python实现动态人脸捕获 python3.6.3+opencv3.3.0实现动态人脸捕获

import cv2
import numpy as np

cv2.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()