基于python OpenCV实现动态人脸检测

import cv2 
import numpy as np 
 
cv2.namedWindow("test") 
cap = cv2.VideoCapture(0) #加载摄像头录制 
# cap = cv2.VideoCapture("test.mp4") #打开视频文件 
success, frame = cap.read() 
# classifier = cv2.CascadeClassifier("/Users/yuki/anaconda/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml") 

# 确保此xml文件与该py文件在一个文件夹下，否则将这里改为绝对路径 
 
#haarcascade_frontalface_default.xml 
classifier = cv2.CascadeClassifier("/Users/yuki/anaconda/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml") 

# 确保此xml文件与该py文件在一个文件夹下，否则将这里改为绝对路径 
 
while success: 
 success, frame = cap.read() 
 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 = (w // divisor, h // divisor) 
 faceRects = classifier.detectMultiScale(image, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, minSize) 
 if len(faceRects) > 0: 
  for faceRect in faceRects: 
   x, y, w, h = faceRect 
   cv2.rectangle(frame,(x,y),(x+h,y+w),(0,255,0),2) 
   #锁定 眼和嘴巴 
#cv2.circle(frame, (x + w // 4, y + h // 4 + 30), min(w // 8, h // 8), (255, 0, 0)) # 左眼 
#cv2.circle(frame, (x + 3 * w //4, y + h // 4 + 30), min(w // 8, h // 8), (255, 0, 0)) #右眼 
#cv2.rectangle(frame, (x + 3 * w // 8, y + 3 * h // 4), (x + 5 * w // 8, y + 7 * h // 8), (255, 0, 0))#嘴巴 
 cv2.imshow("test", frame) 
 key = cv2.waitKey(10) 
 c = chr(key & 255) 
 if c in ['q', 'Q', chr(27)]: 
  break 
cv2.destroyWindow("test")