face_rect.py

#-*- 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:\ProgramData\Anaconda2\pkgs\opencv3-3.1.0-py27_0\Library\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, 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]))