shape_predictor = "./shape_predictor_68_face_landmarks.dat"
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(shape_predictor)
frame = cv2.imread(imgfullpath)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = detector(gray,0) #也可以对彩色图像提取人脸区域
for rect in rects:
face_img = gray[max(rect.top(),1):min(rect.bottom(),frame.shape[0]-1), max(rect.left(),1):min(rect.right(),frame.shape[1]-1)] #提取的人脸区域有可能超出图像的边界
#### landmarks ###
shape = predictor(gray,rect)
shape = face_utils.shape_to_np(shape)
i = 1
for (x,y) in shape:
cv2.circle(face_img,(x,y),1,(0,255,0),-1)
cv2.putText(face_img, str(i), (x-rect.left(), y-rect.top()),cv2.FONT_HERSHEY_SIMPLEX, 0.3, (0, 0, 255), 1)
i += 1
cv2.imshow('frame',frame)
cv2.waitkey(0)
dlib提取人脸区域及关键点检测
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转载自blog.csdn.net/yy2yy99/article/details/103525864
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