangle=90)\n", - " \n", - " marginlines = np.append(vmarginlines, hmarginlines, axis=0)\n", - " # marginlines = marginlines.astype(int)\n", - " # # print(marginlines)\n", - " # reshaped = np.reshape(marginlines, (-1,1, 2))\n", - " # # reshaped = cv2.convexHull(reshaped)\n", - " # # print(reshaped)\n", - " \n", - " \n", - " \n", - " colourdst = cv2.cvtColor(morphedl, cv2.COLOR_GRAY2BGR)\n", - " # out = cv2.drawContours(colourdst, [reshaped], -1, (0,255,0), thickness=3)\n", - " # return out\n", - " \n", - " \n", - " #### NEW IDEA: MERGE THE WHITEOUT BACKGROUND AND TEXT CLARIFICATION STEP BECAUSE DOING THE OTSU THRESHOLD SEEMS TO WORK PRETTY WELL AND IF I JUST WHITE OUT THE OUTER AREA (ACTUALLY WHITE)\n", - " # THEN I HAVE JUST THE TEXT\n", - " \n", - "\n", - " if marginlines is not None:\n", - " for l in marginlines:\n", - " cv2.line(colourdst, (int(l[0]), int(l[1])), (int(l[2]), int(l[3])), (0,0,255), 3, cv2.LINE_AA)\n", - " return colourdst\n", - "\n", - "\n", - "\n", - "\n", - "\n", - " ## IDEA:\n", - " # MASK OUT THE WORDS USING OUR MASKS MADE FROM THE STUFF BELOW. THEN WHEN CANNY IS DONE TO IT, IT SHOULDN'T HAVE A WHOLE BUNCH OF SHIT IN THE CENTER. STILL NEED TO FIGURE OUT HOW TO LINK THE HOUGH LINES AROUND THE RECEIPT\n", - "\n", - "\n", - "\n", - "\n", - "\n", - " # morphedl = 255-cv2.morphologyEx(255-threshl, cv2.MORPH_OPEN, kernel, iterations=3)\n", - " morphedl = paddedl\n", - " morphedl = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernel, iterations=1)\n", - " morphedl = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernelell, iterations=1)\n", - "\n", - " # return morphedl\n", - " \n", - " contours, heirarchy = cv2.findContours(morphedl, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " # print(contours[0].shape)\n", - " print(contours[0])\n", - " biggestcontour = max(contours, key=cv2.contourArea)\n", - " return canny\n", - " \n", - " \n", - " blank = np.full(labl.shape, 255, dtype=np.uint8)\n", - " mask1 = blank.copy()\n", - " mask1 = mf.padWithColour(mask1, sdim*2, sdim*2, fill=255)\n", - " mask1 = cv2.drawContours(mask1, [biggestcontour], -1, 0, thickness=cv2.FILLED)\n", - " \n", - " \n", - " mask1 = mask1[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " \n", - " \n", - " # resizemask = cv2.resize(mask1, (ogshape[1], ogshape[0]))\n", - " # return resizemask\n", - " maskc = cv2.cvtColor(mask1, cv2.COLOR_GRAY2BGR)\n", - " # print(maskc.shape)\n", - " # print(image.shape)\n", - " whitedbackground = cv2.bitwise_or(mainimage, maskc)\n", - " # return whitedbackground\n", - " \n", - " \n", - " lab2 = cv2.cvtColor(whitedbackground, cv2.COLOR_BGR2LAB)\n", - " \n", - " lab2l = lab2[:,:,0]\n", - " \n", - " \n", - " otsu2 = cv2.threshold(lab2l, 0, 255, cv2.THRESH_OTSU)[1]\n", - " \n", - " expandedmask1 = cv2.morphologyEx(mask1, cv2.MORPH_DILATE, kernel, iterations=1)\n", - " expandedmask1 = cv2.morphologyEx(expandedmask1, cv2.MORPH_DILATE, kernelell, iterations=1)\n", - " # return expandedmask1\n", - " \n", - " maskmerge = cv2.bitwise_and(otsu2, 255-expandedmask1)\n", - " return mask1\n", - " return maskmerge\n", - " \n", - " # return otsu2\n", - " \n", - " mpad = mf.padWithColour(maskmerge, sdim*2, sdim*2, fill=0)\n", - " return mpad\n", - " \n", - " #MORPHOLOGIES \n", - " morphed2 = cv2.morphologyEx(mpad, cv2.MORPH_ERODE, kernel, iterations=1)\n", - " morphed2 = cv2.morphologyEx(morphed2, cv2.MORPH_ERODE, kernelell, iterations=1)\n", - " return morphed2\n", - " \n", - " contours, heirarchy = cv2.findContours(morphed2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " biggestcontour = max(contours, key=cv2.contourArea)\n", - " \n", - " \n", - " mask2 = blank.copy()\n", - " mask2 = mf.padWithColour(mask2, sdim*2, sdim*2, fill=255)\n", - " mask2 = cv2.drawContours(mask2, [biggestcontour], -1, 0, thickness=cv2.FILLED)\n", - " \n", - " \n", - " mask2 = mask2[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " \n", - " return mask2\n", - " \n", - " test = cv2.inpaint(whitedbackground, resizemask, 3, cv2.INPAINT_TELEA)\n", - " \n", - " return test\n", - " \n", - " contours, heirarchy = cv2.findContours(255-labl, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n", - " \n", - " imgout = cv2.drawContours(mainimage, contours, -1, (0,255,0), thickness=3)\n", - " return imgout\n", - " \n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def textleaver(image):\n", - " ogshape = image.shape\n", - " shrunkdim=1000\n", - " if (image.shape[1] > image.shape[0]):\n", - " shrunkimg, scaler = mf.ResizeWithAspectRatio(image, width=shrunkdim, retscale=True)\n", - " else:\n", - " shrunkimg, scaler = mf.ResizeWithAspectRatio(image, height=shrunkdim, retscale=True)\n", - " \n", - " mainimage = shrunkimg\n", - " \n", - " sdim = int(min(mainimage.shape[0], mainimage.shape[1])/5)\n", - " srkernel = cv2.getStructuringElement(cv2.MORPH_RECT, (sdim, sdim))\n", - " skernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (sdim, sdim))\n", - " \n", - " oglab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)\n", - " lab = cv2.cvtColor(mainimage, cv2.COLOR_BGR2LAB)\n", - " \n", - " imglist = []\n", - " # imglist.append(mainimage)\n", - " \n", - " labl = lab[:,:,0]\n", - " oglabl = oglab[:,:,0]\n", - " # # imglist.append(labl)\n", - " # # imglist.append(cv2.cvtColor(image, cv2.COLOR_BGR2GRAY))\n", - " # laba = lab[:,:,1]\n", - " # # imglist.append(laba)\n", - " # labb = lab[:,:,2]\n", - " # # imglist.append(labb)\n", - " \n", - " divisor = 1.5\n", - " window = int(min(labl.shape)/divisor)\n", - " window = window if window%2 == 1 else window + 1\n", - " # canny = cv2.Canny(labl, 0, 500)\n", - " ethreshl = cv2.threshold(labl, 0, 255, cv2.THRESH_OTSU)[1]\n", - " threshl = cv2.threshold(labl, 0, 255, cv2.THRESH_OTSU)[1]\n", - " # threshl = cv2.adaptiveThreshold(labl, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, window, 35)\n", - " \n", - " \n", - " ogwindow = int(min(oglabl.shape)/divisor)\n", - " ogwindow = window if window%2 == 1 else window + 1\n", - " print(ogwindow)\n", - " ogthreshl = cv2.threshold(oglabl, 0, 255, cv2.THRESH_TRIANGLE)[1]\n", - " return ogthreshl\n", - " # ogthreshl = cv2.adaptiveThreshold(oglabl, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, ogwindow, 35)\n", - " # return threshl\n", - " \n", - " colourthresh = cv2.cvtColor(threshl, cv2.COLOR_GRAY2BGR)\n", - " \n", - " dim = int(min(mainimage.shape[0], mainimage.shape[1])/100)\n", - " # dim = 2\n", - " # dim = dotsize\n", - " dim = max(3,dim)\n", - " kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (dim, dim))\n", - " kernelell = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dim, dim))\n", - " \n", - " # paddedl = mf.padWithColour(threshl, sdim*2, sdim*2, fill=0)\n", - " paddedl = threshl\n", - " # return paddedl\n", - " \n", - " \n", - " # morphedl = 255-cv2.morphologyEx(255-threshl, cv2.MORPH_OPEN, kernel, iterations=3)\n", - " morphedl = paddedl\n", - " morphed1l = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernel, iterations=1)\n", - " # morphed1l = cv2.morphologyEx(morphed1l, cv2.MORPH_OPEN, kernel, iterations=1)\n", - " # morphed1l = cv2.morphologyEx(morphed1l, cv2.MORPH_OPEN, kernel, iterations=1)\n", - " # morphed1l = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernelell, iterations=2)\n", - " \n", - " emorphed1l = cv2.morphologyEx(ethreshl, cv2.MORPH_ERODE, kernel, iterations=1)\n", - "\n", - " # return morphedl\n", - " \n", - " contours, heirarchy = cv2.findContours(morphed1l, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " biggestcontour = max(contours, key=cv2.contourArea)\n", - " \n", - " # temp = cv2.drawContours(colourthresh, [biggestcontour], -1, (0,255,0), thickness=1)\n", - " # return temp\n", - " \n", - " \n", - " blank = np.full(labl.shape, 255, dtype=np.uint8)\n", - " mask1 = blank.copy()\n", - " # mask1 = mf.padWithColour(mask1, sdim*2, sdim*2, fill=255)\n", - " mask1 = cv2.drawContours(mask1, [biggestcontour], -1, 0, thickness=cv2.FILLED)\n", - " ## need to change the erosion so that if the paper goes to the edge, it doesn't get eroded in (because that means the paper is right to the edge and writing may be close)\n", - " \n", - " contours, heirarchy = cv2.findContours(morphed1l, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " biggestcontour = max(contours, key=cv2.contourArea)\n", - " \n", - " emask1 = blank.copy()\n", - " emask1 = cv2.drawContours(emask1, [biggestcontour], -1, 0, thickness=cv2.FILLED)\n", - " \n", - " mask1 = 255-cv2.morphologyEx(255-mask1, cv2.MORPH_ERODE, kernel, iterations=2)\n", - " \n", - " emask1 = 255-cv2.morphologyEx(255-emask1, cv2.MORPH_ERODE, kernel, iterations=2)\n", - " \n", - " \n", - " # mask1 = mask1[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " # return mask1\n", - " \n", - " # morphed2l = mf.padWithColour(morphedl, sdim*2, sdim*2, fill=255)\n", - " morphed2l = cv2.morphologyEx(morphedl, cv2.MORPH_OPEN, kernel, iterations=1)\n", - " morphed2l = cv2.morphologyEx(morphedl, cv2.MORPH_ERODE, kernel, iterations=1)\n", - " # morphed2l = morphed2l[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " \n", - " # return morphed2l\n", - " # print(mask1.shape)\n", - " # print(morphed2l.shape)\n", - " morphed2l = cv2.bitwise_or(morphed2l, 255-mask1)\n", - " # return morphed2l\n", - "\n", - " # paddedthreshl = mf.padWithColour(morphed2l, sdim*2, sdim*2, fill=255)\n", - " # temp = cv2.drawContours(colourthresh, [biggestcontour], -1, (0,255,0), thickness=1)\n", - " # return temp\n", - "\n", - "\n", - " morphed2l = cv2.morphologyEx(morphed2l, cv2.MORPH_ERODE, kernel, iterations=1)\n", - " morphed2l = cv2.morphologyEx(morphed2l, cv2.MORPH_ERODE, kernelell, iterations=1)\n", - " # return morphed2l\n", - " # morphed2l = cv2.bitwise_or(morphed2l, 255-emask1)\n", - " \n", - " # morphed2l = morphed2l[(sdim*2):-(sdim*2), (sdim*2):-(sdim*2)]\n", - " \n", - " resizedmask = cv2.resize(255-morphed2l, (ogshape[1], ogshape[0]))\n", - " temp_final = cv2.bitwise_or(ogthreshl, resizedmask)\n", - " \n", - " dim=3\n", - " kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dim, dim))\n", - " temp_final = cv2.morphologyEx(temp_final, cv2.MORPH_OPEN, kernel)\n", - " temp_final = cv2.morphologyEx(temp_final, cv2.MORPH_OPEN, kernel)\n", - " # temp_final = cv2.morphologyEx(temp_final, cv2.MORPH_CLOSE, kernel)\n", - " # temp_final = cv2.morphologyEx(temp_final, cv2.MORPH_OPEN, kernel)\n", - " return temp_final" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def cropclarifying(image):\n", - " # whitedbackground = whiteoutbackground(image)\n", - " # return whitedbackground\n", - "\n", - " # textrefined = mf.textClarifying(whitedbackground)\n", - " textrefined = textleaver(image)\n", - " return textrefined\n", - " #maybe now is when I put in the line removing function\n", - "\n", - " lineout = mf.removeLinesFromText(textrefined)\n", - "\n", - " return lineout\n", - " # implement a function that's called refine text" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def houghlineprocessing(image):\n", - " croppedanddeskewed, angle = mf.houghlinedeskewandcrop(image)\n", - " # return croppedanddeskewed\n", - " \n", - " \n", - " # postprocessed = cropclarifying(croppedanddeskewed)\n", - " postprocessed = croppedanddeskewed\n", - " # return postprocessed\n", - " # postprocessed = mf.croptoblack(postprocessed)\n", - " \n", - " # postprocessed = cv2.cvtColor(postprocessed, cv2.COLOR_GRAY2BGR)\n", - " # return postprocessed\n", - " \n", - " # final = mf.externaldeskew(postprocessed, fill=(255,255,255))\n", - " # rotangle = mf.receipttextdeskew(postprocessed, fill=(255,255,255), returnangle=True)\n", - " final = postprocessed\n", - " \n", - " \n", - " # final = mf.croptoblack(final)\n", - " \n", - " # cv2.imshow(\"postprocessed\", mf.ResizeWithAspectRatio(postprocessed, 1000))\n", - " # cv2.imshow(\"final\", mf.ResizeWithAspectRatio(final, 1000))\n", - " # cv2.waitKey(0)\n", - " # cv2.destroyAllWindows()\n", - " \n", - " return final" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# print(img.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0\n" - ] - } - ], - "source": [ - "# prepped, scaler, hp, vp = mf.squareandthenresize(img, fill=255, width=1000, returnscalerinfo=True)\n", - "outs = houghlineprocessing(img)\n", - "# outs = prepimageforhoughline(img, returnrect=True)\n", - "# print(img.shape)\n", - "# outs = houghlinedeskewandcrop(img)\n", - "# outs = outs[0]\n", - "# print(croprect)\n", - "#need to fix premorphCrop. it removes too much" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# shrunk, scaler, hp, vp = mf.squareandthenresize(img, fill=255, width=1000, returnscalerinfo=True)\n", - "# shrunk1, croprect = mf.premorphCrop(shrunk)\n", - "# print(croprect)\n", - "# print(int(30*4.032 - 0))\n", - "# # temp = img[100:, :, :]\n", - "# temp = shrunk[croprect[1]:croprect[1]+croprect[3], croprect[0]:croprect[0]+croprect[2], :]\n" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imshow(\"temp\", mf.ResizeWithAspectRatio(out, height=1000))\n", - "# # cv2.imshow(\"shrunk1\", mf.ResizeWithAspectRatio(shrunk1, height=1000))\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "testall = True" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "if not testall:\n", - " showimgs(outs)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "# # for out in outs:\n", - "# # if (out.shape[0] > out.shape[1]):\n", - "# # cv2.imshow(\"test1\", mf.ResizeWithAspectRatio(out, height=1000))\n", - "# # else:\\\n", - "# # cv2.imshow(\"test1\", mf.ResizeWithAspectRatio(out, width=1000))\n", - "# # key = cv2.waitKey(0)\n", - "# # cv2.destroyAllWindows()\n", - "# # if (key == 107):\n", - "# # break\n", - "# if (isinstance(outs, np.ndarray)):\n", - "# if (outs.shape[0] > outs.shape[1]):\n", - "# cv2.imshow(\"test\", mf.ResizeWithAspectRatio(outs, height=1350))\n", - "# else:\n", - "# cv2.imshow(\"test\", mf.ResizeWithAspectRatio(outs, width=1000))\n", - "# else:\n", - "# for i, out in enumerate(outs):\n", - "# if (out.shape[0] > out.shape[1]):\n", - "# cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, height=1350))\n", - "# else:\n", - "# cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, width=1000))\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.9740282517223996\n", - "-2.0053522829578814\n", - "-0.9740282517223996\n", - "0.0\n", - "0.9740282517223996\n", - "-0.9740282517223996\n", - "-0.011669615052326776\n", - "2.0053522829578814\n", - "0.0\n", - "0.0\n", - "0.0\n", - "-2.979380534680281\n", - "0.0\n", - "0.0\n", - "-2.0053522829578814\n", - "-11.000789666511807\n", - "average time: 0.19967518746852875(s)\n" - ] - } - ], - "source": [ - "if testall:\n", - " results = testondataset(\"/mnt/dataset/baseimages/\", houghlineprocessing)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "# if testall:\n", - "# showimgs(results)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "# print(results[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "if testall:\n", - " writeimgs(\"/mnt/code/autocropper/result_images/\", results)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/include/cropper.h b/code/autocropper/include/cropper.h deleted file mode 100644 index 7cdc2f4..0000000 --- a/code/autocropper/include/cropper.h +++ /dev/null @@ -1,11 +0,0 @@ -#ifndef CROPPER_H -#define CROPPER_H - -#include - - -bool crop(cv::InputArray src, cv::OutputArray dst, bool fastsearch = true, int imageHeight = 700); - - - -#endif //CROPPER_H \ No newline at end of file diff --git a/code/autocropper/include/ppdefinitions.h b/code/autocropper/include/ppdefinitions.h deleted file mode 100644 index c930382..0000000 --- a/code/autocropper/include/ppdefinitions.h +++ /dev/null @@ -1 +0,0 @@ -#define DEBUG 1 diff --git a/code/autocropper/main.cpp b/code/autocropper/main.cpp deleted file mode 100644 index f88c73d..0000000 --- a/code/autocropper/main.cpp +++ /dev/null @@ -1,43 +0,0 @@ -#include - -#include - -// PLAN: -// Implement selective search -// Implement Canny edge detection and then find a good rectangle -// Do L2 loss with the corners of the rectangle and choose the selective search rectangle with the lowest loss - - -//for testing delete later -#include - -int main(int argc, char** argv) { - - if (argc < 2) { - std::cerr << "BAD" << std::endl; - return -1; - } - - cv::Mat imOut, result; - - imOut = cv::imread(argv[1]); - if (imOut.empty()) { - std::cout << "Could not open or find the image!\n" << std::endl; - std::cout << "Usage: " << argv[0] << " " << std::endl; - return -1; - } - - crop(imOut, result, true, 1000); - - - int imageHeight = 800; - int newWidth = result.cols * imageHeight / result.rows; - cv::resize(result, result, cv::Size(newWidth, imageHeight)); - - cv::imshow("banana", result); - imwrite("../testing_space/cropped.jpg", result); - cv::waitKey(); - return 0; -} - - diff --git a/code/autocropper/myfunctions.py b/code/autocropper/myfunctions.py deleted file mode 100644 index f2765ad..0000000 --- a/code/autocropper/myfunctions.py +++ /dev/null @@ -1,1178 +0,0 @@ -import cv2 -import numpy as np -import math -from deskew import determine_skew -import heapq as hq -import torchvision.transforms.v2 as v2 -import scipy.stats as st - -## ------------------------------helper functions------------------------------ -def ResizeWithAspectRatio(image, width=None, height=None, inter=cv2.INTER_AREA, retscale=False): - dim = None - (h, w) = image.shape[:2] - - if width is None and height is None: - if (retscale == True): - return (image, 1) - return image - if width is None: - r = height / float(h) - dim = (int(w * r), height) - else: - r = width / float(w) - dim = (width, int(h * r)) - - if (retscale == True): - # print("hi") - return (cv2.resize(image, dim, interpolation=inter), 1/r) - return cv2.resize(image, dim, interpolation=inter) - - -def squareandthenresize(image, fill=0, width=None, height=None, inter=cv2.INTER_AREA, returnscalerinfo=False): - out = squarepad(image, fill=fill, returnoffset=returnscalerinfo) - if (returnscalerinfo): - squaredimage, hp, vp = out - else: - squaredimage = out - out = ResizeWithAspectRatio(squaredimage, width=width, height=height, inter=inter, retscale=returnscalerinfo) - if (returnscalerinfo): - finalimage, scaler = out - return finalimage, scaler, hp, vp - else: - finalimage = out - return finalimage - - -# class SquarePad: -# def __init__(self, fill): -# self.fill = fill - -# def __call__(self, image): -# w, h = image.shape[1], image.shape[0] -# max_wh = np.max([w, h]) -# hp = int((max_wh - w) / 2) -# vp = int((max_wh - h) / 2) -# padding = (hp, vp, hp, vp) -# return cv2.copyMakeBorder(image, vp, vp, hp, hp, cv2.BORDER_CONSTANT, self.fill) - - -def squarepad(image, fill=0, returnoffset=False): - w, h = image.shape[1], image.shape[0] - max_wh = np.max([w, h]) - hp = int((max_wh - w) / 2) - vp = int((max_wh - h) / 2) - padding = (hp, vp, hp, vp) - if (returnoffset): - return cv2.copyMakeBorder(image, vp, vp, hp, hp, cv2.BORDER_CONSTANT, fill), hp, vp - return cv2.copyMakeBorder(image, vp, vp, hp, hp, cv2.BORDER_CONSTANT, fill) - -def rotate(img, angle, fill=(0,0,0)): - rows,cols = img.shape[0], img.shape[1] - M = cv2.getRotationMatrix2D((cols/2,rows/2),angle,1) - dst = cv2.warpAffine(img,M,(cols,rows), borderValue=fill) - return dst - - -def clip(n, lower, upper): - return max(lower, min(n, upper)) - -def colourscaler(n, min, max): - temp = n-min - diff = abs(max - min) - return clip((temp/diff)*255, 0, 255) - -def padWithColour(img, hpadding=0, vpadding=0, fill=(0,0,0)): - borderType = cv2.BORDER_CONSTANT - out = cv2.copyMakeBorder(img, vpadding, vpadding, hpadding, hpadding, borderType, None, fill) - return out - -def mergecontours(contours): - cont = np.vstack(contours) - finalcontour = cv2.convexHull(cont) - return finalcontour - - - -# funtion to correct the median-angle to give it to the cv2.warpaffine() function -# specifically, when getting the angle from a minAreaRect rectangle -def anglecorrector(angle): - if 0 <= angle <= 90: - corrected_angle = angle - 90 - elif -45 <= angle < 0: - corrected_angle = angle - 90 - elif -90 <= angle < -45: - corrected_angle = 90 + angle - return corrected_angle - -tensorize = v2.Compose([v2.ToImageTensor(), v2.ConvertImageDtype()]) ## for converting an image (usually PIL image) to a pytorch tensor - -## ------------------------------for selective segmentation search crop------------------------------ -def rectArea(rect): - # print(rect) - return rect[2]*rect[3] - -def biggestRects(n, rects): - dict = {} - # outrects = np.zeros(shape=(n, 4)) - for rect in rects: - dict[tuple(rect)] = rectArea(rect) - # maxh.heappush(rectArea(rect)) - # print(maxh[0]) - - - heap = [(-value, key) for key,value in dict.items()] - largest = hq.nsmallest(n, heap) - - - # hq.heapify(list(dict.items())) - # for i in range(0,n): - # outrects[i] = maxh.heappop() - # print(outrects) - return [key for value, key in largest] - -def overlapRect(rects): - leftwall = -1 - rightwall = -1 - topwall = -1 - bottomwall = -1 - for (x, y, w, h) in rects: - if (leftwall == -1): - leftwall = x - rightwall = x + w - topwall = y - bottomwall = y + h - continue - leftwall = max(leftwall, x) - rightwall = min(rightwall, x+w) - topwall = max(topwall, y) - bottomwall = min(bottomwall, y+h) - - if (topwall >= bottomwall or leftwall >= rightwall): - return (-1, -1, -1, -1) - return (leftwall, topwall, rightwall-leftwall, bottomwall-topwall) - - -def selectiveSearchSegmentationImp(image): - ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation() - ss.setBaseImage(image) - ss.switchToSelectiveSearchFast() - return ss.process() - -## ------------------------------other rectangle stuff------------------------------ -def containsrect(outer, inner, xywhtype=True): - if xywhtype and (outer[0] > inner[0]) or (outer[1] > inner[1]) or (outer[0]+outer[2] < inner[0]+inner[2]) or (outer[1]+outer[3] < inner[1]+inner[3]): - return False - if not xywhtype and (outer[0] > inner[0]) or (outer[1] > inner[1]) or (outer[2] < inner[2]) or (outer[3] < inner[3]): - return False - return True - -def xywhrectto2prect(rect): - return (rect[0], rect[1], rect[0]+rect[2], rect[1]+rect[3]) - -def twoprecttoxywhrect(rect): - return (rect[0], rect[1], rect[2]-rect[0], rect[3]-rect[1]) - -def mergerects(rects, xywhtype=True): - maxrect = [-1,-1,-1,-1] - for i, rect in enumerate(rects): - if (i == 0): - maxrect[0] = rect[0] - maxrect[1] = rect[1] - maxrect[0] = min(maxrect[0], rect[0]) - maxrect[1] = min(maxrect[1], rect[1]) - if (xywhtype): - maxrect[2] = max(maxrect[2], rect[0]+rect[2]) - maxrect[3] = max(maxrect[3], rect[1]+rect[3]) - else: - maxrect[2] = max(maxrect[2], rect[2]) - maxrect[3] = max(maxrect[3], rect[3]) - if (xywhtype): - maxrect[2] = maxrect[2]-maxrect[0] - maxrect[3] = maxrect[3]-maxrect[1] - return maxrect - -def rectscontaining(rect, outerrects): - temprects = set() - for i, outerrect in enumerate(outerrects): - if containsrect(outerrect, rect): - temprects.add(i) - return temprects - - -## ------------------------------specific to houghline cropping and deskewing------------------------------ -def lineAngle(line): - # print(line) - angle = (math.atan2(line[3] - line[1], line[2] - line[0]) % np.pi) - (np.pi/2) - return angle - -def WithinXDegrees(lines, margin, baseangle=0): - # outlines = np.array([[]]) - outlines = np.empty((0, 4)) - # print(outlines.shape) - for line in lines: - # print(type(line)) - # print(abs(lineAngle(line[0]))) - if (np.rad2deg(abs(lineAngle(line[0])+np.deg2rad(baseangle))) <= margin): - outlines = np.append(outlines, [line[0]], axis=0) - return outlines - -def lineBoundingRect(lines, asRect=False, returnint=False): - maxvals = lines.max(0) - minvals = lines.min(0) - x1 = min(minvals[0],minvals[2]) - y1 = min(minvals[1],minvals[3]) - x2 = max(maxvals[0],maxvals[2]) - y2 = max(maxvals[1],maxvals[3]) - if (asRect): - x2 -= x1 - y2 -= y1 - if (returnint): - x1 = int(x1) - y1 = int(y1) - x2 = int(x2) - y2 = int(y2) - - x1 = max(0, x1) - x2 = max(0,x2) - y1 = max(0, y1) - y2 = max(0, y2) - - return (x1,y1,x2,y2) - # print(lines.max(0)) - # print(type(lines)) - -def lineswithinrange(lines, pt1, pt2, x=True, y=False): - out_lines = lines - if (x): - minx = min(pt1[0], pt2[0]) - maxx = max(pt1[0], pt2[0]) - out_lines = [line for line in out_lines if ((min(line[0],line[2]) >= minx) and (max(line[0],line[2]) <= maxx))] - if (y): - miny = min(pt1[1], pt2[1]) - maxy = max(pt1[1], pt2[1]) - out_lines = [line for line in out_lines if ((min(line[1],line[3]) >= minx) and (max(line[1],line[3]) <= maxx))] - return out_lines - -def premorphCrop(image): - # convert to grayscale - gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) - - window = gray.shape[1]//8 - if window % 2 == 0: - window += 1 - # print(window) - # gray = cv2.blur(gray, (11,11)) - - # threshold - # thresh = cv2.threshold(gray, 170, 255, cv2.THRESH_BINARY)[1] - - thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, window, 2) - - # return thresh - - # apply morphology - kernel = np.ones((9,9), np.uint8) - morph = cv2.morphologyEx(thresh, cv2.MORPH_ERODE, kernel) - # morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel) - kernel = np.ones((9,9), np.uint8) - morph = cv2.morphologyEx(morph, cv2.MORPH_CLOSE, kernel) - kernel = np.ones((3,3), np.uint8) - morph = cv2.morphologyEx(morph, cv2.MORPH_CLOSE, kernel) - - # return morph - - - - # get largest contour - contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) - contours = contours[0] if len(contours) == 2 else contours[1] - area_thresh = 0 - for c in contours: - area = cv2.contourArea(c) - if area > area_thresh: - area_thresh = area - big_contour = c - - - # get bounding box - x,y,w,h = cv2.boundingRect(big_contour) - - # draw filled contour on black background - mask = np.zeros_like(gray) - mask = cv2.merge([mask,mask,mask]) - # mask = cv2.blur(mask,(121,121)) - cv2.drawContours(mask, [big_contour], -1, (255,255,255), cv2.FILLED) - - # apply mask to input - result1 = image.copy() - mask = cv2.blur(mask,(3,3)) - result1 = cv2.bitwise_and(result1, mask) - - # crop result - result2 = result1[y:y+h, x:x+w] - return result2, (x,y,w,h) - - -def rotatePoint(img, pt, angle, returnint=True): - rotateaxisx = img.shape[0]/2 - rotateaxisy = img.shape[1]/2 - tempx = pt[0] - rotateaxisx - tempy = pt[1] - rotateaxisy - rotatedx = tempx*math.cos(np.deg2rad(-angle)) - tempy*math.sin(np.deg2rad(-angle)) - rotatedy = tempx*math.sin(np.deg2rad(-angle)) + tempy*math.cos(np.deg2rad(-angle)) - finalx = rotatedx + rotateaxisx - finaly = rotatedy + rotateaxisy - if (returnint): - finalx = int(finalx) - finaly = int(finaly) - return (finalx, finaly) - -def rotateRect(img, rect, angle, returnint=True, asRect=False): - if (asRect): - pt1 = rotatePoint(img, (rect[0],rect[1]), angle, returnint) - pt2 = rotatePoint(img, (rect[0]+rect[2],rect[1]+rect[3]), angle, returnint) - return (pt1[0], pt1[1], pt2[0]-pt1[0], pt2[1]-pt1[1]) - else: - pt1 = rotatePoint(img, (rect[0],rect[1]), angle, returnint) - pt2 = rotatePoint(img, (rect[2],rect[3]), angle, returnint) - return (pt1[0], pt1[1], pt2[0], pt2[1]) - -def rotateLine(img, line, angle, returnint=True): - pt1 = rotatePoint(img, (line[0],line[1]), angle, returnint) - pt2 = rotatePoint(img, (line[2],line[3]), angle, returnint) - return (pt1[0], pt1[1], pt2[0], pt2[1]) - -def prepimageforhoughline(image, returnrect=True): - prepped, scaler, hp, vp = squareandthenresize(image, fill=255, width=1000, returnscalerinfo=True) - ogpreppedshape = prepped.shape - prepped, croprect = premorphCrop(prepped) - if (prepped.shape[1] > prepped.shape[0]): - prepped, preppedscaler = ResizeWithAspectRatio(prepped, width=1000, retscale=True) - else: - prepped, preppedscaler = ResizeWithAspectRatio(prepped, height=1000, retscale=True) - finalcroprect = (int(croprect[0]*scaler - hp), int(croprect[1]*scaler - vp), int(croprect[2]*scaler), int(croprect[3]*scaler)) - gray1 = cv2.cvtColor(prepped, cv2.COLOR_BGR2GRAY) - - dst1 = cv2.Canny(gray1, 0, 500, None, 3) - - - kernel = np.ones((5,5), np.uint8) - out = cv2.morphologyEx(dst1, cv2.MORPH_DILATE, kernel) - out = cv2.blur(out, (5,5)) - kernel = np.ones((6,6), np.uint8) - dst1 = cv2.morphologyEx(out, cv2.MORPH_ERODE, kernel) - # return dst1 - - dst1 = cv2.Canny(dst1, 0, 500, None, 3) - # return dst1 - accompaniedimage = image[finalcroprect[1]:finalcroprect[1]+finalcroprect[3], finalcroprect[0]:finalcroprect[0]+finalcroprect[2], :] - if returnrect: - borderType = cv2.BORDER_CONSTANT - preppadding = [croprect[0], croprect[1], ogpreppedshape[1]-(croprect[0]+croprect[2]), ogpreppedshape[0]-(croprect[1]+croprect[3])] - preppadding = [int(s/preppedscaler) for s in preppadding] - paddedprepped = cv2.copyMakeBorder(dst1, preppadding[1], preppadding[3], preppadding[0], preppadding[2], borderType, 0) - - squaredimage = squarepad(image, fill=0) - - return dst1, accompaniedimage, paddedprepped, squaredimage, finalcroprect - else: - return dst1, accompaniedimage - -def houghlinedeskewangle(image): - lines = cv2.HoughLines(image, 1, np.pi/180, int(max(image.shape[0], image.shape[1])/6), None, 0, 0) - angles = np.zeros(len(lines)) - if lines is not None: - for i in range(0, len(lines)): - rho = lines[i][0][0] - theta = lines[i][0][1] - a = math.cos(theta) - b = math.sin(theta) - x0 = a * rho - y0 = b * rho - unroundedpt1 = (x0 + 1000*(-b), y0 + 1000*(a)) - unroundedpt2 = (x0 - 1000*(-b), y0 - 1000*(a)) - pt1 = (int(unroundedpt1[0]), int(unroundedpt1[1])) - pt2 = (int(unroundedpt2[0]), int(unroundedpt2[1])) - v1_theta = math.atan2(pt1[1], pt1[0]) - v2_theta = math.atan2(pt2[1], pt2[0]) - # print(math.atan2(unroundedpt2[1] - unroundedpt1[1], unroundedpt2[0] - unroundedpt1[0]) % np.pi) - # print(lineAngle((unroundedpt1[0], unroundedpt1[1], unroundedpt2[0], unroundedpt2[1]))) - # angles[i] = math.atan2(unroundedpt2[1] - unroundedpt1[1], unroundedpt2[0] - unroundedpt1[0]) % np.pi - angles[i] = lineAngle((unroundedpt1[0], unroundedpt1[1], unroundedpt2[0], unroundedpt2[1])) - # cv2.line(cdstP, pt1, pt2, (0,0,255), 3, cv2.LINE_AA) - - mode = st.mode(np.around(angles, decimals=3))[0] - rotationangle = np.rad2deg(mode) - return rotationangle - -def determineextrapadding(h,w, angle): - radangle = abs(np.deg2rad(angle)) - # print(type(h), type(w), type(angle)) - # print(h, w, angle) - # print(radangle) - totalheightrot = w*np.sin(radangle) + h*np.cos(radangle) - # print(h, totalheightrot) - totalwidthrot = h*np.sin(radangle) + w*np.cos(radangle) - # print(w, totalwidthrot) - vpad = int(max(0,math.ceil((totalheightrot - h)/2))) - hpad = int(max(0,math.ceil((totalwidthrot-w)/2))) - # print(vpad, hpad) - return hpad, vpad - -def rotatewithexactpadding(img, angle, fill=(0,0,0)): - h, w = img.shape[0], img.shape[1] - hpad, vpad = determineextrapadding(h=h,w=w, angle=angle) - # fill1 = fill - # print(fill) - baseimage = padWithColour(img, hpad, vpad, fill=fill) - # return baseimage - rotatedimg = rotate(baseimage, angle,fill=fill) - return rotatedimg - -def houghlinepcrop(baseimage, preppedimage, scalingmultiplier): - rotatedlines = cv2.HoughLinesP(preppedimage, 1, np.pi / 180, 30, None, 90, 30) - - vmarginlines = WithinXDegrees(rotatedlines, 7) - hmarginlines = WithinXDegrees(rotatedlines, 7, baseangle=90) - # vrect = lineBoundingRect(vmarginlines,asRect=False, returnint=True) - # hmarginlines = lineswithinrange(hmarginlines, (vrect[0], vrect[1]), (vrect[2],vrect[3]), x=True, y=False) - marginlines = np.append(vmarginlines, hmarginlines, axis=0) - - # colourdst = cv2.cvtColor(preppedimage, cv2.COLOR_GRAY2BGR) - # if marginlines is not None: - # for l in marginlines: - # cv2.line(colourdst, (int(l[0]), int(l[1])), (int(l[2]), int(l[3])), (0,0,255), 3, cv2.LINE_AA) - # return colourdst - - rect = lineBoundingRect(marginlines,asRect=False, returnint=True) - scaledrect = (int(rect[0]*scalingmultiplier), int(rect[1]*scalingmultiplier), int(rect[2]*scalingmultiplier), int(rect[3]*scalingmultiplier)) - croppedbaseimage = baseimage[scaledrect[1]:scaledrect[3], scaledrect[0]:scaledrect[2], :] - return croppedbaseimage - -def contourcrop(baseimage): - shrunkencbi, sizemultiplier = ResizeWithAspectRatio(baseimage, width=1000, retscale=True) - gray = cv2.cvtColor(shrunkencbi, cv2.COLOR_BGR2GRAY) - # thresh = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)[1] - thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_TRIANGLE)[1] - # window = gray.shape[1]//7 - # if window % 2 == 0: - # window += 1 - # thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, window, 10) - - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,5)) - # thresh = cv2.morphologyEx(thresh, cv2.MORPH_ERODE, kernel, iterations=2) - thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel) - # return thresh - - contours, heirarchy = cv2.findContours(thresh,cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) - - # temp = cv2.drawContours(shrunkencbi, contours, -1, (0,255,0), thickness=3) - # biggestcontour = max(contours, key=cv2.contourArea) - # temp = cv2.drawContours(shrunkencbi, [biggestcontour], -1, (0,255,0), thickness=3) - - # return temp - - mx = (0,0,0,0) - mx_area = 0 - - for i, cont in enumerate(contours): - rect = cv2.boundingRect(cont) - area = rectArea(rect) - if (area > mx_area): - mx = rect - mx_area = area - - - scaledmx = (int(mx[0]*sizemultiplier), int(mx[1]*sizemultiplier), int(mx[2]*sizemultiplier), int(mx[3]*sizemultiplier)) - finalbaseimage = baseimage[scaledmx[1]:scaledmx[1]+scaledmx[3], scaledmx[0]:scaledmx[0]+scaledmx[2], :] - return finalbaseimage - -def houghlinedeskewthencrop(baseimage, preppedimage, rotationangle, croprect): - rotatedbaseimage = rotatewithexactpadding(baseimage, rotationangle, fill=(0,0,0)) - rotateddst1 = rotatewithexactpadding(preppedimage, rotationangle, fill=(0,0,0)) - sizemultiplier = rotatedbaseimage.shape[0]/rotateddst1.shape[0] - - - croppedbaseimage = houghlinepcrop(rotatedbaseimage, rotateddst1, sizemultiplier) - - finalbaseimage = contourcrop(croppedbaseimage) - - return finalbaseimage, rotationangle - -def houghlinedeskewandcrop(image): - croppedcanny, croppedimage, canny, ogimage, rect = prepimageforhoughline(image, returnrect=True) ## scaling and cropping occurs. need to also return the changes done - # return canny, ogimage - # print(canny.shape) - # print(croppedogimage.shape) - - ## -----------------finding angle to deskew----------------- - rotationangle = houghlinedeskewangle(croppedcanny) - # print(croppedcanny.shape) - # print(abs(rotationangle)) - if (croppedcanny.shape[0] > croppedcanny.shape[1]): - if (rotationangle > 45): - rotationangle -= 90 - elif rotationangle < -45: - rotationangle += 90 - # print(rotationangle) - # elif (croppedcanny.shape[1] > croppedcanny.shape[0]): - # if (rotationangle > 45): - # rotationangle -= 90 - # elif rotationangle < -45: - # rotationangle += 90 - # print(rotationangle) - - - # rotatorrect = findcroprectforangle(rect, angle) - - # -----------------end of finding angle to deskew----------------- - - ## -----------------deskewing and then cropping----------------- - outimg, angle = houghlinedeskewthencrop(ogimage, canny, rotationangle, rect) - return outimg, angle - -def bruteforceprocessrects(greaterrects, lesserrects): - # squaredgrects = np.array([mf.xywhrectto2prect(rect) for rect in greaterrects]) - # squaredlrects = np.array([mf.xywhrectto2prect(rect) for rect in lesserrects]) - # print(squaredgrects) - # print(type(squaredgrects)) - # greatersortedbylowerx = (greaterrects[:,0]).argsort() - # greatersortedbylowery = (greaterrects[:,1]).argsort() - # greatersortedbyupperx = (greaterrects[:,0]+greaterrects[:,2]).argsort() - # greatersortedbyuppery = (greaterrects[:,1]+greaterrects[:,3]).argsort() - outerboxes = [] - for innerrect in lesserrects: - outerboxes.append(rectscontaining(innerrect, greaterrects)) - - actingrects = lesserrects.copy() - ##IMPLEMENT BRUTEFORCE MERGE/RECHECKCONTAINS HERE - i = 0 - while (i < len(actingrects)): - for j in range(i+1, len(outerboxes)): - # print("i ", i, " j ", j) - if (len(outerboxes[i].intersection(outerboxes[j])) != 0): - mergedrect = mergerects([actingrects[i], actingrects[j]]) - # print(actingrects[i], actingrects[j], mergedrect) - actingrects[i] = mergedrect - # print(actingrects) - actingrects = np.delete(actingrects, j, axis=0) - # print(actingrects) - outerboxes[i] = rectscontaining(actingrects[i], greaterrects) - outerboxes.pop(j) - i = i-1 - break - i = i+1 - # print(actingrects) - return actingrects - -def processrects(greaterrects, lesserrects): - return bruteforceprocessrects(greaterrects, lesserrects) - -def whiteoutbackground(image): - imagecpy = image.copy() - gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) - - # blur = cv2.blur(gray, (7,7)) - - # window = 51 - window = gray.shape[1]//8 - if window % 2 == 0: - window += 1 - thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, window, 2) - # thresh2 = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU)[1] - # thresh = cv2.bitwise_and(thresh1, thresh2) - # return thresh - - # dim = int(min(thresh.shape[0], thresh.shape[1])/400) - # dim = 3 - # kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (dim, dim)) - # morphedthresh = cv2.morphologyEx(thresh, cv2.MORPH_ERODE, kernel) - # return morphedthresh - - - - contours1, heirarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # contours2, heirarchy = cv2.findContours(morphedthresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - - - - biggestcontour1 = max(contours1, key=cv2.contourArea) - # biggestcontour2 = max(contours2, key=cv2.contourArea) - - epsilon = 0.0005*cv2.arcLength(biggestcontour1,True) - approx = cv2.approxPolyDP(biggestcontour1,epsilon,True) - # approx = cv2.convexHull(approx) - epsilon = 0.001*cv2.arcLength(approx,True) - approx = cv2.approxPolyDP(approx,epsilon,True) - # approx = cv2.convexHull(biggestcontour1) - # print(approx) - - # imagecpy = cv2.drawContours(imagecpy, [biggestcontour1], -1, (0,255,0), thickness=3) - # imagecpy = cv2.drawContours(imagecpy, [biggestcontour2], -1, (0,0,255), thickness=3) - - # imagecpy = cv2.drawContours(imagecpy, [approx], -1, (0,255,0), thickness=3) - # return imagecpy - - blank = np.full(thresh.shape, 255, dtype=np.uint8) - mask = blank.copy() - mask = cv2.drawContours(mask, [biggestcontour1], -1, (0,0,0), thickness=cv2.FILLED) - # mask = cv2.drawContours(mask, [approx], -1, (0,0,0), thickness=cv2.FILLED) - # mask = cv2.drawContours(mask, [biggestcontour2], -1, (0,0,0), thickness=cv2.FILLED) - - # return mask - - invertmask = 255 - mask - - - dim = int(min(invertmask.shape[0], invertmask.shape[1])/200) - # # dim = 21 - # print(dim) - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (dim, dim)) - # invertmask = cv2.morphologyEx(invertmask, cv2.MORPH_DILATE, kernel) - mask = 255 - cv2.morphologyEx(invertmask, cv2.MORPH_ERODE, kernel, iterations=1) - # return mask - - mask1 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR) - whitedbackground = cv2.bitwise_or(image, mask1) - # return whitedbackground - - mask2 = blank.copy() - mask2 = 255-cv2.drawContours(mask2, [approx], -1, (0,0,0), thickness=cv2.FILLED) - - dim = int(min(mask2.shape[0], mask2.shape[1])/50) - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (dim, dim)) - morphedmask = 255-cv2.morphologyEx(mask2, cv2.MORPH_OPEN, kernel, iterations=3) - # return morphedmask - - finalmask = cv2.bitwise_or(mask, morphedmask) - - - finalmaskbgr = cv2.cvtColor(finalmask, cv2.COLOR_GRAY2BGR) - # return finalmaskbgr - - whitedbackground = cv2.bitwise_or(whitedbackground, finalmaskbgr) - # return whitedbackground - - test = cv2.inpaint(whitedbackground, finalmask, 3, cv2.INPAINT_TELEA) - return test - -def removeCardinalLines(image, horizontal=False): - # kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) - axis = 0 - if (horizontal): - cardinal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (25,1)) - axis = 1 - else: - cardinal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,15)) - lines = cv2.morphologyEx(image, cv2.MORPH_OPEN, cardinal_kernel, iterations=2) - # lines = cv2.morphologyEx(lines, cv2.MORPH_OPEN, kernel, iterations=2) - # return lines - - mask = np.zeros(image.shape, dtype=np.uint8) - contours, _ = cv2.findContours(255-lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # mask = cv2.drawContours(mask, contours, -1, 255, thickness=3) - # return mask - - - boxes = [] - dims = np.array([]) - rects = [] - for contour in contours: - rect = cv2.minAreaRect(contour) - rect = list(rect) - rect[1]=list(rect[1]) - if (rect[1][axis] > rect[1][1-axis]): - rect[2] = rect[2] -90 - temp = rect[1][1] - rect[1][1]=rect[1][0] - rect[1][0]=temp - # print(rect) - rects.append(rect) - dims = np.append(dims, rect[1][axis]) - - # box = cv2.boxPoints(rect) - # box = np.intp(box) - # boxes.append(box) - # mask = cv2.drawContours(mask, [box], -1, 255, thickness=2) - # break - # return mask - # print(dims) - meddim = np.median(dims) - # print(meddim) - - for rect in rects: - # print(rect[1][axis]) - # print(meddim/2) - # print(rect[1][1-axis]) - # print(rect[1][axis]) - if (rect[1][axis] < meddim/2 and rect[1][1-axis] > image.shape[axis]/5): - adjustedrect = rect - adjustedrect[1][0] += 3 - adjustedrect[1][1] += 3 - box = cv2.boxPoints(adjustedrect) - box = np.intp(box) - # boxes.append(box) - # mask = cv2.drawContours(mask, [box], -1, 255, thickness=2) - image = cv2.drawContours(image, [box], -1, 255, thickness=cv2.FILLED) - - # return mask - - return image - - -def removeLinesFromText(image): - image = removeCardinalLines(image) - image = removeCardinalLines(image, horizontal=True) - return image - - - -def cropclarifying(image): - whitedbackground = whiteoutbackground(image) - # return whitedbackground - - textrefined = textClarifying(whitedbackground) - # return textrefined - #maybe now is when I put in the line removing function - - lineout = removeLinesFromText(textrefined) - - return lineout - # implement a function that's called refine text - -def croptoblack(image, extraborder=10, returnrect=False): - invertedimage = cv2.bitwise_not(image) - blackpixels = cv2.findNonZero(invertedimage) - mins = np.min(blackpixels, axis=0) - minx = max(mins[0][0]-extraborder, 0) - miny = max(mins[0][1]-extraborder, 0) - maxs = np.max(blackpixels, axis=0) - maxx = min(maxs[0][0]+extraborder, image.shape[1]) - maxy = min(maxs[0][1]+extraborder, image.shape[0]) - # print(blackpixels) - if (returnrect): - return [minx,miny,maxx-minx,maxy-miny] - return image[miny:maxy, minx:maxx] - -def reduceColours(x, centering=127): - a=0.00008 - b=40 - c=256 - x = x.astype(int) - # value = np.cbrt((x-centering)/a)+centering - value = -((c+4)/(1+np.exp((x-centering)/b)))+c - value = np.clip(value, 0, 255) - return value.astype(np.uint8) - -def bwadjustment(image, center=127): - gray = reduceColours(image,center) - - return gray - -def textClarifying(image): - - ## Try using the LAB colour space??? - gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) - autothreshold = np.clip(np.mean(gray)/1.2, 0, 255) - - lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB) - # hls = cv2.cvtColor(image, cv2.COLOR_BGR2HLS) - - kernel1 = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5)) - kernel2 = cv2.getStructuringElement(cv2.MORPH_RECT, (4, 4)) - kernel3 = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)) - kernel4 = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2)) - kernel5 = cv2.getStructuringElement(cv2.MORPH_RECT, (8, 8)) - kernel6 = cv2.getStructuringElement(cv2.MORPH_RECT, (20, 2)) - kernel7 = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 8)) - adaptivekernel = None - - # return lab[:,:,2] - - currentimgofatype = lab[:,:,0] # L-channel: expresses the brightness in the image - - # imglist = [] - - Bthresh = cv2.adaptiveThreshold(currentimgofatype, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 201, 35) - - # return Bthresh - - contours, heirarchy = cv2.findContours(255-Bthresh,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # imgcopy = cv2.drawContours(imgcopy, contours, -1, color=(0,255,0), thickness=1) - # return imgcopy - - boundingboxes = np.empty((len(contours), 4), dtype=int) - - for i, contour in enumerate(contours): - b = cv2.boundingRect(contour) - boundingboxes[i] = b - # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), 128, thickness=3) - # return imgcopy - - epsilonvalue = np.median(boundingboxes, axis=0)[3] - - adaptivekernel = cv2.getStructuringElement(cv2.MORPH_RECT, (int(epsilonvalue/15), int(epsilonvalue/15))) - - # imglist.append(Bthresh) - # imglist.append(255-Bthresh) - - morphedBthresh = cv2.morphologyEx(Bthresh, cv2.MORPH_DILATE, kernel3, iterations=2) - # morphedBthresh = cv2.morphologyEx(Bthresh, cv2.MORPH_DILATE, adaptivekernel, iterations=2) - goodmorphBthresh = cv2.morphologyEx(Bthresh, cv2.MORPH_ERODE, kernel4, iterations=2) - # goodmorphBthresh = cv2.morphologyEx(Bthresh, cv2.MORPH_ERODE, adaptivekernel, iterations=3) - # morphedBthresh = cv2.morphologyEx(morphedBthresh, cv2.MORPH_DILATE, kernel7) - # imglist.append(morphedBthresh) - # imglist.append(goodmorphBthresh) - - - thresh = cv2.threshold(currentimgofatype, 0, 255, cv2.THRESH_OTSU)[1] - # imglist.append(thresh) - - morphedthresh = cv2.morphologyEx(thresh, cv2.MORPH_ERODE, kernel6) - morphedthresh = cv2.morphologyEx(morphedthresh, cv2.MORPH_ERODE, kernel7) - reducedthresh = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, adaptivekernel, iterations=1) - - - - # imglist.append(morphedthresh) - # imglist.append(reducedthresh) - anded1 = cv2.bitwise_and(255-Bthresh, morphedthresh) - anded2 = cv2.bitwise_and(reducedthresh, 255-morphedthresh) - # imglist.append(anded1) - # imglist.append(anded2) - - contours, other = cv2.findContours(anded2, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE) - # print(other) - - mask = np.full(gray.shape,fill_value=255, dtype=np.uint8) - - for i, contour in enumerate(contours): - if (other[0][i][2] != -1 and other[0][i][3] == -1): - b = cv2.boundingRect(contour) - # image = cv2.rectangle(image, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), (0,255,0), thickness=3) - mask = cv2.rectangle(mask, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), 0, thickness=cv2.FILLED) - - # bingus = cv2.bitwise_or(goodmorphBthresh, mask) - bingus = cv2.bitwise_or(Bthresh, mask) - # bingus = cv2.morphologyEx(bingus, cv2.MORPH_CLOSE, adaptivekernel) - # imglist.append(bingus) - # return imglist - return bingus - - -## ------------------------------specific to row summation deskewing------------------------------ -def sum_rows(img): - # Create a list to store the row sums - row_sums = [] - # Iterate through the rows - for r in range(img.shape[0]-1): - # Sum the row - row_sum = sum(sum(img[r:r+1,:])) - # Add the sum to the list - row_sums.append(row_sum) - # Normalize range to (0,255) - row_sums = (row_sums/max(row_sums)) * 255 - # Return - return row_sums - - - - -## ------------------------------active functions------------------------------ - -## ------------------------------cropping------------------------------ -def morphologyCrop(image, withRectangle=False): - # convert to grayscale - gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) - - # threshold - thresh = cv2.threshold(gray, 170, 255, cv2.THRESH_BINARY)[1] - - # apply morphology - kernel = np.ones((7,7), np.uint8) - morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel) - kernel = np.ones((9,9), np.uint8) - morph = cv2.morphologyEx(morph, cv2.MORPH_ERODE, kernel) - - - # get largest contour - contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) - contours = contours[0] if len(contours) == 2 else contours[1] - area_thresh = 0 - for c in contours: - area = cv2.contourArea(c) - if area > area_thresh: - area_thresh = area - big_contour = c - - - # get bounding box - x,y,w,h = cv2.boundingRect(big_contour) - - # draw filled contour on black background - mask = np.zeros_like(gray) - mask = cv2.merge([mask,mask,mask]) - # mask = cv2.blur(mask,(121,121)) - cv2.drawContours(mask, [big_contour], -1, (255,255,255), cv2.FILLED) - - # apply mask to input - result1 = image.copy() - result1 = cv2.bitwise_and(result1, mask) - - # crop result - result2 = result1[y:y+h, x:x+w] - if (withRectangle): - return result2, (x,y,w,h) - return result2 - - - -##### ------------------------------TEST CODE FOR SELECTIVESEARCHCROP------------------------------ -# ## Test this code for the masking/colour squishing. it essentially can just speed up clipping the edges. -# #!/usr/local/bin/python3 -# import cv2 as cv -# import numpy as np - -# # Load the aerial image and convert to HSV colourspace -# image = cv.imread("aerial.png") -# hsv=cv.cvtColor(image,cv.COLOR_BGR2HSV) - -# # Define lower and uppper limits of what we call "brown" -# brown_lo=np.array([10,0,0]) -# brown_hi=np.array([20,255,255]) - -# # Mask image to only select browns -# mask=cv.inRange(hsv,brown_lo,brown_hi) - -# # Change image to red where we found brown -# image[mask>0]=(0,0,255) - -# cv.imwrite("result.png",image) - -#CAN ALSO TRY USING NUMPY VECTORIZATION -#------------------------------------------------------------------------------------------ -def selectiveSearchCrop(image): - img, scale = ResizeWithAspectRatio(image,300, retscale=True) - rects = selectiveSearchSegmentationImp(cv2.GaussianBlur(img, (15,15),0)) - bigRects = biggestRects(20, rects) - overlaprectangle = overlapRect(bigRects) - if (overlaprectangle[0] == -1): - # print("hi") - return image - # print(image.shape) - finalrect = (int(overlaprectangle[0]*scale), int(overlaprectangle[1]*scale), int(overlaprectangle[2]*scale), int(overlaprectangle[3]*scale)) - # print(finalrect) - return image[finalrect[0]: finalrect[0]+finalrect[2], finalrect[1]: finalrect[1]+finalrect[3], :] - -def cannyEdgeCrop(image, lower = 100, upper = 255, threshold1 = 50, threshold2 = 350): - lower = max(0,lower) - upper = min(255, upper) - gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) - - scaled_gray = np.zeros(gray.shape, gray.dtype) - - # for y in range(0,gray.shape[0]): - # for x in range(0,gray.shape[1]): - # scaled_gray[y][x] = colourscaler(gray[y][x], lower, upper) - scaled_gray = gray - - blurred = cv2.GaussianBlur(scaled_gray, (15,15),0) - edged = cv2.Canny(blurred, threshold1, threshold2) - return edged - -def houghlineCrop(image): - prepped = premorphCrop(image) - prepped = ResizeWithAspectRatio(prepped,1000) - # kernel = np.ones((5,5), np.uint8) - # prepped = cv2.dilate(prepped, kernel, iterations=1) - gray1 = cv2.cvtColor(prepped, cv2.COLOR_BGR2GRAY) - dst1 = cv2.Canny(gray1, 0, 500, None, 3) - cdstP = prepped.copy() - cdstPmargin = cdstP.copy() - linesP = cv2.HoughLinesP(dst1, 1, np.pi / 180, 30, None, 80, 30) - - vmarginlines = WithinXDegrees(linesP, 7) - hmarginlines = WithinXDegrees(linesP, 7, baseangle=90) - vrect = lineBoundingRect(vmarginlines,asRect=False, returnint=True) - hmarginlines = lineswithinrange(hmarginlines, (vrect[0], vrect[1]), (vrect[2],vrect[3]), x=True, y=False) - # print(hmarginlines) - if (hmarginlines != []): - marginlines = np.append(vmarginlines, hmarginlines, axis=0) - else: - marginlines = vmarginlines - - # print(marginlines) - rect = lineBoundingRect(marginlines,asRect=False, returnint=True) - # print(rect) - # cdstP = cv2.rectangle(cdstP, (rect[0],rect[1]), (rect[2],rect[3]), (0,255,0), 3) - # print(cdstP.shape) - cropped = cdstP[rect[1]:rect[3], rect[0]:rect[2],:] - - # if marginlines is not None: - # for i in range(0, len(marginlines)): - # l = marginlines[i] - # cv2.line(cdstP, (int(l[0]), int(l[1])), (int(l[2]), int(l[3])), (255,0,0), 3, cv2.LINE_AA) - return cropped - - - - -## ------------------------------deskewing------------------------------ -def rowsumdeskew(image, withangle=False): - src = 255 - cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) - scores = [] - - - # # square the image - # h,w = src.shape - # small_dimention = min(h,w) - # src = src[:small_dimention, :small_dimention] - src = squarepad(src, fill=255) - - - src = cv2.threshold(src, 70, 255, cv2.THRESH_BINARY)[1] - src = ResizeWithAspectRatio(src, height=250) - - angle = 0 - finalangle = 0 - while angle <= 360: - # Rotate the source image - img = rotate(src, angle) - # Crop the center 1/3rd of the image (roi is filled with text) - h,w = img.shape - buffer = min(h, w) - int(min(h,w)/1.5) - roi = img[int(h/2-buffer):int(h/2+buffer), int(w/2-buffer):int(w/2+buffer)] - # # Create background to draw transform on - # bg = np.zeros((buffer*2, buffer*2), np.uint8) - # Compute the sums of the rows - row_sums = sum_rows(roi) - # High score --> Zebra stripes - score = np.count_nonzero(row_sums) - scores.append(score) - # othercount = othercount + 1 - # Image has best rotation - if score <= min(scores): - # count = count + 1 - # Save the rotatied image - # print('found optimal rotation') - # best_rotation = img.copy() - finalangle = angle - # goodangle = angle - # k = display_data(roi, row_sums, buffer) - # if k == 27: break - # Increment angle and try again - angle += .75 - # cv2.destroyAllWindows() - if (withangle): - return rotate(image,finalangle), finalangle - return rotate(image, finalangle) - -def externaldeskew(image, fill=(0,0,0), alreadygray=False): - # image = io.imread(_img) - # print(type(image)) - if (alreadygray): - grayscale = image.copy() - else: - grayscale = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) - grayscale = squarepad(grayscale,fill=255) - grayscale = ResizeWithAspectRatio(grayscale, height=300) - # print(type(grayscale)) - angle = determine_skew(grayscale) - # print(angle) - rotated = rotate(image, angle, fill=fill) - return rotated - -def getreceipttextAngle(cvImage) -> float: - # Prep image, copy, convert to gray scale, blur, and threshold - newImage = padWithColour(cvImage, hpadding=50, vpadding=50, fill=(255,255,255)) - # return newImage - gray = cv2.cvtColor(newImage, cv2.COLOR_BGR2GRAY) - blur = cv2.GaussianBlur(gray, (9, 9), 0) - thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1] - - # Apply dilate to merge text into meaningful lines/paragraphs. - # Use larger kernel on X axis to merge characters into single line, cancelling out any spaces. - # But use smaller kernel on Y axis to separate between different blocks of text - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10, 5)) - dilate = cv2.dilate(thresh, kernel, iterations=5) - # return dilate - - # Find all contours - contours, hierarchy = cv2.findContours(dilate, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) - contours = sorted(contours, key = cv2.contourArea, reverse = True) - - # Find largest contour and surround in min area box - largestContour = contours[0] - - mergedcontour = mergecontours(contours) - - # return cv2.drawContours(newImage, [mergedcontour], -1, (0,255,0), thickness=3) - minAreaRect = cv2.minAreaRect(mergedcontour) - minAreaRect = list(minAreaRect) - minAreaRect[1] = list(minAreaRect[1]) - if (minAreaRect[1][0] > minAreaRect[1][1]): - temp = minAreaRect[1][0] - minAreaRect[1][0] = minAreaRect[1][1] - minAreaRect[1][1] = temp - minAreaRect[2] -= 90 - # return cv2.drawContours(newImage, [largestContour], -1, (0,255,0), thickness=3) - # minAreaRect = cv2.minAreaRect(largestContour) - - box = cv2.boxPoints(minAreaRect) - box = np.intp(box) - newImage = cv2.drawContours(newImage, [box], -1, (0,255,0), thickness=3) - # return newImage - - # Determine the angle. Convert it to the value that was originally used to obtain skewed image - angle = minAreaRect[-1] - # print(angle) - angle = anglecorrector(angle)+90 - # print(angle) - return angle - -def receipttextdeskew(img, fill=(0,0,0), returnangle=False): - colourimg = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) - angle = getreceipttextAngle(colourimg) - if returnangle: - return angle - # padimg = padWithColour(img, hpadding=50, vpadding=50, fill=fill) - # print(img.shape) - # grayfill = int((fill[0]*0.299) + (fill[1]*0.587) + (fill[2]*0.114)) - rotated = rotatewithexactpadding(colourimg, angle, fill=fill) - grayrotated = cv2.cvtColor(rotated, cv2.COLOR_BGR2GRAY) - # print(grayrotated) - croprect = croptoblack(grayrotated, returnrect=True) - # rotated = cv2.cvtColor(rotated, cv2.COLOR_GRAY2BGR) - rotated = rotated[croprect[1]:croprect[1]+croprect[3], croprect[0]:croprect[0]+croprect[2], :] - rotated = padWithColour(rotated, hpadding=50, vpadding=50, fill=fill) - return rotated - -## ------------------------------Full deskewing and cropping------------------------------ -def houghlineprocessing(image): - croppedanddeskewed, angle = houghlinedeskewandcrop(image) - # return croppedanddeskewed - - - # postprocessed = cropclarifying(croppedanddeskewed) - postprocessed = croppedanddeskewed - # return postprocessed - # postprocessed = mf.croptoblack(postprocessed) - - # postprocessed = cv2.cvtColor(postprocessed, cv2.COLOR_GRAY2BGR) - # return postprocessed - - # final = mf.externaldeskew(postprocessed, fill=(255,255,255)) - # rotangle = mf.receipttextdeskew(postprocessed, fill=(255,255,255), returnangle=True) - final = postprocessed - - - # final = mf.croptoblack(final) - - # cv2.imshow("postprocessed", mf.ResizeWithAspectRatio(postprocessed, 1000)) - # cv2.imshow("final", mf.ResizeWithAspectRatio(final, 1000)) - # cv2.waitKey(0) - # cv2.destroyAllWindows() - - return final - -###### DESIRE: CONVERT STUFF RELATED TO THE HOUGHLINE PROCESSING INTO C SINCE IT ONLY REALLY USES OPENCV \ No newline at end of file diff --git a/code/autocropper/notebooks/helper_notebooks/dataset_viewer.ipynb b/code/autocropper/notebooks/helper_notebooks/dataset_viewer.ipynb deleted file mode 100644 index 9f6978e..0000000 --- a/code/autocropper/notebooks/helper_notebooks/dataset_viewer.ipynb +++ /dev/null @@ -1,297 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "version=2.0\n", - "cachepath=\"../.cache/\"\n", - "savepath=\"./savespot/\"" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [], - "source": [ - "import torch\n", - "from torch.utils.data import DataLoader\n", - "import torch.nn as nn\n", - "import torch.nn.functional as fn\n", - "import torch.optim as optim\n", - "import torchvision.transforms.functional as tvf\n", - "import torchvision.transforms.v2 as v2\n", - "import torchvision.models as models\n", - "import torchvision.transforms as t\n", - "\n", - "\n", - "from PIL import Image\n", - "\n", - "import datasets as ds\n", - "from tqdm.autonotebook import tqdm\n", - "\n", - "import random\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import numpy as np\n", - "\n", - "\n", - "torch.cuda.empty_cache()\n", - "\n", - "\n", - "import os\n", - "import cv2\n", - "import myfunctions as mf" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [], - "source": [ - "# array = np.load(\"./testing_space/outputarray.npy\")\n", - "# counter = np.load(\"./testing_space/counter.npy\")" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [], - "source": [ - "# print(array)\n", - "# print(counter)" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [], - "source": [ - "# def ResizeWithAspectRatio(image, width=None, height=None, inter=cv2.INTER_AREA):\n", - "# dim = None\n", - "# (h, w) = image.shape[:2]\n", - "\n", - "# if width is None and height is None:\n", - "# return image\n", - "# if width is None:\n", - "# r = height / float(h)\n", - "# dim = (int(w * r), height)\n", - "# else:\n", - "# r = width / float(w)\n", - "# dim = (width, int(h * r))\n", - "\n", - "# return cv2.resize(image, dim, interpolation=inter)" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [], - "source": [ - "working_dataset = ds.load_from_disk(cachepath + \"datasets/customrotation/\")\n", - "ogdataset = ds.load_dataset(\"aharley/rvl_cdip\")\n", - "\n", - "\n", - "prepimage = v2.Compose([v2.Grayscale(num_output_channels=3),v2.Resize(512), v2.CenterCrop(512),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - "tensorize = v2.Compose([v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - "grayscaler = v2.Grayscale(num_output_channels=3)\n", - "\n", - "\n", - "working_dataset.set_transform(prepimage)\n", - "ogdataset.set_transform(prepimage)" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [], - "source": [ - "active_dataset = ogdataset['train'] # working_dataset['train']\n", - "index = random.randint(0, len(active_dataset)-1)\n", - "index=0" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "metadata": {}, - "outputs": [], - "source": [ - "# plt.imshow(t.ToPILImage()(working_dataset['test'][3]['image']), cmap='gray', vmin=0, vmax=255)\n", - "# plt.show()\n", - "# rotationapplier = model(working_dataset['test'][3]['image']).item()\n", - "# print(rotationapplier)\n", - "# img = tvf.rotate(working_dataset['test'][3]['image'], rotationapplier)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [], - "source": [ - "# plt.imshow(t.ToPILImage()(img), cmap='gray', vmin=0, vmax=255)\n", - "# plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0\n", - "1\n", - "2\n", - "3\n", - "4\n", - "5\n", - "6\n", - "5\n", - "6\n", - "7\n" - ] - } - ], - "source": [ - "# To call the model on a bunch of the images and rotate them back\n", - "copied = False\n", - "while(True):\n", - " activeimage = active_dataset[index]['image']\n", - " # img = cv2.imread(active_dataset[index]['image'], 0)\n", - " open_cv_image = np.array(t.ToPILImage()(activeimage))\n", - " open_cv_image = mf.ResizeWithAspectRatio(open_cv_image, 1000)\n", - " # cv2.namedWindow(\"image\", cv2.WINDOW_NORMAL)\n", - " # cv2.setWindowProperty(\"image\", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)\n", - " cv2.imshow(\"image\", open_cv_image)\n", - " if (copied == False):\n", - " print(index)\n", - " key = cv2.waitKey(0)\n", - "\n", - " if key == ord('c'):\n", - " # print(\"\\tCopying this one\")\n", - " copied = True\n", - " elif key == ord('x'):\n", - " index -= 1\n", - " copied = False\n", - " elif key == ord('v'):\n", - " index +=1\n", - " copied = False\n", - " elif key == ord('q'):\n", - " break\n", - " \n", - " if (index < 0):\n", - " index = len(active_dataset)-index\n", - " if (index >= len(active_dataset)):\n", - " index = 0 + (index-len(active_dataset))\n", - " \n", - " cv2.destroyAllWindows()\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "277943\n" - ] - } - ], - "source": [ - "print(index)" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.imshow(t.ToPILImage()(ogdataset['train'][index]['image']), cmap='gray', vmin=0, vmax=255)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# # for trying to call the model on the picture repeatedly to see if it will just get more and more straight if it's called multiple times\n", - "\n", - "# currentimage = working_dataset['test'][3]['image']\n", - "# while(True):\n", - "# rotationapplier = model(currentimage).item()\n", - "# print(rotationapplier)\n", - "# img = tvf.rotate(currentimage, rotationapplier)\n", - "# open_cv_image = np.array(t.ToPILImage()(img))\n", - "# cv2.imshow(f'current image', open_cv_image)\n", - "# key = cv2.waitKey(0)\n", - " \n", - "# if key == ord('q'):\n", - "# break\n", - "# elif key == ord('v'):\n", - "# currentimage = img\n", - "# # cv2.destroyAllWindows()\n", - "# cv2.destroyAllWindows()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/helper_notebooks/houghlinetechnique.ipynb b/code/autocropper/notebooks/helper_notebooks/houghlinetechnique.ipynb deleted file mode 100644 index a873ecc..0000000 --- a/code/autocropper/notebooks/helper_notebooks/houghlinetechnique.ipynb +++ /dev/null @@ -1,430 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "# https://docs.opencv.org/3.4/d9/db0/tutorial_hough_lines.html\n", - "# https://medium.com/@9sphere/machine-vision-recipes-deskewing-document-images-e17827894c34\n", - "# https://towardsdatascience.com/pre-processing-in-ocr-fc231c6035a7" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#initially for deskewing and cropping. moving to a doc for just cropping now that deskewing" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "import cv2\n", - "import numpy as np\n", - "import math\n", - "import myfunctions as mf\n", - "\n", - "import scipy.stats as st" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "# def ResizeWithAspectRatio(image, width=None, height=None, inter=cv2.INTER_AREA, retscale=False):\n", - "# dim = None\n", - "# (h, w) = image.shape[:2]\n", - "\n", - "# if width is None and height is None:\n", - "# if (retscale == True):\n", - "# return (image, 1)\n", - "# return image\n", - "# if width is None:\n", - "# r = height / float(h)\n", - "# dim = (int(w * r), height)\n", - "# else:\n", - "# r = width / float(w)\n", - "# dim = (width, int(h * r))\n", - "\n", - "# if (retscale == True):\n", - "# # print(\"hi\")\n", - "# return (cv2.resize(image, dim, interpolation=inter), 1/r)\n", - "# return cv2.resize(image, dim, interpolation=inter)\n", - "\n", - "\n", - "# class SquarePad:\n", - "# def __init__(self, fill):\n", - "# self.fill = fill\n", - " \n", - "# def __call__(self, image):\n", - "# w, h = image.shape[1], image.shape[0]\n", - "# max_wh = np.max([w, h])\n", - "# hp = int((max_wh - w) / 2)\n", - "# vp = int((max_wh - h) / 2)\n", - "# padding = (hp, vp, hp, vp)\n", - "# return cv2.copyMakeBorder(image, vp, vp, hp, hp, cv2.BORDER_CONSTANT, self.fill)\n", - " \n", - " \n", - " \n", - "# def rotate(img, angle):\n", - "# rows,cols = img.shape[0], img.shape[1]\n", - "# M = cv2.getRotationMatrix2D((cols/2,rows/2),angle,1)\n", - "# dst = cv2.warpAffine(img,M,(cols,rows))\n", - "# return dst" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "# def morphologyCrop(image):\n", - "# # convert to grayscale\n", - "# gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)\n", - "\n", - "# # threshold\n", - "# thresh = cv2.threshold(gray, 170, 255, cv2.THRESH_BINARY)[1]\n", - "\n", - "# # apply morphology\n", - "# kernel = np.ones((7,7), np.uint8)\n", - "# morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)\n", - "# kernel = np.ones((9,9), np.uint8)\n", - "# morph = cv2.morphologyEx(morph, cv2.MORPH_ERODE, kernel)\n", - "\n", - "# # get largest contour\n", - "# contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\n", - "# contours = contours[0] if len(contours) == 2 else contours[1]\n", - "# area_thresh = 0\n", - "# for c in contours:\n", - "# area = cv2.contourArea(c)\n", - "# if area > area_thresh:\n", - "# area_thresh = area\n", - "# big_contour = c\n", - "\n", - "\n", - "# # get bounding box\n", - "# x,y,w,h = cv2.boundingRect(big_contour)\n", - "\n", - "# # draw filled contour on black background\n", - "# mask = np.zeros_like(gray)\n", - "# mask = cv2.merge([mask,mask,mask])\n", - "# cv2.drawContours(mask, [big_contour], -1, (255,255,255), cv2.FILLED)\n", - "\n", - "# # apply mask to input\n", - "# result1 = image.copy()\n", - "# result1 = cv2.bitwise_and(result1, mask)\n", - "\n", - "# # crop result\n", - "# result2 = result1[y:y+h, x:x+w]\n", - "# return result2" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "# x = -2*np.pi/3\n", - "# print(x)\n", - "# print(np.pi/3)\n", - "# print(x % np.pi)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "# def lineAngle(line):\n", - "# # print(line)\n", - "# angle = (math.atan2(line[3] - line[1], line[2] - line[0]) % np.pi) - (np.pi/2)\n", - "# return angle\n", - " \n", - "# def WithinXDegrees(lines, margin):\n", - "# # outlines = np.array([[]])\n", - "# outlines = np.empty((0, 4))\n", - "# # print(outlines.shape)\n", - "# for line in lines:\n", - "# # print(type(line))\n", - "# # print(abs(lineAngle(line[0])))\n", - "# if (np.rad2deg(abs(lineAngle(line[0]))) <= margin):\n", - "# outlines = np.append(outlines, [line[0]], axis=0)\n", - "# return outlines\n", - "\n", - "# def lineBoundingRect(lines):\n", - "# maxvals = lines.max(0)\n", - "# minvals = lines.min(0)\n", - "# boundingrect = (min(minvals[0],minvals[2]), min(minvals[1],minvals[3]), max(maxvals[0],maxvals[2]),max(maxvals[1],maxvals[3]))\n", - "# return boundingrect\n", - "# # print(lines.max(0))\n", - "# # print(type(lines))" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "img = cv2.imread('./test_images/IMG_7605.jpg')\n", - "img = mf.SquarePad(fill=255)(img)\n", - "img = mf.rotate(img, 54)\n", - "img = mf.morphologyCrop(mf.ResizeWithAspectRatio(img,1000))" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "# img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n", - "# img = cv2.threshold(img, 200, 255, cv2.THRESH_BINARY)[1]" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"Detected Lines (in red) - Standard Hough Line Transform\", mf.ResizeWithAspectRatio(mf.SquarePad(fill=255)(img), 1000))\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [], - "source": [ - "resizedimg = mf.ResizeWithAspectRatio(mf.SquarePad(fill=255)(img), 500)\n", - "\n", - "# cv2.imshow(\"Detected Lines (in red) - Standard Hough Line Transform\", img)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()\n", - "\n", - "gray = cv2.cvtColor(resizedimg ,cv2.COLOR_BGR2GRAY)\n", - "gray = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)[1]\n", - "cdst = resizedimg.copy()\n", - "\n", - "\n", - "dst = cv2.Canny(gray, 50, 200, None, 3)\n", - "lines = cv2.HoughLines(dst, 1, np.pi/180, 150, None, 0, 0)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [], - "source": [ - "angles = np.zeros(len(lines))\n", - "if lines is not None:\n", - " for i in range(0, len(lines)):\n", - " rho = lines[i][0][0]\n", - " theta = lines[i][0][1]\n", - " a = math.cos(theta)\n", - " b = math.sin(theta)\n", - " x0 = a * rho\n", - " y0 = b * rho\n", - " unroundedpt1 = (x0 + 1000*(-b), y0 + 1000*(a))\n", - " unroundedpt2 = (x0 - 1000*(-b), y0 - 1000*(a))\n", - " pt1 = (int(unroundedpt1[0]), int(unroundedpt1[1]))\n", - " pt2 = (int(unroundedpt2[0]), int(unroundedpt2[1]))\n", - " v1_theta = math.atan2(pt1[1], pt1[0])\n", - " v2_theta = math.atan2(pt2[1], pt2[0])\n", - " # print(math.atan2(unroundedpt2[1] - unroundedpt1[1], unroundedpt2[0] - unroundedpt1[0]) % np.pi)\n", - " # print(lineAngle((unroundedpt1[0], unroundedpt1[1], unroundedpt2[0], unroundedpt2[1])))\n", - " # angles[i] = math.atan2(unroundedpt2[1] - unroundedpt1[1], unroundedpt2[0] - unroundedpt1[0]) % np.pi\n", - " angles[i] = mf.lineAngle((unroundedpt1[0], unroundedpt1[1], unroundedpt2[0], unroundedpt2[1]))\n", - " cv2.line(cdst, pt1, pt2, (0,0,255), 3, cv2.LINE_AA)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-56.7228217179515\n", - "-56.7228217179515\n" - ] - } - ], - "source": [ - "# print(st.mode(np.around(angles, decimals=1)))\n", - "mode = st.mode(np.around(angles, decimals=2))[0]\n", - "print(np.rad2deg(mode))\n", - "# slope = math.tan(np.deg2rad(mode))\n", - "# print(slope)\n", - "# myy0 = 0\n", - "# p1 = [0,myy0]\n", - "# p2 = [0,myy0]\n", - "# while (math.dist(p1, p2) < 5000):\n", - "# p2[0] += 0.5\n", - "# p2[1] += 0.5*slope*1000\n", - "# p2[1] = int(p2[1])\n", - "# print(p2)\n", - "# cv2.line(cdst, p1, p2, (0,255,0), 3, cv2.LINE_AA)\n", - "# rotationangle = np.rad2deg(mode)-90\n", - "rotationangle = np.rad2deg(mode)\n", - "print(rotationangle)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"Detected Lines (in red) - Standard Hough Line Transform\", cdst)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imshow(\"Detected Lines (in red) - Standard Hough Line Transform\", rotate(cdst,rotationangle))\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "rotatedimg = mf.SquarePad(fill=255)(mf.rotate(img, rotationangle))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imshow(\"Rotated Image\", ResizeWithAspectRatio(rotatedimg, 1000))\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "resizedrotatedimg = mf.ResizeWithAspectRatio(rotatedimg, 500)\n", - "gray1 = cv2.cvtColor(resizedrotatedimg, cv2.COLOR_BGR2GRAY)\n", - "dst1 = cv2.Canny(gray1, 0, 500, None, 3)\n", - "cdstP = resizedrotatedimg.copy()\n", - "cdstPmargin = cdstP.copy()\n", - "linesP = cv2.HoughLinesP(dst1, 1, np.pi / 180, 30, None, 100, 30)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "if linesP is not None:\n", - " for i in range(0, len(linesP)):\n", - " l = linesP[i][0]\n", - " cv2.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv2.LINE_AA)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"Detected Lines (in red) - Standard Hough Line Transform\", cdstP)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "# print(linesP)\n", - "marginlines = mf.WithinXDegrees(linesP, 2)\n", - "# print(marginlines)\n", - "if marginlines is not None:\n", - " for i in range(0, len(marginlines)):\n", - " l = marginlines[i]\n", - " cv2.line(cdstPmargin, (int(l[0]), int(l[1])), (int(l[2]), int(l[3])), (0,0,255), 3, cv2.LINE_AA)\n", - " \n", - "# boundingrectout = mf.lineBoundingRect(marginlines)\n", - "# # print(boundingrectout)\n", - "# cdstPmargin = cv2.rectangle(cdstPmargin,(int(boundingrectout[0]),int(boundingrectout[1])),(int(boundingrectout[2]),int(boundingrectout[3])),(0,255,0),2)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"Detected Lines (in red) - Standard Hough Line Transform\", cdstPmargin)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/helper_notebooks/image_viewer.ipynb b/code/autocropper/notebooks/helper_notebooks/image_viewer.ipynb deleted file mode 100644 index d03f143..0000000 --- a/code/autocropper/notebooks/helper_notebooks/image_viewer.ipynb +++ /dev/null @@ -1,385 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 137, - "metadata": {}, - "outputs": [], - "source": [ - "version=2.0\n", - "cachepath=\"../.cache/\"\n", - "savepath=\"./savespot/\"" - ] - }, - { - "cell_type": "code", - "execution_count": 138, - "metadata": {}, - "outputs": [], - "source": [ - "import torch\n", - "from torch.utils.data import DataLoader\n", - "import torch.nn as nn\n", - "import torch.nn.functional as fn\n", - "import torch.optim as optim\n", - "import torchvision.transforms.functional as tvf\n", - "import torchvision.transforms.v2 as v2\n", - "import torchvision.models as models\n", - "import torchvision.transforms as t\n", - "\n", - "\n", - "from PIL import Image\n", - "\n", - "import datasets as ds\n", - "from tqdm.autonotebook import tqdm\n", - "\n", - "import random\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import numpy as np\n", - "\n", - "\n", - "torch.cuda.empty_cache()\n", - "\n", - "\n", - "import os\n", - "import cv2" - ] - }, - { - "cell_type": "code", - "execution_count": 139, - "metadata": {}, - "outputs": [], - "source": [ - "# array = np.load(\"./testing_space/outputarray.npy\")\n", - "# counter = np.load(\"./testing_space/counter.npy\")" - ] - }, - { - "cell_type": "code", - "execution_count": 140, - "metadata": {}, - "outputs": [], - "source": [ - "# print(array)\n", - "# print(counter)" - ] - }, - { - "cell_type": "code", - "execution_count": 141, - "metadata": {}, - "outputs": [], - "source": [ - "class RotationDeterminer(nn.Module):\n", - " def __init__(self, new=False):\n", - " super(RotationDeterminer,self).__init__()\n", - " \n", - " torch.cuda.empty_cache()\n", - " \n", - " self.device = torch.device(\"cpu\")\n", - " if torch.cuda.is_available:\n", - " self.device = torch.device(\"cuda:0\")\n", - " \n", - " \n", - " self.appliers = [v2.RandomApply(transforms=[v2.RandomPosterize(bits=1)], p=0.25),\n", - " v2.RandomApply(transforms=[v2.ElasticTransform(alpha=25.0)], p=0.25), # maybe add fill=appliedFill\n", - " v2.RandomApply(transforms=[v2.GaussianBlur(kernel_size=(5,9), sigma=(0.1,2.))],p=0.25),\n", - " v2.RandomApply(transforms=[v2.RandomEqualize()],p=0.25)]\n", - " \n", - " \n", - " # self.conv = nn.Sequential(nn.Conv2d(3, 9, kernel_size=11,stride=3), # 1100 x 1100 => 201 x 201\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(9, 18, kernel_size=5,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.MaxPool2d(kernel_size=4, stride=2),\n", - " # nn.Conv2d(18, 36, kernel_size=3,stride=2),\n", - " # nn.BatchNorm2d(36),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(36, 72, kernel_size=3,stride=2),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.AvgPool2d(kernel_size=5, stride=3),\n", - " # nn.Conv2d(72, 144, kernel_size=3,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(144, 288, kernel_size=5,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.MaxPool2d(kernel_size=4, stride=1),\n", - " # nn.Conv2d(288, 192, kernel_size=3,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(192, 192, kernel_size=3,stride=1), # => 1\n", - " # nn.ReLU(inplace=True))\n", - " # print(\"hi\")\n", - " self.conv = models.resnet18(pretrained=new)\n", - " \n", - " self.classifier = nn.Sequential(nn.Linear(1000, 4096),\n", - " nn.ReLU(inplace=True),\n", - " nn.Linear(4096,1))\n", - " \n", - " self.lossfunc = nn.MSELoss()\n", - " \n", - " self.imageprep = v2.Compose([self.SquarePad(),v2.Resize(512),v2.Grayscale(num_output_channels=3),v2.CenterCrop(512),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - " \n", - " \n", - " class SquarePad:\n", - " def __call__(self, image):\n", - " # print(\"hi type:\", type(image))\n", - " temp = image.size()\n", - " w = temp[-2]\n", - " h = temp[-1]\n", - " max_wh = max([w, h])\n", - " hp = int((max_wh - w) / 2)\n", - " vp = int((max_wh - h) / 2)\n", - " padding = (hp, vp, hp, vp)\n", - " return tvf.pad(image, padding, 0, 'edge')\n", - "\n", - "\n", - " \n", - "\n", - " \n", - " def forward(self, image):\n", - "\n", - " transformedimage = self.imageprep(image)\n", - " transformedimage = transformedimage.to(self.device)\n", - "\n", - " if (len(transformedimage.shape) != 4 and len(transformedimage.shape) != 3):\n", - " raise Exception(\"Sorry, Dimension of image is incorrect (\", len(transformedimage.shape),\"). Expected a 3D (single image) or 4D (batch of images) tensor\")\n", - "\n", - " if (len(transformedimage.shape) == 3):\n", - " x = transformedimage.unsqueeze(0)\n", - " else:\n", - " x = transformedimage\n", - " \n", - " x = self.conv(x)\n", - " # print(x.shape)\n", - " # x = nn.Flatten(start_dim=-1)(x)\n", - " # print(x.shape)\n", - " x = self.classifier(x)\n", - " # print(x.shape)\n", - " guessRotation = nn.Flatten(start_dim=0)(x)\n", - " \n", - " return guessRotation\n", - " \n", - " def loss(self, guess, trueAnswer):\n", - " return self.lossfunc(guess, trueAnswer)\n", - " \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 142, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n", - " warnings.warn(\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n", - " warnings.warn(msg)\n" - ] - } - ], - "source": [ - "model = RotationDeterminer(new=True)\n", - "device = torch.device(\"cpu\")\n", - "if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " model = model.to(device)" - ] - }, - { - "cell_type": "code", - "execution_count": 143, - "metadata": {}, - "outputs": [], - "source": [ - "# def ResizeWithAspectRatio(image, width=None, height=None, inter=cv2.INTER_AREA):\n", - "# dim = None\n", - "# (h, w) = image.shape[:2]\n", - "\n", - "# if width is None and height is None:\n", - "# return image\n", - "# if width is None:\n", - "# r = height / float(h)\n", - "# dim = (int(w * r), height)\n", - "# else:\n", - "# r = width / float(w)\n", - "# dim = (width, int(h * r))\n", - "\n", - "# return cv2.resize(image, dim, interpolation=inter)" - ] - }, - { - "cell_type": "code", - "execution_count": 163, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "torch.Size([1, 4032, 3024])\n", - "torch.Size([3, 4032, 3024])\n", - "0.7532281875610352\n" - ] - } - ], - "source": [ - "working_dataset = ds.load_from_disk(cachepath + \"datasets/customrotation/\")\n", - "prepimage = v2.Compose([v2.Grayscale(num_output_channels=3),v2.Resize(512), v2.CenterCrop(512),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - "tensorize = v2.Compose([v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - "grayscaler = v2.Grayscale(num_output_channels=3)\n", - "working_dataset.set_transform(prepimage)\n", - "counter = np.load(savepath + \"/v\"+str(version)+\"/counter.npy\")\n", - "model.load_state_dict(torch.load(savepath + \"/v\"+str(version)+\"/modelsave\" + str(counter) +\"epochs\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 165, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "torch.Size([1, 800, 723])\n", - "torch.Size([3, 800, 723])\n", - "-1.3860492706298828\n" - ] - } - ], - "source": [ - "filereadimage = cv2.imread(\"./testing_space/cropped.jpg\", 0)\n", - "# print(type(filereadimage))\n", - "tensorizedimage = torch.unsqueeze(torch.from_numpy(filereadimage),0)\n", - "print(tensorizedimage.shape)\n", - "adjustedtensorizedimage = tensorize(grayscaler(t.ToPILImage()(tensorizedimage)))\n", - "print(adjustedtensorizedimage.shape)\n", - "rotation = model(adjustedtensorizedimage).item()\n", - "print(rotation)\n", - "rotatedimage = t.Resize(size=1000)(tvf.rotate(adjustedtensorizedimage, rotation))\n", - "# imS = mf.ResizeWithAspectRatio(filereadimage, 1000)\n", - "# imS = cv2.resize(filereadimage, (960, 540)) \n", - "open_cv_image = np.array(t.ToPILImage()(rotatedimage))\n", - "cv2.imshow(f'image', open_cv_image)\n", - "key = cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "index = 0\n", - "active_dataset = working_dataset['test']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# plt.imshow(t.ToPILImage()(working_dataset['test'][3]['image']), cmap='gray', vmin=0, vmax=255)\n", - "# plt.show()\n", - "# rotationapplier = model(working_dataset['test'][3]['image']).item()\n", - "# print(rotationapplier)\n", - "# img = tvf.rotate(working_dataset['test'][3]['image'], rotationapplier)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# plt.imshow(t.ToPILImage()(img), cmap='gray', vmin=0, vmax=255)\n", - "# plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# # To call the model on a bunch of the images and rotate them back\n", - "\n", - "# while(True):\n", - "# activeimage = active_dataset[index]['image']\n", - "# # img = cv2.imread(active_dataset[index]['image'], 0)\n", - "# activeimage = tvf.rotate(activeimage, model(activeimage).item())\n", - "# open_cv_image = np.array(t.ToPILImage()(activeimage))\n", - "# print(index)\n", - "# cv2.imshow(f'current image', open_cv_image)\n", - "# key = cv2.waitKey(0)\n", - "\n", - "# if key == ord('c'):\n", - "# print(\"\\tCopying this one\")\n", - "# elif key == ord('x'):\n", - "# index -= 1\n", - "# elif key == ord('v'):\n", - "# index +=1\n", - "# elif key == ord('q'):\n", - "# break\n", - "\n", - "# cv2.destroyAllWindows()\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# # for trying to call the model on the picture repeatedly to see if it will just get more and more straight if it's called multiple times\n", - "\n", - "# currentimage = working_dataset['test'][3]['image']\n", - "# while(True):\n", - "# rotationapplier = model(currentimage).item()\n", - "# print(rotationapplier)\n", - "# img = tvf.rotate(currentimage, rotationapplier)\n", - "# open_cv_image = np.array(t.ToPILImage()(img))\n", - "# cv2.imshow(f'current image', open_cv_image)\n", - "# key = cv2.waitKey(0)\n", - " \n", - "# if key == ord('q'):\n", - "# break\n", - "# elif key == ord('v'):\n", - "# currentimage = img\n", - "# # cv2.destroyAllWindows()\n", - "# cv2.destroyAllWindows()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/helper_notebooks/rotator_dataset_augmentor.ipynb b/code/autocropper/notebooks/helper_notebooks/rotator_dataset_augmentor.ipynb deleted file mode 100644 index e1e9877..0000000 --- a/code/autocropper/notebooks/helper_notebooks/rotator_dataset_augmentor.ipynb +++ /dev/null @@ -1,417 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "# from datasets import load_dataset, Image\n", - "import datasets as ds\n", - "import PIL\n", - "import torchvision.transforms.functional as tvf\n", - "from torchvision.transforms import v2\n", - "import random\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "original_dataset = ds.load_dataset(\"aharley/rvl_cdip\")" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "# Create own dataset from the images of the original dataset but make the labels the float value for the rotation. do the random rotation on all of the training ones but the labels for the validation and test should/can be 0\n", - "trainblacklist = [5, 102664, 102667, 277943]\n", - "testblacklist = [6, 11, 14, 18, 27, 35, 37, 54, 33669] # 33669 is a corrupt image\n", - "validationblacklist = []\n", - "og_training_dataset = original_dataset['train'].select([i for i in range(len(original_dataset['train'])) if i not in trainblacklist])\n", - "og_testing_dataset = original_dataset['test'].select([i for i in range(len(original_dataset['test'])) if i not in testblacklist])\n", - "og_validation_dataset = original_dataset['validation'].select([i for i in range(len(original_dataset['validation'])) if i not in validationblacklist])\n", - "\n", - "# type(og_testing_dataset)\n", - "\n", - "# print(type(transform_picture(og_testing_dataset[0], params)))\n", - "# out = transform_picture(og_testing_dataset[0], params)\n", - "# print(out['image'])\n" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "319998\n" - ] - } - ], - "source": [ - "print(len(og_training_dataset))" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "def has_valid_image(ex):\n", - " print(type(ex))\n", - " try:\n", - " PIL.Image.open(ex[\"image\"][\"path\"])\n", - " except Exception:\n", - " print(\"hi\")\n", - " return False\n", - " return True\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# dataset = original_dataset.cast_column(\"image\", ds.Image(decode=False))\n", - "# dataset = dataset.filter(has_valid_image)\n", - "# filtered_dataset = dataset.cast_column(\"image\", ds.Image(decode=True))" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# Parameter Declaration\n", - "minRotation=-180\n", - "maxRotation=180\n", - "minTranslation=0\n", - "maxTranslation=150\n", - "minScale = 0.4\n", - "maxScale = 1\n", - "minShear = 0\n", - "maxShear = 0\n", - "\n", - "minFill=255\n", - "maxFill=255\n", - "\n", - "params = {\"minRotation\":minRotation,\"maxRotation\":maxRotation,\"minTranslation\":minTranslation,\"maxTranslation\":maxTranslation,\"minScale\":minScale,\"maxScale\":maxScale,\"minShear\":minShear,\"maxShear\":maxShear,\"minFill\":minFill,\"maxFill\":maxFill}" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "class SquarePad:\n", - " def __init__(self, fill):\n", - " self.fill = fill\n", - " \n", - " def __call__(self, image):\n", - " w, h = image.size\n", - " max_wh = np.max([w, h])\n", - " hp = int((max_wh - w) / 2)\n", - " vp = int((max_wh - h) / 2)\n", - " padding = (hp, vp, hp, vp)\n", - " return tvf.pad(image, padding,fill=self.fill, padding_mode='constant')\n", - "\n", - "\n", - "\n", - "\n", - "def transform_picture(image_label, parameters):\n", - " image = image_label['image']\n", - "\n", - " appliedRotation = random.uniform(parameters['minRotation'], parameters['maxRotation'])\n", - " appliedXTranslation = random.uniform(parameters['minTranslation'], parameters['maxTranslation'])\n", - " appliedYTranslation = random.uniform(parameters['minTranslation'], parameters['maxTranslation'])\n", - " appliedScale = random.uniform(parameters['minScale'], parameters['maxScale'])\n", - " appliedFill = random.uniform(parameters['minFill'], parameters['maxFill'])\n", - " appliedXShear = random.uniform(parameters['minShear'], parameters['maxShear'])\n", - " appliedYShear = random.uniform(parameters['minShear'], parameters['maxShear'])\n", - " \n", - " appliers = v2.Compose([v2.RandomApply(transforms=[v2.RandomPosterize(bits=1)], p=0.25),\n", - " v2.RandomApply(transforms=[v2.ElasticTransform(alpha=25.0, fill=appliedFill)], p=0.25), # maybe add fill=appliedFill\n", - " v2.RandomApply(transforms=[v2.GaussianBlur(kernel_size=(5,9), sigma=(0.1,2.))],p=0.25),\n", - " v2.RandomApply(transforms=[v2.RandomEqualize()],p=0.25),\n", - " SquarePad(fill=appliedFill),v2.Resize(1100)])\n", - " \n", - " adjustedimage = tvf.affine(image, appliedRotation, [appliedXTranslation,appliedYTranslation], appliedScale, [appliedXShear, appliedYShear], fill=appliedFill)\n", - "\n", - " adjustedimage = appliers(adjustedimage)\n", - "\n", - " \n", - " return {'image':adjustedimage,'rotation':appliedRotation}" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "bd95dc0201c2419e982f8167e16db6b5", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Map (num_proc=4): 0%| | 0/39999 [00:00= 33669):\n", - " index = index + 1\n", - " utils.save_image(entry['image'], \"./datasetimages/test/\"+str(index)+\".jpg\")" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "88288b649a64430bb52e2ae5720e4b1f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/320000 [00:00 other.val\n", - " def __eq__(self, other): return self.val == other.val\n", - " def __str__(self): return str(self.val)\n", - " \n", - "class MinHeap(object):\n", - " def __init__(self): self.h = []\n", - " def heappush(self, x): heapq.heappush(self.h, x)\n", - " def heappop(self): return heapq.heappop(self.h)\n", - " def __getitem__(self, i): return self.h[i]\n", - " def __len__(self): return len(self.h)\n", - " \n", - "class MaxHeap(MinHeap):\n", - " def heappush(self, x): heapq.heappush(self.h, MaxHeapObj(x))\n", - " def heappop(self): return heapq.heappop(self.h).val\n", - " def __getitem__(self, i): return self.h[i].val" - ] - }, - { - "cell_type": "code", - "execution_count": 353, - "metadata": {}, - "outputs": [], - "source": [ - "# def clip(n, lower, upper):\n", - "# return max(lower, min(n, upper))\n", - "\n", - "# def colourscaler(n, min, max):\n", - "# temp = n-min\n", - "# diff = abs(max - min)\n", - "# return clip((temp/diff)*255, 0, 255)" - ] - }, - { - "cell_type": "code", - "execution_count": 354, - "metadata": {}, - "outputs": [], - "source": [ - "# inline double clip(double n, double lower, double upper) {\n", - "# return std::max(lower, std::min(n, upper));\n", - "# };\n", - "\n", - "# inline double colourscaler(double n, double min, double max) {\n", - "# double temp = n - min;\n", - "# double diff = std::abs(max - min);\n", - "# return clip((temp / diff) * 255, 0, 255);\n", - "# };" - ] - }, - { - "cell_type": "code", - "execution_count": 355, - "metadata": {}, - "outputs": [], - "source": [ - "# ## Test this code for the masking/colour squishing. it essentially can just speed up clipping the edges.