Python基于OpenCV批量提取视频中的人脸并保存

#-*- coding: UTF-8 -*-
import cv2
from PIL import Image
name = 'name'
def getface(path):
  cap = cv2.VideoCapture(path)
  classfier = cv2.CascadeClassifier("/home/coding/workspace/haarcascades/haarcascade_frontalface_alt2.xml")
  suc = cap.isOpened()  # 是否成功打开
  frame_count = 0
  out_count = 0
  while suc:
      frame_count += 1
      if out_count > 599: #最多取出多少张
        break
      suc, frame = cap.read() #读取一帧
      params = []
      params.append(2)  # params.append(1)
      grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)  #将当前桢图像转换成灰度图像
      faceRects = classfier.detectMultiScale(grey, scaleFactor = 1.2, minNeighbors = 3, minSize = (32, 32)) #读取脸部位置
      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
                image = frame[y - 10: y + h + 10, x - 10: x + w + 10]
                image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) #转为灰度图
                img_new = cv2.resize(image,(47,57), interpolation = cv2.INTER_CUBIC) #处理面部的大小
                cv2.imwrite('/home/coding/workspace/Data/'+ name +'/%d.jpg' % out_count, img_new, params) #存储到指定目录
                out_count += 1
                print('成功提取'+ name +'的第%d个脸部'%out_count)
                break #每帧只获取一张脸，删除这个即为读出全部面部
  cap.release()
  cv2.destroyAllWindows()
  print('总帧数:', frame_count)
  print('提取脸部:',out_count)

if __name__ == '__main__':
    getface("/home/coding/workspace/Data/Videos/"+ name +".mp4") #参数为视频地址