#-*- coding: utf-8 -*-

import cv2
import sys
from PIL import Image

def CatchUsbVideo(window_name, camera_idx,catch_pic_num,path_name):
	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(0 + cv2.CAP_DSHOW)                
    
    #告诉OpenCV使用人脸识别分类器
	classfier = cv2.CascadeClassifier("d:/python/Lib/site-packages/cv2/data/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)
	num=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)
                        
        #将当前帧保存为图片
				img_name = '%s/%d.jpg'%(path_name, num)                
				image = frame[y - 10: y + h + 10, x - 10: x + w + 10]
				cv2.imwrite(img_name, image)                                
                                
				num += 1                
				if num >= (catch_pic_num):   #如果超过指定最大保存数量退出循环
					break
                 
                #画出矩形框
				cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)
				  
				#显示当前捕捉到了多少人脸图片了，这样站在那里被拍摄时心里有个数，不用两眼一抹黑傻等着
				font = cv2.FONT_HERSHEY_SIMPLEX
				cv2.putText(frame,'num:%d' % (num),(x + 30, y + 30), font, 1, (255,0,255),4)                
         
        #超过指定最大保存数量结束程序
		if num >= (catch_pic_num): break                
                        
         #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__':
    CatchUsbVideo("识别人脸区域", 0 + cv2.CAP_DSHOW,100,'mypicture')