\n", - "# #!/usr/local/bin/python3\n", - "# import cv2 as cv\n", - "# import numpy as np\n", - "\n", - "# # Load the aerial image and convert to HSV colourspace\n", - "# image = cv.imread(\"aerial.png\")\n", - "# hsv=cv.cvtColor(image,cv.COLOR_BGR2HSV)\n", - "\n", - "# # Define lower and uppper limits of what we call \"brown\"\n", - "# brown_lo=np.array([10,0,0])\n", - "# brown_hi=np.array([20,255,255])\n", - "\n", - "# # Mask image to only select browns\n", - "# mask=cv.inRange(hsv,brown_lo,brown_hi)\n", - "\n", - "# # Change image to red where we found brown\n", - "# image[mask>0]=(0,0,255)\n", - "\n", - "# cv.imwrite(\"result.png\",image)\n", - "\n", - "#CAN ALSO TRY USING NUMPY VECTORIZATION" - ] - }, - { - "cell_type": "code", - "execution_count": 356, - "metadata": {}, - "outputs": [], - "source": [ - "# def rotate(img, angle):\n", - "# rows,cols = img.shape[0], img.shape[1]\n", - "# M = cv2.getRotationMatrix2D((cols/2,rows/2),angle,1)\n", - "# dst = cv2.warpAffine(img,M,(cols,rows))\n", - "# return dst" - ] - }, - { - "cell_type": "code", - "execution_count": 357, - "metadata": {}, - "outputs": [], - "source": [ - "def crop(image, lower = 100, upper = 255, threshold1 = 50, threshold2 = 350):\n", - " lower = max(0,lower)\n", - " upper = min(255, upper)\n", - " gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)\n", - "\n", - " scaled_gray = np.zeros(gray.shape, gray.dtype)\n", - " \n", - " # for y in range(0,gray.shape[0]):\n", - " # for x in range(0,gray.shape[1]):\n", - " # scaled_gray[y][x] = colourscaler(gray[y][x], lower, upper)\n", - " scaled_gray = gray\n", - " \n", - " blurred = cv2.GaussianBlur(scaled_gray, (15,15),0)\n", - " # blurred = scaled_gray\n", - " edged = cv2.Canny(blurred, threshold1, threshold2)\n", - " # meangrayscale = cv2.mean(scaled_gray)[0]\n", - " # print(meangrayscale)\n", - " # edged = cv2.Canny(blurred, int(meangrayscale*2), int(meangrayscale*4))\n", - " return edged\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 358, - "metadata": {}, - "outputs": [], - "source": [ - "def selectiveSearchSegmentationImp(image):\n", - " ss = cv2.ximgproc.segmentation.createSelectiveSearchSegmentation()\n", - " ss.setBaseImage(image)\n", - " ss.switchToSelectiveSearchFast()\n", - " return ss.process()" - ] - }, - { - "cell_type": "code", - "execution_count": 359, - "metadata": {}, - "outputs": [], - "source": [ - "img = cv2.imread('./testing_space/final.jpg')" - ] - }, - { - "cell_type": "code", - "execution_count": 360, - "metadata": {}, - "outputs": [], - "source": [ - "# def rectArea(rect):\n", - "# # print(rect)\n", - "# return rect[2]*rect[3]\n", - "\n", - "# def biggestRects(n, rects):\n", - "# dict = {}\n", - "# # outrects = np.zeros(shape=(n, 4))\n", - "# for rect in rects:\n", - "# dict[tuple(rect)] = mf.rectArea(rect)\n", - "# # maxh.heappush(mf.rectArea(rect))\n", - "# # print(maxh[0])\n", - " \n", - " \n", - "# heap = [(-value, key) for key,value in dict.items()]\n", - "# largest = hq.nsmallest(n, heap)\n", - " \n", - "\n", - "# # hq.heapify(list(dict.items()))\n", - "# # for i in range(0,n):\n", - "# # outrects[i] = maxh.heappop()\n", - "# # print(outrects)\n", - "# return [key for value, key in largest]\n", - "\n", - "# def overlapRect(rects):\n", - "# leftwall = -1\n", - "# rightwall = -1\n", - "# topwall = -1\n", - "# bottomwall = -1\n", - "# for (x, y, w, h) in rects:\n", - "# if (leftwall == -1):\n", - "# leftwall = x\n", - "# rightwall = x + w\n", - "# topwall = y\n", - "# bottomwall = y + h\n", - "# continue\n", - "# leftwall = max(leftwall, x)\n", - "# rightwall = min(rightwall, x+w)\n", - "# topwall = max(topwall, y)\n", - "# bottomwall = min(bottomwall, y+h)\n", - " \n", - "# if (topwall >= bottomwall or leftwall >= rightwall):\n", - "# return (-1, -1, -1, -1)\n", - "# return (leftwall, topwall, rightwall-leftwall, bottomwall-topwall)" - ] - }, - { - "cell_type": "code", - "execution_count": 344, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(-1, -1, -1, -1)\n" - ] - } - ], - "source": [ - "# rect = crop(img)\n", - "\n", - "# _, thresholded = cv2.threshold(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), 200, 255, cv2.THRESH_BINARY)\n", - "\n", - "rects = selectiveSearchSegmentationImp(cv2.GaussianBlur(ResizeWithAspectRatio(img,300), (15,15),0))\n", - "# mf.rectArea(rects[0])\n", - "bigRects = mf.biggestRects(20, rects)\n", - "# print(bigRects)\n", - "\n", - "finalrect = mf.overlapRect(bigRects)\n", - "print(finalrect)\n", - "output = ResizeWithAspectRatio(img,300)\n", - "for (x, y, w, h) in [finalrect]:\n", - "\t\t# draw the region proposal bounding box on the image\n", - "\t\tcolor = [random.randint(0, 255) for j in range(0, 3)]\n", - "\t\tcv2.rectangle(output, (x, y), (x + w, y + h), color, 2)\n", - "\n", - "# edges = cv2.Canny(cv2.GaussianBlur(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), (15,15),0),255 / 4, 255)\n", - "\n", - "# plt.imshow(edges, cmap='gray', vmin=0, vmax=255)\n", - "# plt.show()\n", - "\n", - "cv2.imshow(\"banana\", output)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()\n", - "\n", - "\n", - "# print(range(0,img.shape[1]))\n", - "# for i in range(0,img.shape[1]):\n", - "# print(i)" - ] - }, - { - "cell_type": "code", - "execution_count": 389, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "1\n" - ] - } - ], - "source": [ - "temp = ResizeWithAspectRatio(crop(img, threshold1=150, threshold2=350),500)\n", - "contours, _ = cv2.findContours(temp, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - "# print(type(contours))\n", - "# max(cv2.contourArea(contours))\n", - "# areas = list(map(cv2.contourArea, contours))\n", - "# print(areas)\n", - "contourindex = np.argmax(list(map(cv2.contourArea, contours)))\n", - "temp = cv2.drawContours(temp, contours, contourindex, (255,0,0), 2)\n", - "cv2.imshow(\"banana\", temp)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()\n", - "print(contourindex)\n", - "rect = cv2.boundingRect(contours[contourindex])\n", - "color = (random.randint(0,256), random.randint(0,256), random.randint(0,256))\n", - "result = cv2.rectangle(ResizeWithAspectRatio(img,500), rect, color, 3)" - ] - }, - { - "cell_type": "code", - "execution_count": 362, - "metadata": {}, - "outputs": [], - "source": [ - "# print(contourindex)" - ] - }, - { - "cell_type": "code", - "execution_count": 371, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"banana\", result)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 348, - "metadata": {}, - "outputs": [], - "source": [ - "# HSV = cv2.cvtColor(ResizeWithAspectRatio(img,500), cv2.COLOR_BGR2HSV)\n", - "# low = np.array([0,0,10])\n", - "# high = np.array([179,10,255])\n", - "\n", - "# mask = cv2.inRange(HSV,low,high)\n", - "\n", - "# cv2.imshow(\"banana\", mask)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 349, - "metadata": {}, - "outputs": [], - "source": [ - " # cv::Mat gray, scaled_gray, blurred, edged;\n", - "\n", - " # lower = std::max(lower, 0);\n", - " # upper = std::min(upper, 255);\n", - "\n", - " # cv::cvtColor(src, gray, cv::COLOR_BGR2GRAY);\n", - " # scaled_gray = cv::Mat::zeros(gray.size(), gray.type());\n", - "\n", - " # for (int y = 0; y < gray.rows; y++) {\n", - " # for (int x = 0; x < gray.cols; x++) {\n", - " # scaled_gray.at(y, x) =\n", - " # cv::saturate_cast(colourscaler(gray.at(y, x), lower, upper));\n", - " # }\n", - " # }\n", - "\n", - " # cv::GaussianBlur(scaled_gray, blurred, cv::Size(15, 15), 0);\n", - " # cv::Canny(blurred, edged, threshold1, threshold2);\n", - "\n", - " # std::vector> contours;\n", - " # std::vector heirarchy;\n", - " # cv::Mat approx;\n", - "\n", - " # cv::findContours(edged, contours, heirarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE);\n", - "\n", - " # cv::cvtColor(gray, gray, cv::COLOR_GRAY2BGR);\n", - "\n", - " # std::sort(contours.begin(), contours.end(), [](std::vector a, std::vector b) {\n", - " # return cv::arcLength(a, false) > cv::arcLength(b, false); });\n", - "\n", - " # int numContours = contours.size();\n", - "\n", - "\n", - " # return cv::boundingRect(contours[0]);" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/oldnotebooks/manualcropandrotate.ipynb b/code/autocropper/notebooks/oldnotebooks/manualcropandrotate.ipynb deleted file mode 100644 index e026ae3..0000000 --- a/code/autocropper/notebooks/oldnotebooks/manualcropandrotate.ipynb +++ /dev/null @@ -1,94 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "import cv2\n", - "import numpy as np\n", - "\n", - "import torch\n", - "import torchvision.transforms.functional as tvf\n", - "import torchvision.transforms.v2 as v2\n", - "import torchvision.transforms as t\n", - "import myfunctions as mf\n", - "\n", - "from skimage import io\n", - "from matplotlib import pyplot as plt\n", - "import time\n", - "\n", - "import myfunctions as mf" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "# read image as grayscale\n", - "img = cv2.imread('./test_images/IMG_7594.jpg')" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "cropped = mf.morphologyCrop(img)\n", - "# rotated = deskew(cropped)\n", - "# cropped2 = morphologyCrop(rotated)\n", - "# cropped2 = selectiveSearchCrop(rotated)\n", - "# cropped3 = cannyEdgeCrop(cropped2)\n", - "cv2.imwrite(\"./testing_space/final.jpg\", cropped)\n", - "# final = rotate(cropped2, 180) # need to implement the code to determine if a doc is upside down" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "### Deskew seems to work \n", - "# Note licencing for the deskew package and " - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/oldnotebooks/manualrotationchecker.ipynb b/code/autocropper/notebooks/oldnotebooks/manualrotationchecker.ipynb deleted file mode 100644 index 05d8961..0000000 --- a/code/autocropper/notebooks/oldnotebooks/manualrotationchecker.ipynb +++ /dev/null @@ -1,316 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# can probably be deleted or put somewhere. Was the original code for the rowsumdeskew" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "import cv2\n", - "import numpy as np\n" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "\n", - "src = 255 - cv2.imread('./testing_space/cropped1.jpg',0)\n", - "scores = []\n", - "\n", - "h,w = src.shape\n", - "small_dimention = min(h,w)\n", - "src = src[:small_dimention, :small_dimention]\n", - "\n", - "out = cv2.VideoWriter('./temp/video.avi',\n", - " cv2.VideoWriter_fourcc('M','J','P','G'),\n", - " 15, (320,320))\n", - "\n", - "src = cv2.threshold(src, 100, 255, cv2.THRESH_BINARY)[1]" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "def rotate(img, angle):\n", - " rows,cols = img.shape\n", - " M = cv2.getRotationMatrix2D((cols/2,rows/2),angle,1)\n", - " dst = cv2.warpAffine(img,M,(cols,rows))\n", - " return dst\n", - "\n", - "def sum_rows(img):\n", - " # Create a list to store the row sums\n", - " row_sums = []\n", - " # Iterate through the rows\n", - " for r in range(img.shape[0]-1):\n", - " # Sum the row\n", - " row_sum = sum(sum(img[r:r+1,:]))\n", - " # Add the sum to the list\n", - " row_sums.append(row_sum)\n", - " # Normalize range to (0,255)\n", - " row_sums = (row_sums/max(row_sums)) * 255\n", - " # Return\n", - " return row_sums\n", - "\n", - "def display_data(roi, row_sums, buffer): \n", - " # Create background to draw transform on\n", - " bg = np.zeros((buffer*2, buffer*2), np.uint8) \n", - " # Iterate through the rows and draw on the background\n", - " for row in range(roi.shape[0]-1):\n", - " row_sum = row_sums[row]\n", - " bg[row:row+1, :] = row_sum\n", - " left_side = int(buffer/3)\n", - " bg[:, left_side:] = roi[:,left_side:] \n", - " cv2.imshow('bg1', bg)\n", - " k = cv2.waitKey(1)\n", - " out.write(cv2.cvtColor(cv2.resize(bg, (320,320)), cv2.COLOR_GRAY2BGR))\n", - " return k\n" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "count = 0\n", - "othercount = 0\n", - "goodangle = 0" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imshow('bg1', src)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "found optimal rotation\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n", - "found optimal rotation\n" - ] - } - ], - "source": [ - "# Rotate the image around in a circle\n", - "angle = 0\n", - "while angle <= 360:\n", - " # Rotate the source image\n", - " img = rotate(src, angle) \n", - " # Crop the center 1/3rd of the image (roi is filled with text)\n", - " h,w = img.shape\n", - " buffer = min(h, w) - int(min(h,w)/1.5)\n", - " roi = img[int(h/2-buffer):int(h/2+buffer), int(w/2-buffer):int(w/2+buffer)]\n", - " # Create background to draw transform on\n", - " bg = np.zeros((buffer*2, buffer*2), np.uint8)\n", - " # Compute the sums of the rows\n", - " row_sums = sum_rows(roi)\n", - " # High score --> Zebra stripes\n", - " score = np.count_nonzero(row_sums)\n", - " scores.append(score)\n", - " othercount = othercount + 1\n", - " # Image has best rotation\n", - " if score <= min(scores):\n", - " count = count + 1\n", - " # Save the rotatied image\n", - " print('found optimal rotation')\n", - " best_rotation = img.copy()\n", - " goodangle = angle\n", - " k = display_data(roi, row_sums, buffer)\n", - " if k == 27: break\n", - " # Increment angle and try again\n", - " angle += .75\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "25\n", - "481\n", - "349.5\n" - ] - } - ], - "source": [ - "print(count)\n", - "print(othercount)\n", - "print(goodangle)\n", - "cv2.imshow('bg1', best_rotation)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "print(\"start\")\n", - "\n", - "# Rotate the image around in a circle\n", - "angle = 0\n", - "while angle <= 360:\n", - " # Rotate the source image\n", - " img = rotate(src, angle) \n", - " # Crop the center 1/3rd of the image (roi is filled with text)\n", - " h,w = img.shape\n", - " buffer = min(h, w) - int(min(h,w)/1.5)\n", - " #roi = img.copy()\n", - " roi = img[int(h/2-buffer):int(h/2+buffer), int(w/2-buffer):int(w/2+buffer)]\n", - " # Create background to draw transform on\n", - " bg = np.zeros((buffer*2, buffer*2), np.uint8)\n", - " # Threshold image\n", - " _, roi = cv2.threshold(roi, 140, 255, cv2.THRESH_BINARY)\n", - " # Compute the sums of the rows\n", - " row_sums = sum_rows(roi)\n", - " # High score --> Zebra stripes\n", - " score = np.count_nonzero(row_sums)\n", - " if sum(row_sums) < 100000: scores.append(angle)\n", - " k = display_data(roi, row_sums, buffer)\n", - " if k == 27: break\n", - " # Increment angle and try again\n", - " angle += .5\n", - " print(\"loop\")\n", - "cv2.destroyAllWindows()\n", - "\n", - "print(\"endofrotate\")\n", - "\n", - "# Create images for display purposes\t\n", - "display = src.copy()\n", - "# Create an image that contains bins. \n", - "bins_image = np.zeros_like(display)\n", - "for angle in scores:\n", - " # Rotate the image and draw a line on it\n", - " display = rotate(display, angle) \n", - " cv2.line(display, (0,int(h/2)), (w,int(h/2)), 255, 1)\n", - " display = rotate(display, -angle)\n", - " # Rotate the bins image\n", - " bins_image = rotate(bins_image, angle)\n", - " # Draw a line on a temporary image\n", - " temp = np.zeros_like(bins_image)\n", - " cv2.line(temp, (0,int(h/2)), (w,int(h/2)), 50, 1)\n", - " # 'Fill' up the bins\n", - " bins_image += temp\n", - " bins_image = rotate(bins_image, -angle)\n", - " \n", - "print(\"endofbins\")\n", - "\n", - "# Find the most filled bin\n", - "for col in range(bins_image.shape[0]-1):\n", - "\tcolumn = bins_image[:, col:col+1]\n", - "\tif np.amax(column) == np.amax(bins_image): x = col\n", - "for col in range(bins_image.shape[0]-1):\n", - "\tcolumn = bins_image[:, col:col+1]\n", - "\tif np.amax(column) == np.amax(bins_image): y = col\n", - "# Draw circles showing the most filled bin\n", - "cv2.circle(display, (x,y), 560, 255, 5)\n", - "\n", - "print(\"plotting\")\n", - "\n", - "# Plot with Matplotlib\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.image as mpimg\n", - "f, axarr = plt.subplots(1,3, sharex=True)\n", - "axarr[0].imshow(src)\n", - "axarr[1].imshow(display)\n", - "axarr[2].imshow(bins_image)\n", - "axarr[0].set_title('Source Image')\n", - "axarr[1].set_title('Output')\n", - "axarr[2].set_title('Bins Image')\n", - "axarr[0].axis('off')\n", - "axarr[1].axis('off')\n", - "axarr[2].axis('off')\n", - "plt.show()\n", - "\n", - "cv2.waitKey()\n", - "cv2.destroyAllWindows()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/counter.npy b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/counter.npy deleted file mode 100644 index 6d846f6..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/counter.npy and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave1 epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave1 epochs deleted file mode 100644 index 2b5b551..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave1 epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave10 epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave10 epochs deleted file mode 100644 index 81775ab..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave10 epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave15 epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave15 epochs deleted file mode 100644 index 69cebe6..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave15 epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave4 epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave4 epochs deleted file mode 100644 index a024aca..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave4 epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave6 epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave6 epochs deleted file mode 100644 index cc07573..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/modelsave6 epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/outputarray.npy b/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/outputarray.npy deleted file mode 100644 index a80a34b..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v1.1/outputarray.npy and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/counter.npy b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/counter.npy deleted file mode 100644 index 910aa62..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/counter.npy and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave0epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave0epochs deleted file mode 100644 index 4694a92..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave0epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave11epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave11epochs deleted file mode 100644 index 8590a1e..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave11epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave13epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave13epochs deleted file mode 100644 index 9f62c11..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave13epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave1epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave1epochs deleted file mode 100644 index 77be29d..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave1epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave5epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave5epochs deleted file mode 100644 index f9da167..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave5epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave8epochs b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave8epochs deleted file mode 100644 index b3d4129..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/modelsave8epochs and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/outputarray copy.npy b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/outputarray copy.npy deleted file mode 100644 index 2f647dc..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/outputarray copy.npy and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/outputarray.npy b/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/outputarray.npy deleted file mode 100644 index 6ccf2e9..0000000 Binary files a/code/autocropper/notebooks/oldnotebooks/modelsaves/v2.0/outputarray.npy and /dev/null differ diff --git a/code/autocropper/notebooks/oldnotebooks/rotator.ipynb b/code/autocropper/notebooks/oldnotebooks/rotator.ipynb deleted file mode 100644 index c00e60b..0000000 --- a/code/autocropper/notebooks/oldnotebooks/rotator.ipynb +++ /dev/null @@ -1,777 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n" - ] - } - ], - "source": [ - "import torch\n", - "import torch.nn as nn\n", - "import torch.nn.functional as fn\n", - "import torch.optim as optim\n", - "import torchvision.transforms.functional as tvf\n", - "from torchvision.transforms import v2\n", - "from torch.utils.data import DataLoader\n", - "\n", - "from PIL import Image\n", - "\n", - "import datasets as ds\n", - "from tqdm.autonotebook import tqdm\n", - "\n", - "import random\n", - "\n", - "import matplotlib.pyplot as plt\n", - "\n", - "import numpy as np\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# original_dataset = ds.load_dataset(\"aharley/rvl_cdip\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "working_dataset = ds.load_from_disk(\"../.cache/huggingfaces/datasets/customrotation/\")\n", - "prepimage = v2.Compose([v2.Grayscale(num_output_channels=3),v2.Resize(1100), v2.CenterCrop(1100),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - "working_dataset.set_transform(prepimage)\n", - "torch.cuda.empty_cache()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# Parameter Declaration\n", - "minRotation=-180\n", - "maxRotation=180\n", - "minTranslation=0\n", - "maxTranslation=150\n", - "minScale = 0.4\n", - "maxScale = 1\n", - "minShear = 0\n", - "maxShear = 0\n", - "\n", - "minFill=0\n", - "maxFill=255\n", - "\n", - "params = {\"minRotation\":minRotation,\"maxRotation\":maxRotation,\"minTranslation\":minTranslation,\"maxTranslation\":maxTranslation,\"minScale\":minScale,\"maxScale\":maxScale,\"minShear\":minShear,\"maxShear\":maxShear,\"minFill\":minFill,\"maxFill\":maxFill}" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "def transform_picture(image_label, parameters):\n", - " image = image_label['image']\n", - "\n", - " appliedRotation = random.uniform(parameters['minRotation'], parameters['maxRotation'])\n", - " appliedXTranslation = random.uniform(parameters['minTranslation'], parameters['maxTranslation'])\n", - " appliedYTranslation = random.uniform(parameters['minTranslation'], parameters['maxTranslation'])\n", - " appliedScale = random.uniform(parameters['minScale'], parameters['maxScale'])\n", - " appliedFill = random.uniform(parameters['minFill'], parameters['maxFill'])\n", - " appliedXShear = random.uniform(parameters['minShear'], parameters['maxShear'])\n", - " appliedYShear = random.uniform(parameters['minShear'], parameters['maxShear'])\n", - " \n", - " appliers = [v2.RandomApply(transforms=[v2.RandomPosterize(bits=1)], p=0.25),\n", - " v2.RandomApply(transforms=[v2.ElasticTransform(alpha=25.0, fill=appliedFill)], p=0.25), # maybe add fill=appliedFill\n", - " v2.RandomApply(transforms=[v2.GaussianBlur(kernel_size=(5,9), sigma=(0.1,2.))],p=0.25),\n", - " v2.RandomApply(transforms=[v2.RandomEqualize()],p=0.25)]\n", - " \n", - " adjustedimage = tvf.affine(image, appliedRotation, [appliedXTranslation,appliedYTranslation], appliedScale, [appliedXShear, appliedYShear], fill=appliedFill)\n", - "\n", - " for applier in appliers:\n", - " adjustedimage = applier(adjustedimage)\n", - "\n", - " \n", - " adjustedimage = tvf.resize(adjustedimage, size=[1100,1100])\n", - " \n", - " return {'image':adjustedimage,'label':appliedRotation}" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# # Create own dataset from the images of the original dataset but make the labels the float value for the rotation. do the random rotation on all of the training ones but the labels for the validation and test should/can be 0\n", - "# og_training_dataset = original_dataset['train']\n", - "# og_testing_dataset = original_dataset['test']\n", - "# og_validation_dataset = original_dataset['validation']\n", - "\n", - "# type(og_testing_dataset[0]['label'])\n", - "\n", - "# # type(transform_picture(og_testing_dataset[0], params))\n", - "# new_testing_dataset = og_testing_dataset.map(transform_picture, fn_kwargs={'parameters':params})" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# class WorkaroundDataset(torch.utils.data.Dataset):\n", - "# def __init__(self, dataset):\n", - "# self._dataset = dataset\n", - "\n", - "# def __len__(self):\n", - "# return len(self._dataset)\n", - "\n", - "# def __getitem__(self, idx):\n", - "# return v2.Compose([v2.ToImageTensor(), v2.ConvertImageDtype()])(self._dataset[idx]['image'])" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# # type(image_dataset['train'][0]['image'])\n", - "# # print(image_dataset['train'][0]['image'])\n", - "# img = image_dataset['train'][2]['image']\n", - "# # img\n", - "# # print(img.size)\n", - "# crop = tvf.resize(img, size=[500])\n", - "# # crop\n", - "# # print(crop.size)\n", - "# newimg = tvf.affine(crop, 180, [0,0], 0.7, 0)\n", - "# newimg" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "# appliedRotation = random.uniform(minRotation, maxRotation)\n", - "# appliedXTranslation = random.uniform(minTranslation, maxTranslation)\n", - "# appliedYTranslation = random.uniform(minTranslation, maxTranslation)\n", - "# appliedScale = random.uniform(minScale, maxScale)\n", - "# appliedFill = random.uniform(minFill, maxFill)\n", - "\n", - "\n", - "\n", - "# newimg = tvf.affine(crop, appliedRotation, [appliedXTranslation,appliedYTranslation], appliedScale, shear, fill=appliedFill)\n", - "# newimg\n", - "\n", - "# appliers = [v2.RandomApply(transforms=[v2.RandomPosterize(bits=1)], p=0.25),\n", - "# v2.RandomApply(transforms=[v2.ElasticTransform(alpha=25.0, fill=appliedFill)], p=0.25),\n", - "# v2.RandomApply(transforms=[v2.GaussianBlur(kernel_size=(5,9), sigma=(0.1,2.))],p=0.25),\n", - "# v2.RandomApply(transforms=[v2.RandomEqualize()],p=0.25)]\n", - "\n", - "# for applier in appliers:\n", - "# newimg = applier(newimg)\n", - " \n", - "# # newimg\n", - "# newimg= tvf.resize(newimg, size=[1000,1000])\n", - "# newimg\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# class SquarePad:\n", - "# \tdef __call__(self, image):\n", - "# \t\tw, h = image.size\n", - "# \t\tmax_wh = np.max([w, h])\n", - "# \t\thp = int((max_wh - w) / 2)\n", - "# \t\tvp = int((max_wh - h) / 2)\n", - "# \t\tpadding = (hp, vp, hp, vp)\n", - "# \t\treturn tvf.pad(image, padding, 0, 'constant')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "class RotationDeterminer(nn.Module):\n", - " def __init__(self):\n", - " super().__init__()\n", - " \n", - " torch.cuda.empty_cache()\n", - " \n", - " self.device = torch.device(\"cpu\")\n", - " if torch.cuda.is_available:\n", - " self.device = torch.device(\"cuda:0\")\n", - " \n", - " \n", - " self.appliers = [v2.RandomApply(transforms=[v2.RandomPosterize(bits=1)], p=0.25),\n", - " v2.RandomApply(transforms=[v2.ElasticTransform(alpha=25.0)], p=0.25), # maybe add fill=appliedFill\n", - " v2.RandomApply(transforms=[v2.GaussianBlur(kernel_size=(5,9), sigma=(0.1,2.))],p=0.25),\n", - " v2.RandomApply(transforms=[v2.RandomEqualize()],p=0.25)]\n", - " \n", - " \n", - " self.conv = nn.Sequential(nn.Conv2d(3, 9, kernel_size=11,stride=3), # 1100 x 1100 => 201 x 201\n", - " nn.ReLU(inplace=True),\n", - " nn.Conv2d(9, 18, kernel_size=5,stride=1),\n", - " nn.ReLU(inplace=True),\n", - " nn.MaxPool2d(kernel_size=4, stride=2),\n", - " nn.Conv2d(18, 36, kernel_size=3,stride=2),\n", - " nn.ReLU(inplace=True),\n", - " nn.Conv2d(36, 72, kernel_size=3,stride=2),\n", - " nn.ReLU(inplace=True),\n", - " nn.AvgPool2d(kernel_size=5, stride=3),\n", - " nn.Conv2d(72, 144, kernel_size=3,stride=1),\n", - " nn.ReLU(inplace=True),\n", - " nn.Conv2d(144, 288, kernel_size=5,stride=1),\n", - " nn.ReLU(inplace=True),\n", - " nn.MaxPool2d(kernel_size=4, stride=1),\n", - " nn.Conv2d(288, 192, kernel_size=3,stride=1),\n", - " nn.ReLU(inplace=True),\n", - " nn.Conv2d(192, 192, kernel_size=3,stride=1), # => 1\n", - " nn.ReLU(inplace=True))\n", - " \n", - " self.classifier = nn.Sequential(nn.Dropout(),\n", - " nn.Linear(192, 2048),\n", - " nn.ReLU(inplace=True),\n", - " nn.Dropout(),\n", - " nn.Linear(2048,2048),\n", - " nn.ReLU(inplace=True),\n", - " nn.Linear(2048,1))\n", - " \n", - " self.lossfunc = nn.MSELoss()\n", - " \n", - " self.imageprep = v2.Compose([self.SquarePad(),v2.Resize(1100),v2.Grayscale(num_output_channels=3),v2.CenterCrop(1100),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - " \n", - " \n", - " class SquarePad:\n", - " def __call__(self, image):\n", - " # print(\"hi type:\", type(image))\n", - " temp = image.size()\n", - " w = temp[-2]\n", - " h = temp[-1]\n", - " max_wh = max([w, h])\n", - " hp = int((max_wh - w) / 2)\n", - " vp = int((max_wh - h) / 2)\n", - " padding = (hp, vp, hp, vp)\n", - " return tvf.pad(image, padding, 0, 'edge')\n", - "\n", - "\n", - " \n", - "\n", - " \n", - " def forward(self, image):\n", - "\n", - " transformedimage = self.imageprep(image)\n", - " transformedimage = transformedimage.to(self.device)\n", - "\n", - " x = self.conv(transformedimage)\n", - " x = nn.Flatten(start_dim=-3)(x)\n", - " x = self.classifier(x)\n", - " guessRotation = nn.Flatten(start_dim=0)(x)\n", - " \n", - " return guessRotation\n", - " \n", - " def loss(self, guess, trueAnswer):\n", - " return self.lossfunc(guess, trueAnswer)\n", - " \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# def batchmaker(entries, batchsize):\n", - "# random.shuffle(entries)\n", - "# listing = []\n", - "# for i in range(0,len(entries), batchsize):\n", - "# listing.append(entries[i:i+batchsize])\n", - "# return listing" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "# print(type(v2.Compose([v2.ToImageTensor(), v2.ConvertImageDtype()])(image_dataset['train'][0]['image'])))" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "# a, b, x = working_dataset['train'][0]['image'].size()\n", - "# print(x)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "def train(model, dataset, batchsize, num_epochs, stepsize, totalnumiters = -1):\n", - " device = torch.device(\"cpu\")\n", - " if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " model = model.cuda()\n", - " optimizer = optim.Adam(model.parameters(), lr=stepsize)\n", - " \n", - " counter = totalnumiters\n", - " model = model.train()\n", - " \n", - " breakearly = True\n", - " if totalnumiters == -1:\n", - " print(\"hi\")\n", - " breakearly = False\n", - " totalnumiters = len(dataset) + 1\n", - " \n", - " for e in range(num_epochs):\n", - " \n", - " train_dataloader = DataLoader(dataset, batch_size=batchsize, shuffle=True)\n", - " \n", - " pbar = tqdm(train_dataloader)\n", - " \n", - " for i, batch in enumerate(pbar):\n", - " torch.cuda.empty_cache()\n", - " images, truerotations = batch['image'], batch['rotation']\n", - " images = images.to(device)\n", - " truerotations = truerotations.to(device)\n", - "\n", - " optimizer.zero_grad()\n", - " \n", - " guessRotation = model(images)\n", - " \n", - " truerotations = truerotations.float()\n", - " \n", - " loss = model.loss(guessRotation, truerotations)\n", - " \n", - " loss.backward()\n", - " \n", - " optimizer.step()\n", - " counter = counter - batchsize\n", - " if counter <= 0 and breakearly:\n", - " print(\"endearly\")\n", - " return\n", - "\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "testimage = working_dataset['train'][10]['image']\n", - "\n", - "# testimage = v2.Compose([v2.Grayscale(num_output_channels=3),v2.ToTensor(),])(testimage)\n", - "# testimage.size()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "# plt.imshow(testimage)\n", - "# plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "# temp = testimage.size()\n", - "# print(temp[-3])" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "model = RotationDeterminer()\n", - "device = torch.device(\"cpu\")\n", - "if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " model = model.cuda()\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "# output = model(testimage)\n", - "# print(output)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "# train_dataloader = DataLoader(working_dataset['test'], batch_size=100, shuffle=True)\n", - "# hold = next(iter(train_dataloader))\n", - "# images1, labels1 = hold['image'], hold['rotation']\n", - "# # print(images1)\n", - "# print(labels1.size())" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "hi\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "faff1411ea0d485b9321271ebe6820db", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/12800 [00:00 201 x 201\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(9, 18, kernel_size=5,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.MaxPool2d(kernel_size=4, stride=2),\n", - " # nn.Conv2d(18, 36, kernel_size=3,stride=2),\n", - " # nn.BatchNorm2d(36),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(36, 72, kernel_size=3,stride=2),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.AvgPool2d(kernel_size=5, stride=3),\n", - " # nn.Conv2d(72, 144, kernel_size=3,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(144, 288, kernel_size=5,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.MaxPool2d(kernel_size=4, stride=1),\n", - " # nn.Conv2d(288, 192, kernel_size=3,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(192, 192, kernel_size=3,stride=1), # => 1\n", - " # nn.ReLU(inplace=True))\n", - " # print(\"hi\")\n", - " self.conv = models.resnet18(pretrained=new)\n", - " \n", - " self.classifier = nn.Sequential(nn.Linear(1000, 4096),\n", - " nn.ReLU(inplace=True),\n", - " nn.Linear(4096,1))\n", - " \n", - " self.lossfunc = nn.MSELoss()\n", - " \n", - " self.imageprep = v2.Compose([self.SquarePad(),v2.Resize(512),v2.Grayscale(num_output_channels=3),v2.CenterCrop(512),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - " \n", - " \n", - " class SquarePad:\n", - " def __call__(self, image):\n", - " # print(\"hi type:\", type(image))\n", - " temp = image.size()\n", - " w = temp[-2]\n", - " h = temp[-1]\n", - " max_wh = max([w, h])\n", - " hp = int((max_wh - w) / 2)\n", - " vp = int((max_wh - h) / 2)\n", - " padding = (hp, vp, hp, vp)\n", - " return tvf.pad(image, padding, 0, 'edge')\n", - "\n", - "\n", - " \n", - "\n", - " \n", - " def forward(self, image):\n", - "\n", - " transformedimage = self.imageprep(image)\n", - " transformedimage = transformedimage.to(self.device)\n", - "\n", - " if (len(transformedimage.shape) != 4 and len(transformedimage.shape) != 3):\n", - " raise Exception(\"Sorry, Dimension of image is incorrect (\", len(transformedimage.shape),\"). Expected a 3D (single image) or 4D (batch of images) tensor\")\n", - "\n", - " if (len(transformedimage.shape) == 3):\n", - " x = transformedimage.unsqueeze(0)\n", - " else:\n", - " x = transformedimage\n", - " \n", - " x = self.conv(x)\n", - " # print(x.shape)\n", - " # x = nn.Flatten(start_dim=-1)(x)\n", - " # print(x.shape)\n", - " x = self.classifier(x)\n", - " # print(x.shape)\n", - " guessRotation = nn.Flatten(start_dim=0)(x)\n", - " \n", - " return guessRotation\n", - " \n", - " def loss(self, guess, trueAnswer):\n", - " return self.lossfunc(guess, trueAnswer)\n", - " \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def train(model, dataset, batchsize, num_epochs, stepsize, totalnumiters = -1):\n", - " device = torch.device(\"cpu\")\n", - " if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " model = model.cuda()\n", - " optimizer = optim.Adam(model.parameters(), lr=stepsize)\n", - " \n", - " counter = totalnumiters\n", - " model = model.train()\n", - " \n", - " breakearly = True\n", - " if totalnumiters == -1:\n", - " print(\"hi\")\n", - " breakearly = False\n", - " totalnumiters = len(dataset) + 1\n", - " \n", - " for e in range(num_epochs):\n", - " \n", - " train_dataloader = DataLoader(dataset, batch_size=batchsize, shuffle=True)\n", - " \n", - " pbar = tqdm(train_dataloader)\n", - " \n", - " for i, batch in enumerate(pbar):\n", - " torch.cuda.empty_cache()\n", - " images, truerotations = batch['image'], batch['rotation']\n", - " images = images.to(device)\n", - " truerotations = truerotations.to(device)\n", - "\n", - " optimizer.zero_grad()\n", - " \n", - " guessRotation = model(images)\n", - " \n", - " truerotations = truerotations.float()\n", - " \n", - " loss = model.loss(guessRotation, truerotations)\n", - " \n", - " loss.backward()\n", - " \n", - " optimizer.step()\n", - " counter = counter - batchsize\n", - " if counter <= 0 and breakearly:\n", - " print(\"endearly\")\n", - " return\n", - "\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def measure(model, dataset):\n", - " total=0\n", - " within30=0\n", - " within15=0\n", - " within10=0\n", - " within5=0\n", - " within1=0\n", - " withintenth=0\n", - " model = model.eval()\n", - " pbar = tqdm(dataset)\n", - " for i, sample in enumerate(pbar):\n", - " if (i % 100 == 0):\n", - " torch.cuda.empty_cache()\n", - " images, truerotations = sample['image'], sample['rotation']\n", - " output = model(images)\n", - " outputvalue = output.item()\n", - " total = total + 1\n", - " if (abs(outputvalue - truerotations) < 0.1):\n", - " withintenth = withintenth + 1\n", - " within1 = within1 + 1\n", - " within5 = within5 + 1\n", - " within10 = within10 + 1\n", - " within15 = within15 + 1\n", - " within30 = within30 + 1\n", - " elif (abs(outputvalue - truerotations) < 1):\n", - " within1 = within1 + 1\n", - " within5 = within5 + 1\n", - " within10 = within10 + 1\n", - " within15 = within15 + 1\n", - " within30 = within30 + 1\n", - " elif (abs(outputvalue - truerotations) < 5):\n", - " within5 = within5 + 1\n", - " within10 = within10 + 1\n", - " within15 = within15 + 1\n", - " within30 = within30 + 1\n", - " elif (abs(outputvalue - truerotations) < 10):\n", - " within10 = within10 + 1\n", - " within15 = within15 + 1\n", - " within30 = within30 + 1\n", - " elif (abs(outputvalue - truerotations) < 15):\n", - " within15 = within15 + 1\n", - " within30 = within30 + 1\n", - " elif (abs(outputvalue - truerotations) < 30):\n", - " within30 = within30 + 1\n", - " # print(\"Hi\")\n", - " return {\"Within 30 Degrees\": within30/total, \"Within 15 Degrees\": within15/total, \"Within 10 Degrees\": within10/total, \"Within 5 Degrees\": within5/total, \"Within 1 Degree\": within1/total, \"Within 0.1 Degree\": withintenth/total}" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n", - " warnings.warn(\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n", - " warnings.warn(msg)\n" - ] - } - ], - "source": [ - "model = RotationDeterminer(new=True)\n", - "device = torch.device(\"cpu\")\n", - "if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " model = model.to(device)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# # used when starting a new model training\n", - "# counter = 0\n", - "# outputarray = np.array([])\n", - "# tempdict = {\"Epochs Done\": counter}\n", - "# tempdict.update(measure(model, working_dataset['validation']))\n", - "# outputarray = np.append(outputarray, tempdict)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# load values\n", - "counter = np.load(savepath + \"/v\"+str(version)+\"/counter.npy\")\n", - "model.load_state_dict(torch.load(savepath + \"/v\"+str(version)+\"/modelsave\" + str(counter) +\"epochs\"))\n", - "outputarray = np.load(savepath + \"/v\"+str(version)+\"/outputarray.npy\", allow_pickle=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "# # used to rollback the model one training loop\n", - "# counter = 6\n", - "# outputarray = #removed the 7th element, will go from the 6th epoch" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "hi\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "3048e1546e12444193f99b15781768d9", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/12800 [00:00 area_thresh:\n", - " area_thresh = area\n", - " big_contour = c\n", - "\n", - "\n", - "# get bounding box\n", - "x,y,w,h = cv2.boundingRect(big_contour)\n", - "\n", - "# draw filled contour on black background\n", - "mask = np.zeros_like(gray)\n", - "mask = cv2.merge([mask,mask,mask])\n", - "cv2.drawContours(mask, [big_contour], -1, (255,255,255), cv2.FILLED)\n", - "\n", - "# apply mask to input\n", - "result1 = img.copy()\n", - "result1 = cv2.bitwise_and(result1, mask)\n", - "\n", - "# crop result\n", - "result2 = result1[y:y+h, x:x+w]\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], - "source": [ - "# view result\n", - "# cv2.imshow(\"threshold\", thresh)\n", - "# cv2.imshow(\"morph\", morph)\n", - "# cv2.imshow(\"mask\", mask)\n", - "# cv2.imshow(\"result1\", result1)\n", - "resizedresult2 = mf.ResizeWithAspectRatio(result2, 1000)\n", - "cv2.imwrite(\"./testing_space/cropped1.jpg\", resizedresult2)\n", - "cv2.imshow(\"result2\", resizedresult2)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "class RotationDeterminer(nn.Module):\n", - " def __init__(self, new=False):\n", - " super(RotationDeterminer,self).__init__()\n", - " \n", - " torch.cuda.empty_cache()\n", - " \n", - " self.device = torch.device(\"cpu\")\n", - " if torch.cuda.is_available:\n", - " self.device = torch.device(\"cuda:0\")\n", - " \n", - " \n", - " self.appliers = [v2.RandomApply(transforms=[v2.RandomPosterize(bits=1)], p=0.25),\n", - " v2.RandomApply(transforms=[v2.ElasticTransform(alpha=25.0)], p=0.25), # maybe add fill=appliedFill\n", - " v2.RandomApply(transforms=[v2.GaussianBlur(kernel_size=(5,9), sigma=(0.1,2.))],p=0.25),\n", - " v2.RandomApply(transforms=[v2.RandomEqualize()],p=0.25)]\n", - " \n", - " \n", - " # self.conv = nn.Sequential(nn.Conv2d(3, 9, kernel_size=11,stride=3), # 1100 x 1100 => 201 x 201\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(9, 18, kernel_size=5,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.MaxPool2d(kernel_size=4, stride=2),\n", - " # nn.Conv2d(18, 36, kernel_size=3,stride=2),\n", - " # nn.BatchNorm2d(36),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(36, 72, kernel_size=3,stride=2),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.AvgPool2d(kernel_size=5, stride=3),\n", - " # nn.Conv2d(72, 144, kernel_size=3,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(144, 288, kernel_size=5,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.MaxPool2d(kernel_size=4, stride=1),\n", - " # nn.Conv2d(288, 192, kernel_size=3,stride=1),\n", - " # nn.ReLU(inplace=True),\n", - " # nn.Conv2d(192, 192, kernel_size=3,stride=1), # => 1\n", - " # nn.ReLU(inplace=True))\n", - " # print(\"hi\")\n", - " self.conv = models.resnet18(pretrained=new)\n", - " \n", - " self.classifier = nn.Sequential(nn.Linear(1000, 4096),\n", - " nn.ReLU(inplace=True),\n", - " nn.Linear(4096,1))\n", - " \n", - " self.lossfunc = nn.MSELoss()\n", - " \n", - " self.imageprep = v2.Compose([self.SquarePad(),v2.Resize(512),v2.Grayscale(num_output_channels=3),v2.CenterCrop(512),v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - " \n", - " \n", - " class SquarePad:\n", - " def __call__(self, image):\n", - " # print(\"hi type:\", type(image))\n", - " temp = image.size()\n", - " w = temp[-2]\n", - " h = temp[-1]\n", - " max_wh = max([w, h])\n", - " hp = int((max_wh - w) / 2)\n", - " vp = int((max_wh - h) / 2)\n", - " padding = (hp, vp, hp, vp)\n", - " return tvf.pad(image, padding, 0, 'edge')\n", - "\n", - "\n", - " \n", - "\n", - " \n", - " def forward(self, image):\n", - "\n", - " transformedimage = self.imageprep(image)\n", - " transformedimage = transformedimage.to(self.device)\n", - "\n", - " if (len(transformedimage.shape) != 4 and len(transformedimage.shape) != 3):\n", - " raise Exception(\"Sorry, Dimension of image is incorrect (\", len(transformedimage.shape),\"). Expected a 3D (single image) or 4D (batch of images) tensor\")\n", - "\n", - " if (len(transformedimage.shape) == 3):\n", - " x = transformedimage.unsqueeze(0)\n", - " else:\n", - " x = transformedimage\n", - " \n", - " x = self.conv(x)\n", - " # print(x.shape)\n", - " # x = nn.Flatten(start_dim=-1)(x)\n", - " # print(x.shape)\n", - " x = self.classifier(x)\n", - " # print(x.shape)\n", - " guessRotation = nn.Flatten(start_dim=0)(x)\n", - " \n", - " return guessRotation\n", - " \n", - " def loss(self, guess, trueAnswer):\n", - " return self.lossfunc(guess, trueAnswer)\n", - " \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n", - " warnings.warn(\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n", - " warnings.warn(msg)\n" - ] - } - ], - "source": [ - "model = RotationDeterminer(new=True)\n", - "device = torch.device(\"cpu\")\n", - "if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " model = model.to(device)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "torch.Size([1, 1174, 1000])\n", - "torch.Size([3, 1174, 1000])\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n", - " warnings.warn(\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-0.1470905989408493\n" - ] - } - ], - "source": [ - "tensorize = v2.Compose([v2.ToImageTensor(), v2.ConvertImageDtype()])\n", - "grayscaler = v2.Grayscale(num_output_channels=3)\n", - "\n", - "imagetobeprocessed = cv2.cvtColor(resizedresult2,cv2.COLOR_BGR2GRAY)\n", - "\n", - "\n", - "tensorizedimage = torch.unsqueeze(torch.from_numpy(imagetobeprocessed),0)\n", - "print(tensorizedimage.shape)\n", - "adjustedtensorizedimage = tensorize(grayscaler(t.ToPILImage()(tensorizedimage)))\n", - "print(adjustedtensorizedimage.shape)\n", - "rotation = model(adjustedtensorizedimage).item()\n", - "print(rotation)\n", - "rotatedimage = t.Resize(size=1000)(tvf.rotate(adjustedtensorizedimage, rotation))\n", - "# imS = mf.ResizeWithAspectRatio(filereadimage, 1000)\n", - "# imS = cv2.resize(filereadimage, (960, 540)) \n", - "open_cv_image = np.array(t.ToPILImage()(rotatedimage))\n", - "cv2.imshow(f'image', open_cv_image)\n", - "key = cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# # save result\n", - "# cv2.imwrite(\"paper_thresh.jpg\", thresh)\n", - "# cv2.imwrite(\"paper_morph.jpg\", morph)\n", - "# cv2.imwrite(\"paper_mask.jpg\", mask)\n", - "# cv2.imwrite(\"paper_result1.jpg\", result1)\n", - "# cv2.imwrite(\"paper_result2.jpg\", result2)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - }, - "orig_nbformat": 4 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/notebooks/oldnotebooks/tobedeleted.ipynb b/code/autocropper/notebooks/oldnotebooks/tobedeleted.ipynb deleted file mode 100644 index 65f30e8..0000000 --- a/code/autocropper/notebooks/oldnotebooks/tobedeleted.ipynb +++ /dev/null @@ -1,387 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 772, - "metadata": {}, - "outputs": [], - "source": [ - "import cv2\n", - "import numpy as np\n", - "\n", - "import myfunctions as mf\n", - "\n", - "\n", - "import scipy.stats as st\n", - "import math" - ] - }, - { - "cell_type": "code", - "execution_count": 773, - "metadata": {}, - "outputs": [], - "source": [ - "# read image as grayscale\n", - "img = cv2.imread('./test_images/IMG_7605.jpg')\n", - "# img = mf.ResizeWithAspectRatio(img,1000)\n", - "# img = mf.rotate(img, 54)" - ] - }, - { - "cell_type": "code", - "execution_count": 774, - "metadata": {}, - "outputs": [], - "source": [ - "prepped = mf.ResizeWithAspectRatio(mf.SquarePad(fill=255)(img),1000)\n", - "prepped = mf.premorphCrop(prepped)\n", - "prepped = mf.ResizeWithAspectRatio(mf.SquarePad(fill=255)(prepped),1000)\n", - "# kernel = np.ones((5,5), np.uint8)\n", - "# prepped = cv2.dilate(prepped, kernel, iterations=1)\n", - "gray1 = cv2.cvtColor(prepped, cv2.COLOR_BGR2GRAY)\n", - "dst1 = cv2.Canny(gray1, 0, 500, None, 3)\n", - "\n", - "kernel = np.ones((5,5), np.uint8)\n", - "out = cv2.morphologyEx(dst1, cv2.MORPH_DILATE, kernel)\n", - "out = cv2.blur(out, (5,5))\n", - "kernel = np.ones((6,6), np.uint8)\n", - "dst1 = cv2.morphologyEx(out, cv2.MORPH_ERODE, kernel)\n", - "\n", - "dst1 = cv2.Canny(dst1, 0, 500, None, 3)\n", - "\n", - "cdstP = prepped.copy()\n", - "cdstPmargin = cdstP.copy()\n", - "basecdstP = cdstP.copy()\n", - "linesP = cv2.HoughLinesP(dst1, 1, np.pi / 180, 30, None, 90, 30)" - ] - }, - { - "cell_type": "code", - "execution_count": 779, - "metadata": {}, - "outputs": [], - "source": [ - "# # testing = dst1.copy()\n", - "# # kernel = np.ones((5,5), np.uint8)\n", - "# # out = cv2.morphologyEx(testing, cv2.MORPH_DILATE, kernel)\n", - "# # out = cv2.blur(out, (5,5))\n", - "# # kernel = np.ones((3,3), np.uint8)\n", - "# # out = cv2.morphologyEx(out, cv2.MORPH_ERODE, kernel)\n", - "cv2.imshow(\"result1\", dst1)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 758, - "metadata": {}, - "outputs": [], - "source": [ - "angles = np.zeros(len(linesP))\n", - "if linesP is not None:\n", - " for i in range(0, len(linesP)):\n", - " l = linesP[i][0]\n", - " angles[i] = mf.lineAngle(l)\n", - " cv2.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv2.LINE_AA)" - ] - }, - { - "cell_type": "code", - "execution_count": 759, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imshow(\"result1\", cdstP)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 760, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-3.093972093706445\n" - ] - } - ], - "source": [ - "mode = st.mode(np.around(angles, decimals=3))[0]\n", - "rotationangle = np.rad2deg(mode)\n", - "print(rotationangle)" - ] - }, - { - "cell_type": "code", - "execution_count": 761, - "metadata": {}, - "outputs": [], - "source": [ - "rotatedcdstP = mf.rotate(basecdstP, rotationangle)" - ] - }, - { - "cell_type": "code", - "execution_count": 762, - "metadata": {}, - "outputs": [], - "source": [ - "vmarginlines = mf.WithinXDegrees(linesP, 7, baseangle=rotationangle)\n", - "hmarginlines = mf.WithinXDegrees(linesP, 7, baseangle=90+rotationangle)\n", - "vrect = mf.lineBoundingRect(vmarginlines,asRect=False, returnint=True)\n", - "hmarginlines = mf.lineswithinrange(hmarginlines, (vrect[0], vrect[1]), (vrect[2],vrect[3]), x=True, y=False)\n", - "\n", - "\n", - "if (hmarginlines != []):\n", - " marginlines = np.append(vmarginlines, hmarginlines, axis=0)\n", - "else:\n", - " marginlines = vmarginlines\n", - " \n", - "rect = mf.lineBoundingRect(marginlines,asRect=False, returnint=True)\n", - "cdstP = cv2.rectangle(cdstP, (rect[0],rect[1]), (rect[2],rect[3]), (0,255,0), 3)" - ] - }, - { - "cell_type": "code", - "execution_count": 763, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"result1\", cdstP)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 764, - "metadata": {}, - "outputs": [], - "source": [ - "#####NEED TO WORK ON SCORING THE LINES SO IT PICKS THE CORRECT ORIENTATION (horizontal vs vertical) AND SO THAT THE CROPPING RECTANGLE MOVES/GET TRANSFORMED WITH IT" - ] - }, - { - "cell_type": "code", - "execution_count": 780, - "metadata": {}, - "outputs": [], - "source": [ - "def rotatePoint(img, pt, angle, returnint=True):\n", - " rotateaxisx = img.shape[0]/2\n", - " rotateaxisy = img.shape[1]/2\n", - " tempx = pt[0] - rotateaxisx\n", - " tempy = pt[1] - rotateaxisy\n", - " rotatedx = tempx*math.cos(np.deg2rad(-angle)) - tempy*math.sin(np.deg2rad(-angle))\n", - " rotatedy = tempx*math.sin(np.deg2rad(-angle)) + tempy*math.cos(np.deg2rad(-angle))\n", - " finalx = rotatedx + rotateaxisx\n", - " finaly = rotatedy + rotateaxisy\n", - " if (returnint):\n", - " finalx = int(finalx)\n", - " finaly = int(finaly)\n", - " return (finalx, finaly)\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 766, - "metadata": {}, - "outputs": [], - "source": [ - "def rotateRect(img, rect, angle, returnint=True, asRect=False):\n", - " if (asRect):\n", - " pt1 = rotatePoint(img, (rect[0],rect[1]), angle, returnint)\n", - " pt2 = rotatePoint(img, (rect[0]+rect[2],rect[1]+rect[3]), angle, returnint)\n", - " return (pt1[0], pt1[1], pt2[0]-pt1[0], pt2[1]-pt1[1])\n", - " else:\n", - " pt1 = rotatePoint(img, (rect[0],rect[1]), angle, returnint)\n", - " pt2 = rotatePoint(img, (rect[2],rect[3]), angle, returnint)\n", - " return (pt1[0], pt1[1], pt2[0], pt2[1])\n", - "\n", - "def rotateLine(img, line, angle, returnint=True):\n", - " pt1 = rotatePoint(img, (line[0],line[1]), angle, returnint)\n", - " pt2 = rotatePoint(img, (line[2],line[3]), angle, returnint)\n", - " return (pt1[0], pt1[1], pt2[0], pt2[1])\n", - " \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 767, - "metadata": {}, - "outputs": [], - "source": [ - "# print(linesP.shape)\n", - "rotatedlines = [rotateLine(rotatedcdstP, line[0], rotationangle) for line in linesP]\n", - "rotatedlines = np.reshape(rotatedlines, (len(rotatedlines),1,4))\n", - "# rotatedlines = linesP\n", - "# print(rotatedlines.shape)" - ] - }, - { - "cell_type": "code", - "execution_count": 768, - "metadata": {}, - "outputs": [], - "source": [ - "vmarginlines = mf.WithinXDegrees(rotatedlines, 7)\n", - "hmarginlines = mf.WithinXDegrees(rotatedlines, 7, baseangle=90)\n", - "vrect = mf.lineBoundingRect(vmarginlines,asRect=False, returnint=True)\n", - "hmarginlines = mf.lineswithinrange(hmarginlines, (vrect[0], vrect[1]), (vrect[2],vrect[3]), x=True, y=False)\n", - "\n", - "if (hmarginlines != []):\n", - " marginlines = np.append(vmarginlines, hmarginlines, axis=0)\n", - "else:\n", - " marginlines = vmarginlines\n", - " \n", - "rect = mf.lineBoundingRect(marginlines,asRect=False, returnint=True)\n", - "# rect = vrect\n", - "rotatedcdstP = cv2.rectangle(rotatedcdstP, (rect[0],rect[1]), (rect[2],rect[3]), (0,255,0), 3)" - ] - }, - { - "cell_type": "code", - "execution_count": 769, - "metadata": {}, - "outputs": [], - "source": [ - "if rotatedlines is not None:\n", - " for i in range(0, len(rotatedlines)):\n", - " l = rotatedlines[i][0]\n", - " cv2.line(rotatedcdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv2.LINE_AA)" - ] - }, - { - "cell_type": "code", - "execution_count": 771, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"result1\", rotatedcdstP)\n", - "# cv2.imshow(\"result1\", cdstP)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 394, - "metadata": {}, - "outputs": [], - "source": [ - "vmarginlines = mf.WithinXDegrees(linesP, 7)\n", - "hmarginlines = mf.WithinXDegrees(linesP, 7, baseangle=90)\n", - "vrect = mf.lineBoundingRect(vmarginlines,asRect=False, returnint=True)\n", - "hmarginlines = mf.lineswithinrange(hmarginlines, (vrect[0], vrect[1]), (vrect[2],vrect[3]), x=True, y=False)\n", - "\n", - "\n", - "if (hmarginlines != []):\n", - " marginlines = np.append(vmarginlines, hmarginlines, axis=0)\n", - "else:\n", - " marginlines = vmarginlines\n", - "\n", - "rect = mf.lineBoundingRect(marginlines,asRect=False, returnint=True)\n", - "cdstP = cv2.rectangle(cdstP, (rect[0],rect[1]), (rect[2],rect[3]), (0,255,0), 3)\n", - "\n", - "\n", - "# rotatedrect = rotateRect(cdstP, rect, -rotationangle)\n", - "\n", - "# rotatedcdstP = cv2.rectangle(rotatedcdstP, (rotatedrect[0],rotatedrect[1]), (rotatedrect[2],rotatedrect[3]), (0,255,0), 3)" - ] - }, - { - "cell_type": "code", - "execution_count": 395, - "metadata": {}, - "outputs": [], - "source": [ - "###figure out how to rotate rectangle" - ] - }, - { - "cell_type": "code", - "execution_count": 396, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"result1\", cdstP)\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 397, - "metadata": {}, - "outputs": [], - "source": [ - "# vmarginlines = mf.WithinXDegrees(linesP, 7)\n", - "# hmarginlines = mf.WithinXDegrees(linesP, 7, baseangle=90)\n", - "# vrect = mf.lineBoundingRect(vmarginlines,asRect=False, returnint=True)\n", - "# hmarginlines = mf.lineswithinrange(hmarginlines, (vrect[0], vrect[1]), (vrect[2],vrect[3]), x=True, y=False)\n", - "# # print(hmarginlines)\n", - "# if (hmarginlines != []):\n", - "# marginlines = np.append(vmarginlines, hmarginlines, axis=0)\n", - "# else:\n", - "# marginlines = vmarginlines\n", - "\n", - "# # print(marginlines)\n", - "# rect = mf.lineBoundingRect(marginlines,asRect=False, returnint=True)\n", - "# # print(rect)\n", - "# cdstP = cv2.rectangle(cdstP, (rect[0],rect[1]), (rect[2],rect[3]), (0,255,0), 3)\n", - "# # print(cdstP.shape)\n", - "# # cropped = cdstP[rect[1]:rect[3], rect[0]:rect[2],:]\n", - "\n", - "# if marginlines is not None:\n", - "# for i in range(0, len(marginlines)):\n", - "# l = marginlines[i]\n", - "# cv2.line(cdstP, (int(l[0]), int(l[1])), (int(l[2]), int(l[3])), (255,0,0), 3, cv2.LINE_AA)" - ] - }, - { - "cell_type": "code", - "execution_count": 398, - "metadata": {}, - "outputs": [], - "source": [ - "# # view result\n", - "# # cv2.imshow(\"threshold\", thresh)\n", - "# # cv2.imshow(\"morph\", morph)\n", - "# # cv2.imshow(\"mask\", mask)\n", - "# cv2.imshow(\"result1\", mf.ResizeWithAspectRatio(cdstP,height=1000))\n", - "# # cv2.imshow(\"result2\", cropped)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/src/cropper.cpp b/code/autocropper/src/cropper.cpp deleted file mode 100644 index 898aa2b..0000000 --- a/code/autocropper/src/cropper.cpp +++ /dev/null @@ -1,165 +0,0 @@ -#include "cropper.h" - -#include -#include -#include - - -using namespace cv::ximgproc::segmentation; - - - -inline cv::Point topLeft(cv::Rect rect) { - return cv::Point(rect.x, rect.y); -} - -inline cv::Point bottomLeft(cv::Rect rect) { - return cv::Point(rect.x, rect.y + rect.height); -} - -inline cv::Point topRight(cv::Rect rect) { - return cv::Point(rect.x + rect.width, rect.y); -} - -inline cv::Point bottomRight(cv::Rect rect) { - return cv::Point(rect.x + rect.width, rect.y + rect.height); -} - -inline double distanceBetweenPoints(cv::Point p1, cv::Point p2) { - return std::sqrt(std::pow(p1.x - p2.x, 2) + std::pow(p1.y - p2.y, 2)); -} - -inline void scaleRect(cv::Rect& r, int originalheight, int currentheight) { - int scalingFactor = originalheight / currentheight; - r.x *= scalingFactor; - r.y *= scalingFactor; - r.width *= scalingFactor; - r.height *= scalingFactor; -} - - -// uses the L2 loss of the corners of the rectangles -double MSELossRect(cv::Rect r1, cv::Rect r2) { - return (distanceBetweenPoints(topLeft(r1), topLeft(r2)) + - distanceBetweenPoints(bottomLeft(r1), bottomLeft(r2)) + - distanceBetweenPoints(topRight(r1), topRight(r2)) + - distanceBetweenPoints(bottomRight(r1), bottomRight(r2))) / 4.0; -} - -std::vector selectiveSearchSegmentationActor(cv::InputArray src, bool fast = true, int imageHeight = 800) { - cv::setUseOptimized(true); - cv::setNumThreads(4); - - cv::Mat temp = src.getMat(); - - cv::Ptr ss = - createSelectiveSearchSegmentation(); - - - ss->setBaseImage(temp); - - if (fast) { - ss->switchToSelectiveSearchFast(); - } else { - ss->switchToSelectiveSearchQuality(); - } - - - std::vector rects; - - ss->process(rects); - return rects; -} - -inline double clip(double n, double lower, double upper) { - return std::max(lower, std::min(n, upper)); -}; - -inline double colourscaler(double n, double min, double max) { - double temp = n - min; - double diff = std::abs(max - min); - return clip((temp / diff) * 255, 0, 255); -}; - - -cv::Rect cannyEdgeRectangle(cv::InputArray src, int lower = 100, int upper = 255, double threshold1 = 50, double threshold2 = 350) { - cv::Mat gray, scaled_gray, blurred, edged; - - lower = std::max(lower, 0); - upper = std::min(upper, 255); - - cv::cvtColor(src, gray, cv::COLOR_BGR2GRAY); - scaled_gray = cv::Mat::zeros(gray.size(), gray.type()); - - for (int y = 0; y < gray.rows; y++) { - for (int x = 0; x < gray.cols; x++) { - scaled_gray.at(y, x) = - cv::saturate_cast(colourscaler(gray.at(y, x), lower, upper)); - } - } - - cv::GaussianBlur(scaled_gray, blurred, cv::Size(15, 15), 0); - cv::Canny(blurred, edged, threshold1, threshold2); - - std::vector> contours; - std::vector heirarchy; - cv::Mat approx; - - cv::findContours(edged, contours, heirarchy, cv::RETR_TREE, cv::CHAIN_APPROX_SIMPLE); - - cv::cvtColor(gray, gray, cv::COLOR_GRAY2BGR); - - std::sort(contours.begin(), contours.end(), [](std::vector a, std::vector b) { - return cv::arcLength(a, false) > cv::arcLength(b, false); }); - - int numContours = contours.size(); - - - return cv::boundingRect(contours[0]); -} - -bool crop(cv::InputArray src, cv::OutputArray dst, bool fastsearch, int imageHeight) { //add other params or maybe overload or something - - cv::Mat temp; - src.copyTo(temp); - int newWidth = temp.cols * imageHeight / temp.rows; - cv::resize(temp, temp, cv::Size(newWidth, imageHeight)); - - - - cv::Rect cannyRect = cannyEdgeRectangle(temp, 100, 255, 255 / 4, 255); - - - std::vector rects = selectiveSearchSegmentationActor(temp, fastsearch); - - - - int indexOfMin = -1; - double currentMin = std::numeric_limits::max(); - - int lengthOfRects = rects.size(); - for (int i = 0; i < lengthOfRects; i++) { - double tempMin = MSELossRect(rects[i], cannyRect); - if (tempMin < currentMin) { - indexOfMin = i; - currentMin = tempMin; - } - } - - cv::Rect goodRect = rects[indexOfMin]; - - - cv::Rect finalRect; - if (goodRect.area() > cannyRect.area()) { - finalRect = goodRect; - } else { - finalRect = cannyRect; - } - cv::Mat extra = src.getMat(); - scaleRect(finalRect, extra.rows, temp.rows); - extra = extra(finalRect); - extra.copyTo(dst); - - - return true; -} \ No newline at end of file diff --git a/code/autocropper/temp.ipynb b/code/autocropper/temp.ipynb deleted file mode 100644 index eaaa67d..0000000 --- a/code/autocropper/temp.ipynb +++ /dev/null @@ -1,1240 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n" - ] - } - ], - "source": [ - "import cv2\n", - "import numpy as np\n", - "\n", - "import myfunctions as mf\n", - "\n", - "\n", - "import scipy.stats as st\n", - "import math" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# read image as grayscale\n", - "img = cv2.imread('./test_images/IMG_7605.jpg')\n", - "# img = mf.ResizeWithAspectRatio(img,1000)\n", - "# img = mf.rotate(img, 54)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def reduceColours(x):\n", - " b=10\n", - " c=1.2\n", - " x = x.astype(int)\n", - " value = ((x-b)*c) + (b*(c-1))\n", - " value = np.clip(value, 0, 255)\n", - " return value.astype(np.uint8)\n", - "\n", - "def bwadjustment(image):\n", - " # # print(image)\n", - " # gray = image.astype(int)\n", - " # gray += 1\n", - " # # print(gray)\n", - " # gray = np.emath.logn(1.0218, gray)\n", - " # # print(gray)\n", - " # gray = np.clip(gray, 0, 255)\n", - " # gray = gray.astype(np.uint8)\n", - " gray = reduceColours(image)\n", - " \n", - " return gray\n", - "\n", - "\n", - "\n", - "\n", - "def testingfunction(image):\n", - " gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n", - " \n", - " # sigma = 0.5\n", - " # v = np.median(image)\n", - " # lower = int(max(0, (1.0 - sigma) * v))\n", - " # upper = int(min(255, (1.0 + sigma) * v))\n", - " \n", - " # upper = 500\n", - " \n", - " \n", - " # thresh = cv2.Canny(gray, lower, upper, None, 3)\n", - " \n", - " gray = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 21, 20)\n", - " \n", - " \n", - " return gray\n", - "\n", - "\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "#####NEED TO WORK ON SCORING THE LINES SO IT PICKS THE CORRECT ORIENTATION (horizontal vs vertical) AND SO THAT THE CROPPING RECTANGLE MOVES/GET TRANSFORMED WITH IT\n", - "\n", - "\n", - "## CAN MAYBE ALSO USE NORMAL HOUGHLINE STUFF TO GET MORE LINES OR GET AN EXTRA BIT OF WEIGHTING OR SOMETHING" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "### NON-UTILITY FUNCTIONS" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "### IGNORED UTILITY FUNCTIONS\n", - "def resize_to_screen(src, maxw=1280, maxh=700, copy=False):\n", - "\n", - " height, width = src.shape[:2]\n", - "\n", - " scl_x = float(width)/maxw\n", - " scl_y = float(height)/maxh\n", - "\n", - " scl = int(np.ceil(max(scl_x, scl_y)))\n", - "\n", - " if scl > 1.0:\n", - " inv_scl = 1.0/scl\n", - " img = cv2.resize(src, (0, 0), None, inv_scl, inv_scl, cv2.INTER_AREA)\n", - " elif copy:\n", - " img = src.copy()\n", - " else:\n", - " img = src\n", - "\n", - " return img\n", - "\n", - "def main():\n", - "\n", - " if len(sys.argv) < 2:\n", - " print 'usage:', sys.argv[0], 'IMAGE1 [IMAGE2 ...]'\n", - " sys.exit(0)\n", - "\n", - " if DEBUG_LEVEL > 0 and DEBUG_OUTPUT != 'file':\n", - " cv2.namedWindow(WINDOW_NAME)\n", - "\n", - " outfiles = []\n", - "\n", - " for imgfile in sys.argv[1:]:\n", - "\n", - " img = cv2.imread(imgfile)\n", - " small = resize_to_screen(img)\n", - " basename = os.path.basename(imgfile)\n", - " name, _ = os.path.splitext(basename)\n", - "\n", - " print 'loaded', basename, 'with size', imgsize(img),\n", - " print 'and resized to', imgsize(small)\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.0, 'original', small)\n", - "\n", - " pagemask, page_outline = get_page_extents(small)\n", - "\n", - " cinfo_list = get_contours(name, small, pagemask, 'text')\n", - " spans = assemble_spans(name, small, pagemask, cinfo_list)\n", - "\n", - " if len(spans) < 3:\n", - " print ' detecting lines because only', len(spans), 'text spans'\n", - " cinfo_list = get_contours(name, small, pagemask, 'line')\n", - " spans2 = assemble_spans(name, small, pagemask, cinfo_list)\n", - " if len(spans2) > len(spans):\n", - " spans = spans2\n", - "\n", - " if len(spans) < 1:\n", - " print 'skipping', name, 'because only', len(spans), 'spans'\n", - " continue\n", - "\n", - " span_points = sample_spans(small.shape, spans)\n", - "\n", - " print ' got', len(spans), 'spans',\n", - " print 'with', sum([len(pts) for pts in span_points]), 'points.'\n", - "\n", - " corners, ycoords, xcoords = keypoints_from_samples(name, small,\n", - " pagemask,\n", - " page_outline,\n", - " span_points)\n", - "\n", - " rough_dims, span_counts, params = get_default_params(corners,\n", - " ycoords, xcoords)\n", - "\n", - " dstpoints = np.vstack((corners[0].reshape((1, 1, 2)),) +\n", - " tuple(span_points))\n", - "\n", - " params = optimize_params(name, small,\n", - " dstpoints,\n", - " span_counts, params)\n", - "\n", - " page_dims = get_page_dims(corners, rough_dims, params)\n", - "\n", - " outfile = remap_image(name, img, small, page_dims, params)\n", - "\n", - " outfiles.append(outfile)\n", - "\n", - " print ' wrote', outfile\n", - " print\n", - "\n", - " print 'to convert to PDF (requires ImageMagick):'\n", - " print ' convert -compress Group4 ' + ' '.join(outfiles) + ' output.pdf'\n", - "\n", - "\n", - "if __name__ == '__main__':\n", - " main()\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#!/usr/bin/env python\n", - "######################################################################\n", - "# page_dewarp.py - Proof-of-concept of page-dewarping based on a\n", - "# \"cubic sheet\" model. Requires OpenCV (version 3 or greater),\n", - "# PIL/Pillow, and scipy.optimize.\n", - "######################################################################\n", - "# Author: Matt Zucker\n", - "# Date: July 2016\n", - "# License: MIT License (see LICENSE.txt)\n", - "######################################################################\n", - "\n", - "import os\n", - "import sys\n", - "import datetime\n", - "import cv2\n", - "from PIL import Image\n", - "import numpy as np\n", - "import scipy.optimize\n", - "\n", - "# for some reason pylint complains about cv2 members being undefined :(\n", - "# pylint: disable=E1101\n", - "\n", - "OUTPUT_ZOOM = 1.0 # how much to zoom output relative to *original* image\n", - "OUTPUT_DPI = 300 # just affects stated DPI of PNG, not appearance\n", - "REMAP_DECIMATE = 16 # downscaling factor for remapping image\n", - "\n", - "ADAPTIVE_WINSZ = 55 # window size for adaptive threshold in reduced px\n", - "\n", - "TEXT_MIN_WIDTH = 15 # min reduced px width of detected text contour\n", - "TEXT_MIN_HEIGHT = 2 # min reduced px height of detected text contour\n", - "TEXT_MIN_ASPECT = 1.5 # filter out text contours below this w/h ratio\n", - "TEXT_MAX_THICKNESS = 10 # max reduced px thickness of detected text contour\n", - "\n", - "EDGE_MAX_OVERLAP = 1.0 # max reduced px horiz. overlap of contours in span\n", - "EDGE_MAX_LENGTH = 100.0 # max reduced px length of edge connecting contours\n", - "EDGE_ANGLE_COST = 10.0 # cost of angles in edges (tradeoff vs. length)\n", - "EDGE_MAX_ANGLE = 7.5 # maximum change in angle allowed between contours\n", - "\n", - "RVEC_IDX = slice(0, 3) # index of rvec in params vector\n", - "TVEC_IDX = slice(3, 6) # index of tvec in params vector\n", - "CUBIC_IDX = slice(6, 8) # index of cubic slopes in params vector\n", - "\n", - "SPAN_MIN_WIDTH = 30 # minimum reduced px width for span\n", - "SPAN_PX_PER_STEP = 20 # reduced px spacing for sampling along spans\n", - "FOCAL_LENGTH = 1.2 # normalized focal length of camera\n", - "\n", - "DEBUG_LEVEL = 0 # 0=none, 1=some, 2=lots, 3=all\n", - "DEBUG_OUTPUT = 'file' # file, screen, both\n", - "\n", - "WINDOW_NAME = 'Dewarp' # Window name for visualization\n", - "\n", - "# nice color palette for visualizing contours, etc.\n", - "CCOLORS = [\n", - " (255, 0, 0),\n", - " (255, 63, 0),\n", - " (255, 127, 0),\n", - " (255, 191, 0),\n", - " (255, 255, 0),\n", - " (191, 255, 0),\n", - " (127, 255, 0),\n", - " (63, 255, 0),\n", - " (0, 255, 0),\n", - " (0, 255, 63),\n", - " (0, 255, 127),\n", - " (0, 255, 191),\n", - " (0, 255, 255),\n", - " (0, 191, 255),\n", - " (0, 127, 255),\n", - " (0, 63, 255),\n", - " (0, 0, 255),\n", - " (63, 0, 255),\n", - " (127, 0, 255),\n", - " (191, 0, 255),\n", - " (255, 0, 255),\n", - " (255, 0, 191),\n", - " (255, 0, 127),\n", - " (255, 0, 63),\n", - "]\n", - "\n", - "# default intrinsic parameter matrix\n", - "K = np.array([\n", - " [FOCAL_LENGTH, 0, 0],\n", - " [0, FOCAL_LENGTH, 0],\n", - " [0, 0, 1]], dtype=np.float32)\n", - "\n", - "\n", - "def debug_show(name, step, text, display):\n", - "\n", - " if DEBUG_OUTPUT != 'screen':\n", - " filetext = text.replace(' ', '_')\n", - " outfile = name + '_debug_' + str(step) + '_' + filetext + '.png'\n", - " cv2.imwrite(outfile, display)\n", - "\n", - " if DEBUG_OUTPUT != 'file':\n", - "\n", - " image = display.copy()\n", - " height = image.shape[0]\n", - "\n", - " cv2.putText(image, text, (16, height-16),\n", - " cv2.FONT_HERSHEY_SIMPLEX, 1.0,\n", - " (0, 0, 0), 3, cv2.LINE_AA)\n", - "\n", - " cv2.putText(image, text, (16, height-16),\n", - " cv2.FONT_HERSHEY_SIMPLEX, 1.0,\n", - " (255, 255, 255), 1, cv2.LINE_AA)\n", - "\n", - " cv2.imshow(WINDOW_NAME, image)\n", - "\n", - " while cv2.waitKey(5) < 0:\n", - " pass\n", - "\n", - "\n", - "def round_nearest_multiple(i, factor):\n", - " i = int(i)\n", - " rem = i % factor\n", - " if not rem:\n", - " return i\n", - " else:\n", - " return i + factor - rem\n", - "\n", - "\n", - "def pix2norm(shape, pts):\n", - " height, width = shape[:2]\n", - " scl = 2.0/(max(height, width))\n", - " offset = np.array([width, height], dtype=pts.dtype).reshape((-1, 1, 2))*0.5\n", - " return (pts - offset) * scl\n", - "\n", - "\n", - "def norm2pix(shape, pts, as_integer):\n", - " height, width = shape[:2]\n", - " scl = max(height, width)*0.5\n", - " offset = np.array([0.5*width, 0.5*height],\n", - " dtype=pts.dtype).reshape((-1, 1, 2))\n", - " rval = pts * scl + offset\n", - " if as_integer:\n", - " return (rval + 0.5).astype(int)\n", - " else:\n", - " return rval\n", - "\n", - "\n", - "def fltp(point):\n", - " return tuple(point.astype(int).flatten())\n", - "\n", - "\n", - "def draw_correspondences(img, dstpoints, projpts):\n", - "\n", - " display = img.copy()\n", - " dstpoints = norm2pix(img.shape, dstpoints, True)\n", - " projpts = norm2pix(img.shape, projpts, True)\n", - "\n", - " for pts, color in [(projpts, (255, 0, 0)),\n", - " (dstpoints, (0, 0, 255))]:\n", - "\n", - " for point in pts:\n", - " cv2.circle(display, fltp(point), 3, color, -1, cv2.LINE_AA)\n", - "\n", - " for point_a, point_b in zip(projpts, dstpoints):\n", - " cv2.line(display, fltp(point_a), fltp(point_b),\n", - " (255, 255, 255), 1, cv2.LINE_AA)\n", - "\n", - " return display\n", - "\n", - "\n", - "def get_default_params(corners, ycoords, xcoords):\n", - "\n", - " # page width and height\n", - " page_width = np.linalg.norm(corners[1] - corners[0])\n", - " page_height = np.linalg.norm(corners[-1] - corners[0])\n", - " rough_dims = (page_width, page_height)\n", - "\n", - " # our initial guess for the cubic has no slope\n", - " cubic_slopes = [0.0, 0.0]\n", - "\n", - " # object points of flat page in 3D coordinates\n", - " corners_object3d = np.array([\n", - " [0, 0, 0],\n", - " [page_width, 0, 0],\n", - " [page_width, page_height, 0],\n", - " [0, page_height, 0]])\n", - "\n", - " # estimate rotation and translation from four 2D-to-3D point\n", - " # correspondences\n", - " _, rvec, tvec = cv2.solvePnP(corners_object3d,\n", - " corners, K, np.zeros(5))\n", - "\n", - " span_counts = [len(xc) for xc in xcoords]\n", - "\n", - " params = np.hstack((np.array(rvec).flatten(),\n", - " np.array(tvec).flatten(),\n", - " np.array(cubic_slopes).flatten(),\n", - " ycoords.flatten()) +\n", - " tuple(xcoords))\n", - "\n", - " return rough_dims, span_counts, params\n", - "\n", - "\n", - "def project_xy(xy_coords, pvec):\n", - "\n", - " # get cubic polynomial coefficients given\n", - " #\n", - " # f(0) = 0, f'(0) = alpha\n", - " # f(1) = 0, f'(1) = beta\n", - "\n", - " alpha, beta = tuple(pvec[CUBIC_IDX])\n", - "\n", - " poly = np.array([\n", - " alpha + beta,\n", - " -2*alpha - beta,\n", - " alpha,\n", - " 0])\n", - "\n", - " xy_coords = xy_coords.reshape((-1, 2))\n", - " z_coords = np.polyval(poly, xy_coords[:, 0])\n", - "\n", - " objpoints = np.hstack((xy_coords, z_coords.reshape((-1, 1))))\n", - "\n", - " image_points, _ = cv2.projectPoints(objpoints,\n", - " pvec[RVEC_IDX],\n", - " pvec[TVEC_IDX],\n", - " K, np.zeros(5))\n", - "\n", - " return image_points\n", - "\n", - "\n", - "def project_keypoints(pvec, keypoint_index):\n", - "\n", - " xy_coords = pvec[keypoint_index]\n", - " xy_coords[0, :] = 0\n", - "\n", - " return project_xy(xy_coords, pvec)\n", - "\n", - "\n", - "def box(width, height):\n", - " return np.ones((height, width), dtype=np.uint8)\n", - "\n", - "\n", - "\n", - "def get_mask(name, small, pagemask, masktype):\n", - "\n", - " sgray = cv2.cvtColor(small, cv2.COLOR_RGB2GRAY)\n", - "\n", - " if masktype == 'text':\n", - "\n", - " mask = cv2.adaptiveThreshold(sgray, 255, cv2.ADAPTIVE_THRESH_MEAN_C,\n", - " cv2.THRESH_BINARY_INV,\n", - " ADAPTIVE_WINSZ,\n", - " 25)\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.1, 'thresholded', mask)\n", - "\n", - " mask = cv2.dilate(mask, box(9, 1))\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.2, 'dilated', mask)\n", - "\n", - " mask = cv2.erode(mask, box(1, 3))\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.3, 'eroded', mask)\n", - "\n", - " else:\n", - "\n", - " mask = cv2.adaptiveThreshold(sgray, 255, cv2.ADAPTIVE_THRESH_MEAN_C,\n", - " cv2.THRESH_BINARY_INV,\n", - " ADAPTIVE_WINSZ,\n", - " 7)\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.4, 'thresholded', mask)\n", - "\n", - " mask = cv2.erode(mask, box(3, 1), iterations=3)\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.5, 'eroded', mask)\n", - "\n", - " mask = cv2.dilate(mask, box(8, 2))\n", - "\n", - " if DEBUG_LEVEL >= 3:\n", - " debug_show(name, 0.6, 'dilated', mask)\n", - "\n", - " return np.minimum(mask, pagemask)\n", - "\n", - "\n", - "def interval_measure_overlap(int_a, int_b):\n", - " return min(int_a[1], int_b[1]) - max(int_a[0], int_b[0])\n", - "\n", - "\n", - "def angle_dist(angle_b, angle_a):\n", - "\n", - " diff = angle_b - angle_a\n", - "\n", - " while diff > np.pi:\n", - " diff -= 2*np.pi\n", - "\n", - " while diff < -np.pi:\n", - " diff += 2*np.pi\n", - "\n", - " return np.abs(diff)\n", - "\n", - "\n", - "def blob_mean_and_tangent(contour):\n", - "\n", - " moments = cv2.moments(contour)\n", - "\n", - " area = moments['m00']\n", - "\n", - " mean_x = moments['m10'] / area\n", - " mean_y = moments['m01'] / area\n", - "\n", - " moments_matrix = np.array([\n", - " [moments['mu20'], moments['mu11']],\n", - " [moments['mu11'], moments['mu02']]\n", - " ]) / area\n", - "\n", - " _, svd_u, _ = cv2.SVDecomp(moments_matrix)\n", - "\n", - " center = np.array([mean_x, mean_y])\n", - " tangent = svd_u[:, 0].flatten().copy()\n", - "\n", - " return center, tangent\n", - "\n", - "\n", - "class ContourInfo(object):\n", - "\n", - " def __init__(self, contour, rect, mask):\n", - "\n", - " self.contour = contour\n", - " self.rect = rect\n", - " self.mask = mask\n", - "\n", - " self.center, self.tangent = blob_mean_and_tangent(contour)\n", - "\n", - " self.angle = np.arctan2(self.tangent[1], self.tangent[0])\n", - "\n", - " clx = [self.proj_x(point) for point in contour]\n", - "\n", - " lxmin = min(clx)\n", - " lxmax = max(clx)\n", - "\n", - " self.local_xrng = (lxmin, lxmax)\n", - "\n", - " self.point0 = self.center + self.tangent * lxmin\n", - " self.point1 = self.center + self.tangent * lxmax\n", - "\n", - " self.pred = None\n", - " self.succ = None\n", - "\n", - " def proj_x(self, point):\n", - " return np.dot(self.tangent, point.flatten()-self.center)\n", - "\n", - " def local_overlap(self, other):\n", - " xmin = self.proj_x(other.point0)\n", - " xmax = self.proj_x(other.point1)\n", - " return interval_measure_overlap(self.local_xrng, (xmin, xmax))\n", - "\n", - "\n", - "def generate_candidate_edge(cinfo_a, cinfo_b):\n", - "\n", - " # we want a left of b (so a's successor will be b and b's\n", - " # predecessor will be a) make sure right endpoint of b is to the\n", - " # right of left endpoint of a.\n", - " if cinfo_a.point0[0] > cinfo_b.point1[0]:\n", - " tmp = cinfo_a\n", - " cinfo_a = cinfo_b\n", - " cinfo_b = tmp\n", - "\n", - " x_overlap_a = cinfo_a.local_overlap(cinfo_b)\n", - " x_overlap_b = cinfo_b.local_overlap(cinfo_a)\n", - "\n", - " overall_tangent = cinfo_b.center - cinfo_a.center\n", - " overall_angle = np.arctan2(overall_tangent[1], overall_tangent[0])\n", - "\n", - " delta_angle = max(angle_dist(cinfo_a.angle, overall_angle),\n", - " angle_dist(cinfo_b.angle, overall_angle)) * 180/np.pi\n", - "\n", - " # we want the largest overlap in x to be small\n", - " x_overlap = max(x_overlap_a, x_overlap_b)\n", - "\n", - " dist = np.linalg.norm(cinfo_b.point0 - cinfo_a.point1)\n", - "\n", - " if (dist > EDGE_MAX_LENGTH or\n", - " x_overlap > EDGE_MAX_OVERLAP or\n", - " delta_angle > EDGE_MAX_ANGLE):\n", - " return None\n", - " else:\n", - " score = dist + delta_angle*EDGE_ANGLE_COST\n", - " return (score, cinfo_a, cinfo_b)\n", - "\n", - "\n", - "def make_tight_mask(contour, xmin, ymin, width, height):\n", - "\n", - " tight_mask = np.zeros((height, width), dtype=np.uint8)\n", - " tight_contour = contour - np.array((xmin, ymin)).reshape((-1, 1, 2))\n", - "\n", - " cv2.drawContours(tight_mask, [tight_contour], 0,\n", - " (1, 1, 1), -1)\n", - "\n", - " return tight_mask\n", - "\n", - "\n", - "def get_contours(name, small, pagemask, masktype):\n", - "\n", - " mask = get_mask(name, small, pagemask, masktype)\n", - "\n", - " _, contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL,\n", - " cv2.CHAIN_APPROX_NONE)\n", - "\n", - " contours_out = []\n", - "\n", - " for contour in contours:\n", - "\n", - " rect = cv2.boundingRect(contour)\n", - " xmin, ymin, width, height = rect\n", - "\n", - " if (width < TEXT_MIN_WIDTH or\n", - " height < TEXT_MIN_HEIGHT or\n", - " width < TEXT_MIN_ASPECT*height):\n", - " continue\n", - "\n", - " tight_mask = make_tight_mask(contour, xmin, ymin, width, height)\n", - "\n", - " if tight_mask.sum(axis=0).max() > TEXT_MAX_THICKNESS:\n", - " continue\n", - "\n", - " contours_out.append(ContourInfo(contour, rect, tight_mask))\n", - "\n", - " if DEBUG_LEVEL >= 2:\n", - " visualize_contours(name, small, contours_out)\n", - "\n", - " return contours_out\n", - "\n", - "\n", - "def assemble_spans(name, small, pagemask, cinfo_list):\n", - "\n", - " # sort list\n", - " cinfo_list = sorted(cinfo_list, key=lambda cinfo: cinfo.rect[1])\n", - "\n", - " # generate all candidate edges\n", - " candidate_edges = []\n", - "\n", - " for i, cinfo_i in enumerate(cinfo_list):\n", - " for j in range(i):\n", - " # note e is of the form (score, left_cinfo, right_cinfo)\n", - " edge = generate_candidate_edge(cinfo_i, cinfo_list[j])\n", - " if edge is not None:\n", - " candidate_edges.append(edge)\n", - "\n", - " # sort candidate edges by score (lower is better)\n", - " candidate_edges.sort()\n", - "\n", - " # for each candidate edge\n", - " for _, cinfo_a, cinfo_b in candidate_edges:\n", - " # if left and right are unassigned, join them\n", - " if cinfo_a.succ is None and cinfo_b.pred is None:\n", - " cinfo_a.succ = cinfo_b\n", - " cinfo_b.pred = cinfo_a\n", - "\n", - " # generate list of spans as output\n", - " spans = []\n", - "\n", - " # until we have removed everything from the list\n", - " while cinfo_list:\n", - "\n", - " # get the first on the list\n", - " cinfo = cinfo_list[0]\n", - "\n", - " # keep following predecessors until none exists\n", - " while cinfo.pred:\n", - " cinfo = cinfo.pred\n", - "\n", - " # start a new span\n", - " cur_span = []\n", - "\n", - " width = 0.0\n", - "\n", - " # follow successors til end of span\n", - " while cinfo:\n", - " # remove from list (sadly making this loop *also* O(n^2)\n", - " cinfo_list.remove(cinfo)\n", - " # add to span\n", - " cur_span.append(cinfo)\n", - " width += cinfo.local_xrng[1] - cinfo.local_xrng[0]\n", - " # set successor\n", - " cinfo = cinfo.succ\n", - "\n", - " # add if long enough\n", - " if width > SPAN_MIN_WIDTH:\n", - " spans.append(cur_span)\n", - "\n", - " if DEBUG_LEVEL >= 2:\n", - " visualize_spans(name, small, pagemask, spans)\n", - "\n", - " return spans\n", - "\n", - "\n", - "def sample_spans(shape, spans):\n", - "\n", - " span_points = []\n", - "\n", - " for span in spans:\n", - "\n", - " contour_points = []\n", - "\n", - " for cinfo in span:\n", - "\n", - " yvals = np.arange(cinfo.mask.shape[0]).reshape((-1, 1))\n", - " totals = (yvals * cinfo.mask).sum(axis=0)\n", - " means = totals / cinfo.mask.sum(axis=0)\n", - "\n", - " xmin, ymin = cinfo.rect[:2]\n", - "\n", - " step = SPAN_PX_PER_STEP\n", - " start = ((len(means)-1) % step) / 2\n", - "\n", - " contour_points += [(x+xmin, means[x]+ymin)\n", - " for x in range(start, len(means), step)]\n", - "\n", - " contour_points = np.array(contour_points,\n", - " dtype=np.float32).reshape((-1, 1, 2))\n", - "\n", - " contour_points = pix2norm(shape, contour_points)\n", - "\n", - " span_points.append(contour_points)\n", - "\n", - " return span_points\n", - "\n", - "\n", - "def keypoints_from_samples(name, small, pagemask, page_outline,\n", - " span_points):\n", - "\n", - " all_evecs = np.array([[0.0, 0.0]])\n", - " all_weights = 0\n", - "\n", - " for points in span_points:\n", - "\n", - " _, evec = cv2.PCACompute(points.reshape((-1, 2)),\n", - " None, maxComponents=1)\n", - "\n", - " weight = np.linalg.norm(points[-1] - points[0])\n", - "\n", - " all_evecs += evec * weight\n", - " all_weights += weight\n", - "\n", - " evec = all_evecs / all_weights\n", - "\n", - " x_dir = evec.flatten()\n", - "\n", - " if x_dir[0] < 0:\n", - " x_dir = -x_dir\n", - "\n", - " y_dir = np.array([-x_dir[1], x_dir[0]])\n", - "\n", - " pagecoords = cv2.convexHull(page_outline)\n", - " pagecoords = pix2norm(pagemask.shape, pagecoords.reshape((-1, 1, 2)))\n", - " pagecoords = pagecoords.reshape((-1, 2))\n", - "\n", - " px_coords = np.dot(pagecoords, x_dir)\n", - " py_coords = np.dot(pagecoords, y_dir)\n", - "\n", - " px0 = px_coords.min()\n", - " px1 = px_coords.max()\n", - "\n", - " py0 = py_coords.min()\n", - " py1 = py_coords.max()\n", - "\n", - " p00 = px0 * x_dir + py0 * y_dir\n", - " p10 = px1 * x_dir + py0 * y_dir\n", - " p11 = px1 * x_dir + py1 * y_dir\n", - " p01 = px0 * x_dir + py1 * y_dir\n", - "\n", - " corners = np.vstack((p00, p10, p11, p01)).reshape((-1, 1, 2))\n", - "\n", - " ycoords = []\n", - " xcoords = []\n", - "\n", - " for points in span_points:\n", - " pts = points.reshape((-1, 2))\n", - " px_coords = np.dot(pts, x_dir)\n", - " py_coords = np.dot(pts, y_dir)\n", - " ycoords.append(py_coords.mean() - py0)\n", - " xcoords.append(px_coords - px0)\n", - "\n", - " if DEBUG_LEVEL >= 2:\n", - " visualize_span_points(name, small, span_points, corners)\n", - "\n", - " return corners, np.array(ycoords), xcoords\n", - "\n", - "\n", - "def visualize_contours(name, small, cinfo_list):\n", - "\n", - " regions = np.zeros_like(small)\n", - "\n", - " for j, cinfo in enumerate(cinfo_list):\n", - "\n", - " cv2.drawContours(regions, [cinfo.contour], 0,\n", - " CCOLORS[j % len(CCOLORS)], -1)\n", - "\n", - " mask = (regions.max(axis=2) != 0)\n", - "\n", - " display = small.copy()\n", - " display[mask] = (display[mask]/2) + (regions[mask]/2)\n", - "\n", - " for j, cinfo in enumerate(cinfo_list):\n", - " color = CCOLORS[j % len(CCOLORS)]\n", - " color = tuple([c/4 for c in color])\n", - "\n", - " cv2.circle(display, fltp(cinfo.center), 3,\n", - " (255, 255, 255), 1, cv2.LINE_AA)\n", - "\n", - " cv2.line(display, fltp(cinfo.point0), fltp(cinfo.point1),\n", - " (255, 255, 255), 1, cv2.LINE_AA)\n", - "\n", - " debug_show(name, 1, 'contours', display)\n", - "\n", - "\n", - "def visualize_spans(name, small, pagemask, spans):\n", - "\n", - " regions = np.zeros_like(small)\n", - "\n", - " for i, span in enumerate(spans):\n", - " contours = [cinfo.contour for cinfo in span]\n", - " cv2.drawContours(regions, contours, -1,\n", - " CCOLORS[i*3 % len(CCOLORS)], -1)\n", - "\n", - " mask = (regions.max(axis=2) != 0)\n", - "\n", - " display = small.copy()\n", - " display[mask] = (display[mask]/2) + (regions[mask]/2)\n", - " display[pagemask == 0] /= 4\n", - "\n", - " debug_show(name, 2, 'spans', display)\n", - "\n", - "\n", - "def visualize_span_points(name, small, span_points, corners):\n", - "\n", - " display = small.copy()\n", - "\n", - " for i, points in enumerate(span_points):\n", - "\n", - " points = norm2pix(small.shape, points, False)\n", - "\n", - " mean, small_evec = cv2.PCACompute(points.reshape((-1, 2)),\n", - " None,\n", - " maxComponents=1)\n", - "\n", - " dps = np.dot(points.reshape((-1, 2)), small_evec.reshape((2, 1)))\n", - " dpm = np.dot(mean.flatten(), small_evec.flatten())\n", - "\n", - " point0 = mean + small_evec * (dps.min()-dpm)\n", - " point1 = mean + small_evec * (dps.max()-dpm)\n", - "\n", - " for point in points:\n", - " cv2.circle(display, fltp(point), 3,\n", - " CCOLORS[i % len(CCOLORS)], -1, cv2.LINE_AA)\n", - "\n", - " cv2.line(display, fltp(point0), fltp(point1),\n", - " (255, 255, 255), 1, cv2.LINE_AA)\n", - "\n", - " cv2.polylines(display, [norm2pix(small.shape, corners, True)],\n", - " True, (255, 255, 255))\n", - "\n", - " debug_show(name, 3, 'span points', display)\n", - "\n", - "\n", - "def imgsize(img):\n", - " height, width = img.shape[:2]\n", - " return '{}x{}'.format(width, height)\n", - "\n", - "\n", - "def make_keypoint_index(span_counts):\n", - "\n", - " nspans = len(span_counts)\n", - " npts = sum(span_counts)\n", - " keypoint_index = np.zeros((npts+1, 2), dtype=int)\n", - " start = 1\n", - "\n", - " for i, count in enumerate(span_counts):\n", - " end = start + count\n", - " keypoint_index[start:start+end, 1] = 8+i\n", - " start = end\n", - "\n", - " keypoint_index[1:, 0] = np.arange(npts) + 8 + nspans\n", - "\n", - " return keypoint_index\n", - "\n", - "\n", - "def optimize_params(name, small, dstpoints, span_counts, params):\n", - "\n", - " keypoint_index = make_keypoint_index(span_counts)\n", - "\n", - " def objective(pvec):\n", - " ppts = project_keypoints(pvec, keypoint_index)\n", - " return np.sum((dstpoints - ppts)**2)\n", - "\n", - " print ' initial objective is', objective(params)\n", - "\n", - " if DEBUG_LEVEL >= 1:\n", - " projpts = project_keypoints(params, keypoint_index)\n", - " display = draw_correspondences(small, dstpoints, projpts)\n", - " debug_show(name, 4, 'keypoints before', display)\n", - "\n", - " print ' optimizing', len(params), 'parameters...'