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")