python opencv3实现人脸识别（windows）

#coding:utf-8  import cv2 import sys from PIL import Image   def CatchUsbVideo(window_name, camera_idx):   cv2.namedWindow(window_name)    # 视频来源，可以来自一段已存好的视频，也可以直接来自USB摄像头   cap = cv2.VideoCapture(camera_idx)    # 告诉OpenCV使用人脸识别分类器   classfier = cv2.CascadeClassifier("C://opencv//build//etc//haarcascades//haarcascade_frontalface_alt2.xml")    # 识别出人脸后要画的边框的颜色，RGB格式   color = (0, 255, 0)    while cap.isOpened():     ok, frame = cap.read() # 读取一帧数据     if not ok:       break        # 将当前帧转换成灰度图像     grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)      # 人脸检测，1.2和2分别为图片缩放比例和需要检测的有效点数     faceRects = classfier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))     if len(faceRects) > 0: # 大于0则检测到人脸       for faceRect in faceRects: # 单独框出每一张人脸         x, y, w, h = faceRect         cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 3) #5控制绿色框的粗细      # 显示图像     cv2.imshow(window_name, frame)     c = cv2.waitKey(10)     if c & 0xFF == ord('q'):       break        # 释放摄像头并销毁所有窗口   cap.release()   cv2.destroyAllWindows()   if __name__ == '__main__':   CatchUsbVideo("FaceRect", 0)   # if len(sys.argv) != 2:   #   print("Usage:%s camera_id/r/n" % (sys.argv[0]))   # else:   #   CatchUsbVideo("识别人脸区域", int(sys.argv[1]))