\n", - " start = datetime.datetime.now()\n", - " res = scipy.optimize.minimize(objective, params,\n", - " method='Powell')\n", - " end = datetime.datetime.now()\n", - " print ' optimization took', round((end-start).total_seconds(), 2), 'sec.'\n", - " print ' final objective is', res.fun\n", - " params = res.x\n", - "\n", - " if DEBUG_LEVEL >= 1:\n", - " projpts = project_keypoints(params, keypoint_index)\n", - " display = draw_correspondences(small, dstpoints, projpts)\n", - " debug_show(name, 5, 'keypoints after', display)\n", - "\n", - " return params\n", - "\n", - "\n", - "def get_page_dims(corners, rough_dims, params):\n", - "\n", - " dst_br = corners[2].flatten()\n", - "\n", - " dims = np.array(rough_dims)\n", - "\n", - " def objective(dims):\n", - " proj_br = project_xy(dims, params)\n", - " return np.sum((dst_br - proj_br.flatten())**2)\n", - "\n", - " res = scipy.optimize.minimize(objective, dims, method='Powell')\n", - " dims = res.x\n", - "\n", - " print ' got page dims', dims[0], 'x', dims[1]\n", - "\n", - " return dims\n", - "\n", - "\n", - "def remap_image(name, img, small, page_dims, params):\n", - "\n", - " height = 0.5 * page_dims[1] * OUTPUT_ZOOM * img.shape[0]\n", - " height = round_nearest_multiple(height, REMAP_DECIMATE)\n", - "\n", - " width = round_nearest_multiple(height * page_dims[0] / page_dims[1],\n", - " REMAP_DECIMATE)\n", - "\n", - " print ' output will be {}x{}'.format(width, height)\n", - "\n", - " height_small = height / REMAP_DECIMATE\n", - " width_small = width / REMAP_DECIMATE\n", - "\n", - " page_x_range = np.linspace(0, page_dims[0], width_small)\n", - " page_y_range = np.linspace(0, page_dims[1], height_small)\n", - "\n", - " page_x_coords, page_y_coords = np.meshgrid(page_x_range, page_y_range)\n", - "\n", - " page_xy_coords = np.hstack((page_x_coords.flatten().reshape((-1, 1)),\n", - " page_y_coords.flatten().reshape((-1, 1))))\n", - "\n", - " page_xy_coords = page_xy_coords.astype(np.float32)\n", - "\n", - " image_points = project_xy(page_xy_coords, params)\n", - " image_points = norm2pix(img.shape, image_points, False)\n", - "\n", - " image_x_coords = image_points[:, 0, 0].reshape(page_x_coords.shape)\n", - " image_y_coords = image_points[:, 0, 1].reshape(page_y_coords.shape)\n", - "\n", - " image_x_coords = cv2.resize(image_x_coords, (width, height),\n", - " interpolation=cv2.INTER_CUBIC)\n", - "\n", - " image_y_coords = cv2.resize(image_y_coords, (width, height),\n", - " interpolation=cv2.INTER_CUBIC)\n", - "\n", - " img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n", - "\n", - " remapped = cv2.remap(img_gray, image_x_coords, image_y_coords,\n", - " cv2.INTER_CUBIC,\n", - " None, cv2.BORDER_REPLICATE)\n", - "\n", - " thresh = cv2.adaptiveThreshold(remapped, 255, cv2.ADAPTIVE_THRESH_MEAN_C,\n", - " cv2.THRESH_BINARY, ADAPTIVE_WINSZ, 25)\n", - "\n", - " pil_image = Image.fromarray(thresh)\n", - " pil_image = pil_image.convert('1')\n", - "\n", - " threshfile = name + '_thresh.png'\n", - " pil_image.save(threshfile, dpi=(OUTPUT_DPI, OUTPUT_DPI))\n", - "\n", - " if DEBUG_LEVEL >= 1:\n", - " height = small.shape[0]\n", - " width = int(round(height * float(thresh.shape[1])/thresh.shape[0]))\n", - " display = cv2.resize(thresh, (width, height),\n", - " interpolation=cv2.INTER_AREA)\n", - " debug_show(name, 6, 'output', display)\n", - "\n", - " return threshfile\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "PAGE_MARGIN_X = 0 # reduced px to ignore near L/R edge\n", - "PAGE_MARGIN_Y = 0 # reduced px to ignore near T/B edge\n", - "\n", - "\n", - "def get_page_extents(small):\n", - "\n", - " height, width = small.shape[:2]\n", - "\n", - " xmin = PAGE_MARGIN_X\n", - " ymin = PAGE_MARGIN_Y\n", - " xmax = width-PAGE_MARGIN_X\n", - " ymax = height-PAGE_MARGIN_Y\n", - "\n", - " page = np.zeros((height, width), dtype=np.uint8)\n", - " cv2.rectangle(page, (xmin, ymin), (xmax, ymax), (255, 255, 255), -1)\n", - "\n", - " outline = np.array([\n", - " [xmin, ymin],\n", - " [xmin, ymax],\n", - " [xmax, ymax],\n", - " [xmax, ymin]])\n", - "\n", - " return page, outline\n", - "\n", - "\n", - "def cubicsheetdewarp(image):\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def houghlineprocessing(image):\n", - " croppedanddeskewed, _ = mf.houghlinedeskewandcrop(image)\n", - " ##IF IT DOESN'T CHANGE THE IMAGE (CHANGE THE _ TO SOMETHING USEFUL), THEN CROPCLARIFYING SHOULD JUST DO THE TEXT ISOLATION SECTION AND NOT TRY AND WHITE OUT ANY BACKGROUND. \n", - " ## IF THERE'S NO CROPPING, MAYBE EVEN JUMP RIGHT TO USING THE EXTERNAL DESKEW FIRST BEFORE TOSSING IT INTO CROPCLARIFYING\n", - " \n", - " postprocessed = mf.cropclarifying(croppedanddeskewed)\n", - " # return postprocessed\n", - " \n", - " # dewarp here\n", - " postprocessed = cubicsheetdewarp(postprocessed)\n", - " \n", - " return postprocessed\n", - " \n", - " postprocessed = mf.croptoblack(postprocessed)\n", - " \n", - " postprocessed = cv2.cvtColor(postprocessed, cv2.COLOR_GRAY2BGR)\n", - " \n", - " final = mf.externaldeskew(postprocessed, fill=(255,255,255))\n", - " \n", - " # cv2.imshow(\"postprocessed\", mf.ResizeWithAspectRatio(postprocessed, 1000))\n", - " # cv2.imshow(\"final\", mf.ResizeWithAspectRatio(final, 1000))\n", - " # cv2.waitKey(0)\n", - " # cv2.destroyAllWindows()\n", - " \n", - " return final" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "out = houghlineprocessing(img)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "# cropped, rotangle = houghlinedeskewandcrop(img)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# _, angle = mf.houghlinedeskew(img, withangle=True)\n", - "# print(angle)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# if (abs(rotangle - angle) - 90 <= 5):\n", - "# print(\"hi\")q" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "cv2.imshow(\"result2\", mf.ResizeWithAspectRatio(out, height=1000))\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# prepped = mf.squareandthenresize(cropped, fill=255, width=1000)\n", - "# prepped, _ = mf.premorphCrop(prepped)\n", - "# prepped = mf.squareandthenresize(prepped, fill=255, width=1000)\n", - "# gray1 = cv2.cvtColor(prepped, cv2.COLOR_BGR2GRAY)\n", - "# dst1 = cv2.Canny(gray1, 0, 500, None, 3)\n", - "\n", - "# # cdstP = prepped.copy()\n", - "# # linesP = cv2.HoughLinesP(dst1, 1, np.pi / 180, 30, None, 90, 30)\n", - "# # if linesP is not None:\n", - "# # for i in range(0, len(linesP)):\n", - "# # l = linesP[i][0]\n", - "# # # anglesP[i] = mf.lineAngle(l)\n", - "# # cv2.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv2.LINE_AA)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imshow(\"result2\", dst1)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "### tasks. use contours to get the biggest contour and get a mask from it and then white out the external area. and then use thresholding or whatever to make the paper white. can try and get the mean colour of the paper area and then use that to autothreshold or something." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "# gray = cv2.cvtColor(cropped, cv2.COLOR_BGR2GRAY)\n", - "# thresh = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)[1]\n", - "# contours, heirarchy =cv2.findContours(thresh,cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)\n", - "# mx = (0,0,0,0)\n", - "# mx_area = 0\n", - "# for cont in contours:\n", - "# rect = cv2.boundingRect(cont)\n", - "# area = mf.rectArea(rect)\n", - "# if (area > mx_area):\n", - "# mx = rect\n", - "# mx_area = area\n", - "\n", - "# cropped = cv2.rectangle(cropped, (mx[0], mx[1]), (mx[0]+mx[2], mx[1]+mx[3]), (0,255,0), 3)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "# # # view result\n", - "# # # cv2.imshow(\"threshold\", thresh)\n", - "# # # cv2.imshow(\"morph\", morph)\n", - "# # # cv2.imshow(\"mask\", mask)\n", - "# # cv2.imshow(\"result1\", mf.ResizeWithAspectRatio(cdstP,height=1000))\n", - "# cv2.imshow(\"result2\", cropped)\n", - "# cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/autocropper/test_images/IMG_7594.jpg b/code/autocropper/test_images/IMG_7594.jpg deleted file mode 100644 index 79936e9..0000000 Binary files a/code/autocropper/test_images/IMG_7594.jpg and /dev/null differ diff --git a/code/autocropper/test_images/IMG_7604.jpg b/code/autocropper/test_images/IMG_7604.jpg deleted file mode 100644 index fc25bd5..0000000 Binary files a/code/autocropper/test_images/IMG_7604.jpg and /dev/null differ diff --git a/code/autocropper/test_images/IMG_7605.jpg b/code/autocropper/test_images/IMG_7605.jpg deleted file mode 100644 index b58854d..0000000 Binary files a/code/autocropper/test_images/IMG_7605.jpg and /dev/null differ diff --git a/code/autocropper/test_images/IMG_7640.jpg b/code/autocropper/test_images/IMG_7640.jpg deleted file mode 100644 index 5ac7648..0000000 Binary files a/code/autocropper/test_images/IMG_7640.jpg and /dev/null differ diff --git a/code/autocropper/test_images/IvV2y.png b/code/autocropper/test_images/IvV2y.png deleted file mode 100644 index a1bd714..0000000 Binary files a/code/autocropper/test_images/IvV2y.png and /dev/null differ diff --git a/code/externallibraries/stbimagehelpers/stb_image.h b/code/externallibraries/stbimagehelpers/stb_image.h deleted file mode 100644 index 5e807a0..0000000 --- a/code/externallibraries/stbimagehelpers/stb_image.h +++ /dev/null @@ -1,7987 +0,0 @@ -/* stb_image - v2.28 - public domain image loader - http://nothings.org/stb - no warranty implied; use at your own risk - - Do this: - #define STB_IMAGE_IMPLEMENTATION - before you include this file in *one* C or C++ file to create the implementation. - - // i.e. it should look like this: - #include ... - #include ... - #include ... - #define STB_IMAGE_IMPLEMENTATION - #include "stb_image.h" - - You can #define STBI_ASSERT(x) before the #include to avoid using assert.h. - And #define STBI_MALLOC, STBI_REALLOC, and STBI_FREE to avoid using malloc,realloc,free - - - QUICK NOTES: - Primarily of interest to game developers and other people who can - avoid problematic images and only need the trivial interface - - JPEG baseline & progressive (12 bpc/arithmetic not supported, same as stock IJG lib) - PNG 1/2/4/8/16-bit-per-channel - - TGA (not sure what subset, if a subset) - BMP non-1bpp, non-RLE - PSD (composited view only, no extra channels, 8/16 bit-per-channel) - - GIF (*comp always reports as 4-channel) - HDR (radiance rgbE format) - PIC (Softimage PIC) - PNM (PPM and PGM binary only) - - Animated GIF still needs a proper API, but here's one way to do it: - http://gist.github.com/urraka/685d9a6340b26b830d49 - - - decode from memory or through FILE (define STBI_NO_STDIO to remove code) - - decode from arbitrary I/O callbacks - - SIMD acceleration on x86/x64 (SSE2) and ARM (NEON) - - Full documentation under "DOCUMENTATION" below. - - -LICENSE - - See end of file for license information. - -RECENT REVISION HISTORY: - - 2.28 (2023-01-29) many error fixes, security errors, just tons of stuff - 2.27 (2021-07-11) document stbi_info better, 16-bit PNM support, bug fixes - 2.26 (2020-07-13) many minor fixes - 2.25 (2020-02-02) fix warnings - 2.24 (2020-02-02) fix warnings; thread-local failure_reason and flip_vertically - 2.23 (2019-08-11) fix clang static analysis warning - 2.22 (2019-03-04) gif fixes, fix warnings - 2.21 (2019-02-25) fix typo in comment - 2.20 (2019-02-07) support utf8 filenames in Windows; fix warnings and platform ifdefs - 2.19 (2018-02-11) fix warning - 2.18 (2018-01-30) fix warnings - 2.17 (2018-01-29) bugfix, 1-bit BMP, 16-bitness query, fix warnings - 2.16 (2017-07-23) all functions have 16-bit variants; optimizations; bugfixes - 2.15 (2017-03-18) fix png-1,2,4; all Imagenet JPGs; no runtime SSE detection on GCC - 2.14 (2017-03-03) remove deprecated STBI_JPEG_OLD; fixes for Imagenet JPGs - 2.13 (2016-12-04) experimental 16-bit API, only for PNG so far; fixes - 2.12 (2016-04-02) fix typo in 2.11 PSD fix that caused crashes - 2.11 (2016-04-02) 16-bit PNGS; enable SSE2 in non-gcc x64 - RGB-format JPEG; remove white matting in PSD; - allocate large structures on the stack; - correct channel count for PNG & BMP - 2.10 (2016-01-22) avoid warning introduced in 2.09 - 2.09 (2016-01-16) 16-bit TGA; comments in PNM files; STBI_REALLOC_SIZED - - See end of file for full revision history. - - - ============================ Contributors ========================= - - Image formats Extensions, features - Sean Barrett (jpeg, png, bmp) Jetro Lauha (stbi_info) - Nicolas Schulz (hdr, psd) Martin "SpartanJ" Golini (stbi_info) - Jonathan Dummer (tga) James "moose2000" Brown (iPhone PNG) - Jean-Marc Lienher (gif) Ben "Disch" Wenger (io callbacks) - Tom Seddon (pic) Omar Cornut (1/2/4-bit PNG) - Thatcher Ulrich (psd) Nicolas Guillemot (vertical flip) - Ken Miller (pgm, ppm) Richard Mitton (16-bit PSD) - github:urraka (animated gif) Junggon Kim (PNM comments) - Christopher Forseth (animated gif) Daniel Gibson (16-bit TGA) - socks-the-fox (16-bit PNG) - Jeremy Sawicki (handle all ImageNet JPGs) - Optimizations & bugfixes Mikhail Morozov (1-bit BMP) - Fabian "ryg" Giesen Anael Seghezzi (is-16-bit query) - Arseny Kapoulkine Simon Breuss (16-bit PNM) - John-Mark Allen - Carmelo J Fdez-Aguera - - Bug & warning fixes - Marc LeBlanc David Woo Guillaume George Martins Mozeiko - Christpher Lloyd Jerry Jansson Joseph Thomson Blazej Dariusz Roszkowski - Phil Jordan Dave Moore Roy Eltham - Hayaki Saito Nathan Reed Won Chun - Luke Graham Johan Duparc Nick Verigakis the Horde3D community - Thomas Ruf Ronny Chevalier github:rlyeh - Janez Zemva John Bartholomew Michal Cichon github:romigrou - Jonathan Blow Ken Hamada Tero Hanninen github:svdijk - Eugene Golushkov Laurent Gomila Cort Stratton github:snagar - Aruelien Pocheville Sergio Gonzalez Thibault Reuille github:Zelex - Cass Everitt Ryamond Barbiero github:grim210 - Paul Du Bois Engin Manap Aldo Culquicondor github:sammyhw - Philipp Wiesemann Dale Weiler Oriol Ferrer Mesia github:phprus - Josh Tobin Neil Bickford Matthew Gregan github:poppolopoppo - Julian Raschke Gregory Mullen Christian Floisand github:darealshinji - Baldur Karlsson Kevin Schmidt JR Smith github:Michaelangel007 - Brad Weinberger Matvey Cherevko github:mosra - Luca Sas Alexander Veselov Zack Middleton [reserved] - Ryan C. Gordon [reserved] [reserved] - DO NOT ADD YOUR NAME HERE - - Jacko Dirks - - To add your name to the credits, pick a random blank space in the middle and fill it. - 80% of merge conflicts on stb PRs are due to people adding their name at the end - of the credits. -*/ - -#ifndef STBI_INCLUDE_STB_IMAGE_H -#define STBI_INCLUDE_STB_IMAGE_H - -// DOCUMENTATION -// -// Limitations: -// - no 12-bit-per-channel JPEG -// - no JPEGs with arithmetic coding -// - GIF always returns *comp=4 -// -// Basic usage (see HDR discussion below for HDR usage): -// int x,y,n; -// unsigned char *data = stbi_load(filename, &x, &y, &n, 0); -// // ... process data if not NULL ... -// // ... x = width, y = height, n = # 8-bit components per pixel ... -// // ... replace '0' with '1'..'4' to force that many components per pixel -// // ... but 'n' will always be the number that it would have been if you said 0 -// stbi_image_free(data); -// -// Standard parameters: -// int *x -- outputs image width in pixels -// int *y -- outputs image height in pixels -// int *channels_in_file -- outputs # of image components in image file -// int desired_channels -- if non-zero, # of image components requested in result -// -// The return value from an image loader is an 'unsigned char *' which points -// to the pixel data, or NULL on an allocation failure or if the image is -// corrupt or invalid. The pixel data consists of *y scanlines of *x pixels, -// with each pixel consisting of N interleaved 8-bit components; the first -// pixel pointed to is top-left-most in the image. There is no padding between -// image scanlines or between pixels, regardless of format. The number of -// components N is 'desired_channels' if desired_channels is non-zero, or -// *channels_in_file otherwise. If desired_channels is non-zero, -// *channels_in_file has the number of components that _would_ have been -// output otherwise. E.g. if you set desired_channels to 4, you will always -// get RGBA output, but you can check *channels_in_file to see if it's trivially -// opaque because e.g. there were only 3 channels in the source image. -// -// An output image with N components has the following components interleaved -// in this order in each pixel: -// -// N=#comp components -// 1 grey -// 2 grey, alpha -// 3 red, green, blue -// 4 red, green, blue, alpha -// -// If image loading fails for any reason, the return value will be NULL, -// and *x, *y, *channels_in_file will be unchanged. The function -// stbi_failure_reason() can be queried for an extremely brief, end-user -// unfriendly explanation of why the load failed. Define STBI_NO_FAILURE_STRINGS -// to avoid compiling these strings at all, and STBI_FAILURE_USERMSG to get slightly -// more user-friendly ones. -// -// Paletted PNG, BMP, GIF, and PIC images are automatically depalettized. -// -// To query the width, height and component count of an image without having to -// decode the full file, you can use the stbi_info family of functions: -// -// int x,y,n,ok; -// ok = stbi_info(filename, &x, &y, &n); -// // returns ok=1 and sets x, y, n if image is a supported format, -// // 0 otherwise. -// -// Note that stb_image pervasively uses ints in its public API for sizes, -// including sizes of memory buffers. This is now part of the API and thus -// hard to change without causing breakage. As a result, the various image -// loaders all have certain limits on image size; these differ somewhat -// by format but generally boil down to either just under 2GB or just under -// 1GB. When the decoded image would be larger than this, stb_image decoding -// will fail. -// -// Additionally, stb_image will reject image files that have any of their -// dimensions set to a larger value than the configurable STBI_MAX_DIMENSIONS, -// which defaults to 2**24 = 16777216 pixels. Due to the above memory limit, -// the only way to have an image with such dimensions load correctly -// is for it to have a rather extreme aspect ratio. Either way, the -// assumption here is that such larger images are likely to be malformed -// or malicious. If you do need to load an image with individual dimensions -// larger than that, and it still fits in the overall size limit, you can -// #define STBI_MAX_DIMENSIONS on your own to be something larger. -// -// =========================================================================== -// -// UNICODE: -// -// If compiling for Windows and you wish to use Unicode filenames, compile -// with -// #define STBI_WINDOWS_UTF8 -// and pass utf8-encoded filenames. Call stbi_convert_wchar_to_utf8 to convert -// Windows wchar_t filenames to utf8. -// -// =========================================================================== -// -// Philosophy -// -// stb libraries are designed with the following priorities: -// -// 1. easy to use -// 2. easy to maintain -// 3. good performance -// -// Sometimes I let "good performance" creep up in priority over "easy to maintain", -// and for best performance I may provide less-easy-to-use APIs that give higher -// performance, in addition to the easy-to-use ones. Nevertheless, it's important -// to keep in mind that from the standpoint of you, a client of this library, -// all you care about is #1 and #3, and stb libraries DO NOT emphasize #3 above all. -// -// Some secondary priorities arise directly from the first two, some of which -// provide more explicit reasons why performance can't be emphasized. -// -// - Portable ("ease of use") -// - Small source code footprint ("easy to maintain") -// - No dependencies ("ease of use") -// -// =========================================================================== -// -// I/O callbacks -// -// I/O callbacks allow you to read from arbitrary sources, like packaged -// files or some other source. Data read from callbacks are processed -// through a small internal buffer (currently 128 bytes) to try to reduce -// overhead. -// -// The three functions you must define are "read" (reads some bytes of data), -// "skip" (skips some bytes of data), "eof" (reports if the stream is at the end). -// -// =========================================================================== -// -// SIMD support -// -// The JPEG decoder will try to automatically use SIMD kernels on x86 when -// supported by the compiler. For ARM Neon support, you must explicitly -// request it. -// -// (The old do-it-yourself SIMD API is no longer supported in the current -// code.) -// -// On x86, SSE2 will automatically be used when available based on a run-time -// test; if not, the generic C versions are used as a fall-back. On ARM targets, -// the typical path is to have separate builds for NEON and non-NEON devices -// (at least this is true for iOS and Android). Therefore, the NEON support is -// toggled by a build flag: define STBI_NEON to get NEON loops. -// -// If for some reason you do not want to use any of SIMD code, or if -// you have issues compiling it, you can disable it entirely by -// defining STBI_NO_SIMD. -// -// =========================================================================== -// -// HDR image support (disable by defining STBI_NO_HDR) -// -// stb_image supports loading HDR images in general, and currently the Radiance -// .HDR file format specifically. You can still load any file through the existing -// interface; if you attempt to load an HDR file, it will be automatically remapped -// to LDR, assuming gamma 2.2 and an arbitrary scale factor defaulting to 1; -// both of these constants can be reconfigured through this interface: -// -// stbi_hdr_to_ldr_gamma(2.2f); -// stbi_hdr_to_ldr_scale(1.0f); -// -// (note, do not use _inverse_ constants; stbi_image will invert them -// appropriately). -// -// Additionally, there is a new, parallel interface for loading files as -// (linear) floats to preserve the full dynamic range: -// -// float *data = stbi_loadf(filename, &x, &y, &n, 0); -// -// If you load LDR images through this interface, those images will -// be promoted to floating point values, run through the inverse of -// constants corresponding to the above: -// -// stbi_ldr_to_hdr_scale(1.0f); -// stbi_ldr_to_hdr_gamma(2.2f); -// -// Finally, given a filename (or an open file or memory block--see header -// file for details) containing image data, you can query for the "most -// appropriate" interface to use (that is, whether the image is HDR or -// not), using: -// -// stbi_is_hdr(char *filename); -// -// =========================================================================== -// -// iPhone PNG support: -// -// We optionally support converting iPhone-formatted PNGs (which store -// premultiplied BGRA) back to RGB, even though they're internally encoded -// differently. To enable this conversion, call -// stbi_convert_iphone_png_to_rgb(1). -// -// Call stbi_set_unpremultiply_on_load(1) as well to force a divide per -// pixel to remove any premultiplied alpha *only* if the image file explicitly -// says there's premultiplied data (currently only happens in iPhone images, -// and only if iPhone convert-to-rgb processing is on). -// -// =========================================================================== -// -// ADDITIONAL CONFIGURATION -// -// - You can suppress implementation of any of the decoders to reduce -// your code footprint by #defining one or more of the following -// symbols before creating the implementation. -// -// STBI_NO_JPEG -// STBI_NO_PNG -// STBI_NO_BMP -// STBI_NO_PSD -// STBI_NO_TGA -// STBI_NO_GIF -// STBI_NO_HDR -// STBI_NO_PIC -// STBI_NO_PNM (.ppm and .pgm) -// -// - You can request *only* certain decoders and suppress all other ones -// (this will be more forward-compatible, as addition of new decoders -// doesn't require you to disable them explicitly): -// -// STBI_ONLY_JPEG -// STBI_ONLY_PNG -// STBI_ONLY_BMP -// STBI_ONLY_PSD -// STBI_ONLY_TGA -// STBI_ONLY_GIF -// STBI_ONLY_HDR -// STBI_ONLY_PIC -// STBI_ONLY_PNM (.ppm and .pgm) -// -// - If you use STBI_NO_PNG (or _ONLY_ without PNG), and you still -// want the zlib decoder to be available, #define STBI_SUPPORT_ZLIB -// -// - If you define STBI_MAX_DIMENSIONS, stb_image will reject images greater -// than that size (in either width or height) without further processing. -// This is to let programs in the wild set an upper bound to prevent -// denial-of-service attacks on untrusted data, as one could generate a -// valid image of gigantic dimensions and force stb_image to allocate a -// huge block of memory and spend disproportionate time decoding it. By -// default this is set to (1 << 24), which is 16777216, but that's still -// very big. - -#ifndef STBI_NO_STDIO -#include -#endif // STBI_NO_STDIO - -#define STBI_VERSION 1 - -enum -{ - STBI_default = 0, // only used for desired_channels - - STBI_grey = 1, - STBI_grey_alpha = 2, - STBI_rgb = 3, - STBI_rgb_alpha = 4 -}; - -#include -typedef unsigned char stbi_uc; -typedef unsigned short stbi_us; - -#ifdef __cplusplus -extern "C" { -#endif - -#ifndef STBIDEF -#ifdef STB_IMAGE_STATIC -#define STBIDEF static -#else -#define STBIDEF extern -#endif -#endif - -////////////////////////////////////////////////////////////////////////////// -// -// PRIMARY API - works on images of any type -// - -// -// load image by filename, open file, or memory buffer -// - -typedef struct -{ - int (*read) (void *user,char *data,int size); // fill 'data' with 'size' bytes. return number of bytes actually read - void (*skip) (void *user,int n); // skip the next 'n' bytes, or 'unget' the last -n bytes if negative - int (*eof) (void *user); // returns nonzero if we are at end of file/data -} stbi_io_callbacks; - -//////////////////////////////////// -// -// 8-bits-per-channel interface -// - -STBIDEF stbi_uc *stbi_load_from_memory (stbi_uc const *buffer, int len , int *x, int *y, int *channels_in_file, int desired_channels); -STBIDEF stbi_uc *stbi_load_from_callbacks(stbi_io_callbacks const *clbk , void *user, int *x, int *y, int *channels_in_file, int desired_channels); - -#ifndef STBI_NO_STDIO -STBIDEF stbi_uc *stbi_load (char const *filename, int *x, int *y, int *channels_in_file, int desired_channels); -STBIDEF stbi_uc *stbi_load_from_file (FILE *f, int *x, int *y, int *channels_in_file, int desired_channels); -// for stbi_load_from_file, file pointer is left pointing immediately after image -#endif - -#ifndef STBI_NO_GIF -STBIDEF stbi_uc *stbi_load_gif_from_memory(stbi_uc const *buffer, int len, int **delays, int *x, int *y, int *z, int *comp, int req_comp); -#endif - -#ifdef STBI_WINDOWS_UTF8 -STBIDEF int stbi_convert_wchar_to_utf8(char *buffer, size_t bufferlen, const wchar_t* input); -#endif - -//////////////////////////////////// -// -// 16-bits-per-channel interface -// - -STBIDEF stbi_us *stbi_load_16_from_memory (stbi_uc const *buffer, int len, int *x, int *y, int *channels_in_file, int desired_channels); -STBIDEF stbi_us *stbi_load_16_from_callbacks(stbi_io_callbacks const *clbk, void *user, int *x, int *y, int *channels_in_file, int desired_channels); - -#ifndef STBI_NO_STDIO -STBIDEF stbi_us *stbi_load_16 (char const *filename, int *x, int *y, int *channels_in_file, int desired_channels); -STBIDEF stbi_us *stbi_load_from_file_16(FILE *f, int *x, int *y, int *channels_in_file, int desired_channels); -#endif - -//////////////////////////////////// -// -// float-per-channel interface -// -#ifndef STBI_NO_LINEAR - STBIDEF float *stbi_loadf_from_memory (stbi_uc const *buffer, int len, int *x, int *y, int *channels_in_file, int desired_channels); - STBIDEF float *stbi_loadf_from_callbacks (stbi_io_callbacks const *clbk, void *user, int *x, int *y, int *channels_in_file, int desired_channels); - - #ifndef STBI_NO_STDIO - STBIDEF float *stbi_loadf (char const *filename, int *x, int *y, int *channels_in_file, int desired_channels); - STBIDEF float *stbi_loadf_from_file (FILE *f, int *x, int *y, int *channels_in_file, int desired_channels); - #endif -#endif - -#ifndef STBI_NO_HDR - STBIDEF void stbi_hdr_to_ldr_gamma(float gamma); - STBIDEF void stbi_hdr_to_ldr_scale(float scale); -#endif // STBI_NO_HDR - -#ifndef STBI_NO_LINEAR - STBIDEF void stbi_ldr_to_hdr_gamma(float gamma); - STBIDEF void stbi_ldr_to_hdr_scale(float scale); -#endif // STBI_NO_LINEAR - -// stbi_is_hdr is always defined, but always returns false if STBI_NO_HDR -STBIDEF int stbi_is_hdr_from_callbacks(stbi_io_callbacks const *clbk, void *user); -STBIDEF int stbi_is_hdr_from_memory(stbi_uc const *buffer, int len); -#ifndef STBI_NO_STDIO -STBIDEF int stbi_is_hdr (char const *filename); -STBIDEF int stbi_is_hdr_from_file(FILE *f); -#endif // STBI_NO_STDIO - - -// get a VERY brief reason for failure -// on most compilers (and ALL modern mainstream compilers) this is threadsafe -STBIDEF const char *stbi_failure_reason (void); - -// free the loaded image -- this is just free() -STBIDEF void stbi_image_free (void *retval_from_stbi_load); - -// get image dimensions & components without fully decoding -STBIDEF int stbi_info_from_memory(stbi_uc const *buffer, int len, int *x, int *y, int *comp); -STBIDEF int stbi_info_from_callbacks(stbi_io_callbacks const *clbk, void *user, int *x, int *y, int *comp); -STBIDEF int stbi_is_16_bit_from_memory(stbi_uc const *buffer, int len); -STBIDEF int stbi_is_16_bit_from_callbacks(stbi_io_callbacks const *clbk, void *user); - -#ifndef STBI_NO_STDIO -STBIDEF int stbi_info (char const *filename, int *x, int *y, int *comp); -STBIDEF int stbi_info_from_file (FILE *f, int *x, int *y, int *comp); -STBIDEF int stbi_is_16_bit (char const *filename); -STBIDEF int stbi_is_16_bit_from_file(FILE *f); -#endif - - - -// for image formats that explicitly notate that they have premultiplied alpha, -// we just return the colors as stored in the file. set this flag to force -// unpremultiplication. results are undefined if the unpremultiply overflow. -STBIDEF void stbi_set_unpremultiply_on_load(int flag_true_if_should_unpremultiply); - -// indicate whether we should process iphone images back to canonical format, -// or just pass them through "as-is" -STBIDEF void stbi_convert_iphone_png_to_rgb(int flag_true_if_should_convert); - -// flip the image vertically, so the first pixel in the output array is the bottom left -STBIDEF void stbi_set_flip_vertically_on_load(int flag_true_if_should_flip); - -// as above, but only applies to images loaded on the thread that calls the function -// this function is only available if your compiler supports thread-local variables; -// calling it will fail to link if your compiler doesn't -STBIDEF void stbi_set_unpremultiply_on_load_thread(int flag_true_if_should_unpremultiply); -STBIDEF void stbi_convert_iphone_png_to_rgb_thread(int flag_true_if_should_convert); -STBIDEF void stbi_set_flip_vertically_on_load_thread(int flag_true_if_should_flip); - -// ZLIB client - used by PNG, available for other purposes - -STBIDEF char *stbi_zlib_decode_malloc_guesssize(const char *buffer, int len, int initial_size, int *outlen); -STBIDEF char *stbi_zlib_decode_malloc_guesssize_headerflag(const char *buffer, int len, int initial_size, int *outlen, int parse_header); -STBIDEF char *stbi_zlib_decode_malloc(const char *buffer, int len, int *outlen); -STBIDEF int stbi_zlib_decode_buffer(char *obuffer, int olen, const char *ibuffer, int ilen); - -STBIDEF char *stbi_zlib_decode_noheader_malloc(const char *buffer, int len, int *outlen); -STBIDEF int stbi_zlib_decode_noheader_buffer(char *obuffer, int olen, const char *ibuffer, int ilen); - - -#ifdef __cplusplus -} -#endif - -// -// -//// end header file ///////////////////////////////////////////////////// -#endif // STBI_INCLUDE_STB_IMAGE_H - -#ifdef STB_IMAGE_IMPLEMENTATION - -#if defined(STBI_ONLY_JPEG) || defined(STBI_ONLY_PNG) || defined(STBI_ONLY_BMP) \ - || defined(STBI_ONLY_TGA) || defined(STBI_ONLY_GIF) || defined(STBI_ONLY_PSD) \ - || defined(STBI_ONLY_HDR) || defined(STBI_ONLY_PIC) || defined(STBI_ONLY_PNM) \ - || defined(STBI_ONLY_ZLIB) - #ifndef STBI_ONLY_JPEG - #define STBI_NO_JPEG - #endif - #ifndef STBI_ONLY_PNG - #define STBI_NO_PNG - #endif - #ifndef STBI_ONLY_BMP - #define STBI_NO_BMP - #endif - #ifndef STBI_ONLY_PSD - #define STBI_NO_PSD - #endif - #ifndef STBI_ONLY_TGA - #define STBI_NO_TGA - #endif - #ifndef STBI_ONLY_GIF - #define STBI_NO_GIF - #endif - #ifndef STBI_ONLY_HDR - #define STBI_NO_HDR - #endif - #ifndef STBI_ONLY_PIC - #define STBI_NO_PIC - #endif - #ifndef STBI_ONLY_PNM - #define STBI_NO_PNM - #endif -#endif - -#if defined(STBI_NO_PNG) && !defined(STBI_SUPPORT_ZLIB) && !defined(STBI_NO_ZLIB) -#define STBI_NO_ZLIB -#endif - - -#include -#include // ptrdiff_t on osx -#include -#include -#include - -#if !defined(STBI_NO_LINEAR) || !defined(STBI_NO_HDR) -#include // ldexp, pow -#endif - -#ifndef STBI_NO_STDIO -#include -#endif - -#ifndef STBI_ASSERT -#include -#define STBI_ASSERT(x) assert(x) -#endif - -#ifdef __cplusplus -#define STBI_EXTERN extern "C" -#else -#define STBI_EXTERN extern -#endif - - -#ifndef _MSC_VER - #ifdef __cplusplus - #define stbi_inline inline - #else - #define stbi_inline - #endif -#else - #define stbi_inline __forceinline -#endif - -#ifndef STBI_NO_THREAD_LOCALS - #if defined(__cplusplus) && __cplusplus >= 201103L - #define STBI_THREAD_LOCAL thread_local - #elif defined(__GNUC__) && __GNUC__ < 5 - #define STBI_THREAD_LOCAL __thread - #elif defined(_MSC_VER) - #define STBI_THREAD_LOCAL __declspec(thread) - #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 201112L && !defined(__STDC_NO_THREADS__) - #define STBI_THREAD_LOCAL _Thread_local - #endif - - #ifndef STBI_THREAD_LOCAL - #if defined(__GNUC__) - #define STBI_THREAD_LOCAL __thread - #endif - #endif -#endif - -#if defined(_MSC_VER) || defined(__SYMBIAN32__) -typedef unsigned short stbi__uint16; -typedef signed short stbi__int16; -typedef unsigned int stbi__uint32; -typedef signed int stbi__int32; -#else -#include -typedef uint16_t stbi__uint16; -typedef int16_t stbi__int16; -typedef uint32_t stbi__uint32; -typedef int32_t stbi__int32; -#endif - -// should produce compiler error if size is wrong -typedef unsigned char validate_uint32[sizeof(stbi__uint32)==4 ? 1 : -1]; - -#ifdef _MSC_VER -#define STBI_NOTUSED(v) (void)(v) -#else -#define STBI_NOTUSED(v) (void)sizeof(v) -#endif - -#ifdef _MSC_VER -#define STBI_HAS_LROTL -#endif - -#ifdef STBI_HAS_LROTL - #define stbi_lrot(x,y) _lrotl(x,y) -#else - #define stbi_lrot(x,y) (((x) << (y)) | ((x) >> (-(y) & 31))) -#endif - -#if defined(STBI_MALLOC) && defined(STBI_FREE) && (defined(STBI_REALLOC) || defined(STBI_REALLOC_SIZED)) -// ok -#elif !defined(STBI_MALLOC) && !defined(STBI_FREE) && !defined(STBI_REALLOC) && !defined(STBI_REALLOC_SIZED) -// ok -#else -#error "Must define all or none of STBI_MALLOC, STBI_FREE, and STBI_REALLOC (or STBI_REALLOC_SIZED)." -#endif - -#ifndef STBI_MALLOC -#define STBI_MALLOC(sz) malloc(sz) -#define STBI_REALLOC(p,newsz) realloc(p,newsz) -#define STBI_FREE(p) free(p) -#endif - -#ifndef STBI_REALLOC_SIZED -#define STBI_REALLOC_SIZED(p,oldsz,newsz) STBI_REALLOC(p,newsz) -#endif - -// x86/x64 detection -#if defined(__x86_64__) || defined(_M_X64) -#define STBI__X64_TARGET -#elif defined(__i386) || defined(_M_IX86) -#define STBI__X86_TARGET -#endif - -#if defined(__GNUC__) && defined(STBI__X86_TARGET) && !defined(__SSE2__) && !defined(STBI_NO_SIMD) -// gcc doesn't support sse2 intrinsics unless you compile with -msse2, -// which in turn means it gets to use SSE2 everywhere. This is unfortunate, -// but previous attempts to provide the SSE2 functions with runtime -// detection caused numerous issues. The way architecture extensions are -// exposed in GCC/Clang is, sadly, not really suited for one-file libs. -// New behavior: if compiled with -msse2, we use SSE2 without any -// detection; if not, we don't use it at all. -#define STBI_NO_SIMD -#endif - -#if defined(__MINGW32__) && defined(STBI__X86_TARGET) && !defined(STBI_MINGW_ENABLE_SSE2) && !defined(STBI_NO_SIMD) -// Note that __MINGW32__ doesn't actually mean 32-bit, so we have to avoid STBI__X64_TARGET -// -// 32-bit MinGW wants ESP to be 16-byte aligned, but this is not in the -// Windows ABI and VC++ as well as Windows DLLs don't maintain that invariant. -// As a result, enabling SSE2 on 32-bit MinGW is dangerous when not -// simultaneously enabling "-mstackrealign". -// -// See https://github.com/nothings/stb/issues/81 for more information. -// -// So default to no SSE2 on 32-bit MinGW. If you've read this far and added -// -mstackrealign to your build settings, feel free to #define STBI_MINGW_ENABLE_SSE2. -#define STBI_NO_SIMD -#endif - -#if !defined(STBI_NO_SIMD) && (defined(STBI__X86_TARGET) || defined(STBI__X64_TARGET)) -#define STBI_SSE2 -#include - -#ifdef _MSC_VER - -#if _MSC_VER >= 1400 // not VC6 -#include // __cpuid -static int stbi__cpuid3(void) -{ - int info[4]; - __cpuid(info,1); - return info[3]; -} -#else -static int stbi__cpuid3(void) -{ - int res; - __asm { - mov eax,1 - cpuid - mov res,edx - } - return res; -} -#endif - -#define STBI_SIMD_ALIGN(type, name) __declspec(align(16)) type name - -#if !defined(STBI_NO_JPEG) && defined(STBI_SSE2) -static int stbi__sse2_available(void) -{ - int info3 = stbi__cpuid3(); - return ((info3 >> 26) & 1) != 0; -} -#endif - -#else // assume GCC-style if not VC++ -#define STBI_SIMD_ALIGN(type, name) type name __attribute__((aligned(16))) - -#if !defined(STBI_NO_JPEG) && defined(STBI_SSE2) -static int stbi__sse2_available(void) -{ - // If we're even attempting to compile this on GCC/Clang, that means - // -msse2 is on, which means the compiler is allowed to use SSE2 - // instructions at will, and so are we. - return 1; -} -#endif - -#endif -#endif - -// ARM NEON -#if defined(STBI_NO_SIMD) && defined(STBI_NEON) -#undef STBI_NEON -#endif - -#ifdef STBI_NEON -#include -#ifdef _MSC_VER -#define STBI_SIMD_ALIGN(type, name) __declspec(align(16)) type name -#else -#define STBI_SIMD_ALIGN(type, name) type name __attribute__((aligned(16))) -#endif -#endif - -#ifndef STBI_SIMD_ALIGN -#define STBI_SIMD_ALIGN(type, name) type name -#endif - -#ifndef STBI_MAX_DIMENSIONS -#define STBI_MAX_DIMENSIONS (1 << 24) -#endif - -/////////////////////////////////////////////// -// -// stbi__context struct and start_xxx functions - -// stbi__context structure is our basic context used by all images, so it -// contains all the IO context, plus some basic image information -typedef struct -{ - stbi__uint32 img_x, img_y; - int img_n, img_out_n; - - stbi_io_callbacks io; - void *io_user_data; - - int read_from_callbacks; - int buflen; - stbi_uc buffer_start[128]; - int callback_already_read; - - stbi_uc *img_buffer, *img_buffer_end; - stbi_uc *img_buffer_original, *img_buffer_original_end; -} stbi__context; - - -static void stbi__refill_buffer(stbi__context *s); - -// initialize a memory-decode context -static void stbi__start_mem(stbi__context *s, stbi_uc const *buffer, int len) -{ - s->io.read = NULL; - s->read_from_callbacks = 0; - s->callback_already_read = 0; - s->img_buffer = s->img_buffer_original = (stbi_uc *) buffer; - s->img_buffer_end = s->img_buffer_original_end = (stbi_uc *) buffer+len; -} - -// initialize a callback-based context -static void stbi__start_callbacks(stbi__context *s, stbi_io_callbacks *c, void *user) -{ - s->io = *c; - s->io_user_data = user; - s->buflen = sizeof(s->buffer_start); - s->read_from_callbacks = 1; - s->callback_already_read = 0; - s->img_buffer = s->img_buffer_original = s->buffer_start; - stbi__refill_buffer(s); - s->img_buffer_original_end = s->img_buffer_end; -} - -#ifndef STBI_NO_STDIO - -static int stbi__stdio_read(void *user, char *data, int size) -{ - return (int) fread(data,1,size,(FILE*) user); -} - -static void stbi__stdio_skip(void *user, int n) -{ - int ch; - fseek((FILE*) user, n, SEEK_CUR); - ch = fgetc((FILE*) user); /* have to read a byte to reset feof()'s flag */ - if (ch != EOF) { - ungetc(ch, (FILE *) user); /* push byte back onto stream if valid. */ - } -} - -static int stbi__stdio_eof(void *user) -{ - return feof((FILE*) user) || ferror((FILE *) user); -} - -static stbi_io_callbacks stbi__stdio_callbacks = -{ - stbi__stdio_read, - stbi__stdio_skip, - stbi__stdio_eof, -}; - -static void stbi__start_file(stbi__context *s, FILE *f) -{ - stbi__start_callbacks(s, &stbi__stdio_callbacks, (void *) f); -} - -//static void stop_file(stbi__context *s) { } - -#endif // !STBI_NO_STDIO - -static void stbi__rewind(stbi__context *s) -{ - // conceptually rewind SHOULD rewind to the beginning of the stream, - // but we just rewind to the beginning of the initial buffer, because - // we only use it after doing 'test', which only ever looks at at most 92 bytes - s->img_buffer = s->img_buffer_original; - s->img_buffer_end = s->img_buffer_original_end; -} - -enum -{ - STBI_ORDER_RGB, - STBI_ORDER_BGR -}; - -typedef struct -{ - int bits_per_channel; - int num_channels; - int channel_order; -} stbi__result_info; - -#ifndef STBI_NO_JPEG -static int stbi__jpeg_test(stbi__context *s); -static void *stbi__jpeg_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__jpeg_info(stbi__context *s, int *x, int *y, int *comp); -#endif - -#ifndef STBI_NO_PNG -static int stbi__png_test(stbi__context *s); -static void *stbi__png_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__png_info(stbi__context *s, int *x, int *y, int *comp); -static int stbi__png_is16(stbi__context *s); -#endif - -#ifndef STBI_NO_BMP -static int stbi__bmp_test(stbi__context *s); -static void *stbi__bmp_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__bmp_info(stbi__context *s, int *x, int *y, int *comp); -#endif - -#ifndef STBI_NO_TGA -static int stbi__tga_test(stbi__context *s); -static void *stbi__tga_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__tga_info(stbi__context *s, int *x, int *y, int *comp); -#endif - -#ifndef STBI_NO_PSD -static int stbi__psd_test(stbi__context *s); -static void *stbi__psd_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri, int bpc); -static int stbi__psd_info(stbi__context *s, int *x, int *y, int *comp); -static int stbi__psd_is16(stbi__context *s); -#endif - -#ifndef STBI_NO_HDR -static int stbi__hdr_test(stbi__context *s); -static float *stbi__hdr_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__hdr_info(stbi__context *s, int *x, int *y, int *comp); -#endif - -#ifndef STBI_NO_PIC -static int stbi__pic_test(stbi__context *s); -static void *stbi__pic_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__pic_info(stbi__context *s, int *x, int *y, int *comp); -#endif - -#ifndef STBI_NO_GIF -static int stbi__gif_test(stbi__context *s); -static void *stbi__gif_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static void *stbi__load_gif_main(stbi__context *s, int **delays, int *x, int *y, int *z, int *comp, int req_comp); -static int stbi__gif_info(stbi__context *s, int *x, int *y, int *comp); -#endif - -#ifndef STBI_NO_PNM -static int stbi__pnm_test(stbi__context *s); -static void *stbi__pnm_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri); -static int stbi__pnm_info(stbi__context *s, int *x, int *y, int *comp); -static int stbi__pnm_is16(stbi__context *s); -#endif - -static -#ifdef STBI_THREAD_LOCAL -STBI_THREAD_LOCAL -#endif -const char *stbi__g_failure_reason; - -STBIDEF const char *stbi_failure_reason(void) -{ - return stbi__g_failure_reason; -} - -#ifndef STBI_NO_FAILURE_STRINGS -static int stbi__err(const char *str) -{ - stbi__g_failure_reason = str; - return 0; -} -#endif - -static void *stbi__malloc(size_t size) -{ - return STBI_MALLOC(size); -} - -// stb_image uses ints pervasively, including for offset calculations. -// therefore the largest decoded image size we can support with the -// current code, even on 64-bit targets, is INT_MAX. this is not a -// significant limitation for the intended use case. -// -// we do, however, need to make sure our size calculations don't -// overflow. hence a few helper functions for size calculations that -// multiply integers together, making sure that they're non-negative -// and no overflow occurs. - -// return 1 if the sum is valid, 0 on overflow. -// negative terms are considered invalid. -static int stbi__addsizes_valid(int a, int b) -{ - if (b < 0) return 0; - // now 0 <= b <= INT_MAX, hence also - // 0 <= INT_MAX - b <= INTMAX. - // And "a + b <= INT_MAX" (which might overflow) is the - // same as a <= INT_MAX - b (no overflow) - return a <= INT_MAX - b; -} - -// returns 1 if the product is valid, 0 on overflow. -// negative factors are considered invalid. -static int stbi__mul2sizes_valid(int a, int b) -{ - if (a < 0 || b < 0) return 0; - if (b == 0) return 1; // mul-by-0 is always safe - // portable way to check for no overflows in a*b - return a <= INT_MAX/b; -} - -#if !defined(STBI_NO_JPEG) || !defined(STBI_NO_PNG) || !defined(STBI_NO_TGA) || !defined(STBI_NO_HDR) -// returns 1 if "a*b + add" has no negative terms/factors and doesn't overflow -static int stbi__mad2sizes_valid(int a, int b, int add) -{ - return stbi__mul2sizes_valid(a, b) && stbi__addsizes_valid(a*b, add); -} -#endif - -// returns 1 if "a*b*c + add" has no negative terms/factors and doesn't overflow -static int stbi__mad3sizes_valid(int a, int b, int c, int add) -{ - return stbi__mul2sizes_valid(a, b) && stbi__mul2sizes_valid(a*b, c) && - stbi__addsizes_valid(a*b*c, add); -} - -// returns 1 if "a*b*c*d + add" has no negative terms/factors and doesn't overflow -#if !defined(STBI_NO_LINEAR) || !defined(STBI_NO_HDR) || !defined(STBI_NO_PNM) -static int stbi__mad4sizes_valid(int a, int b, int c, int d, int add) -{ - return stbi__mul2sizes_valid(a, b) && stbi__mul2sizes_valid(a*b, c) && - stbi__mul2sizes_valid(a*b*c, d) && stbi__addsizes_valid(a*b*c*d, add); -} -#endif - -#if !defined(STBI_NO_JPEG) || !defined(STBI_NO_PNG) || !defined(STBI_NO_TGA) || !defined(STBI_NO_HDR) -// mallocs with size overflow checking -static void *stbi__malloc_mad2(int a, int b, int add) -{ - if (!stbi__mad2sizes_valid(a, b, add)) return NULL; - return stbi__malloc(a*b + add); -} -#endif - -static void *stbi__malloc_mad3(int a, int b, int c, int add) -{ - if (!stbi__mad3sizes_valid(a, b, c, add)) return NULL; - return stbi__malloc(a*b*c + add); -} - -#if !defined(STBI_NO_LINEAR) || !defined(STBI_NO_HDR) || !defined(STBI_NO_PNM) -static void *stbi__malloc_mad4(int a, int b, int c, int d, int add) -{ - if (!stbi__mad4sizes_valid(a, b, c, d, add)) return NULL; - return stbi__malloc(a*b*c*d + add); -} -#endif - -// returns 1 if the sum of two signed ints is valid (between -2^31 and 2^31-1 inclusive), 0 on overflow. -static int stbi__addints_valid(int a, int b) -{ - if ((a >= 0) != (b >= 0)) return 1; // a and b have different signs, so no overflow - if (a < 0 && b < 0) return a >= INT_MIN - b; // same as a + b >= INT_MIN; INT_MIN - b cannot overflow since b < 0. - return a <= INT_MAX - b; -} - -// returns 1 if the product of two signed shorts is valid, 0 on overflow. -static int stbi__mul2shorts_valid(short a, short b) -{ - if (b == 0 || b == -1) return 1; // multiplication by 0 is always 0; check for -1 so SHRT_MIN/b doesn't overflow - if ((a >= 0) == (b >= 0)) return a <= SHRT_MAX/b; // product is positive, so similar to mul2sizes_valid - if (b < 0) return a <= SHRT_MIN / b; // same as a * b >= SHRT_MIN - return a >= SHRT_MIN / b; -} - -// stbi__err - error -// stbi__errpf - error returning pointer to float -// stbi__errpuc - error returning pointer to unsigned char - -#ifdef STBI_NO_FAILURE_STRINGS - #define stbi__err(x,y) 0 -#elif defined(STBI_FAILURE_USERMSG) - #define stbi__err(x,y) stbi__err(y) -#else - #define stbi__err(x,y) stbi__err(x) -#endif - -#define stbi__errpf(x,y) ((float *)(size_t) (stbi__err(x,y)?NULL:NULL)) -#define stbi__errpuc(x,y) ((unsigned char *)(size_t) (stbi__err(x,y)?NULL:NULL)) - -STBIDEF void stbi_image_free(void *retval_from_stbi_load) -{ - STBI_FREE(retval_from_stbi_load); -} - -#ifndef STBI_NO_LINEAR -static float *stbi__ldr_to_hdr(stbi_uc *data, int x, int y, int comp); -#endif - -#ifndef STBI_NO_HDR -static stbi_uc *stbi__hdr_to_ldr(float *data, int x, int y, int comp); -#endif - -static int stbi__vertically_flip_on_load_global = 0; - -STBIDEF void stbi_set_flip_vertically_on_load(int flag_true_if_should_flip) -{ - stbi__vertically_flip_on_load_global = flag_true_if_should_flip; -} - -#ifndef STBI_THREAD_LOCAL -#define stbi__vertically_flip_on_load stbi__vertically_flip_on_load_global -#else -static STBI_THREAD_LOCAL int stbi__vertically_flip_on_load_local, stbi__vertically_flip_on_load_set; - -STBIDEF void stbi_set_flip_vertically_on_load_thread(int flag_true_if_should_flip) -{ - stbi__vertically_flip_on_load_local = flag_true_if_should_flip; - stbi__vertically_flip_on_load_set = 1; -} - -#define stbi__vertically_flip_on_load (stbi__vertically_flip_on_load_set \ - ? stbi__vertically_flip_on_load_local \ - : stbi__vertically_flip_on_load_global) -#endif // STBI_THREAD_LOCAL - -static void *stbi__load_main(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri, int bpc) -{ - memset(ri, 0, sizeof(*ri)); // make sure it's initialized if we add new fields - ri->bits_per_channel = 8; // default is 8 so most paths don't have to be changed - ri->channel_order = STBI_ORDER_RGB; // all current input & output are this, but this is here so we can add BGR order - ri->num_channels = 0; - - // test the formats with a very explicit header first (at least a FOURCC - // or distinctive magic number first) - #ifndef STBI_NO_PNG - if (stbi__png_test(s)) return stbi__png_load(s,x,y,comp,req_comp, ri); - #endif - #ifndef STBI_NO_BMP - if (stbi__bmp_test(s)) return stbi__bmp_load(s,x,y,comp,req_comp, ri); - #endif - #ifndef STBI_NO_GIF - if (stbi__gif_test(s)) return stbi__gif_load(s,x,y,comp,req_comp, ri); - #endif - #ifndef STBI_NO_PSD - if (stbi__psd_test(s)) return stbi__psd_load(s,x,y,comp,req_comp, ri, bpc); - #else - STBI_NOTUSED(bpc); - #endif - #ifndef STBI_NO_PIC - if (stbi__pic_test(s)) return stbi__pic_load(s,x,y,comp,req_comp, ri); - #endif - - // then the formats that can end up attempting to load with just 1 or 2 - // bytes matching expectations; these are prone to false positives, so - // try them later - #ifndef STBI_NO_JPEG - if (stbi__jpeg_test(s)) return stbi__jpeg_load(s,x,y,comp,req_comp, ri); - #endif - #ifndef STBI_NO_PNM - if (stbi__pnm_test(s)) return stbi__pnm_load(s,x,y,comp,req_comp, ri); - #endif - - #ifndef STBI_NO_HDR - if (stbi__hdr_test(s)) { - float *hdr = stbi__hdr_load(s, x,y,comp,req_comp, ri); - return stbi__hdr_to_ldr(hdr, *x, *y, req_comp ? req_comp : *comp); - } - #endif - - #ifndef STBI_NO_TGA - // test tga last because it's a crappy test! - if (stbi__tga_test(s)) - return stbi__tga_load(s,x,y,comp,req_comp, ri); - #endif - - return stbi__errpuc("unknown image type", "Image not of any known type, or corrupt"); -} - -static stbi_uc *stbi__convert_16_to_8(stbi__uint16 *orig, int w, int h, int channels) -{ - int i; - int img_len = w * h * channels; - stbi_uc *reduced; - - reduced = (stbi_uc *) stbi__malloc(img_len); - if (reduced == NULL) return stbi__errpuc("outofmem", "Out of memory"); - - for (i = 0; i < img_len; ++i) - reduced[i] = (stbi_uc)((orig[i] >> 8) & 0xFF); // top half of each byte is sufficient approx of 16->8 bit scaling - - STBI_FREE(orig); - return reduced; -} - -static stbi__uint16 *stbi__convert_8_to_16(stbi_uc *orig, int w, int h, int channels) -{ - int i; - int img_len = w * h * channels; - stbi__uint16 *enlarged; - - enlarged = (stbi__uint16 *) stbi__malloc(img_len*2); - if (enlarged == NULL) return (stbi__uint16 *) stbi__errpuc("outofmem", "Out of memory"); - - for (i = 0; i < img_len; ++i) - enlarged[i] = (stbi__uint16)((orig[i] << 8) + orig[i]); // replicate to high and low byte, maps 0->0, 255->0xffff - - STBI_FREE(orig); - return enlarged; -} - -static void stbi__vertical_flip(void *image, int w, int h, int bytes_per_pixel) -{ - int row; - size_t bytes_per_row = (size_t)w * bytes_per_pixel; - stbi_uc temp[2048]; - stbi_uc *bytes = (stbi_uc *)image; - - for (row = 0; row < (h>>1); row++) { - stbi_uc *row0 = bytes + row*bytes_per_row; - stbi_uc *row1 = bytes + (h - row - 1)*bytes_per_row; - // swap row0 with row1 - size_t bytes_left = bytes_per_row; - while (bytes_left) { - size_t bytes_copy = (bytes_left < sizeof(temp)) ? bytes_left : sizeof(temp); - memcpy(temp, row0, bytes_copy); - memcpy(row0, row1, bytes_copy); - memcpy(row1, temp, bytes_copy); - row0 += bytes_copy; - row1 += bytes_copy; - bytes_left -= bytes_copy; - } - } -} - -#ifndef STBI_NO_GIF -static void stbi__vertical_flip_slices(void *image, int w, int h, int z, int bytes_per_pixel) -{ - int slice; - int slice_size = w * h * bytes_per_pixel; - - stbi_uc *bytes = (stbi_uc *)image; - for (slice = 0; slice < z; ++slice) { - stbi__vertical_flip(bytes, w, h, bytes_per_pixel); - bytes += slice_size; - } -} -#endif - -static unsigned char *stbi__load_and_postprocess_8bit(stbi__context *s, int *x, int *y, int *comp, int req_comp) -{ - stbi__result_info ri; - void *result = stbi__load_main(s, x, y, comp, req_comp, &ri, 8); - - if (result == NULL) - return NULL; - - // it is the responsibility of the loaders to make sure we get either 8 or 16 bit. - STBI_ASSERT(ri.bits_per_channel == 8 || ri.bits_per_channel == 16); - - if (ri.bits_per_channel != 8) { - result = stbi__convert_16_to_8((stbi__uint16 *) result, *x, *y, req_comp == 0 ? *comp : req_comp); - ri.bits_per_channel = 8; - } - - // @TODO: move stbi__convert_format to here - - if (stbi__vertically_flip_on_load) { - int channels = req_comp ? req_comp : *comp; - stbi__vertical_flip(result, *x, *y, channels * sizeof(stbi_uc)); - } - - return (unsigned char *) result; -} - -static stbi__uint16 *stbi__load_and_postprocess_16bit(stbi__context *s, int *x, int *y, int *comp, int req_comp) -{ - stbi__result_info ri; - void *result = stbi__load_main(s, x, y, comp, req_comp, &ri, 16); - - if (result == NULL) - return NULL; - - // it is the responsibility of the loaders to make sure we get either 8 or 16 bit. - STBI_ASSERT(ri.bits_per_channel == 8 || ri.bits_per_channel == 16); - - if (ri.bits_per_channel != 16) { - result = stbi__convert_8_to_16((stbi_uc *) result, *x, *y, req_comp == 0 ? *comp : req_comp); - ri.bits_per_channel = 16; - } - - // @TODO: move stbi__convert_format16 to here - // @TODO: special case RGB-to-Y (and RGBA-to-YA) for 8-bit-to-16-bit case to keep more precision - - if (stbi__vertically_flip_on_load) { - int channels = req_comp ? req_comp : *comp; - stbi__vertical_flip(result, *x, *y, channels * sizeof(stbi__uint16)); - } - - return (stbi__uint16 *) result; -} - -#if !defined(STBI_NO_HDR) && !defined(STBI_NO_LINEAR) -static void stbi__float_postprocess(float *result, int *x, int *y, int *comp, int req_comp) -{ - if (stbi__vertically_flip_on_load && result != NULL) { - int channels = req_comp ? req_comp : *comp; - stbi__vertical_flip(result, *x, *y, channels * sizeof(float)); - } -} -#endif - -#ifndef STBI_NO_STDIO - -#if defined(_WIN32) && defined(STBI_WINDOWS_UTF8) -STBI_EXTERN __declspec(dllimport) int __stdcall MultiByteToWideChar(unsigned int cp, unsigned long flags, const char *str, int cbmb, wchar_t *widestr, int cchwide); -STBI_EXTERN __declspec(dllimport) int __stdcall WideCharToMultiByte(unsigned int cp, unsigned long flags, const wchar_t *widestr, int cchwide, char *str, int cbmb, const char *defchar, int *used_default); -#endif - -#if defined(_WIN32) && defined(STBI_WINDOWS_UTF8) -STBIDEF int stbi_convert_wchar_to_utf8(char *buffer, size_t bufferlen, const wchar_t* input) -{ - return WideCharToMultiByte(65001 /* UTF8 */, 0, input, -1, buffer, (int) bufferlen, NULL, NULL); -} -#endif - -static FILE *stbi__fopen(char const *filename, char const *mode) -{ - FILE *f; -#if defined(_WIN32) && defined(STBI_WINDOWS_UTF8) - wchar_t wMode[64]; - wchar_t wFilename[1024]; - if (0 == MultiByteToWideChar(65001 /* UTF8 */, 0, filename, -1, wFilename, sizeof(wFilename)/sizeof(*wFilename))) - return 0; - - if (0 == MultiByteToWideChar(65001 /* UTF8 */, 0, mode, -1, wMode, sizeof(wMode)/sizeof(*wMode))) - return 0; - -#if defined(_MSC_VER) && _MSC_VER >= 1400 - if (0 != _wfopen_s(&f, wFilename, wMode)) - f = 0; -#else - f = _wfopen(wFilename, wMode); -#endif - -#elif defined(_MSC_VER) && _MSC_VER >= 1400 - if (0 != fopen_s(&f, filename, mode)) - f=0; -#else - f = fopen(filename, mode); -#endif - return f; -} - - -STBIDEF stbi_uc *stbi_load(char const *filename, int *x, int *y, int *comp, int req_comp) -{ - FILE *f = stbi__fopen(filename, "rb"); - unsigned char *result; - if (!f) return stbi__errpuc("can't fopen", "Unable to open file"); - result = stbi_load_from_file(f,x,y,comp,req_comp); - fclose(f); - return result; -} - -STBIDEF stbi_uc *stbi_load_from_file(FILE *f, int *x, int *y, int *comp, int req_comp) -{ - unsigned char *result; - stbi__context s; - stbi__start_file(&s,f); - result = stbi__load_and_postprocess_8bit(&s,x,y,comp,req_comp); - if (result) { - // need to 'unget' all the characters in the IO buffer - fseek(f, - (int) (s.img_buffer_end - s.img_buffer), SEEK_CUR); - } - return result; -} - -STBIDEF stbi__uint16 *stbi_load_from_file_16(FILE *f, int *x, int *y, int *comp, int req_comp) -{ - stbi__uint16 *result; - stbi__context s; - stbi__start_file(&s,f); - result = stbi__load_and_postprocess_16bit(&s,x,y,comp,req_comp); - if (result) { - // need to 'unget' all the characters in the IO buffer - fseek(f, - (int) (s.img_buffer_end - s.img_buffer), SEEK_CUR); - } - return result; -} - -STBIDEF stbi_us *stbi_load_16(char const *filename, int *x, int *y, int *comp, int req_comp) -{ - FILE *f = stbi__fopen(filename, "rb"); - stbi__uint16 *result; - if (!f) return (stbi_us *) stbi__errpuc("can't fopen", "Unable to open file"); - result = stbi_load_from_file_16(f,x,y,comp,req_comp); - fclose(f); - return result; -} - - -#endif //!STBI_NO_STDIO - -STBIDEF stbi_us *stbi_load_16_from_memory(stbi_uc const *buffer, int len, int *x, int *y, int *channels_in_file, int desired_channels) -{ - stbi__context s; - stbi__start_mem(&s,buffer,len); - return stbi__load_and_postprocess_16bit(&s,x,y,channels_in_file,desired_channels); -} - -STBIDEF stbi_us *stbi_load_16_from_callbacks(stbi_io_callbacks const *clbk, void *user, int *x, int *y, int *channels_in_file, int desired_channels) -{ - stbi__context s; - stbi__start_callbacks(&s, (stbi_io_callbacks *)clbk, user); - return stbi__load_and_postprocess_16bit(&s,x,y,channels_in_file,desired_channels); -} - -STBIDEF stbi_uc *stbi_load_from_memory(stbi_uc const *buffer, int len, int *x, int *y, int *comp, int req_comp) -{ - stbi__context s; - stbi__start_mem(&s,buffer,len); - return stbi__load_and_postprocess_8bit(&s,x,y,comp,req_comp); -} - -STBIDEF stbi_uc *stbi_load_from_callbacks(stbi_io_callbacks const *clbk, void *user, int *x, int *y, int *comp, int req_comp) -{ - stbi__context s; - stbi__start_callbacks(&s, (stbi_io_callbacks *) clbk, user); - return stbi__load_and_postprocess_8bit(&s,x,y,comp,req_comp); -} - -#ifndef STBI_NO_GIF -STBIDEF stbi_uc *stbi_load_gif_from_memory(stbi_uc const *buffer, int len, int **delays, int *x, int *y, int *z, int *comp, int req_comp) -{ - unsigned char *result; - stbi__context s; - stbi__start_mem(&s,buffer,len); - - result = (unsigned char*) stbi__load_gif_main(&s, delays, x, y, z, comp, req_comp); - if (stbi__vertically_flip_on_load) { - stbi__vertical_flip_slices( result, *x, *y, *z, *comp ); - } - - return result; -} -#endif - -#ifndef STBI_NO_LINEAR -static float *stbi__loadf_main(stbi__context *s, int *x, int *y, int *comp, int req_comp) -{ - unsigned char *data; - #ifndef STBI_NO_HDR - if (stbi__hdr_test(s)) { - stbi__result_info ri; - float *hdr_data = stbi__hdr_load(s,x,y,comp,req_comp, &ri); - if (hdr_data) - stbi__float_postprocess(hdr_data,x,y,comp,req_comp); - return hdr_data; - } - #endif - data = stbi__load_and_postprocess_8bit(s, x, y, comp, req_comp); - if (data) - return stbi__ldr_to_hdr(data, *x, *y, req_comp ? req_comp : *comp); - return stbi__errpf("unknown image type", "Image not of any known type, or corrupt"); -} - -STBIDEF float *stbi_loadf_from_memory(stbi_uc const *buffer, int len, int *x, int *y, int *comp, int req_comp) -{ - stbi__context s; - stbi__start_mem(&s,buffer,len); - return stbi__loadf_main(&s,x,y,comp,req_comp); -} - -STBIDEF float *stbi_loadf_from_callbacks(stbi_io_callbacks const *clbk, void *user, int *x, int *y, int *comp, int req_comp) -{ - stbi__context s; - stbi__start_callbacks(&s, (stbi_io_callbacks *) clbk, user); - return stbi__loadf_main(&s,x,y,comp,req_comp); -} - -#ifndef STBI_NO_STDIO -STBIDEF float *stbi_loadf(char const *filename, int *x, int *y, int *comp, int req_comp) -{ - float *result; - FILE *f = stbi__fopen(filename, "rb"); - if (!f) return stbi__errpf("can't fopen", "Unable to open file"); - result = stbi_loadf_from_file(f,x,y,comp,req_comp); - fclose(f); - return result; -} - -STBIDEF float *stbi_loadf_from_file(FILE *f, int *x, int *y, int *comp, int req_comp) -{ - stbi__context s; - stbi__start_file(&s,f); - return stbi__loadf_main(&s,x,y,comp,req_comp); -} -#endif // !STBI_NO_STDIO - -#endif // !STBI_NO_LINEAR - -// these is-hdr-or-not is defined independent of whether STBI_NO_LINEAR is -// defined, for API simplicity; if STBI_NO_LINEAR is defined, it always -// reports false! - -STBIDEF int stbi_is_hdr_from_memory(stbi_uc const *buffer, int len) -{ - #ifndef STBI_NO_HDR - stbi__context s; - stbi__start_mem(&s,buffer,len); - return stbi__hdr_test(&s); - #else - STBI_NOTUSED(buffer); - STBI_NOTUSED(len); - return 0; - #endif -} - -#ifndef STBI_NO_STDIO -STBIDEF int stbi_is_hdr (char const *filename) -{ - FILE *f = stbi__fopen(filename, "rb"); - int result=0; - if (f) { - result = stbi_is_hdr_from_file(f); - fclose(f); - } - return result; -} - -STBIDEF int stbi_is_hdr_from_file(FILE *f) -{ - #ifndef STBI_NO_HDR - long pos = ftell(f); - int res; - stbi__context s; - stbi__start_file(&s,f); - res = stbi__hdr_test(&s); - fseek(f, pos, SEEK_SET); - return res; - #else - STBI_NOTUSED(f); - return 0; - #endif -} -#endif // !STBI_NO_STDIO - -STBIDEF int stbi_is_hdr_from_callbacks(stbi_io_callbacks const *clbk, void *user) -{ - #ifndef STBI_NO_HDR - stbi__context s; - stbi__start_callbacks(&s, (stbi_io_callbacks *) clbk, user); - return stbi__hdr_test(&s); - #else - STBI_NOTUSED(clbk); - STBI_NOTUSED(user); - return 0; - #endif -} - -#ifndef STBI_NO_LINEAR -static float stbi__l2h_gamma=2.2f, stbi__l2h_scale=1.0f; - -STBIDEF void stbi_ldr_to_hdr_gamma(float gamma) { stbi__l2h_gamma = gamma; } -STBIDEF void stbi_ldr_to_hdr_scale(float scale) { stbi__l2h_scale = scale; } -#endif - -static float stbi__h2l_gamma_i=1.0f/2.2f, stbi__h2l_scale_i=1.0f; - -STBIDEF void stbi_hdr_to_ldr_gamma(float gamma) { stbi__h2l_gamma_i = 1/gamma; } -STBIDEF void stbi_hdr_to_ldr_scale(float scale) { stbi__h2l_scale_i = 1/scale; } - - -////////////////////////////////////////////////////////////////////////////// -// -// Common code used by all image loaders -// - -enum -{ - STBI__SCAN_load=0, - STBI__SCAN_type, - STBI__SCAN_header -}; - -static void stbi__refill_buffer(stbi__context *s) -{ - int n = (s->io.read)(s->io_user_data,(char*)s->buffer_start,s->buflen); - s->callback_already_read += (int) (s->img_buffer - s->img_buffer_original); - if (n == 0) { - // at end of file, treat same as if from memory, but need to handle case - // where s->img_buffer isn't pointing to safe memory, e.g. 0-byte file - s->read_from_callbacks = 0; - s->img_buffer = s->buffer_start; - s->img_buffer_end = s->buffer_start+1; - *s->img_buffer = 0; - } else { - s->img_buffer = s->buffer_start; - s->img_buffer_end = s->buffer_start + n; - } -} - -stbi_inline static stbi_uc stbi__get8(stbi__context *s) -{ - if (s->img_buffer < s->img_buffer_end) - return *s->img_buffer++; - if (s->read_from_callbacks) { - stbi__refill_buffer(s); - return *s->img_buffer++; - } - return 0; -} - -#if defined(STBI_NO_JPEG) && defined(STBI_NO_HDR) && defined(STBI_NO_PIC) && defined(STBI_NO_PNM) -// nothing -#else -stbi_inline static int stbi__at_eof(stbi__context *s) -{ - if (s->io.read) { - if (!(s->io.eof)(s->io_user_data)) return 0; - // if feof() is true, check if buffer = end - // special case: we've only got the special 0 character at the end - if (s->read_from_callbacks == 0) return 1; - } - - return s->img_buffer >= s->img_buffer_end; -} -#endif - -#if defined(STBI_NO_JPEG) && defined(STBI_NO_PNG) && defined(STBI_NO_BMP) && defined(STBI_NO_PSD) && defined(STBI_NO_TGA) && defined(STBI_NO_GIF) && defined(STBI_NO_PIC) -// nothing -#else -static void stbi__skip(stbi__context *s, int n) -{ - if (n == 0) return; // already there! - if (n < 0) { - s->img_buffer = s->img_buffer_end; - return; - } - if (s->io.read) { - int blen = (int) (s->img_buffer_end - s->img_buffer); - if (blen < n) { - s->img_buffer = s->img_buffer_end; - (s->io.skip)(s->io_user_data, n - blen); - return; - } - } - s->img_buffer += n; -} -#endif - -#if defined(STBI_NO_PNG) && defined(STBI_NO_TGA) && defined(STBI_NO_HDR) && defined(STBI_NO_PNM) -// nothing -#else -static int stbi__getn(stbi__context *s, stbi_uc *buffer, int n) -{ - if (s->io.read) { - int blen = (int) (s->img_buffer_end - s->img_buffer); - if (blen < n) { - int res, count; - - memcpy(buffer, s->img_buffer, blen); - - count = (s->io.read)(s->io_user_data, (char*) buffer + blen, n - blen); - res = (count == (n-blen)); - s->img_buffer = s->img_buffer_end; - return res; - } - } - - if (s->img_buffer+n <= s->img_buffer_end) { - memcpy(buffer, s->img_buffer, n); - s->img_buffer += n; - return 1; - } else - return 0; -} -#endif - -#if defined(STBI_NO_JPEG) && defined(STBI_NO_PNG) && defined(STBI_NO_PSD) && defined(STBI_NO_PIC) -// nothing -#else -static int stbi__get16be(stbi__context *s) -{ - int z = stbi__get8(s); - return (z << 8) + stbi__get8(s); -} -#endif - -#if defined(STBI_NO_PNG) && defined(STBI_NO_PSD) && defined(STBI_NO_PIC) -// nothing -#else -static stbi__uint32 stbi__get32be(stbi__context *s) -{ - stbi__uint32 z = stbi__get16be(s); - return (z << 16) + stbi__get16be(s); -} -#endif - -#if defined(STBI_NO_BMP) && defined(STBI_NO_TGA) && defined(STBI_NO_GIF) -// nothing -#else -static int stbi__get16le(stbi__context *s) -{ - int z = stbi__get8(s); - return z + (stbi__get8(s) << 8); -} -#endif - -#ifndef STBI_NO_BMP -static stbi__uint32 stbi__get32le(stbi__context *s) -{ - stbi__uint32 z = stbi__get16le(s); - z += (stbi__uint32)stbi__get16le(s) << 16; - return z; -} -#endif - -#define STBI__BYTECAST(x) ((stbi_uc) ((x) & 255)) // truncate int to byte without warnings - -#if defined(STBI_NO_JPEG) && defined(STBI_NO_PNG) && defined(STBI_NO_BMP) && defined(STBI_NO_PSD) && defined(STBI_NO_TGA) && defined(STBI_NO_GIF) && defined(STBI_NO_PIC) && defined(STBI_NO_PNM) -// nothing -#else -////////////////////////////////////////////////////////////////////////////// -// -// generic converter from built-in img_n to req_comp -// individual types do this automatically as much as possible (e.g. jpeg -// does all cases internally since it needs to colorspace convert anyway, -// and it never has alpha, so very few cases ). png can automatically -// interleave an alpha=255 channel, but falls back to this for other cases -// -// assume data buffer is malloced, so malloc a new one and free that one -// only failure mode is malloc failing - -static stbi_uc stbi__compute_y(int r, int g, int b) -{ - return (stbi_uc) (((r*77) + (g*150) + (29*b)) >> 8); -} -#endif - -#if defined(STBI_NO_PNG) && defined(STBI_NO_BMP) && defined(STBI_NO_PSD) && defined(STBI_NO_TGA) && defined(STBI_NO_GIF) && defined(STBI_NO_PIC) && defined(STBI_NO_PNM) -// nothing -#else -static unsigned char *stbi__convert_format(unsigned char *data, int img_n, int req_comp, unsigned int x, unsigned int y) -{ - int i,j; - unsigned char *good; - - if (req_comp == img_n) return data; - STBI_ASSERT(req_comp >= 1 && req_comp <= 4); - - good = (unsigned char *) stbi__malloc_mad3(req_comp, x, y, 0); - if (good == NULL) { - STBI_FREE(data); - return stbi__errpuc("outofmem", "Out of memory"); - } - - for (j=0; j < (int) y; ++j) { - unsigned char *src = data + j * x * img_n ; - unsigned char *dest = good + j * x * req_comp; - - #define STBI__COMBO(a,b) ((a)*8+(b)) - #define STBI__CASE(a,b) case STBI__COMBO(a,b): for(i=x-1; i >= 0; --i, src += a, dest += b) - // convert source image with img_n components to one with req_comp components; - // avoid switch per pixel, so use switch per scanline and massive macros - switch (STBI__COMBO(img_n, req_comp)) { - STBI__CASE(1,2) { dest[0]=src[0]; dest[1]=255; } break; - STBI__CASE(1,3) { dest[0]=dest[1]=dest[2]=src[0]; } break; - STBI__CASE(1,4) { dest[0]=dest[1]=dest[2]=src[0]; dest[3]=255; } break; - STBI__CASE(2,1) { dest[0]=src[0]; } break; - STBI__CASE(2,3) { dest[0]=dest[1]=dest[2]=src[0]; } break; - STBI__CASE(2,4) { dest[0]=dest[1]=dest[2]=src[0]; dest[3]=src[1]; } break; - STBI__CASE(3,4) { dest[0]=src[0];dest[1]=src[1];dest[2]=src[2];dest[3]=255; } break; - STBI__CASE(3,1) { dest[0]=stbi__compute_y(src[0],src[1],src[2]); } break; - STBI__CASE(3,2) { dest[0]=stbi__compute_y(src[0],src[1],src[2]); dest[1] = 255; } break; - STBI__CASE(4,1) { dest[0]=stbi__compute_y(src[0],src[1],src[2]); } break; - STBI__CASE(4,2) { dest[0]=stbi__compute_y(src[0],src[1],src[2]); dest[1] = src[3]; } break; - STBI__CASE(4,3) { dest[0]=src[0];dest[1]=src[1];dest[2]=src[2]; } break; - default: STBI_ASSERT(0); STBI_FREE(data); STBI_FREE(good); return stbi__errpuc("unsupported", "Unsupported format conversion"); - } - #undef STBI__CASE - } - - STBI_FREE(data); - return good; -} -#endif - -#if defined(STBI_NO_PNG) && defined(STBI_NO_PSD) -// nothing -#else -static stbi__uint16 stbi__compute_y_16(int r, int g, int b) -{ - return (stbi__uint16) (((r*77) + (g*150) + (29*b)) >> 8); -} -#endif - -#if defined(STBI_NO_PNG) && defined(STBI_NO_PSD) -// nothing -#else -static stbi__uint16 *stbi__convert_format16(stbi__uint16 *data, int img_n, int req_comp, unsigned int x, unsigned int y) -{ - int i,j; - stbi__uint16 *good; - - if (req_comp == img_n) return data; - STBI_ASSERT(req_comp >= 1 && req_comp <= 4); - - good = (stbi__uint16 *) stbi__malloc(req_comp * x * y * 2); - if (good == NULL) { - STBI_FREE(data); - return (stbi__uint16 *) stbi__errpuc("outofmem", "Out of memory"); - } - - for (j=0; j < (int) y; ++j) { - stbi__uint16 *src = data + j * x * img_n ; - stbi__uint16 *dest = good + j * x * req_comp; - - #define STBI__COMBO(a,b) ((a)*8+(b)) - #define STBI__CASE(a,b) case STBI__COMBO(a,b): for(i=x-1; i >= 0; --i, src += a, dest += b) - // convert source image with img_n components to one with req_comp components; - // avoid switch per pixel, so use switch per scanline and massive macros - switch (STBI__COMBO(img_n, req_comp)) { - STBI__CASE(1,2) { dest[0]=src[0]; dest[1]=0xffff; } break; - STBI__CASE(1,3) { dest[0]=dest[1]=dest[2]=src[0]; } break; - STBI__CASE(1,4) { dest[0]=dest[1]=dest[2]=src[0]; dest[3]=0xffff; } break; - STBI__CASE(2,1) { dest[0]=src[0]; } break; - STBI__CASE(2,3) { dest[0]=dest[1]=dest[2]=src[0]; } break; - STBI__CASE(2,4) { dest[0]=dest[1]=dest[2]=src[0]; dest[3]=src[1]; } break; - STBI__CASE(3,4) { dest[0]=src[0];dest[1]=src[1];dest[2]=src[2];dest[3]=0xffff; } break; - STBI__CASE(3,1) { dest[0]=stbi__compute_y_16(src[0],src[1],src[2]); } break; - STBI__CASE(3,2) { dest[0]=stbi__compute_y_16(src[0],src[1],src[2]); dest[1] = 0xffff; } break; - STBI__CASE(4,1) { dest[0]=stbi__compute_y_16(src[0],src[1],src[2]); } break; - STBI__CASE(4,2) { dest[0]=stbi__compute_y_16(src[0],src[1],src[2]); dest[1] = src[3]; } break; - STBI__CASE(4,3) { dest[0]=src[0];dest[1]=src[1];dest[2]=src[2]; } break; - default: STBI_ASSERT(0); STBI_FREE(data); STBI_FREE(good); return (stbi__uint16*) stbi__errpuc("unsupported", "Unsupported format conversion"); - } - #undef STBI__CASE - } - - STBI_FREE(data); - return good; -} -#endif - -#ifndef STBI_NO_LINEAR -static float *stbi__ldr_to_hdr(stbi_uc *data, int x, int y, int comp) -{ - int i,k,n; - float *output; - if (!data) return NULL; - output = (float *) stbi__malloc_mad4(x, y, comp, sizeof(float), 0); - if (output == NULL) { STBI_FREE(data); return stbi__errpf("outofmem", "Out of memory"); } - // compute number of non-alpha components - if (comp & 1) n = comp; else n = comp-1; - for (i=0; i < x*y; ++i) { - for (k=0; k < n; ++k) { - output[i*comp + k] = (float) (pow(data[i*comp+k]/255.0f, stbi__l2h_gamma) * stbi__l2h_scale); - } - } - if (n < comp) { - for (i=0; i < x*y; ++i) { - output[i*comp + n] = data[i*comp + n]/255.0f; - } - } - STBI_FREE(data); - return output; -} -#endif - -#ifndef STBI_NO_HDR -#define stbi__float2int(x) ((int) (x)) -static stbi_uc *stbi__hdr_to_ldr(float *data, int x, int y, int comp) -{ - int i,k,n; - stbi_uc *output; - if (!data) return NULL; - output = (stbi_uc *) stbi__malloc_mad3(x, y, comp, 0); - if (output == NULL) { STBI_FREE(data); return stbi__errpuc("outofmem", "Out of memory"); } - // compute number of non-alpha components - if (comp & 1) n = comp; else n = comp-1; - for (i=0; i < x*y; ++i) { - for (k=0; k < n; ++k) { - float z = (float) pow(data[i*comp+k]*stbi__h2l_scale_i, stbi__h2l_gamma_i) * 255 + 0.5f; - if (z < 0) z = 0; - if (z > 255) z = 255; - output[i*comp + k] = (stbi_uc) stbi__float2int(z); - } - if (k < comp) { - float z = data[i*comp+k] * 255 + 0.5f; - if (z < 0) z = 0; - if (z > 255) z = 255; - output[i*comp + k] = (stbi_uc) stbi__float2int(z); - } - } - STBI_FREE(data); - return output; -} -#endif - -////////////////////////////////////////////////////////////////////////////// -// -// "baseline" JPEG/JFIF decoder -// -// simple implementation -// - doesn't support delayed output of y-dimension -// - simple interface (only one output format: 8-bit interleaved RGB) -// - doesn't try to recover corrupt jpegs -// - doesn't allow partial loading, loading multiple at once -// - still fast on x86 (copying globals into locals doesn't help x86) -// - allocates lots of intermediate memory (full size of all components) -// - non-interleaved case requires this anyway -// - allows good upsampling (see next) -// high-quality -// - upsampled channels are bilinearly interpolated, even across blocks -// - quality integer IDCT derived from IJG's 'slow' -// performance -// - fast huffman; reasonable integer IDCT -// - some SIMD kernels for common paths on targets with SSE2/NEON -// - uses a lot of intermediate memory, could cache poorly - -#ifndef STBI_NO_JPEG - -// huffman decoding acceleration -#define FAST_BITS 9 // larger handles more cases; smaller stomps less cache - -typedef struct -{ - stbi_uc fast[1 << FAST_BITS]; - // weirdly, repacking this into AoS is a 10% speed loss, instead of a win - stbi__uint16 code[256]; - stbi_uc values[256]; - stbi_uc size[257]; - unsigned int maxcode[18]; - int delta[17]; // old 'firstsymbol' - old 'firstcode' -} stbi__huffman; - -typedef struct -{ - stbi__context *s; - stbi__huffman huff_dc[4]; - stbi__huffman huff_ac[4]; - stbi__uint16 dequant[4][64]; - stbi__int16 fast_ac[4][1 << FAST_BITS]; - -// sizes for components, interleaved MCUs - int img_h_max, img_v_max; - int img_mcu_x, img_mcu_y; - int img_mcu_w, img_mcu_h; - -// definition of jpeg image component - struct - { - int id; - int h,v; - int tq; - int hd,ha; - int dc_pred; - - int x,y,w2,h2; - stbi_uc *data; - void *raw_data, *raw_coeff; - stbi_uc *linebuf; - short *coeff; // progressive only - int coeff_w, coeff_h; // number of 8x8 coefficient blocks - } img_comp[4]; - - stbi__uint32 code_buffer; // jpeg entropy-coded buffer - int code_bits; // number of valid bits - unsigned char marker; // marker seen while filling entropy buffer - int nomore; // flag if we saw a marker so must stop - - int progressive; - int spec_start; - int spec_end; - int succ_high; - int succ_low; - int eob_run; - int jfif; - int app14_color_transform; // Adobe APP14 tag - int rgb; - - int scan_n, order[4]; - int restart_interval, todo; - -// kernels - void (*idct_block_kernel)(stbi_uc *out, int out_stride, short data[64]); - void (*YCbCr_to_RGB_kernel)(stbi_uc *out, const stbi_uc *y, const stbi_uc *pcb, const stbi_uc *pcr, int count, int step); - stbi_uc *(*resample_row_hv_2_kernel)(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs); -} stbi__jpeg; - -static int stbi__build_huffman(stbi__huffman *h, int *count) -{ - int i,j,k=0; - unsigned int code; - // build size list for each symbol (from JPEG spec) - for (i=0; i < 16; ++i) { - for (j=0; j < count[i]; ++j) { - h->size[k++] = (stbi_uc) (i+1); - if(k >= 257) return stbi__err("bad size list","Corrupt JPEG"); - } - } - h->size[k] = 0; - - // compute actual symbols (from jpeg spec) - code = 0; - k = 0; - for(j=1; j <= 16; ++j) { - // compute delta to add to code to compute symbol id - h->delta[j] = k - code; - if (h->size[k] == j) { - while (h->size[k] == j) - h->code[k++] = (stbi__uint16) (code++); - if (code-1 >= (1u << j)) return stbi__err("bad code lengths","Corrupt JPEG"); - } - // compute largest code + 1 for this size, preshifted as needed later - h->maxcode[j] = code << (16-j); - code <<= 1; - } - h->maxcode[j] = 0xffffffff; - - // build non-spec acceleration table; 255 is flag for not-accelerated - memset(h->fast, 255, 1 << FAST_BITS); - for (i=0; i < k; ++i) { - int s = h->size[i]; - if (s <= FAST_BITS) { - int c = h->code[i] << (FAST_BITS-s); - int m = 1 << (FAST_BITS-s); - for (j=0; j < m; ++j) { - h->fast[c+j] = (stbi_uc) i; - } - } - } - return 1; -} - -// build a table that decodes both magnitude and value of small ACs in -// one go. -static void stbi__build_fast_ac(stbi__int16 *fast_ac, stbi__huffman *h) -{ - int i; - for (i=0; i < (1 << FAST_BITS); ++i) { - stbi_uc fast = h->fast[i]; - fast_ac[i] = 0; - if (fast < 255) { - int rs = h->values[fast]; - int run = (rs >> 4) & 15; - int magbits = rs & 15; - int len = h->size[fast]; - - if (magbits && len + magbits <= FAST_BITS) { - // magnitude code followed by receive_extend code - int k = ((i << len) & ((1 << FAST_BITS) - 1)) >> (FAST_BITS - magbits); - int m = 1 << (magbits - 1); - if (k < m) k += (~0U << magbits) + 1; - // if the result is small enough, we can fit it in fast_ac table - if (k >= -128 && k <= 127) - fast_ac[i] = (stbi__int16) ((k * 256) + (run * 16) + (len + magbits)); - } - } - } -} - -static void stbi__grow_buffer_unsafe(stbi__jpeg *j) -{ - do { - unsigned int b = j->nomore ? 