96 lines
2.1 KiB
Go
96 lines
2.1 KiB
Go
package photo
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import (
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"errors"
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"os"
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"code.nonshy.com/nonshy/website/pkg/config"
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"code.nonshy.com/nonshy/website/pkg/log"
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pigo "github.com/esimov/pigo/core"
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)
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// Functionality to do with face detection in pictures.
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var (
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faceScoreReady bool
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faceClassifier *pigo.Pigo
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cascadeFile []byte
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)
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// InitFaceScore initializes the face recognition library (esimov/pigo).
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func InitFaceScore() {
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if faceScoreReady {
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return
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}
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if !config.Current.FaceScore.Enabled {
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log.Error("InitFaceScore: not enabled in settings, face detection will not run")
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return
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}
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// Load the cascade file needed for face detection.
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data, err := os.ReadFile(config.Current.FaceScore.CascadeFile)
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if err != nil {
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log.Error("InitFaceScore: could not load cascade file (%s): %s", config.Current.FaceScore.CascadeFile, err)
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return
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}
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cascadeFile = data
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log.Info("Initializing FaceScore with cascade file (%d bytes)", len(cascadeFile))
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faceClassifier = pigo.NewPigo()
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faceClassifier, err = faceClassifier.Unpack(cascadeFile)
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if err != nil {
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log.Error("InitFaceScore: could not unpack the cascade file: %s", err)
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return
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}
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faceScoreReady = true
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}
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// ComputeFaceScore checks a photo on disk and returns the detected face score.
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func ComputeFaceScore(filename string) (float64, error) {
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if !faceScoreReady {
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return 0, errors.New("face detection is not available")
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}
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src, err := pigo.GetImage(filename)
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if err != nil {
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return 0, err
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}
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var (
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pixels = pigo.RgbToGrayscale(src)
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cols, rows = src.Bounds().Max.X, src.Bounds().Max.Y
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cParams = pigo.CascadeParams{
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MinSize: 20,
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MaxSize: 1000,
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ShiftFactor: 0.1,
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ScaleFactor: 1.1,
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ImageParams: pigo.ImageParams{
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Pixels: pixels,
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Rows: rows,
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Cols: cols,
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Dim: cols,
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},
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}
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)
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// Run the classifier.
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dets := faceClassifier.RunCascade(cParams, 0.0)
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for _, row := range dets {
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log.Warn("%+v", row)
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}
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// Note: the classifier may return multiple matched faces, return the highest score.
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var highest float32
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for _, row := range dets {
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if row.Q > highest {
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highest = row.Q
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}
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}
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return float64(highest), nil
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}
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