Start on face detection

api/scanner/face_detection/face_detector.go

@@ -0,0 +1,135 @@
+package face_detection
+
+import (
+	"log"
+	"path/filepath"
+	"sync"
+
+	"github.com/Kagami/go-face"
+	"github.com/photoview/photoview/api/graphql/models"
+	"github.com/pkg/errors"
+	"gorm.io/gorm"
+)
+
+type FaceDetector struct {
+	mutex   sync.Mutex
+	db      *gorm.DB
+	rec     *face.Recognizer
+	samples []face.Descriptor
+	cats    []int32
+}
+
+var GlobalFaceDetector FaceDetector
+
+func InitializeFaceDetector(db *gorm.DB) error {
+
+	log.Println("Initializing face detector")
+
+	rec, err := face.NewRecognizer(filepath.Join("data", "models"))
+	if err != nil {
+		return errors.Wrap(err, "initialize facedetect recognizer")
+	}
+
+	samples, cats, err := getSamplesFromDatabase(db)
+	if err != nil {
+		return errors.Wrap(err, "get face detection samples from database")
+	}
+
+	GlobalFaceDetector = FaceDetector{
+		db:      db,
+		rec:     rec,
+		samples: samples,
+		cats:    cats,
+	}
+
+	return nil
+}
+
+func getSamplesFromDatabase(db *gorm.DB) (samples []face.Descriptor, cats []int32, err error) {
+	samples = make([]face.Descriptor, 0)
+	cats = make([]int32, 0)
+
+	return
+}
+
+func (fd *FaceDetector) DetectFaces(media *models.Media) error {
+	if err := fd.db.Model(media).Preload("MediaURL").First(&media).Error; err != nil {
+		return err
+	}
+
+	var thumbnailURL *models.MediaURL
+	for _, url := range media.MediaURL {
+		if url.Purpose == models.PhotoThumbnail {
+			thumbnailURL = &url
+			thumbnailURL.Media = media
+			break
+		}
+	}
+
+	if thumbnailURL == nil {
+		return errors.New("thumbnail url is missing")
+	}
+
+	thumbnailPath, err := thumbnailURL.CachedPath()
+	if err != nil {
+		return err
+	}
+
+	fd.mutex.Lock()
+	faces, err := fd.rec.RecognizeFile(thumbnailPath)
+	fd.mutex.Unlock()
+
+	if err != nil {
+		return errors.Wrap(err, "error read faces")
+	}
+
+	for _, face := range faces {
+		fd.classifyFace(&face, media)
+	}
+
+	return nil
+}
+
+func (fd *FaceDetector) classifyFace(face *face.Face, media *models.Media) error {
+	fd.mutex.Lock()
+	defer fd.mutex.Unlock()
+
+	match := fd.rec.ClassifyThreshold(face.Descriptor, 0.2)
+
+	imageFace := models.ImageFace{
+		MediaID:    media.ID,
+		Descriptor: models.FaceDescriptor(face.Descriptor),
+	}
+
+	var faceGroup models.FaceGroup
+
+	// If no match add it new to samples
+	if match < 0 {
+		log.Println("No match, assigning new face")
+
+		faceGroup = models.FaceGroup{
+			ImageFaces: []models.ImageFace{imageFace},
+		}
+
+		if err := fd.db.Create(&faceGroup).Error; err != nil {
+			return err
+		}
+
+	} else {
+		log.Println("Found match")
+
+		if err := fd.db.First(&faceGroup, int(match)).Error; err != nil {
+			return err
+		}
+
+		if err := fd.db.Model(&faceGroup).Association("ImageFaces").Append(&imageFace); err != nil {
+			return err
+		}
+	}
+
+	fd.samples = append(fd.samples, face.Descriptor)
+	fd.cats = append(fd.cats, int32(faceGroup.ID))
+
+	fd.rec.SetSamples(fd.samples, fd.cats)
+	return nil
+}