0 : stbi__get8(j->s); - if (b == 0xff) { - int c = stbi__get8(j->s); - while (c == 0xff) c = stbi__get8(j->s); // consume fill bytes - if (c != 0) { - j->marker = (unsigned char) c; - j->nomore = 1; - return; - } - } - j->code_buffer |= b << (24 - j->code_bits); - j->code_bits += 8; - } while (j->code_bits <= 24); -} - -// (1 << n) - 1 -static const stbi__uint32 stbi__bmask[17]={0,1,3,7,15,31,63,127,255,511,1023,2047,4095,8191,16383,32767,65535}; - -// decode a jpeg huffman value from the bitstream -stbi_inline static int stbi__jpeg_huff_decode(stbi__jpeg *j, stbi__huffman *h) -{ - unsigned int temp; - int c,k; - - if (j->code_bits < 16) stbi__grow_buffer_unsafe(j); - - // look at the top FAST_BITS and determine what symbol ID it is, - // if the code is <= FAST_BITS - c = (j->code_buffer >> (32 - FAST_BITS)) & ((1 << FAST_BITS)-1); - k = h->fast[c]; - if (k < 255) { - int s = h->size[k]; - if (s > j->code_bits) - return -1; - j->code_buffer <<= s; - j->code_bits -= s; - return h->values[k]; - } - - // naive test is to shift the code_buffer down so k bits are - // valid, then test against maxcode. To speed this up, we've - // preshifted maxcode left so that it has (16-k) 0s at the - // end; in other words, regardless of the number of bits, it - // wants to be compared against something shifted to have 16; - // that way we don't need to shift inside the loop. - temp = j->code_buffer >> 16; - for (k=FAST_BITS+1 ; ; ++k) - if (temp < h->maxcode[k]) - break; - if (k == 17) { - // error! code not found - j->code_bits -= 16; - return -1; - } - - if (k > j->code_bits) - return -1; - - // convert the huffman code to the symbol id - c = ((j->code_buffer >> (32 - k)) & stbi__bmask[k]) + h->delta[k]; - if(c < 0 || c >= 256) // symbol id out of bounds! - return -1; - STBI_ASSERT((((j->code_buffer) >> (32 - h->size[c])) & stbi__bmask[h->size[c]]) == h->code[c]); - - // convert the id to a symbol - j->code_bits -= k; - j->code_buffer <<= k; - return h->values[c]; -} - -// bias[n] = (-1<code_bits < n) stbi__grow_buffer_unsafe(j); - if (j->code_bits < n) return 0; // ran out of bits from stream, return 0s intead of continuing - - sgn = j->code_buffer >> 31; // sign bit always in MSB; 0 if MSB clear (positive), 1 if MSB set (negative) - k = stbi_lrot(j->code_buffer, n); - j->code_buffer = k & ~stbi__bmask[n]; - k &= stbi__bmask[n]; - j->code_bits -= n; - return k + (stbi__jbias[n] & (sgn - 1)); -} - -// get some unsigned bits -stbi_inline static int stbi__jpeg_get_bits(stbi__jpeg *j, int n) -{ - unsigned int k; - if (j->code_bits < n) stbi__grow_buffer_unsafe(j); - if (j->code_bits < n) return 0; // ran out of bits from stream, return 0s intead of continuing - k = stbi_lrot(j->code_buffer, n); - j->code_buffer = k & ~stbi__bmask[n]; - k &= stbi__bmask[n]; - j->code_bits -= n; - return k; -} - -stbi_inline static int stbi__jpeg_get_bit(stbi__jpeg *j) -{ - unsigned int k; - if (j->code_bits < 1) stbi__grow_buffer_unsafe(j); - if (j->code_bits < 1) return 0; // ran out of bits from stream, return 0s intead of continuing - k = j->code_buffer; - j->code_buffer <<= 1; - --j->code_bits; - return k & 0x80000000; -} - -// given a value that's at position X in the zigzag stream, -// where does it appear in the 8x8 matrix coded as row-major? -static const stbi_uc stbi__jpeg_dezigzag[64+15] = -{ - 0, 1, 8, 16, 9, 2, 3, 10, - 17, 24, 32, 25, 18, 11, 4, 5, - 12, 19, 26, 33, 40, 48, 41, 34, - 27, 20, 13, 6, 7, 14, 21, 28, - 35, 42, 49, 56, 57, 50, 43, 36, - 29, 22, 15, 23, 30, 37, 44, 51, - 58, 59, 52, 45, 38, 31, 39, 46, - 53, 60, 61, 54, 47, 55, 62, 63, - // let corrupt input sample past end - 63, 63, 63, 63, 63, 63, 63, 63, - 63, 63, 63, 63, 63, 63, 63 -}; - -// decode one 64-entry block-- -static int stbi__jpeg_decode_block(stbi__jpeg *j, short data[64], stbi__huffman *hdc, stbi__huffman *hac, stbi__int16 *fac, int b, stbi__uint16 *dequant) -{ - int diff,dc,k; - int t; - - if (j->code_bits < 16) stbi__grow_buffer_unsafe(j); - t = stbi__jpeg_huff_decode(j, hdc); - if (t < 0 || t > 15) return stbi__err("bad huffman code","Corrupt JPEG"); - - // 0 all the ac values now so we can do it 32-bits at a time - memset(data,0,64*sizeof(data[0])); - - diff = t ? stbi__extend_receive(j, t) : 0; - if (!stbi__addints_valid(j->img_comp[b].dc_pred, diff)) return stbi__err("bad delta","Corrupt JPEG"); - dc = j->img_comp[b].dc_pred + diff; - j->img_comp[b].dc_pred = dc; - if (!stbi__mul2shorts_valid(dc, dequant[0])) return stbi__err("can't merge dc and ac", "Corrupt JPEG"); - data[0] = (short) (dc * dequant[0]); - - // decode AC components, see JPEG spec - k = 1; - do { - unsigned int zig; - int c,r,s; - if (j->code_bits < 16) stbi__grow_buffer_unsafe(j); - c = (j->code_buffer >> (32 - FAST_BITS)) & ((1 << FAST_BITS)-1); - r = fac[c]; - if (r) { // fast-AC path - k += (r >> 4) & 15; // run - s = r & 15; // combined length - if (s > j->code_bits) return stbi__err("bad huffman code", "Combined length longer than code bits available"); - j->code_buffer <<= s; - j->code_bits -= s; - // decode into unzigzag'd location - zig = stbi__jpeg_dezigzag[k++]; - data[zig] = (short) ((r >> 8) * dequant[zig]); - } else { - int rs = stbi__jpeg_huff_decode(j, hac); - if (rs < 0) return stbi__err("bad huffman code","Corrupt JPEG"); - s = rs & 15; - r = rs >> 4; - if (s == 0) { - if (rs != 0xf0) break; // end block - k += 16; - } else { - k += r; - // decode into unzigzag'd location - zig = stbi__jpeg_dezigzag[k++]; - data[zig] = (short) (stbi__extend_receive(j,s) * dequant[zig]); - } - } - } while (k < 64); - return 1; -} - -static int stbi__jpeg_decode_block_prog_dc(stbi__jpeg *j, short data[64], stbi__huffman *hdc, int b) -{ - int diff,dc; - int t; - if (j->spec_end != 0) return stbi__err("can't merge dc and ac", "Corrupt JPEG"); - - if (j->code_bits < 16) stbi__grow_buffer_unsafe(j); - - if (j->succ_high == 0) { - // first scan for DC coefficient, must be first - memset(data,0,64*sizeof(data[0])); // 0 all the ac values now - t = stbi__jpeg_huff_decode(j, hdc); - if (t < 0 || t > 15) return stbi__err("can't merge dc and ac", "Corrupt JPEG"); - diff = t ? stbi__extend_receive(j, t) : 0; - - if (!stbi__addints_valid(j->img_comp[b].dc_pred, diff)) return stbi__err("bad delta", "Corrupt JPEG"); - dc = j->img_comp[b].dc_pred + diff; - j->img_comp[b].dc_pred = dc; - if (!stbi__mul2shorts_valid(dc, 1 << j->succ_low)) return stbi__err("can't merge dc and ac", "Corrupt JPEG"); - data[0] = (short) (dc * (1 << j->succ_low)); - } else { - // refinement scan for DC coefficient - if (stbi__jpeg_get_bit(j)) - data[0] += (short) (1 << j->succ_low); - } - return 1; -} - -// @OPTIMIZE: store non-zigzagged during the decode passes, -// and only de-zigzag when dequantizing -static int stbi__jpeg_decode_block_prog_ac(stbi__jpeg *j, short data[64], stbi__huffman *hac, stbi__int16 *fac) -{ - int k; - if (j->spec_start == 0) return stbi__err("can't merge dc and ac", "Corrupt JPEG"); - - if (j->succ_high == 0) { - int shift = j->succ_low; - - if (j->eob_run) { - --j->eob_run; - return 1; - } - - k = j->spec_start; - do { - unsigned int zig; - int c,r,s; - if (j->code_bits < 16) stbi__grow_buffer_unsafe(j); - c = (j->code_buffer >> (32 - FAST_BITS)) & ((1 << FAST_BITS)-1); - r = fac[c]; - if (r) { // fast-AC path - k += (r >> 4) & 15; // run - s = r & 15; // combined length - if (s > j->code_bits) return stbi__err("bad huffman code", "Combined length longer than code bits available"); - j->code_buffer <<= s; - j->code_bits -= s; - zig = stbi__jpeg_dezigzag[k++]; - data[zig] = (short) ((r >> 8) * (1 << shift)); - } else { - int rs = stbi__jpeg_huff_decode(j, hac); - if (rs < 0) return stbi__err("bad huffman code","Corrupt JPEG"); - s = rs & 15; - r = rs >> 4; - if (s == 0) { - if (r < 15) { - j->eob_run = (1 << r); - if (r) - j->eob_run += stbi__jpeg_get_bits(j, r); - --j->eob_run; - break; - } - k += 16; - } else { - k += r; - zig = stbi__jpeg_dezigzag[k++]; - data[zig] = (short) (stbi__extend_receive(j,s) * (1 << shift)); - } - } - } while (k <= j->spec_end); - } else { - // refinement scan for these AC coefficients - - short bit = (short) (1 << j->succ_low); - - if (j->eob_run) { - --j->eob_run; - for (k = j->spec_start; k <= j->spec_end; ++k) { - short *p = &data[stbi__jpeg_dezigzag[k]]; - if (*p != 0) - if (stbi__jpeg_get_bit(j)) - if ((*p & bit)==0) { - if (*p > 0) - *p += bit; - else - *p -= bit; - } - } - } else { - k = j->spec_start; - do { - int r,s; - int rs = stbi__jpeg_huff_decode(j, hac); // @OPTIMIZE see if we can use the fast path here, advance-by-r is so slow, eh - if (rs < 0) return stbi__err("bad huffman code","Corrupt JPEG"); - s = rs & 15; - r = rs >> 4; - if (s == 0) { - if (r < 15) { - j->eob_run = (1 << r) - 1; - if (r) - j->eob_run += stbi__jpeg_get_bits(j, r); - r = 64; // force end of block - } else { - // r=15 s=0 should write 16 0s, so we just do - // a run of 15 0s and then write s (which is 0), - // so we don't have to do anything special here - } - } else { - if (s != 1) return stbi__err("bad huffman code", "Corrupt JPEG"); - // sign bit - if (stbi__jpeg_get_bit(j)) - s = bit; - else - s = -bit; - } - - // advance by r - while (k <= j->spec_end) { - short *p = &data[stbi__jpeg_dezigzag[k++]]; - if (*p != 0) { - if (stbi__jpeg_get_bit(j)) - if ((*p & bit)==0) { - if (*p > 0) - *p += bit; - else - *p -= bit; - } - } else { - if (r == 0) { - *p = (short) s; - break; - } - --r; - } - } - } while (k <= j->spec_end); - } - } - return 1; -} - -// take a -128..127 value and stbi__clamp it and convert to 0..255 -stbi_inline static stbi_uc stbi__clamp(int x) -{ - // trick to use a single test to catch both cases - if ((unsigned int) x > 255) { - if (x < 0) return 0; - if (x > 255) return 255; - } - return (stbi_uc) x; -} - -#define stbi__f2f(x) ((int) (((x) * 4096 + 0.5))) -#define stbi__fsh(x) ((x) * 4096) - -// derived from jidctint -- DCT_ISLOW -#define STBI__IDCT_1D(s0,s1,s2,s3,s4,s5,s6,s7) \ - int t0,t1,t2,t3,p1,p2,p3,p4,p5,x0,x1,x2,x3; \ - p2 = s2; \ - p3 = s6; \ - p1 = (p2+p3) * stbi__f2f(0.5411961f); \ - t2 = p1 + p3*stbi__f2f(-1.847759065f); \ - t3 = p1 + p2*stbi__f2f( 0.765366865f); \ - p2 = s0; \ - p3 = s4; \ - t0 = stbi__fsh(p2+p3); \ - t1 = stbi__fsh(p2-p3); \ - x0 = t0+t3; \ - x3 = t0-t3; \ - x1 = t1+t2; \ - x2 = t1-t2; \ - t0 = s7; \ - t1 = s5; \ - t2 = s3; \ - t3 = s1; \ - p3 = t0+t2; \ - p4 = t1+t3; \ - p1 = t0+t3; \ - p2 = t1+t2; \ - p5 = (p3+p4)*stbi__f2f( 1.175875602f); \ - t0 = t0*stbi__f2f( 0.298631336f); \ - t1 = t1*stbi__f2f( 2.053119869f); \ - t2 = t2*stbi__f2f( 3.072711026f); \ - t3 = t3*stbi__f2f( 1.501321110f); \ - p1 = p5 + p1*stbi__f2f(-0.899976223f); \ - p2 = p5 + p2*stbi__f2f(-2.562915447f); \ - p3 = p3*stbi__f2f(-1.961570560f); \ - p4 = p4*stbi__f2f(-0.390180644f); \ - t3 += p1+p4; \ - t2 += p2+p3; \ - t1 += p2+p4; \ - t0 += p1+p3; - -static void stbi__idct_block(stbi_uc *out, int out_stride, short data[64]) -{ - int i,val[64],*v=val; - stbi_uc *o; - short *d = data; - - // columns - for (i=0; i < 8; ++i,++d, ++v) { - // if all zeroes, shortcut -- this avoids dequantizing 0s and IDCTing - if (d[ 8]==0 && d[16]==0 && d[24]==0 && d[32]==0 - && d[40]==0 && d[48]==0 && d[56]==0) { - // no shortcut 0 seconds - // (1|2|3|4|5|6|7)==0 0 seconds - // all separate -0.047 seconds - // 1 && 2|3 && 4|5 && 6|7: -0.047 seconds - int dcterm = d[0]*4; - v[0] = v[8] = v[16] = v[24] = v[32] = v[40] = v[48] = v[56] = dcterm; - } else { - STBI__IDCT_1D(d[ 0],d[ 8],d[16],d[24],d[32],d[40],d[48],d[56]) - // constants scaled things up by 1<<12; let's bring them back - // down, but keep 2 extra bits of precision - x0 += 512; x1 += 512; x2 += 512; x3 += 512; - v[ 0] = (x0+t3) >> 10; - v[56] = (x0-t3) >> 10; - v[ 8] = (x1+t2) >> 10; - v[48] = (x1-t2) >> 10; - v[16] = (x2+t1) >> 10; - v[40] = (x2-t1) >> 10; - v[24] = (x3+t0) >> 10; - v[32] = (x3-t0) >> 10; - } - } - - for (i=0, v=val, o=out; i < 8; ++i,v+=8,o+=out_stride) { - // no fast case since the first 1D IDCT spread components out - STBI__IDCT_1D(v[0],v[1],v[2],v[3],v[4],v[5],v[6],v[7]) - // constants scaled things up by 1<<12, plus we had 1<<2 from first - // loop, plus horizontal and vertical each scale by sqrt(8) so together - // we've got an extra 1<<3, so 1<<17 total we need to remove. - // so we want to round that, which means adding 0.5 * 1<<17, - // aka 65536. Also, we'll end up with -128 to 127 that we want - // to encode as 0..255 by adding 128, so we'll add that before the shift - x0 += 65536 + (128<<17); - x1 += 65536 + (128<<17); - x2 += 65536 + (128<<17); - x3 += 65536 + (128<<17); - // tried computing the shifts into temps, or'ing the temps to see - // if any were out of range, but that was slower - o[0] = stbi__clamp((x0+t3) >> 17); - o[7] = stbi__clamp((x0-t3) >> 17); - o[1] = stbi__clamp((x1+t2) >> 17); - o[6] = stbi__clamp((x1-t2) >> 17); - o[2] = stbi__clamp((x2+t1) >> 17); - o[5] = stbi__clamp((x2-t1) >> 17); - o[3] = stbi__clamp((x3+t0) >> 17); - o[4] = stbi__clamp((x3-t0) >> 17); - } -} - -#ifdef STBI_SSE2 -// sse2 integer IDCT. not the fastest possible implementation but it -// produces bit-identical results to the generic C version so it's -// fully "transparent". -static void stbi__idct_simd(stbi_uc *out, int out_stride, short data[64]) -{ - // This is constructed to match our regular (generic) integer IDCT exactly. - __m128i row0, row1, row2, row3, row4, row5, row6, row7; - __m128i tmp; - - // dot product constant: even elems=x, odd elems=y - #define dct_const(x,y) _mm_setr_epi16((x),(y),(x),(y),(x),(y),(x),(y)) - - // out(0) = c0[even]*x + c0[odd]*y (c0, x, y 16-bit, out 32-bit) - // out(1) = c1[even]*x + c1[odd]*y - #define dct_rot(out0,out1, x,y,c0,c1) \ - __m128i c0##lo = _mm_unpacklo_epi16((x),(y)); \ - __m128i c0##hi = _mm_unpackhi_epi16((x),(y)); \ - __m128i out0##_l = _mm_madd_epi16(c0##lo, c0); \ - __m128i out0##_h = _mm_madd_epi16(c0##hi, c0); \ - __m128i out1##_l = _mm_madd_epi16(c0##lo, c1); \ - __m128i out1##_h = _mm_madd_epi16(c0##hi, c1) - - // out = in << 12 (in 16-bit, out 32-bit) - #define dct_widen(out, in) \ - __m128i out##_l = _mm_srai_epi32(_mm_unpacklo_epi16(_mm_setzero_si128(), (in)), 4); \ - __m128i out##_h = _mm_srai_epi32(_mm_unpackhi_epi16(_mm_setzero_si128(), (in)), 4) - - // wide add - #define dct_wadd(out, a, b) \ - __m128i out##_l = _mm_add_epi32(a##_l, b##_l); \ - __m128i out##_h = _mm_add_epi32(a##_h, b##_h) - - // wide sub - #define dct_wsub(out, a, b) \ - __m128i out##_l = _mm_sub_epi32(a##_l, b##_l); \ - __m128i out##_h = _mm_sub_epi32(a##_h, b##_h) - - // butterfly a/b, add bias, then shift by "s" and pack - #define dct_bfly32o(out0, out1, a,b,bias,s) \ - { \ - __m128i abiased_l = _mm_add_epi32(a##_l, bias); \ - __m128i abiased_h = _mm_add_epi32(a##_h, bias); \ - dct_wadd(sum, abiased, b); \ - dct_wsub(dif, abiased, b); \ - out0 = _mm_packs_epi32(_mm_srai_epi32(sum_l, s), _mm_srai_epi32(sum_h, s)); \ - out1 = _mm_packs_epi32(_mm_srai_epi32(dif_l, s), _mm_srai_epi32(dif_h, s)); \ - } - - // 8-bit interleave step (for transposes) - #define dct_interleave8(a, b) \ - tmp = a; \ - a = _mm_unpacklo_epi8(a, b); \ - b = _mm_unpackhi_epi8(tmp, b) - - // 16-bit interleave step (for transposes) - #define dct_interleave16(a, b) \ - tmp = a; \ - a = _mm_unpacklo_epi16(a, b); \ - b = _mm_unpackhi_epi16(tmp, b) - - #define dct_pass(bias,shift) \ - { \ - /* even part */ \ - dct_rot(t2e,t3e, row2,row6, rot0_0,rot0_1); \ - __m128i sum04 = _mm_add_epi16(row0, row4); \ - __m128i dif04 = _mm_sub_epi16(row0, row4); \ - dct_widen(t0e, sum04); \ - dct_widen(t1e, dif04); \ - dct_wadd(x0, t0e, t3e); \ - dct_wsub(x3, t0e, t3e); \ - dct_wadd(x1, t1e, t2e); \ - dct_wsub(x2, t1e, t2e); \ - /* odd part */ \ - dct_rot(y0o,y2o, row7,row3, rot2_0,rot2_1); \ - dct_rot(y1o,y3o, row5,row1, rot3_0,rot3_1); \ - __m128i sum17 = _mm_add_epi16(row1, row7); \ - __m128i sum35 = _mm_add_epi16(row3, row5); \ - dct_rot(y4o,y5o, sum17,sum35, rot1_0,rot1_1); \ - dct_wadd(x4, y0o, y4o); \ - dct_wadd(x5, y1o, y5o); \ - dct_wadd(x6, y2o, y5o); \ - dct_wadd(x7, y3o, y4o); \ - dct_bfly32o(row0,row7, x0,x7,bias,shift); \ - dct_bfly32o(row1,row6, x1,x6,bias,shift); \ - dct_bfly32o(row2,row5, x2,x5,bias,shift); \ - dct_bfly32o(row3,row4, x3,x4,bias,shift); \ - } - - __m128i rot0_0 = dct_const(stbi__f2f(0.5411961f), stbi__f2f(0.5411961f) + stbi__f2f(-1.847759065f)); - __m128i rot0_1 = dct_const(stbi__f2f(0.5411961f) + stbi__f2f( 0.765366865f), stbi__f2f(0.5411961f)); - __m128i rot1_0 = dct_const(stbi__f2f(1.175875602f) + stbi__f2f(-0.899976223f), stbi__f2f(1.175875602f)); - __m128i rot1_1 = dct_const(stbi__f2f(1.175875602f), stbi__f2f(1.175875602f) + stbi__f2f(-2.562915447f)); - __m128i rot2_0 = dct_const(stbi__f2f(-1.961570560f) + stbi__f2f( 0.298631336f), stbi__f2f(-1.961570560f)); - __m128i rot2_1 = dct_const(stbi__f2f(-1.961570560f), stbi__f2f(-1.961570560f) + stbi__f2f( 3.072711026f)); - __m128i rot3_0 = dct_const(stbi__f2f(-0.390180644f) + stbi__f2f( 2.053119869f), stbi__f2f(-0.390180644f)); - __m128i rot3_1 = dct_const(stbi__f2f(-0.390180644f), stbi__f2f(-0.390180644f) + stbi__f2f( 1.501321110f)); - - // rounding biases in column/row passes, see stbi__idct_block for explanation. - __m128i bias_0 = _mm_set1_epi32(512); - __m128i bias_1 = _mm_set1_epi32(65536 + (128<<17)); - - // load - row0 = _mm_load_si128((const __m128i *) (data + 0*8)); - row1 = _mm_load_si128((const __m128i *) (data + 1*8)); - row2 = _mm_load_si128((const __m128i *) (data + 2*8)); - row3 = _mm_load_si128((const __m128i *) (data + 3*8)); - row4 = _mm_load_si128((const __m128i *) (data + 4*8)); - row5 = _mm_load_si128((const __m128i *) (data + 5*8)); - row6 = _mm_load_si128((const __m128i *) (data + 6*8)); - row7 = _mm_load_si128((const __m128i *) (data + 7*8)); - - // column pass - dct_pass(bias_0, 10); - - { - // 16bit 8x8 transpose pass 1 - dct_interleave16(row0, row4); - dct_interleave16(row1, row5); - dct_interleave16(row2, row6); - dct_interleave16(row3, row7); - - // transpose pass 2 - dct_interleave16(row0, row2); - dct_interleave16(row1, row3); - dct_interleave16(row4, row6); - dct_interleave16(row5, row7); - - // transpose pass 3 - dct_interleave16(row0, row1); - dct_interleave16(row2, row3); - dct_interleave16(row4, row5); - dct_interleave16(row6, row7); - } - - // row pass - dct_pass(bias_1, 17); - - { - // pack - __m128i p0 = _mm_packus_epi16(row0, row1); // a0a1a2a3...a7b0b1b2b3...b7 - __m128i p1 = _mm_packus_epi16(row2, row3); - __m128i p2 = _mm_packus_epi16(row4, row5); - __m128i p3 = _mm_packus_epi16(row6, row7); - - // 8bit 8x8 transpose pass 1 - dct_interleave8(p0, p2); // a0e0a1e1... - dct_interleave8(p1, p3); // c0g0c1g1... - - // transpose pass 2 - dct_interleave8(p0, p1); // a0c0e0g0... - dct_interleave8(p2, p3); // b0d0f0h0... - - // transpose pass 3 - dct_interleave8(p0, p2); // a0b0c0d0... - dct_interleave8(p1, p3); // a4b4c4d4... - - // store - _mm_storel_epi64((__m128i *) out, p0); out += out_stride; - _mm_storel_epi64((__m128i *) out, _mm_shuffle_epi32(p0, 0x4e)); out += out_stride; - _mm_storel_epi64((__m128i *) out, p2); out += out_stride; - _mm_storel_epi64((__m128i *) out, _mm_shuffle_epi32(p2, 0x4e)); out += out_stride; - _mm_storel_epi64((__m128i *) out, p1); out += out_stride; - _mm_storel_epi64((__m128i *) out, _mm_shuffle_epi32(p1, 0x4e)); out += out_stride; - _mm_storel_epi64((__m128i *) out, p3); out += out_stride; - _mm_storel_epi64((__m128i *) out, _mm_shuffle_epi32(p3, 0x4e)); - } - -#undef dct_const -#undef dct_rot -#undef dct_widen -#undef dct_wadd -#undef dct_wsub -#undef dct_bfly32o -#undef dct_interleave8 -#undef dct_interleave16 -#undef dct_pass -} - -#endif // STBI_SSE2 - -#ifdef STBI_NEON - -// NEON integer IDCT. should produce bit-identical -// results to the generic C version. -static void stbi__idct_simd(stbi_uc *out, int out_stride, short data[64]) -{ - int16x8_t row0, row1, row2, row3, row4, row5, row6, row7; - - int16x4_t rot0_0 = vdup_n_s16(stbi__f2f(0.5411961f)); - int16x4_t rot0_1 = vdup_n_s16(stbi__f2f(-1.847759065f)); - int16x4_t rot0_2 = vdup_n_s16(stbi__f2f( 0.765366865f)); - int16x4_t rot1_0 = vdup_n_s16(stbi__f2f( 1.175875602f)); - int16x4_t rot1_1 = vdup_n_s16(stbi__f2f(-0.899976223f)); - int16x4_t rot1_2 = vdup_n_s16(stbi__f2f(-2.562915447f)); - int16x4_t rot2_0 = vdup_n_s16(stbi__f2f(-1.961570560f)); - int16x4_t rot2_1 = vdup_n_s16(stbi__f2f(-0.390180644f)); - int16x4_t rot3_0 = vdup_n_s16(stbi__f2f( 0.298631336f)); - int16x4_t rot3_1 = vdup_n_s16(stbi__f2f( 2.053119869f)); - int16x4_t rot3_2 = vdup_n_s16(stbi__f2f( 3.072711026f)); - int16x4_t rot3_3 = vdup_n_s16(stbi__f2f( 1.501321110f)); - -#define dct_long_mul(out, inq, coeff) \ - int32x4_t out##_l = vmull_s16(vget_low_s16(inq), coeff); \ - int32x4_t out##_h = vmull_s16(vget_high_s16(inq), coeff) - -#define dct_long_mac(out, acc, inq, coeff) \ - int32x4_t out##_l = vmlal_s16(acc##_l, vget_low_s16(inq), coeff); \ - int32x4_t out##_h = vmlal_s16(acc##_h, vget_high_s16(inq), coeff) - -#define dct_widen(out, inq) \ - int32x4_t out##_l = vshll_n_s16(vget_low_s16(inq), 12); \ - int32x4_t out##_h = vshll_n_s16(vget_high_s16(inq), 12) - -// wide add -#define dct_wadd(out, a, b) \ - int32x4_t out##_l = vaddq_s32(a##_l, b##_l); \ - int32x4_t out##_h = vaddq_s32(a##_h, b##_h) - -// wide sub -#define dct_wsub(out, a, b) \ - int32x4_t out##_l = vsubq_s32(a##_l, b##_l); \ - int32x4_t out##_h = vsubq_s32(a##_h, b##_h) - -// butterfly a/b, then shift using "shiftop" by "s" and pack -#define dct_bfly32o(out0,out1, a,b,shiftop,s) \ - { \ - dct_wadd(sum, a, b); \ - dct_wsub(dif, a, b); \ - out0 = vcombine_s16(shiftop(sum_l, s), shiftop(sum_h, s)); \ - out1 = vcombine_s16(shiftop(dif_l, s), shiftop(dif_h, s)); \ - } - -#define dct_pass(shiftop, shift) \ - { \ - /* even part */ \ - int16x8_t sum26 = vaddq_s16(row2, row6); \ - dct_long_mul(p1e, sum26, rot0_0); \ - dct_long_mac(t2e, p1e, row6, rot0_1); \ - dct_long_mac(t3e, p1e, row2, rot0_2); \ - int16x8_t sum04 = vaddq_s16(row0, row4); \ - int16x8_t dif04 = vsubq_s16(row0, row4); \ - dct_widen(t0e, sum04); \ - dct_widen(t1e, dif04); \ - dct_wadd(x0, t0e, t3e); \ - dct_wsub(x3, t0e, t3e); \ - dct_wadd(x1, t1e, t2e); \ - dct_wsub(x2, t1e, t2e); \ - /* odd part */ \ - int16x8_t sum15 = vaddq_s16(row1, row5); \ - int16x8_t sum17 = vaddq_s16(row1, row7); \ - int16x8_t sum35 = vaddq_s16(row3, row5); \ - int16x8_t sum37 = vaddq_s16(row3, row7); \ - int16x8_t sumodd = vaddq_s16(sum17, sum35); \ - dct_long_mul(p5o, sumodd, rot1_0); \ - dct_long_mac(p1o, p5o, sum17, rot1_1); \ - dct_long_mac(p2o, p5o, sum35, rot1_2); \ - dct_long_mul(p3o, sum37, rot2_0); \ - dct_long_mul(p4o, sum15, rot2_1); \ - dct_wadd(sump13o, p1o, p3o); \ - dct_wadd(sump24o, p2o, p4o); \ - dct_wadd(sump23o, p2o, p3o); \ - dct_wadd(sump14o, p1o, p4o); \ - dct_long_mac(x4, sump13o, row7, rot3_0); \ - dct_long_mac(x5, sump24o, row5, rot3_1); \ - dct_long_mac(x6, sump23o, row3, rot3_2); \ - dct_long_mac(x7, sump14o, row1, rot3_3); \ - dct_bfly32o(row0,row7, x0,x7,shiftop,shift); \ - dct_bfly32o(row1,row6, x1,x6,shiftop,shift); \ - dct_bfly32o(row2,row5, x2,x5,shiftop,shift); \ - dct_bfly32o(row3,row4, x3,x4,shiftop,shift); \ - } - - // load - row0 = vld1q_s16(data + 0*8); - row1 = vld1q_s16(data + 1*8); - row2 = vld1q_s16(data + 2*8); - row3 = vld1q_s16(data + 3*8); - row4 = vld1q_s16(data + 4*8); - row5 = vld1q_s16(data + 5*8); - row6 = vld1q_s16(data + 6*8); - row7 = vld1q_s16(data + 7*8); - - // add DC bias - row0 = vaddq_s16(row0, vsetq_lane_s16(1024, vdupq_n_s16(0), 0)); - - // column pass - dct_pass(vrshrn_n_s32, 10); - - // 16bit 8x8 transpose - { -// these three map to a single VTRN.16, VTRN.32, and VSWP, respectively. -// whether compilers actually get this is another story, sadly. -#define dct_trn16(x, y) { int16x8x2_t t = vtrnq_s16(x, y); x = t.val[0]; y = t.val[1]; } -#define dct_trn32(x, y) { int32x4x2_t t = vtrnq_s32(vreinterpretq_s32_s16(x), vreinterpretq_s32_s16(y)); x = vreinterpretq_s16_s32(t.val[0]); y = vreinterpretq_s16_s32(t.val[1]); } -#define dct_trn64(x, y) { int16x8_t x0 = x; int16x8_t y0 = y; x = vcombine_s16(vget_low_s16(x0), vget_low_s16(y0)); y = vcombine_s16(vget_high_s16(x0), vget_high_s16(y0)); } - - // pass 1 - dct_trn16(row0, row1); // a0b0a2b2a4b4a6b6 - dct_trn16(row2, row3); - dct_trn16(row4, row5); - dct_trn16(row6, row7); - - // pass 2 - dct_trn32(row0, row2); // a0b0c0d0a4b4c4d4 - dct_trn32(row1, row3); - dct_trn32(row4, row6); - dct_trn32(row5, row7); - - // pass 3 - dct_trn64(row0, row4); // a0b0c0d0e0f0g0h0 - dct_trn64(row1, row5); - dct_trn64(row2, row6); - dct_trn64(row3, row7); - -#undef dct_trn16 -#undef dct_trn32 -#undef dct_trn64 - } - - // row pass - // vrshrn_n_s32 only supports shifts up to 16, we need - // 17. so do a non-rounding shift of 16 first then follow - // up with a rounding shift by 1. - dct_pass(vshrn_n_s32, 16); - - { - // pack and round - uint8x8_t p0 = vqrshrun_n_s16(row0, 1); - uint8x8_t p1 = vqrshrun_n_s16(row1, 1); - uint8x8_t p2 = vqrshrun_n_s16(row2, 1); - uint8x8_t p3 = vqrshrun_n_s16(row3, 1); - uint8x8_t p4 = vqrshrun_n_s16(row4, 1); - uint8x8_t p5 = vqrshrun_n_s16(row5, 1); - uint8x8_t p6 = vqrshrun_n_s16(row6, 1); - uint8x8_t p7 = vqrshrun_n_s16(row7, 1); - - // again, these can translate into one instruction, but often don't. -#define dct_trn8_8(x, y) { uint8x8x2_t t = vtrn_u8(x, y); x = t.val[0]; y = t.val[1]; } -#define dct_trn8_16(x, y) { uint16x4x2_t t = vtrn_u16(vreinterpret_u16_u8(x), vreinterpret_u16_u8(y)); x = vreinterpret_u8_u16(t.val[0]); y = vreinterpret_u8_u16(t.val[1]); } -#define dct_trn8_32(x, y) { uint32x2x2_t t = vtrn_u32(vreinterpret_u32_u8(x), vreinterpret_u32_u8(y)); x = vreinterpret_u8_u32(t.val[0]); y = vreinterpret_u8_u32(t.val[1]); } - - // sadly can't use interleaved stores here since we only write - // 8 bytes to each scan line! - - // 8x8 8-bit transpose pass 1 - dct_trn8_8(p0, p1); - dct_trn8_8(p2, p3); - dct_trn8_8(p4, p5); - dct_trn8_8(p6, p7); - - // pass 2 - dct_trn8_16(p0, p2); - dct_trn8_16(p1, p3); - dct_trn8_16(p4, p6); - dct_trn8_16(p5, p7); - - // pass 3 - dct_trn8_32(p0, p4); - dct_trn8_32(p1, p5); - dct_trn8_32(p2, p6); - dct_trn8_32(p3, p7); - - // store - vst1_u8(out, p0); out += out_stride; - vst1_u8(out, p1); out += out_stride; - vst1_u8(out, p2); out += out_stride; - vst1_u8(out, p3); out += out_stride; - vst1_u8(out, p4); out += out_stride; - vst1_u8(out, p5); out += out_stride; - vst1_u8(out, p6); out += out_stride; - vst1_u8(out, p7); - -#undef dct_trn8_8 -#undef dct_trn8_16 -#undef dct_trn8_32 - } - -#undef dct_long_mul -#undef dct_long_mac -#undef dct_widen -#undef dct_wadd -#undef dct_wsub -#undef dct_bfly32o -#undef dct_pass -} - -#endif // STBI_NEON - -#define STBI__MARKER_none 0xff -// if there's a pending marker from the entropy stream, return that -// otherwise, fetch from the stream and get a marker. if there's no -// marker, return 0xff, which is never a valid marker value -static stbi_uc stbi__get_marker(stbi__jpeg *j) -{ - stbi_uc x; - if (j->marker != STBI__MARKER_none) { x = j->marker; j->marker = STBI__MARKER_none; return x; } - x = stbi__get8(j->s); - if (x != 0xff) return STBI__MARKER_none; - while (x == 0xff) - x = stbi__get8(j->s); // consume repeated 0xff fill bytes - return x; -} - -// in each scan, we'll have scan_n components, and the order -// of the components is specified by order[] -#define STBI__RESTART(x) ((x) >= 0xd0 && (x) <= 0xd7) - -// after a restart interval, stbi__jpeg_reset the entropy decoder and -// the dc prediction -static void stbi__jpeg_reset(stbi__jpeg *j) -{ - j->code_bits = 0; - j->code_buffer = 0; - j->nomore = 0; - j->img_comp[0].dc_pred = j->img_comp[1].dc_pred = j->img_comp[2].dc_pred = j->img_comp[3].dc_pred = 0; - j->marker = STBI__MARKER_none; - j->todo = j->restart_interval ? j->restart_interval : 0x7fffffff; - j->eob_run = 0; - // no more than 1<<31 MCUs if no restart_interal? that's plenty safe, - // since we don't even allow 1<<30 pixels -} - -static int stbi__parse_entropy_coded_data(stbi__jpeg *z) -{ - stbi__jpeg_reset(z); - if (!z->progressive) { - if (z->scan_n == 1) { - int i,j; - STBI_SIMD_ALIGN(short, data[64]); - int n = z->order[0]; - // non-interleaved data, we just need to process one block at a time, - // in trivial scanline order - // number of blocks to do just depends on how many actual "pixels" this - // component has, independent of interleaved MCU blocking and such - int w = (z->img_comp[n].x+7) >> 3; - int h = (z->img_comp[n].y+7) >> 3; - for (j=0; j < h; ++j) { - for (i=0; i < w; ++i) { - int ha = z->img_comp[n].ha; - if (!stbi__jpeg_decode_block(z, data, z->huff_dc+z->img_comp[n].hd, z->huff_ac+ha, z->fast_ac[ha], n, z->dequant[z->img_comp[n].tq])) return 0; - z->idct_block_kernel(z->img_comp[n].data+z->img_comp[n].w2*j*8+i*8, z->img_comp[n].w2, data); - // every data block is an MCU, so countdown the restart interval - if (--z->todo <= 0) { - if (z->code_bits < 24) stbi__grow_buffer_unsafe(z); - // if it's NOT a restart, then just bail, so we get corrupt data - // rather than no data - if (!STBI__RESTART(z->marker)) return 1; - stbi__jpeg_reset(z); - } - } - } - return 1; - } else { // interleaved - int i,j,k,x,y; - STBI_SIMD_ALIGN(short, data[64]); - for (j=0; j < z->img_mcu_y; ++j) { - for (i=0; i < z->img_mcu_x; ++i) { - // scan an interleaved mcu... process scan_n components in order - for (k=0; k < z->scan_n; ++k) { - int n = z->order[k]; - // scan out an mcu's worth of this component; that's just determined - // by the basic H and V specified for the component - for (y=0; y < z->img_comp[n].v; ++y) { - for (x=0; x < z->img_comp[n].h; ++x) { - int x2 = (i*z->img_comp[n].h + x)*8; - int y2 = (j*z->img_comp[n].v + y)*8; - int ha = z->img_comp[n].ha; - if (!stbi__jpeg_decode_block(z, data, z->huff_dc+z->img_comp[n].hd, z->huff_ac+ha, z->fast_ac[ha], n, z->dequant[z->img_comp[n].tq])) return 0; - z->idct_block_kernel(z->img_comp[n].data+z->img_comp[n].w2*y2+x2, z->img_comp[n].w2, data); - } - } - } - // after all interleaved components, that's an interleaved MCU, - // so now count down the restart interval - if (--z->todo <= 0) { - if (z->code_bits < 24) stbi__grow_buffer_unsafe(z); - if (!STBI__RESTART(z->marker)) return 1; - stbi__jpeg_reset(z); - } - } - } - return 1; - } - } else { - if (z->scan_n == 1) { - int i,j; - int n = z->order[0]; - // non-interleaved data, we just need to process one block at a time, - // in trivial scanline order - // number of blocks to do just depends on how many actual "pixels" this - // component has, independent of interleaved MCU blocking and such - int w = (z->img_comp[n].x+7) >> 3; - int h = (z->img_comp[n].y+7) >> 3; - for (j=0; j < h; ++j) { - for (i=0; i < w; ++i) { - short *data = z->img_comp[n].coeff + 64 * (i + j * z->img_comp[n].coeff_w); - if (z->spec_start == 0) { - if (!stbi__jpeg_decode_block_prog_dc(z, data, &z->huff_dc[z->img_comp[n].hd], n)) - return 0; - } else { - int ha = z->img_comp[n].ha; - if (!stbi__jpeg_decode_block_prog_ac(z, data, &z->huff_ac[ha], z->fast_ac[ha])) - return 0; - } - // every data block is an MCU, so countdown the restart interval - if (--z->todo <= 0) { - if (z->code_bits < 24) stbi__grow_buffer_unsafe(z); - if (!STBI__RESTART(z->marker)) return 1; - stbi__jpeg_reset(z); - } - } - } - return 1; - } else { // interleaved - int i,j,k,x,y; - for (j=0; j < z->img_mcu_y; ++j) { - for (i=0; i < z->img_mcu_x; ++i) { - // scan an interleaved mcu... process scan_n components in order - for (k=0; k < z->scan_n; ++k) { - int n = z->order[k]; - // scan out an mcu's worth of this component; that's just determined - // by the basic H and V specified for the component - for (y=0; y < z->img_comp[n].v; ++y) { - for (x=0; x < z->img_comp[n].h; ++x) { - int x2 = (i*z->img_comp[n].h + x); - int y2 = (j*z->img_comp[n].v + y); - short *data = z->img_comp[n].coeff + 64 * (x2 + y2 * z->img_comp[n].coeff_w); - if (!stbi__jpeg_decode_block_prog_dc(z, data, &z->huff_dc[z->img_comp[n].hd], n)) - return 0; - } - } - } - // after all interleaved components, that's an interleaved MCU, - // so now count down the restart interval - if (--z->todo <= 0) { - if (z->code_bits < 24) stbi__grow_buffer_unsafe(z); - if (!STBI__RESTART(z->marker)) return 1; - stbi__jpeg_reset(z); - } - } - } - return 1; - } - } -} - -static void stbi__jpeg_dequantize(short *data, stbi__uint16 *dequant) -{ - int i; - for (i=0; i < 64; ++i) - data[i] *= dequant[i]; -} - -static void stbi__jpeg_finish(stbi__jpeg *z) -{ - if (z->progressive) { - // dequantize and idct the data - int i,j,n; - for (n=0; n < z->s->img_n; ++n) { - int w = (z->img_comp[n].x+7) >> 3; - int h = (z->img_comp[n].y+7) >> 3; - for (j=0; j < h; ++j) { - for (i=0; i < w; ++i) { - short *data = z->img_comp[n].coeff + 64 * (i + j * z->img_comp[n].coeff_w); - stbi__jpeg_dequantize(data, z->dequant[z->img_comp[n].tq]); - z->idct_block_kernel(z->img_comp[n].data+z->img_comp[n].w2*j*8+i*8, z->img_comp[n].w2, data); - } - } - } - } -} - -static int stbi__process_marker(stbi__jpeg *z, int m) -{ - int L; - switch (m) { - case STBI__MARKER_none: // no marker found - return stbi__err("expected marker","Corrupt JPEG"); - - case 0xDD: // DRI - specify restart interval - if (stbi__get16be(z->s) != 4) return stbi__err("bad DRI len","Corrupt JPEG"); - z->restart_interval = stbi__get16be(z->s); - return 1; - - case 0xDB: // DQT - define quantization table - L = stbi__get16be(z->s)-2; - while (L > 0) { - int q = stbi__get8(z->s); - int p = q >> 4, sixteen = (p != 0); - int t = q & 15,i; - if (p != 0 && p != 1) return stbi__err("bad DQT type","Corrupt JPEG"); - if (t > 3) return stbi__err("bad DQT table","Corrupt JPEG"); - - for (i=0; i < 64; ++i) - z->dequant[t][stbi__jpeg_dezigzag[i]] = (stbi__uint16)(sixteen ? stbi__get16be(z->s) : stbi__get8(z->s)); - L -= (sixteen ? 129 : 65); - } - return L==0; - - case 0xC4: // DHT - define huffman table - L = stbi__get16be(z->s)-2; - while (L > 0) { - stbi_uc *v; - int sizes[16],i,n=0; - int q = stbi__get8(z->s); - int tc = q >> 4; - int th = q & 15; - if (tc > 1 || th > 3) return stbi__err("bad DHT header","Corrupt JPEG"); - for (i=0; i < 16; ++i) { - sizes[i] = stbi__get8(z->s); - n += sizes[i]; - } - if(n > 256) return stbi__err("bad DHT header","Corrupt JPEG"); // Loop over i < n would write past end of values! - L -= 17; - if (tc == 0) { - if (!stbi__build_huffman(z->huff_dc+th, sizes)) return 0; - v = z->huff_dc[th].values; - } else { - if (!stbi__build_huffman(z->huff_ac+th, sizes)) return 0; - v = z->huff_ac[th].values; - } - for (i=0; i < n; ++i) - v[i] = stbi__get8(z->s); - if (tc != 0) - stbi__build_fast_ac(z->fast_ac[th], z->huff_ac + th); - L -= n; - } - return L==0; - } - - // check for comment block or APP blocks - if ((m >= 0xE0 && m <= 0xEF) || m == 0xFE) { - L = stbi__get16be(z->s); - if (L < 2) { - if (m == 0xFE) - return stbi__err("bad COM len","Corrupt JPEG"); - else - return stbi__err("bad APP len","Corrupt JPEG"); - } - L -= 2; - - if (m == 0xE0 && L >= 5) { // JFIF APP0 segment - static const unsigned char tag[5] = {'J','F','I','F','\0'}; - int ok = 1; - int i; - for (i=0; i < 5; ++i) - if (stbi__get8(z->s) != tag[i]) - ok = 0; - L -= 5; - if (ok) - z->jfif = 1; - } else if (m == 0xEE && L >= 12) { // Adobe APP14 segment - static const unsigned char tag[6] = {'A','d','o','b','e','\0'}; - int ok = 1; - int i; - for (i=0; i < 6; ++i) - if (stbi__get8(z->s) != tag[i]) - ok = 0; - L -= 6; - if (ok) { - stbi__get8(z->s); // version - stbi__get16be(z->s); // flags0 - stbi__get16be(z->s); // flags1 - z->app14_color_transform = stbi__get8(z->s); // color transform - L -= 6; - } - } - - stbi__skip(z->s, L); - return 1; - } - - return stbi__err("unknown marker","Corrupt JPEG"); -} - -// after we see SOS -static int stbi__process_scan_header(stbi__jpeg *z) -{ - int i; - int Ls = stbi__get16be(z->s); - z->scan_n = stbi__get8(z->s); - if (z->scan_n < 1 || z->scan_n > 4 || z->scan_n > (int) z->s->img_n) return stbi__err("bad SOS component count","Corrupt JPEG"); - if (Ls != 6+2*z->scan_n) return stbi__err("bad SOS len","Corrupt JPEG"); - for (i=0; i < z->scan_n; ++i) { - int id = stbi__get8(z->s), which; - int q = stbi__get8(z->s); - for (which = 0; which < z->s->img_n; ++which) - if (z->img_comp[which].id == id) - break; - if (which == z->s->img_n) return 0; // no match - z->img_comp[which].hd = q >> 4; if (z->img_comp[which].hd > 3) return stbi__err("bad DC huff","Corrupt JPEG"); - z->img_comp[which].ha = q & 15; if (z->img_comp[which].ha > 3) return stbi__err("bad AC huff","Corrupt JPEG"); - z->order[i] = which; - } - - { - int aa; - z->spec_start = stbi__get8(z->s); - z->spec_end = stbi__get8(z->s); // should be 63, but might be 0 - aa = stbi__get8(z->s); - z->succ_high = (aa >> 4); - z->succ_low = (aa & 15); - if (z->progressive) { - if (z->spec_start > 63 || z->spec_end > 63 || z->spec_start > z->spec_end || z->succ_high > 13 || z->succ_low > 13) - return stbi__err("bad SOS", "Corrupt JPEG"); - } else { - if (z->spec_start != 0) return stbi__err("bad SOS","Corrupt JPEG"); - if (z->succ_high != 0 || z->succ_low != 0) return stbi__err("bad SOS","Corrupt JPEG"); - z->spec_end = 63; - } - } - - return 1; -} - -static int stbi__free_jpeg_components(stbi__jpeg *z, int ncomp, int why) -{ - int i; - for (i=0; i < ncomp; ++i) { - if (z->img_comp[i].raw_data) { - STBI_FREE(z->img_comp[i].raw_data); - z->img_comp[i].raw_data = NULL; - z->img_comp[i].data = NULL; - } - if (z->img_comp[i].raw_coeff) { - STBI_FREE(z->img_comp[i].raw_coeff); - z->img_comp[i].raw_coeff = 0; - z->img_comp[i].coeff = 0; - } - if (z->img_comp[i].linebuf) { - STBI_FREE(z->img_comp[i].linebuf); - z->img_comp[i].linebuf = NULL; - } - } - return why; -} - -static int stbi__process_frame_header(stbi__jpeg *z, int scan) -{ - stbi__context *s = z->s; - int Lf,p,i,q, h_max=1,v_max=1,c; - Lf = stbi__get16be(s); if (Lf < 11) return stbi__err("bad SOF len","Corrupt JPEG"); // JPEG - p = stbi__get8(s); if (p != 8) return stbi__err("only 8-bit","JPEG format not supported: 8-bit only"); // JPEG baseline - s->img_y = stbi__get16be(s); if (s->img_y == 0) return stbi__err("no header height", "JPEG format not supported: delayed height"); // Legal, but we don't handle it--but neither does IJG - s->img_x = stbi__get16be(s); if (s->img_x == 0) return stbi__err("0 width","Corrupt JPEG"); // JPEG requires - if (s->img_y > STBI_MAX_DIMENSIONS) return stbi__err("too large","Very large image (corrupt?)"); - if (s->img_x > STBI_MAX_DIMENSIONS) return stbi__err("too large","Very large image (corrupt?)"); - c = stbi__get8(s); - if (c != 3 && c != 1 && c != 4) return stbi__err("bad component count","Corrupt JPEG"); - s->img_n = c; - for (i=0; i < c; ++i) { - z->img_comp[i].data = NULL; - z->img_comp[i].linebuf = NULL; - } - - if (Lf != 8+3*s->img_n) return stbi__err("bad SOF len","Corrupt JPEG"); - - z->rgb = 0; - for (i=0; i < s->img_n; ++i) { - static const unsigned char rgb[3] = { 'R', 'G', 'B' }; - z->img_comp[i].id = stbi__get8(s); - if (s->img_n == 3 && z->img_comp[i].id == rgb[i]) - ++z->rgb; - q = stbi__get8(s); - z->img_comp[i].h = (q >> 4); if (!z->img_comp[i].h || z->img_comp[i].h > 4) return stbi__err("bad H","Corrupt JPEG"); - z->img_comp[i].v = q & 15; if (!z->img_comp[i].v || z->img_comp[i].v > 4) return stbi__err("bad V","Corrupt JPEG"); - z->img_comp[i].tq = stbi__get8(s); if (z->img_comp[i].tq > 3) return stbi__err("bad TQ","Corrupt JPEG"); - } - - if (scan != STBI__SCAN_load) return 1; - - if (!stbi__mad3sizes_valid(s->img_x, s->img_y, s->img_n, 0)) return stbi__err("too large", "Image too large to decode"); - - for (i=0; i < s->img_n; ++i) { - if (z->img_comp[i].h > h_max) h_max = z->img_comp[i].h; - if (z->img_comp[i].v > v_max) v_max = z->img_comp[i].v; - } - - // check that plane subsampling factors are integer ratios; our resamplers can't deal with fractional ratios - // and I've never seen a non-corrupted JPEG file actually use them - for (i=0; i < s->img_n; ++i) { - if (h_max % z->img_comp[i].h != 0) return stbi__err("bad H","Corrupt JPEG"); - if (v_max % z->img_comp[i].v != 0) return stbi__err("bad V","Corrupt JPEG"); - } - - // compute interleaved mcu info - z->img_h_max = h_max; - z->img_v_max = v_max; - z->img_mcu_w = h_max * 8; - z->img_mcu_h = v_max * 8; - // these sizes can't be more than 17 bits - z->img_mcu_x = (s->img_x + z->img_mcu_w-1) / z->img_mcu_w; - z->img_mcu_y = (s->img_y + z->img_mcu_h-1) / z->img_mcu_h; - - for (i=0; i < s->img_n; ++i) { - // number of effective pixels (e.g. for non-interleaved MCU) - z->img_comp[i].x = (s->img_x * z->img_comp[i].h + h_max-1) / h_max; - z->img_comp[i].y = (s->img_y * z->img_comp[i].v + v_max-1) / v_max; - // to simplify generation, we'll allocate enough memory to decode - // the bogus oversized data from using interleaved MCUs and their - // big blocks (e.g. a 16x16 iMCU on an image of width 33); we won't - // discard the extra data until colorspace conversion - // - // img_mcu_x, img_mcu_y: <=17 bits; comp[i].h and .v are <=4 (checked earlier) - // so these muls can't overflow with 32-bit ints (which we require) - z->img_comp[i].w2 = z->img_mcu_x * z->img_comp[i].h * 8; - z->img_comp[i].h2 = z->img_mcu_y * z->img_comp[i].v * 8; - z->img_comp[i].coeff = 0; - z->img_comp[i].raw_coeff = 0; - z->img_comp[i].linebuf = NULL; - z->img_comp[i].raw_data = stbi__malloc_mad2(z->img_comp[i].w2, z->img_comp[i].h2, 15); - if (z->img_comp[i].raw_data == NULL) - return stbi__free_jpeg_components(z, i+1, stbi__err("outofmem", "Out of memory")); - // align blocks for idct using mmx/sse - z->img_comp[i].data = (stbi_uc*) (((size_t) z->img_comp[i].raw_data + 15) & ~15); - if (z->progressive) { - // w2, h2 are multiples of 8 (see above) - z->img_comp[i].coeff_w = z->img_comp[i].w2 / 8; - z->img_comp[i].coeff_h = z->img_comp[i].h2 / 8; - z->img_comp[i].raw_coeff = stbi__malloc_mad3(z->img_comp[i].w2, z->img_comp[i].h2, sizeof(short), 15); - if (z->img_comp[i].raw_coeff == NULL) - return stbi__free_jpeg_components(z, i+1, stbi__err("outofmem", "Out of memory")); - z->img_comp[i].coeff = (short*) (((size_t) z->img_comp[i].raw_coeff + 15) & ~15); - } - } - - return 1; -} - -// use comparisons since in some cases we handle more than one case (e.g. SOF) -#define stbi__DNL(x) ((x) == 0xdc) -#define stbi__SOI(x) ((x) == 0xd8) -#define stbi__EOI(x) ((x) == 0xd9) -#define stbi__SOF(x) ((x) == 0xc0 || (x) == 0xc1 || (x) == 0xc2) -#define stbi__SOS(x) ((x) == 0xda) - -#define stbi__SOF_progressive(x) ((x) == 0xc2) - -static int stbi__decode_jpeg_header(stbi__jpeg *z, int scan) -{ - int m; - z->jfif = 0; - z->app14_color_transform = -1; // valid values are 0,1,2 - z->marker = STBI__MARKER_none; // initialize cached marker to empty - m = stbi__get_marker(z); - if (!stbi__SOI(m)) return stbi__err("no SOI","Corrupt JPEG"); - if (scan == STBI__SCAN_type) return 1; - m = stbi__get_marker(z); - while (!stbi__SOF(m)) { - if (!stbi__process_marker(z,m)) return 0; - m = stbi__get_marker(z); - while (m == STBI__MARKER_none) { - // some files have extra padding after their blocks, so ok, we'll scan - if (stbi__at_eof(z->s)) return stbi__err("no SOF", "Corrupt JPEG"); - m = stbi__get_marker(z); - } - } - z->progressive = stbi__SOF_progressive(m); - if (!stbi__process_frame_header(z, scan)) return 0; - return 1; -} - -static int stbi__skip_jpeg_junk_at_end(stbi__jpeg *j) -{ - // some JPEGs have junk at end, skip over it but if we find what looks - // like a valid marker, resume there - while (!stbi__at_eof(j->s)) { - int x = stbi__get8(j->s); - while (x == 255) { // might be a marker - if (stbi__at_eof(j->s)) return STBI__MARKER_none; - x = stbi__get8(j->s); - if (x != 0x00 && x != 0xff) { - // not a stuffed zero or lead-in to another marker, looks - // like an actual marker, return it - return x; - } - // stuffed zero has x=0 now which ends the loop, meaning we go - // back to regular scan loop. - // repeated 0xff keeps trying to read the next byte of the marker. - } - } - return STBI__MARKER_none; -} - -// decode image to YCbCr format -static int stbi__decode_jpeg_image(stbi__jpeg *j) -{ - int m; - for (m = 0; m < 4; m++) { - j->img_comp[m].raw_data = NULL; - j->img_comp[m].raw_coeff = NULL; - } - j->restart_interval = 0; - if (!stbi__decode_jpeg_header(j, STBI__SCAN_load)) return 0; - m = stbi__get_marker(j); - while (!stbi__EOI(m)) { - if (stbi__SOS(m)) { - if (!stbi__process_scan_header(j)) return 0; - if (!stbi__parse_entropy_coded_data(j)) return 0; - if (j->marker == STBI__MARKER_none ) { - j->marker = stbi__skip_jpeg_junk_at_end(j); - // if we reach eof without hitting a marker, stbi__get_marker() below will fail and we'll eventually return 0 - } - m = stbi__get_marker(j); - if (STBI__RESTART(m)) - m = stbi__get_marker(j); - } else if (stbi__DNL(m)) { - int Ld = stbi__get16be(j->s); - stbi__uint32 NL = stbi__get16be(j->s); - if (Ld != 4) return stbi__err("bad DNL len", "Corrupt JPEG"); - if (NL != j->s->img_y) return stbi__err("bad DNL height", "Corrupt JPEG"); - m = stbi__get_marker(j); - } else { - if (!stbi__process_marker(j, m)) return 1; - m = stbi__get_marker(j); - } - } - if (j->progressive) - stbi__jpeg_finish(j); - return 1; -} - -// static jfif-centered resampling (across block boundaries) - -typedef stbi_uc *(*resample_row_func)(stbi_uc *out, stbi_uc *in0, stbi_uc *in1, - int w, int hs); - -#define stbi__div4(x) ((stbi_uc) ((x) >> 2)) - -static stbi_uc *resample_row_1(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs) -{ - STBI_NOTUSED(out); - STBI_NOTUSED(in_far); - STBI_NOTUSED(w); - STBI_NOTUSED(hs); - return in_near; -} - -static stbi_uc* stbi__resample_row_v_2(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs) -{ - // need to generate two samples vertically for every one in input - int i; - STBI_NOTUSED(hs); - for (i=0; i < w; ++i) - out[i] = stbi__div4(3*in_near[i] + in_far[i] + 2); - return out; -} - -static stbi_uc* stbi__resample_row_h_2(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs) -{ - // need to generate two samples horizontally for every one in input - int i; - stbi_uc *input = in_near; - - if (w == 1) { - // if only one sample, can't do any interpolation - out[0] = out[1] = input[0]; - return out; - } - - out[0] = input[0]; - out[1] = stbi__div4(input[0]*3 + input[1] + 2); - for (i=1; i < w-1; ++i) { - int n = 3*input[i]+2; - out[i*2+0] = stbi__div4(n+input[i-1]); - out[i*2+1] = stbi__div4(n+input[i+1]); - } - out[i*2+0] = stbi__div4(input[w-2]*3 + input[w-1] + 2); - out[i*2+1] = input[w-1]; - - STBI_NOTUSED(in_far); - STBI_NOTUSED(hs); - - return out; -} - -#define stbi__div16(x) ((stbi_uc) ((x) >> 4)) - -static stbi_uc *stbi__resample_row_hv_2(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs) -{ - // need to generate 2x2 samples for every one in input - int i,t0,t1; - if (w == 1) { - out[0] = out[1] = stbi__div4(3*in_near[0] + in_far[0] + 2); - return out; - } - - t1 = 3*in_near[0] + in_far[0]; - out[0] = stbi__div4(t1+2); - for (i=1; i < w; ++i) { - t0 = t1; - t1 = 3*in_near[i]+in_far[i]; - out[i*2-1] = stbi__div16(3*t0 + t1 + 8); - out[i*2 ] = stbi__div16(3*t1 + t0 + 8); - } - out[w*2-1] = stbi__div4(t1+2); - - STBI_NOTUSED(hs); - - return out; -} - -#if defined(STBI_SSE2) || defined(STBI_NEON) -static stbi_uc *stbi__resample_row_hv_2_simd(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs) -{ - // need to generate 2x2 samples for every one in input - int i=0,t0,t1; - - if (w == 1) { - out[0] = out[1] = stbi__div4(3*in_near[0] + in_far[0] + 2); - return out; - } - - t1 = 3*in_near[0] + in_far[0]; - // process groups of 8 pixels for as long as we can. - // note we can't handle the last pixel in a row in this loop - // because we need to handle the filter boundary conditions. - for (; i < ((w-1) & ~7); i += 8) { -#if defined(STBI_SSE2) - // load and perform the vertical filtering pass - // this uses 3*x + y = 4*x + (y - x) - __m128i zero = _mm_setzero_si128(); - __m128i farb = _mm_loadl_epi64((__m128i *) (in_far + i)); - __m128i nearb = _mm_loadl_epi64((__m128i *) (in_near + i)); - __m128i farw = _mm_unpacklo_epi8(farb, zero); - __m128i nearw = _mm_unpacklo_epi8(nearb, zero); - __m128i diff = _mm_sub_epi16(farw, nearw); - __m128i nears = _mm_slli_epi16(nearw, 2); - __m128i curr = _mm_add_epi16(nears, diff); // current row - - // horizontal filter works the same based on shifted vers of current - // row. "prev" is current row shifted right by 1 pixel; we need to - // insert the previous pixel value (from t1). - // "next" is current row shifted left by 1 pixel, with first pixel - // of next block of 8 pixels added in. - __m128i prv0 = _mm_slli_si128(curr, 2); - __m128i nxt0 = _mm_srli_si128(curr, 2); - __m128i prev = _mm_insert_epi16(prv0, t1, 0); - __m128i next = _mm_insert_epi16(nxt0, 3*in_near[i+8] + in_far[i+8], 7); - - // horizontal filter, polyphase implementation since it's convenient: - // even pixels = 3*cur + prev = cur*4 + (prev - cur) - // odd pixels = 3*cur + next = cur*4 + (next - cur) - // note the shared term. - __m128i bias = _mm_set1_epi16(8); - __m128i curs = _mm_slli_epi16(curr, 2); - __m128i prvd = _mm_sub_epi16(prev, curr); - __m128i nxtd = _mm_sub_epi16(next, curr); - __m128i curb = _mm_add_epi16(curs, bias); - __m128i even = _mm_add_epi16(prvd, curb); - __m128i odd = _mm_add_epi16(nxtd, curb); - - // interleave even and odd pixels, then undo scaling. - __m128i int0 = _mm_unpacklo_epi16(even, odd); - __m128i int1 = _mm_unpackhi_epi16(even, odd); - __m128i de0 = _mm_srli_epi16(int0, 4); - __m128i de1 = _mm_srli_epi16(int1, 4); - - // pack and write output - __m128i outv = _mm_packus_epi16(de0, de1); - _mm_storeu_si128((__m128i *) (out + i*2), outv); -#elif defined(STBI_NEON) - // load and perform the vertical filtering pass - // this uses 3*x + y = 4*x + (y - x) - uint8x8_t farb = vld1_u8(in_far + i); - uint8x8_t nearb = vld1_u8(in_near + i); - int16x8_t diff = vreinterpretq_s16_u16(vsubl_u8(farb, nearb)); - int16x8_t nears = vreinterpretq_s16_u16(vshll_n_u8(nearb, 2)); - int16x8_t curr = vaddq_s16(nears, diff); // current row - - // horizontal filter works the same based on shifted vers of current - // row. "prev" is current row shifted right by 1 pixel; we need to - // insert the previous pixel value (from t1). - // "next" is current row shifted left by 1 pixel, with first pixel - // of next block of 8 pixels added in. - int16x8_t prv0 = vextq_s16(curr, curr, 7); - int16x8_t nxt0 = vextq_s16(curr, curr, 1); - int16x8_t prev = vsetq_lane_s16(t1, prv0, 0); - int16x8_t next = vsetq_lane_s16(3*in_near[i+8] + in_far[i+8], nxt0, 7); - - // horizontal filter, polyphase implementation since it's convenient: - // even pixels = 3*cur + prev = cur*4 + (prev - cur) - // odd pixels = 3*cur + next = cur*4 + (next - cur) - // note the shared term. - int16x8_t curs = vshlq_n_s16(curr, 2); - int16x8_t prvd = vsubq_s16(prev, curr); - int16x8_t nxtd = vsubq_s16(next, curr); - int16x8_t even = vaddq_s16(curs, prvd); - int16x8_t odd = vaddq_s16(curs, nxtd); - - // undo scaling and round, then store with even/odd phases interleaved - uint8x8x2_t o; - o.val[0] = vqrshrun_n_s16(even, 4); - o.val[1] = vqrshrun_n_s16(odd, 4); - vst2_u8(out + i*2, o); -#endif - - // "previous" value for next iter - t1 = 3*in_near[i+7] + in_far[i+7]; - } - - t0 = t1; - t1 = 3*in_near[i] + in_far[i]; - out[i*2] = stbi__div16(3*t1 + t0 + 8); - - for (++i; i < w; ++i) { - t0 = t1; - t1 = 3*in_near[i]+in_far[i]; - out[i*2-1] = stbi__div16(3*t0 + t1 + 8); - out[i*2 ] = stbi__div16(3*t1 + t0 + 8); - } - out[w*2-1] = stbi__div4(t1+2); - - STBI_NOTUSED(hs); - - return out; -} -#endif - -static stbi_uc *stbi__resample_row_generic(stbi_uc *out, stbi_uc *in_near, stbi_uc *in_far, int w, int hs) -{ - // resample with nearest-neighbor - int i,j; - STBI_NOTUSED(in_far); - for (i=0; i < w; ++i) - for (j=0; j < hs; ++j) - out[i*hs+j] = in_near[i]; - return out; -} - -// this is a reduced-precision calculation of YCbCr-to-RGB introduced -// to make sure the code produces the same results in both SIMD and scalar -#define stbi__float2fixed(x) (((int) ((x) * 4096.0f + 0.5f)) << 8) -static void stbi__YCbCr_to_RGB_row(stbi_uc *out, const stbi_uc *y, const stbi_uc *pcb, const stbi_uc *pcr, int count, int step) -{ - int i; - for (i=0; i < count; ++i) { - int y_fixed = (y[i] << 20) + (1<<19); // rounding - int r,g,b; - int cr = pcr[i] - 128; - int cb = pcb[i] - 128; - r = y_fixed + cr* stbi__float2fixed(1.40200f); - g = y_fixed + (cr*-stbi__float2fixed(0.71414f)) + ((cb*-stbi__float2fixed(0.34414f)) & 0xffff0000); - b = y_fixed + cb* stbi__float2fixed(1.77200f); - r >>= 20; - g >>= 20; - b >>= 20; - if ((unsigned) r > 255) { if (r < 0) r = 0; else r = 255; } - if ((unsigned) g > 255) { if (g < 0) g = 0; else g = 255; } - if ((unsigned) b > 255) { if (b < 0) b = 0; else b = 255; } - out[0] = (stbi_uc)r; - out[1] = (stbi_uc)g; - out[2] = (stbi_uc)b; - out[3] = 255; - out += step; - } -} - -#if defined(STBI_SSE2) || defined(STBI_NEON) -static void stbi__YCbCr_to_RGB_simd(stbi_uc *out, stbi_uc const *y, stbi_uc const *pcb, stbi_uc const *pcr, int count, int step) -{ - int i = 0; - -#ifdef STBI_SSE2 - // step == 3 is pretty ugly on the final interleave, and i'm not convinced - // it's useful in practice (you wouldn't use it for textures, for example). - // so just accelerate step == 4 case. - if (step == 4) { - // this is a fairly straightforward implementation and not super-optimized. - __m128i signflip = _mm_set1_epi8(-0x80); - __m128i cr_const0 = _mm_set1_epi16( (short) ( 1.40200f*4096.0f+0.5f)); - __m128i cr_const1 = _mm_set1_epi16( - (short) ( 0.71414f*4096.0f+0.5f)); - __m128i cb_const0 = _mm_set1_epi16( - (short) ( 0.34414f*4096.0f+0.5f)); - __m128i cb_const1 = _mm_set1_epi16( (short) ( 1.77200f*4096.0f+0.5f)); - __m128i y_bias = _mm_set1_epi8((char) (unsigned char) 128); - __m128i xw = _mm_set1_epi16(255); // alpha channel - - for (; i+7 < count; i += 8) { - // load - __m128i y_bytes = _mm_loadl_epi64((__m128i *) (y+i)); - __m128i cr_bytes = _mm_loadl_epi64((__m128i *) (pcr+i)); - __m128i cb_bytes = _mm_loadl_epi64((__m128i *) (pcb+i)); - __m128i cr_biased = _mm_xor_si128(cr_bytes, signflip); // -128 - __m128i cb_biased = _mm_xor_si128(cb_bytes, signflip); // -128 - - // unpack to short (and left-shift cr, cb by 8) - __m128i yw = _mm_unpacklo_epi8(y_bias, y_bytes); - __m128i crw = _mm_unpacklo_epi8(_mm_setzero_si128(), cr_biased); - __m128i cbw = _mm_unpacklo_epi8(_mm_setzero_si128(), cb_biased); - - // color transform - __m128i yws = _mm_srli_epi16(yw, 4); - __m128i cr0 = _mm_mulhi_epi16(cr_const0, crw); - __m128i cb0 = _mm_mulhi_epi16(cb_const0, cbw); - __m128i cb1 = _mm_mulhi_epi16(cbw, cb_const1); - __m128i cr1 = _mm_mulhi_epi16(crw, cr_const1); - __m128i rws = _mm_add_epi16(cr0, yws); - __m128i gwt = _mm_add_epi16(cb0, yws); - __m128i bws = _mm_add_epi16(yws, cb1); - __m128i gws = _mm_add_epi16(gwt, cr1); - - // descale - __m128i rw = _mm_srai_epi16(rws, 4); - __m128i bw = _mm_srai_epi16(bws, 4); - __m128i gw = _mm_srai_epi16(gws, 4); - - // back to byte, set up for transpose - __m128i brb = _mm_packus_epi16(rw, bw); - __m128i gxb = _mm_packus_epi16(gw, xw); - - // transpose to interleave channels - __m128i t0 = _mm_unpacklo_epi8(brb, gxb); - __m128i t1 = _mm_unpackhi_epi8(brb, gxb); - __m128i o0 = _mm_unpacklo_epi16(t0, t1); - __m128i o1 = _mm_unpackhi_epi16(t0, t1); - - // store - _mm_storeu_si128((__m128i *) (out + 0), o0); - _mm_storeu_si128((__m128i *) (out + 16), o1); - out += 32; - } - } -#endif - -#ifdef STBI_NEON - // in this version, step=3 support would be easy to add. but is there demand? - if (step == 4) { - // this is a fairly straightforward implementation and not super-optimized. - uint8x8_t signflip = vdup_n_u8(0x80); - int16x8_t cr_const0 = vdupq_n_s16( (short) ( 1.40200f*4096.0f+0.5f)); - int16x8_t cr_const1 = vdupq_n_s16( - (short) ( 0.71414f*4096.0f+0.5f)); - int16x8_t cb_const0 = vdupq_n_s16( - (short) ( 0.34414f*4096.0f+0.5f)); - int16x8_t cb_const1 = vdupq_n_s16( (short) ( 1.77200f*4096.0f+0.5f)); - - for (; i+7 < count; i += 8) { - // load - uint8x8_t y_bytes = vld1_u8(y + i); - uint8x8_t cr_bytes = vld1_u8(pcr + i); - uint8x8_t cb_bytes = vld1_u8(pcb + i); - int8x8_t cr_biased = vreinterpret_s8_u8(vsub_u8(cr_bytes, signflip)); - int8x8_t cb_biased = vreinterpret_s8_u8(vsub_u8(cb_bytes, signflip)); - - // expand to s16 - int16x8_t yws = vreinterpretq_s16_u16(vshll_n_u8(y_bytes, 4)); - int16x8_t crw = vshll_n_s8(cr_biased, 7); - int16x8_t cbw = vshll_n_s8(cb_biased, 7); - - // color transform - int16x8_t cr0 = vqdmulhq_s16(crw, cr_const0); - int16x8_t cb0 = vqdmulhq_s16(cbw, cb_const0); - int16x8_t cr1 = vqdmulhq_s16(crw, cr_const1); - int16x8_t cb1 = vqdmulhq_s16(cbw, cb_const1); - int16x8_t rws = vaddq_s16(yws, cr0); - int16x8_t gws = vaddq_s16(vaddq_s16(yws, cb0), cr1); - int16x8_t bws = vaddq_s16(yws, cb1); - - // undo scaling, round, convert to byte - uint8x8x4_t o; - o.val[0] = vqrshrun_n_s16(rws, 4); - o.val[1] = vqrshrun_n_s16(gws, 4); - o.val[2] = vqrshrun_n_s16(bws, 4); - o.val[3] = vdup_n_u8(255); - - // store, interleaving r/g/b/a - vst4_u8(out, o); - out += 8*4; - } - } -#endif - - for (; i < count; ++i) { - int y_fixed = (y[i] << 20) + (1<<19); // rounding - int r,g,b; - int cr = pcr[i] - 128; - int cb = pcb[i] - 128; - r = y_fixed + cr* stbi__float2fixed(1.40200f); - g = y_fixed + cr*-stbi__float2fixed(0.71414f) + ((cb*-stbi__float2fixed(0.34414f)) & 0xffff0000); - b = y_fixed + cb* stbi__float2fixed(1.77200f); - r >>= 20; - g >>= 20; - b >>= 20; - if ((unsigned) r > 255) { if (r < 0) r = 0; else r = 255; } - if ((unsigned) g > 255) { if (g < 0) g = 0; else g = 255; } - if ((unsigned) b > 255) { if (b < 0) b = 0; else b = 255; } - out[0] = (stbi_uc)r; - out[1] = (stbi_uc)g; - out[2] = (stbi_uc)b; - out[3] = 255; - out += step; - } -} -#endif - -// set up the kernels -static void stbi__setup_jpeg(stbi__jpeg *j) -{ - j->idct_block_kernel = stbi__idct_block; - j->YCbCr_to_RGB_kernel = stbi__YCbCr_to_RGB_row; - j->resample_row_hv_2_kernel = stbi__resample_row_hv_2; - -#ifdef STBI_SSE2 - if (stbi__sse2_available()) { - j->idct_block_kernel = stbi__idct_simd; - j->YCbCr_to_RGB_kernel = stbi__YCbCr_to_RGB_simd; - j->resample_row_hv_2_kernel = stbi__resample_row_hv_2_simd; - } -#endif - -#ifdef STBI_NEON - j->idct_block_kernel = stbi__idct_simd; - j->YCbCr_to_RGB_kernel = stbi__YCbCr_to_RGB_simd; - j->resample_row_hv_2_kernel = stbi__resample_row_hv_2_simd; -#endif -} - -// clean up the temporary component buffers -static void stbi__cleanup_jpeg(stbi__jpeg *j) -{ - stbi__free_jpeg_components(j, j->s->img_n, 0); -} - -typedef struct -{ - resample_row_func resample; - stbi_uc *line0,*line1; - int hs,vs; // expansion factor in each axis - int w_lores; // horizontal pixels pre-expansion - int ystep; // how far through vertical expansion we are - int ypos; // which pre-expansion row we're on -} stbi__resample; - -// fast 0..255 * 0..255 => 0..255 rounded multiplication -static stbi_uc stbi__blinn_8x8(stbi_uc x, stbi_uc y) -{ - unsigned int t = x*y + 128; - return (stbi_uc) ((t + (t >>8)) >> 8); -} - -static stbi_uc *load_jpeg_image(stbi__jpeg *z, int *out_x, int *out_y, int *comp, int req_comp) -{ - int n, decode_n, is_rgb; - z->s->img_n = 0; // make stbi__cleanup_jpeg safe - - // validate req_comp - if (req_comp < 0 || req_comp > 4) return stbi__errpuc("bad req_comp", "Internal error"); - - // load a jpeg image from whichever source, but leave in YCbCr format - if (!stbi__decode_jpeg_image(z)) { stbi__cleanup_jpeg(z); return NULL; } - - // determine actual number of components to generate - n = req_comp ? req_comp : z->s->img_n >= 3 ? 3 : 1; - - is_rgb = z->s->img_n == 3 && (z->rgb == 3 || (z->app14_color_transform == 0 && !z->jfif)); - - if (z->s->img_n == 3 && n < 3 && !is_rgb) - decode_n = 1; - else - decode_n = z->s->img_n; - - // nothing to do if no components requested; check this now to avoid - // accessing uninitialized coutput[0] later - if (decode_n <= 0) { stbi__cleanup_jpeg(z); return NULL; } - - // resample and color-convert - { - int k; - unsigned int i,j; - stbi_uc *output; - stbi_uc *coutput[4] = { NULL, NULL, NULL, NULL }; - - stbi__resample res_comp[4]; - - for (k=0; k < decode_n; ++k) { - stbi__resample *r = &res_comp[k]; - - // allocate line buffer big enough for upsampling off the edges - // with upsample factor of 4 - z->img_comp[k].linebuf = (stbi_uc *) stbi__malloc(z->s->img_x + 3); - if (!z->img_comp[k].linebuf) { stbi__cleanup_jpeg(z); return stbi__errpuc("outofmem", "Out of memory"); } - - r->hs = z->img_h_max / z->img_comp[k].h; - r->vs = z->img_v_max / z->img_comp[k].v; - r->ystep = r->vs >> 1; - r->w_lores = (z->s->img_x + r->hs-1) / r->hs; - r->ypos = 0; - r->line0 = r->line1 = z->img_comp[k].data; - - if (r->hs == 1 && r->vs == 1) r->resample = resample_row_1; - else if (r->hs == 1 && r->vs == 2) r->resample = stbi__resample_row_v_2; - else if (r->hs == 2 && r->vs == 1) r->resample = stbi__resample_row_h_2; - else if (r->hs == 2 && r->vs == 2) r->resample = z->resample_row_hv_2_kernel; - else r->resample = stbi__resample_row_generic; - } - - // can't error after this so, this is safe - output = (stbi_uc *) stbi__malloc_mad3(n, z->s->img_x, z->s->img_y, 1); - if (!output) { stbi__cleanup_jpeg(z); return stbi__errpuc("outofmem", "Out of memory"); } - - // now go ahead and resample - for (j=0; j < z->s->img_y; ++j) { - stbi_uc *out = output + n * z->s->img_x * j; - for (k=0; k < decode_n; ++k) { - stbi__resample *r = &res_comp[k]; - int y_bot = r->ystep >= (r->vs >> 1); - coutput[k] = r->resample(z->img_comp[k].linebuf, - y_bot ? r->line1 : r->line0, - y_bot ? r->line0 : r->line1, - r->w_lores, r->hs); - if (++r->ystep >= r->vs) { - r->ystep = 0; - r->line0 = r->line1; - if (++r->ypos < z->img_comp[k].y) - r->line1 += z->img_comp[k].w2; - } - } - if (n >= 3) { - stbi_uc *y = coutput[0]; - if (z->s->img_n == 3) { - if (is_rgb) { - for (i=0; i < z->s->img_x; ++i) { - out[0] = y[i]; - out[1] = coutput[1][i]; - out[2] = coutput[2][i]; - out[3] = 255; - out += n; - } - } else { - z->YCbCr_to_RGB_kernel(out, y, coutput[1], coutput[2], z->s->img_x, n); - } - } else if (z->s->img_n == 4) { - if (z->app14_color_transform == 0) { // CMYK - for (i=0; i < z->s->img_x; ++i) { - stbi_uc m = coutput[3][i]; - out[0] = stbi__blinn_8x8(coutput[0][i], m); - out[1] = stbi__blinn_8x8(coutput[1][i], m); - out[2] = stbi__blinn_8x8(coutput[2][i], m); - out[3] = 255; - out += n; - } - } else if (z->app14_color_transform == 2) { // YCCK - z->YCbCr_to_RGB_kernel(out, y, coutput[1], coutput[2], z->s->img_x, n); - for (i=0; i < z->s->img_x; ++i) { - stbi_uc m = coutput[3][i]; - out[0] = stbi__blinn_8x8(255 - out[0], m); - out[1] = stbi__blinn_8x8(255 - out[1], m); - out[2] = stbi__blinn_8x8(255 - out[2], m); - out += n; - } - } else { // YCbCr + alpha? Ignore the fourth channel for now - z->YCbCr_to_RGB_kernel(out, y, coutput[1], coutput[2], z->s->img_x, n); - } - } else - for (i=0; i < z->s->img_x; ++i) { - out[0] = out[1] = out[2] = y[i]; - out[3] = 255; // not used if n==3 - out += n; - } - } else { - if (is_rgb) { - if (n == 1) - for (i=0; i < z->s->img_x; ++i) - *out++ = stbi__compute_y(coutput[0][i], coutput[1][i], coutput[2][i]); - else { - for (i=0; i < z->s->img_x; ++i, out += 2) { - out[0] = stbi__compute_y(coutput[0][i], coutput[1][i], coutput[2][i]); - out[1] = 255; - } - } - } else if (z->s->img_n == 4 && z->app14_color_transform == 0) { - for (i=0; i < z->s->img_x; ++i) { - stbi_uc m = coutput[3][i]; - stbi_uc r = stbi__blinn_8x8(coutput[0][i], m); - stbi_uc g = stbi__blinn_8x8(coutput[1][i], m); - stbi_uc b = stbi__blinn_8x8(coutput[2][i], m); - out[0] = stbi__compute_y(r, g, b); - out[1] = 255; - out += n; - } - } else if (z->s->img_n == 4 && z->app14_color_transform == 2) { - for (i=0; i < z->s->img_x; ++i) { - out[0] = stbi__blinn_8x8(255 - coutput[0][i], coutput[3][i]); - out[1] = 255; - out += n; - } - } else { - stbi_uc *y = coutput[0]; - if (n == 1) - for (i=0; i < z->s->img_x; ++i) out[i] = y[i]; - else - for (i=0; i < z->s->img_x; ++i) { *out++ = y[i]; *out++ = 255; } - } - } - } - stbi__cleanup_jpeg(z); - *out_x = z->s->img_x; - *out_y = z->s->img_y; - if (comp) *comp = z->s->img_n >= 3 ? 3 : 1; // report original components, not output - return output; - } -} - -static void *stbi__jpeg_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - unsigned char* result; - stbi__jpeg* j = (stbi__jpeg*) stbi__malloc(sizeof(stbi__jpeg)); - if (!j) return stbi__errpuc("outofmem", "Out of memory"); - memset(j, 0, sizeof(stbi__jpeg)); - STBI_NOTUSED(ri); - j->s = s; - stbi__setup_jpeg(j); - result = load_jpeg_image(j, x,y,comp,req_comp); - STBI_FREE(j); - return result; -} - -static int stbi__jpeg_test(stbi__context *s) -{ - int r; - stbi__jpeg* j = (stbi__jpeg*)stbi__malloc(sizeof(stbi__jpeg)); - if (!j) return stbi__err("outofmem", "Out of memory"); - memset(j, 0, sizeof(stbi__jpeg)); - j->s = s; - stbi__setup_jpeg(j); - r = stbi__decode_jpeg_header(j, STBI__SCAN_type); - stbi__rewind(s); - STBI_FREE(j); - return r; -} - -static int stbi__jpeg_info_raw(stbi__jpeg *j, int *x, int *y, int *comp) -{ - if (!stbi__decode_jpeg_header(j, STBI__SCAN_header)) { - stbi__rewind( j->s ); - return 0; - } - if (x) *x = j->s->img_x; - if (y) *y = j->s->img_y; - if (comp) *comp = j->s->img_n >= 3 ? 3 : 1; - return 1; -} - -static int stbi__jpeg_info(stbi__context *s, int *x, int *y, int *comp) -{ - int result; - stbi__jpeg* j = (stbi__jpeg*) (stbi__malloc(sizeof(stbi__jpeg))); - if (!j) return stbi__err("outofmem", "Out of memory"); - memset(j, 0, sizeof(stbi__jpeg)); - j->s = s; - result = stbi__jpeg_info_raw(j, x, y, comp); - STBI_FREE(j); - return result; -} -#endif - -// public domain zlib decode v0.2 Sean Barrett 2006-11-18 -// simple implementation -// - all input must be provided in an upfront buffer -// - all output is written to a single output buffer (can malloc/realloc) -// performance -// - fast huffman - -#ifndef STBI_NO_ZLIB - -// fast-way is faster to check than jpeg huffman, but slow way is slower -#define STBI__ZFAST_BITS 9 // accelerate all cases in default tables -#define STBI__ZFAST_MASK ((1 << STBI__ZFAST_BITS) - 1) -#define STBI__ZNSYMS 288 // number of symbols in literal/length alphabet - -// zlib-style huffman encoding -// (jpegs packs from left, zlib from right, so can't share code) -typedef struct -{ - stbi__uint16 fast[1 << STBI__ZFAST_BITS]; - stbi__uint16 firstcode[16]; - int maxcode[17]; - stbi__uint16 firstsymbol[16]; - stbi_uc size[STBI__ZNSYMS]; - stbi__uint16 value[STBI__ZNSYMS]; -} stbi__zhuffman; - -stbi_inline static int stbi__bitreverse16(int n) -{ - n = ((n & 0xAAAA) >> 1) | ((n & 0x5555) << 1); - n = ((n & 0xCCCC) >> 2) | ((n & 0x3333) << 2); - n = ((n & 0xF0F0) >> 4) | ((n & 0x0F0F) << 4); - n = ((n & 0xFF00) >> 8) | ((n & 0x00FF) << 8); - return n; -} - -stbi_inline static int stbi__bit_reverse(int v, int bits) -{ - STBI_ASSERT(bits <= 16); - // to bit reverse n bits, reverse 16 and shift - // e.g. 11 bits, bit reverse and shift away 5 - return stbi__bitreverse16(v) >> (16-bits); -} - -static int stbi__zbuild_huffman(stbi__zhuffman *z, const stbi_uc *sizelist, int num) -{ - int i,k=0; - int code, next_code[16], sizes[17]; - - // DEFLATE spec for generating codes - memset(sizes, 0, sizeof(sizes)); - memset(z->fast, 0, sizeof(z->fast)); - for (i=0; i < num; ++i) - ++sizes[sizelist[i]]; - sizes[0] = 0; - for (i=1; i < 16; ++i) - if (sizes[i] > (1 << i)) - return stbi__err("bad sizes", "Corrupt PNG"); - code = 0; - for (i=1; i < 16; ++i) { - next_code[i] = code; - z->firstcode[i] = (stbi__uint16) code; - z->firstsymbol[i] = (stbi__uint16) k; - code = (code + sizes[i]); - if (sizes[i]) - if (code-1 >= (1 << i)) return stbi__err("bad codelengths","Corrupt PNG"); - z->maxcode[i] = code << (16-i); // preshift for inner loop - code <<= 1; - k += sizes[i]; - } - z->maxcode[16] = 0x10000; // sentinel - for (i=0; i < num; ++i) { - int s = sizelist[i]; - if (s) { - int c = next_code[s] - z->firstcode[s] + z->firstsymbol[s]; - stbi__uint16 fastv = (stbi__uint16) ((s << 9) | i); - z->size [c] = (stbi_uc ) s; - z->value[c] = (stbi__uint16) i; - if (s <= STBI__ZFAST_BITS) { - int j = stbi__bit_reverse(next_code[s],s); - while (j < (1 << STBI__ZFAST_BITS)) { - z->fast[j] = fastv; - j += (1 << s); - } - } - ++next_code[s]; - } - } - return 1; -} - -// zlib-from-memory implementation for PNG reading -// because PNG allows splitting the zlib stream arbitrarily, -// and it's annoying structurally to have PNG call ZLIB call PNG, -// we require PNG read all the IDATs and combine them into a single -// memory buffer - -typedef struct -{ - stbi_uc *zbuffer, *zbuffer_end; - int num_bits; - stbi__uint32 code_buffer; - - char *zout; - char *zout_start; - char *zout_end; - int z_expandable; - - stbi__zhuffman z_length, z_distance; -} stbi__zbuf; - -stbi_inline static int stbi__zeof(stbi__zbuf *z) -{ - return (z->zbuffer >= z->zbuffer_end); -} - -stbi_inline static stbi_uc stbi__zget8(stbi__zbuf *z) -{ - return stbi__zeof(z) ? 0 : *z->zbuffer++; -} - -static void stbi__fill_bits(stbi__zbuf *z) -{ - do { - if (z->code_buffer >= (1U << z->num_bits)) { - z->zbuffer = z->zbuffer_end; /* treat this as EOF so we fail. */ - return; - } - z->code_buffer |= (unsigned int) stbi__zget8(z) << z->num_bits; - z->num_bits += 8; - } while (z->num_bits <= 24); -} - -stbi_inline static unsigned int stbi__zreceive(stbi__zbuf *z, int n) -{ - unsigned int k; - if (z->num_bits < n) stbi__fill_bits(z); - k = z->code_buffer & ((1 << n) - 1); - z->code_buffer >>= n; - z->num_bits -= n; - return k; -} - -static int stbi__zhuffman_decode_slowpath(stbi__zbuf *a, stbi__zhuffman *z) -{ - int b,s,k; - // not resolved by fast table, so compute it the slow way - // use jpeg approach, which requires MSbits at top - k = stbi__bit_reverse(a->code_buffer, 16); - for (s=STBI__ZFAST_BITS+1; ; ++s) - if (k < z->maxcode[s]) - break; - if (s >= 16) return -1; // invalid code! - // code size is s, so: - b = (k >> (16-s)) - z->firstcode[s] + z->firstsymbol[s]; - if (b >= STBI__ZNSYMS) return -1; // some data was corrupt somewhere! - if (z->size[b] != s) return -1; // was originally an assert, but report failure instead. - a->code_buffer >>= s; - a->num_bits -= s; - return z->value[b]; -} - -stbi_inline static int stbi__zhuffman_decode(stbi__zbuf *a, stbi__zhuffman *z) -{ - int b,s; - if (a->num_bits < 16) { - if (stbi__zeof(a)) { - return -1; /* report error for unexpected end of data. */ - } - stbi__fill_bits(a); - } - b = z->fast[a->code_buffer & STBI__ZFAST_MASK]; - if (b) { - s = b >> 9; - a->code_buffer >>= s; - a->num_bits -= s; - return b & 511; - } - return stbi__zhuffman_decode_slowpath(a, z); -} - -static int stbi__zexpand(stbi__zbuf *z, char *zout, int n) // need to make room for n bytes -{ - char *q; - unsigned int cur, limit, old_limit; - z->zout = zout; - if (!z->z_expandable) return stbi__err("output buffer limit","Corrupt PNG"); - cur = (unsigned int) (z->zout - z->zout_start); - limit = old_limit = (unsigned) (z->zout_end - z->zout_start); - if (UINT_MAX - cur < (unsigned) n) return stbi__err("outofmem", "Out of memory"); - while (cur + n > limit) { - if(limit > UINT_MAX / 2) return stbi__err("outofmem", "Out of memory"); - limit *= 2; - } - q = (char *) STBI_REALLOC_SIZED(z->zout_start, old_limit, limit); - STBI_NOTUSED(old_limit); - if (q == NULL) return stbi__err("outofmem", "Out of memory"); - z->zout_start = q; - z->zout = q + cur; - z->zout_end = q + limit; - return 1; -} - -static const int stbi__zlength_base[31] = { - 3,4,5,6,7,8,9,10,11,13, - 15,17,19,23,27,31,35,43,51,59, - 67,83,99,115,131,163,195,227,258,0,0 }; - -static const int stbi__zlength_extra[31]= -{ 0,0,0,0,0,0,0,0,1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,0,0,0 }; - -static const int stbi__zdist_base[32] = { 1,2,3,4,5,7,9,13,17,25,33,49,65,97,129,193, -257,385,513,769,1025,1537,2049,3073,4097,6145,8193,12289,16385,24577,0,0}; - -static const int stbi__zdist_extra[32] = -{ 0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13}; - -static int stbi__parse_huffman_block(stbi__zbuf *a) -{ - char *zout = a->zout; - for(;;) { - int z = stbi__zhuffman_decode(a, &a->z_length); - if (z < 256) { - if (z < 0) return stbi__err("bad huffman code","Corrupt PNG"); // error in huffman codes - if (zout >= a->zout_end) { - if (!stbi__zexpand(a, zout, 1)) return 0; - zout = a->zout; - } - *zout++ = (char) z; - } else { - stbi_uc *p; - int len,dist; - if (z == 256) { - a->zout = zout; - return 1; - } - if (z >= 286) return stbi__err("bad huffman code","Corrupt PNG"); // per DEFLATE, length codes 286 and 287 must not appear in compressed data - z -= 257; - len = stbi__zlength_base[z]; - if (stbi__zlength_extra[z]) len += stbi__zreceive(a, stbi__zlength_extra[z]); - z = stbi__zhuffman_decode(a, &a->z_distance); - if (z < 0 || z >= 30) return stbi__err("bad huffman code","Corrupt PNG"); // per DEFLATE, distance codes 30 and 31 must not appear in compressed data - dist = stbi__zdist_base[z]; - if (stbi__zdist_extra[z]) dist += stbi__zreceive(a, stbi__zdist_extra[z]); - if (zout - a->zout_start < dist) return stbi__err("bad dist","Corrupt PNG"); - if (zout + len > a->zout_end) { - if (!stbi__zexpand(a, zout, len)) return 0; - zout = a->zout; - } - p = (stbi_uc *) (zout - dist); - if (dist == 1) { // run of one byte; common in images. - stbi_uc v = *p; - if (len) { do *zout++ = v; while (--len); } - } else { - if (len) { do *zout++ = *p++; while (--len); } - } - } - } -} - -static int stbi__compute_huffman_codes(stbi__zbuf *a) -{ - static const stbi_uc length_dezigzag[19] = { 16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15 }; - stbi__zhuffman z_codelength; - stbi_uc lencodes[286+32+137];//padding for maximum single op - stbi_uc codelength_sizes[19]; - int i,n; - - int hlit = stbi__zreceive(a,5) + 257; - int hdist = stbi__zreceive(a,5) + 1; - int hclen = stbi__zreceive(a,4) + 4; - int ntot = hlit + hdist; - - memset(codelength_sizes, 0, sizeof(codelength_sizes)); - for (i=0; i < hclen; ++i) { - int s = stbi__zreceive(a,3); - codelength_sizes[length_dezigzag[i]] = (stbi_uc) s; - } - if (!stbi__zbuild_huffman(&z_codelength, codelength_sizes, 19)) return 0; - - n = 0; - while (n < ntot) { - int c = stbi__zhuffman_decode(a, &z_codelength); - if (c < 0 || c >= 19) return stbi__err("bad codelengths", "Corrupt PNG"); - if (c < 16) - lencodes[n++] = (stbi_uc) c; - else { - stbi_uc fill = 0; - if (c == 16) { - c = stbi__zreceive(a,2)+3; - if (n == 0) return stbi__err("bad codelengths", "Corrupt PNG"); - fill = lencodes[n-1]; - } else if (c == 17) { - c = stbi__zreceive(a,3)+3; - } else if (c == 18) { - c = stbi__zreceive(a,7)+11; - } else { - return stbi__err("bad codelengths", "Corrupt PNG"); - } - if (ntot - n < c) return stbi__err("bad codelengths", "Corrupt PNG"); - memset(lencodes+n, fill, c); - n += c; - } - } - if (n != ntot) return stbi__err("bad codelengths","Corrupt PNG"); - if (!stbi__zbuild_huffman(&a->z_length, lencodes, hlit)) return 0; - if (!stbi__zbuild_huffman(&a->z_distance, lencodes+hlit, hdist)) return 0; - return 1; -} - -static int stbi__parse_uncompressed_block(stbi__zbuf *a) -{ - stbi_uc header[4]; - int len,nlen,k; - if (a->num_bits & 7) - stbi__zreceive(a, a->num_bits & 7); // discard - // drain the bit-packed data into header - k = 0; - while (a->num_bits > 0) { - header[k++] = (stbi_uc) (a->code_buffer & 255); // suppress MSVC run-time check - a->code_buffer >>= 8; - a->num_bits -= 8; - } - if (a->num_bits < 0) return stbi__err("zlib corrupt","Corrupt PNG"); - // now fill header the normal way - while (k < 4) - header[k++] = stbi__zget8(a); - len = header[1] * 256 + header[0]; - nlen = header[3] * 256 + header[2]; - if (nlen != (len ^ 0xffff)) return stbi__err("zlib corrupt","Corrupt PNG"); - if (a->zbuffer + len > a->zbuffer_end) return stbi__err("read past buffer","Corrupt PNG"); - if (a->zout + len > a->zout_end) - if (!stbi__zexpand(a, a->zout, len)) return 0; - memcpy(a->zout, a->zbuffer, len); - a->zbuffer += len; - a->zout += len; - return 1; -} - -static int stbi__parse_zlib_header(stbi__zbuf *a) -{ - int cmf = stbi__zget8(a); - int cm = cmf & 15; - /* int cinfo = cmf >> 4; */ - int flg = stbi__zget8(a); - if (stbi__zeof(a)) return stbi__err("bad zlib header","Corrupt PNG"); // zlib spec - if ((cmf*256+flg) % 31 != 0) return stbi__err("bad zlib header","Corrupt PNG"); // zlib spec - if (flg & 32) return stbi__err("no preset dict","Corrupt PNG"); // preset dictionary not allowed in png - if (cm != 8) return stbi__err("bad compression","Corrupt PNG"); // DEFLATE required for png - // window = 1 << (8 + cinfo)... but who cares, we fully buffer output - return 1; -} - -static const stbi_uc stbi__zdefault_length[STBI__ZNSYMS] = -{ - 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, - 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, - 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, - 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, - 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, - 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, - 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, - 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, - 7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7, 7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,8 -}; -static const stbi_uc stbi__zdefault_distance[32] = -{ - 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5 -}; -/* -Init algorithm: -{ - int i; // use <= to match clearly with spec - for (i=0; i <= 143; ++i) stbi__zdefault_length[i] = 8; - for ( ; i <= 255; ++i) stbi__zdefault_length[i] = 9; - for ( ; i <= 279; ++i) stbi__zdefault_length[i] = 7; - for ( ; i <= 287; ++i) stbi__zdefault_length[i] = 8; - - for (i=0; i <= 31; ++i) stbi__zdefault_distance[i] = 5; -} -*/ - -static int stbi__parse_zlib(stbi__zbuf *a, int parse_header) -{ - int final, type; - if (parse_header) - if (!stbi__parse_zlib_header(a)) return 0; - a->num_bits = 0; - a->code_buffer = 0; - do { - final = stbi__zreceive(a,1); - type = stbi__zreceive(a,2); - if (type == 0) { - if (!stbi__parse_uncompressed_block(a)) return 0; - } else if (type == 3) { - return 0; - } else { - if (type == 1) { - // use fixed code lengths - if (!stbi__zbuild_huffman(&a->z_length , stbi__zdefault_length , STBI__ZNSYMS)) return 0; - if (!stbi__zbuild_huffman(&a->z_distance, stbi__zdefault_distance, 32)) return 0; - } else { - if (!stbi__compute_huffman_codes(a)) return 0; - } - if (!stbi__parse_huffman_block(a)) return 0; - } - } while (!final); - return 1; -} - -static int stbi__do_zlib(stbi__zbuf *a, char *obuf, int olen, int exp, int parse_header) -{ - a->zout_start = obuf; - a->zout = obuf; - a->zout_end = obuf + olen; - a->z_expandable = exp; - - return stbi__parse_zlib(a, parse_header); -} - -STBIDEF char *stbi_zlib_decode_malloc_guesssize(const char *buffer, int len, int initial_size, int *outlen) -{ - stbi__zbuf a; - char *p = (char *) stbi__malloc(initial_size); - if (p == NULL) return NULL; - a.zbuffer = (stbi_uc *) buffer; - a.zbuffer_end = (stbi_uc *) buffer + len; - if (stbi__do_zlib(&a, p, initial_size, 1, 1)) { - if (outlen) *outlen = (int) (a.zout - a.zout_start); - return a.zout_start; - } else { - STBI_FREE(a.zout_start); - return NULL; - } -} - -STBIDEF char *stbi_zlib_decode_malloc(char const *buffer, int len, int *outlen) -{ - return stbi_zlib_decode_malloc_guesssize(buffer, len, 16384, outlen); -} - -STBIDEF char *stbi_zlib_decode_malloc_guesssize_headerflag(const char *buffer, int len, int initial_size, int *outlen, int parse_header) -{ - stbi__zbuf a; - char *p = (char *) stbi__malloc(initial_size); - if (p == NULL) return NULL; - a.zbuffer = (stbi_uc *) buffer; - a.zbuffer_end = (stbi_uc *) buffer + len; - if (stbi__do_zlib(&a, p, initial_size, 1, parse_header)) { - if (outlen) *outlen = (int) (a.zout - a.zout_start); - return a.zout_start; - } else { - STBI_FREE(a.zout_start); - return NULL; - } -} - -STBIDEF int stbi_zlib_decode_buffer(char *obuffer, int olen, char const *ibuffer, int ilen) -{ - stbi__zbuf a; - a.zbuffer = (stbi_uc *) ibuffer; - a.zbuffer_end = (stbi_uc *) ibuffer + ilen; - if (stbi__do_zlib(&a, obuffer, olen, 0, 1)) - return (int) (a.zout - a.zout_start); - else - return -1; -} - -STBIDEF char *stbi_zlib_decode_noheader_malloc(char const *buffer, int len, int *outlen) -{ - stbi__zbuf a; - char *p = (char *) stbi__malloc(16384); - if (p == NULL) return NULL; - a.zbuffer = (stbi_uc *) buffer; - a.zbuffer_end = (stbi_uc *) buffer+len; - if (stbi__do_zlib(&a, p, 16384, 1, 0)) { - if (outlen) *outlen = (int) (a.zout - a.zout_start); - return a.zout_start; - } else { - STBI_FREE(a.zout_start); - return NULL; - } -} - -STBIDEF int stbi_zlib_decode_noheader_buffer(char *obuffer, int olen, const char *ibuffer, int ilen) -{ - stbi__zbuf a; - a.zbuffer = (stbi_uc *) ibuffer; - a.zbuffer_end = (stbi_uc *) ibuffer + ilen; - if (stbi__do_zlib(&a, obuffer, olen, 0, 0)) - return (int) (a.zout - a.zout_start); - else - return -1; -} -#endif - -// public domain "baseline" PNG decoder v0.10 Sean Barrett 2006-11-18 -// simple implementation -// - only 8-bit samples -// - no CRC checking -// - allocates lots of intermediate memory -// - avoids problem of streaming data between subsystems -// - avoids explicit window management -// performance -// - uses stb_zlib, a PD zlib implementation with fast huffman decoding - -#ifndef STBI_NO_PNG -typedef struct -{ - stbi__uint32 length; - stbi__uint32 type; -} stbi__pngchunk; - -static stbi__pngchunk stbi__get_chunk_header(stbi__context *s) -{ - stbi__pngchunk c; - c.length = stbi__get32be(s); - c.type = stbi__get32be(s); - return c; -} - -static int stbi__check_png_header(stbi__context *s) -{ - static const stbi_uc png_sig[8] = { 137,80,78,71,13,10,26,10 }; - int i; - for (i=0; i < 8; ++i) - if (stbi__get8(s) != png_sig[i]) return stbi__err("bad png sig","Not a PNG"); - return 1; -} - -typedef struct -{ - stbi__context *s; - stbi_uc *idata, *expanded, *out; - int depth; -} stbi__png; - - -enum { - STBI__F_none=0, - STBI__F_sub=1, - STBI__F_up=2, - STBI__F_avg=3, - STBI__F_paeth=4, - // synthetic filters used for first scanline to avoid needing a dummy row of 0s - STBI__F_avg_first, - STBI__F_paeth_first -}; - -static stbi_uc first_row_filter[5] = -{ - STBI__F_none, - STBI__F_sub, - STBI__F_none, - STBI__F_avg_first, - STBI__F_paeth_first -}; - -static int stbi__paeth(int a, int b, int c) -{ - int p = a + b - c; - int pa = abs(p-a); - int pb = abs(p-b); - int pc = abs(p-c); - if (pa <= pb && pa <= pc) return a; - if (pb <= pc) return b; - return c; -} - -static const stbi_uc stbi__depth_scale_table[9] = { 0, 0xff, 0x55, 0, 0x11, 0,0,0, 0x01 }; - -// create the png data from post-deflated data -static int stbi__create_png_image_raw(stbi__png *a, stbi_uc *raw, stbi__uint32 raw_len, int out_n, stbi__uint32 x, stbi__uint32 y, int depth, int color) -{ - int bytes = (depth == 16? 2 : 1); - stbi__context *s = a->s; - stbi__uint32 i,j,stride = x*out_n*bytes; - stbi__uint32 img_len, img_width_bytes; - int k; - int img_n = s->img_n; // copy it into a local for later - - int output_bytes = out_n*bytes; - int filter_bytes = img_n*bytes; - int width = x; - - STBI_ASSERT(out_n == s->img_n || out_n == s->img_n+1); - a->out = (stbi_uc *) stbi__malloc_mad3(x, y, output_bytes, 0); // extra bytes to write off the end into - if (!a->out) return stbi__err("outofmem", "Out of memory"); - - if (!stbi__mad3sizes_valid(img_n, x, depth, 7)) return stbi__err("too large", "Corrupt PNG"); - img_width_bytes = (((img_n * x * depth) + 7) >> 3); - img_len = (img_width_bytes + 1) * y; - - // we used to check for exact match between raw_len and img_len on non-interlaced PNGs, - // but issue #276 reported a PNG in the wild that had extra data at the end (all zeros), - // so just check for raw_len < img_len always. - if (raw_len < img_len) return stbi__err("not enough pixels","Corrupt PNG"); - - for (j=0; j < y; ++j) { - stbi_uc *cur = a->out + stride*j; - stbi_uc *prior; - int filter = *raw++; - - if (filter > 4) - return stbi__err("invalid filter","Corrupt PNG"); - - if (depth < 8) { - if (img_width_bytes > x) return stbi__err("invalid width","Corrupt PNG"); - cur += x*out_n - img_width_bytes; // store output to the rightmost img_len bytes, so we can decode in place - filter_bytes = 1; - width = img_width_bytes; - } - prior = cur - stride; // bugfix: need to compute this after 'cur +=' computation above - - // if first row, use special filter that doesn't sample previous row - if (j == 0) filter = first_row_filter[filter]; - - // handle first byte explicitly - for (k=0; k < filter_bytes; ++k) { - switch (filter) { - case STBI__F_none : cur[k] = raw[k]; break; - case STBI__F_sub : cur[k] = raw[k]; break; - case STBI__F_up : cur[k] = STBI__BYTECAST(raw[k] + prior[k]); break; - case STBI__F_avg : cur[k] = STBI__BYTECAST(raw[k] + (prior[k]>>1)); break; - case STBI__F_paeth : cur[k] = STBI__BYTECAST(raw[k] + stbi__paeth(0,prior[k],0)); break; - case STBI__F_avg_first : cur[k] = raw[k]; break; - case STBI__F_paeth_first: cur[k] = raw[k]; break; - } - } - - if (depth == 8) { - if (img_n != out_n) - cur[img_n] = 255; // first pixel - raw += img_n; - cur += out_n; - prior += out_n; - } else if (depth == 16) { - if (img_n != out_n) { - cur[filter_bytes] = 255; // first pixel top byte - cur[filter_bytes+1] = 255; // first pixel bottom byte - } - raw += filter_bytes; - cur += output_bytes; - prior += output_bytes; - } else { - raw += 1; - cur += 1; - prior += 1; - } - - // this is a little gross, so that we don't switch per-pixel or per-component - if (depth < 8 || img_n == out_n) { - int nk = (width - 1)*filter_bytes; - #define STBI__CASE(f) \ - case f: \ - for (k=0; k < nk; ++k) - switch (filter) { - // "none" filter turns into a memcpy here; make that explicit. - case STBI__F_none: memcpy(cur, raw, nk); break; - STBI__CASE(STBI__F_sub) { cur[k] = STBI__BYTECAST(raw[k] + cur[k-filter_bytes]); } break; - STBI__CASE(STBI__F_up) { cur[k] = STBI__BYTECAST(raw[k] + prior[k]); } break; - STBI__CASE(STBI__F_avg) { cur[k] = STBI__BYTECAST(raw[k] + ((prior[k] + cur[k-filter_bytes])>>1)); } break; - STBI__CASE(STBI__F_paeth) { cur[k] = STBI__BYTECAST(raw[k] + stbi__paeth(cur[k-filter_bytes],prior[k],prior[k-filter_bytes])); } break; - STBI__CASE(STBI__F_avg_first) { cur[k] = STBI__BYTECAST(raw[k] + (cur[k-filter_bytes] >> 1)); } break; - STBI__CASE(STBI__F_paeth_first) { cur[k] = STBI__BYTECAST(raw[k] + stbi__paeth(cur[k-filter_bytes],0,0)); } break; - } - #undef STBI__CASE - raw += nk; - } else { - STBI_ASSERT(img_n+1 == out_n); - #define STBI__CASE(f) \ - case f: \ - for (i=x-1; i >= 1; --i, cur[filter_bytes]=255,raw+=filter_bytes,cur+=output_bytes,prior+=output_bytes) \ - for (k=0; k < filter_bytes; ++k) - switch (filter) { - STBI__CASE(STBI__F_none) { cur[k] = raw[k]; } break; - STBI__CASE(STBI__F_sub) { cur[k] = STBI__BYTECAST(raw[k] + cur[k- output_bytes]); } break; - STBI__CASE(STBI__F_up) { cur[k] = STBI__BYTECAST(raw[k] + prior[k]); } break; - STBI__CASE(STBI__F_avg) { cur[k] = STBI__BYTECAST(raw[k] + ((prior[k] + cur[k- output_bytes])>>1)); } break; - STBI__CASE(STBI__F_paeth) { cur[k] = STBI__BYTECAST(raw[k] + stbi__paeth(cur[k- output_bytes],prior[k],prior[k- output_bytes])); } break; - STBI__CASE(STBI__F_avg_first) { cur[k] = STBI__BYTECAST(raw[k] + (cur[k- output_bytes] >> 1)); } break; - STBI__CASE(STBI__F_paeth_first) { cur[k] = STBI__BYTECAST(raw[k] + stbi__paeth(cur[k- output_bytes],0,0)); } break; - } - #undef STBI__CASE - - // the loop above sets the high byte of the pixels' alpha, but for - // 16 bit png files we also need the low byte set. we'll do that here. - if (depth == 16) { - cur = a->out + stride*j; // start at the beginning of the row again - for (i=0; i < x; ++i,cur+=output_bytes) { - cur[filter_bytes+1] = 255; - } - } - } - } - - // we make a separate pass to expand bits to pixels; for performance, - // this could run two scanlines behind the above code, so it won't - // intefere with filtering but will still be in the cache. - if (depth < 8) { - for (j=0; j < y; ++j) { - stbi_uc *cur = a->out + stride*j; - stbi_uc *in = a->out + stride*j + x*out_n - img_width_bytes; - // unpack 1/2/4-bit into a 8-bit buffer. allows us to keep the common 8-bit path optimal at minimal cost for 1/2/4-bit - // png guarante byte alignment, if width is not multiple of 8/4/2 we'll decode dummy trailing data that will be skipped in the later loop - stbi_uc scale = (color == 0) ? stbi__depth_scale_table[depth] : 1; // scale grayscale values to 0..255 range - - // note that the final byte might overshoot and write more data than desired. - // we can allocate enough data that this never writes out of memory, but it - // could also overwrite the next scanline. can it overwrite non-empty data - // on the next scanline? yes, consider 1-pixel-wide scanlines with 1-bit-per-pixel. - // so we need to explicitly clamp the final ones - - if (depth == 4) { - for (k=x*img_n; k >= 2; k-=2, ++in) { - *cur++ = scale * ((*in >> 4) ); - *cur++ = scale * ((*in ) & 0x0f); - } - if (k > 0) *cur++ = scale * ((*in >> 4) ); - } else if (depth == 2) { - for (k=x*img_n; k >= 4; k-=4, ++in) { - *cur++ = scale * ((*in >> 6) ); - *cur++ = scale * ((*in >> 4) & 0x03); - *cur++ = scale * ((*in >> 2) & 0x03); - *cur++ = scale * ((*in ) & 0x03); - } - if (k > 0) *cur++ = scale * ((*in >> 6) ); - if (k > 1) *cur++ = scale * ((*in >> 4) & 0x03); - if (k > 2) *cur++ = scale * ((*in >> 2) & 0x03); - } else if (depth == 1) { - for (k=x*img_n; k >= 8; k-=8, ++in) { - *cur++ = scale * ((*in >> 7) ); - *cur++ = scale * ((*in >> 6) & 0x01); - *cur++ = scale * ((*in >> 5) & 0x01); - *cur++ = scale * ((*in >> 4) & 0x01); - *cur++ = scale * ((*in >> 3) & 0x01); - *cur++ = scale * ((*in >> 2) & 0x01); - *cur++ = scale * ((*in >> 1) & 0x01); - *cur++ = scale * ((*in ) & 0x01); - } - if (k > 0) *cur++ = scale * ((*in >> 7) ); - if (k > 1) *cur++ = scale * ((*in >> 6) & 0x01); - if (k > 2) *cur++ = scale * ((*in >> 5) & 0x01); - if (k > 3) *cur++ = scale * ((*in >> 4) & 0x01); - if (k > 4) *cur++ = scale * ((*in >> 3) & 0x01); - if (k > 5) *cur++ = scale * ((*in >> 2) & 0x01); - if (k > 6) *cur++ = scale * ((*in >> 1) & 0x01); - } - if (img_n != out_n) { - int q; - // insert alpha = 255 - cur = a->out + stride*j; - if (img_n == 1) { - for (q=x-1; q >= 0; --q) { - cur[q*2+1] = 255; - cur[q*2+0] = cur[q]; - } - } else { - STBI_ASSERT(img_n == 3); - for (q=x-1; q >= 0; --q) { - cur[q*4+3] = 255; - cur[q*4+2] = cur[q*3+2]; - cur[q*4+1] = cur[q*3+1]; - cur[q*4+0] = cur[q*3+0]; - } - } - } - } - } else if (depth == 16) { - // force the image data from big-endian to platform-native. - // this is done in a separate pass due to the decoding relying - // on the data being untouched, but could probably be done - // per-line during decode if care is taken. - stbi_uc *cur = a->out; - stbi__uint16 *cur16 = (stbi__uint16*)cur; - - for(i=0; i < x*y*out_n; ++i,cur16++,cur+=2) { - *cur16 = (cur[0] << 8) | cur[1]; - } - } - - return 1; -} - -static int stbi__create_png_image(stbi__png *a, stbi_uc *image_data, stbi__uint32 image_data_len, int out_n, int depth, int color, int interlaced) -{ - int bytes = (depth == 16 ? 