python3.6.3+opencv3.3.0实现动态人脸捕获

import cv2import numpy as npcv2.namedWindow("Face_Detect") #定义一个窗口cap=cv2.VideoCapture(0) #捕获摄像头图像success,frame=cap.read() #读入第一帧classifier=cv2.CascadeClassifier("C:/opencv-3.3.0/data/haarcascades/haarcascade_frontalface_alt.xml")**#定义人脸识别的分类数据集，需要自己查找，在opencv的目录下，参考上面我的路径**while success:#如果读入帧正常 size=frame.shape[:2] image=np.zeros(size,dtype=np.float16) image=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY) cv2.equalizeHist(image,image) divisor=8 h,w=size minSize=(int(w/divisor),int(h/divisor)) #像素一定是整数，或者用w//divisor faceRects=classifier.detectMultiScale(image,1.2,2,cv2.CASCADE_SCALE_IMAGE,minSize) #人脸识别 if len(faceRects)> 0:  for faceRect in faceRects:   x,y,w,h=faceRect   cv2.circle(frame,(x+w//2,y+h//2),min(w//2,h//2),(255,0,0),2) #圆形轮廓   cv2.circle(frame,(x+w//4,y+2*h//5),min(w//8,h//8),(0,255,0),2) #左眼轮廓   cv2.circle(frame,(x+3*w//4,y+2*h//5),min(w//8,h//8),(0,255,0),2)#右眼轮廓   cv2.circle(frame,(x+w//2,y+2*h//3),min(w//8,h//8),(0,255,0),2) #鼻子轮廓   cv2.rectangle(frame, (x, y), (x+w, y+h), (0,0,255),2)   #矩形轮廓 cv2.imshow("Face_Detect",frame) #显示轮廓 success,frame=cap.read()#如正常则读入下一帧 c=chr(key&255) if c in ['q','Q',chr(27)]:#如果键入‘q'退出循环  print('exit'/n)  break#退出循环 #循环结束则清零cap.release()cv2.destroyAllWindows()