Python OpenCV调用摄像头检测人脸并截图

#-*- coding: utf-8 -*-# import 进openCV的库import cv2###调用电脑摄像头检测人脸并截图def CatchPICFromVideo(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(camera_idx) #告诉OpenCV使用人脸识别分类器 classfier = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml") #识别出人脸后要画的边框的颜色，RGB格式, color是一个不可增删的数组 color = (0, 255, 0) num = 0 while cap.isOpened():  ok, frame = cap.read() #读取一帧数据  if not ok:   break  grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) #将当前桢图像转换成灰度图像  #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    #将当前帧保存为图片    img_name = "%s/%d.jpg" % (path_name, num)    #print(img_name)    image = frame[y - 10: y + h + 10, x - 10: x + w + 10]    cv2.imwrite(img_name, image,[int(cv2.IMWRITE_PNG_COMPRESSION), 9])    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/100' % (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__': # 连续截100张图像，存进image文件夹中 CatchPICFromVideo("get face", 0, 99, "/image")