2 : 1); - int out_bytes = out_n * bytes; - stbi_uc *final; - int p; - if (!interlaced) - return stbi__create_png_image_raw(a, image_data, image_data_len, out_n, a->s->img_x, a->s->img_y, depth, color); - - // de-interlacing - final = (stbi_uc *) stbi__malloc_mad3(a->s->img_x, a->s->img_y, out_bytes, 0); - if (!final) return stbi__err("outofmem", "Out of memory"); - for (p=0; p < 7; ++p) { - int xorig[] = { 0,4,0,2,0,1,0 }; - int yorig[] = { 0,0,4,0,2,0,1 }; - int xspc[] = { 8,8,4,4,2,2,1 }; - int yspc[] = { 8,8,8,4,4,2,2 }; - int i,j,x,y; - // pass1_x[4] = 0, pass1_x[5] = 1, pass1_x[12] = 1 - x = (a->s->img_x - xorig[p] + xspc[p]-1) / xspc[p]; - y = (a->s->img_y - yorig[p] + yspc[p]-1) / yspc[p]; - if (x && y) { - stbi__uint32 img_len = ((((a->s->img_n * x * depth) + 7) >> 3) + 1) * y; - if (!stbi__create_png_image_raw(a, image_data, image_data_len, out_n, x, y, depth, color)) { - STBI_FREE(final); - return 0; - } - for (j=0; j < y; ++j) { - for (i=0; i < x; ++i) { - int out_y = j*yspc[p]+yorig[p]; - int out_x = i*xspc[p]+xorig[p]; - memcpy(final + out_y*a->s->img_x*out_bytes + out_x*out_bytes, - a->out + (j*x+i)*out_bytes, out_bytes); - } - } - STBI_FREE(a->out); - image_data += img_len; - image_data_len -= img_len; - } - } - a->out = final; - - return 1; -} - -static int stbi__compute_transparency(stbi__png *z, stbi_uc tc[3], int out_n) -{ - stbi__context *s = z->s; - stbi__uint32 i, pixel_count = s->img_x * s->img_y; - stbi_uc *p = z->out; - - // compute color-based transparency, assuming we've - // already got 255 as the alpha value in the output - STBI_ASSERT(out_n == 2 || out_n == 4); - - if (out_n == 2) { - for (i=0; i < pixel_count; ++i) { - p[1] = (p[0] == tc[0] ? 0 : 255); - p += 2; - } - } else { - for (i=0; i < pixel_count; ++i) { - if (p[0] == tc[0] && p[1] == tc[1] && p[2] == tc[2]) - p[3] = 0; - p += 4; - } - } - return 1; -} - -static int stbi__compute_transparency16(stbi__png *z, stbi__uint16 tc[3], int out_n) -{ - stbi__context *s = z->s; - stbi__uint32 i, pixel_count = s->img_x * s->img_y; - stbi__uint16 *p = (stbi__uint16*) z->out; - - // compute color-based transparency, assuming we've - // already got 65535 as the alpha value in the output - STBI_ASSERT(out_n == 2 || out_n == 4); - - if (out_n == 2) { - for (i = 0; i < pixel_count; ++i) { - p[1] = (p[0] == tc[0] ? 0 : 65535); - p += 2; - } - } else { - for (i = 0; i < pixel_count; ++i) { - if (p[0] == tc[0] && p[1] == tc[1] && p[2] == tc[2]) - p[3] = 0; - p += 4; - } - } - return 1; -} - -static int stbi__expand_png_palette(stbi__png *a, stbi_uc *palette, int len, int pal_img_n) -{ - stbi__uint32 i, pixel_count = a->s->img_x * a->s->img_y; - stbi_uc *p, *temp_out, *orig = a->out; - - p = (stbi_uc *) stbi__malloc_mad2(pixel_count, pal_img_n, 0); - if (p == NULL) return stbi__err("outofmem", "Out of memory"); - - // between here and free(out) below, exitting would leak - temp_out = p; - - if (pal_img_n == 3) { - for (i=0; i < pixel_count; ++i) { - int n = orig[i]*4; - p[0] = palette[n ]; - p[1] = palette[n+1]; - p[2] = palette[n+2]; - p += 3; - } - } else { - for (i=0; i < pixel_count; ++i) { - int n = orig[i]*4; - p[0] = palette[n ]; - p[1] = palette[n+1]; - p[2] = palette[n+2]; - p[3] = palette[n+3]; - p += 4; - } - } - STBI_FREE(a->out); - a->out = temp_out; - - STBI_NOTUSED(len); - - return 1; -} - -static int stbi__unpremultiply_on_load_global = 0; -static int stbi__de_iphone_flag_global = 0; - -STBIDEF void stbi_set_unpremultiply_on_load(int flag_true_if_should_unpremultiply) -{ - stbi__unpremultiply_on_load_global = flag_true_if_should_unpremultiply; -} - -STBIDEF void stbi_convert_iphone_png_to_rgb(int flag_true_if_should_convert) -{ - stbi__de_iphone_flag_global = flag_true_if_should_convert; -} - -#ifndef STBI_THREAD_LOCAL -#define stbi__unpremultiply_on_load stbi__unpremultiply_on_load_global -#define stbi__de_iphone_flag stbi__de_iphone_flag_global -#else -static STBI_THREAD_LOCAL int stbi__unpremultiply_on_load_local, stbi__unpremultiply_on_load_set; -static STBI_THREAD_LOCAL int stbi__de_iphone_flag_local, stbi__de_iphone_flag_set; - -STBIDEF void stbi_set_unpremultiply_on_load_thread(int flag_true_if_should_unpremultiply) -{ - stbi__unpremultiply_on_load_local = flag_true_if_should_unpremultiply; - stbi__unpremultiply_on_load_set = 1; -} - -STBIDEF void stbi_convert_iphone_png_to_rgb_thread(int flag_true_if_should_convert) -{ - stbi__de_iphone_flag_local = flag_true_if_should_convert; - stbi__de_iphone_flag_set = 1; -} - -#define stbi__unpremultiply_on_load (stbi__unpremultiply_on_load_set \ - ? stbi__unpremultiply_on_load_local \ - : stbi__unpremultiply_on_load_global) -#define stbi__de_iphone_flag (stbi__de_iphone_flag_set \ - ? stbi__de_iphone_flag_local \ - : stbi__de_iphone_flag_global) -#endif // STBI_THREAD_LOCAL - -static void stbi__de_iphone(stbi__png *z) -{ - stbi__context *s = z->s; - stbi__uint32 i, pixel_count = s->img_x * s->img_y; - stbi_uc *p = z->out; - - if (s->img_out_n == 3) { // convert bgr to rgb - for (i=0; i < pixel_count; ++i) { - stbi_uc t = p[0]; - p[0] = p[2]; - p[2] = t; - p += 3; - } - } else { - STBI_ASSERT(s->img_out_n == 4); - if (stbi__unpremultiply_on_load) { - // convert bgr to rgb and unpremultiply - for (i=0; i < pixel_count; ++i) { - stbi_uc a = p[3]; - stbi_uc t = p[0]; - if (a) { - stbi_uc half = a / 2; - p[0] = (p[2] * 255 + half) / a; - p[1] = (p[1] * 255 + half) / a; - p[2] = ( t * 255 + half) / a; - } else { - p[0] = p[2]; - p[2] = t; - } - p += 4; - } - } else { - // convert bgr to rgb - for (i=0; i < pixel_count; ++i) { - stbi_uc t = p[0]; - p[0] = p[2]; - p[2] = t; - p += 4; - } - } - } -} - -#define STBI__PNG_TYPE(a,b,c,d) (((unsigned) (a) << 24) + ((unsigned) (b) << 16) + ((unsigned) (c) << 8) + (unsigned) (d)) - -static int stbi__parse_png_file(stbi__png *z, int scan, int req_comp) -{ - stbi_uc palette[1024], pal_img_n=0; - stbi_uc has_trans=0, tc[3]={0}; - stbi__uint16 tc16[3]; - stbi__uint32 ioff=0, idata_limit=0, i, pal_len=0; - int first=1,k,interlace=0, color=0, is_iphone=0; - stbi__context *s = z->s; - - z->expanded = NULL; - z->idata = NULL; - z->out = NULL; - - if (!stbi__check_png_header(s)) return 0; - - if (scan == STBI__SCAN_type) return 1; - - for (;;) { - stbi__pngchunk c = stbi__get_chunk_header(s); - switch (c.type) { - case STBI__PNG_TYPE('C','g','B','I'): - is_iphone = 1; - stbi__skip(s, c.length); - break; - case STBI__PNG_TYPE('I','H','D','R'): { - int comp,filter; - if (!first) return stbi__err("multiple IHDR","Corrupt PNG"); - first = 0; - if (c.length != 13) return stbi__err("bad IHDR len","Corrupt PNG"); - s->img_x = stbi__get32be(s); - s->img_y = stbi__get32be(s); - if (s->img_y > STBI_MAX_DIMENSIONS) return stbi__err("too large","Very large image (corrupt?)"); - if (s->img_x > STBI_MAX_DIMENSIONS) return stbi__err("too large","Very large image (corrupt?)"); - z->depth = stbi__get8(s); if (z->depth != 1 && z->depth != 2 && z->depth != 4 && z->depth != 8 && z->depth != 16) return stbi__err("1/2/4/8/16-bit only","PNG not supported: 1/2/4/8/16-bit only"); - color = stbi__get8(s); if (color > 6) return stbi__err("bad ctype","Corrupt PNG"); - if (color == 3 && z->depth == 16) return stbi__err("bad ctype","Corrupt PNG"); - if (color == 3) pal_img_n = 3; else if (color & 1) return stbi__err("bad ctype","Corrupt PNG"); - comp = stbi__get8(s); if (comp) return stbi__err("bad comp method","Corrupt PNG"); - filter= stbi__get8(s); if (filter) return stbi__err("bad filter method","Corrupt PNG"); - interlace = stbi__get8(s); if (interlace>1) return stbi__err("bad interlace method","Corrupt PNG"); - if (!s->img_x || !s->img_y) return stbi__err("0-pixel image","Corrupt PNG"); - if (!pal_img_n) { - s->img_n = (color & 2 ? 3 : 1) + (color & 4 ? 1 : 0); - if ((1 << 30) / s->img_x / s->img_n < s->img_y) return stbi__err("too large", "Image too large to decode"); - } else { - // if paletted, then pal_n is our final components, and - // img_n is # components to decompress/filter. - s->img_n = 1; - if ((1 << 30) / s->img_x / 4 < s->img_y) return stbi__err("too large","Corrupt PNG"); - } - // even with SCAN_header, have to scan to see if we have a tRNS - break; - } - - case STBI__PNG_TYPE('P','L','T','E'): { - if (first) return stbi__err("first not IHDR", "Corrupt PNG"); - if (c.length > 256*3) return stbi__err("invalid PLTE","Corrupt PNG"); - pal_len = c.length / 3; - if (pal_len * 3 != c.length) return stbi__err("invalid PLTE","Corrupt PNG"); - for (i=0; i < pal_len; ++i) { - palette[i*4+0] = stbi__get8(s); - palette[i*4+1] = stbi__get8(s); - palette[i*4+2] = stbi__get8(s); - palette[i*4+3] = 255; - } - break; - } - - case STBI__PNG_TYPE('t','R','N','S'): { - if (first) return stbi__err("first not IHDR", "Corrupt PNG"); - if (z->idata) return stbi__err("tRNS after IDAT","Corrupt PNG"); - if (pal_img_n) { - if (scan == STBI__SCAN_header) { s->img_n = 4; return 1; } - if (pal_len == 0) return stbi__err("tRNS before PLTE","Corrupt PNG"); - if (c.length > pal_len) return stbi__err("bad tRNS len","Corrupt PNG"); - pal_img_n = 4; - for (i=0; i < c.length; ++i) - palette[i*4+3] = stbi__get8(s); - } else { - if (!(s->img_n & 1)) return stbi__err("tRNS with alpha","Corrupt PNG"); - if (c.length != (stbi__uint32) s->img_n*2) return stbi__err("bad tRNS len","Corrupt PNG"); - has_trans = 1; - // non-paletted with tRNS = constant alpha. if header-scanning, we can stop now. - if (scan == STBI__SCAN_header) { ++s->img_n; return 1; } - if (z->depth == 16) { - for (k = 0; k < s->img_n; ++k) tc16[k] = (stbi__uint16)stbi__get16be(s); // copy the values as-is - } else { - for (k = 0; k < s->img_n; ++k) tc[k] = (stbi_uc)(stbi__get16be(s) & 255) * stbi__depth_scale_table[z->depth]; // non 8-bit images will be larger - } - } - break; - } - - case STBI__PNG_TYPE('I','D','A','T'): { - if (first) return stbi__err("first not IHDR", "Corrupt PNG"); - if (pal_img_n && !pal_len) return stbi__err("no PLTE","Corrupt PNG"); - if (scan == STBI__SCAN_header) { - // header scan definitely stops at first IDAT - if (pal_img_n) - s->img_n = pal_img_n; - return 1; - } - if (c.length > (1u << 30)) return stbi__err("IDAT size limit", "IDAT section larger than 2^30 bytes"); - if ((int)(ioff + c.length) < (int)ioff) return 0; - if (ioff + c.length > idata_limit) { - stbi__uint32 idata_limit_old = idata_limit; - stbi_uc *p; - if (idata_limit == 0) idata_limit = c.length > 4096 ? c.length : 4096; - while (ioff + c.length > idata_limit) - idata_limit *= 2; - STBI_NOTUSED(idata_limit_old); - p = (stbi_uc *) STBI_REALLOC_SIZED(z->idata, idata_limit_old, idata_limit); if (p == NULL) return stbi__err("outofmem", "Out of memory"); - z->idata = p; - } - if (!stbi__getn(s, z->idata+ioff,c.length)) return stbi__err("outofdata","Corrupt PNG"); - ioff += c.length; - break; - } - - case STBI__PNG_TYPE('I','E','N','D'): { - stbi__uint32 raw_len, bpl; - if (first) return stbi__err("first not IHDR", "Corrupt PNG"); - if (scan != STBI__SCAN_load) return 1; - if (z->idata == NULL) return stbi__err("no IDAT","Corrupt PNG"); - // initial guess for decoded data size to avoid unnecessary reallocs - bpl = (s->img_x * z->depth + 7) / 8; // bytes per line, per component - raw_len = bpl * s->img_y * s->img_n /* pixels */ + s->img_y /* filter mode per row */; - z->expanded = (stbi_uc *) stbi_zlib_decode_malloc_guesssize_headerflag((char *) z->idata, ioff, raw_len, (int *) &raw_len, !is_iphone); - if (z->expanded == NULL) return 0; // zlib should set error - STBI_FREE(z->idata); z->idata = NULL; - if ((req_comp == s->img_n+1 && req_comp != 3 && !pal_img_n) || has_trans) - s->img_out_n = s->img_n+1; - else - s->img_out_n = s->img_n; - if (!stbi__create_png_image(z, z->expanded, raw_len, s->img_out_n, z->depth, color, interlace)) return 0; - if (has_trans) { - if (z->depth == 16) { - if (!stbi__compute_transparency16(z, tc16, s->img_out_n)) return 0; - } else { - if (!stbi__compute_transparency(z, tc, s->img_out_n)) return 0; - } - } - if (is_iphone && stbi__de_iphone_flag && s->img_out_n > 2) - stbi__de_iphone(z); - if (pal_img_n) { - // pal_img_n == 3 or 4 - s->img_n = pal_img_n; // record the actual colors we had - s->img_out_n = pal_img_n; - if (req_comp >= 3) s->img_out_n = req_comp; - if (!stbi__expand_png_palette(z, palette, pal_len, s->img_out_n)) - return 0; - } else if (has_trans) { - // non-paletted image with tRNS -> source image has (constant) alpha - ++s->img_n; - } - STBI_FREE(z->expanded); z->expanded = NULL; - // end of PNG chunk, read and skip CRC - stbi__get32be(s); - return 1; - } - - default: - // if critical, fail - if (first) return stbi__err("first not IHDR", "Corrupt PNG"); - if ((c.type & (1 << 29)) == 0) { - #ifndef STBI_NO_FAILURE_STRINGS - // not threadsafe - static char invalid_chunk[] = "XXXX PNG chunk not known"; - invalid_chunk[0] = STBI__BYTECAST(c.type >> 24); - invalid_chunk[1] = STBI__BYTECAST(c.type >> 16); - invalid_chunk[2] = STBI__BYTECAST(c.type >> 8); - invalid_chunk[3] = STBI__BYTECAST(c.type >> 0); - #endif - return stbi__err(invalid_chunk, "PNG not supported: unknown PNG chunk type"); - } - stbi__skip(s, c.length); - break; - } - // end of PNG chunk, read and skip CRC - stbi__get32be(s); - } -} - -static void *stbi__do_png(stbi__png *p, int *x, int *y, int *n, int req_comp, stbi__result_info *ri) -{ - void *result=NULL; - if (req_comp < 0 || req_comp > 4) return stbi__errpuc("bad req_comp", "Internal error"); - if (stbi__parse_png_file(p, STBI__SCAN_load, req_comp)) { - if (p->depth <= 8) - ri->bits_per_channel = 8; - else if (p->depth == 16) - ri->bits_per_channel = 16; - else - return stbi__errpuc("bad bits_per_channel", "PNG not supported: unsupported color depth"); - result = p->out; - p->out = NULL; - if (req_comp && req_comp != p->s->img_out_n) { - if (ri->bits_per_channel == 8) - result = stbi__convert_format((unsigned char *) result, p->s->img_out_n, req_comp, p->s->img_x, p->s->img_y); - else - result = stbi__convert_format16((stbi__uint16 *) result, p->s->img_out_n, req_comp, p->s->img_x, p->s->img_y); - p->s->img_out_n = req_comp; - if (result == NULL) return result; - } - *x = p->s->img_x; - *y = p->s->img_y; - if (n) *n = p->s->img_n; - } - STBI_FREE(p->out); p->out = NULL; - STBI_FREE(p->expanded); p->expanded = NULL; - STBI_FREE(p->idata); p->idata = NULL; - - return result; -} - -static void *stbi__png_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - stbi__png p; - p.s = s; - return stbi__do_png(&p, x,y,comp,req_comp, ri); -} - -static int stbi__png_test(stbi__context *s) -{ - int r; - r = stbi__check_png_header(s); - stbi__rewind(s); - return r; -} - -static int stbi__png_info_raw(stbi__png *p, int *x, int *y, int *comp) -{ - if (!stbi__parse_png_file(p, STBI__SCAN_header, 0)) { - stbi__rewind( p->s ); - return 0; - } - if (x) *x = p->s->img_x; - if (y) *y = p->s->img_y; - if (comp) *comp = p->s->img_n; - return 1; -} - -static int stbi__png_info(stbi__context *s, int *x, int *y, int *comp) -{ - stbi__png p; - p.s = s; - return stbi__png_info_raw(&p, x, y, comp); -} - -static int stbi__png_is16(stbi__context *s) -{ - stbi__png p; - p.s = s; - if (!stbi__png_info_raw(&p, NULL, NULL, NULL)) - return 0; - if (p.depth != 16) { - stbi__rewind(p.s); - return 0; - } - return 1; -} -#endif - -// Microsoft/Windows BMP image - -#ifndef STBI_NO_BMP -static int stbi__bmp_test_raw(stbi__context *s) -{ - int r; - int sz; - if (stbi__get8(s) != 'B') return 0; - if (stbi__get8(s) != 'M') return 0; - stbi__get32le(s); // discard filesize - stbi__get16le(s); // discard reserved - stbi__get16le(s); // discard reserved - stbi__get32le(s); // discard data offset - sz = stbi__get32le(s); - r = (sz == 12 || sz == 40 || sz == 56 || sz == 108 || sz == 124); - return r; -} - -static int stbi__bmp_test(stbi__context *s) -{ - int r = stbi__bmp_test_raw(s); - stbi__rewind(s); - return r; -} - - -// returns 0..31 for the highest set bit -static int stbi__high_bit(unsigned int z) -{ - int n=0; - if (z == 0) return -1; - if (z >= 0x10000) { n += 16; z >>= 16; } - if (z >= 0x00100) { n += 8; z >>= 8; } - if (z >= 0x00010) { n += 4; z >>= 4; } - if (z >= 0x00004) { n += 2; z >>= 2; } - if (z >= 0x00002) { n += 1;/* >>= 1;*/ } - return n; -} - -static int stbi__bitcount(unsigned int a) -{ - a = (a & 0x55555555) + ((a >> 1) & 0x55555555); // max 2 - a = (a & 0x33333333) + ((a >> 2) & 0x33333333); // max 4 - a = (a + (a >> 4)) & 0x0f0f0f0f; // max 8 per 4, now 8 bits - a = (a + (a >> 8)); // max 16 per 8 bits - a = (a + (a >> 16)); // max 32 per 8 bits - return a & 0xff; -} - -// extract an arbitrarily-aligned N-bit value (N=bits) -// from v, and then make it 8-bits long and fractionally -// extend it to full full range. -static int stbi__shiftsigned(unsigned int v, int shift, int bits) -{ - static unsigned int mul_table[9] = { - 0, - 0xff/*0b11111111*/, 0x55/*0b01010101*/, 0x49/*0b01001001*/, 0x11/*0b00010001*/, - 0x21/*0b00100001*/, 0x41/*0b01000001*/, 0x81/*0b10000001*/, 0x01/*0b00000001*/, - }; - static unsigned int shift_table[9] = { - 0, 0,0,1,0,2,4,6,0, - }; - if (shift < 0) - v <<= -shift; - else - v >>= shift; - STBI_ASSERT(v < 256); - v >>= (8-bits); - STBI_ASSERT(bits >= 0 && bits <= 8); - return (int) ((unsigned) v * mul_table[bits]) >> shift_table[bits]; -} - -typedef struct -{ - int bpp, offset, hsz; - unsigned int mr,mg,mb,ma, all_a; - int extra_read; -} stbi__bmp_data; - -static int stbi__bmp_set_mask_defaults(stbi__bmp_data *info, int compress) -{ - // BI_BITFIELDS specifies masks explicitly, don't override - if (compress == 3) - return 1; - - if (compress == 0) { - if (info->bpp == 16) { - info->mr = 31u << 10; - info->mg = 31u << 5; - info->mb = 31u << 0; - } else if (info->bpp == 32) { - info->mr = 0xffu << 16; - info->mg = 0xffu << 8; - info->mb = 0xffu << 0; - info->ma = 0xffu << 24; - info->all_a = 0; // if all_a is 0 at end, then we loaded alpha channel but it was all 0 - } else { - // otherwise, use defaults, which is all-0 - info->mr = info->mg = info->mb = info->ma = 0; - } - return 1; - } - return 0; // error -} - -static void *stbi__bmp_parse_header(stbi__context *s, stbi__bmp_data *info) -{ - int hsz; - if (stbi__get8(s) != 'B' || stbi__get8(s) != 'M') return stbi__errpuc("not BMP", "Corrupt BMP"); - stbi__get32le(s); // discard filesize - stbi__get16le(s); // discard reserved - stbi__get16le(s); // discard reserved - info->offset = stbi__get32le(s); - info->hsz = hsz = stbi__get32le(s); - info->mr = info->mg = info->mb = info->ma = 0; - info->extra_read = 14; - - if (info->offset < 0) return stbi__errpuc("bad BMP", "bad BMP"); - - if (hsz != 12 && hsz != 40 && hsz != 56 && hsz != 108 && hsz != 124) return stbi__errpuc("unknown BMP", "BMP type not supported: unknown"); - if (hsz == 12) { - s->img_x = stbi__get16le(s); - s->img_y = stbi__get16le(s); - } else { - s->img_x = stbi__get32le(s); - s->img_y = stbi__get32le(s); - } - if (stbi__get16le(s) != 1) return stbi__errpuc("bad BMP", "bad BMP"); - info->bpp = stbi__get16le(s); - if (hsz != 12) { - int compress = stbi__get32le(s); - if (compress == 1 || compress == 2) return stbi__errpuc("BMP RLE", "BMP type not supported: RLE"); - if (compress >= 4) return stbi__errpuc("BMP JPEG/PNG", "BMP type not supported: unsupported compression"); // this includes PNG/JPEG modes - if (compress == 3 && info->bpp != 16 && info->bpp != 32) return stbi__errpuc("bad BMP", "bad BMP"); // bitfields requires 16 or 32 bits/pixel - stbi__get32le(s); // discard sizeof - stbi__get32le(s); // discard hres - stbi__get32le(s); // discard vres - stbi__get32le(s); // discard colorsused - stbi__get32le(s); // discard max important - if (hsz == 40 || hsz == 56) { - if (hsz == 56) { - stbi__get32le(s); - stbi__get32le(s); - stbi__get32le(s); - stbi__get32le(s); - } - if (info->bpp == 16 || info->bpp == 32) { - if (compress == 0) { - stbi__bmp_set_mask_defaults(info, compress); - } else if (compress == 3) { - info->mr = stbi__get32le(s); - info->mg = stbi__get32le(s); - info->mb = stbi__get32le(s); - info->extra_read += 12; - // not documented, but generated by photoshop and handled by mspaint - if (info->mr == info->mg && info->mg == info->mb) { - // ?!?!? - return stbi__errpuc("bad BMP", "bad BMP"); - } - } else - return stbi__errpuc("bad BMP", "bad BMP"); - } - } else { - // V4/V5 header - int i; - if (hsz != 108 && hsz != 124) - return stbi__errpuc("bad BMP", "bad BMP"); - info->mr = stbi__get32le(s); - info->mg = stbi__get32le(s); - info->mb = stbi__get32le(s); - info->ma = stbi__get32le(s); - if (compress != 3) // override mr/mg/mb unless in BI_BITFIELDS mode, as per docs - stbi__bmp_set_mask_defaults(info, compress); - stbi__get32le(s); // discard color space - for (i=0; i < 12; ++i) - stbi__get32le(s); // discard color space parameters - if (hsz == 124) { - stbi__get32le(s); // discard rendering intent - stbi__get32le(s); // discard offset of profile data - stbi__get32le(s); // discard size of profile data - stbi__get32le(s); // discard reserved - } - } - } - return (void *) 1; -} - - -static void *stbi__bmp_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - stbi_uc *out; - unsigned int mr=0,mg=0,mb=0,ma=0, all_a; - stbi_uc pal[256][4]; - int psize=0,i,j,width; - int flip_vertically, pad, target; - stbi__bmp_data info; - STBI_NOTUSED(ri); - - info.all_a = 255; - if (stbi__bmp_parse_header(s, &info) == NULL) - return NULL; // error code already set - - flip_vertically = ((int) s->img_y) > 0; - s->img_y = abs((int) s->img_y); - - if (s->img_y > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - if (s->img_x > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - - mr = info.mr; - mg = info.mg; - mb = info.mb; - ma = info.ma; - all_a = info.all_a; - - if (info.hsz == 12) { - if (info.bpp < 24) - psize = (info.offset - info.extra_read - 24) / 3; - } else { - if (info.bpp < 16) - psize = (info.offset - info.extra_read - info.hsz) >> 2; - } - if (psize == 0) { - // accept some number of extra bytes after the header, but if the offset points either to before - // the header ends or implies a large amount of extra data, reject the file as malformed - int bytes_read_so_far = s->callback_already_read + (int)(s->img_buffer - s->img_buffer_original); - int header_limit = 1024; // max we actually read is below 256 bytes currently. - int extra_data_limit = 256*4; // what ordinarily goes here is a palette; 256 entries*4 bytes is its max size. - if (bytes_read_so_far <= 0 || bytes_read_so_far > header_limit) { - return stbi__errpuc("bad header", "Corrupt BMP"); - } - // we established that bytes_read_so_far is positive and sensible. - // the first half of this test rejects offsets that are either too small positives, or - // negative, and guarantees that info.offset >= bytes_read_so_far > 0. this in turn - // ensures the number computed in the second half of the test can't overflow. - if (info.offset < bytes_read_so_far || info.offset - bytes_read_so_far > extra_data_limit) { - return stbi__errpuc("bad offset", "Corrupt BMP"); - } else { - stbi__skip(s, info.offset - bytes_read_so_far); - } - } - - if (info.bpp == 24 && ma == 0xff000000) - s->img_n = 3; - else - s->img_n = ma ? 4 : 3; - if (req_comp && req_comp >= 3) // we can directly decode 3 or 4 - target = req_comp; - else - target = s->img_n; // if they want monochrome, we'll post-convert - - // sanity-check size - if (!stbi__mad3sizes_valid(target, s->img_x, s->img_y, 0)) - return stbi__errpuc("too large", "Corrupt BMP"); - - out = (stbi_uc *) stbi__malloc_mad3(target, s->img_x, s->img_y, 0); - if (!out) return stbi__errpuc("outofmem", "Out of memory"); - if (info.bpp < 16) { - int z=0; - if (psize == 0 || psize > 256) { STBI_FREE(out); return stbi__errpuc("invalid", "Corrupt BMP"); } - for (i=0; i < psize; ++i) { - pal[i][2] = stbi__get8(s); - pal[i][1] = stbi__get8(s); - pal[i][0] = stbi__get8(s); - if (info.hsz != 12) stbi__get8(s); - pal[i][3] = 255; - } - stbi__skip(s, info.offset - info.extra_read - info.hsz - psize * (info.hsz == 12 ? 3 : 4)); - if (info.bpp == 1) width = (s->img_x + 7) >> 3; - else if (info.bpp == 4) width = (s->img_x + 1) >> 1; - else if (info.bpp == 8) width = s->img_x; - else { STBI_FREE(out); return stbi__errpuc("bad bpp", "Corrupt BMP"); } - pad = (-width)&3; - if (info.bpp == 1) { - for (j=0; j < (int) s->img_y; ++j) { - int bit_offset = 7, v = stbi__get8(s); - for (i=0; i < (int) s->img_x; ++i) { - int color = (v>>bit_offset)&0x1; - out[z++] = pal[color][0]; - out[z++] = pal[color][1]; - out[z++] = pal[color][2]; - if (target == 4) out[z++] = 255; - if (i+1 == (int) s->img_x) break; - if((--bit_offset) < 0) { - bit_offset = 7; - v = stbi__get8(s); - } - } - stbi__skip(s, pad); - } - } else { - for (j=0; j < (int) s->img_y; ++j) { - for (i=0; i < (int) s->img_x; i += 2) { - int v=stbi__get8(s),v2=0; - if (info.bpp == 4) { - v2 = v & 15; - v >>= 4; - } - out[z++] = pal[v][0]; - out[z++] = pal[v][1]; - out[z++] = pal[v][2]; - if (target == 4) out[z++] = 255; - if (i+1 == (int) s->img_x) break; - v = (info.bpp == 8) ? stbi__get8(s) : v2; - out[z++] = pal[v][0]; - out[z++] = pal[v][1]; - out[z++] = pal[v][2]; - if (target == 4) out[z++] = 255; - } - stbi__skip(s, pad); - } - } - } else { - int rshift=0,gshift=0,bshift=0,ashift=0,rcount=0,gcount=0,bcount=0,acount=0; - int z = 0; - int easy=0; - stbi__skip(s, info.offset - info.extra_read - info.hsz); - if (info.bpp == 24) width = 3 * s->img_x; - else if (info.bpp == 16) width = 2*s->img_x; - else /* bpp = 32 and pad = 0 */ width=0; - pad = (-width) & 3; - if (info.bpp == 24) { - easy = 1; - } else if (info.bpp == 32) { - if (mb == 0xff && mg == 0xff00 && mr == 0x00ff0000 && ma == 0xff000000) - easy = 2; - } - if (!easy) { - if (!mr || !mg || !mb) { STBI_FREE(out); return stbi__errpuc("bad masks", "Corrupt BMP"); } - // right shift amt to put high bit in position #7 - rshift = stbi__high_bit(mr)-7; rcount = stbi__bitcount(mr); - gshift = stbi__high_bit(mg)-7; gcount = stbi__bitcount(mg); - bshift = stbi__high_bit(mb)-7; bcount = stbi__bitcount(mb); - ashift = stbi__high_bit(ma)-7; acount = stbi__bitcount(ma); - if (rcount > 8 || gcount > 8 || bcount > 8 || acount > 8) { STBI_FREE(out); return stbi__errpuc("bad masks", "Corrupt BMP"); } - } - for (j=0; j < (int) s->img_y; ++j) { - if (easy) { - for (i=0; i < (int) s->img_x; ++i) { - unsigned char a; - out[z+2] = stbi__get8(s); - out[z+1] = stbi__get8(s); - out[z+0] = stbi__get8(s); - z += 3; - a = (easy == 2 ? stbi__get8(s) : 255); - all_a |= a; - if (target == 4) out[z++] = a; - } - } else { - int bpp = info.bpp; - for (i=0; i < (int) s->img_x; ++i) { - stbi__uint32 v = (bpp == 16 ? (stbi__uint32) stbi__get16le(s) : stbi__get32le(s)); - unsigned int a; - out[z++] = STBI__BYTECAST(stbi__shiftsigned(v & mr, rshift, rcount)); - out[z++] = STBI__BYTECAST(stbi__shiftsigned(v & mg, gshift, gcount)); - out[z++] = STBI__BYTECAST(stbi__shiftsigned(v & mb, bshift, bcount)); - a = (ma ? stbi__shiftsigned(v & ma, ashift, acount) : 255); - all_a |= a; - if (target == 4) out[z++] = STBI__BYTECAST(a); - } - } - stbi__skip(s, pad); - } - } - - // if alpha channel is all 0s, replace with all 255s - if (target == 4 && all_a == 0) - for (i=4*s->img_x*s->img_y-1; i >= 0; i -= 4) - out[i] = 255; - - if (flip_vertically) { - stbi_uc t; - for (j=0; j < (int) s->img_y>>1; ++j) { - stbi_uc *p1 = out + j *s->img_x*target; - stbi_uc *p2 = out + (s->img_y-1-j)*s->img_x*target; - for (i=0; i < (int) s->img_x*target; ++i) { - t = p1[i]; p1[i] = p2[i]; p2[i] = t; - } - } - } - - if (req_comp && req_comp != target) { - out = stbi__convert_format(out, target, req_comp, s->img_x, s->img_y); - if (out == NULL) return out; // stbi__convert_format frees input on failure - } - - *x = s->img_x; - *y = s->img_y; - if (comp) *comp = s->img_n; - return out; -} -#endif - -// Targa Truevision - TGA -// by Jonathan Dummer -#ifndef STBI_NO_TGA -// returns STBI_rgb or whatever, 0 on error -static int stbi__tga_get_comp(int bits_per_pixel, int is_grey, int* is_rgb16) -{ - // only RGB or RGBA (incl. 16bit) or grey allowed - if (is_rgb16) *is_rgb16 = 0; - switch(bits_per_pixel) { - case 8: return STBI_grey; - case 16: if(is_grey) return STBI_grey_alpha; - // fallthrough - case 15: if(is_rgb16) *is_rgb16 = 1; - return STBI_rgb; - case 24: // fallthrough - case 32: return bits_per_pixel/8; - default: return 0; - } -} - -static int stbi__tga_info(stbi__context *s, int *x, int *y, int *comp) -{ - int tga_w, tga_h, tga_comp, tga_image_type, tga_bits_per_pixel, tga_colormap_bpp; - int sz, tga_colormap_type; - stbi__get8(s); // discard Offset - tga_colormap_type = stbi__get8(s); // colormap type - if( tga_colormap_type > 1 ) { - stbi__rewind(s); - return 0; // only RGB or indexed allowed - } - tga_image_type = stbi__get8(s); // image type - if ( tga_colormap_type == 1 ) { // colormapped (paletted) image - if (tga_image_type != 1 && tga_image_type != 9) { - stbi__rewind(s); - return 0; - } - stbi__skip(s,4); // skip index of first colormap entry and number of entries - sz = stbi__get8(s); // check bits per palette color entry - if ( (sz != 8) && (sz != 15) && (sz != 16) && (sz != 24) && (sz != 32) ) { - stbi__rewind(s); - return 0; - } - stbi__skip(s,4); // skip image x and y origin - tga_colormap_bpp = sz; - } else { // "normal" image w/o colormap - only RGB or grey allowed, +/- RLE - if ( (tga_image_type != 2) && (tga_image_type != 3) && (tga_image_type != 10) && (tga_image_type != 11) ) { - stbi__rewind(s); - return 0; // only RGB or grey allowed, +/- RLE - } - stbi__skip(s,9); // skip colormap specification and image x/y origin - tga_colormap_bpp = 0; - } - tga_w = stbi__get16le(s); - if( tga_w < 1 ) { - stbi__rewind(s); - return 0; // test width - } - tga_h = stbi__get16le(s); - if( tga_h < 1 ) { - stbi__rewind(s); - return 0; // test height - } - tga_bits_per_pixel = stbi__get8(s); // bits per pixel - stbi__get8(s); // ignore alpha bits - if (tga_colormap_bpp != 0) { - if((tga_bits_per_pixel != 8) && (tga_bits_per_pixel != 16)) { - // when using a colormap, tga_bits_per_pixel is the size of the indexes - // I don't think anything but 8 or 16bit indexes makes sense - stbi__rewind(s); - return 0; - } - tga_comp = stbi__tga_get_comp(tga_colormap_bpp, 0, NULL); - } else { - tga_comp = stbi__tga_get_comp(tga_bits_per_pixel, (tga_image_type == 3) || (tga_image_type == 11), NULL); - } - if(!tga_comp) { - stbi__rewind(s); - return 0; - } - if (x) *x = tga_w; - if (y) *y = tga_h; - if (comp) *comp = tga_comp; - return 1; // seems to have passed everything -} - -static int stbi__tga_test(stbi__context *s) -{ - int res = 0; - int sz, tga_color_type; - stbi__get8(s); // discard Offset - tga_color_type = stbi__get8(s); // color type - if ( tga_color_type > 1 ) goto errorEnd; // only RGB or indexed allowed - sz = stbi__get8(s); // image type - if ( tga_color_type == 1 ) { // colormapped (paletted) image - if (sz != 1 && sz != 9) goto errorEnd; // colortype 1 demands image type 1 or 9 - stbi__skip(s,4); // skip index of first colormap entry and number of entries - sz = stbi__get8(s); // check bits per palette color entry - if ( (sz != 8) && (sz != 15) && (sz != 16) && (sz != 24) && (sz != 32) ) goto errorEnd; - stbi__skip(s,4); // skip image x and y origin - } else { // "normal" image w/o colormap - if ( (sz != 2) && (sz != 3) && (sz != 10) && (sz != 11) ) goto errorEnd; // only RGB or grey allowed, +/- RLE - stbi__skip(s,9); // skip colormap specification and image x/y origin - } - if ( stbi__get16le(s) < 1 ) goto errorEnd; // test width - if ( stbi__get16le(s) < 1 ) goto errorEnd; // test height - sz = stbi__get8(s); // bits per pixel - if ( (tga_color_type == 1) && (sz != 8) && (sz != 16) ) goto errorEnd; // for colormapped images, bpp is size of an index - if ( (sz != 8) && (sz != 15) && (sz != 16) && (sz != 24) && (sz != 32) ) goto errorEnd; - - res = 1; // if we got this far, everything's good and we can return 1 instead of 0 - -errorEnd: - stbi__rewind(s); - return res; -} - -// read 16bit value and convert to 24bit RGB -static void stbi__tga_read_rgb16(stbi__context *s, stbi_uc* out) -{ - stbi__uint16 px = (stbi__uint16)stbi__get16le(s); - stbi__uint16 fiveBitMask = 31; - // we have 3 channels with 5bits each - int r = (px >> 10) & fiveBitMask; - int g = (px >> 5) & fiveBitMask; - int b = px & fiveBitMask; - // Note that this saves the data in RGB(A) order, so it doesn't need to be swapped later - out[0] = (stbi_uc)((r * 255)/31); - out[1] = (stbi_uc)((g * 255)/31); - out[2] = (stbi_uc)((b * 255)/31); - - // some people claim that the most significant bit might be used for alpha - // (possibly if an alpha-bit is set in the "image descriptor byte") - // but that only made 16bit test images completely translucent.. - // so let's treat all 15 and 16bit TGAs as RGB with no alpha. -} - -static void *stbi__tga_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - // read in the TGA header stuff - int tga_offset = stbi__get8(s); - int tga_indexed = stbi__get8(s); - int tga_image_type = stbi__get8(s); - int tga_is_RLE = 0; - int tga_palette_start = stbi__get16le(s); - int tga_palette_len = stbi__get16le(s); - int tga_palette_bits = stbi__get8(s); - int tga_x_origin = stbi__get16le(s); - int tga_y_origin = stbi__get16le(s); - int tga_width = stbi__get16le(s); - int tga_height = stbi__get16le(s); - int tga_bits_per_pixel = stbi__get8(s); - int tga_comp, tga_rgb16=0; - int tga_inverted = stbi__get8(s); - // int tga_alpha_bits = tga_inverted & 15; // the 4 lowest bits - unused (useless?) - // image data - unsigned char *tga_data; - unsigned char *tga_palette = NULL; - int i, j; - unsigned char raw_data[4] = {0}; - int RLE_count = 0; - int RLE_repeating = 0; - int read_next_pixel = 1; - STBI_NOTUSED(ri); - STBI_NOTUSED(tga_x_origin); // @TODO - STBI_NOTUSED(tga_y_origin); // @TODO - - if (tga_height > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - if (tga_width > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - - // do a tiny bit of precessing - if ( tga_image_type >= 8 ) - { - tga_image_type -= 8; - tga_is_RLE = 1; - } - tga_inverted = 1 - ((tga_inverted >> 5) & 1); - - // If I'm paletted, then I'll use the number of bits from the palette - if ( tga_indexed ) tga_comp = stbi__tga_get_comp(tga_palette_bits, 0, &tga_rgb16); - else tga_comp = stbi__tga_get_comp(tga_bits_per_pixel, (tga_image_type == 3), &tga_rgb16); - - if(!tga_comp) // shouldn't really happen, stbi__tga_test() should have ensured basic consistency - return stbi__errpuc("bad format", "Can't find out TGA pixelformat"); - - // tga info - *x = tga_width; - *y = tga_height; - if (comp) *comp = tga_comp; - - if (!stbi__mad3sizes_valid(tga_width, tga_height, tga_comp, 0)) - return stbi__errpuc("too large", "Corrupt TGA"); - - tga_data = (unsigned char*)stbi__malloc_mad3(tga_width, tga_height, tga_comp, 0); - if (!tga_data) return stbi__errpuc("outofmem", "Out of memory"); - - // skip to the data's starting position (offset usually = 0) - stbi__skip(s, tga_offset ); - - if ( !tga_indexed && !tga_is_RLE && !tga_rgb16 ) { - for (i=0; i < tga_height; ++i) { - int row = tga_inverted ? tga_height -i - 1 : i; - stbi_uc *tga_row = tga_data + row*tga_width*tga_comp; - stbi__getn(s, tga_row, tga_width * tga_comp); - } - } else { - // do I need to load a palette? - if ( tga_indexed) - { - if (tga_palette_len == 0) { /* you have to have at least one entry! */ - STBI_FREE(tga_data); - return stbi__errpuc("bad palette", "Corrupt TGA"); - } - - // any data to skip? (offset usually = 0) - stbi__skip(s, tga_palette_start ); - // load the palette - tga_palette = (unsigned char*)stbi__malloc_mad2(tga_palette_len, tga_comp, 0); - if (!tga_palette) { - STBI_FREE(tga_data); - return stbi__errpuc("outofmem", "Out of memory"); - } - if (tga_rgb16) { - stbi_uc *pal_entry = tga_palette; - STBI_ASSERT(tga_comp == STBI_rgb); - for (i=0; i < tga_palette_len; ++i) { - stbi__tga_read_rgb16(s, pal_entry); - pal_entry += tga_comp; - } - } else if (!stbi__getn(s, tga_palette, tga_palette_len * tga_comp)) { - STBI_FREE(tga_data); - STBI_FREE(tga_palette); - return stbi__errpuc("bad palette", "Corrupt TGA"); - } - } - // load the data - for (i=0; i < tga_width * tga_height; ++i) - { - // if I'm in RLE mode, do I need to get a RLE stbi__pngchunk? - if ( tga_is_RLE ) - { - if ( RLE_count == 0 ) - { - // yep, get the next byte as a RLE command - int RLE_cmd = stbi__get8(s); - RLE_count = 1 + (RLE_cmd & 127); - RLE_repeating = RLE_cmd >> 7; - read_next_pixel = 1; - } else if ( !RLE_repeating ) - { - read_next_pixel = 1; - } - } else - { - read_next_pixel = 1; - } - // OK, if I need to read a pixel, do it now - if ( read_next_pixel ) - { - // load however much data we did have - if ( tga_indexed ) - { - // read in index, then perform the lookup - int pal_idx = (tga_bits_per_pixel == 8) ? stbi__get8(s) : stbi__get16le(s); - if ( pal_idx >= tga_palette_len ) { - // invalid index - pal_idx = 0; - } - pal_idx *= tga_comp; - for (j = 0; j < tga_comp; ++j) { - raw_data[j] = tga_palette[pal_idx+j]; - } - } else if(tga_rgb16) { - STBI_ASSERT(tga_comp == STBI_rgb); - stbi__tga_read_rgb16(s, raw_data); - } else { - // read in the data raw - for (j = 0; j < tga_comp; ++j) { - raw_data[j] = stbi__get8(s); - } - } - // clear the reading flag for the next pixel - read_next_pixel = 0; - } // end of reading a pixel - - // copy data - for (j = 0; j < tga_comp; ++j) - tga_data[i*tga_comp+j] = raw_data[j]; - - // in case we're in RLE mode, keep counting down - --RLE_count; - } - // do I need to invert the image? - if ( tga_inverted ) - { - for (j = 0; j*2 < tga_height; ++j) - { - int index1 = j * tga_width * tga_comp; - int index2 = (tga_height - 1 - j) * tga_width * tga_comp; - for (i = tga_width * tga_comp; i > 0; --i) - { - unsigned char temp = tga_data[index1]; - tga_data[index1] = tga_data[index2]; - tga_data[index2] = temp; - ++index1; - ++index2; - } - } - } - // clear my palette, if I had one - if ( tga_palette != NULL ) - { - STBI_FREE( tga_palette ); - } - } - - // swap RGB - if the source data was RGB16, it already is in the right order - if (tga_comp >= 3 && !tga_rgb16) - { - unsigned char* tga_pixel = tga_data; - for (i=0; i < tga_width * tga_height; ++i) - { - unsigned char temp = tga_pixel[0]; - tga_pixel[0] = tga_pixel[2]; - tga_pixel[2] = temp; - tga_pixel += tga_comp; - } - } - - // convert to target component count - if (req_comp && req_comp != tga_comp) - tga_data = stbi__convert_format(tga_data, tga_comp, req_comp, tga_width, tga_height); - - // the things I do to get rid of an error message, and yet keep - // Microsoft's C compilers happy... [8^( - tga_palette_start = tga_palette_len = tga_palette_bits = - tga_x_origin = tga_y_origin = 0; - STBI_NOTUSED(tga_palette_start); - // OK, done - return tga_data; -} -#endif - -// ************************************************************************************************* -// Photoshop PSD loader -- PD by Thatcher Ulrich, integration by Nicolas Schulz, tweaked by STB - -#ifndef STBI_NO_PSD -static int stbi__psd_test(stbi__context *s) -{ - int r = (stbi__get32be(s) == 0x38425053); - stbi__rewind(s); - return r; -} - -static int stbi__psd_decode_rle(stbi__context *s, stbi_uc *p, int pixelCount) -{ - int count, nleft, len; - - count = 0; - while ((nleft = pixelCount - count) > 0) { - len = stbi__get8(s); - if (len == 128) { - // No-op. - } else if (len < 128) { - // Copy next len+1 bytes literally. - len++; - if (len > nleft) return 0; // corrupt data - count += len; - while (len) { - *p = stbi__get8(s); - p += 4; - len--; - } - } else if (len > 128) { - stbi_uc val; - // Next -len+1 bytes in the dest are replicated from next source byte. - // (Interpret len as a negative 8-bit int.) - len = 257 - len; - if (len > nleft) return 0; // corrupt data - val = stbi__get8(s); - count += len; - while (len) { - *p = val; - p += 4; - len--; - } - } - } - - return 1; -} - -static void *stbi__psd_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri, int bpc) -{ - int pixelCount; - int channelCount, compression; - int channel, i; - int bitdepth; - int w,h; - stbi_uc *out; - STBI_NOTUSED(ri); - - // Check identifier - if (stbi__get32be(s) != 0x38425053) // "8BPS" - return stbi__errpuc("not PSD", "Corrupt PSD image"); - - // Check file type version. - if (stbi__get16be(s) != 1) - return stbi__errpuc("wrong version", "Unsupported version of PSD image"); - - // Skip 6 reserved bytes. - stbi__skip(s, 6 ); - - // Read the number of channels (R, G, B, A, etc). - channelCount = stbi__get16be(s); - if (channelCount < 0 || channelCount > 16) - return stbi__errpuc("wrong channel count", "Unsupported number of channels in PSD image"); - - // Read the rows and columns of the image. - h = stbi__get32be(s); - w = stbi__get32be(s); - - if (h > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - if (w > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - - // Make sure the depth is 8 bits. - bitdepth = stbi__get16be(s); - if (bitdepth != 8 && bitdepth != 16) - return stbi__errpuc("unsupported bit depth", "PSD bit depth is not 8 or 16 bit"); - - // Make sure the color mode is RGB. - // Valid options are: - // 0: Bitmap - // 1: Grayscale - // 2: Indexed color - // 3: RGB color - // 4: CMYK color - // 7: Multichannel - // 8: Duotone - // 9: Lab color - if (stbi__get16be(s) != 3) - return stbi__errpuc("wrong color format", "PSD is not in RGB color format"); - - // Skip the Mode Data. (It's the palette for indexed color; other info for other modes.) - stbi__skip(s,stbi__get32be(s) ); - - // Skip the image resources. (resolution, pen tool paths, etc) - stbi__skip(s, stbi__get32be(s) ); - - // Skip the reserved data. - stbi__skip(s, stbi__get32be(s) ); - - // Find out if the data is compressed. - // Known values: - // 0: no compression - // 1: RLE compressed - compression = stbi__get16be(s); - if (compression > 1) - return stbi__errpuc("bad compression", "PSD has an unknown compression format"); - - // Check size - if (!stbi__mad3sizes_valid(4, w, h, 0)) - return stbi__errpuc("too large", "Corrupt PSD"); - - // Create the destination image. - - if (!compression && bitdepth == 16 && bpc == 16) { - out = (stbi_uc *) stbi__malloc_mad3(8, w, h, 0); - ri->bits_per_channel = 16; - } else - out = (stbi_uc *) stbi__malloc(4 * w*h); - - if (!out) return stbi__errpuc("outofmem", "Out of memory"); - pixelCount = w*h; - - // Initialize the data to zero. - //memset( out, 0, pixelCount * 4 ); - - // Finally, the image data. - if (compression) { - // RLE as used by .PSD and .TIFF - // Loop until you get the number of unpacked bytes you are expecting: - // Read the next source byte into n. - // If n is between 0 and 127 inclusive, copy the next n+1 bytes literally. - // Else if n is between -127 and -1 inclusive, copy the next byte -n+1 times. - // Else if n is 128, noop. - // Endloop - - // The RLE-compressed data is preceded by a 2-byte data count for each row in the data, - // which we're going to just skip. - stbi__skip(s, h * channelCount * 2 ); - - // Read the RLE data by channel. - for (channel = 0; channel < 4; channel++) { - stbi_uc *p; - - p = out+channel; - if (channel >= channelCount) { - // Fill this channel with default data. - for (i = 0; i < pixelCount; i++, p += 4) - *p = (channel == 3 ? 255 : 0); - } else { - // Read the RLE data. - if (!stbi__psd_decode_rle(s, p, pixelCount)) { - STBI_FREE(out); - return stbi__errpuc("corrupt", "bad RLE data"); - } - } - } - - } else { - // We're at the raw image data. It's each channel in order (Red, Green, Blue, Alpha, ...) - // where each channel consists of an 8-bit (or 16-bit) value for each pixel in the image. - - // Read the data by channel. - for (channel = 0; channel < 4; channel++) { - if (channel >= channelCount) { - // Fill this channel with default data. - if (bitdepth == 16 && bpc == 16) { - stbi__uint16 *q = ((stbi__uint16 *) out) + channel; - stbi__uint16 val = channel == 3 ? 65535 : 0; - for (i = 0; i < pixelCount; i++, q += 4) - *q = val; - } else { - stbi_uc *p = out+channel; - stbi_uc val = channel == 3 ? 255 : 0; - for (i = 0; i < pixelCount; i++, p += 4) - *p = val; - } - } else { - if (ri->bits_per_channel == 16) { // output bpc - stbi__uint16 *q = ((stbi__uint16 *) out) + channel; - for (i = 0; i < pixelCount; i++, q += 4) - *q = (stbi__uint16) stbi__get16be(s); - } else { - stbi_uc *p = out+channel; - if (bitdepth == 16) { // input bpc - for (i = 0; i < pixelCount; i++, p += 4) - *p = (stbi_uc) (stbi__get16be(s) >> 8); - } else { - for (i = 0; i < pixelCount; i++, p += 4) - *p = stbi__get8(s); - } - } - } - } - } - - // remove weird white matte from PSD - if (channelCount >= 4) { - if (ri->bits_per_channel == 16) { - for (i=0; i < w*h; ++i) { - stbi__uint16 *pixel = (stbi__uint16 *) out + 4*i; - if (pixel[3] != 0 && pixel[3] != 65535) { - float a = pixel[3] / 65535.0f; - float ra = 1.0f / a; - float inv_a = 65535.0f * (1 - ra); - pixel[0] = (stbi__uint16) (pixel[0]*ra + inv_a); - pixel[1] = (stbi__uint16) (pixel[1]*ra + inv_a); - pixel[2] = (stbi__uint16) (pixel[2]*ra + inv_a); - } - } - } else { - for (i=0; i < w*h; ++i) { - unsigned char *pixel = out + 4*i; - if (pixel[3] != 0 && pixel[3] != 255) { - float a = pixel[3] / 255.0f; - float ra = 1.0f / a; - float inv_a = 255.0f * (1 - ra); - pixel[0] = (unsigned char) (pixel[0]*ra + inv_a); - pixel[1] = (unsigned char) (pixel[1]*ra + inv_a); - pixel[2] = (unsigned char) (pixel[2]*ra + inv_a); - } - } - } - } - - // convert to desired output format - if (req_comp && req_comp != 4) { - if (ri->bits_per_channel == 16) - out = (stbi_uc *) stbi__convert_format16((stbi__uint16 *) out, 4, req_comp, w, h); - else - out = stbi__convert_format(out, 4, req_comp, w, h); - if (out == NULL) return out; // stbi__convert_format frees input on failure - } - - if (comp) *comp = 4; - *y = h; - *x = w; - - return out; -} -#endif - -// ************************************************************************************************* -// Softimage PIC loader -// by Tom Seddon -// -// See http://softimage.wiki.softimage.com/index.php/INFO:_PIC_file_format -// See http://ozviz.wasp.uwa.edu.au/~pbourke/dataformats/softimagepic/ - -#ifndef STBI_NO_PIC -static int stbi__pic_is4(stbi__context *s,const char *str) -{ - int i; - for (i=0; i<4; ++i) - if (stbi__get8(s) != (stbi_uc)str[i]) - return 0; - - return 1; -} - -static int stbi__pic_test_core(stbi__context *s) -{ - int i; - - if (!stbi__pic_is4(s,"\x53\x80\xF6\x34")) - return 0; - - for(i=0;i<84;++i) - stbi__get8(s); - - if (!stbi__pic_is4(s,"PICT")) - return 0; - - return 1; -} - -typedef struct -{ - stbi_uc size,type,channel; -} stbi__pic_packet; - -static stbi_uc *stbi__readval(stbi__context *s, int channel, stbi_uc *dest) -{ - int mask=0x80, i; - - for (i=0; i<4; ++i, mask>>=1) { - if (channel & mask) { - if (stbi__at_eof(s)) return stbi__errpuc("bad file","PIC file too short"); - dest[i]=stbi__get8(s); - } - } - - return dest; -} - -static void stbi__copyval(int channel,stbi_uc *dest,const stbi_uc *src) -{ - int mask=0x80,i; - - for (i=0;i<4; ++i, mask>>=1) - if (channel&mask) - dest[i]=src[i]; -} - -static stbi_uc *stbi__pic_load_core(stbi__context *s,int width,int height,int *comp, stbi_uc *result) -{ - int act_comp=0,num_packets=0,y,chained; - stbi__pic_packet packets[10]; - - // this will (should...) cater for even some bizarre stuff like having data - // for the same channel in multiple packets. - do { - stbi__pic_packet *packet; - - if (num_packets==sizeof(packets)/sizeof(packets[0])) - return stbi__errpuc("bad format","too many packets"); - - packet = &packets[num_packets++]; - - chained = stbi__get8(s); - packet->size = stbi__get8(s); - packet->type = stbi__get8(s); - packet->channel = stbi__get8(s); - - act_comp |= packet->channel; - - if (stbi__at_eof(s)) return stbi__errpuc("bad file","file too short (reading packets)"); - if (packet->size != 8) return stbi__errpuc("bad format","packet isn't 8bpp"); - } while (chained); - - *comp = (act_comp & 0x10 ? 4 : 3); // has alpha channel? - - for(y=0; ytype) { - default: - return stbi__errpuc("bad format","packet has bad compression type"); - - case 0: {//uncompressed - int x; - - for(x=0;xchannel,dest)) - return 0; - break; - } - - case 1://Pure RLE - { - int left=width, i; - - while (left>0) { - stbi_uc count,value[4]; - - count=stbi__get8(s); - if (stbi__at_eof(s)) return stbi__errpuc("bad file","file too short (pure read count)"); - - if (count > left) - count = (stbi_uc) left; - - if (!stbi__readval(s,packet->channel,value)) return 0; - - for(i=0; ichannel,dest,value); - left -= count; - } - } - break; - - case 2: {//Mixed RLE - int left=width; - while (left>0) { - int count = stbi__get8(s), i; - if (stbi__at_eof(s)) return stbi__errpuc("bad file","file too short (mixed read count)"); - - if (count >= 128) { // Repeated - stbi_uc value[4]; - - if (count==128) - count = stbi__get16be(s); - else - count -= 127; - if (count > left) - return stbi__errpuc("bad file","scanline overrun"); - - if (!stbi__readval(s,packet->channel,value)) - return 0; - - for(i=0;ichannel,dest,value); - } else { // Raw - ++count; - if (count>left) return stbi__errpuc("bad file","scanline overrun"); - - for(i=0;ichannel,dest)) - return 0; - } - left-=count; - } - break; - } - } - } - } - - return result; -} - -static void *stbi__pic_load(stbi__context *s,int *px,int *py,int *comp,int req_comp, stbi__result_info *ri) -{ - stbi_uc *result; - int i, x,y, internal_comp; - STBI_NOTUSED(ri); - - if (!comp) comp = &internal_comp; - - for (i=0; i<92; ++i) - stbi__get8(s); - - x = stbi__get16be(s); - y = stbi__get16be(s); - - if (y > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - if (x > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - - if (stbi__at_eof(s)) return stbi__errpuc("bad file","file too short (pic header)"); - if (!stbi__mad3sizes_valid(x, y, 4, 0)) return stbi__errpuc("too large", "PIC image too large to decode"); - - stbi__get32be(s); //skip `ratio' - stbi__get16be(s); //skip `fields' - stbi__get16be(s); //skip `pad' - - // intermediate buffer is RGBA - result = (stbi_uc *) stbi__malloc_mad3(x, y, 4, 0); - if (!result) return stbi__errpuc("outofmem", "Out of memory"); - memset(result, 0xff, x*y*4); - - if (!stbi__pic_load_core(s,x,y,comp, result)) { - STBI_FREE(result); - result=0; - } - *px = x; - *py = y; - if (req_comp == 0) req_comp = *comp; - result=stbi__convert_format(result,4,req_comp,x,y); - - return result; -} - -static int stbi__pic_test(stbi__context *s) -{ - int r = stbi__pic_test_core(s); - stbi__rewind(s); - return r; -} -#endif - -// ************************************************************************************************* -// GIF loader -- public domain by Jean-Marc Lienher -- simplified/shrunk by stb - -#ifndef STBI_NO_GIF -typedef struct -{ - stbi__int16 prefix; - stbi_uc first; - stbi_uc suffix; -} stbi__gif_lzw; - -typedef struct -{ - int w,h; - stbi_uc *out; // output buffer (always 4 components) - stbi_uc *background; // The current "background" as far as a gif is concerned - stbi_uc *history; - int flags, bgindex, ratio, transparent, eflags; - stbi_uc pal[256][4]; - stbi_uc lpal[256][4]; - stbi__gif_lzw codes[8192]; - stbi_uc *color_table; - int parse, step; - int lflags; - int start_x, start_y; - int max_x, max_y; - int cur_x, cur_y; - int line_size; - int delay; -} stbi__gif; - -static int stbi__gif_test_raw(stbi__context *s) -{ - int sz; - if (stbi__get8(s) != 'G' || stbi__get8(s) != 'I' || stbi__get8(s) != 'F' || stbi__get8(s) != '8') return 0; - sz = stbi__get8(s); - if (sz != '9' && sz != '7') return 0; - if (stbi__get8(s) != 'a') return 0; - return 1; -} - -static int stbi__gif_test(stbi__context *s) -{ - int r = stbi__gif_test_raw(s); - stbi__rewind(s); - return r; -} - -static void stbi__gif_parse_colortable(stbi__context *s, stbi_uc pal[256][4], int num_entries, int transp) -{ - int i; - for (i=0; i < num_entries; ++i) { - pal[i][2] = stbi__get8(s); - pal[i][1] = stbi__get8(s); - pal[i][0] = stbi__get8(s); - pal[i][3] = transp == i ? 0 : 255; - } -} - -static int stbi__gif_header(stbi__context *s, stbi__gif *g, int *comp, int is_info) -{ - stbi_uc version; - if (stbi__get8(s) != 'G' || stbi__get8(s) != 'I' || stbi__get8(s) != 'F' || stbi__get8(s) != '8') - return stbi__err("not GIF", "Corrupt GIF"); - - version = stbi__get8(s); - if (version != '7' && version != '9') return stbi__err("not GIF", "Corrupt GIF"); - if (stbi__get8(s) != 'a') return stbi__err("not GIF", "Corrupt GIF"); - - stbi__g_failure_reason = ""; - g->w = stbi__get16le(s); - g->h = stbi__get16le(s); - g->flags = stbi__get8(s); - g->bgindex = stbi__get8(s); - g->ratio = stbi__get8(s); - g->transparent = -1; - - if (g->w > STBI_MAX_DIMENSIONS) return stbi__err("too large","Very large image (corrupt?)"); - if (g->h > STBI_MAX_DIMENSIONS) return stbi__err("too large","Very large image (corrupt?)"); - - if (comp != 0) *comp = 4; // can't actually tell whether it's 3 or 4 until we parse the comments - - if (is_info) return 1; - - if (g->flags & 0x80) - stbi__gif_parse_colortable(s,g->pal, 2 << (g->flags & 7), -1); - - return 1; -} - -static int stbi__gif_info_raw(stbi__context *s, int *x, int *y, int *comp) -{ - stbi__gif* g = (stbi__gif*) stbi__malloc(sizeof(stbi__gif)); - if (!g) return stbi__err("outofmem", "Out of memory"); - if (!stbi__gif_header(s, g, comp, 1)) { - STBI_FREE(g); - stbi__rewind( s ); - return 0; - } - if (x) *x = g->w; - if (y) *y = g->h; - STBI_FREE(g); - return 1; -} - -static void stbi__out_gif_code(stbi__gif *g, stbi__uint16 code) -{ - stbi_uc *p, *c; - int idx; - - // recurse to decode the prefixes, since the linked-list is backwards, - // and working backwards through an interleaved image would be nasty - if (g->codes[code].prefix >= 0) - stbi__out_gif_code(g, g->codes[code].prefix); - - if (g->cur_y >= g->max_y) return; - - idx = g->cur_x + g->cur_y; - p = &g->out[idx]; - g->history[idx / 4] = 1; - - c = &g->color_table[g->codes[code].suffix * 4]; - if (c[3] > 128) { // don't render transparent pixels; - p[0] = c[2]; - p[1] = c[1]; - p[2] = c[0]; - p[3] = c[3]; - } - g->cur_x += 4; - - if (g->cur_x >= g->max_x) { - g->cur_x = g->start_x; - g->cur_y += g->step; - - while (g->cur_y >= g->max_y && g->parse > 0) { - g->step = (1 << g->parse) * g->line_size; - g->cur_y = g->start_y + (g->step >> 1); - --g->parse; - } - } -} - -static stbi_uc *stbi__process_gif_raster(stbi__context *s, stbi__gif *g) -{ - stbi_uc lzw_cs; - stbi__int32 len, init_code; - stbi__uint32 first; - stbi__int32 codesize, codemask, avail, oldcode, bits, valid_bits, clear; - stbi__gif_lzw *p; - - lzw_cs = stbi__get8(s); - if (lzw_cs > 12) return NULL; - clear = 1 << lzw_cs; - first = 1; - codesize = lzw_cs + 1; - codemask = (1 << codesize) - 1; - bits = 0; - valid_bits = 0; - for (init_code = 0; init_code < clear; init_code++) { - g->codes[init_code].prefix = -1; - g->codes[init_code].first = (stbi_uc) init_code; - g->codes[init_code].suffix = (stbi_uc) init_code; - } - - // support no starting clear code - avail = clear+2; - oldcode = -1; - - len = 0; - for(;;) { - if (valid_bits < codesize) { - if (len == 0) { - len = stbi__get8(s); // start new block - if (len == 0) - return g->out; - } - --len; - bits |= (stbi__int32) stbi__get8(s) << valid_bits; - valid_bits += 8; - } else { - stbi__int32 code = bits & codemask; - bits >>= codesize; - valid_bits -= codesize; - // @OPTIMIZE: is there some way we can accelerate the non-clear path? - if (code == clear) { // clear code - codesize = lzw_cs + 1; - codemask = (1 << codesize) - 1; - avail = clear + 2; - oldcode = -1; - first = 0; - } else if (code == clear + 1) { // end of stream code - stbi__skip(s, len); - while ((len = stbi__get8(s)) > 0) - stbi__skip(s,len); - return g->out; - } else if (code <= avail) { - if (first) { - return stbi__errpuc("no clear code", "Corrupt GIF"); - } - - if (oldcode >= 0) { - p = &g->codes[avail++]; - if (avail > 8192) { - return stbi__errpuc("too many codes", "Corrupt GIF"); - } - - p->prefix = (stbi__int16) oldcode; - p->first = g->codes[oldcode].first; - p->suffix = (code == avail) ? p->first : g->codes[code].first; - } else if (code == avail) - return stbi__errpuc("illegal code in raster", "Corrupt GIF"); - - stbi__out_gif_code(g, (stbi__uint16) code); - - if ((avail & codemask) == 0 && avail <= 0x0FFF) { - codesize++; - codemask = (1 << codesize) - 1; - } - - oldcode = code; - } else { - return stbi__errpuc("illegal code in raster", "Corrupt GIF"); - } - } - } -} - -// this function is designed to support animated gifs, although stb_image doesn't support it -// two back is the image from two frames ago, used for a very specific disposal format -static stbi_uc *stbi__gif_load_next(stbi__context *s, stbi__gif *g, int *comp, int req_comp, stbi_uc *two_back) -{ - int dispose; - int first_frame; - int pi; - int pcount; - STBI_NOTUSED(req_comp); - - // on first frame, any non-written pixels get the background colour (non-transparent) - first_frame = 0; - if (g->out == 0) { - if (!stbi__gif_header(s, g, comp,0)) return 0; // stbi__g_failure_reason set by stbi__gif_header - if (!stbi__mad3sizes_valid(4, g->w, g->h, 0)) - return stbi__errpuc("too large", "GIF image is too large"); - pcount = g->w * g->h; - g->out = (stbi_uc *) stbi__malloc(4 * pcount); - g->background = (stbi_uc *) stbi__malloc(4 * pcount); - g->history = (stbi_uc *) stbi__malloc(pcount); - if (!g->out || !g->background || !g->history) - return stbi__errpuc("outofmem", "Out of memory"); - - // image is treated as "transparent" at the start - ie, nothing overwrites the current background; - // background colour is only used for pixels that are not rendered first frame, after that "background" - // color refers to the color that was there the previous frame. - memset(g->out, 0x00, 4 * pcount); - memset(g->background, 0x00, 4 * pcount); // state of the background (starts transparent) - memset(g->history, 0x00, pcount); // pixels that were affected previous frame - first_frame = 1; - } else { - // second frame - how do we dispose of the previous one? - dispose = (g->eflags & 0x1C) >> 2; - pcount = g->w * g->h; - - if ((dispose == 3) && (two_back == 0)) { - dispose = 2; // if I don't have an image to revert back to, default to the old background - } - - if (dispose == 3) { // use previous graphic - for (pi = 0; pi < pcount; ++pi) { - if (g->history[pi]) { - memcpy( &g->out[pi * 4], &two_back[pi * 4], 4 ); - } - } - } else if (dispose == 2) { - // restore what was changed last frame to background before that frame; - for (pi = 0; pi < pcount; ++pi) { - if (g->history[pi]) { - memcpy( &g->out[pi * 4], &g->background[pi * 4], 4 ); - } - } - } else { - // This is a non-disposal case eithe way, so just - // leave the pixels as is, and they will become the new background - // 1: do not dispose - // 0: not specified. - } - - // background is what out is after the undoing of the previou frame; - memcpy( g->background, g->out, 4 * g->w * g->h ); - } - - // clear my history; - memset( g->history, 0x00, g->w * g->h ); // pixels that were affected previous frame - - for (;;) { - int tag = stbi__get8(s); - switch (tag) { - case 0x2C: /* Image Descriptor */ - { - stbi__int32 x, y, w, h; - stbi_uc *o; - - x = stbi__get16le(s); - y = stbi__get16le(s); - w = stbi__get16le(s); - h = stbi__get16le(s); - if (((x + w) > (g->w)) || ((y + h) > (g->h))) - return stbi__errpuc("bad Image Descriptor", "Corrupt GIF"); - - g->line_size = g->w * 4; - g->start_x = x * 4; - g->start_y = y * g->line_size; - g->max_x = g->start_x + w * 4; - g->max_y = g->start_y + h * g->line_size; - g->cur_x = g->start_x; - g->cur_y = g->start_y; - - // if the width of the specified rectangle is 0, that means - // we may not see *any* pixels or the image is malformed; - // to make sure this is caught, move the current y down to - // max_y (which is what out_gif_code checks). - if (w == 0) - g->cur_y = g->max_y; - - g->lflags = stbi__get8(s); - - if (g->lflags & 0x40) { - g->step = 8 * g->line_size; // first interlaced spacing - g->parse = 3; - } else { - g->step = g->line_size; - g->parse = 0; - } - - if (g->lflags & 0x80) { - stbi__gif_parse_colortable(s,g->lpal, 2 << (g->lflags & 7), g->eflags & 0x01 ? g->transparent : -1); - g->color_table = (stbi_uc *) g->lpal; - } else if (g->flags & 0x80) { - g->color_table = (stbi_uc *) g->pal; - } else - return stbi__errpuc("missing color table", "Corrupt GIF"); - - o = stbi__process_gif_raster(s, g); - if (!o) return NULL; - - // if this was the first frame, - pcount = g->w * g->h; - if (first_frame && (g->bgindex > 0)) { - // if first frame, any pixel not drawn to gets the background color - for (pi = 0; pi < pcount; ++pi) { - if (g->history[pi] == 0) { - g->pal[g->bgindex][3] = 255; // just in case it was made transparent, undo that; It will be reset next frame if need be; - memcpy( &g->out[pi * 4], &g->pal[g->bgindex], 4 ); - } - } - } - - return o; - } - - case 0x21: // Comment Extension. - { - int len; - int ext = stbi__get8(s); - if (ext == 0xF9) { // Graphic Control Extension. - len = stbi__get8(s); - if (len == 4) { - g->eflags = stbi__get8(s); - g->delay = 10 * stbi__get16le(s); // delay - 1/100th of a second, saving as 1/1000ths. - - // unset old transparent - if (g->transparent >= 0) { - g->pal[g->transparent][3] = 255; - } - if (g->eflags & 0x01) { - g->transparent = stbi__get8(s); - if (g->transparent >= 0) { - g->pal[g->transparent][3] = 0; - } - } else { - // don't need transparent - stbi__skip(s, 1); - g->transparent = -1; - } - } else { - stbi__skip(s, len); - break; - } - } - while ((len = stbi__get8(s)) != 0) { - stbi__skip(s, len); - } - break; - } - - case 0x3B: // gif stream termination code - return (stbi_uc *) s; // using '1' causes warning on some compilers - - default: - return stbi__errpuc("unknown code", "Corrupt GIF"); - } - } -} - -static void *stbi__load_gif_main_outofmem(stbi__gif *g, stbi_uc *out, int **delays) -{ - STBI_FREE(g->out); - STBI_FREE(g->history); - STBI_FREE(g->background); - - if (out) STBI_FREE(out); - if (delays && *delays) STBI_FREE(*delays); - return stbi__errpuc("outofmem", "Out of memory"); -} - -static void *stbi__load_gif_main(stbi__context *s, int **delays, int *x, int *y, int *z, int *comp, int req_comp) -{ - if (stbi__gif_test(s)) { - int layers = 0; - stbi_uc *u = 0; - stbi_uc *out = 0; - stbi_uc *two_back = 0; - stbi__gif g; - int stride; - int out_size = 0; - int delays_size = 0; - - STBI_NOTUSED(out_size); - STBI_NOTUSED(delays_size); - - memset(&g, 0, sizeof(g)); - if (delays) { - *delays = 0; - } - - do { - u = stbi__gif_load_next(s, &g, comp, req_comp, two_back); - if (u == (stbi_uc *) s) u = 0; // end of animated gif marker - - if (u) { - *x = g.w; - *y = g.h; - ++layers; - stride = g.w * g.h * 4; - - if (out) { - void *tmp = (stbi_uc*) STBI_REALLOC_SIZED( out, out_size, layers * stride ); - if (!tmp) - return stbi__load_gif_main_outofmem(&g, out, delays); - else { - out = (stbi_uc*) tmp; - out_size = layers * stride; - } - - if (delays) { - int *new_delays = (int*) STBI_REALLOC_SIZED( *delays, delays_size, sizeof(int) * layers ); - if (!new_delays) - return stbi__load_gif_main_outofmem(&g, out, delays); - *delays = new_delays; - delays_size = layers * sizeof(int); - } - } else { - out = (stbi_uc*)stbi__malloc( layers * stride ); - if (!out) - return stbi__load_gif_main_outofmem(&g, out, delays); - out_size = layers * stride; - if (delays) { - *delays = (int*) stbi__malloc( layers * sizeof(int) ); - if (!*delays) - return stbi__load_gif_main_outofmem(&g, out, delays); - delays_size = layers * sizeof(int); - } - } - memcpy( out + ((layers - 1) * stride), u, stride ); - if (layers >= 2) { - two_back = out - 2 * stride; - } - - if (delays) { - (*delays)[layers - 1U] = g.delay; - } - } - } while (u != 0); - - // free temp buffer; - STBI_FREE(g.out); - STBI_FREE(g.history); - STBI_FREE(g.background); - - // do the final conversion after loading everything; - if (req_comp && req_comp != 4) - out = stbi__convert_format(out, 4, req_comp, layers * g.w, g.h); - - *z = layers; - return out; - } else { - return stbi__errpuc("not GIF", "Image was not as a gif type."); - } -} - -static void *stbi__gif_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - stbi_uc *u = 0; - stbi__gif g; - memset(&g, 0, sizeof(g)); - STBI_NOTUSED(ri); - - u = stbi__gif_load_next(s, &g, comp, req_comp, 0); - if (u == (stbi_uc *) s) u = 0; // end of animated gif marker - if (u) { - *x = g.w; - *y = g.h; - - // moved conversion to after successful load so that the same - // can be done for multiple frames. - if (req_comp && req_comp != 4) - u = stbi__convert_format(u, 4, req_comp, g.w, g.h); - } else if (g.out) { - // if there was an error and we allocated an image buffer, free it! - STBI_FREE(g.out); - } - - // free buffers needed for multiple frame loading; - STBI_FREE(g.history); - STBI_FREE(g.background); - - return u; -} - -static int stbi__gif_info(stbi__context *s, int *x, int *y, int *comp) -{ - return stbi__gif_info_raw(s,x,y,comp); -} -#endif - -// ************************************************************************************************* -// Radiance RGBE HDR loader -// originally by Nicolas Schulz -#ifndef STBI_NO_HDR -static int stbi__hdr_test_core(stbi__context *s, const char *signature) -{ - int i; - for (i=0; signature[i]; ++i) - if (stbi__get8(s) != signature[i]) - return 0; - stbi__rewind(s); - return 1; -} - -static int stbi__hdr_test(stbi__context* s) -{ - int r = stbi__hdr_test_core(s, "#?RADIANCE\n"); - stbi__rewind(s); - if(!r) { - r = stbi__hdr_test_core(s, "#?RGBE\n"); - stbi__rewind(s); - } - return r; -} - -#define STBI__HDR_BUFLEN 1024 -static char *stbi__hdr_gettoken(stbi__context *z, char *buffer) -{ - int len=0; - char c = '\0'; - - c = (char) stbi__get8(z); - - while (!stbi__at_eof(z) && c != '\n') { - buffer[len++] = c; - if (len == STBI__HDR_BUFLEN-1) { - // flush to end of line - while (!stbi__at_eof(z) && stbi__get8(z) != '\n') - ; - break; - } - c = (char) stbi__get8(z); - } - - buffer[len] = 0; - return buffer; -} - -static void stbi__hdr_convert(float *output, stbi_uc *input, int req_comp) -{ - if ( input[3] != 0 ) { - float f1; - // Exponent - f1 = (float) ldexp(1.0f, input[3] - (int)(128 + 8)); - if (req_comp <= 2) - output[0] = (input[0] + input[1] + input[2]) * f1 / 3; - else { - output[0] = input[0] * f1; - output[1] = input[1] * f1; - output[2] = input[2] * f1; - } - if (req_comp == 2) output[1] = 1; - if (req_comp == 4) output[3] = 1; - } else { - switch (req_comp) { - case 4: output[3] = 1; /* fallthrough */ - case 3: output[0] = output[1] = output[2] = 0; - break; - case 2: output[1] = 1; /* fallthrough */ - case 1: output[0] = 0; - break; - } - } -} - -static float *stbi__hdr_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - char buffer[STBI__HDR_BUFLEN]; - char *token; - int valid = 0; - int width, height; - stbi_uc *scanline; - float *hdr_data; - int len; - unsigned char count, value; - int i, j, k, c1,c2, z; - const char *headerToken; - STBI_NOTUSED(ri); - - // Check identifier - headerToken = stbi__hdr_gettoken(s,buffer); - if (strcmp(headerToken, "#?RADIANCE") != 0 && strcmp(headerToken, "#?RGBE") != 0) - return stbi__errpf("not HDR", "Corrupt HDR image"); - - // Parse header - for(;;) { - token = stbi__hdr_gettoken(s,buffer); - if (token[0] == 0) break; - if (strcmp(token, "FORMAT=32-bit_rle_rgbe") == 0) valid = 1; - } - - if (!valid) return stbi__errpf("unsupported format", "Unsupported HDR format"); - - // Parse width and height - // can't use sscanf() if we're not using stdio! - token = stbi__hdr_gettoken(s,buffer); - if (strncmp(token, "-Y ", 3)) return stbi__errpf("unsupported data layout", "Unsupported HDR format"); - token += 3; - height = (int) strtol(token, &token, 10); - while (*token == ' ') ++token; - if (strncmp(token, "+X ", 3)) return stbi__errpf("unsupported data layout", "Unsupported HDR format"); - token += 3; - width = (int) strtol(token, NULL, 10); - - if (height > STBI_MAX_DIMENSIONS) return stbi__errpf("too large","Very large image (corrupt?)"); - if (width > STBI_MAX_DIMENSIONS) return stbi__errpf("too large","Very large image (corrupt?)"); - - *x = width; - *y = height; - - if (comp) *comp = 3; - if (req_comp == 0) req_comp = 3; - - if (!stbi__mad4sizes_valid(width, height, req_comp, sizeof(float), 0)) - return stbi__errpf("too large", "HDR image is too large"); - - // Read data - hdr_data = (float *) stbi__malloc_mad4(width, height, req_comp, sizeof(float), 0); - if (!hdr_data) - return stbi__errpf("outofmem", "Out of memory"); - - // Load image data - // image data is stored as some number of sca - if ( width < 8 || width >= 32768) { - // Read flat data - for (j=0; j < height; ++j) { - for (i=0; i < width; ++i) { - stbi_uc rgbe[4]; - main_decode_loop: - stbi__getn(s, rgbe, 4); - stbi__hdr_convert(hdr_data + j * width * req_comp + i * req_comp, rgbe, req_comp); - } - } - } else { - // Read RLE-encoded data - scanline = NULL; - - for (j = 0; j < height; ++j) { - c1 = stbi__get8(s); - c2 = stbi__get8(s); - len = stbi__get8(s); - if (c1 != 2 || c2 != 2 || (len & 0x80)) { - // not run-length encoded, so we have to actually use THIS data as a decoded - // pixel (note this can't be a valid pixel--one of RGB must be >= 128) - stbi_uc rgbe[4]; - rgbe[0] = (stbi_uc) c1; - rgbe[1] = (stbi_uc) c2; - rgbe[2] = (stbi_uc) len; - rgbe[3] = (stbi_uc) stbi__get8(s); - stbi__hdr_convert(hdr_data, rgbe, req_comp); - i = 1; - j = 0; - STBI_FREE(scanline); - goto main_decode_loop; // yes, this makes no sense - } - len <<= 8; - len |= stbi__get8(s); - if (len != width) { STBI_FREE(hdr_data); STBI_FREE(scanline); return stbi__errpf("invalid decoded scanline length", "corrupt HDR"); } - if (scanline == NULL) { - scanline = (stbi_uc *) stbi__malloc_mad2(width, 4, 0); - if (!scanline) { - STBI_FREE(hdr_data); - return stbi__errpf("outofmem", "Out of memory"); - } - } - - for (k = 0; k < 4; ++k) { - int nleft; - i = 0; - while ((nleft = width - i) > 0) { - count = stbi__get8(s); - if (count > 128) { - // Run - value = stbi__get8(s); - count -= 128; - if ((count == 0) || (count > nleft)) { STBI_FREE(hdr_data); STBI_FREE(scanline); return stbi__errpf("corrupt", "bad RLE data in HDR"); } - for (z = 0; z < count; ++z) - scanline[i++ * 4 + k] = value; - } else { - // Dump - if ((count == 0) || (count > nleft)) { STBI_FREE(hdr_data); STBI_FREE(scanline); return stbi__errpf("corrupt", "bad RLE data in HDR"); } - for (z = 0; z < count; ++z) - scanline[i++ * 4 + k] = stbi__get8(s); - } - } - } - for (i=0; i < width; ++i) - stbi__hdr_convert(hdr_data+(j*width + i)*req_comp, scanline + i*4, req_comp); - } - if (scanline) - STBI_FREE(scanline); - } - - return hdr_data; -} - -static int stbi__hdr_info(stbi__context *s, int *x, int *y, int *comp) -{ - char buffer[STBI__HDR_BUFLEN]; - char *token; - int valid = 0; - int dummy; - - if (!x) x = &dummy; - if (!y) y = &dummy; - if (!comp) comp = &dummy; - - if (stbi__hdr_test(s) == 0) { - stbi__rewind( s ); - return 0; - } - - for(;;) { - token = stbi__hdr_gettoken(s,buffer); - if (token[0] == 0) break; - if (strcmp(token, "FORMAT=32-bit_rle_rgbe") == 0) valid = 1; - } - - if (!valid) { - stbi__rewind( s ); - return 0; - } - token = stbi__hdr_gettoken(s,buffer); - if (strncmp(token, "-Y ", 3)) { - stbi__rewind( s ); - return 0; - } - token += 3; - *y = (int) strtol(token, &token, 10); - while (*token == ' ') ++token; - if (strncmp(token, "+X ", 3)) { - stbi__rewind( s ); - return 0; - } - token += 3; - *x = (int) strtol(token, NULL, 10); - *comp = 3; - return 1; -} -#endif // STBI_NO_HDR - -#ifndef STBI_NO_BMP -static int stbi__bmp_info(stbi__context *s, int *x, int *y, int *comp) -{ - void *p; - stbi__bmp_data info; - - info.all_a = 255; - p = stbi__bmp_parse_header(s, &info); - if (p == NULL) { - stbi__rewind( s ); - return 0; - } - if (x) *x = s->img_x; - if (y) *y = s->img_y; - if (comp) { - if (info.bpp == 24 && info.ma == 0xff000000) - *comp = 3; - else - *comp = info.ma ? 4 : 3; - } - return 1; -} -#endif - -#ifndef STBI_NO_PSD -static int stbi__psd_info(stbi__context *s, int *x, int *y, int *comp) -{ - int channelCount, dummy, depth; - if (!x) x = &dummy; - if (!y) y = &dummy; - if (!comp) comp = &dummy; - if (stbi__get32be(s) != 0x38425053) { - stbi__rewind( s ); - return 0; - } - if (stbi__get16be(s) != 1) { - stbi__rewind( s ); - return 0; - } - stbi__skip(s, 6); - channelCount = stbi__get16be(s); - if (channelCount < 0 || channelCount > 16) { - stbi__rewind( s ); - return 0; - } - *y = stbi__get32be(s); - *x = stbi__get32be(s); - depth = stbi__get16be(s); - if (depth != 8 && depth != 16) { - stbi__rewind( s ); - return 0; - } - if (stbi__get16be(s) != 3) { - stbi__rewind( s ); - return 0; - } - *comp = 4; - return 1; -} - -static int stbi__psd_is16(stbi__context *s) -{ - int channelCount, depth; - if (stbi__get32be(s) != 0x38425053) { - stbi__rewind( s ); - return 0; - } - if (stbi__get16be(s) != 1) { - stbi__rewind( s ); - return 0; - } - stbi__skip(s, 6); - channelCount = stbi__get16be(s); - if (channelCount < 0 || channelCount > 16) { - stbi__rewind( s ); - return 0; - } - STBI_NOTUSED(stbi__get32be(s)); - STBI_NOTUSED(stbi__get32be(s)); - depth = stbi__get16be(s); - if (depth != 16) { - stbi__rewind( s ); - return 0; - } - return 1; -} -#endif - -#ifndef STBI_NO_PIC -static int stbi__pic_info(stbi__context *s, int *x, int *y, int *comp) -{ - int act_comp=0,num_packets=0,chained,dummy; - stbi__pic_packet packets[10]; - - if (!x) x = &dummy; - if (!y) y = &dummy; - if (!comp) comp = &dummy; - - if (!stbi__pic_is4(s,"\x53\x80\xF6\x34")) { - stbi__rewind(s); - return 0; - } - - stbi__skip(s, 88); - - *x = stbi__get16be(s); - *y = stbi__get16be(s); - if (stbi__at_eof(s)) { - stbi__rewind( s); - return 0; - } - if ( (*x) != 0 && (1 << 28) / (*x) < (*y)) { - stbi__rewind( s ); - return 0; - } - - stbi__skip(s, 8); - - do { - stbi__pic_packet *packet; - - if (num_packets==sizeof(packets)/sizeof(packets[0])) - return 0; - - packet = &packets[num_packets++]; - chained = stbi__get8(s); - packet->size = stbi__get8(s); - packet->type = stbi__get8(s); - packet->channel = stbi__get8(s); - act_comp |= packet->channel; - - if (stbi__at_eof(s)) { - stbi__rewind( s ); - return 0; - } - if (packet->size != 8) { - stbi__rewind( s ); - return 0; - } - } while (chained); - - *comp = (act_comp & 0x10 ? 4 : 3); - - return 1; -} -#endif - -// ************************************************************************************************* -// Portable Gray Map and Portable Pixel Map loader -// by Ken Miller -// -// PGM: http://netpbm.sourceforge.net/doc/pgm.html -// PPM: http://netpbm.sourceforge.net/doc/ppm.html -// -// Known limitations: -// Does not support comments in the header section -// Does not support ASCII image data (formats P2 and P3) - -#ifndef STBI_NO_PNM - -static int stbi__pnm_test(stbi__context *s) -{ - char p, t; - p = (char) stbi__get8(s); - t = (char) stbi__get8(s); - if (p != 'P' || (t != '5' && t != '6')) { - stbi__rewind( s ); - return 0; - } - return 1; -} - -static void *stbi__pnm_load(stbi__context *s, int *x, int *y, int *comp, int req_comp, stbi__result_info *ri) -{ - stbi_uc *out; - STBI_NOTUSED(ri); - - ri->bits_per_channel = stbi__pnm_info(s, (int *)&s->img_x, (int *)&s->img_y, (int *)&s->img_n); - if (ri->bits_per_channel == 0) - return 0; - - if (s->img_y > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - if (s->img_x > STBI_MAX_DIMENSIONS) return stbi__errpuc("too large","Very large image (corrupt?)"); - - *x = s->img_x; - *y = s->img_y; - if (comp) *comp = s->img_n; - - if (!stbi__mad4sizes_valid(s->img_n, s->img_x, s->img_y, ri->bits_per_channel / 8, 0)) - return stbi__errpuc("too large", "PNM too large"); - - out = (stbi_uc *) stbi__malloc_mad4(s->img_n, s->img_x, s->img_y, ri->bits_per_channel / 8, 0); - if (!out) return stbi__errpuc("outofmem", "Out of memory"); - if (!stbi__getn(s, out, s->img_n * s->img_x * s->img_y * (ri->bits_per_channel / 8))) { - STBI_FREE(out); - return stbi__errpuc("bad PNM", "PNM file truncated"); - } - - if (req_comp && req_comp != s->img_n) { - if (ri->bits_per_channel == 16) { - out = (stbi_uc *) stbi__convert_format16((stbi__uint16 *) out, s->img_n, req_comp, s->img_x, s->img_y); - } else { - out = stbi__convert_format(out, s->img_n, req_comp, s->img_x, s->img_y); - } - if (out == NULL) return out; // stbi__convert_format frees input on failure - } - return out; -} - -static int stbi__pnm_isspace(char c) -{ - return c == ' ' || c == '\t' || c == '\n' || c == '\v' || c == '\f' || c == '\r'; -} - -static void stbi__pnm_skip_whitespace(stbi__context *s, char *c) -{ - for (;;) { - while (!stbi__at_eof(s) && stbi__pnm_isspace(*c)) - *c = (char) stbi__get8(s); - - if (stbi__at_eof(s) || *c != '#') - break; - - while (!stbi__at_eof(s) && *c != '\n' && *c != '\r' ) - *c = (char) stbi__get8(s); - } -} - -static int stbi__pnm_isdigit(char c) -{ - return c >= '0' && c <= '9'; -} - -static int stbi__pnm_getinteger(stbi__context *s, char *c) -{ - int value = 0; - - while (!stbi__at_eof(s) && stbi__pnm_isdigit(*c)) { - value = value*10 + (*c - '0'); - *c = (char) stbi__get8(s); - if((value > 214748364) || (value == 214748364 && *c > '7')) - return stbi__err("integer parse overflow", "Parsing an integer in the PPM header overflowed a 32-bit int"); - } - - return value; -} - -static int stbi__pnm_info(stbi__context *s, int *x, int *y, int *comp) -{ - int maxv, dummy; - char c, p, t; - - if (!x) x = &dummy; - if (!y) y = &dummy; - if (!comp) comp = &dummy; - - stbi__rewind(s); - - // Get identifier - p = (char) stbi__get8(s); - t = (char) stbi__get8(s); - if (p != 'P' || (t != '5' && t != '6')) { - stbi__rewind(s); - return 0; - } - - *comp = (t == '6') ? 3 : 1; // '5' is 1-component .pgm; '6' is 3-component .ppm - - c = (char) stbi__get8(s); - stbi__pnm_skip_whitespace(s, &c); - - *x = stbi__pnm_getinteger(s, &c); // read width - if(*x == 0) - return stbi__err("invalid width", "PPM image header had zero or overflowing width"); - stbi__pnm_skip_whitespace(s, &c); - - *y = stbi__pnm_getinteger(s, &c); // read height - if (*y == 0) - return stbi__err("invalid width", "PPM image header had zero or overflowing width"); - stbi__pnm_skip_whitespace(s, &c); - - maxv = stbi__pnm_getinteger(s, &c); // read max value - if (maxv > 65535) - return stbi__err("max value > 65535", "PPM image supports only 8-bit and 16-bit images"); - else if (maxv > 255) - return 16; - else - return 8; -} - -static int stbi__pnm_is16(stbi__context *s) -{ - if (stbi__pnm_info(s, NULL, NULL, NULL) == 16) - return 1; - return 0; -} -#endif - -static int stbi__info_main(stbi__context *s, int *x, int *y, int *comp) -{ - #ifndef STBI_NO_JPEG - if (stbi__jpeg_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_PNG - if (stbi__png_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_GIF - if (stbi__gif_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_BMP - if (stbi__bmp_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_PSD - if (stbi__psd_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_PIC - if (stbi__pic_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_PNM - if (stbi__pnm_info(s, x, y, comp)) return 1; - #endif - - #ifndef STBI_NO_HDR - if (stbi__hdr_info(s, x, y, comp)) return 1; - #endif - - // test tga last because it's a crappy test! - #ifndef STBI_NO_TGA - if (stbi__tga_info(s, x, y, comp)) - return 1; - #endif - return stbi__err("unknown image type", "Image not of any known type, or corrupt"); -} - -static int stbi__is_16_main(stbi__context *s) -{ - #ifndef STBI_NO_PNG - if (stbi__png_is16(s)) return 1; - #endif - - #ifndef STBI_NO_PSD - if (stbi__psd_is16(s)) return 1; - #endif - - #ifndef STBI_NO_PNM - if (stbi__pnm_is16(s)) return 1; - #endif - return 0; -} - -#ifndef STBI_NO_STDIO -STBIDEF int stbi_info(char const *filename, int *x, int *y, int *comp) -{ - FILE *f = stbi__fopen(filename, "rb"); - int result; - if (!f) return stbi__err("can't fopen", "Unable to open file"); - result = stbi_info_from_file(f, x, y, comp); - fclose(f); - return result; -} - -STBIDEF int stbi_info_from_file(FILE *f, int *x, int *y, int *comp) -{ - int r; - stbi__context s; - long pos = ftell(f); - stbi__start_file(&s, f); - r = stbi__info_main(&s,x,y,comp); - fseek(f,pos,SEEK_SET); - return r; -} - -STBIDEF int stbi_is_16_bit(char const *filename) -{ - FILE *f = stbi__fopen(filename, "rb"); - int result; - if (!f) return stbi__err("can't fopen", "Unable to open file"); - result = stbi_is_16_bit_from_file(f); - fclose(f); - return result; -} - -STBIDEF int stbi_is_16_bit_from_file(FILE *f) -{ - int r; - stbi__context s; - long pos = ftell(f); - stbi__start_file(&s, f); - r = stbi__is_16_main(&s); - fseek(f,pos,SEEK_SET); - return r; -} -#endif // !STBI_NO_STDIO - -STBIDEF int stbi_info_from_memory(stbi_uc const *buffer, int len, int *x, int *y, int *comp) -{ - stbi__context s; - stbi__start_mem(&s,buffer,len); - return stbi__info_main(&s,x,y,comp); -} - -STBIDEF int stbi_info_from_callbacks(stbi_io_callbacks const *c, void *user, int *x, int *y, int *comp) -{ - stbi__context s; - stbi__start_callbacks(&s, (stbi_io_callbacks *) c, user); - return stbi__info_main(&s,x,y,comp); -} - -STBIDEF int stbi_is_16_bit_from_memory(stbi_uc const *buffer, int len) -{ - stbi__context s; - stbi__start_mem(&s,buffer,len); - return stbi__is_16_main(&s); -} - -STBIDEF int stbi_is_16_bit_from_callbacks(stbi_io_callbacks const *c, void *user) -{ - stbi__context s; - stbi__start_callbacks(&s, (stbi_io_callbacks *) c, user); - return stbi__is_16_main(&s); -} - -#endif // STB_IMAGE_IMPLEMENTATION - -/* - revision history: - 2.20 (2019-02-07) support utf8 filenames in Windows; fix warnings and platform ifdefs - 2.19 (2018-02-11) fix warning - 2.18 (2018-01-30) fix warnings - 2.17 (2018-01-29) change sbti__shiftsigned to avoid clang -O2 bug - 1-bit BMP - *_is_16_bit api - avoid warnings - 2.16 (2017-07-23) all functions have 16-bit variants; - STBI_NO_STDIO works again; - compilation fixes; - fix rounding in unpremultiply; - optimize vertical flip; - disable raw_len validation; - documentation fixes - 2.15 (2017-03-18) fix png-1,2,4 bug; now all Imagenet JPGs decode; - warning fixes; disable run-time SSE detection on gcc; - uniform handling of optional "return" values; - thread-safe initialization of zlib tables - 2.14 (2017-03-03) remove deprecated STBI_JPEG_OLD; fixes for Imagenet JPGs - 2.13 (2016-11-29) add 16-bit API, only supported for PNG right now - 2.12 (2016-04-02) fix typo in 2.11 PSD fix that caused crashes - 2.11 (2016-04-02) allocate large structures on the stack - remove white matting for transparent PSD - fix reported channel count for PNG & BMP - re-enable SSE2 in non-gcc 64-bit - support RGB-formatted JPEG - read 16-bit PNGs (only as 8-bit) - 2.10 (2016-01-22) avoid warning introduced in 2.09 by STBI_REALLOC_SIZED - 2.09 (2016-01-16) allow comments in PNM files - 16-bit-per-pixel TGA (not bit-per-component) - info() for TGA could break due to .hdr handling - info() for BMP to shares code instead of sloppy parse - can use STBI_REALLOC_SIZED if allocator doesn't support realloc - code cleanup - 2.08 (2015-09-13) fix to 2.07 cleanup, reading RGB PSD as RGBA - 2.07 (2015-09-13) fix compiler warnings - partial animated GIF support - limited 16-bpc PSD support - #ifdef unused functions - bug with < 92 byte PIC,PNM,HDR,TGA - 2.06 (2015-04-19) fix bug where PSD returns wrong '*comp' value - 2.05 (2015-04-19) fix bug in progressive JPEG handling, fix warning - 2.04 (2015-04-15) try to re-enable SIMD on MinGW 64-bit - 2.03 (2015-04-12) extra corruption checking (mmozeiko) - stbi_set_flip_vertically_on_load (nguillemot) - fix NEON support; fix mingw support - 2.02 (2015-01-19) fix incorrect assert, fix warning - 2.01 (2015-01-17) fix various warnings; suppress SIMD on gcc 32-bit without -msse2 - 2.00b (2014-12-25) fix STBI_MALLOC in progressive JPEG - 2.00 (2014-12-25) optimize JPG, including x86 SSE2 & NEON SIMD (ryg) - progressive JPEG (stb) - PGM/PPM support (Ken Miller) - STBI_MALLOC,STBI_REALLOC,STBI_FREE - GIF bugfix -- seemingly never worked - STBI_NO_*, STBI_ONLY_* - 1.48 (2014-12-14) fix incorrectly-named assert() - 1.47 (2014-12-14) 1/2/4-bit PNG support, both direct and paletted (Omar Cornut & stb) - optimize PNG (ryg) - fix bug in interlaced PNG with user-specified channel count (stb) - 1.46 (2014-08-26) - fix broken tRNS chunk (colorkey-style transparency) in non-paletted PNG - 1.45 (2014-08-16) - fix MSVC-ARM internal compiler error by wrapping malloc - 1.44 (2014-08-07) - various warning fixes from Ronny Chevalier - 1.43 (2014-07-15) - fix MSVC-only compiler problem in code changed in 1.42 - 1.42 (2014-07-09) - don't define _CRT_SECURE_NO_WARNINGS (affects user code) - fixes to stbi__cleanup_jpeg path - added STBI_ASSERT to avoid requiring assert.h - 1.41 (2014-06-25) - fix search&replace from 1.36 that messed up comments/error messages - 1.40 (2014-06-22) - fix gcc struct-initialization warning - 1.39 (2014-06-15) - fix to TGA optimization when req_comp != number of components in TGA; - fix to GIF loading because BMP wasn't rewinding (whoops, no GIFs in my test suite) - add support for BMP version 5 (more ignored fields) - 1.38 (2014-06-06) - suppress MSVC warnings on integer casts truncating values - fix accidental rename of 'skip' field of I/O - 1.37 (2014-06-04) - remove duplicate typedef - 1.36 (2014-06-03) - convert to header file single-file library - if de-iphone isn't set, load iphone images color-swapped instead of returning NULL - 1.35 (2014-05-27) - various warnings - fix broken STBI_SIMD path - fix bug where stbi_load_from_file no longer left file pointer in correct place - fix broken non-easy path for 32-bit BMP (possibly never used) - TGA optimization by Arseny Kapoulkine - 1.34 (unknown) - use STBI_NOTUSED in stbi__resample_row_generic(), fix one more leak in tga failure case - 1.33 (2011-07-14) - make stbi_is_hdr work in STBI_NO_HDR (as specified), minor compiler-friendly improvements - 1.32 (2011-07-13) - support for "info" function for all supported filetypes (SpartanJ) - 1.31 (2011-06-20) - a few more leak fixes, bug in PNG handling (SpartanJ) - 1.30 (2011-06-11) - added ability to load files via callbacks to accomidate custom input streams (Ben Wenger) - removed deprecated format-specific test/load functions - removed support for installable file formats (stbi_loader) -- would have been broken for IO callbacks anyway - error cases in bmp and tga give messages and don't leak (Raymond Barbiero, grisha) - fix inefficiency in decoding 32-bit BMP (David Woo) - 1.29 (2010-08-16) - various warning fixes from Aurelien Pocheville - 1.28 (2010-08-01) - fix bug in GIF palette transparency (SpartanJ) - 1.27 (2010-08-01) - cast-to-stbi_uc to fix warnings - 1.26 (2010-07-24) - fix bug in file buffering for PNG reported by SpartanJ - 1.25 (2010-07-17) - refix trans_data warning (Won Chun) - 1.24 (2010-07-12) - perf improvements reading from files on platforms with lock-heavy fgetc() - minor perf improvements for jpeg - deprecated type-specific functions so we'll get feedback if they're needed - attempt to fix trans_data warning (Won Chun) - 1.23 fixed bug in iPhone support - 1.22 (2010-07-10) - removed image *writing* support - stbi_info support from Jetro Lauha - GIF support from Jean-Marc Lienher - iPhone PNG-extensions from James Brown - warning-fixes from Nicolas Schulz and Janez Zemva (i.stbi__err. Janez (U+017D)emva) - 1.21 fix use of 'stbi_uc' in header (reported by jon blow) - 1.20 added support for Softimage PIC, by Tom Seddon - 1.19 bug in interlaced PNG corruption check (found by ryg) - 1.18 (2008-08-02) - fix a threading bug (local mutable static) - 1.17 support interlaced PNG - 1.16 major bugfix - stbi__convert_format converted one too many pixels - 1.15 initialize some fields for thread safety - 1.14 fix threadsafe conversion bug - header-file-only version (#define STBI_HEADER_FILE_ONLY before including) - 1.13 threadsafe - 1.12 const qualifiers in the API - 1.11 Support installable IDCT, colorspace conversion routines - 1.10 Fixes for 64-bit (don't use "unsigned long") - optimized upsampling by Fabian "ryg" Giesen - 1.09 Fix format-conversion for PSD code (bad global variables!) - 1.08 Thatcher Ulrich's PSD code integrated by Nicolas Schulz - 1.07 attempt to fix C++ warning/errors again - 1.06 attempt to fix C++ warning/errors again - 1.05 fix TGA loading to return correct *comp and use good luminance calc - 1.04 default float alpha is 1, not 255; use 'void *' for stbi_image_free - 1.03 bugfixes to STBI_NO_STDIO, STBI_NO_HDR - 1.02 support for (subset of) HDR files, float interface for preferred access to them - 1.01 fix bug: possible bug in handling right-side up bmps... not sure - fix bug: the stbi__bmp_load() and stbi__tga_load() functions didn't work at all - 1.00 interface to zlib that skips zlib header - 0.99 correct handling of alpha in palette - 0.98 TGA loader by lonesock; dynamically add loaders (untested) - 0.97 jpeg errors on too large a file; also catch another malloc failure - 0.96 fix detection of invalid v value - particleman@mollyrocket forum - 0.95 during header scan, seek to markers in case of padding - 0.94 STBI_NO_STDIO to disable stdio usage; rename all #defines the same - 0.93 handle jpegtran output; verbose errors - 0.92 read 4,8,16,24,32-bit BMP files of several formats - 0.91 output 24-bit Windows 3.0 BMP files - 0.90 fix a few more warnings; bump version number to approach 1.0 - 0.61 bugfixes due to Marc LeBlanc, Christopher Lloyd - 0.60 fix compiling as c++ - 0.59 fix warnings: merge Dave Moore's -Wall fixes - 0.58 fix bug: zlib uncompressed mode len/nlen was wrong endian - 0.57 fix bug: jpg last huffman symbol before marker was >9 bits but less than 16 available - 0.56 fix bug: zlib uncompressed mode len vs. nlen - 0.55 fix bug: restart_interval not initialized to 0 - 0.54 allow NULL for 'int *comp' - 0.53 fix bug in png 3->4; speedup png decoding - 0.52 png handles req_comp=3,4 directly; minor cleanup; jpeg comments - 0.51 obey req_comp requests, 1-component jpegs return as 1-component, - on 'test' only check type, not whether we support this variant - 0.50 (2006-11-19) - first released version -*/ - - -/* ------------------------------------------------------------------------------- -This software is available under 2 licenses -- choose whichever you prefer. ------------------------------------------------------------------------------- -ALTERNATIVE A - MIT License -Copyright (c) 2017 Sean Barrett -Permission is hereby granted, free of charge, to any person obtaining a copy of -this software and associated documentation files (the "Software"), to deal in -the Software without restriction, including without limitation the rights to -use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies -of the Software, and to permit persons to whom the Software is furnished to do -so, subject to the following conditions: -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. ------------------------------------------------------------------------------- -ALTERNATIVE B - Public Domain (www.unlicense.org) -This is free and unencumbered software released into the public domain. -Anyone is free to copy, modify, publish, use, compile, sell, or distribute this -software, either in source code form or as a compiled binary, for any purpose, -commercial or non-commercial, and by any means. -In jurisdictions that recognize copyright laws, the author or authors of this -software dedicate any and all copyright interest in the software to the public -domain. We make this dedication for the benefit of the public at large and to -the detriment of our heirs and successors. We intend this dedication to be an -overt act of relinquishment in perpetuity of all present and future rights to -this software under copyright law. