func (detector *FaceDetector) DetectGlasses(image *opencv.IplImage, roi pixelArea) (leftEyes, rightEyes pixelCoords) {
var topFace opencv.Rect
var eyes pixelCoords
topFace.Init(roi.X(), roi.Y()+int(float64(roi.Height())*0.20), roi.Width(), int(float64(roi.Height())/2))
image.SetROI(topFace)
for _, eye := range detector.glassesCascade.DetectObjects(image) {
leftEyes = append(leftEyes, pixelCoord{
x: eye.X() + topFaceLeft.X(),
y: eye.Y() + topFaceLeft.Y(),
width: eye.Width(),
height: eye.Height(),
})
}
fmt.Println(len(leftEyes), " left eyes found")
image.SetROI(topFaceRight)
for _, eye := range detector.glassesCascade.DetectObjects(image) {
rightEyes = append(rightEyes, pixelCoord{
x: eye.X() + topFaceRight.X(),
y: eye.Y() + topFaceRight.Y(),
width: eye.Width(),
height: eye.Height(),
})
}
fmt.Println(len(rightEyes), " right eyes found")
image.ResetROI()
return
}
func main() {
runtime.GOMAXPROCS(runtime.NumCPU())
_, currentfile, _, _ := runtime.Caller(0)
cascade := path.Join(path.Dir(currentfile), "haarcascade_frontalface_alt.xml")
window := opencv.NewWindowDriver()
camera := opencv.NewCameraDriver("tcp://192.168.1.1:5555")
ardroneAdaptor := ardrone.NewAdaptor()
drone := ardrone.NewDriver(ardroneAdaptor)
work := func() {
detect := false
drone.TakeOff()
var image *cv.IplImage
camera.On(opencv.Frame, func(data interface{}) {
image = data.(*cv.IplImage)
if !detect {
window.ShowImage(image)
}
})
drone.On(ardrone.Flying, func(data interface{}) {
gobot.After(1*time.Second, func() { drone.Up(0.2) })
gobot.After(2*time.Second, func() { drone.Hover() })
gobot.After(5*time.Second, func() {
detect = true
gobot.Every(300*time.Millisecond, func() {
drone.Hover()
i := image
faces := opencv.DetectFaces(cascade, i)
biggest := 0
var face *cv.Rect
for _, f := range faces {
if f.Width() > biggest {
biggest = f.Width()
face = f
}
}
if face != nil {
opencv.DrawRectangles(i, []*cv.Rect{face}, 0, 255, 0, 5)
centerX := float64(image.Width()) * 0.5
turn := -(float64(face.X()) - centerX) / centerX
fmt.Println("turning:", turn)
if turn < 0 {
drone.Clockwise(math.Abs(turn * 0.4))
} else {
drone.CounterClockwise(math.Abs(turn * 0.4))
}
}
window.ShowImage(i)
})
gobot.After(20*time.Second, func() { drone.Land() })
})
})
}
robot := gobot.NewRobot("face",
[]gobot.Connection{ardroneAdaptor},
[]gobot.Device{window, camera, drone},
work,
)
robot.Start()
}
func (s smartcropResizer) smartResize(input image.Image, dstWidth, dstHeight int) (image.Image, error) {
if dstWidth < 0 || dstHeight < 0 {
return nil, fmt.Errorf("Please specify both width and height for your target image")
}
scaledInput, scale, err := normalizeInput(input, 1024)
if err != nil {
return input, err
}
cvImage := opencv.FromImage(scaledInput)
_, err = os.Stat(s.haarcascade)
if err != nil {
return input, err
}
cascade := opencv.LoadHaarClassifierCascade(s.haarcascade)
faces := cascade.DetectObjects(cvImage)
if len(faces) == 0 {
return nil, ErrNoFacesFound
}
var biggestFace *opencv.Rect
for _, f := range faces {
if biggestFace == nil {
biggestFace = f
continue
}
biggestArea := biggestFace.Width() * biggestFace.Height()
currentArea := f.Width() * f.Height()
if biggestArea < currentArea {
biggestFace = f
}
}
log.Printf("Faces found %d\n", len(faces))
if biggestFace == nil {
return nil, ErrNoFacesFound
}
faceArea := biggestFace.Width() * biggestFace.Height()
imagePixels := scaledInput.Bounds().Dx() * scaledInput.Bounds().Dy()
faceAreaPercentage := float64(faceArea) / float64(imagePixels)
if faceAreaPercentage < faceImageTreshold {
return nil, fmt.Errorf("face area too small: %.2f.\n", faceAreaPercentage)
}
if sub, ok := input.(subImager); ok {
x := int(float64(biggestFace.X()) * scale)
y := int(float64(biggestFace.Y()) * scale)
width := int(float64(biggestFace.Width()) * scale)
height := int(float64(biggestFace.Height()) * scale)
facePoint := image.Pt(x, y)
target := image.Rect(0, 0, int(float64(dstWidth)*scale), int(float64(dstHeight)*scale))
r := image.Rect(0, 0, x+width, y+height).Add(facePoint)
for !target.In(r) && r.Min.X > 0 && r.Min.Y > 0 {
r = image.Rect(r.Min.X-1, r.Min.Y-1, r.Max.X+1, r.Max.Y+1)
}
cropImage := sub.SubImage(r)
return imaging.Thumbnail(cropImage, dstWidth, dstHeight, imaging.Lanczos), nil
}
return input, err
}