python实现人脸识别代码

#-*- 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("/usr/local/share/OpenCV/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, 2)
            
    #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__':
  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]))

#告诉OpenCV使用人脸识别分类器
classfier = cv2.CascadeClassifier("/usr/local/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml")

#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, 2)