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN -ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION -WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ------------------------------------------------------------------------------- -*/ diff --git a/code/externallibraries/stbimagehelpers/stb_image_resize.h b/code/externallibraries/stbimagehelpers/stb_image_resize.h deleted file mode 100644 index ef9e6fe..0000000 --- a/code/externallibraries/stbimagehelpers/stb_image_resize.h +++ /dev/null @@ -1,2634 +0,0 @@ -/* stb_image_resize - v0.97 - public domain image resizing - by Jorge L Rodriguez (@VinoBS) - 2014 - http://github.com/nothings/stb - - Written with emphasis on usability, portability, and efficiency. (No - SIMD or threads, so it be easily outperformed by libs that use those.) - Only scaling and translation is supported, no rotations or shears. - Easy API downsamples w/Mitchell filter, upsamples w/cubic interpolation. - - COMPILING & LINKING - In one C/C++ file that #includes this file, do this: - #define STB_IMAGE_RESIZE_IMPLEMENTATION - before the #include. That will create the implementation in that file. - - QUICKSTART - stbir_resize_uint8( input_pixels , in_w , in_h , 0, - output_pixels, out_w, out_h, 0, num_channels) - stbir_resize_float(...) - stbir_resize_uint8_srgb( input_pixels , in_w , in_h , 0, - output_pixels, out_w, out_h, 0, - num_channels , alpha_chan , 0) - stbir_resize_uint8_srgb_edgemode( - input_pixels , in_w , in_h , 0, - output_pixels, out_w, out_h, 0, - num_channels , alpha_chan , 0, STBIR_EDGE_CLAMP) - // WRAP/REFLECT/ZERO - - FULL API - See the "header file" section of the source for API documentation. - - ADDITIONAL DOCUMENTATION - - SRGB & FLOATING POINT REPRESENTATION - The sRGB functions presume IEEE floating point. If you do not have - IEEE floating point, define STBIR_NON_IEEE_FLOAT. This will use - a slower implementation. - - MEMORY ALLOCATION - The resize functions here perform a single memory allocation using - malloc. To control the memory allocation, before the #include that - triggers the implementation, do: - - #define STBIR_MALLOC(size,context) ... - #define STBIR_FREE(ptr,context) ... - - Each resize function makes exactly one call to malloc/free, so to use - temp memory, store the temp memory in the context and return that. - - ASSERT - Define STBIR_ASSERT(boolval) to override assert() and not use assert.h - - OPTIMIZATION - Define STBIR_SATURATE_INT to compute clamp values in-range using - integer operations instead of float operations. This may be faster - on some platforms. - - DEFAULT FILTERS - For functions which don't provide explicit control over what filters - to use, you can change the compile-time defaults with - - #define STBIR_DEFAULT_FILTER_UPSAMPLE STBIR_FILTER_something - #define STBIR_DEFAULT_FILTER_DOWNSAMPLE STBIR_FILTER_something - - See stbir_filter in the header-file section for the list of filters. - - NEW FILTERS - A number of 1D filter kernels are used. For a list of - supported filters see the stbir_filter enum. To add a new filter, - write a filter function and add it to stbir__filter_info_table. - - PROGRESS - For interactive use with slow resize operations, you can install - a progress-report callback: - - #define STBIR_PROGRESS_REPORT(val) some_func(val) - - The parameter val is a float which goes from 0 to 1 as progress is made. - - For example: - - static void my_progress_report(float progress); - #define STBIR_PROGRESS_REPORT(val) my_progress_report(val) - - #define STB_IMAGE_RESIZE_IMPLEMENTATION - #include "stb_image_resize.h" - - static void my_progress_report(float progress) - { - printf("Progress: %f%%\n", progress*100); - } - - MAX CHANNELS - If your image has more than 64 channels, define STBIR_MAX_CHANNELS - to the max you'll have. - - ALPHA CHANNEL - Most of the resizing functions provide the ability to control how - the alpha channel of an image is processed. The important things - to know about this: - - 1. The best mathematically-behaved version of alpha to use is - called "premultiplied alpha", in which the other color channels - have had the alpha value multiplied in. If you use premultiplied - alpha, linear filtering (such as image resampling done by this - library, or performed in texture units on GPUs) does the "right - thing". While premultiplied alpha is standard in the movie CGI - industry, it is still uncommon in the videogame/real-time world. - - If you linearly filter non-premultiplied alpha, strange effects - occur. (For example, the 50/50 average of 99% transparent bright green - and 1% transparent black produces 50% transparent dark green when - non-premultiplied, whereas premultiplied it produces 50% - transparent near-black. The former introduces green energy - that doesn't exist in the source image.) - - 2. Artists should not edit premultiplied-alpha images; artists - want non-premultiplied alpha images. Thus, art tools generally output - non-premultiplied alpha images. - - 3. You will get best results in most cases by converting images - to premultiplied alpha before processing them mathematically. - - 4. If you pass the flag STBIR_FLAG_ALPHA_PREMULTIPLIED, the - resizer does not do anything special for the alpha channel; - it is resampled identically to other channels. This produces - the correct results for premultiplied-alpha images, but produces - less-than-ideal results for non-premultiplied-alpha images. - - 5. If you do not pass the flag STBIR_FLAG_ALPHA_PREMULTIPLIED, - then the resizer weights the contribution of input pixels - based on their alpha values, or, equivalently, it multiplies - the alpha value into the color channels, resamples, then divides - by the resultant alpha value. Input pixels which have alpha=0 do - not contribute at all to output pixels unless _all_ of the input - pixels affecting that output pixel have alpha=0, in which case - the result for that pixel is the same as it would be without - STBIR_FLAG_ALPHA_PREMULTIPLIED. However, this is only true for - input images in integer formats. For input images in float format, - input pixels with alpha=0 have no effect, and output pixels - which have alpha=0 will be 0 in all channels. (For float images, - you can manually achieve the same result by adding a tiny epsilon - value to the alpha channel of every image, and then subtracting - or clamping it at the end.) - - 6. You can suppress the behavior described in #5 and make - all-0-alpha pixels have 0 in all channels by #defining - STBIR_NO_ALPHA_EPSILON. - - 7. You can separately control whether the alpha channel is - interpreted as linear or affected by the colorspace. By default - it is linear; you almost never want to apply the colorspace. - (For example, graphics hardware does not apply sRGB conversion - to the alpha channel.) - - CONTRIBUTORS - Jorge L Rodriguez: Implementation - Sean Barrett: API design, optimizations - Aras Pranckevicius: bugfix - Nathan Reed: warning fixes - - REVISIONS - 0.97 (2020-02-02) fixed warning - 0.96 (2019-03-04) fixed warnings - 0.95 (2017-07-23) fixed warnings - 0.94 (2017-03-18) fixed warnings - 0.93 (2017-03-03) fixed bug with certain combinations of heights - 0.92 (2017-01-02) fix integer overflow on large (>2GB) images - 0.91 (2016-04-02) fix warnings; fix handling of subpixel regions - 0.90 (2014-09-17) first released version - - LICENSE - See end of file for license information. - - TODO - Don't decode all of the image data when only processing a partial tile - Don't use full-width decode buffers when only processing a partial tile - When processing wide images, break processing into tiles so data fits in L1 cache - Installable filters? - Resize that respects alpha test coverage - (Reference code: FloatImage::alphaTestCoverage and FloatImage::scaleAlphaToCoverage: - https://code.google.com/p/nvidia-texture-tools/source/browse/trunk/src/nvimage/FloatImage.cpp ) -*/ - -#ifndef STBIR_INCLUDE_STB_IMAGE_RESIZE_H -#define STBIR_INCLUDE_STB_IMAGE_RESIZE_H - -#ifdef _MSC_VER -typedef unsigned char stbir_uint8; -typedef unsigned short stbir_uint16; -typedef unsigned int stbir_uint32; -#else -#include -typedef uint8_t stbir_uint8; -typedef uint16_t stbir_uint16; -typedef uint32_t stbir_uint32; -#endif - -#ifndef STBIRDEF -#ifdef STB_IMAGE_RESIZE_STATIC -#define STBIRDEF static -#else -#ifdef __cplusplus -#define STBIRDEF extern "C" -#else -#define STBIRDEF extern -#endif -#endif -#endif - -////////////////////////////////////////////////////////////////////////////// -// -// Easy-to-use API: -// -// * "input pixels" points to an array of image data with 'num_channels' channels (e.g. RGB=3, RGBA=4) -// * input_w is input image width (x-axis), input_h is input image height (y-axis) -// * stride is the offset between successive rows of image data in memory, in bytes. you can -// specify 0 to mean packed continuously in memory -// * alpha channel is treated identically to other channels. -// * colorspace is linear or sRGB as specified by function name -// * returned result is 1 for success or 0 in case of an error. -// #define STBIR_ASSERT() to trigger an assert on parameter validation errors. -// * Memory required grows approximately linearly with input and output size, but with -// discontinuities at input_w == output_w and input_h == output_h. -// * These functions use a "default" resampling filter defined at compile time. To change the filter, -// you can change the compile-time defaults by #defining STBIR_DEFAULT_FILTER_UPSAMPLE -// and STBIR_DEFAULT_FILTER_DOWNSAMPLE, or you can use the medium-complexity API. - -STBIRDEF int stbir_resize_uint8( const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels); - -STBIRDEF int stbir_resize_float( const float *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - float *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels); - - -// The following functions interpret image data as gamma-corrected sRGB. -// Specify STBIR_ALPHA_CHANNEL_NONE if you have no alpha channel, -// or otherwise provide the index of the alpha channel. Flags value -// of 0 will probably do the right thing if you're not sure what -// the flags mean. - -#define STBIR_ALPHA_CHANNEL_NONE -1 - -// Set this flag if your texture has premultiplied alpha. Otherwise, stbir will -// use alpha-weighted resampling (effectively premultiplying, resampling, -// then unpremultiplying). -#define STBIR_FLAG_ALPHA_PREMULTIPLIED (1 << 0) -// The specified alpha channel should be handled as gamma-corrected value even -// when doing sRGB operations. -#define STBIR_FLAG_ALPHA_USES_COLORSPACE (1 << 1) - -STBIRDEF int stbir_resize_uint8_srgb(const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags); - - -typedef enum -{ - STBIR_EDGE_CLAMP = 1, - STBIR_EDGE_REFLECT = 2, - STBIR_EDGE_WRAP = 3, - STBIR_EDGE_ZERO = 4, -} stbir_edge; - -// This function adds the ability to specify how requests to sample off the edge of the image are handled. -STBIRDEF int stbir_resize_uint8_srgb_edgemode(const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode); - -////////////////////////////////////////////////////////////////////////////// -// -// Medium-complexity API -// -// This extends the easy-to-use API as follows: -// -// * Alpha-channel can be processed separately -// * If alpha_channel is not STBIR_ALPHA_CHANNEL_NONE -// * Alpha channel will not be gamma corrected (unless flags&STBIR_FLAG_GAMMA_CORRECT) -// * Filters will be weighted by alpha channel (unless flags&STBIR_FLAG_ALPHA_PREMULTIPLIED) -// * Filter can be selected explicitly -// * uint16 image type -// * sRGB colorspace available for all types -// * context parameter for passing to STBIR_MALLOC - -typedef enum -{ - STBIR_FILTER_DEFAULT = 0, // use same filter type that easy-to-use API chooses - STBIR_FILTER_BOX = 1, // A trapezoid w/1-pixel wide ramps, same result as box for integer scale ratios - STBIR_FILTER_TRIANGLE = 2, // On upsampling, produces same results as bilinear texture filtering - STBIR_FILTER_CUBICBSPLINE = 3, // The cubic b-spline (aka Mitchell-Netrevalli with B=1,C=0), gaussian-esque - STBIR_FILTER_CATMULLROM = 4, // An interpolating cubic spline - STBIR_FILTER_MITCHELL = 5, // Mitchell-Netrevalli filter with B=1/3, C=1/3 -} stbir_filter; - -typedef enum -{ - STBIR_COLORSPACE_LINEAR, - STBIR_COLORSPACE_SRGB, - - STBIR_MAX_COLORSPACES, -} stbir_colorspace; - -// The following functions are all identical except for the type of the image data - -STBIRDEF int stbir_resize_uint8_generic( const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode, stbir_filter filter, stbir_colorspace space, - void *alloc_context); - -STBIRDEF int stbir_resize_uint16_generic(const stbir_uint16 *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - stbir_uint16 *output_pixels , int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode, stbir_filter filter, stbir_colorspace space, - void *alloc_context); - -STBIRDEF int stbir_resize_float_generic( const float *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - float *output_pixels , int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode, stbir_filter filter, stbir_colorspace space, - void *alloc_context); - - - -////////////////////////////////////////////////////////////////////////////// -// -// Full-complexity API -// -// This extends the medium API as follows: -// -// * uint32 image type -// * not typesafe -// * separate filter types for each axis -// * separate edge modes for each axis -// * can specify scale explicitly for subpixel correctness -// * can specify image source tile using texture coordinates - -typedef enum -{ - STBIR_TYPE_UINT8 , - STBIR_TYPE_UINT16, - STBIR_TYPE_UINT32, - STBIR_TYPE_FLOAT , - - STBIR_MAX_TYPES -} stbir_datatype; - -STBIRDEF int stbir_resize( const void *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - void *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - stbir_datatype datatype, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_mode_horizontal, stbir_edge edge_mode_vertical, - stbir_filter filter_horizontal, stbir_filter filter_vertical, - stbir_colorspace space, void *alloc_context); - -STBIRDEF int stbir_resize_subpixel(const void *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - void *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - stbir_datatype datatype, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_mode_horizontal, stbir_edge edge_mode_vertical, - stbir_filter filter_horizontal, stbir_filter filter_vertical, - stbir_colorspace space, void *alloc_context, - float x_scale, float y_scale, - float x_offset, float y_offset); - -STBIRDEF int stbir_resize_region( const void *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - void *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - stbir_datatype datatype, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_mode_horizontal, stbir_edge edge_mode_vertical, - stbir_filter filter_horizontal, stbir_filter filter_vertical, - stbir_colorspace space, void *alloc_context, - float s0, float t0, float s1, float t1); -// (s0, t0) & (s1, t1) are the top-left and bottom right corner (uv addressing style: [0, 1]x[0, 1]) of a region of the input image to use. - -// -// -//// end header file ///////////////////////////////////////////////////// -#endif // STBIR_INCLUDE_STB_IMAGE_RESIZE_H - - - - - -#ifdef STB_IMAGE_RESIZE_IMPLEMENTATION - -#ifndef STBIR_ASSERT -#include -#define STBIR_ASSERT(x) assert(x) -#endif - -// For memset -#include - -#include - -#ifndef STBIR_MALLOC -#include -// use comma operator to evaluate c, to avoid "unused parameter" warnings -#define STBIR_MALLOC(size,c) ((void)(c), malloc(size)) -#define STBIR_FREE(ptr,c) ((void)(c), free(ptr)) -#endif - -#ifndef _MSC_VER -#ifdef __cplusplus -#define stbir__inline inline -#else -#define stbir__inline -#endif -#else -#define stbir__inline __forceinline -#endif - - -// should produce compiler error if size is wrong -typedef unsigned char stbir__validate_uint32[sizeof(stbir_uint32) == 4 ? 1 : -1]; - -#ifdef _MSC_VER -#define STBIR__NOTUSED(v) (void)(v) -#else -#define STBIR__NOTUSED(v) (void)sizeof(v) -#endif - -#define STBIR__ARRAY_SIZE(a) (sizeof((a))/sizeof((a)[0])) - -#ifndef STBIR_DEFAULT_FILTER_UPSAMPLE -#define STBIR_DEFAULT_FILTER_UPSAMPLE STBIR_FILTER_CATMULLROM -#endif - -#ifndef STBIR_DEFAULT_FILTER_DOWNSAMPLE -#define STBIR_DEFAULT_FILTER_DOWNSAMPLE STBIR_FILTER_MITCHELL -#endif - -#ifndef STBIR_PROGRESS_REPORT -#define STBIR_PROGRESS_REPORT(float_0_to_1) -#endif - -#ifndef STBIR_MAX_CHANNELS -#define STBIR_MAX_CHANNELS 64 -#endif - -#if STBIR_MAX_CHANNELS > 65536 -#error "Too many channels; STBIR_MAX_CHANNELS must be no more than 65536." -// because we store the indices in 16-bit variables -#endif - -// This value is added to alpha just before premultiplication to avoid -// zeroing out color values. It is equivalent to 2^-80. If you don't want -// that behavior (it may interfere if you have floating point images with -// very small alpha values) then you can define STBIR_NO_ALPHA_EPSILON to -// disable it. -#ifndef STBIR_ALPHA_EPSILON -#define STBIR_ALPHA_EPSILON ((float)1 / (1 << 20) / (1 << 20) / (1 << 20) / (1 << 20)) -#endif - - - -#ifdef _MSC_VER -#define STBIR__UNUSED_PARAM(v) (void)(v) -#else -#define STBIR__UNUSED_PARAM(v) (void)sizeof(v) -#endif - -// must match stbir_datatype -static unsigned char stbir__type_size[] = { - 1, // STBIR_TYPE_UINT8 - 2, // STBIR_TYPE_UINT16 - 4, // STBIR_TYPE_UINT32 - 4, // STBIR_TYPE_FLOAT -}; - -// Kernel function centered at 0 -typedef float (stbir__kernel_fn)(float x, float scale); -typedef float (stbir__support_fn)(float scale); - -typedef struct -{ - stbir__kernel_fn* kernel; - stbir__support_fn* support; -} stbir__filter_info; - -// When upsampling, the contributors are which source pixels contribute. -// When downsampling, the contributors are which destination pixels are contributed to. -typedef struct -{ - int n0; // First contributing pixel - int n1; // Last contributing pixel -} stbir__contributors; - -typedef struct -{ - const void* input_data; - int input_w; - int input_h; - int input_stride_bytes; - - void* output_data; - int output_w; - int output_h; - int output_stride_bytes; - - float s0, t0, s1, t1; - - float horizontal_shift; // Units: output pixels - float vertical_shift; // Units: output pixels - float horizontal_scale; - float vertical_scale; - - int channels; - int alpha_channel; - stbir_uint32 flags; - stbir_datatype type; - stbir_filter horizontal_filter; - stbir_filter vertical_filter; - stbir_edge edge_horizontal; - stbir_edge edge_vertical; - stbir_colorspace colorspace; - - stbir__contributors* horizontal_contributors; - float* horizontal_coefficients; - - stbir__contributors* vertical_contributors; - float* vertical_coefficients; - - int decode_buffer_pixels; - float* decode_buffer; - - float* horizontal_buffer; - - // cache these because ceil/floor are inexplicably showing up in profile - int horizontal_coefficient_width; - int vertical_coefficient_width; - int horizontal_filter_pixel_width; - int vertical_filter_pixel_width; - int horizontal_filter_pixel_margin; - int vertical_filter_pixel_margin; - int horizontal_num_contributors; - int vertical_num_contributors; - - int ring_buffer_length_bytes; // The length of an individual entry in the ring buffer. The total number of ring buffers is stbir__get_filter_pixel_width(filter) - int ring_buffer_num_entries; // Total number of entries in the ring buffer. - int ring_buffer_first_scanline; - int ring_buffer_last_scanline; - int ring_buffer_begin_index; // first_scanline is at this index in the ring buffer - float* ring_buffer; - - float* encode_buffer; // A temporary buffer to store floats so we don't lose precision while we do multiply-adds. - - int horizontal_contributors_size; - int horizontal_coefficients_size; - int vertical_contributors_size; - int vertical_coefficients_size; - int decode_buffer_size; - int horizontal_buffer_size; - int ring_buffer_size; - int encode_buffer_size; -} stbir__info; - - -static const float stbir__max_uint8_as_float = 255.0f; -static const float stbir__max_uint16_as_float = 65535.0f; -static const double stbir__max_uint32_as_float = 4294967295.0; - - -static stbir__inline int stbir__min(int a, int b) -{ - return a < b ? a : b; -} - -static stbir__inline float stbir__saturate(float x) -{ - if (x < 0) - return 0; - - if (x > 1) - return 1; - - return x; -} - -#ifdef STBIR_SATURATE_INT -static stbir__inline stbir_uint8 stbir__saturate8(int x) -{ - if ((unsigned int) x <= 255) - return x; - - if (x < 0) - return 0; - - return 255; -} - -static stbir__inline stbir_uint16 stbir__saturate16(int x) -{ - if ((unsigned int) x <= 65535) - return x; - - if (x < 0) - return 0; - - return 65535; -} -#endif - -static float stbir__srgb_uchar_to_linear_float[256] = { - 0.000000f, 0.000304f, 0.000607f, 0.000911f, 0.001214f, 0.001518f, 0.001821f, 0.002125f, 0.002428f, 0.002732f, 0.003035f, - 0.003347f, 0.003677f, 0.004025f, 0.004391f, 0.004777f, 0.005182f, 0.005605f, 0.006049f, 0.006512f, 0.006995f, 0.007499f, - 0.008023f, 0.008568f, 0.009134f, 0.009721f, 0.010330f, 0.010960f, 0.011612f, 0.012286f, 0.012983f, 0.013702f, 0.014444f, - 0.015209f, 0.015996f, 0.016807f, 0.017642f, 0.018500f, 0.019382f, 0.020289f, 0.021219f, 0.022174f, 0.023153f, 0.024158f, - 0.025187f, 0.026241f, 0.027321f, 0.028426f, 0.029557f, 0.030713f, 0.031896f, 0.033105f, 0.034340f, 0.035601f, 0.036889f, - 0.038204f, 0.039546f, 0.040915f, 0.042311f, 0.043735f, 0.045186f, 0.046665f, 0.048172f, 0.049707f, 0.051269f, 0.052861f, - 0.054480f, 0.056128f, 0.057805f, 0.059511f, 0.061246f, 0.063010f, 0.064803f, 0.066626f, 0.068478f, 0.070360f, 0.072272f, - 0.074214f, 0.076185f, 0.078187f, 0.080220f, 0.082283f, 0.084376f, 0.086500f, 0.088656f, 0.090842f, 0.093059f, 0.095307f, - 0.097587f, 0.099899f, 0.102242f, 0.104616f, 0.107023f, 0.109462f, 0.111932f, 0.114435f, 0.116971f, 0.119538f, 0.122139f, - 0.124772f, 0.127438f, 0.130136f, 0.132868f, 0.135633f, 0.138432f, 0.141263f, 0.144128f, 0.147027f, 0.149960f, 0.152926f, - 0.155926f, 0.158961f, 0.162029f, 0.165132f, 0.168269f, 0.171441f, 0.174647f, 0.177888f, 0.181164f, 0.184475f, 0.187821f, - 0.191202f, 0.194618f, 0.198069f, 0.201556f, 0.205079f, 0.208637f, 0.212231f, 0.215861f, 0.219526f, 0.223228f, 0.226966f, - 0.230740f, 0.234551f, 0.238398f, 0.242281f, 0.246201f, 0.250158f, 0.254152f, 0.258183f, 0.262251f, 0.266356f, 0.270498f, - 0.274677f, 0.278894f, 0.283149f, 0.287441f, 0.291771f, 0.296138f, 0.300544f, 0.304987f, 0.309469f, 0.313989f, 0.318547f, - 0.323143f, 0.327778f, 0.332452f, 0.337164f, 0.341914f, 0.346704f, 0.351533f, 0.356400f, 0.361307f, 0.366253f, 0.371238f, - 0.376262f, 0.381326f, 0.386430f, 0.391573f, 0.396755f, 0.401978f, 0.407240f, 0.412543f, 0.417885f, 0.423268f, 0.428691f, - 0.434154f, 0.439657f, 0.445201f, 0.450786f, 0.456411f, 0.462077f, 0.467784f, 0.473532f, 0.479320f, 0.485150f, 0.491021f, - 0.496933f, 0.502887f, 0.508881f, 0.514918f, 0.520996f, 0.527115f, 0.533276f, 0.539480f, 0.545725f, 0.552011f, 0.558340f, - 0.564712f, 0.571125f, 0.577581f, 0.584078f, 0.590619f, 0.597202f, 0.603827f, 0.610496f, 0.617207f, 0.623960f, 0.630757f, - 0.637597f, 0.644480f, 0.651406f, 0.658375f, 0.665387f, 0.672443f, 0.679543f, 0.686685f, 0.693872f, 0.701102f, 0.708376f, - 0.715694f, 0.723055f, 0.730461f, 0.737911f, 0.745404f, 0.752942f, 0.760525f, 0.768151f, 0.775822f, 0.783538f, 0.791298f, - 0.799103f, 0.806952f, 0.814847f, 0.822786f, 0.830770f, 0.838799f, 0.846873f, 0.854993f, 0.863157f, 0.871367f, 0.879622f, - 0.887923f, 0.896269f, 0.904661f, 0.913099f, 0.921582f, 0.930111f, 0.938686f, 0.947307f, 0.955974f, 0.964686f, 0.973445f, - 0.982251f, 0.991102f, 1.0f -}; - -static float stbir__srgb_to_linear(float f) -{ - if (f <= 0.04045f) - return f / 12.92f; - else - return (float)pow((f + 0.055f) / 1.055f, 2.4f); -} - -static float stbir__linear_to_srgb(float f) -{ - if (f <= 0.0031308f) - return f * 12.92f; - else - return 1.055f * (float)pow(f, 1 / 2.4f) - 0.055f; -} - -#ifndef STBIR_NON_IEEE_FLOAT -// From https://gist.github.com/rygorous/2203834 - -typedef union -{ - stbir_uint32 u; - float f; -} stbir__FP32; - -static const stbir_uint32 fp32_to_srgb8_tab4[104] = { - 0x0073000d, 0x007a000d, 0x0080000d, 0x0087000d, 0x008d000d, 0x0094000d, 0x009a000d, 0x00a1000d, - 0x00a7001a, 0x00b4001a, 0x00c1001a, 0x00ce001a, 0x00da001a, 0x00e7001a, 0x00f4001a, 0x0101001a, - 0x010e0033, 0x01280033, 0x01410033, 0x015b0033, 0x01750033, 0x018f0033, 0x01a80033, 0x01c20033, - 0x01dc0067, 0x020f0067, 0x02430067, 0x02760067, 0x02aa0067, 0x02dd0067, 0x03110067, 0x03440067, - 0x037800ce, 0x03df00ce, 0x044600ce, 0x04ad00ce, 0x051400ce, 0x057b00c5, 0x05dd00bc, 0x063b00b5, - 0x06970158, 0x07420142, 0x07e30130, 0x087b0120, 0x090b0112, 0x09940106, 0x0a1700fc, 0x0a9500f2, - 0x0b0f01cb, 0x0bf401ae, 0x0ccb0195, 0x0d950180, 0x0e56016e, 0x0f0d015e, 0x0fbc0150, 0x10630143, - 0x11070264, 0x1238023e, 0x1357021d, 0x14660201, 0x156601e9, 0x165a01d3, 0x174401c0, 0x182401af, - 0x18fe0331, 0x1a9602fe, 0x1c1502d2, 0x1d7e02ad, 0x1ed4028d, 0x201a0270, 0x21520256, 0x227d0240, - 0x239f0443, 0x25c003fe, 0x27bf03c4, 0x29a10392, 0x2b6a0367, 0x2d1d0341, 0x2ebe031f, 0x304d0300, - 0x31d105b0, 0x34a80555, 0x37520507, 0x39d504c5, 0x3c37048b, 0x3e7c0458, 0x40a8042a, 0x42bd0401, - 0x44c20798, 0x488e071e, 0x4c1c06b6, 0x4f76065d, 0x52a50610, 0x55ac05cc, 0x5892058f, 0x5b590559, - 0x5e0c0a23, 0x631c0980, 0x67db08f6, 0x6c55087f, 0x70940818, 0x74a007bd, 0x787d076c, 0x7c330723, -}; - -static stbir_uint8 stbir__linear_to_srgb_uchar(float in) -{ - static const stbir__FP32 almostone = { 0x3f7fffff }; // 1-eps - static const stbir__FP32 minval = { (127-13) << 23 }; - stbir_uint32 tab,bias,scale,t; - stbir__FP32 f; - - // Clamp to [2^(-13), 1-eps]; these two values map to 0 and 1, respectively. - // The tests are carefully written so that NaNs map to 0, same as in the reference - // implementation. - if (!(in > minval.f)) // written this way to catch NaNs - in = minval.f; - if (in > almostone.f) - in = almostone.f; - - // Do the table lookup and unpack bias, scale - f.f = in; - tab = fp32_to_srgb8_tab4[(f.u - minval.u) >> 20]; - bias = (tab >> 16) << 9; - scale = tab & 0xffff; - - // Grab next-highest mantissa bits and perform linear interpolation - t = (f.u >> 12) & 0xff; - return (unsigned char) ((bias + scale*t) >> 16); -} - -#else -// sRGB transition values, scaled by 1<<28 -static int stbir__srgb_offset_to_linear_scaled[256] = -{ - 0, 40738, 122216, 203693, 285170, 366648, 448125, 529603, - 611080, 692557, 774035, 855852, 942009, 1033024, 1128971, 1229926, - 1335959, 1447142, 1563542, 1685229, 1812268, 1944725, 2082664, 2226148, - 2375238, 2529996, 2690481, 2856753, 3028870, 3206888, 3390865, 3580856, - 3776916, 3979100, 4187460, 4402049, 4622919, 4850123, 5083710, 5323731, - 5570236, 5823273, 6082892, 6349140, 6622065, 6901714, 7188133, 7481369, - 7781466, 8088471, 8402427, 8723380, 9051372, 9386448, 9728650, 10078021, - 10434603, 10798439, 11169569, 11548036, 11933879, 12327139, 12727857, 13136073, - 13551826, 13975156, 14406100, 14844697, 15290987, 15745007, 16206795, 16676389, - 17153826, 17639142, 18132374, 18633560, 19142734, 19659934, 20185196, 20718552, - 21260042, 21809696, 22367554, 22933648, 23508010, 24090680, 24681686, 25281066, - 25888850, 26505076, 27129772, 27762974, 28404716, 29055026, 29713942, 30381490, - 31057708, 31742624, 32436272, 33138682, 33849884, 34569912, 35298800, 36036568, - 36783260, 37538896, 38303512, 39077136, 39859796, 40651528, 41452360, 42262316, - 43081432, 43909732, 44747252, 45594016, 46450052, 47315392, 48190064, 49074096, - 49967516, 50870356, 51782636, 52704392, 53635648, 54576432, 55526772, 56486700, - 57456236, 58435408, 59424248, 60422780, 61431036, 62449032, 63476804, 64514376, - 65561776, 66619028, 67686160, 68763192, 69850160, 70947088, 72053992, 73170912, - 74297864, 75434880, 76581976, 77739184, 78906536, 80084040, 81271736, 82469648, - 83677792, 84896192, 86124888, 87363888, 88613232, 89872928, 91143016, 92423512, - 93714432, 95015816, 96327688, 97650056, 98982952, 100326408, 101680440, 103045072, - 104420320, 105806224, 107202800, 108610064, 110028048, 111456776, 112896264, 114346544, - 115807632, 117279552, 118762328, 120255976, 121760536, 123276016, 124802440, 126339832, - 127888216, 129447616, 131018048, 132599544, 134192112, 135795792, 137410592, 139036528, - 140673648, 142321952, 143981456, 145652208, 147334208, 149027488, 150732064, 152447968, - 154175200, 155913792, 157663776, 159425168, 161197984, 162982240, 164777968, 166585184, - 168403904, 170234160, 172075968, 173929344, 175794320, 177670896, 179559120, 181458992, - 183370528, 185293776, 187228736, 189175424, 191133888, 193104112, 195086128, 197079968, - 199085648, 201103184, 203132592, 205173888, 207227120, 209292272, 211369392, 213458480, - 215559568, 217672656, 219797792, 221934976, 224084240, 226245600, 228419056, 230604656, - 232802400, 235012320, 237234432, 239468736, 241715280, 243974080, 246245120, 248528464, - 250824112, 253132064, 255452368, 257785040, 260130080, 262487520, 264857376, 267239664, -}; - -static stbir_uint8 stbir__linear_to_srgb_uchar(float f) -{ - int x = (int) (f * (1 << 28)); // has headroom so you don't need to clamp - int v = 0; - int i; - - // Refine the guess with a short binary search. - i = v + 128; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 64; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 32; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 16; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 8; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 4; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 2; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - i = v + 1; if (x >= stbir__srgb_offset_to_linear_scaled[i]) v = i; - - return (stbir_uint8) v; -} -#endif - -static float stbir__filter_trapezoid(float x, float scale) -{ - float halfscale = scale / 2; - float t = 0.5f + halfscale; - STBIR_ASSERT(scale <= 1); - - x = (float)fabs(x); - - if (x >= t) - return 0; - else - { - float r = 0.5f - halfscale; - if (x <= r) - return 1; - else - return (t - x) / scale; - } -} - -static float stbir__support_trapezoid(float scale) -{ - STBIR_ASSERT(scale <= 1); - return 0.5f + scale / 2; -} - -static float stbir__filter_triangle(float x, float s) -{ - STBIR__UNUSED_PARAM(s); - - x = (float)fabs(x); - - if (x <= 1.0f) - return 1 - x; - else - return 0; -} - -static float stbir__filter_cubic(float x, float s) -{ - STBIR__UNUSED_PARAM(s); - - x = (float)fabs(x); - - if (x < 1.0f) - return (4 + x*x*(3*x - 6))/6; - else if (x < 2.0f) - return (8 + x*(-12 + x*(6 - x)))/6; - - return (0.0f); -} - -static float stbir__filter_catmullrom(float x, float s) -{ - STBIR__UNUSED_PARAM(s); - - x = (float)fabs(x); - - if (x < 1.0f) - return 1 - x*x*(2.5f - 1.5f*x); - else if (x < 2.0f) - return 2 - x*(4 + x*(0.5f*x - 2.5f)); - - return (0.0f); -} - -static float stbir__filter_mitchell(float x, float s) -{ - STBIR__UNUSED_PARAM(s); - - x = (float)fabs(x); - - if (x < 1.0f) - return (16 + x*x*(21 * x - 36))/18; - else if (x < 2.0f) - return (32 + x*(-60 + x*(36 - 7*x)))/18; - - return (0.0f); -} - -static float stbir__support_zero(float s) -{ - STBIR__UNUSED_PARAM(s); - return 0; -} - -static float stbir__support_one(float s) -{ - STBIR__UNUSED_PARAM(s); - return 1; -} - -static float stbir__support_two(float s) -{ - STBIR__UNUSED_PARAM(s); - return 2; -} - -static stbir__filter_info stbir__filter_info_table[] = { - { NULL, stbir__support_zero }, - { stbir__filter_trapezoid, stbir__support_trapezoid }, - { stbir__filter_triangle, stbir__support_one }, - { stbir__filter_cubic, stbir__support_two }, - { stbir__filter_catmullrom, stbir__support_two }, - { stbir__filter_mitchell, stbir__support_two }, -}; - -stbir__inline static int stbir__use_upsampling(float ratio) -{ - return ratio > 1; -} - -stbir__inline static int stbir__use_width_upsampling(stbir__info* stbir_info) -{ - return stbir__use_upsampling(stbir_info->horizontal_scale); -} - -stbir__inline static int stbir__use_height_upsampling(stbir__info* stbir_info) -{ - return stbir__use_upsampling(stbir_info->vertical_scale); -} - -// This is the maximum number of input samples that can affect an output sample -// with the given filter -static int stbir__get_filter_pixel_width(stbir_filter filter, float scale) -{ - STBIR_ASSERT(filter != 0); - STBIR_ASSERT(filter < STBIR__ARRAY_SIZE(stbir__filter_info_table)); - - if (stbir__use_upsampling(scale)) - return (int)ceil(stbir__filter_info_table[filter].support(1/scale) * 2); - else - return (int)ceil(stbir__filter_info_table[filter].support(scale) * 2 / scale); -} - -// This is how much to expand buffers to account for filters seeking outside -// the image boundaries. -static int stbir__get_filter_pixel_margin(stbir_filter filter, float scale) -{ - return stbir__get_filter_pixel_width(filter, scale) / 2; -} - -static int stbir__get_coefficient_width(stbir_filter filter, float scale) -{ - if (stbir__use_upsampling(scale)) - return (int)ceil(stbir__filter_info_table[filter].support(1 / scale) * 2); - else - return (int)ceil(stbir__filter_info_table[filter].support(scale) * 2); -} - -static int stbir__get_contributors(float scale, stbir_filter filter, int input_size, int output_size) -{ - if (stbir__use_upsampling(scale)) - return output_size; - else - return (input_size + stbir__get_filter_pixel_margin(filter, scale) * 2); -} - -static int stbir__get_total_horizontal_coefficients(stbir__info* info) -{ - return info->horizontal_num_contributors - * stbir__get_coefficient_width (info->horizontal_filter, info->horizontal_scale); -} - -static int stbir__get_total_vertical_coefficients(stbir__info* info) -{ - return info->vertical_num_contributors - * stbir__get_coefficient_width (info->vertical_filter, info->vertical_scale); -} - -static stbir__contributors* stbir__get_contributor(stbir__contributors* contributors, int n) -{ - return &contributors[n]; -} - -// For perf reasons this code is duplicated in stbir__resample_horizontal_upsample/downsample, -// if you change it here change it there too. -static float* stbir__get_coefficient(float* coefficients, stbir_filter filter, float scale, int n, int c) -{ - int width = stbir__get_coefficient_width(filter, scale); - return &coefficients[width*n + c]; -} - -static int stbir__edge_wrap_slow(stbir_edge edge, int n, int max) -{ - switch (edge) - { - case STBIR_EDGE_ZERO: - return 0; // we'll decode the wrong pixel here, and then overwrite with 0s later - - case STBIR_EDGE_CLAMP: - if (n < 0) - return 0; - - if (n >= max) - return max - 1; - - return n; // NOTREACHED - - case STBIR_EDGE_REFLECT: - { - if (n < 0) - { - if (n < max) - return -n; - else - return max - 1; - } - - if (n >= max) - { - int max2 = max * 2; - if (n >= max2) - return 0; - else - return max2 - n - 1; - } - - return n; // NOTREACHED - } - - case STBIR_EDGE_WRAP: - if (n >= 0) - return (n % max); - else - { - int m = (-n) % max; - - if (m != 0) - m = max - m; - - return (m); - } - // NOTREACHED - - default: - STBIR_ASSERT(!"Unimplemented edge type"); - return 0; - } -} - -stbir__inline static int stbir__edge_wrap(stbir_edge edge, int n, int max) -{ - // avoid per-pixel switch - if (n >= 0 && n < max) - return n; - return stbir__edge_wrap_slow(edge, n, max); -} - -// What input pixels contribute to this output pixel? -static void stbir__calculate_sample_range_upsample(int n, float out_filter_radius, float scale_ratio, float out_shift, int* in_first_pixel, int* in_last_pixel, float* in_center_of_out) -{ - float out_pixel_center = (float)n + 0.5f; - float out_pixel_influence_lowerbound = out_pixel_center - out_filter_radius; - float out_pixel_influence_upperbound = out_pixel_center + out_filter_radius; - - float in_pixel_influence_lowerbound = (out_pixel_influence_lowerbound + out_shift) / scale_ratio; - float in_pixel_influence_upperbound = (out_pixel_influence_upperbound + out_shift) / scale_ratio; - - *in_center_of_out = (out_pixel_center + out_shift) / scale_ratio; - *in_first_pixel = (int)(floor(in_pixel_influence_lowerbound + 0.5)); - *in_last_pixel = (int)(floor(in_pixel_influence_upperbound - 0.5)); -} - -// What output pixels does this input pixel contribute to? -static void stbir__calculate_sample_range_downsample(int n, float in_pixels_radius, float scale_ratio, float out_shift, int* out_first_pixel, int* out_last_pixel, float* out_center_of_in) -{ - float in_pixel_center = (float)n + 0.5f; - float in_pixel_influence_lowerbound = in_pixel_center - in_pixels_radius; - float in_pixel_influence_upperbound = in_pixel_center + in_pixels_radius; - - float out_pixel_influence_lowerbound = in_pixel_influence_lowerbound * scale_ratio - out_shift; - float out_pixel_influence_upperbound = in_pixel_influence_upperbound * scale_ratio - out_shift; - - *out_center_of_in = in_pixel_center * scale_ratio - out_shift; - *out_first_pixel = (int)(floor(out_pixel_influence_lowerbound + 0.5)); - *out_last_pixel = (int)(floor(out_pixel_influence_upperbound - 0.5)); -} - -static void stbir__calculate_coefficients_upsample(stbir_filter filter, float scale, int in_first_pixel, int in_last_pixel, float in_center_of_out, stbir__contributors* contributor, float* coefficient_group) -{ - int i; - float total_filter = 0; - float filter_scale; - - STBIR_ASSERT(in_last_pixel - in_first_pixel <= (int)ceil(stbir__filter_info_table[filter].support(1/scale) * 2)); // Taken directly from stbir__get_coefficient_width() which we can't call because we don't know if we're horizontal or vertical. - - contributor->n0 = in_first_pixel; - contributor->n1 = in_last_pixel; - - STBIR_ASSERT(contributor->n1 >= contributor->n0); - - for (i = 0; i <= in_last_pixel - in_first_pixel; i++) - { - float in_pixel_center = (float)(i + in_first_pixel) + 0.5f; - coefficient_group[i] = stbir__filter_info_table[filter].kernel(in_center_of_out - in_pixel_center, 1 / scale); - - // If the coefficient is zero, skip it. (Don't do the <0 check here, we want the influence of those outside pixels.) - if (i == 0 && !coefficient_group[i]) - { - contributor->n0 = ++in_first_pixel; - i--; - continue; - } - - total_filter += coefficient_group[i]; - } - - // NOTE(fg): Not actually true in general, nor is there any reason to expect it should be. - // It would be true in exact math but is at best approximately true in floating-point math, - // and it would not make sense to try and put actual bounds on this here because it depends - // on the image aspect ratio which can get pretty extreme. - //STBIR_ASSERT(stbir__filter_info_table[filter].kernel((float)(in_last_pixel + 1) + 0.5f - in_center_of_out, 1/scale) == 0); - - STBIR_ASSERT(total_filter > 0.9); - STBIR_ASSERT(total_filter < 1.1f); // Make sure it's not way off. - - // Make sure the sum of all coefficients is 1. - filter_scale = 1 / total_filter; - - for (i = 0; i <= in_last_pixel - in_first_pixel; i++) - coefficient_group[i] *= filter_scale; - - for (i = in_last_pixel - in_first_pixel; i >= 0; i--) - { - if (coefficient_group[i]) - break; - - // This line has no weight. We can skip it. - contributor->n1 = contributor->n0 + i - 1; - } -} - -static void stbir__calculate_coefficients_downsample(stbir_filter filter, float scale_ratio, int out_first_pixel, int out_last_pixel, float out_center_of_in, stbir__contributors* contributor, float* coefficient_group) -{ - int i; - - STBIR_ASSERT(out_last_pixel - out_first_pixel <= (int)ceil(stbir__filter_info_table[filter].support(scale_ratio) * 2)); // Taken directly from stbir__get_coefficient_width() which we can't call because we don't know if we're horizontal or vertical. - - contributor->n0 = out_first_pixel; - contributor->n1 = out_last_pixel; - - STBIR_ASSERT(contributor->n1 >= contributor->n0); - - for (i = 0; i <= out_last_pixel - out_first_pixel; i++) - { - float out_pixel_center = (float)(i + out_first_pixel) + 0.5f; - float x = out_pixel_center - out_center_of_in; - coefficient_group[i] = stbir__filter_info_table[filter].kernel(x, scale_ratio) * scale_ratio; - } - - // NOTE(fg): Not actually true in general, nor is there any reason to expect it should be. - // It would be true in exact math but is at best approximately true in floating-point math, - // and it would not make sense to try and put actual bounds on this here because it depends - // on the image aspect ratio which can get pretty extreme. - //STBIR_ASSERT(stbir__filter_info_table[filter].kernel((float)(out_last_pixel + 1) + 0.5f - out_center_of_in, scale_ratio) == 0); - - for (i = out_last_pixel - out_first_pixel; i >= 0; i--) - { - if (coefficient_group[i]) - break; - - // This line has no weight. We can skip it. - contributor->n1 = contributor->n0 + i - 1; - } -} - -static void stbir__normalize_downsample_coefficients(stbir__contributors* contributors, float* coefficients, stbir_filter filter, float scale_ratio, int input_size, int output_size) -{ - int num_contributors = stbir__get_contributors(scale_ratio, filter, input_size, output_size); - int num_coefficients = stbir__get_coefficient_width(filter, scale_ratio); - int i, j; - int skip; - - for (i = 0; i < output_size; i++) - { - float scale; - float total = 0; - - for (j = 0; j < num_contributors; j++) - { - if (i >= contributors[j].n0 && i <= contributors[j].n1) - { - float coefficient = *stbir__get_coefficient(coefficients, filter, scale_ratio, j, i - contributors[j].n0); - total += coefficient; - } - else if (i < contributors[j].n0) - break; - } - - STBIR_ASSERT(total > 0.9f); - STBIR_ASSERT(total < 1.1f); - - scale = 1 / total; - - for (j = 0; j < num_contributors; j++) - { - if (i >= contributors[j].n0 && i <= contributors[j].n1) - *stbir__get_coefficient(coefficients, filter, scale_ratio, j, i - contributors[j].n0) *= scale; - else if (i < contributors[j].n0) - break; - } - } - - // Optimize: Skip zero coefficients and contributions outside of image bounds. - // Do this after normalizing because normalization depends on the n0/n1 values. - for (j = 0; j < num_contributors; j++) - { - int range, max, width; - - skip = 0; - while (*stbir__get_coefficient(coefficients, filter, scale_ratio, j, skip) == 0) - skip++; - - contributors[j].n0 += skip; - - while (contributors[j].n0 < 0) - { - contributors[j].n0++; - skip++; - } - - range = contributors[j].n1 - contributors[j].n0 + 1; - max = stbir__min(num_coefficients, range); - - width = stbir__get_coefficient_width(filter, scale_ratio); - for (i = 0; i < max; i++) - { - if (i + skip >= width) - break; - - *stbir__get_coefficient(coefficients, filter, scale_ratio, j, i) = *stbir__get_coefficient(coefficients, filter, scale_ratio, j, i + skip); - } - - continue; - } - - // Using min to avoid writing into invalid pixels. - for (i = 0; i < num_contributors; i++) - contributors[i].n1 = stbir__min(contributors[i].n1, output_size - 1); -} - -// Each scan line uses the same kernel values so we should calculate the kernel -// values once and then we can use them for every scan line. -static void stbir__calculate_filters(stbir__contributors* contributors, float* coefficients, stbir_filter filter, float scale_ratio, float shift, int input_size, int output_size) -{ - int n; - int total_contributors = stbir__get_contributors(scale_ratio, filter, input_size, output_size); - - if (stbir__use_upsampling(scale_ratio)) - { - float out_pixels_radius = stbir__filter_info_table[filter].support(1 / scale_ratio) * scale_ratio; - - // Looping through out pixels - for (n = 0; n < total_contributors; n++) - { - float in_center_of_out; // Center of the current out pixel in the in pixel space - int in_first_pixel, in_last_pixel; - - stbir__calculate_sample_range_upsample(n, out_pixels_radius, scale_ratio, shift, &in_first_pixel, &in_last_pixel, &in_center_of_out); - - stbir__calculate_coefficients_upsample(filter, scale_ratio, in_first_pixel, in_last_pixel, in_center_of_out, stbir__get_contributor(contributors, n), stbir__get_coefficient(coefficients, filter, scale_ratio, n, 0)); - } - } - else - { - float in_pixels_radius = stbir__filter_info_table[filter].support(scale_ratio) / scale_ratio; - - // Looping through in pixels - for (n = 0; n < total_contributors; n++) - { - float out_center_of_in; // Center of the current out pixel in the in pixel space - int out_first_pixel, out_last_pixel; - int n_adjusted = n - stbir__get_filter_pixel_margin(filter, scale_ratio); - - stbir__calculate_sample_range_downsample(n_adjusted, in_pixels_radius, scale_ratio, shift, &out_first_pixel, &out_last_pixel, &out_center_of_in); - - stbir__calculate_coefficients_downsample(filter, scale_ratio, out_first_pixel, out_last_pixel, out_center_of_in, stbir__get_contributor(contributors, n), stbir__get_coefficient(coefficients, filter, scale_ratio, n, 0)); - } - - stbir__normalize_downsample_coefficients(contributors, coefficients, filter, scale_ratio, input_size, output_size); - } -} - -static float* stbir__get_decode_buffer(stbir__info* stbir_info) -{ - // The 0 index of the decode buffer starts after the margin. This makes - // it okay to use negative indexes on the decode buffer. - return &stbir_info->decode_buffer[stbir_info->horizontal_filter_pixel_margin * stbir_info->channels]; -} - -#define STBIR__DECODE(type, colorspace) ((int)(type) * (STBIR_MAX_COLORSPACES) + (int)(colorspace)) - -static void stbir__decode_scanline(stbir__info* stbir_info, int n) -{ - int c; - int channels = stbir_info->channels; - int alpha_channel = stbir_info->alpha_channel; - int type = stbir_info->type; - int colorspace = stbir_info->colorspace; - int input_w = stbir_info->input_w; - size_t input_stride_bytes = stbir_info->input_stride_bytes; - float* decode_buffer = stbir__get_decode_buffer(stbir_info); - stbir_edge edge_horizontal = stbir_info->edge_horizontal; - stbir_edge edge_vertical = stbir_info->edge_vertical; - size_t in_buffer_row_offset = stbir__edge_wrap(edge_vertical, n, stbir_info->input_h) * input_stride_bytes; - const void* input_data = (char *) stbir_info->input_data + in_buffer_row_offset; - int max_x = input_w + stbir_info->horizontal_filter_pixel_margin; - int decode = STBIR__DECODE(type, colorspace); - - int x = -stbir_info->horizontal_filter_pixel_margin; - - // special handling for STBIR_EDGE_ZERO because it needs to return an item that doesn't appear in the input, - // and we want to avoid paying overhead on every pixel if not STBIR_EDGE_ZERO - if (edge_vertical == STBIR_EDGE_ZERO && (n < 0 || n >= stbir_info->input_h)) - { - for (; x < max_x; x++) - for (c = 0; c < channels; c++) - decode_buffer[x*channels + c] = 0; - return; - } - - switch (decode) - { - case STBIR__DECODE(STBIR_TYPE_UINT8, STBIR_COLORSPACE_LINEAR): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = ((float)((const unsigned char*)input_data)[input_pixel_index + c]) / stbir__max_uint8_as_float; - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT8, STBIR_COLORSPACE_SRGB): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = stbir__srgb_uchar_to_linear_float[((const unsigned char*)input_data)[input_pixel_index + c]]; - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - decode_buffer[decode_pixel_index + alpha_channel] = ((float)((const unsigned char*)input_data)[input_pixel_index + alpha_channel]) / stbir__max_uint8_as_float; - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT16, STBIR_COLORSPACE_LINEAR): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = ((float)((const unsigned short*)input_data)[input_pixel_index + c]) / stbir__max_uint16_as_float; - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT16, STBIR_COLORSPACE_SRGB): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = stbir__srgb_to_linear(((float)((const unsigned short*)input_data)[input_pixel_index + c]) / stbir__max_uint16_as_float); - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - decode_buffer[decode_pixel_index + alpha_channel] = ((float)((const unsigned short*)input_data)[input_pixel_index + alpha_channel]) / stbir__max_uint16_as_float; - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT32, STBIR_COLORSPACE_LINEAR): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = (float)(((double)((const unsigned int*)input_data)[input_pixel_index + c]) / stbir__max_uint32_as_float); - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT32, STBIR_COLORSPACE_SRGB): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = stbir__srgb_to_linear((float)(((double)((const unsigned int*)input_data)[input_pixel_index + c]) / stbir__max_uint32_as_float)); - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - decode_buffer[decode_pixel_index + alpha_channel] = (float)(((double)((const unsigned int*)input_data)[input_pixel_index + alpha_channel]) / stbir__max_uint32_as_float); - } - break; - - case STBIR__DECODE(STBIR_TYPE_FLOAT, STBIR_COLORSPACE_LINEAR): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = ((const float*)input_data)[input_pixel_index + c]; - } - break; - - case STBIR__DECODE(STBIR_TYPE_FLOAT, STBIR_COLORSPACE_SRGB): - for (; x < max_x; x++) - { - int decode_pixel_index = x * channels; - int input_pixel_index = stbir__edge_wrap(edge_horizontal, x, input_w) * channels; - for (c = 0; c < channels; c++) - decode_buffer[decode_pixel_index + c] = stbir__srgb_to_linear(((const float*)input_data)[input_pixel_index + c]); - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - decode_buffer[decode_pixel_index + alpha_channel] = ((const float*)input_data)[input_pixel_index + alpha_channel]; - } - - break; - - default: - STBIR_ASSERT(!"Unknown type/colorspace/channels combination."); - break; - } - - if (!(stbir_info->flags & STBIR_FLAG_ALPHA_PREMULTIPLIED)) - { - for (x = -stbir_info->horizontal_filter_pixel_margin; x < max_x; x++) - { - int decode_pixel_index = x * channels; - - // If the alpha value is 0 it will clobber the color values. Make sure it's not. - float alpha = decode_buffer[decode_pixel_index + alpha_channel]; -#ifndef STBIR_NO_ALPHA_EPSILON - if (stbir_info->type != STBIR_TYPE_FLOAT) { - alpha += STBIR_ALPHA_EPSILON; - decode_buffer[decode_pixel_index + alpha_channel] = alpha; - } -#endif - for (c = 0; c < channels; c++) - { - if (c == alpha_channel) - continue; - - decode_buffer[decode_pixel_index + c] *= alpha; - } - } - } - - if (edge_horizontal == STBIR_EDGE_ZERO) - { - for (x = -stbir_info->horizontal_filter_pixel_margin; x < 0; x++) - { - for (c = 0; c < channels; c++) - decode_buffer[x*channels + c] = 0; - } - for (x = input_w; x < max_x; x++) - { - for (c = 0; c < channels; c++) - decode_buffer[x*channels + c] = 0; - } - } -} - -static float* stbir__get_ring_buffer_entry(float* ring_buffer, int index, int ring_buffer_length) -{ - return &ring_buffer[index * ring_buffer_length]; -} - -static float* stbir__add_empty_ring_buffer_entry(stbir__info* stbir_info, int n) -{ - int ring_buffer_index; - float* ring_buffer; - - stbir_info->ring_buffer_last_scanline = n; - - if (stbir_info->ring_buffer_begin_index < 0) - { - ring_buffer_index = stbir_info->ring_buffer_begin_index = 0; - stbir_info->ring_buffer_first_scanline = n; - } - else - { - ring_buffer_index = (stbir_info->ring_buffer_begin_index + (stbir_info->ring_buffer_last_scanline - stbir_info->ring_buffer_first_scanline)) % stbir_info->ring_buffer_num_entries; - STBIR_ASSERT(ring_buffer_index != stbir_info->ring_buffer_begin_index); - } - - ring_buffer = stbir__get_ring_buffer_entry(stbir_info->ring_buffer, ring_buffer_index, stbir_info->ring_buffer_length_bytes / sizeof(float)); - memset(ring_buffer, 0, stbir_info->ring_buffer_length_bytes); - - return ring_buffer; -} - - -static void stbir__resample_horizontal_upsample(stbir__info* stbir_info, float* output_buffer) -{ - int x, k; - int output_w = stbir_info->output_w; - int channels = stbir_info->channels; - float* decode_buffer = stbir__get_decode_buffer(stbir_info); - stbir__contributors* horizontal_contributors = stbir_info->horizontal_contributors; - float* horizontal_coefficients = stbir_info->horizontal_coefficients; - int coefficient_width = stbir_info->horizontal_coefficient_width; - - for (x = 0; x < output_w; x++) - { - int n0 = horizontal_contributors[x].n0; - int n1 = horizontal_contributors[x].n1; - - int out_pixel_index = x * channels; - int coefficient_group = coefficient_width * x; - int coefficient_counter = 0; - - STBIR_ASSERT(n1 >= n0); - STBIR_ASSERT(n0 >= -stbir_info->horizontal_filter_pixel_margin); - STBIR_ASSERT(n1 >= -stbir_info->horizontal_filter_pixel_margin); - STBIR_ASSERT(n0 < stbir_info->input_w + stbir_info->horizontal_filter_pixel_margin); - STBIR_ASSERT(n1 < stbir_info->input_w + stbir_info->horizontal_filter_pixel_margin); - - switch (channels) { - case 1: - for (k = n0; k <= n1; k++) - { - int in_pixel_index = k * 1; - float coefficient = horizontal_coefficients[coefficient_group + coefficient_counter++]; - STBIR_ASSERT(coefficient != 0); - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - } - break; - case 2: - for (k = n0; k <= n1; k++) - { - int in_pixel_index = k * 2; - float coefficient = horizontal_coefficients[coefficient_group + coefficient_counter++]; - STBIR_ASSERT(coefficient != 0); - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - output_buffer[out_pixel_index + 1] += decode_buffer[in_pixel_index + 1] * coefficient; - } - break; - case 3: - for (k = n0; k <= n1; k++) - { - int in_pixel_index = k * 3; - float coefficient = horizontal_coefficients[coefficient_group + coefficient_counter++]; - STBIR_ASSERT(coefficient != 0); - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - output_buffer[out_pixel_index + 1] += decode_buffer[in_pixel_index + 1] * coefficient; - output_buffer[out_pixel_index + 2] += decode_buffer[in_pixel_index + 2] * coefficient; - } - break; - case 4: - for (k = n0; k <= n1; k++) - { - int in_pixel_index = k * 4; - float coefficient = horizontal_coefficients[coefficient_group + coefficient_counter++]; - STBIR_ASSERT(coefficient != 0); - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - output_buffer[out_pixel_index + 1] += decode_buffer[in_pixel_index + 1] * coefficient; - output_buffer[out_pixel_index + 2] += decode_buffer[in_pixel_index + 2] * coefficient; - output_buffer[out_pixel_index + 3] += decode_buffer[in_pixel_index + 3] * coefficient; - } - break; - default: - for (k = n0; k <= n1; k++) - { - int in_pixel_index = k * channels; - float coefficient = horizontal_coefficients[coefficient_group + coefficient_counter++]; - int c; - STBIR_ASSERT(coefficient != 0); - for (c = 0; c < channels; c++) - output_buffer[out_pixel_index + c] += decode_buffer[in_pixel_index + c] * coefficient; - } - break; - } - } -} - -static void stbir__resample_horizontal_downsample(stbir__info* stbir_info, float* output_buffer) -{ - int x, k; - int input_w = stbir_info->input_w; - int channels = stbir_info->channels; - float* decode_buffer = stbir__get_decode_buffer(stbir_info); - stbir__contributors* horizontal_contributors = stbir_info->horizontal_contributors; - float* horizontal_coefficients = stbir_info->horizontal_coefficients; - int coefficient_width = stbir_info->horizontal_coefficient_width; - int filter_pixel_margin = stbir_info->horizontal_filter_pixel_margin; - int max_x = input_w + filter_pixel_margin * 2; - - STBIR_ASSERT(!stbir__use_width_upsampling(stbir_info)); - - switch (channels) { - case 1: - for (x = 0; x < max_x; x++) - { - int n0 = horizontal_contributors[x].n0; - int n1 = horizontal_contributors[x].n1; - - int in_x = x - filter_pixel_margin; - int in_pixel_index = in_x * 1; - int max_n = n1; - int coefficient_group = coefficient_width * x; - - for (k = n0; k <= max_n; k++) - { - int out_pixel_index = k * 1; - float coefficient = horizontal_coefficients[coefficient_group + k - n0]; - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - } - } - break; - - case 2: - for (x = 0; x < max_x; x++) - { - int n0 = horizontal_contributors[x].n0; - int n1 = horizontal_contributors[x].n1; - - int in_x = x - filter_pixel_margin; - int in_pixel_index = in_x * 2; - int max_n = n1; - int coefficient_group = coefficient_width * x; - - for (k = n0; k <= max_n; k++) - { - int out_pixel_index = k * 2; - float coefficient = horizontal_coefficients[coefficient_group + k - n0]; - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - output_buffer[out_pixel_index + 1] += decode_buffer[in_pixel_index + 1] * coefficient; - } - } - break; - - case 3: - for (x = 0; x < max_x; x++) - { - int n0 = horizontal_contributors[x].n0; - int n1 = horizontal_contributors[x].n1; - - int in_x = x - filter_pixel_margin; - int in_pixel_index = in_x * 3; - int max_n = n1; - int coefficient_group = coefficient_width * x; - - for (k = n0; k <= max_n; k++) - { - int out_pixel_index = k * 3; - float coefficient = horizontal_coefficients[coefficient_group + k - n0]; - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - output_buffer[out_pixel_index + 1] += decode_buffer[in_pixel_index + 1] * coefficient; - output_buffer[out_pixel_index + 2] += decode_buffer[in_pixel_index + 2] * coefficient; - } - } - break; - - case 4: - for (x = 0; x < max_x; x++) - { - int n0 = horizontal_contributors[x].n0; - int n1 = horizontal_contributors[x].n1; - - int in_x = x - filter_pixel_margin; - int in_pixel_index = in_x * 4; - int max_n = n1; - int coefficient_group = coefficient_width * x; - - for (k = n0; k <= max_n; k++) - { - int out_pixel_index = k * 4; - float coefficient = horizontal_coefficients[coefficient_group + k - n0]; - output_buffer[out_pixel_index + 0] += decode_buffer[in_pixel_index + 0] * coefficient; - output_buffer[out_pixel_index + 1] += decode_buffer[in_pixel_index + 1] * coefficient; - output_buffer[out_pixel_index + 2] += decode_buffer[in_pixel_index + 2] * coefficient; - output_buffer[out_pixel_index + 3] += decode_buffer[in_pixel_index + 3] * coefficient; - } - } - break; - - default: - for (x = 0; x < max_x; x++) - { - int n0 = horizontal_contributors[x].n0; - int n1 = horizontal_contributors[x].n1; - - int in_x = x - filter_pixel_margin; - int in_pixel_index = in_x * channels; - int max_n = n1; - int coefficient_group = coefficient_width * x; - - for (k = n0; k <= max_n; k++) - { - int c; - int out_pixel_index = k * channels; - float coefficient = horizontal_coefficients[coefficient_group + k - n0]; - for (c = 0; c < channels; c++) - output_buffer[out_pixel_index + c] += decode_buffer[in_pixel_index + c] * coefficient; - } - } - break; - } -} - -static void stbir__decode_and_resample_upsample(stbir__info* stbir_info, int n) -{ - // Decode the nth scanline from the source image into the decode buffer. - stbir__decode_scanline(stbir_info, n); - - // Now resample it into the ring buffer. - if (stbir__use_width_upsampling(stbir_info)) - stbir__resample_horizontal_upsample(stbir_info, stbir__add_empty_ring_buffer_entry(stbir_info, n)); - else - stbir__resample_horizontal_downsample(stbir_info, stbir__add_empty_ring_buffer_entry(stbir_info, n)); - - // Now it's sitting in the ring buffer ready to be used as source for the vertical sampling. -} - -static void stbir__decode_and_resample_downsample(stbir__info* stbir_info, int n) -{ - // Decode the nth scanline from the source image into the decode buffer. - stbir__decode_scanline(stbir_info, n); - - memset(stbir_info->horizontal_buffer, 0, stbir_info->output_w * stbir_info->channels * sizeof(float)); - - // Now resample it into the horizontal buffer. - if (stbir__use_width_upsampling(stbir_info)) - stbir__resample_horizontal_upsample(stbir_info, stbir_info->horizontal_buffer); - else - stbir__resample_horizontal_downsample(stbir_info, stbir_info->horizontal_buffer); - - // Now it's sitting in the horizontal buffer ready to be distributed into the ring buffers. -} - -// Get the specified scan line from the ring buffer. -static float* stbir__get_ring_buffer_scanline(int get_scanline, float* ring_buffer, int begin_index, int first_scanline, int ring_buffer_num_entries, int ring_buffer_length) -{ - int ring_buffer_index = (begin_index + (get_scanline - first_scanline)) % ring_buffer_num_entries; - return stbir__get_ring_buffer_entry(ring_buffer, ring_buffer_index, ring_buffer_length); -} - - -static void stbir__encode_scanline(stbir__info* stbir_info, int num_pixels, void *output_buffer, float *encode_buffer, int channels, int alpha_channel, int decode) -{ - int x; - int n; - int num_nonalpha; - stbir_uint16 nonalpha[STBIR_MAX_CHANNELS]; - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_PREMULTIPLIED)) - { - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - float alpha = encode_buffer[pixel_index + alpha_channel]; - float reciprocal_alpha = alpha ? 1.0f / alpha : 0; - - // unrolling this produced a 1% slowdown upscaling a large RGBA linear-space image on my machine - stb - for (n = 0; n < channels; n++) - if (n != alpha_channel) - encode_buffer[pixel_index + n] *= reciprocal_alpha; - - // We added in a small epsilon to prevent the color channel from being deleted with zero alpha. - // Because we only add it for integer types, it will automatically be discarded on integer - // conversion, so we don't need to subtract it back out (which would be problematic for - // numeric precision reasons). - } - } - - // build a table of all channels that need colorspace correction, so - // we don't perform colorspace correction on channels that don't need it. - for (x = 0, num_nonalpha = 0; x < channels; ++x) - { - if (x != alpha_channel || (stbir_info->flags & STBIR_FLAG_ALPHA_USES_COLORSPACE)) - { - nonalpha[num_nonalpha++] = (stbir_uint16)x; - } - } - - #define STBIR__ROUND_INT(f) ((int) ((f)+0.5)) - #define STBIR__ROUND_UINT(f) ((stbir_uint32) ((f)+0.5)) - - #ifdef STBIR__SATURATE_INT - #define STBIR__ENCODE_LINEAR8(f) stbir__saturate8 (STBIR__ROUND_INT((f) * stbir__max_uint8_as_float )) - #define STBIR__ENCODE_LINEAR16(f) stbir__saturate16(STBIR__ROUND_INT((f) * stbir__max_uint16_as_float)) - #else - #define STBIR__ENCODE_LINEAR8(f) (unsigned char ) STBIR__ROUND_INT(stbir__saturate(f) * stbir__max_uint8_as_float ) - #define STBIR__ENCODE_LINEAR16(f) (unsigned short) STBIR__ROUND_INT(stbir__saturate(f) * stbir__max_uint16_as_float) - #endif - - switch (decode) - { - case STBIR__DECODE(STBIR_TYPE_UINT8, STBIR_COLORSPACE_LINEAR): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < channels; n++) - { - int index = pixel_index + n; - ((unsigned char*)output_buffer)[index] = STBIR__ENCODE_LINEAR8(encode_buffer[index]); - } - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT8, STBIR_COLORSPACE_SRGB): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < num_nonalpha; n++) - { - int index = pixel_index + nonalpha[n]; - ((unsigned char*)output_buffer)[index] = stbir__linear_to_srgb_uchar(encode_buffer[index]); - } - - if (!(stbir_info->flags & STBIR_FLAG_ALPHA_USES_COLORSPACE)) - ((unsigned char *)output_buffer)[pixel_index + alpha_channel] = STBIR__ENCODE_LINEAR8(encode_buffer[pixel_index+alpha_channel]); - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT16, STBIR_COLORSPACE_LINEAR): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < channels; n++) - { - int index = pixel_index + n; - ((unsigned short*)output_buffer)[index] = STBIR__ENCODE_LINEAR16(encode_buffer[index]); - } - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT16, STBIR_COLORSPACE_SRGB): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < num_nonalpha; n++) - { - int index = pixel_index + nonalpha[n]; - ((unsigned short*)output_buffer)[index] = (unsigned short)STBIR__ROUND_INT(stbir__linear_to_srgb(stbir__saturate(encode_buffer[index])) * stbir__max_uint16_as_float); - } - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - ((unsigned short*)output_buffer)[pixel_index + alpha_channel] = STBIR__ENCODE_LINEAR16(encode_buffer[pixel_index + alpha_channel]); - } - - break; - - case STBIR__DECODE(STBIR_TYPE_UINT32, STBIR_COLORSPACE_LINEAR): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < channels; n++) - { - int index = pixel_index + n; - ((unsigned int*)output_buffer)[index] = (unsigned int)STBIR__ROUND_UINT(((double)stbir__saturate(encode_buffer[index])) * stbir__max_uint32_as_float); - } - } - break; - - case STBIR__DECODE(STBIR_TYPE_UINT32, STBIR_COLORSPACE_SRGB): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < num_nonalpha; n++) - { - int index = pixel_index + nonalpha[n]; - ((unsigned int*)output_buffer)[index] = (unsigned int)STBIR__ROUND_UINT(((double)stbir__linear_to_srgb(stbir__saturate(encode_buffer[index]))) * stbir__max_uint32_as_float); - } - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - ((unsigned int*)output_buffer)[pixel_index + alpha_channel] = (unsigned int)STBIR__ROUND_INT(((double)stbir__saturate(encode_buffer[pixel_index + alpha_channel])) * stbir__max_uint32_as_float); - } - break; - - case STBIR__DECODE(STBIR_TYPE_FLOAT, STBIR_COLORSPACE_LINEAR): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < channels; n++) - { - int index = pixel_index + n; - ((float*)output_buffer)[index] = encode_buffer[index]; - } - } - break; - - case STBIR__DECODE(STBIR_TYPE_FLOAT, STBIR_COLORSPACE_SRGB): - for (x=0; x < num_pixels; ++x) - { - int pixel_index = x*channels; - - for (n = 0; n < num_nonalpha; n++) - { - int index = pixel_index + nonalpha[n]; - ((float*)output_buffer)[index] = stbir__linear_to_srgb(encode_buffer[index]); - } - - if (!(stbir_info->flags&STBIR_FLAG_ALPHA_USES_COLORSPACE)) - ((float*)output_buffer)[pixel_index + alpha_channel] = encode_buffer[pixel_index + alpha_channel]; - } - break; - - default: - STBIR_ASSERT(!"Unknown type/colorspace/channels combination."); - break; - } -} - -static void stbir__resample_vertical_upsample(stbir__info* stbir_info, int n) -{ - int x, k; - int output_w = stbir_info->output_w; - stbir__contributors* vertical_contributors = stbir_info->vertical_contributors; - float* vertical_coefficients = stbir_info->vertical_coefficients; - int channels = stbir_info->channels; - int alpha_channel = stbir_info->alpha_channel; - int type = stbir_info->type; - int colorspace = stbir_info->colorspace; - int ring_buffer_entries = stbir_info->ring_buffer_num_entries; - void* output_data = stbir_info->output_data; - float* encode_buffer = stbir_info->encode_buffer; - int decode = STBIR__DECODE(type, colorspace); - int coefficient_width = stbir_info->vertical_coefficient_width; - int coefficient_counter; - int contributor = n; - - float* ring_buffer = stbir_info->ring_buffer; - int ring_buffer_begin_index = stbir_info->ring_buffer_begin_index; - int ring_buffer_first_scanline = stbir_info->ring_buffer_first_scanline; - int ring_buffer_length = stbir_info->ring_buffer_length_bytes/sizeof(float); - - int n0,n1, output_row_start; - int coefficient_group = coefficient_width * contributor; - - n0 = vertical_contributors[contributor].n0; - n1 = vertical_contributors[contributor].n1; - - output_row_start = n * stbir_info->output_stride_bytes; - - STBIR_ASSERT(stbir__use_height_upsampling(stbir_info)); - - memset(encode_buffer, 0, output_w * sizeof(float) * channels); - - // I tried reblocking this for better cache usage of encode_buffer - // (using x_outer, k, x_inner), but it lost speed. -- stb - - coefficient_counter = 0; - switch (channels) { - case 1: - for (k = n0; k <= n1; k++) - { - int coefficient_index = coefficient_counter++; - float* ring_buffer_entry = stbir__get_ring_buffer_scanline(k, ring_buffer, ring_buffer_begin_index, ring_buffer_first_scanline, ring_buffer_entries, ring_buffer_length); - float coefficient = vertical_coefficients[coefficient_group + coefficient_index]; - for (x = 0; x < output_w; ++x) - { - int in_pixel_index = x * 1; - encode_buffer[in_pixel_index + 0] += ring_buffer_entry[in_pixel_index + 0] * coefficient; - } - } - break; - case 2: - for (k = n0; k <= n1; k++) - { - int coefficient_index = coefficient_counter++; - float* ring_buffer_entry = stbir__get_ring_buffer_scanline(k, ring_buffer, ring_buffer_begin_index, ring_buffer_first_scanline, ring_buffer_entries, ring_buffer_length); - float coefficient = vertical_coefficients[coefficient_group + coefficient_index]; - for (x = 0; x < output_w; ++x) - { - int in_pixel_index = x * 2; - encode_buffer[in_pixel_index + 0] += ring_buffer_entry[in_pixel_index + 0] * coefficient; - encode_buffer[in_pixel_index + 1] += ring_buffer_entry[in_pixel_index + 1] * coefficient; - } - } - break; - case 3: - for (k = n0; k <= n1; k++) - { - int coefficient_index = coefficient_counter++; - float* ring_buffer_entry = stbir__get_ring_buffer_scanline(k, ring_buffer, ring_buffer_begin_index, ring_buffer_first_scanline, ring_buffer_entries, ring_buffer_length); - float coefficient = vertical_coefficients[coefficient_group + coefficient_index]; - for (x = 0; x < output_w; ++x) - { - int in_pixel_index = x * 3; - encode_buffer[in_pixel_index + 0] += ring_buffer_entry[in_pixel_index + 0] * coefficient; - encode_buffer[in_pixel_index + 1] += ring_buffer_entry[in_pixel_index + 1] * coefficient; - encode_buffer[in_pixel_index + 2] += ring_buffer_entry[in_pixel_index + 2] * coefficient; - } - } - break; - case 4: - for (k = n0; k <= n1; k++) - { - int coefficient_index = coefficient_counter++; - float* ring_buffer_entry = stbir__get_ring_buffer_scanline(k, ring_buffer, ring_buffer_begin_index, ring_buffer_first_scanline, ring_buffer_entries, ring_buffer_length); - float coefficient = vertical_coefficients[coefficient_group + coefficient_index]; - for (x = 0; x < output_w; ++x) - { - int in_pixel_index = x * 4; - encode_buffer[in_pixel_index + 0] += ring_buffer_entry[in_pixel_index + 0] * coefficient; - encode_buffer[in_pixel_index + 1] += ring_buffer_entry[in_pixel_index + 1] * coefficient; - encode_buffer[in_pixel_index + 2] += ring_buffer_entry[in_pixel_index + 2] * coefficient; - encode_buffer[in_pixel_index + 3] += ring_buffer_entry[in_pixel_index + 3] * coefficient; - } - } - break; - default: - for (k = n0; k <= n1; k++) - { - int coefficient_index = coefficient_counter++; - float* ring_buffer_entry = stbir__get_ring_buffer_scanline(k, ring_buffer, ring_buffer_begin_index, ring_buffer_first_scanline, ring_buffer_entries, ring_buffer_length); - float coefficient = vertical_coefficients[coefficient_group + coefficient_index]; - for (x = 0; x < output_w; ++x) - { - int in_pixel_index = x * channels; - int c; - for (c = 0; c < channels; c++) - encode_buffer[in_pixel_index + c] += ring_buffer_entry[in_pixel_index + c] * coefficient; - } - } - break; - } - stbir__encode_scanline(stbir_info, output_w, (char *) output_data + output_row_start, encode_buffer, channels, alpha_channel, decode); -} - -static void stbir__resample_vertical_downsample(stbir__info* stbir_info, int n) -{ - int x, k; - int output_w = stbir_info->output_w; - stbir__contributors* vertical_contributors = stbir_info->vertical_contributors; - float* vertical_coefficients = stbir_info->vertical_coefficients; - int channels = stbir_info->channels; - int ring_buffer_entries = stbir_info->ring_buffer_num_entries; - float* horizontal_buffer = stbir_info->horizontal_buffer; - int coefficient_width = stbir_info->vertical_coefficient_width; - int contributor = n + stbir_info->vertical_filter_pixel_margin; - - float* ring_buffer = stbir_info->ring_buffer; - int ring_buffer_begin_index = stbir_info->ring_buffer_begin_index; - int ring_buffer_first_scanline = stbir_info->ring_buffer_first_scanline; - int ring_buffer_length = stbir_info->ring_buffer_length_bytes/sizeof(float); - int n0,n1; - - n0 = vertical_contributors[contributor].n0; - n1 = vertical_contributors[contributor].n1; - - STBIR_ASSERT(!stbir__use_height_upsampling(stbir_info)); - - for (k = n0; k <= n1; k++) - { - int coefficient_index = k - n0; - int coefficient_group = coefficient_width * contributor; - float coefficient = vertical_coefficients[coefficient_group + coefficient_index]; - - float* ring_buffer_entry = stbir__get_ring_buffer_scanline(k, ring_buffer, ring_buffer_begin_index, ring_buffer_first_scanline, ring_buffer_entries, ring_buffer_length); - - switch (channels) { - case 1: - for (x = 0; x < output_w; x++) - { - int in_pixel_index = x * 1; - ring_buffer_entry[in_pixel_index + 0] += horizontal_buffer[in_pixel_index + 0] * coefficient; - } - break; - case 2: - for (x = 0; x < output_w; x++) - { - int in_pixel_index = x * 2; - ring_buffer_entry[in_pixel_index + 0] += horizontal_buffer[in_pixel_index + 0] * coefficient; - ring_buffer_entry[in_pixel_index + 1] += horizontal_buffer[in_pixel_index + 1] * coefficient; - } - break; - case 3: - for (x = 0; x < output_w; x++) - { - int in_pixel_index = x * 3; - ring_buffer_entry[in_pixel_index + 0] += horizontal_buffer[in_pixel_index + 0] * coefficient; - ring_buffer_entry[in_pixel_index + 1] += horizontal_buffer[in_pixel_index + 1] * coefficient; - ring_buffer_entry[in_pixel_index + 2] += horizontal_buffer[in_pixel_index + 2] * coefficient; - } - break; - case 4: - for (x = 0; x < output_w; x++) - { - int in_pixel_index = x * 4; - ring_buffer_entry[in_pixel_index + 0] += horizontal_buffer[in_pixel_index + 0] * coefficient; - ring_buffer_entry[in_pixel_index + 1] += horizontal_buffer[in_pixel_index + 1] * coefficient; - ring_buffer_entry[in_pixel_index + 2] += horizontal_buffer[in_pixel_index + 2] * coefficient; - ring_buffer_entry[in_pixel_index + 3] += horizontal_buffer[in_pixel_index + 3] * coefficient; - } - break; - default: - for (x = 0; x < output_w; x++) - { - int in_pixel_index = x * channels; - - int c; - for (c = 0; c < channels; c++) - ring_buffer_entry[in_pixel_index + c] += horizontal_buffer[in_pixel_index + c] * coefficient; - } - break; - } - } -} - -static void stbir__buffer_loop_upsample(stbir__info* stbir_info) -{ - int y; - float scale_ratio = stbir_info->vertical_scale; - float out_scanlines_radius = stbir__filter_info_table[stbir_info->vertical_filter].support(1/scale_ratio) * scale_ratio; - - STBIR_ASSERT(stbir__use_height_upsampling(stbir_info)); - - for (y = 0; y < stbir_info->output_h; y++) - { - float in_center_of_out = 0; // Center of the current out scanline in the in scanline space - int in_first_scanline = 0, in_last_scanline = 0; - - stbir__calculate_sample_range_upsample(y, out_scanlines_radius, scale_ratio, stbir_info->vertical_shift, &in_first_scanline, &in_last_scanline, &in_center_of_out); - - STBIR_ASSERT(in_last_scanline - in_first_scanline + 1 <= stbir_info->ring_buffer_num_entries); - - if (stbir_info->ring_buffer_begin_index >= 0) - { - // Get rid of whatever we don't need anymore. - while (in_first_scanline > stbir_info->ring_buffer_first_scanline) - { - if (stbir_info->ring_buffer_first_scanline == stbir_info->ring_buffer_last_scanline) - { - // We just popped the last scanline off the ring buffer. - // Reset it to the empty state. - stbir_info->ring_buffer_begin_index = -1; - stbir_info->ring_buffer_first_scanline = 0; - stbir_info->ring_buffer_last_scanline = 0; - break; - } - else - { - stbir_info->ring_buffer_first_scanline++; - stbir_info->ring_buffer_begin_index = (stbir_info->ring_buffer_begin_index + 1) % stbir_info->ring_buffer_num_entries; - } - } - } - - // Load in new ones. - if (stbir_info->ring_buffer_begin_index < 0) - stbir__decode_and_resample_upsample(stbir_info, in_first_scanline); - - while (in_last_scanline > stbir_info->ring_buffer_last_scanline) - stbir__decode_and_resample_upsample(stbir_info, stbir_info->ring_buffer_last_scanline + 1); - - // Now all buffers should be ready to write a row of vertical sampling. - stbir__resample_vertical_upsample(stbir_info, y); - - STBIR_PROGRESS_REPORT((float)y / stbir_info->output_h); - } -} - -static void stbir__empty_ring_buffer(stbir__info* stbir_info, int first_necessary_scanline) -{ - int output_stride_bytes = stbir_info->output_stride_bytes; - int channels = stbir_info->channels; - int alpha_channel = stbir_info->alpha_channel; - int type = stbir_info->type; - int colorspace = stbir_info->colorspace; - int output_w = stbir_info->output_w; - void* output_data = stbir_info->output_data; - int decode = STBIR__DECODE(type, colorspace); - - float* ring_buffer = stbir_info->ring_buffer; - int ring_buffer_length = stbir_info->ring_buffer_length_bytes/sizeof(float); - - if (stbir_info->ring_buffer_begin_index >= 0) - { - // Get rid of whatever we don't need anymore. - while (first_necessary_scanline > stbir_info->ring_buffer_first_scanline) - { - if (stbir_info->ring_buffer_first_scanline >= 0 && stbir_info->ring_buffer_first_scanline < stbir_info->output_h) - { - int output_row_start = stbir_info->ring_buffer_first_scanline * output_stride_bytes; - float* ring_buffer_entry = stbir__get_ring_buffer_entry(ring_buffer, stbir_info->ring_buffer_begin_index, ring_buffer_length); - stbir__encode_scanline(stbir_info, output_w, (char *) output_data + output_row_start, ring_buffer_entry, channels, alpha_channel, decode); - STBIR_PROGRESS_REPORT((float)stbir_info->ring_buffer_first_scanline / stbir_info->output_h); - } - - if (stbir_info->ring_buffer_first_scanline == stbir_info->ring_buffer_last_scanline) - { - // We just popped the last scanline off the ring buffer. - // Reset it to the empty state. - stbir_info->ring_buffer_begin_index = -1; - stbir_info->ring_buffer_first_scanline = 0; - stbir_info->ring_buffer_last_scanline = 0; - break; - } - else - { - stbir_info->ring_buffer_first_scanline++; - stbir_info->ring_buffer_begin_index = (stbir_info->ring_buffer_begin_index + 1) % stbir_info->ring_buffer_num_entries; - } - } - } -} - -static void stbir__buffer_loop_downsample(stbir__info* stbir_info) -{ - int y; - float scale_ratio = stbir_info->vertical_scale; - int output_h = stbir_info->output_h; - float in_pixels_radius = stbir__filter_info_table[stbir_info->vertical_filter].support(scale_ratio) / scale_ratio; - int pixel_margin = stbir_info->vertical_filter_pixel_margin; - int max_y = stbir_info->input_h + pixel_margin; - - STBIR_ASSERT(!stbir__use_height_upsampling(stbir_info)); - - for (y = -pixel_margin; y < max_y; y++) - { - float out_center_of_in; // Center of the current out scanline in the in scanline space - int out_first_scanline, out_last_scanline; - - stbir__calculate_sample_range_downsample(y, in_pixels_radius, scale_ratio, stbir_info->vertical_shift, &out_first_scanline, &out_last_scanline, &out_center_of_in); - - STBIR_ASSERT(out_last_scanline - out_first_scanline + 1 <= stbir_info->ring_buffer_num_entries); - - if (out_last_scanline < 0 || out_first_scanline >= output_h) - continue; - - stbir__empty_ring_buffer(stbir_info, out_first_scanline); - - stbir__decode_and_resample_downsample(stbir_info, y); - - // Load in new ones. - if (stbir_info->ring_buffer_begin_index < 0) - stbir__add_empty_ring_buffer_entry(stbir_info, out_first_scanline); - - while (out_last_scanline > stbir_info->ring_buffer_last_scanline) - stbir__add_empty_ring_buffer_entry(stbir_info, stbir_info->ring_buffer_last_scanline + 1); - - // Now the horizontal buffer is ready to write to all ring buffer rows. - stbir__resample_vertical_downsample(stbir_info, y); - } - - stbir__empty_ring_buffer(stbir_info, stbir_info->output_h); -} - -static void stbir__setup(stbir__info *info, int input_w, int input_h, int output_w, int output_h, int channels) -{ - info->input_w = input_w; - info->input_h = input_h; - info->output_w = output_w; - info->output_h = output_h; - info->channels = channels; -} - -static void stbir__calculate_transform(stbir__info *info, float s0, float t0, float s1, float t1, float *transform) -{ - info->s0 = s0; - info->t0 = t0; - info->s1 = s1; - info->t1 = t1; - - if (transform) - { - info->horizontal_scale = transform[0]; - info->vertical_scale = transform[1]; - info->horizontal_shift = transform[2]; - info->vertical_shift = transform[3]; - } - else - { - info->horizontal_scale = ((float)info->output_w / info->input_w) / (s1 - s0); - info->vertical_scale = ((float)info->output_h / info->input_h) / (t1 - t0); - - info->horizontal_shift = s0 * info->output_w / (s1 - s0); - info->vertical_shift = t0 * info->output_h / (t1 - t0); - } -} - -static void stbir__choose_filter(stbir__info *info, stbir_filter h_filter, stbir_filter v_filter) -{ - if (h_filter == 0) - h_filter = stbir__use_upsampling(info->horizontal_scale) ? STBIR_DEFAULT_FILTER_UPSAMPLE : STBIR_DEFAULT_FILTER_DOWNSAMPLE; - if (v_filter == 0) - v_filter = stbir__use_upsampling(info->vertical_scale) ? STBIR_DEFAULT_FILTER_UPSAMPLE : STBIR_DEFAULT_FILTER_DOWNSAMPLE; - info->horizontal_filter = h_filter; - info->vertical_filter = v_filter; -} - -static stbir_uint32 stbir__calculate_memory(stbir__info *info) -{ - int pixel_margin = stbir__get_filter_pixel_margin(info->horizontal_filter, info->horizontal_scale); - int filter_height = stbir__get_filter_pixel_width(info->vertical_filter, info->vertical_scale); - - info->horizontal_num_contributors = stbir__get_contributors(info->horizontal_scale, info->horizontal_filter, info->input_w, info->output_w); - info->vertical_num_contributors = stbir__get_contributors(info->vertical_scale , info->vertical_filter , info->input_h, info->output_h); - - // One extra entry because floating point precision problems sometimes cause an extra to be necessary. - info->ring_buffer_num_entries = filter_height + 1; - - info->horizontal_contributors_size = info->horizontal_num_contributors * sizeof(stbir__contributors); - info->horizontal_coefficients_size = stbir__get_total_horizontal_coefficients(info) * sizeof(float); - info->vertical_contributors_size = info->vertical_num_contributors * sizeof(stbir__contributors); - info->vertical_coefficients_size = stbir__get_total_vertical_coefficients(info) * sizeof(float); - info->decode_buffer_size = (info->input_w + pixel_margin * 2) * info->channels * sizeof(float); - info->horizontal_buffer_size = info->output_w * info->channels * sizeof(float); - info->ring_buffer_size = info->output_w * info->channels * info->ring_buffer_num_entries * sizeof(float); - info->encode_buffer_size = info->output_w * info->channels * sizeof(float); - - STBIR_ASSERT(info->horizontal_filter != 0); - STBIR_ASSERT(info->horizontal_filter < STBIR__ARRAY_SIZE(stbir__filter_info_table)); // this now happens too late - STBIR_ASSERT(info->vertical_filter != 0); - STBIR_ASSERT(info->vertical_filter < STBIR__ARRAY_SIZE(stbir__filter_info_table)); // this now happens too late - - if (stbir__use_height_upsampling(info)) - // The horizontal buffer is for when we're downsampling the height and we - // can't output the result of sampling the decode buffer directly into the - // ring buffers. - info->horizontal_buffer_size = 0; - else - // The encode buffer is to retain precision in the height upsampling method - // and isn't used when height downsampling. - info->encode_buffer_size = 0; - - return info->horizontal_contributors_size + info->horizontal_coefficients_size - + info->vertical_contributors_size + info->vertical_coefficients_size - + info->decode_buffer_size + info->horizontal_buffer_size - + info->ring_buffer_size + info->encode_buffer_size; -} - -static int stbir__resize_allocated(stbir__info *info, - const void* input_data, int input_stride_in_bytes, - void* output_data, int output_stride_in_bytes, - int alpha_channel, stbir_uint32 flags, stbir_datatype type, - stbir_edge edge_horizontal, stbir_edge edge_vertical, stbir_colorspace colorspace, - void* tempmem, size_t tempmem_size_in_bytes) -{ - size_t memory_required = stbir__calculate_memory(info); - - int width_stride_input = input_stride_in_bytes ? input_stride_in_bytes : info->channels * info->input_w * stbir__type_size[type]; - int width_stride_output = output_stride_in_bytes ? output_stride_in_bytes : info->channels * info->output_w * stbir__type_size[type]; - -#ifdef STBIR_DEBUG_OVERWRITE_TEST -#define OVERWRITE_ARRAY_SIZE 8 - unsigned char overwrite_output_before_pre[OVERWRITE_ARRAY_SIZE]; - unsigned char overwrite_tempmem_before_pre[OVERWRITE_ARRAY_SIZE]; - unsigned char overwrite_output_after_pre[OVERWRITE_ARRAY_SIZE]; - unsigned char overwrite_tempmem_after_pre[OVERWRITE_ARRAY_SIZE]; - - size_t begin_forbidden = width_stride_output * (info->output_h - 1) + info->output_w * info->channels * stbir__type_size[type]; - memcpy(overwrite_output_before_pre, &((unsigned char*)output_data)[-OVERWRITE_ARRAY_SIZE], OVERWRITE_ARRAY_SIZE); - memcpy(overwrite_output_after_pre, &((unsigned char*)output_data)[begin_forbidden], OVERWRITE_ARRAY_SIZE); - memcpy(overwrite_tempmem_before_pre, &((unsigned char*)tempmem)[-OVERWRITE_ARRAY_SIZE], OVERWRITE_ARRAY_SIZE); - memcpy(overwrite_tempmem_after_pre, &((unsigned char*)tempmem)[tempmem_size_in_bytes], OVERWRITE_ARRAY_SIZE); -#endif - - STBIR_ASSERT(info->channels >= 0); - STBIR_ASSERT(info->channels <= STBIR_MAX_CHANNELS); - - if (info->channels < 0 || info->channels > STBIR_MAX_CHANNELS) - return 0; - - STBIR_ASSERT(info->horizontal_filter < STBIR__ARRAY_SIZE(stbir__filter_info_table)); - STBIR_ASSERT(info->vertical_filter < STBIR__ARRAY_SIZE(stbir__filter_info_table)); - - if (info->horizontal_filter >= STBIR__ARRAY_SIZE(stbir__filter_info_table)) - return 0; - if (info->vertical_filter >= STBIR__ARRAY_SIZE(stbir__filter_info_table)) - return 0; - - if (alpha_channel < 0) - flags |= STBIR_FLAG_ALPHA_USES_COLORSPACE | STBIR_FLAG_ALPHA_PREMULTIPLIED; - - if (!