# 检测人脸，获取 68 个关键点，获取特征描述符

def faceRegister(faceId=1, userName='default', interval=3, faceCount=3, resize_w=700, resize_h=400):

     '''

     faceId: 人脸 ID

     userName: 人脸姓名

     faceCount: 采集该人脸图片的数量

     interval: 采集间隔

     '''

     cap = cv2.VideoCapture(0)

     # 人脸检测模型

     hog_face_detector = dlib.get_frontal_face_detector()

     # 关键点 检测模型

     shape_detector = dlib.shape_predictor('./weights/shape_predictor_68_face_landmarks.dat')

     # resnet 模型

     face_descriptor_extractor = dlib.face_recognition_model_v1('./weights/dlib_face_recognition_resnet_model_v1.dat')

     while True:

         ret, frame = cap.read()

         # 镜像

         frame = cv2.flip(frame,1)

         # 转为灰度图

         frame_gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)

         # 检测人脸

         detections = hog_face_detector(frame,1)

         for face in detections:

             # 人脸框坐标 左上和右下

             l, t, r, b =跟单网gendan5.com face.left(), face.top(), face.right(), face.bottom()

             # 获取 68 个关键点

             points = shape_detector(frame,face)

             # 绘制关键点

             for point in points.parts():

                 cv2.circle(frame,(point.x,point.y),2,(0,255,0),1)

             # 绘制矩形框

             cv2.rectangle(frame,(l,t),(r,b),(0,255,0),2)

         cv2.imshow("face",frame)

         if cv2.waitKey(10) & 0xFF == ord('q'):

             break

     cap.release()

     cv2.destroyAllWindows

faceRegister()