Recreate facedetection example with the new APIs

examples/facedetection/main.go

@@ -0,0 +1,107 @@
+package main
+
+import (
+	"image"
+	"io/ioutil"
+	"log"
+	"time"
+
+	pigo "github.com/esimov/pigo/core"
+	"github.com/pion/mediadevices"
+	_ "github.com/pion/mediadevices/pkg/driver/camera" // This is required to register camera adapter
+	"github.com/pion/mediadevices/pkg/frame"
+	"github.com/pion/mediadevices/pkg/prop"
+)
+
+const (
+	confidenceLevel = 5.0
+)
+
+var (
+	cascade    []byte
+	classifier *pigo.Pigo
+)
+
+func must(err error) {
+	if err != nil {
+		panic(err)
+	}
+}
+
+func detectFace(frame *image.YCbCr) bool {
+	bounds := frame.Bounds()
+	cascadeParams := pigo.CascadeParams{
+		MinSize:     100,
+		MaxSize:     600,
+		ShiftFactor: 0.15,
+		ScaleFactor: 1.1,
+		ImageParams: pigo.ImageParams{
+			Pixels: frame.Y, // Y in YCbCr should be enough to detect faces
+			Rows:   bounds.Dy(),
+			Cols:   bounds.Dx(),
+			Dim:    bounds.Dx(),
+		},
+	}
+
+	// Run the classifier over the obtained leaf nodes and return the detection results.
+	// The result contains quadruplets representing the row, column, scale and detection score.
+	dets := classifier.RunCascade(cascadeParams, 0.0)
+
+	// Calculate the intersection over union (IoU) of two clusters.
+	dets = classifier.ClusterDetections(dets, 0)
+
+	for _, det := range dets {
+		if det.Q >= confidenceLevel {
+			return true
+		}
+	}
+
+	return false
+}
+
+func main() {
+	// prepare face detector
+	var err error
+	cascade, err = ioutil.ReadFile("facefinder")
+	if err != nil {
+		log.Fatalf("Error reading the cascade file: %s", err)
+	}
+	p := pigo.NewPigo()
+
+	// Unpack the binary file. This will return the number of cascade trees,
+	// the tree depth, the threshold and the prediction from tree's leaf nodes.
+	classifier, err = p.Unpack(cascade)
+	if err != nil {
+		log.Fatalf("Error unpacking the cascade file: %s", err)
+	}
+
+	mediaStream, err := mediadevices.GetUserMedia(mediadevices.MediaStreamConstraints{
+		Video: func(c *mediadevices.MediaTrackConstraints) {
+			c.FrameFormat = prop.FrameFormatExact(frame.FormatUYVY)
+			c.Width = prop.Int(640)
+			c.Height = prop.Int(480)
+		},
+	})
+	must(err)
+
+	// since we're trying to access the raw data, we need to cast Track to its real type, *mediadevices.VideoTrack
+	videoTrack := mediaStream.GetVideoTracks()[0].(*mediadevices.VideoTrack)
+	defer videoTrack.Close()
+
+	videoReader := videoTrack.NewReader(false)
+	// To save resources, we can simply use 4 fps to detect faces.
+	ticker := time.NewTicker(time.Millisecond * 250)
+	defer ticker.Stop()
+
+	for range ticker.C {
+		frame, release, err := videoReader.Read()
+		must(err)
+
+		// Since we asked the frame format to be exactly YUY2 in GetUserMedia, we can guarantee that it must be YCbCr
+		if detectFace(frame.(*image.YCbCr)) {
+			log.Println("Detect a face")
+		}
+
+		release()
+	}
+}