(flags&STBIR_FLAG_ALPHA_USES_COLORSPACE) || !(flags&STBIR_FLAG_ALPHA_PREMULTIPLIED)) { - STBIR_ASSERT(alpha_channel >= 0 && alpha_channel < info->channels); - } - - if (alpha_channel >= info->channels) - return 0; - - STBIR_ASSERT(tempmem); - - if (!tempmem) - return 0; - - STBIR_ASSERT(tempmem_size_in_bytes >= memory_required); - - if (tempmem_size_in_bytes < memory_required) - return 0; - - memset(tempmem, 0, tempmem_size_in_bytes); - - info->input_data = input_data; - info->input_stride_bytes = width_stride_input; - - info->output_data = output_data; - info->output_stride_bytes = width_stride_output; - - info->alpha_channel = alpha_channel; - info->flags = flags; - info->type = type; - info->edge_horizontal = edge_horizontal; - info->edge_vertical = edge_vertical; - info->colorspace = colorspace; - - info->horizontal_coefficient_width = stbir__get_coefficient_width (info->horizontal_filter, info->horizontal_scale); - info->vertical_coefficient_width = stbir__get_coefficient_width (info->vertical_filter , info->vertical_scale ); - info->horizontal_filter_pixel_width = stbir__get_filter_pixel_width (info->horizontal_filter, info->horizontal_scale); - info->vertical_filter_pixel_width = stbir__get_filter_pixel_width (info->vertical_filter , info->vertical_scale ); - info->horizontal_filter_pixel_margin = stbir__get_filter_pixel_margin(info->horizontal_filter, info->horizontal_scale); - info->vertical_filter_pixel_margin = stbir__get_filter_pixel_margin(info->vertical_filter , info->vertical_scale ); - - info->ring_buffer_length_bytes = info->output_w * info->channels * sizeof(float); - info->decode_buffer_pixels = info->input_w + info->horizontal_filter_pixel_margin * 2; - -#define STBIR__NEXT_MEMPTR(current, newtype) (newtype*)(((unsigned char*)current) + current##_size) - - info->horizontal_contributors = (stbir__contributors *) tempmem; - info->horizontal_coefficients = STBIR__NEXT_MEMPTR(info->horizontal_contributors, float); - info->vertical_contributors = STBIR__NEXT_MEMPTR(info->horizontal_coefficients, stbir__contributors); - info->vertical_coefficients = STBIR__NEXT_MEMPTR(info->vertical_contributors, float); - info->decode_buffer = STBIR__NEXT_MEMPTR(info->vertical_coefficients, float); - - if (stbir__use_height_upsampling(info)) - { - info->horizontal_buffer = NULL; - info->ring_buffer = STBIR__NEXT_MEMPTR(info->decode_buffer, float); - info->encode_buffer = STBIR__NEXT_MEMPTR(info->ring_buffer, float); - - STBIR_ASSERT((size_t)STBIR__NEXT_MEMPTR(info->encode_buffer, unsigned char) == (size_t)tempmem + tempmem_size_in_bytes); - } - else - { - info->horizontal_buffer = STBIR__NEXT_MEMPTR(info->decode_buffer, float); - info->ring_buffer = STBIR__NEXT_MEMPTR(info->horizontal_buffer, float); - info->encode_buffer = NULL; - - STBIR_ASSERT((size_t)STBIR__NEXT_MEMPTR(info->ring_buffer, unsigned char) == (size_t)tempmem + tempmem_size_in_bytes); - } - -#undef STBIR__NEXT_MEMPTR - - // This signals that the ring buffer is empty - info->ring_buffer_begin_index = -1; - - stbir__calculate_filters(info->horizontal_contributors, info->horizontal_coefficients, info->horizontal_filter, info->horizontal_scale, info->horizontal_shift, info->input_w, info->output_w); - stbir__calculate_filters(info->vertical_contributors, info->vertical_coefficients, info->vertical_filter, info->vertical_scale, info->vertical_shift, info->input_h, info->output_h); - - STBIR_PROGRESS_REPORT(0); - - if (stbir__use_height_upsampling(info)) - stbir__buffer_loop_upsample(info); - else - stbir__buffer_loop_downsample(info); - - STBIR_PROGRESS_REPORT(1); - -#ifdef STBIR_DEBUG_OVERWRITE_TEST - STBIR_ASSERT(memcmp(overwrite_output_before_pre, &((unsigned char*)output_data)[-OVERWRITE_ARRAY_SIZE], OVERWRITE_ARRAY_SIZE) == 0); - STBIR_ASSERT(memcmp(overwrite_output_after_pre, &((unsigned char*)output_data)[begin_forbidden], OVERWRITE_ARRAY_SIZE) == 0); - STBIR_ASSERT(memcmp(overwrite_tempmem_before_pre, &((unsigned char*)tempmem)[-OVERWRITE_ARRAY_SIZE], OVERWRITE_ARRAY_SIZE) == 0); - STBIR_ASSERT(memcmp(overwrite_tempmem_after_pre, &((unsigned char*)tempmem)[tempmem_size_in_bytes], OVERWRITE_ARRAY_SIZE) == 0); -#endif - - return 1; -} - - -static int stbir__resize_arbitrary( - void *alloc_context, - const void* input_data, int input_w, int input_h, int input_stride_in_bytes, - void* output_data, int output_w, int output_h, int output_stride_in_bytes, - float s0, float t0, float s1, float t1, float *transform, - int channels, int alpha_channel, stbir_uint32 flags, stbir_datatype type, - stbir_filter h_filter, stbir_filter v_filter, - stbir_edge edge_horizontal, stbir_edge edge_vertical, stbir_colorspace colorspace) -{ - stbir__info info; - int result; - size_t memory_required; - void* extra_memory; - - stbir__setup(&info, input_w, input_h, output_w, output_h, channels); - stbir__calculate_transform(&info, s0,t0,s1,t1,transform); - stbir__choose_filter(&info, h_filter, v_filter); - memory_required = stbir__calculate_memory(&info); - extra_memory = STBIR_MALLOC(memory_required, alloc_context); - - if (!extra_memory) - return 0; - - result = stbir__resize_allocated(&info, input_data, input_stride_in_bytes, - output_data, output_stride_in_bytes, - alpha_channel, flags, type, - edge_horizontal, edge_vertical, - colorspace, extra_memory, memory_required); - - STBIR_FREE(extra_memory, alloc_context); - - return result; -} - -STBIRDEF int stbir_resize_uint8( const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels) -{ - return stbir__resize_arbitrary(NULL, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,-1,0, STBIR_TYPE_UINT8, STBIR_FILTER_DEFAULT, STBIR_FILTER_DEFAULT, - STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP, STBIR_COLORSPACE_LINEAR); -} - -STBIRDEF int stbir_resize_float( const float *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - float *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels) -{ - return stbir__resize_arbitrary(NULL, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,-1,0, STBIR_TYPE_FLOAT, STBIR_FILTER_DEFAULT, STBIR_FILTER_DEFAULT, - STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP, STBIR_COLORSPACE_LINEAR); -} - -STBIRDEF int stbir_resize_uint8_srgb(const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags) -{ - return stbir__resize_arbitrary(NULL, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,alpha_channel,flags, STBIR_TYPE_UINT8, STBIR_FILTER_DEFAULT, STBIR_FILTER_DEFAULT, - STBIR_EDGE_CLAMP, STBIR_EDGE_CLAMP, STBIR_COLORSPACE_SRGB); -} - -STBIRDEF int stbir_resize_uint8_srgb_edgemode(const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode) -{ - return stbir__resize_arbitrary(NULL, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,alpha_channel,flags, STBIR_TYPE_UINT8, STBIR_FILTER_DEFAULT, STBIR_FILTER_DEFAULT, - edge_wrap_mode, edge_wrap_mode, STBIR_COLORSPACE_SRGB); -} - -STBIRDEF int stbir_resize_uint8_generic( const unsigned char *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - unsigned char *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode, stbir_filter filter, stbir_colorspace space, - void *alloc_context) -{ - return stbir__resize_arbitrary(alloc_context, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,alpha_channel,flags, STBIR_TYPE_UINT8, filter, filter, - edge_wrap_mode, edge_wrap_mode, space); -} - -STBIRDEF int stbir_resize_uint16_generic(const stbir_uint16 *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - stbir_uint16 *output_pixels , int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode, stbir_filter filter, stbir_colorspace space, - void *alloc_context) -{ - return stbir__resize_arbitrary(alloc_context, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,alpha_channel,flags, STBIR_TYPE_UINT16, filter, filter, - edge_wrap_mode, edge_wrap_mode, space); -} - - -STBIRDEF int stbir_resize_float_generic( const float *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - float *output_pixels , int output_w, int output_h, int output_stride_in_bytes, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_wrap_mode, stbir_filter filter, stbir_colorspace space, - void *alloc_context) -{ - return stbir__resize_arbitrary(alloc_context, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,alpha_channel,flags, STBIR_TYPE_FLOAT, filter, filter, - edge_wrap_mode, edge_wrap_mode, space); -} - - -STBIRDEF int stbir_resize( const void *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - void *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - stbir_datatype datatype, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_mode_horizontal, stbir_edge edge_mode_vertical, - stbir_filter filter_horizontal, stbir_filter filter_vertical, - stbir_colorspace space, void *alloc_context) -{ - return stbir__resize_arbitrary(alloc_context, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,NULL,num_channels,alpha_channel,flags, datatype, filter_horizontal, filter_vertical, - edge_mode_horizontal, edge_mode_vertical, space); -} - - -STBIRDEF int stbir_resize_subpixel(const void *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - void *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - stbir_datatype datatype, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_mode_horizontal, stbir_edge edge_mode_vertical, - stbir_filter filter_horizontal, stbir_filter filter_vertical, - stbir_colorspace space, void *alloc_context, - float x_scale, float y_scale, - float x_offset, float y_offset) -{ - float transform[4]; - transform[0] = x_scale; - transform[1] = y_scale; - transform[2] = x_offset; - transform[3] = y_offset; - return stbir__resize_arbitrary(alloc_context, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - 0,0,1,1,transform,num_channels,alpha_channel,flags, datatype, filter_horizontal, filter_vertical, - edge_mode_horizontal, edge_mode_vertical, space); -} - -STBIRDEF int stbir_resize_region( const void *input_pixels , int input_w , int input_h , int input_stride_in_bytes, - void *output_pixels, int output_w, int output_h, int output_stride_in_bytes, - stbir_datatype datatype, - int num_channels, int alpha_channel, int flags, - stbir_edge edge_mode_horizontal, stbir_edge edge_mode_vertical, - stbir_filter filter_horizontal, stbir_filter filter_vertical, - stbir_colorspace space, void *alloc_context, - float s0, float t0, float s1, float t1) -{ - return stbir__resize_arbitrary(alloc_context, input_pixels, input_w, input_h, input_stride_in_bytes, - output_pixels, output_w, output_h, output_stride_in_bytes, - s0,t0,s1,t1,NULL,num_channels,alpha_channel,flags, datatype, filter_horizontal, filter_vertical, - edge_mode_horizontal, edge_mode_vertical, space); -} - -#endif // STB_IMAGE_RESIZE_IMPLEMENTATION - -/* ------------------------------------------------------------------------------- -This software is available under 2 licenses -- choose whichever you prefer. ------------------------------------------------------------------------------- -ALTERNATIVE A - MIT License -Copyright (c) 2017 Sean Barrett -Permission is hereby granted, free of charge, to any person obtaining a copy of -this software and associated documentation files (the "Software"), to deal in -the Software without restriction, including without limitation the rights to -use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies -of the Software, and to permit persons to whom the Software is furnished to do -so, subject to the following conditions: -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. ------------------------------------------------------------------------------- -ALTERNATIVE B - Public Domain (www.unlicense.org) -This is free and unencumbered software released into the public domain. -Anyone is free to copy, modify, publish, use, compile, sell, or distribute this -software, either in source code form or as a compiled binary, for any purpose, -commercial or non-commercial, and by any means. -In jurisdictions that recognize copyright laws, the author or authors of this -software dedicate any and all copyright interest in the software to the public -domain. We make this dedication for the benefit of the public at large and to -the detriment of our heirs and successors. We intend this dedication to be an -overt act of relinquishment in perpetuity of all present and future rights to -this software under copyright law. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN -ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION -WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ------------------------------------------------------------------------------- -*/ diff --git a/code/externallibraries/stbimagehelpers/stb_image_write.h b/code/externallibraries/stbimagehelpers/stb_image_write.h deleted file mode 100644 index e4b32ed..0000000 --- a/code/externallibraries/stbimagehelpers/stb_image_write.h +++ /dev/null @@ -1,1724 +0,0 @@ -/* stb_image_write - v1.16 - public domain - http://nothings.org/stb - writes out PNG/BMP/TGA/JPEG/HDR images to C stdio - Sean Barrett 2010-2015 - no warranty implied; use at your own risk - - Before #including, - - #define STB_IMAGE_WRITE_IMPLEMENTATION - - in the file that you want to have the implementation. - - Will probably not work correctly with strict-aliasing optimizations. - -ABOUT: - - This header file is a library for writing images to C stdio or a callback. - - The PNG output is not optimal; it is 20-50% larger than the file - written by a decent optimizing implementation; though providing a custom - zlib compress function (see STBIW_ZLIB_COMPRESS) can mitigate that. - This library is designed for source code compactness and simplicity, - not optimal image file size or run-time performance. - -BUILDING: - - You can #define STBIW_ASSERT(x) before the #include to avoid using assert.h. - You can #define STBIW_MALLOC(), STBIW_REALLOC(), and STBIW_FREE() to replace - malloc,realloc,free. - You can #define STBIW_MEMMOVE() to replace memmove() - You can #define STBIW_ZLIB_COMPRESS to use a custom zlib-style compress function - for PNG compression (instead of the builtin one), it must have the following signature: - unsigned char * my_compress(unsigned char *data, int data_len, int *out_len, int quality); - The returned data will be freed with STBIW_FREE() (free() by default), - so it must be heap allocated with STBIW_MALLOC() (malloc() by default), - -UNICODE: - - If compiling for Windows and you wish to use Unicode filenames, compile - with - #define STBIW_WINDOWS_UTF8 - and pass utf8-encoded filenames. Call stbiw_convert_wchar_to_utf8 to convert - Windows wchar_t filenames to utf8. - -USAGE: - - There are five functions, one for each image file format: - - int stbi_write_png(char const *filename, int w, int h, int comp, const void *data, int stride_in_bytes); - int stbi_write_bmp(char const *filename, int w, int h, int comp, const void *data); - int stbi_write_tga(char const *filename, int w, int h, int comp, const void *data); - int stbi_write_jpg(char const *filename, int w, int h, int comp, const void *data, int quality); - int stbi_write_hdr(char const *filename, int w, int h, int comp, const float *data); - - void stbi_flip_vertically_on_write(int flag); // flag is non-zero to flip data vertically - - There are also five equivalent functions that use an arbitrary write function. You are - expected to open/close your file-equivalent before and after calling these: - - int stbi_write_png_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void *data, int stride_in_bytes); - int stbi_write_bmp_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void *data); - int stbi_write_tga_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void *data); - int stbi_write_hdr_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const float *data); - int stbi_write_jpg_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int quality); - - where the callback is: - void stbi_write_func(void *context, void *data, int size); - - You can configure it with these global variables: - int stbi_write_tga_with_rle; // defaults to true; set to 0 to disable RLE - int stbi_write_png_compression_level; // defaults to 8; set to higher for more compression - int stbi_write_force_png_filter; // defaults to -1; set to 0..5 to force a filter mode - - - You can define STBI_WRITE_NO_STDIO to disable the file variant of these - functions, so the library will not use stdio.h at all. However, this will - also disable HDR writing, because it requires stdio for formatted output. - - Each function returns 0 on failure and non-0 on success. - - The functions create an image file defined by the parameters. The image - is a rectangle of pixels stored from left-to-right, top-to-bottom. - Each pixel contains 'comp' channels of data stored interleaved with 8-bits - per channel, in the following order: 1=Y, 2=YA, 3=RGB, 4=RGBA. (Y is - monochrome color.) The rectangle is 'w' pixels wide and 'h' pixels tall. - The *data pointer points to the first byte of the top-left-most pixel. - For PNG, "stride_in_bytes" is the distance in bytes from the first byte of - a row of pixels to the first byte of the next row of pixels. - - PNG creates output files with the same number of components as the input. - The BMP format expands Y to RGB in the file format and does not - output alpha. - - PNG supports writing rectangles of data even when the bytes storing rows of - data are not consecutive in memory (e.g. sub-rectangles of a larger image), - by supplying the stride between the beginning of adjacent rows. The other - formats do not. (Thus you cannot write a native-format BMP through the BMP - writer, both because it is in BGR order and because it may have padding - at the end of the line.) - - PNG allows you to set the deflate compression level by setting the global - variable 'stbi_write_png_compression_level' (it defaults to 8). - - HDR expects linear float data. Since the format is always 32-bit rgb(e) - data, alpha (if provided) is discarded, and for monochrome data it is - replicated across all three channels. - - TGA supports RLE or non-RLE compressed data. To use non-RLE-compressed - data, set the global variable 'stbi_write_tga_with_rle' to 0. - - JPEG does ignore alpha channels in input data; quality is between 1 and 100. - Higher quality looks better but results in a bigger image. - JPEG baseline (no JPEG progressive). - -CREDITS: - - - Sean Barrett - PNG/BMP/TGA - Baldur Karlsson - HDR - Jean-Sebastien Guay - TGA monochrome - Tim Kelsey - misc enhancements - Alan Hickman - TGA RLE - Emmanuel Julien - initial file IO callback implementation - Jon Olick - original jo_jpeg.cpp code - Daniel Gibson - integrate JPEG, allow external zlib - Aarni Koskela - allow choosing PNG filter - - bugfixes: - github:Chribba - Guillaume Chereau - github:jry2 - github:romigrou - Sergio Gonzalez - Jonas Karlsson - Filip Wasil - Thatcher Ulrich - github:poppolopoppo - Patrick Boettcher - github:xeekworx - Cap Petschulat - Simon Rodriguez - Ivan Tikhonov - github:ignotion - Adam Schackart - Andrew Kensler - -LICENSE - - See end of file for license information. - -*/ - -#ifndef INCLUDE_STB_IMAGE_WRITE_H -#define INCLUDE_STB_IMAGE_WRITE_H - -#include - -// if STB_IMAGE_WRITE_STATIC causes problems, try defining STBIWDEF to 'inline' or 'static inline' -#ifndef STBIWDEF -#ifdef STB_IMAGE_WRITE_STATIC -#define STBIWDEF static -#else -#ifdef __cplusplus -#define STBIWDEF extern "C" -#else -#define STBIWDEF extern -#endif -#endif -#endif - -#ifndef STB_IMAGE_WRITE_STATIC // C++ forbids static forward declarations -STBIWDEF int stbi_write_tga_with_rle; -STBIWDEF int stbi_write_png_compression_level; -STBIWDEF int stbi_write_force_png_filter; -#endif - -#ifndef STBI_WRITE_NO_STDIO -STBIWDEF int stbi_write_png(char const *filename, int w, int h, int comp, const void *data, int stride_in_bytes); -STBIWDEF int stbi_write_bmp(char const *filename, int w, int h, int comp, const void *data); -STBIWDEF int stbi_write_tga(char const *filename, int w, int h, int comp, const void *data); -STBIWDEF int stbi_write_hdr(char const *filename, int w, int h, int comp, const float *data); -STBIWDEF int stbi_write_jpg(char const *filename, int x, int y, int comp, const void *data, int quality); - -#ifdef STBIW_WINDOWS_UTF8 -STBIWDEF int stbiw_convert_wchar_to_utf8(char *buffer, size_t bufferlen, const wchar_t* input); -#endif -#endif - -typedef void stbi_write_func(void *context, void *data, int size); - -STBIWDEF int stbi_write_png_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void *data, int stride_in_bytes); -STBIWDEF int stbi_write_bmp_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void *data); -STBIWDEF int stbi_write_tga_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const void *data); -STBIWDEF int stbi_write_hdr_to_func(stbi_write_func *func, void *context, int w, int h, int comp, const float *data); -STBIWDEF int stbi_write_jpg_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int quality); - -STBIWDEF void stbi_flip_vertically_on_write(int flip_boolean); - -#endif//INCLUDE_STB_IMAGE_WRITE_H - -#ifdef STB_IMAGE_WRITE_IMPLEMENTATION - -#ifdef _WIN32 - #ifndef _CRT_SECURE_NO_WARNINGS - #define _CRT_SECURE_NO_WARNINGS - #endif - #ifndef _CRT_NONSTDC_NO_DEPRECATE - #define _CRT_NONSTDC_NO_DEPRECATE - #endif -#endif - -#ifndef STBI_WRITE_NO_STDIO -#include -#endif // STBI_WRITE_NO_STDIO - -#include -#include -#include -#include - -#if defined(STBIW_MALLOC) && defined(STBIW_FREE) && (defined(STBIW_REALLOC) || defined(STBIW_REALLOC_SIZED)) -// ok -#elif !defined(STBIW_MALLOC) && !defined(STBIW_FREE) && !defined(STBIW_REALLOC) && !defined(STBIW_REALLOC_SIZED) -// ok -#else -#error "Must define all or none of STBIW_MALLOC, STBIW_FREE, and STBIW_REALLOC (or STBIW_REALLOC_SIZED)." -#endif - -#ifndef STBIW_MALLOC -#define STBIW_MALLOC(sz) malloc(sz) -#define STBIW_REALLOC(p,newsz) realloc(p,newsz) -#define STBIW_FREE(p) free(p) -#endif - -#ifndef STBIW_REALLOC_SIZED -#define STBIW_REALLOC_SIZED(p,oldsz,newsz) STBIW_REALLOC(p,newsz) -#endif - - -#ifndef STBIW_MEMMOVE -#define STBIW_MEMMOVE(a,b,sz) memmove(a,b,sz) -#endif - - -#ifndef STBIW_ASSERT -#include -#define STBIW_ASSERT(x) assert(x) -#endif - -#define STBIW_UCHAR(x) (unsigned char) ((x) & 0xff) - -#ifdef STB_IMAGE_WRITE_STATIC -static int stbi_write_png_compression_level = 8; -static int stbi_write_tga_with_rle = 1; -static int stbi_write_force_png_filter = -1; -#else -int stbi_write_png_compression_level = 8; -int stbi_write_tga_with_rle = 1; -int stbi_write_force_png_filter = -1; -#endif - -static int stbi__flip_vertically_on_write = 0; - -STBIWDEF void stbi_flip_vertically_on_write(int flag) -{ - stbi__flip_vertically_on_write = flag; -} - -typedef struct -{ - stbi_write_func *func; - void *context; - unsigned char buffer[64]; - int buf_used; -} stbi__write_context; - -// initialize a callback-based context -static void stbi__start_write_callbacks(stbi__write_context *s, stbi_write_func *c, void *context) -{ - s->func = c; - s->context = context; -} - -#ifndef STBI_WRITE_NO_STDIO - -static void stbi__stdio_write(void *context, void *data, int size) -{ - fwrite(data,1,size,(FILE*) context); -} - -#if defined(_WIN32) && defined(STBIW_WINDOWS_UTF8) -#ifdef __cplusplus -#define STBIW_EXTERN extern "C" -#else -#define STBIW_EXTERN extern -#endif -STBIW_EXTERN __declspec(dllimport) int __stdcall MultiByteToWideChar(unsigned int cp, unsigned long flags, const char *str, int cbmb, wchar_t *widestr, int cchwide); -STBIW_EXTERN __declspec(dllimport) int __stdcall WideCharToMultiByte(unsigned int cp, unsigned long flags, const wchar_t *widestr, int cchwide, char *str, int cbmb, const char *defchar, int *used_default); - -STBIWDEF int stbiw_convert_wchar_to_utf8(char *buffer, size_t bufferlen, const wchar_t* input) -{ - return WideCharToMultiByte(65001 /* UTF8 */, 0, input, -1, buffer, (int) bufferlen, NULL, NULL); -} -#endif - -static FILE *stbiw__fopen(char const *filename, char const *mode) -{ - FILE *f; -#if defined(_WIN32) && defined(STBIW_WINDOWS_UTF8) - wchar_t wMode[64]; - wchar_t wFilename[1024]; - if (0 == MultiByteToWideChar(65001 /* UTF8 */, 0, filename, -1, wFilename, sizeof(wFilename)/sizeof(*wFilename))) - return 0; - - if (0 == MultiByteToWideChar(65001 /* UTF8 */, 0, mode, -1, wMode, sizeof(wMode)/sizeof(*wMode))) - return 0; - -#if defined(_MSC_VER) && _MSC_VER >= 1400 - if (0 != _wfopen_s(&f, wFilename, wMode)) - f = 0; -#else - f = _wfopen(wFilename, wMode); -#endif - -#elif defined(_MSC_VER) && _MSC_VER >= 1400 - if (0 != fopen_s(&f, filename, mode)) - f=0; -#else - f = fopen(filename, mode); -#endif - return f; -} - -static int stbi__start_write_file(stbi__write_context *s, const char *filename) -{ - FILE *f = stbiw__fopen(filename, "wb"); - stbi__start_write_callbacks(s, stbi__stdio_write, (void *) f); - return f != NULL; -} - -static void stbi__end_write_file(stbi__write_context *s) -{ - fclose((FILE *)s->context); -} - -#endif // !STBI_WRITE_NO_STDIO - -typedef unsigned int stbiw_uint32; -typedef int stb_image_write_test[sizeof(stbiw_uint32)==4 ? 1 : -1]; - -static void stbiw__writefv(stbi__write_context *s, const char *fmt, va_list v) -{ - while (*fmt) { - switch (*fmt++) { - case ' ': break; - case '1': { unsigned char x = STBIW_UCHAR(va_arg(v, int)); - s->func(s->context,&x,1); - break; } - case '2': { int x = va_arg(v,int); - unsigned char b[2]; - b[0] = STBIW_UCHAR(x); - b[1] = STBIW_UCHAR(x>>8); - s->func(s->context,b,2); - break; } - case '4': { stbiw_uint32 x = va_arg(v,int); - unsigned char b[4]; - b[0]=STBIW_UCHAR(x); - b[1]=STBIW_UCHAR(x>>8); - b[2]=STBIW_UCHAR(x>>16); - b[3]=STBIW_UCHAR(x>>24); - s->func(s->context,b,4); - break; } - default: - STBIW_ASSERT(0); - return; - } - } -} - -static void stbiw__writef(stbi__write_context *s, const char *fmt, ...) -{ - va_list v; - va_start(v, fmt); - stbiw__writefv(s, fmt, v); - va_end(v); -} - -static void stbiw__write_flush(stbi__write_context *s) -{ - if (s->buf_used) { - s->func(s->context, &s->buffer, s->buf_used); - s->buf_used = 0; - } -} - -static void stbiw__putc(stbi__write_context *s, unsigned char c) -{ - s->func(s->context, &c, 1); -} - -static void stbiw__write1(stbi__write_context *s, unsigned char a) -{ - if ((size_t)s->buf_used + 1 > sizeof(s->buffer)) - stbiw__write_flush(s); - s->buffer[s->buf_used++] = a; -} - -static void stbiw__write3(stbi__write_context *s, unsigned char a, unsigned char b, unsigned char c) -{ - int n; - if ((size_t)s->buf_used + 3 > sizeof(s->buffer)) - stbiw__write_flush(s); - n = s->buf_used; - s->buf_used = n+3; - s->buffer[n+0] = a; - s->buffer[n+1] = b; - s->buffer[n+2] = c; -} - -static void stbiw__write_pixel(stbi__write_context *s, int rgb_dir, int comp, int write_alpha, int expand_mono, unsigned char *d) -{ - unsigned char bg[3] = { 255, 0, 255}, px[3]; - int k; - - if (write_alpha < 0) - stbiw__write1(s, d[comp - 1]); - - switch (comp) { - case 2: // 2 pixels = mono + alpha, alpha is written separately, so same as 1-channel case - case 1: - if (expand_mono) - stbiw__write3(s, d[0], d[0], d[0]); // monochrome bmp - else - stbiw__write1(s, d[0]); // monochrome TGA - break; - case 4: - if (!write_alpha) { - // composite against pink background - for (k = 0; k < 3; ++k) - px[k] = bg[k] + ((d[k] - bg[k]) * d[3]) / 255; - stbiw__write3(s, px[1 - rgb_dir], px[1], px[1 + rgb_dir]); - break; - } - /* FALLTHROUGH */ - case 3: - stbiw__write3(s, d[1 - rgb_dir], d[1], d[1 + rgb_dir]); - break; - } - if (write_alpha > 0) - stbiw__write1(s, d[comp - 1]); -} - -static void stbiw__write_pixels(stbi__write_context *s, int rgb_dir, int vdir, int x, int y, int comp, void *data, int write_alpha, int scanline_pad, int expand_mono) -{ - stbiw_uint32 zero = 0; - int i,j, j_end; - - if (y <= 0) - return; - - if (stbi__flip_vertically_on_write) - vdir *= -1; - - if (vdir < 0) { - j_end = -1; j = y-1; - } else { - j_end = y; j = 0; - } - - for (; j != j_end; j += vdir) { - for (i=0; i < x; ++i) { - unsigned char *d = (unsigned char *) data + (j*x+i)*comp; - stbiw__write_pixel(s, rgb_dir, comp, write_alpha, expand_mono, d); - } - stbiw__write_flush(s); - s->func(s->context, &zero, scanline_pad); - } -} - -static int stbiw__outfile(stbi__write_context *s, int rgb_dir, int vdir, int x, int y, int comp, int expand_mono, void *data, int alpha, int pad, const char *fmt, ...) -{ - if (y < 0 || x < 0) { - return 0; - } else { - va_list v; - va_start(v, fmt); - stbiw__writefv(s, fmt, v); - va_end(v); - stbiw__write_pixels(s,rgb_dir,vdir,x,y,comp,data,alpha,pad, expand_mono); - return 1; - } -} - -static int stbi_write_bmp_core(stbi__write_context *s, int x, int y, int comp, const void *data) -{ - if (comp != 4) { - // write RGB bitmap - int pad = (-x*3) & 3; - return stbiw__outfile(s,-1,-1,x,y,comp,1,(void *) data,0,pad, - "11 4 22 4" "4 44 22 444444", - 'B', 'M', 14+40+(x*3+pad)*y, 0,0, 14+40, // file header - 40, x,y, 1,24, 0,0,0,0,0,0); // bitmap header - } else { - // RGBA bitmaps need a v4 header - // use BI_BITFIELDS mode with 32bpp and alpha mask - // (straight BI_RGB with alpha mask doesn't work in most readers) - return stbiw__outfile(s,-1,-1,x,y,comp,1,(void *)data,1,0, - "11 4 22 4" "4 44 22 444444 4444 4 444 444 444 444", - 'B', 'M', 14+108+x*y*4, 0, 0, 14+108, // file header - 108, x,y, 1,32, 3,0,0,0,0,0, 0xff0000,0xff00,0xff,0xff000000u, 0, 0,0,0, 0,0,0, 0,0,0, 0,0,0); // bitmap V4 header - } -} - -STBIWDEF int stbi_write_bmp_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data) -{ - stbi__write_context s = { 0 }; - stbi__start_write_callbacks(&s, func, context); - return stbi_write_bmp_core(&s, x, y, comp, data); -} - -#ifndef STBI_WRITE_NO_STDIO -STBIWDEF int stbi_write_bmp(char const *filename, int x, int y, int comp, const void *data) -{ - stbi__write_context s = { 0 }; - if (stbi__start_write_file(&s,filename)) { - int r = stbi_write_bmp_core(&s, x, y, comp, data); - stbi__end_write_file(&s); - return r; - } else - return 0; -} -#endif //!STBI_WRITE_NO_STDIO - -static int stbi_write_tga_core(stbi__write_context *s, int x, int y, int comp, void *data) -{ - int has_alpha = (comp == 2 || comp == 4); - int colorbytes = has_alpha ? comp-1 : comp; - int format = colorbytes < 2 ? 3 : 2; // 3 color channels (RGB/RGBA) = 2, 1 color channel (Y/YA) = 3 - - if (y < 0 || x < 0) - return 0; - - if (!stbi_write_tga_with_rle) { - return stbiw__outfile(s, -1, -1, x, y, comp, 0, (void *) data, has_alpha, 0, - "111 221 2222 11", 0, 0, format, 0, 0, 0, 0, 0, x, y, (colorbytes + has_alpha) * 8, has_alpha * 8); - } else { - int i,j,k; - int jend, jdir; - - stbiw__writef(s, "111 221 2222 11", 0,0,format+8, 0,0,0, 0,0,x,y, (colorbytes + has_alpha) * 8, has_alpha * 8); - - if (stbi__flip_vertically_on_write) { - j = 0; - jend = y; - jdir = 1; - } else { - j = y-1; - jend = -1; - jdir = -1; - } - for (; j != jend; j += jdir) { - unsigned char *row = (unsigned char *) data + j * x * comp; - int len; - - for (i = 0; i < x; i += len) { - unsigned char *begin = row + i * comp; - int diff = 1; - len = 1; - - if (i < x - 1) { - ++len; - diff = memcmp(begin, row + (i + 1) * comp, comp); - if (diff) { - const unsigned char *prev = begin; - for (k = i + 2; k < x && len < 128; ++k) { - if (memcmp(prev, row + k * comp, comp)) { - prev += comp; - ++len; - } else { - --len; - break; - } - } - } else { - for (k = i + 2; k < x && len < 128; ++k) { - if (!memcmp(begin, row + k * comp, comp)) { - ++len; - } else { - break; - } - } - } - } - - if (diff) { - unsigned char header = STBIW_UCHAR(len - 1); - stbiw__write1(s, header); - for (k = 0; k < len; ++k) { - stbiw__write_pixel(s, -1, comp, has_alpha, 0, begin + k * comp); - } - } else { - unsigned char header = STBIW_UCHAR(len - 129); - stbiw__write1(s, header); - stbiw__write_pixel(s, -1, comp, has_alpha, 0, begin); - } - } - } - stbiw__write_flush(s); - } - return 1; -} - -STBIWDEF int stbi_write_tga_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data) -{ - stbi__write_context s = { 0 }; - stbi__start_write_callbacks(&s, func, context); - return stbi_write_tga_core(&s, x, y, comp, (void *) data); -} - -#ifndef STBI_WRITE_NO_STDIO -STBIWDEF int stbi_write_tga(char const *filename, int x, int y, int comp, const void *data) -{ - stbi__write_context s = { 0 }; - if (stbi__start_write_file(&s,filename)) { - int r = stbi_write_tga_core(&s, x, y, comp, (void *) data); - stbi__end_write_file(&s); - return r; - } else - return 0; -} -#endif - -// ************************************************************************************************* -// Radiance RGBE HDR writer -// by Baldur Karlsson - -#define stbiw__max(a, b) ((a) > (b) ? (a) : (b)) - -#ifndef STBI_WRITE_NO_STDIO - -static void stbiw__linear_to_rgbe(unsigned char *rgbe, float *linear) -{ - int exponent; - float maxcomp = stbiw__max(linear[0], stbiw__max(linear[1], linear[2])); - - if (maxcomp < 1e-32f) { - rgbe[0] = rgbe[1] = rgbe[2] = rgbe[3] = 0; - } else { - float normalize = (float) frexp(maxcomp, &exponent) * 256.0f/maxcomp; - - rgbe[0] = (unsigned char)(linear[0] * normalize); - rgbe[1] = (unsigned char)(linear[1] * normalize); - rgbe[2] = (unsigned char)(linear[2] * normalize); - rgbe[3] = (unsigned char)(exponent + 128); - } -} - -static void stbiw__write_run_data(stbi__write_context *s, int length, unsigned char databyte) -{ - unsigned char lengthbyte = STBIW_UCHAR(length+128); - STBIW_ASSERT(length+128 <= 255); - s->func(s->context, &lengthbyte, 1); - s->func(s->context, &databyte, 1); -} - -static void stbiw__write_dump_data(stbi__write_context *s, int length, unsigned char *data) -{ - unsigned char lengthbyte = STBIW_UCHAR(length); - STBIW_ASSERT(length <= 128); // inconsistent with spec but consistent with official code - s->func(s->context, &lengthbyte, 1); - s->func(s->context, data, length); -} - -static void stbiw__write_hdr_scanline(stbi__write_context *s, int width, int ncomp, unsigned char *scratch, float *scanline) -{ - unsigned char scanlineheader[4] = { 2, 2, 0, 0 }; - unsigned char rgbe[4]; - float linear[3]; - int x; - - scanlineheader[2] = (width&0xff00)>>8; - scanlineheader[3] = (width&0x00ff); - - /* skip RLE for images too small or large */ - if (width < 8 || width >= 32768) { - for (x=0; x < width; x++) { - switch (ncomp) { - case 4: /* fallthrough */ - case 3: linear[2] = scanline[x*ncomp + 2]; - linear[1] = scanline[x*ncomp + 1]; - linear[0] = scanline[x*ncomp + 0]; - break; - default: - linear[0] = linear[1] = linear[2] = scanline[x*ncomp + 0]; - break; - } - stbiw__linear_to_rgbe(rgbe, linear); - s->func(s->context, rgbe, 4); - } - } else { - int c,r; - /* encode into scratch buffer */ - for (x=0; x < width; x++) { - switch(ncomp) { - case 4: /* fallthrough */ - case 3: linear[2] = scanline[x*ncomp + 2]; - linear[1] = scanline[x*ncomp + 1]; - linear[0] = scanline[x*ncomp + 0]; - break; - default: - linear[0] = linear[1] = linear[2] = scanline[x*ncomp + 0]; - break; - } - stbiw__linear_to_rgbe(rgbe, linear); - scratch[x + width*0] = rgbe[0]; - scratch[x + width*1] = rgbe[1]; - scratch[x + width*2] = rgbe[2]; - scratch[x + width*3] = rgbe[3]; - } - - s->func(s->context, scanlineheader, 4); - - /* RLE each component separately */ - for (c=0; c < 4; c++) { - unsigned char *comp = &scratch[width*c]; - - x = 0; - while (x < width) { - // find first run - r = x; - while (r+2 < width) { - if (comp[r] == comp[r+1] && comp[r] == comp[r+2]) - break; - ++r; - } - if (r+2 >= width) - r = width; - // dump up to first run - while (x < r) { - int len = r-x; - if (len > 128) len = 128; - stbiw__write_dump_data(s, len, &comp[x]); - x += len; - } - // if there's a run, output it - if (r+2 < width) { // same test as what we break out of in search loop, so only true if we break'd - // find next byte after run - while (r < width && comp[r] == comp[x]) - ++r; - // output run up to r - while (x < r) { - int len = r-x; - if (len > 127) len = 127; - stbiw__write_run_data(s, len, comp[x]); - x += len; - } - } - } - } - } -} - -static int stbi_write_hdr_core(stbi__write_context *s, int x, int y, int comp, float *data) -{ - if (y <= 0 || x <= 0 || data == NULL) - return 0; - else { - // Each component is stored separately. Allocate scratch space for full output scanline. - unsigned char *scratch = (unsigned char *) STBIW_MALLOC(x*4); - int i, len; - char buffer[128]; - char header[] = "#?RADIANCE\n# Written by stb_image_write.h\nFORMAT=32-bit_rle_rgbe\n"; - s->func(s->context, header, sizeof(header)-1); - -#ifdef __STDC_LIB_EXT1__ - len = sprintf_s(buffer, sizeof(buffer), "EXPOSURE= 1.0000000000000\n\n-Y %d +X %d\n", y, x); -#else - len = sprintf(buffer, "EXPOSURE= 1.0000000000000\n\n-Y %d +X %d\n", y, x); -#endif - s->func(s->context, buffer, len); - - for(i=0; i < y; i++) - stbiw__write_hdr_scanline(s, x, comp, scratch, data + comp*x*(stbi__flip_vertically_on_write ? y-1-i : i)); - STBIW_FREE(scratch); - return 1; - } -} - -STBIWDEF int stbi_write_hdr_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const float *data) -{ - stbi__write_context s = { 0 }; - stbi__start_write_callbacks(&s, func, context); - return stbi_write_hdr_core(&s, x, y, comp, (float *) data); -} - -STBIWDEF int stbi_write_hdr(char const *filename, int x, int y, int comp, const float *data) -{ - stbi__write_context s = { 0 }; - if (stbi__start_write_file(&s,filename)) { - int r = stbi_write_hdr_core(&s, x, y, comp, (float *) data); - stbi__end_write_file(&s); - return r; - } else - return 0; -} -#endif // STBI_WRITE_NO_STDIO - - -////////////////////////////////////////////////////////////////////////////// -// -// PNG writer -// - -#ifndef STBIW_ZLIB_COMPRESS -// stretchy buffer; stbiw__sbpush() == vector<>::push_back() -- stbiw__sbcount() == vector<>::size() -#define stbiw__sbraw(a) ((int *) (void *) (a) - 2) -#define stbiw__sbm(a) stbiw__sbraw(a)[0] -#define stbiw__sbn(a) stbiw__sbraw(a)[1] - -#define stbiw__sbneedgrow(a,n) ((a)==0 || stbiw__sbn(a)+n >= stbiw__sbm(a)) -#define stbiw__sbmaybegrow(a,n) (stbiw__sbneedgrow(a,(n)) ? stbiw__sbgrow(a,n) : 0) -#define stbiw__sbgrow(a,n) stbiw__sbgrowf((void **) &(a), (n), sizeof(*(a))) - -#define stbiw__sbpush(a, v) (stbiw__sbmaybegrow(a,1), (a)[stbiw__sbn(a)++] = (v)) -#define stbiw__sbcount(a) ((a) ? stbiw__sbn(a) : 0) -#define stbiw__sbfree(a) ((a) ? STBIW_FREE(stbiw__sbraw(a)),0 : 0) - -static void *stbiw__sbgrowf(void **arr, int increment, int itemsize) -{ - int m = *arr ? 2*stbiw__sbm(*arr)+increment : increment+1; - void *p = STBIW_REALLOC_SIZED(*arr ? stbiw__sbraw(*arr) : 0, *arr ? (stbiw__sbm(*arr)*itemsize + sizeof(int)*2) : 0, itemsize * m + sizeof(int)*2); - STBIW_ASSERT(p); - if (p) { - if (!*arr) ((int *) p)[1] = 0; - *arr = (void *) ((int *) p + 2); - stbiw__sbm(*arr) = m; - } - return *arr; -} - -static unsigned char *stbiw__zlib_flushf(unsigned char *data, unsigned int *bitbuffer, int *bitcount) -{ - while (*bitcount >= 8) { - stbiw__sbpush(data, STBIW_UCHAR(*bitbuffer)); - *bitbuffer >>= 8; - *bitcount -= 8; - } - return data; -} - -static int stbiw__zlib_bitrev(int code, int codebits) -{ - int res=0; - while (codebits--) { - res = (res << 1) | (code & 1); - code >>= 1; - } - return res; -} - -static unsigned int stbiw__zlib_countm(unsigned char *a, unsigned char *b, int limit) -{ - int i; - for (i=0; i < limit && i < 258; ++i) - if (a[i] != b[i]) break; - return i; -} - -static unsigned int stbiw__zhash(unsigned char *data) -{ - stbiw_uint32 hash = data[0] + (data[1] << 8) + (data[2] << 16); - hash ^= hash << 3; - hash += hash >> 5; - hash ^= hash << 4; - hash += hash >> 17; - hash ^= hash << 25; - hash += hash >> 6; - return hash; -} - -#define stbiw__zlib_flush() (out = stbiw__zlib_flushf(out, &bitbuf, &bitcount)) -#define stbiw__zlib_add(code,codebits) \ - (bitbuf |= (code) << bitcount, bitcount += (codebits), stbiw__zlib_flush()) -#define stbiw__zlib_huffa(b,c) stbiw__zlib_add(stbiw__zlib_bitrev(b,c),c) -// default huffman tables -#define stbiw__zlib_huff1(n) stbiw__zlib_huffa(0x30 + (n), 8) -#define stbiw__zlib_huff2(n) stbiw__zlib_huffa(0x190 + (n)-144, 9) -#define stbiw__zlib_huff3(n) stbiw__zlib_huffa(0 + (n)-256,7) -#define stbiw__zlib_huff4(n) stbiw__zlib_huffa(0xc0 + (n)-280,8) -#define stbiw__zlib_huff(n) ((n) <= 143 ? stbiw__zlib_huff1(n) : (n) <= 255 ? stbiw__zlib_huff2(n) : (n) <= 279 ? stbiw__zlib_huff3(n) : stbiw__zlib_huff4(n)) -#define stbiw__zlib_huffb(n) ((n) <= 143 ? stbiw__zlib_huff1(n) : stbiw__zlib_huff2(n)) - -#define stbiw__ZHASH 16384 - -#endif // STBIW_ZLIB_COMPRESS - -STBIWDEF unsigned char * stbi_zlib_compress(unsigned char *data, int data_len, int *out_len, int quality) -{ -#ifdef STBIW_ZLIB_COMPRESS - // user provided a zlib compress implementation, use that - return STBIW_ZLIB_COMPRESS(data, data_len, out_len, quality); -#else // use builtin - static unsigned short lengthc[] = { 3,4,5,6,7,8,9,10,11,13,15,17,19,23,27,31,35,43,51,59,67,83,99,115,131,163,195,227,258, 259 }; - static unsigned char lengtheb[]= { 0,0,0,0,0,0,0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 0 }; - static unsigned short distc[] = { 1,2,3,4,5,7,9,13,17,25,33,49,65,97,129,193,257,385,513,769,1025,1537,2049,3073,4097,6145,8193,12289,16385,24577, 32768 }; - static unsigned char disteb[] = { 0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13 }; - unsigned int bitbuf=0; - int i,j, bitcount=0; - unsigned char *out = NULL; - unsigned char ***hash_table = (unsigned char***) STBIW_MALLOC(stbiw__ZHASH * sizeof(unsigned char**)); - if (hash_table == NULL) - return NULL; - if (quality < 5) quality = 5; - - stbiw__sbpush(out, 0x78); // DEFLATE 32K window - stbiw__sbpush(out, 0x5e); // FLEVEL = 1 - stbiw__zlib_add(1,1); // BFINAL = 1 - stbiw__zlib_add(1,2); // BTYPE = 1 -- fixed huffman - - for (i=0; i < stbiw__ZHASH; ++i) - hash_table[i] = NULL; - - i=0; - while (i < data_len-3) { - // hash next 3 bytes of data to be compressed - int h = stbiw__zhash(data+i)&(stbiw__ZHASH-1), best=3; - unsigned char *bestloc = 0; - unsigned char **hlist = hash_table[h]; - int n = stbiw__sbcount(hlist); - for (j=0; j < n; ++j) { - if (hlist[j]-data > i-32768) { // if entry lies within window - int d = stbiw__zlib_countm(hlist[j], data+i, data_len-i); - if (d >= best) { best=d; bestloc=hlist[j]; } - } - } - // when hash table entry is too long, delete half the entries - if (hash_table[h] && stbiw__sbn(hash_table[h]) == 2*quality) { - STBIW_MEMMOVE(hash_table[h], hash_table[h]+quality, sizeof(hash_table[h][0])*quality); - stbiw__sbn(hash_table[h]) = quality; - } - stbiw__sbpush(hash_table[h],data+i); - - if (bestloc) { - // "lazy matching" - check match at *next* byte, and if it's better, do cur byte as literal - h = stbiw__zhash(data+i+1)&(stbiw__ZHASH-1); - hlist = hash_table[h]; - n = stbiw__sbcount(hlist); - for (j=0; j < n; ++j) { - if (hlist[j]-data > i-32767) { - int e = stbiw__zlib_countm(hlist[j], data+i+1, data_len-i-1); - if (e > best) { // if next match is better, bail on current match - bestloc = NULL; - break; - } - } - } - } - - if (bestloc) { - int d = (int) (data+i - bestloc); // distance back - STBIW_ASSERT(d <= 32767 && best <= 258); - for (j=0; best > lengthc[j+1]-1; ++j); - stbiw__zlib_huff(j+257); - if (lengtheb[j]) stbiw__zlib_add(best - lengthc[j], lengtheb[j]); - for (j=0; d > distc[j+1]-1; ++j); - stbiw__zlib_add(stbiw__zlib_bitrev(j,5),5); - if (disteb[j]) stbiw__zlib_add(d - distc[j], disteb[j]); - i += best; - } else { - stbiw__zlib_huffb(data[i]); - ++i; - } - } - // write out final bytes - for (;i < data_len; ++i) - stbiw__zlib_huffb(data[i]); - stbiw__zlib_huff(256); // end of block - // pad with 0 bits to byte boundary - while (bitcount) - stbiw__zlib_add(0,1); - - for (i=0; i < stbiw__ZHASH; ++i) - (void) stbiw__sbfree(hash_table[i]); - STBIW_FREE(hash_table); - - // store uncompressed instead if compression was worse - if (stbiw__sbn(out) > data_len + 2 + ((data_len+32766)/32767)*5) { - stbiw__sbn(out) = 2; // truncate to DEFLATE 32K window and FLEVEL = 1 - for (j = 0; j < data_len;) { - int blocklen = data_len - j; - if (blocklen > 32767) blocklen = 32767; - stbiw__sbpush(out, data_len - j == blocklen); // BFINAL = ?, BTYPE = 0 -- no compression - stbiw__sbpush(out, STBIW_UCHAR(blocklen)); // LEN - stbiw__sbpush(out, STBIW_UCHAR(blocklen >> 8)); - stbiw__sbpush(out, STBIW_UCHAR(~blocklen)); // NLEN - stbiw__sbpush(out, STBIW_UCHAR(~blocklen >> 8)); - memcpy(out+stbiw__sbn(out), data+j, blocklen); - stbiw__sbn(out) += blocklen; - j += blocklen; - } - } - - { - // compute adler32 on input - unsigned int s1=1, s2=0; - int blocklen = (int) (data_len % 5552); - j=0; - while (j < data_len) { - for (i=0; i < blocklen; ++i) { s1 += data[j+i]; s2 += s1; } - s1 %= 65521; s2 %= 65521; - j += blocklen; - blocklen = 5552; - } - stbiw__sbpush(out, STBIW_UCHAR(s2 >> 8)); - stbiw__sbpush(out, STBIW_UCHAR(s2)); - stbiw__sbpush(out, STBIW_UCHAR(s1 >> 8)); - stbiw__sbpush(out, STBIW_UCHAR(s1)); - } - *out_len = stbiw__sbn(out); - // make returned pointer freeable - STBIW_MEMMOVE(stbiw__sbraw(out), out, *out_len); - return (unsigned char *) stbiw__sbraw(out); -#endif // STBIW_ZLIB_COMPRESS -} - -static unsigned int stbiw__crc32(unsigned char *buffer, int len) -{ -#ifdef STBIW_CRC32 - return STBIW_CRC32(buffer, len); -#else - static unsigned int crc_table[256] = - { - 0x00000000, 0x77073096, 0xEE0E612C, 0x990951BA, 0x076DC419, 0x706AF48F, 0xE963A535, 0x9E6495A3, - 0x0eDB8832, 0x79DCB8A4, 0xE0D5E91E, 0x97D2D988, 0x09B64C2B, 0x7EB17CBD, 0xE7B82D07, 0x90BF1D91, - 0x1DB71064, 0x6AB020F2, 0xF3B97148, 0x84BE41DE, 0x1ADAD47D, 0x6DDDE4EB, 0xF4D4B551, 0x83D385C7, - 0x136C9856, 0x646BA8C0, 0xFD62F97A, 0x8A65C9EC, 0x14015C4F, 0x63066CD9, 0xFA0F3D63, 0x8D080DF5, - 0x3B6E20C8, 0x4C69105E, 0xD56041E4, 0xA2677172, 0x3C03E4D1, 0x4B04D447, 0xD20D85FD, 0xA50AB56B, - 0x35B5A8FA, 0x42B2986C, 0xDBBBC9D6, 0xACBCF940, 0x32D86CE3, 0x45DF5C75, 0xDCD60DCF, 0xABD13D59, - 0x26D930AC, 0x51DE003A, 0xC8D75180, 0xBFD06116, 0x21B4F4B5, 0x56B3C423, 0xCFBA9599, 0xB8BDA50F, - 0x2802B89E, 0x5F058808, 0xC60CD9B2, 0xB10BE924, 0x2F6F7C87, 0x58684C11, 0xC1611DAB, 0xB6662D3D, - 0x76DC4190, 0x01DB7106, 0x98D220BC, 0xEFD5102A, 0x71B18589, 0x06B6B51F, 0x9FBFE4A5, 0xE8B8D433, - 0x7807C9A2, 0x0F00F934, 0x9609A88E, 0xE10E9818, 0x7F6A0DBB, 0x086D3D2D, 0x91646C97, 0xE6635C01, - 0x6B6B51F4, 0x1C6C6162, 0x856530D8, 0xF262004E, 0x6C0695ED, 0x1B01A57B, 0x8208F4C1, 0xF50FC457, - 0x65B0D9C6, 0x12B7E950, 0x8BBEB8EA, 0xFCB9887C, 0x62DD1DDF, 0x15DA2D49, 0x8CD37CF3, 0xFBD44C65, - 0x4DB26158, 0x3AB551CE, 0xA3BC0074, 0xD4BB30E2, 0x4ADFA541, 0x3DD895D7, 0xA4D1C46D, 0xD3D6F4FB, - 0x4369E96A, 0x346ED9FC, 0xAD678846, 0xDA60B8D0, 0x44042D73, 0x33031DE5, 0xAA0A4C5F, 0xDD0D7CC9, - 0x5005713C, 0x270241AA, 0xBE0B1010, 0xC90C2086, 0x5768B525, 0x206F85B3, 0xB966D409, 0xCE61E49F, - 0x5EDEF90E, 0x29D9C998, 0xB0D09822, 0xC7D7A8B4, 0x59B33D17, 0x2EB40D81, 0xB7BD5C3B, 0xC0BA6CAD, - 0xEDB88320, 0x9ABFB3B6, 0x03B6E20C, 0x74B1D29A, 0xEAD54739, 0x9DD277AF, 0x04DB2615, 0x73DC1683, - 0xE3630B12, 0x94643B84, 0x0D6D6A3E, 0x7A6A5AA8, 0xE40ECF0B, 0x9309FF9D, 0x0A00AE27, 0x7D079EB1, - 0xF00F9344, 0x8708A3D2, 0x1E01F268, 0x6906C2FE, 0xF762575D, 0x806567CB, 0x196C3671, 0x6E6B06E7, - 0xFED41B76, 0x89D32BE0, 0x10DA7A5A, 0x67DD4ACC, 0xF9B9DF6F, 0x8EBEEFF9, 0x17B7BE43, 0x60B08ED5, - 0xD6D6A3E8, 0xA1D1937E, 0x38D8C2C4, 0x4FDFF252, 0xD1BB67F1, 0xA6BC5767, 0x3FB506DD, 0x48B2364B, - 0xD80D2BDA, 0xAF0A1B4C, 0x36034AF6, 0x41047A60, 0xDF60EFC3, 0xA867DF55, 0x316E8EEF, 0x4669BE79, - 0xCB61B38C, 0xBC66831A, 0x256FD2A0, 0x5268E236, 0xCC0C7795, 0xBB0B4703, 0x220216B9, 0x5505262F, - 0xC5BA3BBE, 0xB2BD0B28, 0x2BB45A92, 0x5CB36A04, 0xC2D7FFA7, 0xB5D0CF31, 0x2CD99E8B, 0x5BDEAE1D, - 0x9B64C2B0, 0xEC63F226, 0x756AA39C, 0x026D930A, 0x9C0906A9, 0xEB0E363F, 0x72076785, 0x05005713, - 0x95BF4A82, 0xE2B87A14, 0x7BB12BAE, 0x0CB61B38, 0x92D28E9B, 0xE5D5BE0D, 0x7CDCEFB7, 0x0BDBDF21, - 0x86D3D2D4, 0xF1D4E242, 0x68DDB3F8, 0x1FDA836E, 0x81BE16CD, 0xF6B9265B, 0x6FB077E1, 0x18B74777, - 0x88085AE6, 0xFF0F6A70, 0x66063BCA, 0x11010B5C, 0x8F659EFF, 0xF862AE69, 0x616BFFD3, 0x166CCF45, - 0xA00AE278, 0xD70DD2EE, 0x4E048354, 0x3903B3C2, 0xA7672661, 0xD06016F7, 0x4969474D, 0x3E6E77DB, - 0xAED16A4A, 0xD9D65ADC, 0x40DF0B66, 0x37D83BF0, 0xA9BCAE53, 0xDEBB9EC5, 0x47B2CF7F, 0x30B5FFE9, - 0xBDBDF21C, 0xCABAC28A, 0x53B39330, 0x24B4A3A6, 0xBAD03605, 0xCDD70693, 0x54DE5729, 0x23D967BF, - 0xB3667A2E, 0xC4614AB8, 0x5D681B02, 0x2A6F2B94, 0xB40BBE37, 0xC30C8EA1, 0x5A05DF1B, 0x2D02EF8D - }; - - unsigned int crc = ~0u; - int i; - for (i=0; i < len; ++i) - crc = (crc >> 8) ^ crc_table[buffer[i] ^ (crc & 0xff)]; - return ~crc; -#endif -} - -#define stbiw__wpng4(o,a,b,c,d) ((o)[0]=STBIW_UCHAR(a),(o)[1]=STBIW_UCHAR(b),(o)[2]=STBIW_UCHAR(c),(o)[3]=STBIW_UCHAR(d),(o)+=4) -#define stbiw__wp32(data,v) stbiw__wpng4(data, (v)>>24,(v)>>16,(v)>>8,(v)); -#define stbiw__wptag(data,s) stbiw__wpng4(data, s[0],s[1],s[2],s[3]) - -static void stbiw__wpcrc(unsigned char **data, int len) -{ - unsigned int crc = stbiw__crc32(*data - len - 4, len+4); - stbiw__wp32(*data, crc); -} - -static unsigned char stbiw__paeth(int a, int b, int c) -{ - int p = a + b - c, pa = abs(p-a), pb = abs(p-b), pc = abs(p-c); - if (pa <= pb && pa <= pc) return STBIW_UCHAR(a); - if (pb <= pc) return STBIW_UCHAR(b); - return STBIW_UCHAR(c); -} - -// @OPTIMIZE: provide an option that always forces left-predict or paeth predict -static void stbiw__encode_png_line(unsigned char *pixels, int stride_bytes, int width, int height, int y, int n, int filter_type, signed char *line_buffer) -{ - static int mapping[] = { 0,1,2,3,4 }; - static int firstmap[] = { 0,1,0,5,6 }; - int *mymap = (y != 0) ? mapping : firstmap; - int i; - int type = mymap[filter_type]; - unsigned char *z = pixels + stride_bytes * (stbi__flip_vertically_on_write ? height-1-y : y); - int signed_stride = stbi__flip_vertically_on_write ? -stride_bytes : stride_bytes; - - if (type==0) { - memcpy(line_buffer, z, width*n); - return; - } - - // first loop isn't optimized since it's just one pixel - for (i = 0; i < n; ++i) { - switch (type) { - case 1: line_buffer[i] = z[i]; break; - case 2: line_buffer[i] = z[i] - z[i-signed_stride]; break; - case 3: line_buffer[i] = z[i] - (z[i-signed_stride]>>1); break; - case 4: line_buffer[i] = (signed char) (z[i] - stbiw__paeth(0,z[i-signed_stride],0)); break; - case 5: line_buffer[i] = z[i]; break; - case 6: line_buffer[i] = z[i]; break; - } - } - switch (type) { - case 1: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - z[i-n]; break; - case 2: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - z[i-signed_stride]; break; - case 3: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - ((z[i-n] + z[i-signed_stride])>>1); break; - case 4: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - stbiw__paeth(z[i-n], z[i-signed_stride], z[i-signed_stride-n]); break; - case 5: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - (z[i-n]>>1); break; - case 6: for (i=n; i < width*n; ++i) line_buffer[i] = z[i] - stbiw__paeth(z[i-n], 0,0); break; - } -} - -STBIWDEF unsigned char *stbi_write_png_to_mem(const unsigned char *pixels, int stride_bytes, int x, int y, int n, int *out_len) -{ - int force_filter = stbi_write_force_png_filter; - int ctype[5] = { -1, 0, 4, 2, 6 }; - unsigned char sig[8] = { 137,80,78,71,13,10,26,10 }; - unsigned char *out,*o, *filt, *zlib; - signed char *line_buffer; - int j,zlen; - - if (stride_bytes == 0) - stride_bytes = x * n; - - if (force_filter >= 5) { - force_filter = -1; - } - - filt = (unsigned char *) STBIW_MALLOC((x*n+1) * y); if (!filt) return 0; - line_buffer = (signed char *) STBIW_MALLOC(x * n); if (!line_buffer) { STBIW_FREE(filt); return 0; } - for (j=0; j < y; ++j) { - int filter_type; - if (force_filter > -1) { - filter_type = force_filter; - stbiw__encode_png_line((unsigned char*)(pixels), stride_bytes, x, y, j, n, force_filter, line_buffer); - } else { // Estimate the best filter by running through all of them: - int best_filter = 0, best_filter_val = 0x7fffffff, est, i; - for (filter_type = 0; filter_type < 5; filter_type++) { - stbiw__encode_png_line((unsigned char*)(pixels), stride_bytes, x, y, j, n, filter_type, line_buffer); - - // Estimate the entropy of the line using this filter; the less, the better. - est = 0; - for (i = 0; i < x*n; ++i) { - est += abs((signed char) line_buffer[i]); - } - if (est < best_filter_val) { - best_filter_val = est; - best_filter = filter_type; - } - } - if (filter_type != best_filter) { // If the last iteration already got us the best filter, don't redo it - stbiw__encode_png_line((unsigned char*)(pixels), stride_bytes, x, y, j, n, best_filter, line_buffer); - filter_type = best_filter; - } - } - // when we get here, filter_type contains the filter type, and line_buffer contains the data - filt[j*(x*n+1)] = (unsigned char) filter_type; - STBIW_MEMMOVE(filt+j*(x*n+1)+1, line_buffer, x*n); - } - STBIW_FREE(line_buffer); - zlib = stbi_zlib_compress(filt, y*( x*n+1), &zlen, stbi_write_png_compression_level); - STBIW_FREE(filt); - if (!zlib) return 0; - - // each tag requires 12 bytes of overhead - out = (unsigned char *) STBIW_MALLOC(8 + 12+13 + 12+zlen + 12); - if (!out) return 0; - *out_len = 8 + 12+13 + 12+zlen + 12; - - o=out; - STBIW_MEMMOVE(o,sig,8); o+= 8; - stbiw__wp32(o, 13); // header length - stbiw__wptag(o, "IHDR"); - stbiw__wp32(o, x); - stbiw__wp32(o, y); - *o++ = 8; - *o++ = STBIW_UCHAR(ctype[n]); - *o++ = 0; - *o++ = 0; - *o++ = 0; - stbiw__wpcrc(&o,13); - - stbiw__wp32(o, zlen); - stbiw__wptag(o, "IDAT"); - STBIW_MEMMOVE(o, zlib, zlen); - o += zlen; - STBIW_FREE(zlib); - stbiw__wpcrc(&o, zlen); - - stbiw__wp32(o,0); - stbiw__wptag(o, "IEND"); - stbiw__wpcrc(&o,0); - - STBIW_ASSERT(o == out + *out_len); - - return out; -} - -#ifndef STBI_WRITE_NO_STDIO -STBIWDEF int stbi_write_png(char const *filename, int x, int y, int comp, const void *data, int stride_bytes) -{ - FILE *f; - int len; - unsigned char *png = stbi_write_png_to_mem((const unsigned char *) data, stride_bytes, x, y, comp, &len); - if (png == NULL) return 0; - - f = stbiw__fopen(filename, "wb"); - if (!f) { STBIW_FREE(png); return 0; } - fwrite(png, 1, len, f); - fclose(f); - STBIW_FREE(png); - return 1; -} -#endif - -STBIWDEF int stbi_write_png_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int stride_bytes) -{ - int len; - unsigned char *png = stbi_write_png_to_mem((const unsigned char *) data, stride_bytes, x, y, comp, &len); - if (png == NULL) return 0; - func(context, png, len); - STBIW_FREE(png); - return 1; -} - - -/* *************************************************************************** - * - * JPEG writer - * - * This is based on Jon Olick's jo_jpeg.cpp: - * public domain Simple, Minimalistic JPEG writer - http://www.jonolick.com/code.html - */ - -static const unsigned char stbiw__jpg_ZigZag[] = { 0,1,5,6,14,15,27,28,2,4,7,13,16,26,29,42,3,8,12,17,25,30,41,43,9,11,18, - 24,31,40,44,53,10,19,23,32,39,45,52,54,20,22,33,38,46,51,55,60,21,34,37,47,50,56,59,61,35,36,48,49,57,58,62,63 }; - -static void stbiw__jpg_writeBits(stbi__write_context *s, int *bitBufP, int *bitCntP, const unsigned short *bs) { - int bitBuf = *bitBufP, bitCnt = *bitCntP; - bitCnt += bs[1]; - bitBuf |= bs[0] << (24 - bitCnt); - while(bitCnt >= 8) { - unsigned char c = (bitBuf >> 16) & 255; - stbiw__putc(s, c); - if(c == 255) { - stbiw__putc(s, 0); - } - bitBuf <<= 8; - bitCnt -= 8; - } - *bitBufP = bitBuf; - *bitCntP = bitCnt; -} - -static void stbiw__jpg_DCT(float *d0p, float *d1p, float *d2p, float *d3p, float *d4p, float *d5p, float *d6p, float *d7p) { - float d0 = *d0p, d1 = *d1p, d2 = *d2p, d3 = *d3p, d4 = *d4p, d5 = *d5p, d6 = *d6p, d7 = *d7p; - float z1, z2, z3, z4, z5, z11, z13; - - float tmp0 = d0 + d7; - float tmp7 = d0 - d7; - float tmp1 = d1 + d6; - float tmp6 = d1 - d6; - float tmp2 = d2 + d5; - float tmp5 = d2 - d5; - float tmp3 = d3 + d4; - float tmp4 = d3 - d4; - - // Even part - float tmp10 = tmp0 + tmp3; // phase 2 - float tmp13 = tmp0 - tmp3; - float tmp11 = tmp1 + tmp2; - float tmp12 = tmp1 - tmp2; - - d0 = tmp10 + tmp11; // phase 3 - d4 = tmp10 - tmp11; - - z1 = (tmp12 + tmp13) * 0.707106781f; // c4 - d2 = tmp13 + z1; // phase 5 - d6 = tmp13 - z1; - - // Odd part - tmp10 = tmp4 + tmp5; // phase 2 - tmp11 = tmp5 + tmp6; - tmp12 = tmp6 + tmp7; - - // The rotator is modified from fig 4-8 to avoid extra negations. - z5 = (tmp10 - tmp12) * 0.382683433f; // c6 - z2 = tmp10 * 0.541196100f + z5; // c2-c6 - z4 = tmp12 * 1.306562965f + z5; // c2+c6 - z3 = tmp11 * 0.707106781f; // c4 - - z11 = tmp7 + z3; // phase 5 - z13 = tmp7 - z3; - - *d5p = z13 + z2; // phase 6 - *d3p = z13 - z2; - *d1p = z11 + z4; - *d7p = z11 - z4; - - *d0p = d0; *d2p = d2; *d4p = d4; *d6p = d6; -} - -static void stbiw__jpg_calcBits(int val, unsigned short bits[2]) { - int tmp1 = val < 0 ? -val : val; - val = val < 0 ? val-1 : val; - bits[1] = 1; - while(tmp1 >>= 1) { - ++bits[1]; - } - bits[0] = val & ((1<0)&&(DU[end0pos]==0); --end0pos) { - } - // end0pos = first element in reverse order !=0 - if(end0pos == 0) { - stbiw__jpg_writeBits(s, bitBuf, bitCnt, EOB); - return DU[0]; - } - for(i = 1; i <= end0pos; ++i) { - int startpos = i; - int nrzeroes; - unsigned short bits[2]; - for (; DU[i]==0 && i<=end0pos; ++i) { - } - nrzeroes = i-startpos; - if ( nrzeroes >= 16 ) { - int lng = nrzeroes>>4; - int nrmarker; - for (nrmarker=1; nrmarker <= lng; ++nrmarker) - stbiw__jpg_writeBits(s, bitBuf, bitCnt, M16zeroes); - nrzeroes &= 15; - } - stbiw__jpg_calcBits(DU[i], bits); - stbiw__jpg_writeBits(s, bitBuf, bitCnt, HTAC[(nrzeroes<<4)+bits[1]]); - stbiw__jpg_writeBits(s, bitBuf, bitCnt, bits); - } - if(end0pos != 63) { - stbiw__jpg_writeBits(s, bitBuf, bitCnt, EOB); - } - return DU[0]; -} - -static int stbi_write_jpg_core(stbi__write_context *s, int width, int height, int comp, const void* data, int quality) { - // Constants that don't pollute global namespace - static const unsigned char std_dc_luminance_nrcodes[] = {0,0,1,5,1,1,1,1,1,1,0,0,0,0,0,0,0}; - static const unsigned char std_dc_luminance_values[] = {0,1,2,3,4,5,6,7,8,9,10,11}; - static const unsigned char std_ac_luminance_nrcodes[] = {0,0,2,1,3,3,2,4,3,5,5,4,4,0,0,1,0x7d}; - static const unsigned char std_ac_luminance_values[] = { - 0x01,0x02,0x03,0x00,0x04,0x11,0x05,0x12,0x21,0x31,0x41,0x06,0x13,0x51,0x61,0x07,0x22,0x71,0x14,0x32,0x81,0x91,0xa1,0x08, - 0x23,0x42,0xb1,0xc1,0x15,0x52,0xd1,0xf0,0x24,0x33,0x62,0x72,0x82,0x09,0x0a,0x16,0x17,0x18,0x19,0x1a,0x25,0x26,0x27,0x28, - 0x29,0x2a,0x34,0x35,0x36,0x37,0x38,0x39,0x3a,0x43,0x44,0x45,0x46,0x47,0x48,0x49,0x4a,0x53,0x54,0x55,0x56,0x57,0x58,0x59, - 0x5a,0x63,0x64,0x65,0x66,0x67,0x68,0x69,0x6a,0x73,0x74,0x75,0x76,0x77,0x78,0x79,0x7a,0x83,0x84,0x85,0x86,0x87,0x88,0x89, - 0x8a,0x92,0x93,0x94,0x95,0x96,0x97,0x98,0x99,0x9a,0xa2,0xa3,0xa4,0xa5,0xa6,0xa7,0xa8,0xa9,0xaa,0xb2,0xb3,0xb4,0xb5,0xb6, - 0xb7,0xb8,0xb9,0xba,0xc2,0xc3,0xc4,0xc5,0xc6,0xc7,0xc8,0xc9,0xca,0xd2,0xd3,0xd4,0xd5,0xd6,0xd7,0xd8,0xd9,0xda,0xe1,0xe2, - 0xe3,0xe4,0xe5,0xe6,0xe7,0xe8,0xe9,0xea,0xf1,0xf2,0xf3,0xf4,0xf5,0xf6,0xf7,0xf8,0xf9,0xfa - }; - static const unsigned char std_dc_chrominance_nrcodes[] = {0,0,3,1,1,1,1,1,1,1,1,1,0,0,0,0,0}; - static const unsigned char std_dc_chrominance_values[] = {0,1,2,3,4,5,6,7,8,9,10,11}; - static const unsigned char std_ac_chrominance_nrcodes[] = {0,0,2,1,2,4,4,3,4,7,5,4,4,0,1,2,0x77}; - static const unsigned char std_ac_chrominance_values[] = { - 0x00,0x01,0x02,0x03,0x11,0x04,0x05,0x21,0x31,0x06,0x12,0x41,0x51,0x07,0x61,0x71,0x13,0x22,0x32,0x81,0x08,0x14,0x42,0x91, - 0xa1,0xb1,0xc1,0x09,0x23,0x33,0x52,0xf0,0x15,0x62,0x72,0xd1,0x0a,0x16,0x24,0x34,0xe1,0x25,0xf1,0x17,0x18,0x19,0x1a,0x26, - 0x27,0x28,0x29,0x2a,0x35,0x36,0x37,0x38,0x39,0x3a,0x43,0x44,0x45,0x46,0x47,0x48,0x49,0x4a,0x53,0x54,0x55,0x56,0x57,0x58, - 0x59,0x5a,0x63,0x64,0x65,0x66,0x67,0x68,0x69,0x6a,0x73,0x74,0x75,0x76,0x77,0x78,0x79,0x7a,0x82,0x83,0x84,0x85,0x86,0x87, - 0x88,0x89,0x8a,0x92,0x93,0x94,0x95,0x96,0x97,0x98,0x99,0x9a,0xa2,0xa3,0xa4,0xa5,0xa6,0xa7,0xa8,0xa9,0xaa,0xb2,0xb3,0xb4, - 0xb5,0xb6,0xb7,0xb8,0xb9,0xba,0xc2,0xc3,0xc4,0xc5,0xc6,0xc7,0xc8,0xc9,0xca,0xd2,0xd3,0xd4,0xd5,0xd6,0xd7,0xd8,0xd9,0xda, - 0xe2,0xe3,0xe4,0xe5,0xe6,0xe7,0xe8,0xe9,0xea,0xf2,0xf3,0xf4,0xf5,0xf6,0xf7,0xf8,0xf9,0xfa - }; - // Huffman tables - static const unsigned short YDC_HT[256][2] = { {0,2},{2,3},{3,3},{4,3},{5,3},{6,3},{14,4},{30,5},{62,6},{126,7},{254,8},{510,9}}; - static const unsigned short UVDC_HT[256][2] = { {0,2},{1,2},{2,2},{6,3},{14,4},{30,5},{62,6},{126,7},{254,8},{510,9},{1022,10},{2046,11}}; - static const unsigned short YAC_HT[256][2] = { - {10,4},{0,2},{1,2},{4,3},{11,4},{26,5},{120,7},{248,8},{1014,10},{65410,16},{65411,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {12,4},{27,5},{121,7},{502,9},{2038,11},{65412,16},{65413,16},{65414,16},{65415,16},{65416,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {28,5},{249,8},{1015,10},{4084,12},{65417,16},{65418,16},{65419,16},{65420,16},{65421,16},{65422,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {58,6},{503,9},{4085,12},{65423,16},{65424,16},{65425,16},{65426,16},{65427,16},{65428,16},{65429,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {59,6},{1016,10},{65430,16},{65431,16},{65432,16},{65433,16},{65434,16},{65435,16},{65436,16},{65437,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {122,7},{2039,11},{65438,16},{65439,16},{65440,16},{65441,16},{65442,16},{65443,16},{65444,16},{65445,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {123,7},{4086,12},{65446,16},{65447,16},{65448,16},{65449,16},{65450,16},{65451,16},{65452,16},{65453,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {250,8},{4087,12},{65454,16},{65455,16},{65456,16},{65457,16},{65458,16},{65459,16},{65460,16},{65461,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {504,9},{32704,15},{65462,16},{65463,16},{65464,16},{65465,16},{65466,16},{65467,16},{65468,16},{65469,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {505,9},{65470,16},{65471,16},{65472,16},{65473,16},{65474,16},{65475,16},{65476,16},{65477,16},{65478,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {506,9},{65479,16},{65480,16},{65481,16},{65482,16},{65483,16},{65484,16},{65485,16},{65486,16},{65487,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {1017,10},{65488,16},{65489,16},{65490,16},{65491,16},{65492,16},{65493,16},{65494,16},{65495,16},{65496,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {1018,10},{65497,16},{65498,16},{65499,16},{65500,16},{65501,16},{65502,16},{65503,16},{65504,16},{65505,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {2040,11},{65506,16},{65507,16},{65508,16},{65509,16},{65510,16},{65511,16},{65512,16},{65513,16},{65514,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {65515,16},{65516,16},{65517,16},{65518,16},{65519,16},{65520,16},{65521,16},{65522,16},{65523,16},{65524,16},{0,0},{0,0},{0,0},{0,0},{0,0}, - {2041,11},{65525,16},{65526,16},{65527,16},{65528,16},{65529,16},{65530,16},{65531,16},{65532,16},{65533,16},{65534,16},{0,0},{0,0},{0,0},{0,0},{0,0} - }; - static const unsigned short UVAC_HT[256][2] = { - {0,2},{1,2},{4,3},{10,4},{24,5},{25,5},{56,6},{120,7},{500,9},{1014,10},{4084,12},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {11,4},{57,6},{246,8},{501,9},{2038,11},{4085,12},{65416,16},{65417,16},{65418,16},{65419,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {26,5},{247,8},{1015,10},{4086,12},{32706,15},{65420,16},{65421,16},{65422,16},{65423,16},{65424,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {27,5},{248,8},{1016,10},{4087,12},{65425,16},{65426,16},{65427,16},{65428,16},{65429,16},{65430,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {58,6},{502,9},{65431,16},{65432,16},{65433,16},{65434,16},{65435,16},{65436,16},{65437,16},{65438,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {59,6},{1017,10},{65439,16},{65440,16},{65441,16},{65442,16},{65443,16},{65444,16},{65445,16},{65446,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {121,7},{2039,11},{65447,16},{65448,16},{65449,16},{65450,16},{65451,16},{65452,16},{65453,16},{65454,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {122,7},{2040,11},{65455,16},{65456,16},{65457,16},{65458,16},{65459,16},{65460,16},{65461,16},{65462,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {249,8},{65463,16},{65464,16},{65465,16},{65466,16},{65467,16},{65468,16},{65469,16},{65470,16},{65471,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {503,9},{65472,16},{65473,16},{65474,16},{65475,16},{65476,16},{65477,16},{65478,16},{65479,16},{65480,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {504,9},{65481,16},{65482,16},{65483,16},{65484,16},{65485,16},{65486,16},{65487,16},{65488,16},{65489,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {505,9},{65490,16},{65491,16},{65492,16},{65493,16},{65494,16},{65495,16},{65496,16},{65497,16},{65498,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {506,9},{65499,16},{65500,16},{65501,16},{65502,16},{65503,16},{65504,16},{65505,16},{65506,16},{65507,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {2041,11},{65508,16},{65509,16},{65510,16},{65511,16},{65512,16},{65513,16},{65514,16},{65515,16},{65516,16},{0,0},{0,0},{0,0},{0,0},{0,0},{0,0}, - {16352,14},{65517,16},{65518,16},{65519,16},{65520,16},{65521,16},{65522,16},{65523,16},{65524,16},{65525,16},{0,0},{0,0},{0,0},{0,0},{0,0}, - {1018,10},{32707,15},{65526,16},{65527,16},{65528,16},{65529,16},{65530,16},{65531,16},{65532,16},{65533,16},{65534,16},{0,0},{0,0},{0,0},{0,0},{0,0} - }; - static const int YQT[] = {16,11,10,16,24,40,51,61,12,12,14,19,26,58,60,55,14,13,16,24,40,57,69,56,14,17,22,29,51,87,80,62,18,22, - 37,56,68,109,103,77,24,35,55,64,81,104,113,92,49,64,78,87,103,121,120,101,72,92,95,98,112,100,103,99}; - static const int UVQT[] = {17,18,24,47,99,99,99,99,18,21,26,66,99,99,99,99,24,26,56,99,99,99,99,99,47,66,99,99,99,99,99,99, - 99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99,99}; - static const float aasf[] = { 1.0f * 2.828427125f, 1.387039845f * 2.828427125f, 1.306562965f * 2.828427125f, 1.175875602f * 2.828427125f, - 1.0f * 2.828427125f, 0.785694958f * 2.828427125f, 0.541196100f * 2.828427125f, 0.275899379f * 2.828427125f }; - - int row, col, i, k, subsample; - float fdtbl_Y[64], fdtbl_UV[64]; - unsigned char YTable[64], UVTable[64]; - - if(!data || !width || !height || comp > 4 || comp < 1) { - return 0; - } - - quality = quality ? quality : 90; - subsample = quality <= 90 ? 1 : 0; - quality = quality < 1 ? 1 : quality > 100 ? 100 : quality; - quality = quality < 50 ? 5000 / quality : 200 - quality * 2; - - for(i = 0; i < 64; ++i) { - int uvti, yti = (YQT[i]*quality+50)/100; - YTable[stbiw__jpg_ZigZag[i]] = (unsigned char) (yti < 1 ? 1 : yti > 255 ? 255 : yti); - uvti = (UVQT[i]*quality+50)/100; - UVTable[stbiw__jpg_ZigZag[i]] = (unsigned char) (uvti < 1 ? 1 : uvti > 255 ? 255 : uvti); - } - - for(row = 0, k = 0; row < 8; ++row) { - for(col = 0; col < 8; ++col, ++k) { - fdtbl_Y[k] = 1 / (YTable [stbiw__jpg_ZigZag[k]] * aasf[row] * aasf[col]); - fdtbl_UV[k] = 1 / (UVTable[stbiw__jpg_ZigZag[k]] * aasf[row] * aasf[col]); - } - } - - // Write Headers - { - static const unsigned char head0[] = { 0xFF,0xD8,0xFF,0xE0,0,0x10,'J','F','I','F',0,1,1,0,0,1,0,1,0,0,0xFF,0xDB,0,0x84,0 }; - static const unsigned char head2[] = { 0xFF,0xDA,0,0xC,3,1,0,2,0x11,3,0x11,0,0x3F,0 }; - const unsigned char head1[] = { 0xFF,0xC0,0,0x11,8,(unsigned char)(height>>8),STBIW_UCHAR(height),(unsigned char)(width>>8),STBIW_UCHAR(width), - 3,1,(unsigned char)(subsample?0x22:0x11),0,2,0x11,1,3,0x11,1,0xFF,0xC4,0x01,0xA2,0 }; - s->func(s->context, (void*)head0, sizeof(head0)); - s->func(s->context, (void*)YTable, sizeof(YTable)); - stbiw__putc(s, 1); - s->func(s->context, UVTable, sizeof(UVTable)); - s->func(s->context, (void*)head1, sizeof(head1)); - s->func(s->context, (void*)(std_dc_luminance_nrcodes+1), sizeof(std_dc_luminance_nrcodes)-1); - s->func(s->context, (void*)std_dc_luminance_values, sizeof(std_dc_luminance_values)); - stbiw__putc(s, 0x10); // HTYACinfo - s->func(s->context, (void*)(std_ac_luminance_nrcodes+1), sizeof(std_ac_luminance_nrcodes)-1); - s->func(s->context, (void*)std_ac_luminance_values, sizeof(std_ac_luminance_values)); - stbiw__putc(s, 1); // HTUDCinfo - s->func(s->context, (void*)(std_dc_chrominance_nrcodes+1), sizeof(std_dc_chrominance_nrcodes)-1); - s->func(s->context, (void*)std_dc_chrominance_values, sizeof(std_dc_chrominance_values)); - stbiw__putc(s, 0x11); // HTUACinfo - s->func(s->context, (void*)(std_ac_chrominance_nrcodes+1), sizeof(std_ac_chrominance_nrcodes)-1); - s->func(s->context, (void*)std_ac_chrominance_values, sizeof(std_ac_chrominance_values)); - s->func(s->context, (void*)head2, sizeof(head2)); - } - - // Encode 8x8 macroblocks - { - static const unsigned short fillBits[] = {0x7F, 7}; - int DCY=0, DCU=0, DCV=0; - int bitBuf=0, bitCnt=0; - // comp == 2 is grey+alpha (alpha is ignored) - int ofsG = comp > 2 ? 1 : 0, ofsB = comp > 2 ? 2 : 0; - const unsigned char *dataR = (const unsigned char *)data; - const unsigned char *dataG = dataR + ofsG; - const unsigned char *dataB = dataR + ofsB; - int x, y, pos; - if(subsample) { - for(y = 0; y < height; y += 16) { - for(x = 0; x < width; x += 16) { - float Y[256], U[256], V[256]; - for(row = y, pos = 0; row < y+16; ++row) { - // row >= height => use last input row - int clamped_row = (row < height) ? row : height - 1; - int base_p = (stbi__flip_vertically_on_write ? (height-1-clamped_row) : clamped_row)*width*comp; - for(col = x; col < x+16; ++col, ++pos) { - // if col >= width => use pixel from last input column - int p = base_p + ((col < width) ? col : (width-1))*comp; - float r = dataR[p], g = dataG[p], b = dataB[p]; - Y[pos]= +0.29900f*r + 0.58700f*g + 0.11400f*b - 128; - U[pos]= -0.16874f*r - 0.33126f*g + 0.50000f*b; - V[pos]= +0.50000f*r - 0.41869f*g - 0.08131f*b; - } - } - DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+0, 16, fdtbl_Y, DCY, YDC_HT, YAC_HT); - DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+8, 16, fdtbl_Y, DCY, YDC_HT, YAC_HT); - DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+128, 16, fdtbl_Y, DCY, YDC_HT, YAC_HT); - DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y+136, 16, fdtbl_Y, DCY, YDC_HT, YAC_HT); - - // subsample U,V - { - float subU[64], subV[64]; - int yy, xx; - for(yy = 0, pos = 0; yy < 8; ++yy) { - for(xx = 0; xx < 8; ++xx, ++pos) { - int j = yy*32+xx*2; - subU[pos] = (U[j+0] + U[j+1] + U[j+16] + U[j+17]) * 0.25f; - subV[pos] = (V[j+0] + V[j+1] + V[j+16] + V[j+17]) * 0.25f; - } - } - DCU = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, subU, 8, fdtbl_UV, DCU, UVDC_HT, UVAC_HT); - DCV = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, subV, 8, fdtbl_UV, DCV, UVDC_HT, UVAC_HT); - } - } - } - } else { - for(y = 0; y < height; y += 8) { - for(x = 0; x < width; x += 8) { - float Y[64], U[64], V[64]; - for(row = y, pos = 0; row < y+8; ++row) { - // row >= height => use last input row - int clamped_row = (row < height) ? row : height - 1; - int base_p = (stbi__flip_vertically_on_write ? (height-1-clamped_row) : clamped_row)*width*comp; - for(col = x; col < x+8; ++col, ++pos) { - // if col >= width => use pixel from last input column - int p = base_p + ((col < width) ? col : (width-1))*comp; - float r = dataR[p], g = dataG[p], b = dataB[p]; - Y[pos]= +0.29900f*r + 0.58700f*g + 0.11400f*b - 128; - U[pos]= -0.16874f*r - 0.33126f*g + 0.50000f*b; - V[pos]= +0.50000f*r - 0.41869f*g - 0.08131f*b; - } - } - - DCY = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, Y, 8, fdtbl_Y, DCY, YDC_HT, YAC_HT); - DCU = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, U, 8, fdtbl_UV, DCU, UVDC_HT, UVAC_HT); - DCV = stbiw__jpg_processDU(s, &bitBuf, &bitCnt, V, 8, fdtbl_UV, DCV, UVDC_HT, UVAC_HT); - } - } - } - - // Do the bit alignment of the EOI marker - stbiw__jpg_writeBits(s, &bitBuf, &bitCnt, fillBits); - } - - // EOI - stbiw__putc(s, 0xFF); - stbiw__putc(s, 0xD9); - - return 1; -} - -STBIWDEF int stbi_write_jpg_to_func(stbi_write_func *func, void *context, int x, int y, int comp, const void *data, int quality) -{ - stbi__write_context s = { 0 }; - stbi__start_write_callbacks(&s, func, context); - return stbi_write_jpg_core(&s, x, y, comp, (void *) data, quality); -} - - -#ifndef STBI_WRITE_NO_STDIO -STBIWDEF int stbi_write_jpg(char const *filename, int x, int y, int comp, const void *data, int quality) -{ - stbi__write_context s = { 0 }; - if (stbi__start_write_file(&s,filename)) { - int r = stbi_write_jpg_core(&s, x, y, comp, data, quality); - stbi__end_write_file(&s); - return r; - } else - return 0; -} -#endif - -#endif // STB_IMAGE_WRITE_IMPLEMENTATION - -/* Revision history - 1.16 (2021-07-11) - make Deflate code emit uncompressed blocks when it would otherwise expand - support writing BMPs with alpha channel - 1.15 (2020-07-13) unknown - 1.14 (2020-02-02) updated JPEG writer to downsample chroma channels - 1.13 - 1.12 - 1.11 (2019-08-11) - - 1.10 (2019-02-07) - support utf8 filenames in Windows; fix warnings and platform ifdefs - 1.09 (2018-02-11) - fix typo in zlib quality API, improve STB_I_W_STATIC in C++ - 1.08 (2018-01-29) - add stbi__flip_vertically_on_write, external zlib, zlib quality, choose PNG filter - 1.07 (2017-07-24) - doc fix - 1.06 (2017-07-23) - writing JPEG (using Jon Olick's code) - 1.05 ??? - 1.04 (2017-03-03) - monochrome BMP expansion - 1.03 ??? - 1.02 (2016-04-02) - avoid allocating large structures on the stack - 1.01 (2016-01-16) - STBIW_REALLOC_SIZED: support allocators with no realloc support - avoid race-condition in crc initialization - minor compile issues - 1.00 (2015-09-14) - installable file IO function - 0.99 (2015-09-13) - warning fixes; TGA rle support - 0.98 (2015-04-08) - added STBIW_MALLOC, STBIW_ASSERT etc - 0.97 (2015-01-18) - fixed HDR asserts, rewrote HDR rle logic - 0.96 (2015-01-17) - add HDR output - fix monochrome BMP - 0.95 (2014-08-17) - add monochrome TGA output - 0.94 (2014-05-31) - rename private functions to avoid conflicts with stb_image.h - 0.93 (2014-05-27) - warning fixes - 0.92 (2010-08-01) - casts to unsigned char to fix warnings - 0.91 (2010-07-17) - first public release - 0.90 first internal release -*/ - -/* ------------------------------------------------------------------------------- -This software is available under 2 licenses -- choose whichever you prefer. ------------------------------------------------------------------------------- -ALTERNATIVE A - MIT License -Copyright (c) 2017 Sean Barrett -Permission is hereby granted, free of charge, to any person obtaining a copy of -this software and associated documentation files (the "Software"), to deal in -the Software without restriction, including without limitation the rights to -use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies -of the Software, and to permit persons to whom the Software is furnished to do -so, subject to the following conditions: -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. ------------------------------------------------------------------------------- -ALTERNATIVE B - Public Domain (www.unlicense.org) -This is free and unencumbered software released into the public domain. -Anyone is free to copy, modify, publish, use, compile, sell, or distribute this -software, either in source code form or as a compiled binary, for any purpose, -commercial or non-commercial, and by any means. -In jurisdictions that recognize copyright laws, the author or authors of this -software dedicate any and all copyright interest in the software to the public -domain. We make this dedication for the benefit of the public at large and to -the detriment of our heirs and successors. We intend this dedication to be an -overt act of relinquishment in perpetuity of all present and future rights to -this software under copyright law. -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN -ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION -WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ------------------------------------------------------------------------------- -*/ diff --git a/code/libraries/CMakeLists.txt b/code/libraries/CMakeLists.txt deleted file mode 100644 index dd51380..0000000 --- a/code/libraries/CMakeLists.txt +++ /dev/null @@ -1,62 +0,0 @@ -cmake_minimum_required(VERSION 3.22) -project(imagemanipulation_libraries - VERSION 0.1 - DESCRIPTION "Libraries for image preprocessing" - LANGUAGES CXX) - -include(GNUInstallDirs) - -find_package(OpenCV REQUIRED) - - - -# RECTANGLE - -add_library(rect SHARED src/rectangle.cpp) - -target_compile_features(rect PRIVATE cxx_std_20) - -# set_target_properties(rect PROPERTIES VERSION ${PROJECT_VERSION}) # git can't deal with the symlinks for some reason - -# set_target_properties(rect PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/rect_lib.h) - -set_target_properties(rect PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/lib) - - -target_link_libraries(rect ${OpenCV_LIBS}) - -target_include_directories(rect - PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/include - PRIVATE ${OpenCV_INCLUDE_DIRS}) - - -# LINE - -add_library(line SHARED src/line.cpp) - -target_compile_features(line PRIVATE cxx_std_20) - -# set_target_properties(line PROPERTIES VERSION ${PROJECT_VERSION}) # git can't deal with the symlinks for some reason - -# set_target_properties(line PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/line_lib.h) - -set_target_properties(line PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/lib) - - -target_link_libraries(line ${OpenCV_LIBS}) - -target_include_directories(line - PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/include - PRIVATE ${OpenCV_INCLUDE_DIRS}) - - -# install(TARGETS rect -# LIBRARY DESTINATION ${CMAKE_INSTALL_LIBDIR} -# PUBLIC_HEADER DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}) - -# find_package(OpenCV REQUIRED) - -# target_include_directories(CropperEx -# PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/include -# PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../externallibraries/stbimagehelpers -# PRIVATE ${OpenCV_INCLUDE_DIRS}) \ No newline at end of file diff --git a/code/libraries/include/line.h b/code/libraries/include/line.h deleted file mode 100644 index 446607f..0000000 --- a/code/libraries/include/line.h +++ /dev/null @@ -1,20 +0,0 @@ -#ifndef LINE_H -#define LINE_H - - -class Line { -private: - -public: - - -private: - - -public: - - -}; - - -#endif //LINE_H \ No newline at end of file diff --git a/code/libraries/include/rectangle.h b/code/libraries/include/rectangle.h deleted file mode 100644 index 173bd48..0000000 --- a/code/libraries/include/rectangle.h +++ /dev/null @@ -1,79 +0,0 @@ -#ifndef RECTANGLE_H -#define RECTANGLE_H - -#include -#include - -// MAYBE MAKE TWOPTOBJECT A PARENT CLASS FOR BOTH LINE AND RECTANGLE? - -class Rectangle { -private: -// properties of the rectangle - double pt1x; - double pt1y; - double pt2x; - double pt2y; - - -public: -// constructor/destructor functions - Rectangle(); //don't know if this should be here - - Rectangle(cv::Rect rect); - Rectangle(cv::Point pt1, cv::Point pt2); - - template ::value>::type* = nullptr> // meant for an int/double/float or some other numeric return type - Rectangle(T pt1x, T pt1y, T pt2x, T pt2y); - - ~Rectangle(); - -private: -// private helper functions - - -public: - void overwriteTopLeft(cv::Point pt); - template ::value>::type* = nullptr> // meant for an int/double/float or some other numeric return type - void overwriteTopLeft(T ptx, T pty); - - void overwriteBottomRight(cv::Point pt); - template ::value>::type* = nullptr> // meant for an int/double/float or some other numeric return type - void overwriteBottomRight(T ptx, T pty); - - template ::value>::type* = nullptr> // meant for an int/double/float or some other numeric return type - cv::Point_ topLeft(); - - template ::value>::type* = nullptr> // meant for an int/double/float or some other numeric return type - cv::Point_ bottomRight(); - - template ::value>::type* = nullptr> - T area(); // meant for an int/double/float or some other numeric return type - - bool containsRect(Rectangle rect); // if this rectangle contains the other rectangle - - // Might need to implement size or width/height retrievers - - // INTERESTING NOTE, OPENCV ASSUMES THAT THE BOTTOM RIGHT BOUNDARY IS NOT INCLUSIVE - - - - // DON'T KNOW WHAT rectscontaining(rect, outerrects) DOES OR HOW IT'S USED - // FOLLOW UP, IT'S PART OF A BRUTE FORCE IMPLEMENTATION FOR OVERLAPPING RECTANGLES - // MAYBE IMPLEMENT IT AS A PRIVATE HELPER FUNCTION OR JUST NOT AT ALL AND HAVE IT BE SEPERATE. IT USES containsRect AS IT'S MAIN PART - - // NOT SURE WHAT TO DO ABOUT rotateRect(img, rect, angle, returnint=True, asRect=False) AS WELL - - -// general rectangle functions - static std::vector biggestNRects(std::vector rects, int n); - static Rectangle overlapRect(std::vector rects); - static Rectangle mergeRects(std::vector rects); - - -}; - -#endif //RECTANGLE_H - - - -// MAYBE IMPLEMENT STUFF FOR LINES AS WELL? \ No newline at end of file diff --git a/code/libraries/include/twoptobject.h b/code/libraries/include/twoptobject.h deleted file mode 100644 index e69de29..0000000 diff --git a/code/libraries/lib/libline.so b/code/libraries/lib/libline.so deleted file mode 100644 index 251b184..0000000 Binary files a/code/libraries/lib/libline.so and /dev/null differ diff --git a/code/libraries/lib/librect.so b/code/libraries/lib/librect.so deleted file mode 100644 index 8c6c49c..0000000 Binary files a/code/libraries/lib/librect.so and /dev/null differ diff --git a/code/libraries/process.py b/code/libraries/process.py deleted file mode 100644 index 01cb2c9..0000000 --- a/code/libraries/process.py +++ /dev/null @@ -1,12 +0,0 @@ - - - -def relabel(datasetpath): - mappingpathwithindataset = "/baseimages/unaugmentednames/mapping.txt" - mappingfilepath = datasetpath+mappingpathwithindataset - mappingfile = open(mappingfilepath, 'r') - maptext = mappingfile.read() - mappingfile.close() - print(maptext) - - diff --git a/code/libraries/src/line.cpp b/code/libraries/src/line.cpp deleted file mode 100644 index b26c481..0000000 --- a/code/libraries/src/line.cpp +++ /dev/null @@ -1 +0,0 @@ -#include "line.h" \ No newline at end of file diff --git a/code/libraries/src/rectangle.cpp b/code/libraries/src/rectangle.cpp deleted file mode 100644 index eb9137c..0000000 --- a/code/libraries/src/rectangle.cpp +++ /dev/null @@ -1,8 +0,0 @@ -#include "rectangle.h" - -// #include "line.h" //ONLY FOR POSSIBLY rotateRect(img, rect, angle, returnint=True, asRect=False) - -#include - - -// use a priority queue with a custom comparator to make a maxheap for biggestNRects https://stackoverflow.com/questions/57271271/is-there-a-maxheap-in-the-c-standard-library \ No newline at end of file diff --git a/code/libraries/src/twoptobject.cpp b/code/libraries/src/twoptobject.cpp deleted file mode 100644 index e69de29..0000000 diff --git a/code/libraries/testprocessing.ipynb b/code/libraries/testprocessing.ipynb deleted file mode 100644 index c9e577b..0000000 --- a/code/libraries/testprocessing.ipynb +++ /dev/null @@ -1,287 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import pathlib\n", - "import shutil\n", - "import cv2\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [], - "source": [ - "import sys\n", - "sys.path.insert(0, '/mnt/code/autocropper')\n", - "import myfunctions as mf" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], - "source": [ - "# os.getcwd()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "# filenames = next(os.walk(\"/mnt/dataset/baseimages/unaugmentednames/\"), (None, None, []))[2]\n", - "# filenames.remove(\"mapping.txt\")\n", - "# print(filenames)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [], - "source": [ - "imagefileextensions = [\".jpg\", \".png\"]\n", - "\n", - "def parsemaptext(text):\n", - " lineseperated = text.split('\\n')\n", - " # if (lineseperated[-1] == ''):\n", - " # lineseperated = lineseperated[:-1]\n", - " # print(lineseperated)\n", - " mappingdict = {}\n", - " for line in lineseperated:\n", - " if line == '':\n", - " continue\n", - " splitline = line.split(\" | \")\n", - " if splitline[0] not in mappingdict:\n", - " mappingdict[splitline[0]] = splitline[1]\n", - " # print(splitline)\n", - " \n", - " \n", - " return mappingdict\n", - "\n", - "\n", - "def readmapfiletodict(mapfilepath):\n", - " if (not os.path.isfile(mapfilepath)):\n", - " # f = open(mapfilepath, \"x\")\n", - " # f.close()\n", - " return {}\n", - " mappingfile = open(mapfilepath, 'r')\n", - " maptext = mappingfile.read()\n", - " mappingfile.close()\n", - " \n", - " mappingdict = parsemaptext(maptext)\n", - " return mappingdict\n", - " \n", - "\n", - "def writemapdicttofile(mapfilepath, mappingdict):\n", - " starting = False\n", - " if (not os.path.isfile(mapfilepath) or os.stat(mapfilepath).st_size == 0):\n", - " file = open(mapfilepath, \"w\")\n", - " starting = True\n", - " # f.close()\n", - " # return {}\n", - " else:\n", - " file = open(mapfilepath, 'a')\n", - " for key in mappingdict:\n", - " if starting:\n", - " file.write(key+\" | \"+mappingdict[key])\n", - " starting = False\n", - " else:\n", - " file.write(\"\\n\"+key+\" | \"+mappingdict[key])\n", - " file.close()\n", - "\n", - "def renameoriginals(datasetpath):\n", - " pathtooriginals = \"baseimages/unaugmentednames/\"\n", - " mappingfilename = \"mapping.txt\"\n", - " mappingpathwithindataset = pathtooriginals+mappingfilename\n", - " mappingfilepath = datasetpath+mappingpathwithindataset\n", - "\n", - " \n", - " mappingdict = readmapfiletodict(mappingfilepath)\n", - " print(mappingdict)\n", - " blacklistednumbers = []\n", - " for key in mappingdict:\n", - " value = mappingdict[key]\n", - " suffix = pathlib.Path(value).suffix\n", - " # print(pathlib.Path(value).name)\n", - " valnum = value[:-len(suffix)]\n", - " blacklistednumbers.append(int(valnum))\n", - " print(blacklistednumbers)\n", - " \n", - " \n", - " \n", - " filenames = next(os.walk(datasetpath+pathtooriginals), (None, None, []))[2]\n", - " if (mappingfilename in filenames):\n", - " filenames.remove(mappingfilename)\n", - " # print(filenames)\n", - " \n", - " mappeddict = {}\n", - " filenamecounter = 0\n", - " for filename in filenames:\n", - " suffix = pathlib.Path(filename).suffix\n", - " if (suffix not in imagefileextensions):\n", - " print(\"Not a valid image \"+filename)\n", - " continue\n", - " if filename in mappingdict:\n", - " continue\n", - " while filenamecounter in blacklistednumbers:\n", - " filenamecounter += 1\n", - " shutil.copyfile(datasetpath+pathtooriginals+filename, datasetpath+\"baseimages/\"+str(filenamecounter)+suffix)\n", - " mappeddict[filename] = str(filenamecounter)+suffix\n", - " filenamecounter += 1\n", - " print(mappeddict)\n", - " writemapdicttofile(mappingfilepath, mappeddict)\n", - " \n", - " # print(maptext)\n", - " \n" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "def autocrop(datasetpath):\n", - " subpathtobasefiles = \"baseimages/\"\n", - " subpathtoaugmentedfiles = \"autocropped/\"\n", - " imagespath = datasetpath + subpathtobasefiles\n", - " \n", - " filenames = next(os.walk(imagespath), (None, None, []))[2]\n", - " \n", - " for filename in filenames:\n", - " suffix = pathlib.Path(filename).suffix\n", - " if (suffix not in imagefileextensions):\n", - " print(\"Not a valid image \"+filename)\n", - " continue\n", - " print(imagespath+filename)\n", - " if (not os.path.isfile(imagespath+filename)):\n", - " print(\"hi\")\n", - " continue\n", - " img = cv2.imread(imagespath+filename)\n", - " # print(img)\n", - " autocropped = mf.houghlineprocessing(img)\n", - " cv2.imwrite(datasetpath+subpathtoaugmentedfiles+filename, autocropped)\n", - " \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], - "source": [ - "def showimgs(imgs):\n", - " if (isinstance(imgs, np.ndarray)):\n", - " if (imgs.shape[0] > imgs.shape[1]):\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(imgs, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(imgs, width=1000))\n", - " else:\n", - " for i, out in enumerate(imgs):\n", - " if (out.shape[0] > out.shape[1]):\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, width=1000))\n", - " cv2.waitKey(0)\n", - " cv2.destroyAllWindows()" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'IMG_7736.jpg': '0.jpg', 'IMG_7737.jpg': '1.jpg', 'IMG_7738.jpg': '2.jpg', 'IMG_7739.jpg': '3.jpg', 'IMG_7740.jpg': '4.jpg', 'IMG_7741.jpg': '5.jpg', 'IMG_7742.jpg': '6.jpg', 'IMG_7743.jpg': '7.jpg', 'IMG_7744.jpg': '8.jpg', 'IMG_7745.jpg': '9.jpg', 'IMG_7747.jpg': '10.jpg', 'IMG_7748.jpg': '11.jpg'}\n", - "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]\n", - "{}\n" - ] - } - ], - "source": [ - "renameoriginals(\"/mnt/dataset/\")" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [ - { - "ename": "error", - "evalue": "OpenCV(4.5.4) ./modules/imgproc/src/resize.cpp:4051: error: (-215:Assertion failed) !ssize.empty() in function 'resize'\n", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31merror\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m/mnt/code/libraries/testprocessing.ipynb Cell 9\u001b[0m line \u001b[0;36m2\n\u001b[1;32m 1\u001b[0m img \u001b[39m=\u001b[39m cv2\u001b[39m.\u001b[39mimread(\u001b[39m'\u001b[39m\u001b[39m/mnt/dataset/baseimages/1.jpg\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m----> 2\u001b[0m out \u001b[39m=\u001b[39m mf\u001b[39m.\u001b[39;49mhoughlineprocessing(img)\n", - "File \u001b[0;32m/mnt/code/autocropper/myfunctions.py:1042\u001b[0m, in \u001b[0;36mhoughlineprocessing\u001b[0;34m(image)\u001b[0m\n\u001b[1;32m 1041\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mhoughlineprocessing\u001b[39m(image):\n\u001b[0;32m-> 1042\u001b[0m croppedanddeskewed, _ \u001b[39m=\u001b[39m houghlinedeskewandcrop(image)\n\u001b[1;32m 1043\u001b[0m \u001b[39m##IF IT DOESN'T CHANGE THE IMAGE (CHANGE THE _ TO SOMETHING USEFUL), THEN CROPCLARIFYING SHOULD JUST DO THE TEXT ISOLATION SECTION AND NOT TRY AND WHITE OUT ANY BACKGROUND.\u001b[39;00m\n\u001b[1;32m 1044\u001b[0m \u001b[39m## IF THERE'S NO CROPPING, MAYBE EVEN JUMP RIGHT TO USING THE EXTERNAL DESKEW FIRST BEFORE TOSSING IT INTO CROPCLARIFYING\u001b[39;00m\n\u001b[1;32m 1046\u001b[0m postprocessed \u001b[39m=\u001b[39m cropclarifying(croppedanddeskewed)\n", - "File \u001b[0;32m/mnt/code/autocropper/myfunctions.py:452\u001b[0m, in \u001b[0;36mhoughlinedeskewandcrop\u001b[0;34m(image)\u001b[0m\n\u001b[1;32m 446\u001b[0m rotationangle \u001b[39m=\u001b[39m houghlinedeskewangle(dst1)\n\u001b[1;32m 448\u001b[0m \u001b[39m# -----------------end of finding angle to deskew-----------------\u001b[39;00m\n\u001b[1;32m 449\u001b[0m \n\u001b[1;32m 450\u001b[0m \u001b[39m## -----------------deskewing and then cropping-----------------\u001b[39;00m\n\u001b[0;32m--> 452\u001b[0m \u001b[39mreturn\u001b[39;00m houghlinedeskewthencrop(croppedogimage, dst1, rotationangle)\n", - "File \u001b[0;32m/mnt/code/autocropper/myfunctions.py:420\u001b[0m, in \u001b[0;36mhoughlinedeskewthencrop\u001b[0;34m(baseimage, preppedimage, rotationangle)\u001b[0m\n\u001b[1;32m 414\u001b[0m scaledrect \u001b[39m=\u001b[39m (\u001b[39mint\u001b[39m(rect[\u001b[39m0\u001b[39m]\u001b[39m*\u001b[39msizemultiplier), \u001b[39mint\u001b[39m(rect[\u001b[39m1\u001b[39m]\u001b[39m*\u001b[39msizemultiplier), \u001b[39mint\u001b[39m(rect[\u001b[39m2\u001b[39m]\u001b[39m*\u001b[39msizemultiplier), \u001b[39mint\u001b[39m(rect[\u001b[39m3\u001b[39m]\u001b[39m*\u001b[39msizemultiplier))\n\u001b[1;32m 416\u001b[0m croppedbaseimage \u001b[39m=\u001b[39m rotatedbaseimage[scaledrect[\u001b[39m1\u001b[39m]:scaledrect[\u001b[39m3\u001b[39m], scaledrect[\u001b[39m0\u001b[39m]:scaledrect[\u001b[39m2\u001b[39m], :]\n\u001b[0;32m--> 420\u001b[0m shrunkencbi, sizemultiplier \u001b[39m=\u001b[39m ResizeWithAspectRatio(croppedbaseimage, width\u001b[39m=\u001b[39;49m\u001b[39m1000\u001b[39;49m, retscale\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m)\n\u001b[1;32m 421\u001b[0m gray \u001b[39m=\u001b[39m cv2\u001b[39m.\u001b[39mcvtColor(shrunkencbi, cv2\u001b[39m.\u001b[39mCOLOR_BGR2GRAY)\n\u001b[1;32m 422\u001b[0m thresh \u001b[39m=\u001b[39m cv2\u001b[39m.\u001b[39mthreshold(gray, \u001b[39m200\u001b[39m, \u001b[39m255\u001b[39m, cv2\u001b[39m.\u001b[39mTHRESH_BINARY)[\u001b[39m1\u001b[39m]\n", - "File \u001b[0;32m/mnt/code/autocropper/myfunctions.py:27\u001b[0m, in \u001b[0;36mResizeWithAspectRatio\u001b[0;34m(image, width, height, inter, retscale)\u001b[0m\n\u001b[1;32m 23\u001b[0m dim \u001b[39m=\u001b[39m (width, \u001b[39mint\u001b[39m(h \u001b[39m*\u001b[39m r))\n\u001b[1;32m 25\u001b[0m \u001b[39mif\u001b[39;00m (retscale \u001b[39m==\u001b[39m \u001b[39mTrue\u001b[39;00m):\n\u001b[1;32m 26\u001b[0m \u001b[39m# print(\"hi\")\u001b[39;00m\n\u001b[0;32m---> 27\u001b[0m \u001b[39mreturn\u001b[39;00m (cv2\u001b[39m.\u001b[39;49mresize(image, dim, interpolation\u001b[39m=\u001b[39;49minter), \u001b[39m1\u001b[39m\u001b[39m/\u001b[39mr)\n\u001b[1;32m 28\u001b[0m \u001b[39mreturn\u001b[39;00m cv2\u001b[39m.\u001b[39mresize(image, dim, interpolation\u001b[39m=\u001b[39minter)\n", - "\u001b[0;31merror\u001b[0m: OpenCV(4.5.4) ./modules/imgproc/src/resize.cpp:4051: error: (-215:Assertion failed) !ssize.empty() in function 'resize'\n" - ] - } - ], - "source": [ - "img = cv2.imread('/mnt/dataset/baseimages/1.jpg')\n", - "out = mf.houghlineprocessing(img)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "showimgs(out)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# autocrop(\"/mnt/dataset/\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/textdataretriever/adjusted_test_images/IMG_7594.jpg b/code/textdataretriever/adjusted_test_images/IMG_7594.jpg deleted file mode 100644 index 5388a88..0000000 Binary files a/code/textdataretriever/adjusted_test_images/IMG_7594.jpg and /dev/null differ diff --git a/code/textdataretriever/adjusted_test_images/IMG_7604.jpg b/code/textdataretriever/adjusted_test_images/IMG_7604.jpg deleted file mode 100644 index a4735ee..0000000 Binary files a/code/textdataretriever/adjusted_test_images/IMG_7604.jpg and /dev/null differ diff --git a/code/textdataretriever/adjusted_test_images/IMG_7605.jpg b/code/textdataretriever/adjusted_test_images/IMG_7605.jpg deleted file mode 100644 index 1e4986b..0000000 Binary files a/code/textdataretriever/adjusted_test_images/IMG_7605.jpg and /dev/null differ diff --git a/code/textdataretriever/adjusted_test_images/IMG_7640.jpg b/code/textdataretriever/adjusted_test_images/IMG_7640.jpg deleted file mode 100644 index a1cc9bc..0000000 Binary files a/code/textdataretriever/adjusted_test_images/IMG_7640.jpg and /dev/null differ diff --git a/code/textdataretriever/adjusted_test_images/IvV2y.png b/code/textdataretriever/adjusted_test_images/IvV2y.png deleted file mode 100644 index 610fa89..0000000 Binary files a/code/textdataretriever/adjusted_test_images/IvV2y.png and /dev/null differ diff --git a/code/textdataretriever/result_images/0.jpg b/code/textdataretriever/result_images/0.jpg deleted file mode 100644 index de255bd..0000000 Binary files a/code/textdataretriever/result_images/0.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/1.jpg b/code/textdataretriever/result_images/1.jpg deleted file mode 100644 index fbc977f..0000000 Binary files a/code/textdataretriever/result_images/1.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/10.jpg b/code/textdataretriever/result_images/10.jpg deleted file mode 100644 index 41d746c..0000000 Binary files a/code/textdataretriever/result_images/10.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/11.jpg b/code/textdataretriever/result_images/11.jpg deleted file mode 100644 index bc6ec81..0000000 Binary files a/code/textdataretriever/result_images/11.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/12.jpg b/code/textdataretriever/result_images/12.jpg deleted file mode 100644 index 92eadeb..0000000 Binary files a/code/textdataretriever/result_images/12.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/13.jpg b/code/textdataretriever/result_images/13.jpg deleted file mode 100644 index 1ea6298..0000000 Binary files a/code/textdataretriever/result_images/13.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/14.jpg b/code/textdataretriever/result_images/14.jpg deleted file mode 100644 index 9365815..0000000 Binary files a/code/textdataretriever/result_images/14.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/15.jpg b/code/textdataretriever/result_images/15.jpg deleted file mode 100644 index bab9e11..0000000 Binary files a/code/textdataretriever/result_images/15.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/16.jpg b/code/textdataretriever/result_images/16.jpg deleted file mode 100644 index 45cb73c..0000000 Binary files a/code/textdataretriever/result_images/16.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/17.jpg b/code/textdataretriever/result_images/17.jpg deleted file mode 100644 index 6e6375d..0000000 Binary files a/code/textdataretriever/result_images/17.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/18.jpg b/code/textdataretriever/result_images/18.jpg deleted file mode 100644 index 0e74fd5..0000000 Binary files a/code/textdataretriever/result_images/18.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/19.jpg b/code/textdataretriever/result_images/19.jpg deleted file mode 100644 index 97b9aaa..0000000 Binary files a/code/textdataretriever/result_images/19.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/2.jpg b/code/textdataretriever/result_images/2.jpg deleted file mode 100644 index f96bfc1..0000000 Binary files a/code/textdataretriever/result_images/2.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/3.jpg b/code/textdataretriever/result_images/3.jpg deleted file mode 100644 index bdef390..0000000 Binary files a/code/textdataretriever/result_images/3.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/4.jpg b/code/textdataretriever/result_images/4.jpg deleted file mode 100644 index 767a330..0000000 Binary files a/code/textdataretriever/result_images/4.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/5.jpg b/code/textdataretriever/result_images/5.jpg deleted file mode 100644 index cb5bb86..0000000 Binary files a/code/textdataretriever/result_images/5.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/6.jpg b/code/textdataretriever/result_images/6.jpg deleted file mode 100644 index f028991..0000000 Binary files a/code/textdataretriever/result_images/6.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/7.jpg b/code/textdataretriever/result_images/7.jpg deleted file mode 100644 index 896f7c2..0000000 Binary files a/code/textdataretriever/result_images/7.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/8.jpg b/code/textdataretriever/result_images/8.jpg deleted file mode 100644 index bb4b041..0000000 Binary files a/code/textdataretriever/result_images/8.jpg and /dev/null differ diff --git a/code/textdataretriever/result_images/9.jpg b/code/textdataretriever/result_images/9.jpg deleted file mode 100644 index 1cd63e0..0000000 Binary files a/code/textdataretriever/result_images/9.jpg and /dev/null differ diff --git a/code/textdataretriever/test_images/IMG_7594.jpg b/code/textdataretriever/test_images/IMG_7594.jpg deleted file mode 100644 index 79936e9..0000000 Binary files a/code/textdataretriever/test_images/IMG_7594.jpg and /dev/null differ diff --git a/code/textdataretriever/test_images/IMG_7604.jpg b/code/textdataretriever/test_images/IMG_7604.jpg deleted file mode 100644 index fc25bd5..0000000 Binary files a/code/textdataretriever/test_images/IMG_7604.jpg and /dev/null differ diff --git a/code/textdataretriever/test_images/IMG_7605.jpg b/code/textdataretriever/test_images/IMG_7605.jpg deleted file mode 100644 index b58854d..0000000 Binary files a/code/textdataretriever/test_images/IMG_7605.jpg and /dev/null differ diff --git a/code/textdataretriever/test_images/IMG_7640.jpg b/code/textdataretriever/test_images/IMG_7640.jpg deleted file mode 100644 index 5ac7648..0000000 Binary files a/code/textdataretriever/test_images/IMG_7640.jpg and /dev/null differ diff --git a/code/textdataretriever/test_images/IvV2y.png b/code/textdataretriever/test_images/IvV2y.png deleted file mode 100644 index a1bd714..0000000 Binary files a/code/textdataretriever/test_images/IvV2y.png and /dev/null differ diff --git a/code/textdataretriever/textextractor/donuttesting.ipynb b/code/textdataretriever/textextractor/donuttesting.ipynb deleted file mode 100644 index cc9769e..0000000 --- a/code/textdataretriever/textextractor/donuttesting.ipynb +++ /dev/null @@ -1,224 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 91, - "metadata": {}, - "outputs": [], - "source": [ - "from PIL import Image\n", - "import torch\n", - "\n", - "\n", - "import sys\n", - "sys.path.insert(0, '../../autocropper')\n", - "import myfunctions as mf\n", - "\n", - "import extractorfunctions as ef\n", - "import cv2\n", - "import time" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [], - "source": [ - "from transformers import DonutProcessor, VisionEncoderDecoderModel" - ] - }, - { - "cell_type": "code", - "execution_count": 93, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Could not find image processor class in the image processor config or the model config. Loading based on pattern matching with the model's feature extractor configuration.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n" - ] - } - ], - "source": [ - "processor = DonutProcessor.from_pretrained(\"naver-clova-ix/donut-base-finetuned-docvqa\")\n", - "model = VisionEncoderDecoderModel.from_pretrained(\"naver-clova-ix/donut-base-finetuned-docvqa\")" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [], - "source": [ - "filename = \"IMG_7640.jpg\"\n", - "pathname = \"../test_images/\"" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "metadata": {}, - "outputs": [], - "source": [ - "# image = Image.open(pathname+filename).convert(\"RGB\")" - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "209562.099385929\n", - "209562.603891718\n" - ] - } - ], - "source": [ - "img = cv2.imread(pathname+filename)\n", - "# croppedanddeskewed, _ = mf.houghlinedeskewandcrop(img)\n", - "# whitedbackground = mf.whiteoutbackground(croppedanddeskewed)\n", - "# print(time.perf_counter())\n", - "out = mf.houghlineprocessing(img)\n", - "# print(time.perf_counter())\n", - "rgbimg = cv2.cvtColor(out, cv2.COLOR_BGR2RGB)\n", - "image = Image.fromarray(rgbimg)" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "" - ] - }, - "execution_count": 97, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "image" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "metadata": {}, - "outputs": [], - "source": [ - "pixel_values = processor(image, return_tensors=\"pt\").pixel_values" - ] - }, - { - "cell_type": "code", - "execution_count": 74, - "metadata": {}, - "outputs": [], - "source": [ - "task_prompt = \"{user_input}\"\n", - "question = \"Is this a receipt?\"\n", - "prompt = task_prompt.replace(\"{user_input}\", question)\n", - "# print(prompt)" - ] - }, - { - "cell_type": "code", - "execution_count": 75, - "metadata": {}, - "outputs": [], - "source": [ - "decoder_input_ids = processor.tokenizer(prompt, add_special_tokens=False, return_tensors=\"pt\")[\"input_ids\"]\n", - "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", - "model.to(device)\n", - "\n", - "outputs = model.generate(pixel_values.to(device),\n", - " decoder_input_ids=decoder_input_ids.to(device),\n", - " max_length=model.decoder.config.max_position_embeddings,\n", - " early_stopping=True,\n", - " pad_token_id=processor.tokenizer.pad_token_id,\n", - " eos_token_id=processor.tokenizer.eos_token_id,\n", - " use_cache=True,\n", - " num_beams=1,\n", - " bad_words_ids=[[processor.tokenizer.unk_token_id]],\n", - " return_dict_in_generate=True,\n", - " output_scores=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Is this a receipt? $14.40\n" - ] - } - ], - "source": [ - "\n", - "import re\n", - "\n", - "seq = processor.batch_decode(outputs.sequences)[0]\n", - "seq = seq.replace(processor.tokenizer.eos_token, \"\").replace(processor.tokenizer.pad_token, \"\")\n", - "seq = re.sub(r\"<.*?>\", \"\", seq, count=1).strip() # remove first task start token\n", - "print(seq)" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'text_sequence': 'Is this a receipt? $14.40'}" - ] - }, - "execution_count": 77, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "processor.token2json(seq)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/textdataretriever/textextractor/extractorfunctions.py b/code/textdataretriever/textextractor/extractorfunctions.py deleted file mode 100644 index 3ff51ea..0000000 --- a/code/textdataretriever/textextractor/extractorfunctions.py +++ /dev/null @@ -1,585 +0,0 @@ -import cv2 -import numpy as np - -import sys -sys.path.insert(0, '../../autocropper') -import myfunctions as mf - - - -## helper functions -def rectcenterpt(rect, xywhrect=True, retint=False): - if (xywhrect): - x = rect[0] + rect[2]/2 - y = rect[1] + rect[3]/2 - else: - x = (rect[0]+rect[2])/2 - y = (rect[1]+rect[3])/2 - if (retint): - x = int(x) - y = int(y) - return (x,y) - -def containsamount(outerrect, innerrect, percentage=1): - tinyrect = mf.overlapRect([outerrect, innerrect]) - tinyarea = tinyrect[2]*tinyrect[3] - if (tinyrect[0] == -1): - tinyarea = 0 - innerrectarea = innerrect[2]*innerrect[3] - if (tinyarea/innerrectarea >= percentage): - return True - return False - -def aboveandbelow(outerrect, innerrect): - if (outerrect[1] < innerrect[1] and outerrect[1]+outerrect[3] > innerrect[1]+innerrect[3]): - return True - return False - -## Below code is an almost direct copy from https://github.com/scrunts23/CS-Data-Science-Build-Week-1/blob/master/model/dbscan.py - -def dbscan(D, eps, MinPts): - ''' - Cluster the dataset `D` using the DBSCAN algorithm. - - dbscan takes a dataset `D` (a list of vectors), a threshold distance - `eps`, and a required number of points `MinPts`. - - It will return a list of cluster labels. The label -1 means noise, and then - the clusters are numbered starting from 1. - ''' - - # This list will hold the final cluster assignment for each point in D. - # There are two reserved values: - # -1 - Indicates a noise point - # 0 - Means the point hasn't been considered yet. - # Initially all labels are 0. - labels = [0]*len(D) - - # C is the ID of the current cluster. - C = 0 - - # This outer loop is just responsible for picking new seed points--a point - # from which to grow a new cluster. - # Once a valid seed point is found, a new cluster is created, and the - # cluster growth is all handled by the 'expandCluster' routine. - - # For each point P in the Dataset D... - # ('P' is the index of the datapoint, rather than the datapoint itself.) - for P in range(0, len(D)): - - # Only points that have not already been claimed can be picked as new - # seed points. - # If the point's label is not 0, continue to the next point. - if not (labels[P] == 0): - continue - - # Find all of P's neighboring points. - NeighborPts = region_query(D, P, eps) - - # If the number is below MinPts, this point is noise. - # This is the only condition under which a point is labeled - # NOISE--when it's not a valid seed point. A NOISE point may later - # be picked up by another cluster as a boundary point (this is the only - # condition under which a cluster label can change--from NOISE to - # something else). - if len(NeighborPts) < MinPts: - labels[P] = -1 - # Otherwise, if there are at least MinPts nearby, use this point as the - # seed for a new cluster. - else: - C += 1 - grow_cluster(D, labels, P, NeighborPts, C, eps, MinPts) - - # All data has been clustered! - return labels - - -def grow_cluster(D, labels, P, NeighborPts, C, eps, MinPts): - ''' - Grow a new cluster with label `C` from the seed point `P`. - - This function searches through the dataset to find all points that belong - to this new cluster. When this function returns, cluster `C` is complete. - - Parameters: - `D` - The dataset (a list of vectors) - `labels` - List storing the cluster labels for all dataset points - `P` - Index of the seed point for this new cluster - `NeighborPts` - All of the neighbors of `P` - `C` - The label for this new cluster. - `eps` - Threshold distance - `MinPts` - Minimum required number of neighbors - ''' - - # Assign the cluster label to the seed point. - labels[P] = C - - # Look at each neighbor of P (neighbors are referred to as Pn). - # NeighborPts will be used as a FIFO queue of points to search--that is, it - # will grow as we discover new branch points for the cluster. The FIFO - # behavior is accomplished by using a while-loop rather than a for-loop. - # In NeighborPts, the points are represented by their index in the original - # dataset. - i = 0 - while i < len(NeighborPts): - - # Get the next point from the queue. - Pn = NeighborPts[i] - - # If Pn was labelled NOISE during the seed search, then we - # know it's not a branch point (it doesn't have enough neighbors), so - # make it a leaf point of cluster C and move on. - if labels[Pn] == -1: - labels[Pn] = C - - # Otherwise, if Pn isn't already claimed, claim it as part of C. - elif labels[Pn] == 0: - # Add Pn to cluster C (Assign cluster label C). - labels[Pn] = C - - # Find all the neighbors of Pn - PnNeighborPts = region_query(D, Pn, eps) - - # If Pn has at least MinPts neighbors, it's a branch point! - # Add all of its neighbors to the FIFO queue to be searched. - if len(PnNeighborPts) >= MinPts: - NeighborPts = NeighborPts + PnNeighborPts - # If Pn *doesn't* have enough neighbors, then it's a leaf point. - # Don't queue up it's neighbors as expansion points. - #else: - # Do nothing - #NeighborPts = NeighborPts - - # Advance to the next point in the FIFO queue. - i += 1 - - # We've finished growing cluster C! - - -def region_query(D, P, eps): - ''' - Find all points in dataset `D` within distance `eps` of point `P`. - - This function calculates the distance between a point P and every other - point in the dataset, and then returns only those points which are within a - threshold distance `eps`. - ''' - neighbors = [] - - # For each point in the dataset... - for Pn in range(0, len(D)): - - # If the distance is below the threshold, add it to the neighbors list. - if (rectcenterpt(D[P])[1] - rectcenterpt(D[Pn])[1]) < eps: - neighbors.append(Pn) - - return neighbors - - -def padWithColour(img, hpadding=0, vpadding=0, fill=(0,0,0)): - borderType = cv2.BORDER_CONSTANT - out = cv2.copyMakeBorder(img, vpadding, vpadding, hpadding, hpadding, borderType, None, fill) - return out - -def mergecontours(contours): - cont = np.vstack(contours) - finalcontour = cv2.convexHull(cont) - return finalcontour - -def getSkewAngle(cvImage) -> float: - # Prep image, copy, convert to gray scale, blur, and threshold - newImage = padWithColour(cvImage, hpadding=50, vpadding=50, fill=(255,255,255)) - # return newImage - gray = cv2.cvtColor(newImage, cv2.COLOR_BGR2GRAY) - blur = cv2.GaussianBlur(gray, (9, 9), 0) - thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1] - - # Apply dilate to merge text into meaningful lines/paragraphs. - # Use larger kernel on X axis to merge characters into single line, cancelling out any spaces. - # But use smaller kernel on Y axis to separate between different blocks of text - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10, 5)) - dilate = cv2.dilate(thresh, kernel, iterations=5) - # return dilate - - # Find all contours - contours, hierarchy = cv2.findContours(dilate, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE) - contours = sorted(contours, key = cv2.contourArea, reverse = True) - - # Find largest contour and surround in min area box - largestContour = contours[0] - - mergedcontour = mergecontours(contours) - - # return cv2.drawContours(newImage, [mergedcontour], -1, (0,255,0), thickness=3) - minAreaRect = cv2.minAreaRect(mergedcontour) - # return cv2.drawContours(newImage, [largestContour], -1, (0,255,0), thickness=3) - # minAreaRect = cv2.minAreaRect(largestContour) - - box = cv2.boxPoints(minAreaRect) - box = np.intp(box) - newImage = cv2.drawContours(newImage, [box], -1, (0,255,0), thickness=3) - # return newImage - - # Determine the angle. Convert it to the value that was originally used to obtain skewed image - angle = minAreaRect[-1] - # print(angle) - if angle > 45: - angle = angle - 90 - if angle < -45: - angle = 90 + angle - # print(angle) - return angle - -def minboxdeskew(img, fill=(0,0,0)): - colourimg = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) - angle = getSkewAngle(colourimg) - padimg = padWithColour(img, hpadding=50, vpadding=50, fill=fill) - rotated = mf.rotate(padimg, angle, fill=fill) - return rotated - - - -def l1linerectretriever(image, divider=2): - shape = image.shape - - imgcopy = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) - # return imgcopy - - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) - linekernel = cv2.getStructuringElement(cv2.MORPH_RECT, (shape[1]//40, 1)) - # reducedimage = image - reducedimage = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel, iterations=1) - # reducedimage = cv2.morphologyEx(reducedimage, cv2.MORPH_ERODE, kernel) - # return reducedimage - - charcanny = cv2.Canny(reducedimage, 0, 500, None, 3) - # return canny - - - lettercontours, heirarchy = cv2.findContours(charcanny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # contours, heirarchy = cv2.findContours(255-reducedimage,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - - # imgcopy = cv2.drawContours(imgcopy, lettercontours, -1, color=(0,255,0), thickness=1) - # return imgcopy - - letterboxes = np.empty((len(lettercontours), 4), dtype=int) - - for i, contour in enumerate(lettercontours): - b = list(cv2.boundingRect(contour)) - # b[0] -= (kernel.shape[0]-1) - # b[1] -= (kernel.shape[1]-1) - # b[2] += (2*kernel.shape[0]-1) - # b[3] += (2*kernel.shape[1]-1) - letterboxes[i] = b - # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), 128, thickness=3) - # return imgcopy - - epsilonvalue = np.median(letterboxes, axis=0)[3]/divider - # print(epsilonvalue) - - - - linemade = 255-cv2.morphologyEx(255-image, cv2.MORPH_DILATE, linekernel) - # return linemade - - linecanny = cv2.Canny(linemade, 0, 500, None, 3) - linecontours, heirarchy = cv2.findContours(linecanny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - - # imgcopy = cv2.drawContours(imgcopy, linecontours, -1, color=(0,255,0), thickness=1) - # return imgcopy - # for i, contour in enumerate(linecontours): - # k = i+1 - # colour = ((k*23123)%255, (k*8654)%255, (k*45242)%255) - # imgcopy = cv2.drawContours(imgcopy, [contour], -1, colour, thickness=1) - # return imgcopy - - - - lineboxes = np.empty((len(linecontours), 4), dtype=int) - - for i, contour in enumerate(linecontours): - b = list(cv2.boundingRect(contour)) - # b[0] -= (kernel.shape[0]-1) - # b[1] -= (kernel.shape[1]-1) - # b[2] += (2*kernel.shape[0]-1) - # b[3] += (2*kernel.shape[1]-1) - lineboxes[i] = b - # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), (0,255,0), thickness=3) - # return imgcopy - - linelabels = dbscan(lineboxes, epsilonvalue, 1) - # print(linelabels) - numclusters = max(linelabels) - - letterboxesbyline = [[] for _ in range(numclusters)] - - for i, linebox in enumerate(lineboxes): - for j, letterbox in enumerate(letterboxes): - if containsamount(linebox, letterbox, 0.9): - letterboxesbyline[linelabels[i]-1].append(letterbox.tolist()) - - # print(len(letterboxesbyline)) - - - # # COLOUR THE RECTANGLES GROUPED - # for i, setofboxes in enumerate(letterboxesbyline): - # k = i+1 - # colour = ((k*23123)%255, (k*8654)%255, (k*45242)%255) - # # print(colour) - # # b = lineboxes[i] - # # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), colour, thickness=3) - # print(i) - # for b in setofboxes: - # print(i) - # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), colour, thickness=3) - # return imgcopy - - mergedboxes = np.empty((numclusters,4), dtype=int) - - tobedeleted = [] - - for i in range(numclusters): - b = mf.mergerects(letterboxesbyline[i]) - # if (b[0] == -1): - # tobedeleted.append(i) - mergedboxes[i] = b - - # if (tobedeleted != []): - # # print("hi") - # mergedboxes = np.delete(mergedboxes, tobedeleted, axis=0) - # letterboxesbyline = [ele for idx, ele in enumerate(letterboxesbyline) if idx not in tobedeleted] - - return mergedboxes, letterboxesbyline - -def sublinerectretriever(image, divider=2): - shape = image.shape - - imgcopy = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) - # return imgcopy - - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) - # reducedimage = image - reducedimage = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel, iterations=1) - # reducedimage = cv2.morphologyEx(reducedimage, cv2.MORPH_ERODE, kernel) - # return reducedimage - - canny = cv2.Canny(reducedimage, 0, 500, None, 3) - # return canny - - - contours, heirarchy = cv2.findContours(canny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # contours, heirarchy = cv2.findContours(255-reducedimage,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - - # imgcopy = cv2.drawContours(imgcopy, contours, -1, color=(0,255,0), thickness=1) - # return imgcopy - - boundingboxes = np.empty((len(contours), 4), dtype=int) - - for i, contour in enumerate(contours): - b = list(cv2.boundingRect(contour)) - b[0] -= (kernel.shape[0]-1) - b[1] -= (kernel.shape[1]-1) - b[2] += (2*kernel.shape[0]-1) - b[3] += (2*kernel.shape[1]-1) - boundingboxes[i] = b - # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), 128, thickness=3) - # return imgcopy - - epsilonvalue = np.median(boundingboxes, axis=0)[3]/divider - # print(epsilonvalue) - - labels = dbscan(boundingboxes, epsilonvalue, 1) - # print(labels) - numclusters = max(labels) - lineboxes = [[] for _ in range(numclusters)] - - for i, item in enumerate(labels): - lineboxes[item-1].append(boundingboxes[i].tolist()) - - - # # COLOUR THE RECTANGLES GROUPED - # for i, setofboxes in enumerate(lineboxes): - # k = i+1 - # colour = ((k*23123)%255, (k*8654)%255, (k*45242)%255) - # # print(colour) - # for b in setofboxes: - # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), colour, thickness=3) - # return imgcopy - - - mergedboxes = np.empty((numclusters,4), dtype=int) - - - for i in range(numclusters): - b = mf.mergerects(lineboxes[i]) - mergedboxes[i] = b - - j = 0 - while (j < len(mergedboxes)): - i = 0 - while (i < len(mergedboxes)): - if (i == j): - i += 1 - continue - outerbox = mergedboxes[j] - innerbox = mergedboxes[i] - if containsamount(outerbox, innerbox, 1) or aboveandbelow(outerbox, innerbox) or innerbox[3] < epsilonvalue: - mergedboxes = np.delete(mergedboxes, i, axis=0) - lineboxes.pop(i) - if (i < j): - j -= 1 - i -= 1 - i += 1 - j += 1 - - return mergedboxes, lineboxes - -def linerectretriever(image, divider=2, sublines=False): - if (sublines): - return sublinerectretriever(image, divider=divider) - else: - return l1linerectretriever(image, divider=divider) - -def lineimagemaker(thresholded, divider=2, sublines=False): - lineimages = [] - mergedboxes, originalboxes = linerectretriever(thresholded, divider=divider, sublines=sublines) - # print(mergedboxes) - # print(originalboxes) - # return thresholded - - mergedboxesordering = (mergedboxes[:,1]).argsort() # sorted by y value (aka lines from top to bottom) - # print(mergedboxesordering) - - goodpoint = 0 - for i, item in enumerate(mergedboxesordering): - if (mergedboxes[item][0] != -1): - goodpoint = i - break - mergedboxesordering = mergedboxesordering[goodpoint:] - - mergedboxes = mergedboxes[mergedboxesordering] - originalboxes = [originalboxes[i] for i in mergedboxesordering] - out = cv2.cvtColor(thresholded.copy(), cv2.COLOR_GRAY2BGR) - # lineimages.append(out) - for i, box in enumerate(mergedboxes): - # print(box) - mask = np.zeros(thresholded.shape, dtype=np.uint8) - whitebackground = np.full(thresholded.shape, fill_value=255, dtype=np.uint8) - # print(originalboxes[i]) - for lb in originalboxes[i]: - mask = cv2.rectangle(mask, (lb[0],lb[1]), (lb[0]+lb[2], lb[1]+lb[3]), (255,255,255), thickness=cv2.FILLED) - - # lineimages[0] = cv2.rectangle(lineimages[0], (box[0],box[1]), (box[0]+box[2], box[1]+box[3]), (0,255,0), thickness=1) - - invertedmask = cv2.bitwise_not(mask) - whitedscreen = cv2.bitwise_and(whitebackground, whitebackground, mask=invertedmask) - lineimage = cv2.bitwise_and(thresholded, thresholded, mask=mask) - lineimage = cv2.bitwise_or(whitedscreen, lineimage)[box[1]:box[1]+box[3], box[0]:box[0]+box[2]] - # lineimage = mf.externaldeskew(lineimage, fill=(255,255,255), alreadygray=True) - # lineimage = thresholded[box[1]:box[1]+box[3], box[0]:box[0]+box[2]] - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) - lineimage = cv2.morphologyEx(lineimage, cv2.MORPH_CLOSE, kernel, iterations=1) - lineimages.append(lineimage) - # lineimages.append(mask) - return lineimages - - - - - -def ismultiline(img): - kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) - reducedimage = cv2.morphologyEx(img, cv2.MORPH_DILATE, kernel) - # reducedimage = cv2.morphologyEx(reducedimage, cv2.MORPH_ERODE, kernel) - - canny = cv2.Canny(reducedimage, 0, 500, None, 3) - # return canny - - - contours, heirarchy = cv2.findContours(canny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - # imgcopy = cv2.drawContours(imgcopy, contours, -1, color=(0,255,0), thickness=1) - # return imgcopy - - boundingboxes = np.empty((len(contours), 4), dtype=int) - - for i, contour in enumerate(contours): - boundingboxes[i] = cv2.boundingRect(contour) - b = boundingboxes[i] - - # heightdetermination = np.median(boundingboxes, axis=0)[3] - heightdetermination = np.max(boundingboxes, axis=0)[3] - # print(heightdetermination) - - if (img.shape[0] > (heightdetermination*1.5) + (2*50)): - return True - return False - - - -### actual function -def lineisolator(image): - # imgcopy = image.copy() - gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) - # thresholded = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1] - # return gray - # return thresholded - thresholded = gray - - - # kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) - - - - lineimages = lineimagemaker(thresholded, 1.5, False) - - # for i, lineimage in enumerate(lineimages): - # lineimages[i] = cv2.morphologyEx(lineimage, cv2.MORPH_ERODE, kernel) - - - finallineimages = [] - - for i, lineimage in enumerate(lineimages): - # if (i == 0): - # finallineimages.append(lineimages[0]) - # continue - deskewedlineimage = minboxdeskew(lineimage, fill=255) - - # finallineimages.append(deskewedlineimage) - # print(deskewedlineimage.shape) - - if (ismultiline(deskewedlineimage)): - # print("hi" + str(i)) - templineimages = lineimagemaker(deskewedlineimage, 2.5, True) - else: - templineimages = lineimagemaker(deskewedlineimage, 1.5, True) - - # templineimages = lineimagemaker(deskewedlineimage, 2) - - finallineimages += templineimages - # finallineimages += templineimages[1:] - - for i, lineimage in enumerate(finallineimages): - deskewedli = minboxdeskew(lineimage, fill=255) - dim = int((deskewedli.shape[0]-100)//20) - # print(dim) - kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dim, dim)) - deskewedli = cv2.morphologyEx(deskewedli, cv2.MORPH_DILATE, kernel,iterations=1) - finallineimages[i] = cv2.morphologyEx(deskewedli, cv2.MORPH_OPEN, kernel) - - - # mergedboxes, originalboxes = linerectretriever(thresholded) - # mask = np.zeros(thresholded.shape, dtype=np.uint8) - # for i, box in enumerate(mergedboxes): - # for lb in originalboxes[i]: - # mask = cv2.rectangle(mask, (lb[0],lb[1]), (lb[0]+lb[2], lb[1]+lb[3]), (255,255,255), thickness=cv2.FILLED) - - # return mask - - - # out = tempfunc(thresholded) - # return out - - return finallineimages - - - \ No newline at end of file diff --git a/code/textdataretriever/textextractor/lineisolatortesting.ipynb b/code/textdataretriever/textextractor/lineisolatortesting.ipynb deleted file mode 100644 index 0c7574a..0000000 --- a/code/textdataretriever/textextractor/lineisolatortesting.ipynb +++ /dev/null @@ -1,511 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import cv2\n", - "import numpy as np\n", - "\n", - "\n", - "import scipy.stats as st\n", - "import math\n", - "\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.10/dist-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n", - "/usr/local/lib/python3.10/dist-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().\n", - " warnings.warn(_BETA_TRANSFORMS_WARNING)\n" - ] - } - ], - "source": [ - "import sys\n", - "sys.path.insert(0, '../../autocropper')\n", - "import myfunctions as mf\n", - "\n", - "import extractorfunctions as ef\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "pathname = \"../test_images/\"\n", - "filename = \"IMG_7640.jpg\"\n", - "# pathname = \"../temp/\"\n", - "# filename = \"test.jpg\"\n", - "# pathname = \"../result_images/\"\n", - "# filename = \"13.jpg\"\n", - "\n", - "# print(pathname+filename)\n", - "img = cv2.imread(pathname+filename)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# import easyocr\n", - "# reader = easyocr.Reader(['en'])" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "def l1linerectretriever(image, divider=2):\n", - " shape = image.shape\n", - "\n", - " imgcopy = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)\n", - " # return imgcopy\n", - " \n", - " kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))\n", - " linekernel = cv2.getStructuringElement(cv2.MORPH_RECT, (shape[1]//40, 1))\n", - " # reducedimage = image\n", - " reducedimage = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel, iterations=1)\n", - " # reducedimage = cv2.morphologyEx(reducedimage, cv2.MORPH_ERODE, kernel)\n", - " # return reducedimage\n", - " \n", - " charcanny = cv2.Canny(reducedimage, 0, 500, None, 3)\n", - " # return canny\n", - " \n", - " \n", - " lettercontours, heirarchy = cv2.findContours(charcanny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " # contours, heirarchy = cv2.findContours(255-reducedimage,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - "\n", - " # imgcopy = cv2.drawContours(imgcopy, lettercontours, -1, color=(0,255,0), thickness=1)\n", - " # return imgcopy\n", - "\n", - " letterboxes = np.empty((len(lettercontours), 4), dtype=int)\n", - " \n", - " for i, contour in enumerate(lettercontours):\n", - " b = list(cv2.boundingRect(contour))\n", - " # b[0] -= (kernel.shape[0]-1)\n", - " # b[1] -= (kernel.shape[1]-1)\n", - " # b[2] += (2*kernel.shape[0]-1)\n", - " # b[3] += (2*kernel.shape[1]-1)\n", - " letterboxes[i] = b\n", - " # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), 128, thickness=3)\n", - " # return imgcopy\n", - " \n", - " epsilonvalue = np.median(letterboxes, axis=0)[3]/divider\n", - " # print(epsilonvalue)\n", - "\n", - "\n", - "\n", - " linemade = 255-cv2.morphologyEx(255-image, cv2.MORPH_DILATE, linekernel)\n", - " # return linemade\n", - "\n", - " linecanny = cv2.Canny(linemade, 0, 500, None, 3)\n", - " linecontours, heirarchy = cv2.findContours(linecanny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - "\n", - " # imgcopy = cv2.drawContours(imgcopy, linecontours, -1, color=(0,255,0), thickness=1)\n", - " # return imgcopy\n", - " # for i, contour in enumerate(linecontours):\n", - " # k = i+1\n", - " # colour = ((k*23123)%255, (k*8654)%255, (k*45242)%255)\n", - " # imgcopy = cv2.drawContours(imgcopy, [contour], -1, colour, thickness=1)\n", - " # return imgcopy\n", - "\n", - "\n", - "\n", - " lineboxes = np.empty((len(linecontours), 4), dtype=int)\n", - " \n", - " for i, contour in enumerate(linecontours):\n", - " b = list(cv2.boundingRect(contour))\n", - " # b[0] -= (kernel.shape[0]-1)\n", - " # b[1] -= (kernel.shape[1]-1)\n", - " # b[2] += (2*kernel.shape[0]-1)\n", - " # b[3] += (2*kernel.shape[1]-1)\n", - " lineboxes[i] = b\n", - " # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), (0,255,0), thickness=3)\n", - " # return imgcopy\n", - "\n", - " linelabels = ef.dbscan(lineboxes, epsilonvalue, 1)\n", - " # print(linelabels)\n", - " numclusters = max(linelabels)\n", - "\n", - " letterboxesbyline = [[] for _ in range(numclusters)]\n", - "\n", - " for i, linebox in enumerate(lineboxes):\n", - " for j, letterbox in enumerate(letterboxes):\n", - " if ef.containsamount(linebox, letterbox, 0.9):\n", - " letterboxesbyline[linelabels[i]-1].append(letterbox.tolist())\n", - "\n", - " # print(len(letterboxesbyline))\n", - "\n", - "\n", - " # # COLOUR THE RECTANGLES GROUPED\n", - " # for i, setofboxes in enumerate(letterboxesbyline):\n", - " # k = i+1\n", - " # colour = ((k*23123)%255, (k*8654)%255, (k*45242)%255)\n", - " # # print(colour)\n", - " # # b = lineboxes[i]\n", - " # # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), colour, thickness=3)\n", - " # print(i)\n", - " # for b in setofboxes:\n", - " # print(i)\n", - " # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), colour, thickness=3)\n", - " # return imgcopy\n", - "\n", - " mergedboxes = np.empty((numclusters,4), dtype=int)\n", - "\n", - " tobedeleted = []\n", - "\n", - " for i in range(numclusters):\n", - " b = mf.mergerects(letterboxesbyline[i])\n", - " # if (b[0] == -1):\n", - " # tobedeleted.append(i)\n", - " mergedboxes[i] = b\n", - "\n", - " # if (tobedeleted != []):\n", - " # # print(\"hi\")\n", - " # mergedboxes = np.delete(mergedboxes, tobedeleted, axis=0)\n", - " # letterboxesbyline = [ele for idx, ele in enumerate(letterboxesbyline) if idx not in tobedeleted]\n", - "\n", - " return mergedboxes, letterboxesbyline\n", - "\n", - "\n", - "\n", - "def sublinerectretriever(image, divider=2):\n", - " shape = image.shape\n", - " \n", - " imgcopy = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)\n", - " # return imgcopy\n", - " \n", - " kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))\n", - " # reducedimage = image\n", - " reducedimage = cv2.morphologyEx(image, cv2.MORPH_DILATE, kernel, iterations=1)\n", - " # reducedimage = cv2.morphologyEx(reducedimage, cv2.MORPH_ERODE, kernel)\n", - " # return reducedimage\n", - " \n", - " canny = cv2.Canny(reducedimage, 0, 500, None, 3)\n", - " # return canny\n", - " \n", - " \n", - " contours, heirarchy = cv2.findContours(canny,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - " # contours, heirarchy = cv2.findContours(255-reducedimage,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n", - "\n", - " # imgcopy = cv2.drawContours(imgcopy, contours, -1, color=(0,255,0), thickness=1)\n", - " # return imgcopy\n", - "\n", - " boundingboxes = np.empty((len(contours), 4), dtype=int)\n", - " \n", - " for i, contour in enumerate(contours):\n", - " b = list(cv2.boundingRect(contour))\n", - " b[0] -= (kernel.shape[0]-1)\n", - " b[1] -= (kernel.shape[1]-1)\n", - " b[2] += (2*kernel.shape[0]-1)\n", - " b[3] += (2*kernel.shape[1]-1)\n", - " boundingboxes[i] = b\n", - " # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), 128, thickness=3)\n", - " # return imgcopy\n", - " \n", - " epsilonvalue = np.median(boundingboxes, axis=0)[3]/divider\n", - " # print(epsilonvalue)\n", - " \n", - " labels = ef.dbscan(boundingboxes, epsilonvalue, 1)\n", - " # print(labels)\n", - " numclusters = max(labels)\n", - " lineboxes = [[] for _ in range(numclusters)]\n", - "\n", - " for i, item in enumerate(labels):\n", - " lineboxes[item-1].append(boundingboxes[i].tolist())\n", - " \n", - " \n", - " # # COLOUR THE RECTANGLES GROUPED\n", - " # for i, setofboxes in enumerate(lineboxes):\n", - " # k = i+1\n", - " # colour = ((k*23123)%255, (k*8654)%255, (k*45242)%255)\n", - " # # print(colour)\n", - " # for b in setofboxes:\n", - " # imgcopy = cv2.rectangle(imgcopy, (b[0],b[1]), (b[0]+b[2], b[1]+b[3]), colour, thickness=3)\n", - " # return imgcopy\n", - " \n", - " \n", - " mergedboxes = np.empty((numclusters,4), dtype=int)\n", - " \n", - " \n", - " for i in range(numclusters):\n", - " b = mf.mergerects(lineboxes[i])\n", - " mergedboxes[i] = b\n", - " \n", - " j = 0\n", - " while (j < len(mergedboxes)):\n", - " i = 0\n", - " while (i < len(mergedboxes)):\n", - " if (i == j):\n", - " i += 1\n", - " continue\n", - " outerbox = mergedboxes[j]\n", - " innerbox = mergedboxes[i]\n", - " if ef.containsamount(outerbox, innerbox, 1) or ef.aboveandbelow(outerbox, innerbox) or innerbox[3] < epsilonvalue:\n", - " mergedboxes = np.delete(mergedboxes, i, axis=0)\n", - " lineboxes.pop(i)\n", - " if (i < j):\n", - " j -= 1\n", - " i -= 1\n", - " i += 1\n", - " j += 1\n", - " \n", - " return mergedboxes, lineboxes\n", - "\n", - "def linerectretriever(image, divider=2, sublines=False):\n", - "\n", - " if (sublines):\n", - " return sublinerectretriever(image, divider=divider)\n", - " else:\n", - " return l1linerectretriever(image, divider=divider)\n", - "\n", - "\n", - "def lineimagemaker(thresholded, divider=2, sublines=False):\n", - " lineimages = []\n", - " mergedboxes, originalboxes = linerectretriever(thresholded, divider=divider, sublines=sublines)\n", - " # print(mergedboxes)\n", - " # print(originalboxes)\n", - " # return thresholded\n", - " \n", - " mergedboxesordering = (mergedboxes[:,1]).argsort() # sorted by y value (aka lines from top to bottom)\n", - " # print(mergedboxesordering)\n", - " \n", - " goodpoint = 0\n", - " for i, item in enumerate(mergedboxesordering):\n", - " if (mergedboxes[item][0] != -1):\n", - " goodpoint = i\n", - " break\n", - " mergedboxesordering = mergedboxesordering[goodpoint:]\n", - "\n", - " mergedboxes = mergedboxes[mergedboxesordering]\n", - " originalboxes = [originalboxes[i] for i in mergedboxesordering]\n", - " out = cv2.cvtColor(thresholded.copy(), cv2.COLOR_GRAY2BGR)\n", - " # lineimages.append(out)\n", - " for i, box in enumerate(mergedboxes):\n", - " # print(box)\n", - " mask = np.zeros(thresholded.shape, dtype=np.uint8)\n", - " whitebackground = np.full(thresholded.shape, fill_value=255, dtype=np.uint8)\n", - " # print(originalboxes[i])\n", - " for lb in originalboxes[i]:\n", - " mask = cv2.rectangle(mask, (lb[0],lb[1]), (lb[0]+lb[2], lb[1]+lb[3]), (255,255,255), thickness=cv2.FILLED)\n", - "\n", - " # lineimages[0] = cv2.rectangle(lineimages[0], (box[0],box[1]), (box[0]+box[2], box[1]+box[3]), (0,255,0), thickness=1)\n", - "\n", - " invertedmask = cv2.bitwise_not(mask)\n", - " whitedscreen = cv2.bitwise_and(whitebackground, whitebackground, mask=invertedmask)\n", - " lineimage = cv2.bitwise_and(thresholded, thresholded, mask=mask)\n", - " lineimage = cv2.bitwise_or(whitedscreen, lineimage)[box[1]:box[1]+box[3], box[0]:box[0]+box[2]]\n", - " # lineimage = mf.externaldeskew(lineimage, fill=(255,255,255), alreadygray=True)\n", - " # lineimage = thresholded[box[1]:box[1]+box[3], box[0]:box[0]+box[2]]\n", - " kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))\n", - " lineimage = cv2.morphologyEx(lineimage, cv2.MORPH_CLOSE, kernel, iterations=1)\n", - " lineimages.append(lineimage)\n", - " # lineimages.append(mask)\n", - " return lineimages\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "def lineisolator(image):\n", - " # imgcopy = image.copy()\n", - " gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n", - " # thresholded = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]\n", - " # return gray\n", - " # return thresholded\n", - " thresholded = gray\n", - " \n", - " \n", - " # kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))\n", - " \n", - " \n", - " \n", - " lineimages = lineimagemaker(thresholded, 1.5, False)\n", - " \n", - " # for i, lineimage in enumerate(lineimages):\n", - " # lineimages[i] = cv2.morphologyEx(lineimage, cv2.MORPH_ERODE, kernel)\n", - "\n", - " \n", - " finallineimages = []\n", - " \n", - " for i, lineimage in enumerate(lineimages):\n", - " # if (i == 0):\n", - " # finallineimages.append(lineimages[0])\n", - " # continue\n", - " deskewedlineimage = ef.minboxdeskew(lineimage, fill=255)\n", - "\n", - " # finallineimages.append(deskewedlineimage)\n", - " # print(deskewedlineimage.shape)\n", - "\n", - " if (ef.ismultiline(deskewedlineimage)):\n", - " # print(\"hi\" + str(i))\n", - " templineimages = lineimagemaker(deskewedlineimage, 2.5, True)\n", - " else:\n", - " templineimages = lineimagemaker(deskewedlineimage, 1.5, True)\n", - "\n", - " # templineimages = lineimagemaker(deskewedlineimage, 2)\n", - "\n", - " finallineimages += templineimages\n", - " # finallineimages += templineimages[1:]\n", - "\n", - " for i, lineimage in enumerate(finallineimages):\n", - " deskewedli = ef.minboxdeskew(lineimage, fill=255)\n", - " dim = int((deskewedli.shape[0]-100)//20)\n", - " # print(dim)\n", - " kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (dim, dim))\n", - " deskewedli = cv2.morphologyEx(deskewedli, cv2.MORPH_DILATE, kernel,iterations=1)\n", - " finallineimages[i] = cv2.morphologyEx(deskewedli, cv2.MORPH_OPEN, kernel)\n", - " \n", - " \n", - " # mergedboxes, originalboxes = linerectretriever(thresholded) \n", - " # mask = np.zeros(thresholded.shape, dtype=np.uint8)\n", - " # for i, box in enumerate(mergedboxes):\n", - " # for lb in originalboxes[i]:\n", - " # mask = cv2.rectangle(mask, (lb[0],lb[1]), (lb[0]+lb[2], lb[1]+lb[3]), (255,255,255), thickness=cv2.FILLED)\n", - "\n", - " # return mask\n", - " \n", - " \n", - " # out = tempfunc(thresholded)\n", - " # return out\n", - " \n", - " return finallineimages" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# result = reader.readtext(pathname+filename)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# print(result)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "bing = mf.houghlineprocessing(img)\n", - "# outs = bing\n", - "outs = ef.lineisolator(bing)\n", - "# # gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n", - "# # outs = linerectretriever(gray)\n", - "# outs = getSkewAngle(img)\n", - "# outs = minboxdeskew(img, fill=(255,255,255))\n", - "# bing = cv2.cvtColor(bing, cv2.COLOR_BGR2GRAY)\n", - "# bing = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n", - "# outs = bing\n", - "# outs = linerectretriever(bing, 1.5, False)\n", - "# outs = lineimagemaker(bing, 1.5, False)\n", - "# for i, _ in enumerate(outs):\n", - "# outs[i] = ef.minboxdeskew(outs[i], fill=255)\n", - "\n", - "# outs = img" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# print(outs)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# for out in outs:\n", - "# if (out.shape[0] > out.shape[1]):\n", - "# cv2.imshow(\"test1\", mf.ResizeWithAspectRatio(out, height=1000))\n", - "# else:\n", - "# cv2.imshow(\"test1\", mf.ResizeWithAspectRatio(out, width=1000))\n", - "# key = cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()\n", - "# if (key == 107):\n", - "# break\n", - "if (isinstance(outs, np.ndarray)):\n", - " if (outs.shape[0] > outs.shape[1]):\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(outs, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(outs, width=1000))\n", - "else:\n", - " for i, out in enumerate(outs):\n", - " # cv2.imwrite(\"../result_images/\"+str(i)+\".jpg\", out)\n", - " if (out.shape[0] > out.shape[1]):\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, width=1000))\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "# cv2.imwrite(\"../temp/test.jpg\", outs[2])" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/textdataretriever/textextractor/modelimp.ipynb b/code/textdataretriever/textextractor/modelimp.ipynb deleted file mode 100644 index c378705..0000000 --- a/code/textdataretriever/textextractor/modelimp.ipynb +++ /dev/null @@ -1,260 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 83, - "metadata": {}, - "outputs": [], - "source": [ - "# https://github.com/NielsRogge/Transformers-Tutorials/blob/master/TrOCR/Inference_with_TrOCR_%2B_Gradio_demo.ipynb\n", - "# https://github.com/NielsRogge/Transformers-Tutorials/tree/master/TrOCR\n", - "# https://huggingface.co/docs/transformers/model_doc/trocr" - ] - }, - { - "cell_type": "code", - "execution_count": 84, - "metadata": {}, - "outputs": [], - "source": [ - "from transformers import TrOCRProcessor\n", - "from transformers import VisionEncoderDecoderModel\n", - "\n", - "from PIL import Image\n", - "import torch" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "metadata": {}, - "outputs": [], - "source": [ - "import sys\n", - "sys.path.insert(0, '../../autocropper')\n", - "import myfunctions as mf\n", - "\n", - "import extractorfunctions as ef\n", - "import cv2" - ] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Could not find image processor class in the image processor config or the model config. Loading based on pattern matching with the model's feature extractor configuration.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Some weights of VisionEncoderDecoderModel were not initialized from the model checkpoint at microsoft/trocr-small-printed and are newly initialized: ['encoder.pooler.dense.bias', 'encoder.pooler.dense.weight']\n", - "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n" - ] - } - ], - "source": [ - "processor = TrOCRProcessor.from_pretrained('microsoft/trocr-small-printed')\n", - "model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-small-printed')" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [], - "source": [ - "device = torch.device(\"cpu\")\n", - "if torch.cuda.is_available:\n", - " device = torch.device(\"cuda:0\")\n", - " \n", - "model = model.to(device)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "metadata": {}, - "outputs": [], - "source": [ - "filename = \"IMG_7640.jpg\"\n", - "pathname = \"../test_images/\"" - ] - }, - { - "cell_type": "code", - "execution_count": 89, - "metadata": {}, - "outputs": [], - "source": [ - "img = cv2.imread(pathname+filename)" - ] - }, - { - "cell_type": "code", - "execution_count": 90, - "metadata": {}, - "outputs": [], - "source": [ - "clarified = mf.houghlineprocessing(img)\n", - "lineimages = ef.lineisolator(clarified)" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "metadata": {}, - "outputs": [], - "source": [ - "# print(len(lineimages))" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [], - "source": [ - "PILversions = []\n", - "for line in lineimages:\n", - " rgbline = cv2.cvtColor(line, cv2.COLOR_GRAY2RGB)\n", - " PILversions.append(Image.fromarray(rgbline))" - ] - }, - { - "cell_type": "code", - "execution_count": 100, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "" - ] - }, - "execution_count": 100, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# PILversions[9]" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [], - "source": [ - "# image = Image.open(\"../result_images/6.jpg\").convert(\"RGB\")\n", - "# image" - ] - }, - { - "cell_type": "code", - "execution_count": 95, - "metadata": {}, - "outputs": [], - "source": [ - "# pixel_values = processor(image, return_tensors=\"pt\").pixel_values\n", - "# # print(pixel_values.shape)\n", - "# # print(image)\n", - "# # print(pixel_values)" - ] - }, - { - "cell_type": "code", - "execution_count": 96, - "metadata": {}, - "outputs": [], - "source": [ - "# pixel_values = processor(image, return_tensors=\"pt\").pixel_values\n", - "# # print(pixel_values.shape)\n", - "# generated_ids = model.generate(pixel_values)\n", - "# generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]\n", - "# print(generated_text)" - ] - }, - { - "cell_type": "code", - "execution_count": 97, - "metadata": {}, - "outputs": [], - "source": [ - "finalstring = \"\"" - ] - }, - { - "cell_type": "code", - "execution_count": 98, - "metadata": {}, - "outputs": [], - "source": [ - "for image in PILversions:\n", - " pixel_values = processor(image, return_tensors=\"pt\").pixel_values\n", - " pixel_values = pixel_values.to(device)\n", - " generated_ids = model.generate(pixel_values)\n", - " generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]\n", - " finalstring = finalstring + generated_text + \"\\n\"\n", - " # print(generated_text)" - ] - }, - { - "cell_type": "code", - "execution_count": 99, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "WALKER'S\n", - "CHOCOLATES\n", - "NO RETURNS OR EXCHANGES\n", - "ON FOOD ITEMS.\n", - "REG 09-22-2023 12:08\n", - "000021\n", - "1 BAKING NT $14.40\n", - "TL $14.40\n", - "CREDIT : $14.40\n", - "LIFE S SHORT\n", - "EAT CHOCOLATE\n", - "\n" - ] - } - ], - "source": [ - "print(finalstring)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/code/textdataretriever/textextractor/temp.ipynb b/code/textdataretriever/textextractor/temp.ipynb deleted file mode 100644 index 5c04f85..0000000 --- a/code/textdataretriever/textextractor/temp.ipynb +++ /dev/null @@ -1,224 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import cv2\n", - "import numpy as np\n", - "\n", - "\n", - "import scipy.stats as st\n", - "import math\n", - "\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import sys\n", - "sys.path.insert(0, '../../autocropper')\n", - "import myfunctions as mf\n", - "\n", - "import extractorfunctions as ef\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# pathname = \"../test_images/\"\n", - "pathname = \"../result_images/\"\n", - "filename = \"13.jpg\"\n", - "\n", - "# print(pathname+filename)\n", - "img = cv2.imread(pathname+filename)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# import easyocr\n", - "# reader = easyocr.Reader(['en'])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def padWithColour(img, hpadding=0, vpadding=0, fill=(0,0,0)):\n", - " borderType = cv2.BORDER_CONSTANT\n", - " out = cv2.copyMakeBorder(img, vpadding, vpadding, hpadding, hpadding, borderType, None, fill)\n", - " return out\n", - "\n", - "def mergecontours(contours):\n", - " cont = np.vstack(contours)\n", - " finalcontour = cv2.convexHull(cont)\n", - " return finalcontour" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def getSkewAngle(cvImage) -> float:\n", - " # Prep image, copy, convert to gray scale, blur, and threshold\n", - " newImage = padWithColour(cvImage, hpadding=50, vpadding=50, fill=(255,255,255))\n", - " # return newImage\n", - " gray = cv2.cvtColor(newImage, cv2.COLOR_BGR2GRAY)\n", - " blur = cv2.GaussianBlur(gray, (9, 9), 0)\n", - " thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]\n", - "\n", - " # Apply dilate to merge text into meaningful lines/paragraphs.\n", - " # Use larger kernel on X axis to merge characters into single line, cancelling out any spaces.\n", - " # But use smaller kernel on Y axis to separate between different blocks of text\n", - " kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (10, 5))\n", - " dilate = cv2.dilate(thresh, kernel, iterations=5)\n", - " # return dilate\n", - "\n", - " # Find all contours\n", - " contours, hierarchy = cv2.findContours(dilate, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)\n", - " contours = sorted(contours, key = cv2.contourArea, reverse = True)\n", - "\n", - " # Find largest contour and surround in min area box\n", - " largestContour = contours[0]\n", - "\n", - " mergedcontour = mergecontours(contours)\n", - "\n", - " # return cv2.drawContours(newImage, [mergedcontour], -1, (0,255,0), thickness=3)\n", - " minAreaRect = cv2.minAreaRect(mergedcontour)\n", - " # return cv2.drawContours(newImage, [largestContour], -1, (0,255,0), thickness=3)\n", - " # minAreaRect = cv2.minAreaRect(largestContour)\n", - "\n", - " box = cv2.boxPoints(minAreaRect)\n", - " box = np.intp(box) \n", - " newImage = cv2.drawContours(newImage, [box], -1, (0,255,0), thickness=3)\n", - " # return newImage\n", - "\n", - " # Determine the angle. Convert it to the value that was originally used to obtain skewed image\n", - " angle = minAreaRect[-1]\n", - " print(angle)\n", - " if angle > 45:\n", - " angle = angle - 90\n", - " if angle < -45:\n", - " angle = 90 + angle\n", - " print(angle)\n", - " return angle\n", - "\n", - "def minboxdeskew(img, fill=(0,0,0)):\n", - " angle = getSkewAngle(img)\n", - " rotated = mf.rotate(img, angle, fill=fill)\n", - " return rotated" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# result = reader.readtext(pathname+filename)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# print(result)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# outs = ef.lineisolator(img)\n", - "# # gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n", - "# # outs = linerectretriever(gray)\n", - "# outs = getSkewAngle(img)\n", - "outs = minboxdeskew(img, fill=(255,255,255))\n", - "# outs = img" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# print(outs)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# for out in outs:\n", - "# if (out.shape[0] > out.shape[1]):\n", - "# cv2.imshow(\"test1\", mf.ResizeWithAspectRatio(out, height=1000))\n", - "# else:\n", - "# cv2.imshow(\"test1\", mf.ResizeWithAspectRatio(out, width=1000))\n", - "# key = cv2.waitKey(0)\n", - "# cv2.destroyAllWindows()\n", - "# if (key == 107):\n", - "# break\n", - "if (isinstance(outs, np.ndarray)):\n", - " if (outs.shape[0] > outs.shape[1]):\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(outs, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\", mf.ResizeWithAspectRatio(outs, width=1000))\n", - "else:\n", - " for i, out in enumerate(outs):\n", - " cv2.imwrite(\"../result_images/\"+str(i)+\".jpg\", out)\n", - " if (out.shape[0] > out.shape[1]):\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, height=1350))\n", - " else:\n", - " cv2.imshow(\"test\"+str(i), mf.ResizeWithAspectRatio(out, width=1000))\n", - "cv2.waitKey(0)\n", - "cv2.destroyAllWindows()\n", - "\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docker/appdockerfile b/docker/appdockerfile deleted file mode 100644 index 9117db2..0000000 --- a/docker/appdockerfile +++ /dev/null @@ -1,51 +0,0 @@ - - -FROM ubuntu:22.04 - -# this is for timezone config -ENV DEBIAN_FRONTEND=noninteractive -ENV TZ=America/Toronto -RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone - - -#-y is for accepting yes when the system asked us for installing the package -RUN apt-get update && \ - apt-get install -y build-essential cmake git gdb pkg-config valgrind systemd-coredump python3-dev && \ - apt-get -y clean && apt-get -y autoremove - -RUN apt-get install -y ca-certificates curl gnupg && mkdir -p /etc/apt/keyrings && \ - curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg && \ - NODE_MAJOR=20 && echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_$NODE_MAJOR.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list && \ - apt-get update && apt-get install nodejs -y && npm install -g npm@latest - - -# RUN apt-get install -y nodejs npm && apt-get -y clean && apt-get -y autoremove - -# RUN npm i -g expo-cli - -# NEEDED TO BUILD OPENCV IN ENV *****************START***************** - -# RUN apt-get install -y build-essential cmake git gdb pkg-config valgrind systemd-coredump libfftw3-dev libgtk2.0-dev - -# RUN git clone https://github.com/opencv/opencv.git && \ -# cd /opencv && mkdir build && cd build && \ -# cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local .. && \ -# make -j"$(nproc)" && \ -# make install && \ -# rm -rf /opencv - -# NEEDED TO BUILD OPENCV IN ENV *****************END***************** - - - -# # 1) google benchmark -# RUN echo "************************ google benchmark ************************" -# RUN git clone https://github.com/google/benchmark -# RUN mkdir -p benchmark/build && cd benchmark/build -# WORKDIR "benchmark/build" -# #RUN cmake -DCMAKE_CXX_FLAGS=-std=c++1z -DGOOGLETEST_PATH=../../googletest -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON ../ && cmake --build . --parallel && cmake --install . -# RUN cmake -DCMAKE_CXX_FLAGS=-std=c++1z -DBENCHMARK_DOWNLOAD_DEPENDENCIES=TRUE -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON ../ && cmake --build . --parallel && cmake --install . -# WORKDIR "/" -# RUN rm -rf benchmark - - diff --git a/docker/autocropperdockerfile b/docker/autocropperdockerfile deleted file mode 100644 index 2f3dbfe..0000000 --- a/docker/autocropperdockerfile +++ /dev/null @@ -1,52 +0,0 @@ - - -FROM ubuntu:22.04 - -# this is for timezone config -ENV DEBIAN_FRONTEND=noninteractive -ENV TZ=America/Toronto -RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone - - -#-y is for accepting yes when the system asked us for installing the package -## removed libglib2.0-0 libfftw3-dev -RUN apt-get update && \ - apt-get install -y build-essential cmake git gdb pkg-config valgrind systemd-coredump python3-opencv libopencv-dev python3-pip python3-dev && \ - apt-get -y clean && apt-get -y autoremove - -RUN python3 -m pip install --upgrade pip - -RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 - -RUN pip3 install datasets && pip3 install jupyter notebook && pip3 install matplotlib && pip3 install deskew - -ENV HF_DATASETS_CACHE="/mnt/code/.cache/datasets" -ENV TORCH_HOME="/mnt/code/.cache/torch" - - -# NEEDED TO BUILD OPENCV IN ENV *****************START***************** - -# RUN apt-get install -y build-essential cmake git gdb pkg-config valgrind systemd-coredump libfftw3-dev libgtk2.0-dev - -# RUN git clone https://github.com/opencv/opencv.git && \ -# cd /opencv && mkdir build && cd build && \ -# cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local .. && \ -# make -j"$(nproc)" && \ -# make install && \ -# rm -rf /opencv - -# NEEDED TO BUILD OPENCV IN ENV *****************END***************** - - - -# # 1) google benchmark -# RUN echo "************************ google benchmark ************************" -# RUN git clone https://github.com/google/benchmark -# RUN mkdir -p benchmark/build && cd benchmark/build -# WORKDIR "benchmark/build" -# #RUN cmake -DCMAKE_CXX_FLAGS=-std=c++1z -DGOOGLETEST_PATH=../../googletest -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON ../ && cmake --build . --parallel && cmake --install . -# RUN cmake -DCMAKE_CXX_FLAGS=-std=c++1z -DBENCHMARK_DOWNLOAD_DEPENDENCIES=TRUE -DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=ON ../ && cmake --build . --parallel && cmake --install . -# WORKDIR "/" -# RUN rm -rf benchmark - - diff --git a/docker/librariesdockerfile b/docker/librariesdockerfile deleted file mode 100644 index 31dc443..0000000 --- a/docker/librariesdockerfile +++ /dev/null @@ -1,20 +0,0 @@ - -FROM ubuntu:22.04 - -# this is for timezone config -ENV DEBIAN_FRONTEND=noninteractive -ENV TZ=America/Toronto -RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone - - -#-y is for accepting yes when the system asked us for installing the package -RUN apt-get update && \ - apt-get install -y build-essential cmake git gdb pkg-config valgrind systemd-coredump python3-opencv libopencv-dev python3-pip python3-dev && \ - apt-get -y clean && apt-get -y autoremove - -RUN pip3 install jupyter notebook - - -RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 -RUN pip3 install matplotlib && pip3 install deskew - diff --git a/docker/textextractordockerfile b/docker/textextractordockerfile deleted file mode 100644 index d6209e4..0000000 --- a/docker/textextractordockerfile +++ /dev/null @@ -1,29 +0,0 @@ - - -FROM ubuntu:22.04 - -# this is for timezone config -ENV DEBIAN_FRONTEND=noninteractive -ENV TZ=America/Toronto -RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone - - -#-y is for accepting yes when the system asked us for installing the package -RUN apt-get update && \ - apt-get install -y build-essential cmake git gdb pkg-config valgrind systemd-coredump python3 python3-opencv libopencv-dev python3-pip && \ - apt-get -y clean && apt-get -y autoremove - -RUN python3 -m pip install --upgrade pip - -RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 - -RUN pip3 install -q transformers && pip3 install sentencepiece && pip3 install protobuf - -RUN pip3 install datasets && pip3 install jupyter notebook && pip3 install matplotlib && pip3 install deskew - -RUN pip3 install easyocr && pip3 uninstall -y opencv-python-headless - -ENV HF_DATASETS_CACHE="/mnt/code/.cache/datasets" -ENV TORCH_HOME="/mnt/code/.cache/torch" -ENV TRANSFORMERS_CACHE="/mnt/code/.cache/transformers" - diff --git a/helpful_links.md b/helpful_links.md deleted file mode 100644 index 6debeea..0000000 --- a/helpful_links.md +++ /dev/null @@ -1,97 +0,0 @@ -OpenCV Modifiers: -https://docs.opencv.org/3.4/d4/d1b/tutorial_histogram_equalization.html -https://stackoverflow.com/questions/39308030/how-do-i-increase-the-contrast-of-an-image-in-python-opencv -https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html -https://docs.opencv.org/4.x/d7/d1b/group__imgproc__misc.html#ggaa9e58d2860d4afa658ef70a9b1115576a0e50a338a4b711a8c48f06a6b105dd98 -https://docs.opencv.org/4.x/d7/d4d/tutorial_py_thresholding.html -https://docs.opencv.org/4.x/d9/d61/tutorial_py_morphological_ops.html -https://docs.opencv.org/4.x/d9/d8b/tutorial_py_contours_hierarchy.html -https://stackoverflow.com/questions/4292249/automatic-calculation-of-low-and-high-thresholds-for-the-canny-operation-in-open -https://stackabuse.com/opencv-thresholding-in-python-with-cv2threshold/ -https://stackoverflow.com/questions/70300189/how-to-keep-only-black-color-text-in-the-image-using-opencv-python -https://stackoverflow.com/questions/50210304/change-the-colors-within-certain-range-to-another-color-using-opencv -https://answers.opencv.org/question/231191/detect-all-black-pixels-inside-a-surrounded-closed-white-area/ - -OpenCV removing straight lines: -https://www.appsloveworld.com/opencv/100/83/remove-straight-lines-from-an-image -https://docs.opencv.org/3.4/df/d3d/tutorial_py_inpainting.html -https://stackoverflow.com/questions/22081908/how-to-determine-the-width-of-the-lines -https://www.google.com/search?q=determine+the+thickness+of+a+line+opencv&rlz=1C1CHBF_enCA1042CA1042&oq=determine+the+thickness+of+a+line+opencv&gs_lcrp=EgZjaHJvbWUyBggAEEUYOdIBCTEzNzY3ajBqMagCALACAA&sourceid=chrome&ie=UTF-8 - -numpy array sorting: -https://stackoverflow.com/questions/12877764/numpy-sort-by-key-function - - -Random OCR/Opencv idea link: -https://pyimagesearch.com/2020/09/21/opencv-automatic-license-number-plate-recognition-anpr-with-python/ - - -DBScan from scratch: -https://scrunts23.medium.com/dbscan-algorithm-from-scratch-in-python-475b82e0571c -https://github.com/scrunts23/CS-Data-Science-Build-Week-1/blob/master/model/dbscan.py - - -Dewarping: -https://www.google.com/search?q=ocr+preprocessing+dewarping+technique&sca_esv=575939874&rlz=1C1CHBF_enCA1042CA1042&ei=fwU3Zc_1DbzG0PEP8JqS2AY&ved=0ahUKEwiPsYL9rI2CAxU8IzQIHXCNBGsQ4dUDCBA&uact=5&oq=ocr+preprocessing+dewarping+technique&gs_lp=Egxnd3Mtd2l6LXNlcnAiJW9jciBwcmVwcm9jZXNzaW5nIGRld2FycGluZyB0ZWNobmlxdWUyBRAhGKABSNQ_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&sclient=gws-wiz-serp -https://www.sciencedirect.com/science/article/pii/S1877050914013787?ref=pdf_download&fr=RR-2&rr=81ade81d3b44a22f -https://pdf.sciencedirectassets.com/280203/1-s2.0-S1877050910X00047/1-s2.0-S187705091000373X/main.pdf?X-Amz-Security-Token=IQoJb3JpZ2luX2VjEGcaCXVzLWVhc3QtMSJHMEUCIFu4Xcnb89uX05vGUFvLuYtXFkB4zEm3KthkS6WQC84lAiEA%2BfaxLUo3qnMIDznl%2F1Z8nuT4nYq2x2R8xtM9vizqB%2FAquwUIkP%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FARAFGgwwNTkwMDM1NDY4NjUiDDD0O8JjINDXsH1j5yqPBQxpo0dvDtwGzFPebXNBUY9ExbYgyfGREbngKY%2BkdP6bwchA3xl6dDTqoH25OfaAfrB5PG8JYOaWe2wLr3XOGhmFBRczP1LTPQokg1F2rGdN0KTkOJW45XqtMPCZBHhvOdVgSxUgFvAqq9hp1uZyOLwotngOAcjGl6NiMXtO6Ln9%2FdEMGMBRG3LkmYGgRo%2FrnKQL7bd7CWaj%2FwsPcCLWw95XBejWhRDoMksfFcZFof4gfdkCnM0ygD4PXiTzpWz2OYUDtrAeJ%2FGdR9hlkE0QdVxPsXf1BJUdB2id2Mj1I8yI1iVO2LnpgHGtWa%2BriemOpaUzVoQUP6pqkqa0KCjidP1GRYaVMjQ5YQvfk5pinWcHtLFuI5SSlGFqnb%2F5W7RtE8dDUhR8sHk6Mwdq%2Fzyj5wtXIUOc8QkKZ0AHh15qDZFEaqjWL7HGNB8xL7AOM7C32mcBeQzMdkpo3ETJGTHIHykdfE2IQQ6cwWRNfCCX52B8%2FG6ledEM6wR7z2%2FY7djM%2FFLkttf59gRBXWTG1R1eBqEJG0ousRwbqXcymtTmCu9PIg1e0i8fzvJJyO5tDie0nTiFK8iekF%2FnOaq3iCRWmVk6CgxHSx5LG1xldY7%2BW5PiChAL23YkV9WHislgdmf20fky8dd6SzKRDpWILZsuraS6yrSbLHlX712d34sW6Y2g6dCTfpjJVDOu9SHvMsFig0uCtbBZMHKo%2B6J4eNmarokgZ%2FkI7IRdEYZxsD%2FblRv95N%2FWWgWnMmOwXQJb58%2F39qUlta8vteShDLoLsiauvaxgrcfq6GRHtWh5QlkR0KWglMcQoqv1%2FW6NFjWKxPJaDDuQ9vYvENFw6cNDNWr2okbCqSUe1e5BOTbE06aKNkQwzp7vqQY6sQFsiQzPC9HOL3yRcH%2FCn%2B%2FIb310y25epUToqO8PBHcxoxXgqaPP5gRy27dyTD%2BE6YlME1mAgj95LwhULsn4F5oo1R20oieqksLIT4KPAn1jaVwhK1iIxp1jYsTpgCwEGZ7padLWDmuRmpqmWJzXTV%2FhTFhLuz00WA5PjRIfnvfFXm7yvnirbQMOiBpfqPFeEZbIsnbQTikYUGNyQNvnCtRibfYTVhiph43NtmUSeiTsQts%3D&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20231027T160109Z&X-Amz-SignedHeaders=host&X-Amz-Expires=300&X-Amz-Credential=ASIAQ3PHCVTYVXDPOIWA%2F20231027%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=fa0f2fe5ed127c227806c2bae2126c88fd31ef05e35820e88f4dc057749bbb3b&hash=184faf0ae8aa00ad4982c3b14ce77f7f5a5444249e74c2a876319d0a7828f356&host=68042c943591013ac2b2430a89b270f6af2c76d8dfd086a07176afe7c76c2c61&pii=S187705091000373X&tid=spdf-57c4ffb1-28d8-4895-8b8e-7189fc466c91&sid=445ee0076e18f74aa1996c48cb48cca0c1bfgxrqa&type=client&tsoh=d3d3LnNjaWVuY2VkaXJlY3QuY29t&ua=19075a5506015058000854&rr=81cc27ef1ff5a214&cc=ca -Picking middle points of characters and fitting them to a curve -https://mzucker.github.io/2016/08/15/page-dewarping.html -https://github.com/mzucker/page_dewarp/blob/master/page_dewarp.py#L344 -https://www.researchgate.net/publication/322780192_Robust_Document_Image_Dewarping_Method_Using_Text-Lines_and_Line_Segments -https://github.com/taeho-kil/Document-Image-Dewarping - - -OCR: -https://github.com/zacharywhitley/awesome-ocr -https://eng-mhasan.medium.com/ocr-with-deep-learning-in-pytorch-b8a481c604fc -https://huggingface.co/docs/transformers/model_doc/trocr -https://deepayan137.github.io/blog/markdown/2020/08/29/building-ocr.html -https://www.width.ai/post/the-best-ways-to-extract-text-from-images-without-tesseract-python -https://eng-mhasan.medium.com/ocr-with-deep-learning-in-python-e443970d09e4 -https://github.com/watersink/Character-Segmentation -https://github.com/githubharald/WordDetector/blob/master/word_detector/__init__.py - - -Line Extraction: -https://medium.com/@vatvenger/extracting-lines-from-ocr-a8f410448fc -https://stackoverflow.com/questions/34981144/split-text-lines-in-scanned-document - - - -Cmake and shared/dynamic Libraries: -https://www.digitalocean.com/community/tutorials/calling-c-functions-from-python -https://www.tutorialspoint.com/how-to-call-a-c-function-in-python -https://stackoverflow.com/questions/43387112/wrapping-c-code-with-python-manually -https://docs.python.org/3/library/ctypes.html -https://stackoverflow.com/questions/38661635/ctypes-struct-returned-from-library -https://www.youtube.com/watch?v=Slfwk28vhws -https://stackoverflow.com/questions/17511496/how-to-create-a-shared-library-with-cmake - - -C++ templates and stuff: -https://stackoverflow.com/questions/115703/storing-c-template-function-definitions-in-a-cpp-file -https://stackoverflow.com/questions/44848011/c-limit-template-type-to-numbers -https://stackoverflow.com/questions/4021981/use-static-assert-to-check-types-passed-to-macro/60769143#60769143 -https://softwareengineering.stackexchange.com/questions/333447/template-restrictions-in-c -https://stackoverflow.com/questions/10442404/invoke-a-c-class-method-without-a-class-instance -https://en.cppreference.com/w/cpp/language/constraints - - -Models/Ideas: -https://huggingface.co/docs/transformers/model_doc/donut -https://huggingface.co/blog/document-ai -https://huggingface.co/EleutherAI/gpt-neo-125m -https://www.width.ai/post/extracting-information-from-unstructured-text-using-algorithms -https://towardsdatascience.com/machine-learning-text-processing-1d5a2d638958 -https://towardsdatascience.com/deep-learning-for-specific-information-extraction-from-unstructured-texts-12c5b9dceada - - -NER: -https://medium.com/mysuperai/what-is-named-entity-recognition-ner-and-how-can-i-use-it-2b68cf6f545d -https://medium.com/@shivamcse17818/bert-model-for-text-extraction-with-code-pytorch-91c13ef82e7b -https://github.com/dayyass/pytorch-ner -https://github.com/senadkurtisi/pytorch-NER/tree/main -https://towardsdatascience.com/named-entity-recognition-with-bert-in-pytorch-a454405e0b6a -https://www.kaggle.com/code/dianalaveena/ner-using-bert-pytorch/notebook -https://wandb.ai/mostafaibrahim17/ml-articles/reports/Named-Entity-Recognition-With-HuggingFace-Using-PyTorch-and-W-B--Vmlldzo0NDgzODA2 diff --git a/miscellaneous/IMG_7594.jpg b/miscellaneous/IMG_7594.jpg deleted file mode 100644 index 79936e9..0000000 Binary files a/miscellaneous/IMG_7594.jpg and /dev/null differ diff --git a/run.sh b/run.sh deleted file mode 100755 index 8dfb6f3..0000000 --- a/run.sh +++ /dev/null @@ -1,166 +0,0 @@ -#!/bin/bash - -# Info - -usage() { - echo "${0} devbranch [devbranch]" 1>&2 - echo "for example: ${0} autocropper" 1>&2 - exit 1 -} - -# Do we have exactly 1 command-line arguments or not? -if [ ! ${#} -ge 1 ]; then - usage -fi - - - -# functions - -stopalldockercontainers() { - branches=( ${branches[@]/"all"} ) - for branch in ${branches[@]}; do - dockercontainername="ri"${branch}"devenv" - - docker stop ${dockercontainername} - - done -} - - - -# actual script - -realbranches=("app" "autocropper textextractor libraries") -branches=() - -for arg in $(seq 1 ${#}); do - if [[ $(echo ${realbranches[@]} | fgrep -w ${!arg}) ]]; then - branches+=( ${!arg} ) - else - echo "${!arg} is not a branch name. The possible branches are: ${realbranches[@]}" 1>&2 - exit 1 - fi -done - -# echo $(pwd) - - -# FIND IP AND SET DISPLAY THING FOR X SERVER -# referenced https://stackoverflow.com/questions/63859293/docker-for-gui-based-environments-on-windows, -# https://stackoverflow.com/questions/53113171/how-can-i-determine-the-ip-address-from-a-bash-script, -# and https://stackoverflow.com/questions/3466166/how-to-check-if-running-in-cygwin-mac-or-linux -unameOut="$(uname -s)" -case "${unameOut}" in - Linux*) machine=Linux;; - Darwin*) machine=Mac;; - CYGWIN*) machine=Cygwin;; - MINGW*) machine=MinGw;; - MSYS_NT*) machine=Git;; - *) machine="UNKNOWN:${unameOut}" -esac - - -# FOR DISPLAYING WINDOWS FROM DOCKER CONTAINER, -# referenced https://cuneyt.aliustaoglu.biz/en/running-gui-applications-in-docker-on-windows-linux-mac-hosts/ - -XSOCK=/tmp/.X11-unix -XAUTH=/tmp/.docker.xauth - -case "${machine}" in - Linux) - DISPLAYFLAGS="-e DISPLAY -v $XSOCK:$XSOCK" - OS="Linux" - ;; - Mac) - LOCAL_IP=${LOCAL_IP:-`ipconfig getifaddr en0`} - xhost + ${LOCAL_IP} - DISPLAY1="${LOCAL_IP}":0 - DISPLAY1="${DISPLAY1## }" - DISPLAYFLAGS="-e DISPLAY=$DISPLAY1 -v $XSOCK:$XSOCK" - OS="Mac" - ;; - *) - LOCAL_IP=${LOCAL_IP:-`ipconfig.exe | grep -im1 'IPv4 Address' | cut -d ':' -f2`} - DISPLAY1="${LOCAL_IP}":0.0 - DISPLAY1="${DISPLAY1## }" - DISPLAYFLAGS="-e DISPLAY="$DISPLAY1 - OS="Windows" -esac - -# echo "docker run --rm -it ${DISPLAYFLAGS} aliustaoglu/firefox" #CAN BE DELETE----------------------------------- -# docker run --rm -it ${DISPLAYFLAGS} aliustaoglu/firefox #CAN BE DELETE----------------------------------- - - -for branch in ${branches[@]}; do - dockercontainername="ri"${branch}"devenv" - imagename=${branch}"indexerenv" - extrarunflags="" - case ${branch} in - "textextractor") - ;& - "autocropper") - if [ "$OS" = "Windows" ]; then - extrarunflags+="--gpus all" - fi - ;; - *) - ;; - esac - - # echo " docker run --rm --mount type=bind,source="$(pwd)"/code,target=/mnt/code -w "//mnt/code" -it --name ${dockercontainername} \ - # ${DISPLAYFLAGS} \ - # --memory=8g --cpus=6 \ - # ${extrarunflags} \ - # ${imagename}" - - # echo "hi" - docker run --rm --mount type=bind,source="$(pwd)"/code,target=/mnt/code --mount type=bind,source="$(pwd)"/customreceiptdataset,target=/mnt/dataset \ - -w "//mnt/code" \ - -it -d --name "${dockercontainername}" ${DISPLAYFLAGS} \ - --memory=8g --cpus=6 \ - ${extrarunflags} ${imagename} - -done - -# docker container ls -a - -if [ ${#branches[@]} -gt 1 ]; then - branches+=( "all" ) -fi -# echo ${realbranches[@]} | fgrep -w "all" - -while [ ! ${#branches[@]} -eq 0 ]; do - echo "Choose docker container to close:" - select branch in "${branches[@]}"; do - if [ $REPLY -le ${#branches[@]} ] && [ $REPLY -ge 0 ]; then - if [ "${branch}" = "all" ]; then - stopalldockercontainers - branches=() - break - fi - # echo $branch - dockercontainername="ri"${branch}"devenv" - docker stop ${dockercontainername} - - branches=( ${branches[@]/$branch} ) - # echo "${branches[@]}" - - if [ ! -n "$(echo ${realbranches[@]} | fgrep -w "all")" -a ${#branches[@]} -eq 2 ]; then - branches=( ${branches[@]/"all"} ) - fi - break - fi - done -done - - - - -if [ "${machine}" == "Mac" ]; then - xhost - ${LOCAL_IP} -fi - - - -exit 0 diff --git a/setup.sh b/setup.sh deleted file mode 100755 index 5a31ace..0000000 --- a/setup.sh +++ /dev/null @@ -1,51 +0,0 @@ -#!/bin/bash - -# Info - -usage() { - echo "${0} devbranch [devbranch]" 1>&2 - echo "for example: ${0} autocropper" 1>&2 - exit 1 -} - -# Do we have exactly 1 command-line arguments or not? -if [ ! ${#} -ge 1 ]; then - usage -fi - -# actual script - -realbranches=("app" "autocropper textextractor libraries") -branches=() - -for arg in $(seq 1 ${#}); do - if [[ $(echo ${realbranches[@]} | fgrep -w ${!arg}) ]]; then - branches+=( ${!arg} ) - else - echo "${!arg} is not a branch name. The possible branches are: ${realbranches[@]}" 1>&2 - exit 1 - fi -done - -for branch in ${branches[@]}; do - cd ./docker - dockerfilename="./"${branch}"dockerfile" - imagename=${branch}"indexerenv" - - # echo "${imagename}" - # echo "$(pwd)" - - # echo "${dockerfilename}" - - echo "----------STARTING ${branch} DOCKER BUILD----------" - - docker build --file ${dockerfilename} --tag ${imagename} . - cd .. - - echo -e "----------${branch} DOCKER BUILD FINISHED----------\n\n\n" -done - -# echo "Run docker on image \"indexerenv\"" -echo "-----WARNING: RUN X SERVER IF ON MAC OR WINDOWS (OR A REQUIRED LINUX DISTRO (NOT UBUNTU)) PRIOR TO RUNNING DOCKER CONTAINER-----" - -exit 0