python openCV获取人脸部分并存储功能

#-*- coding:utf-8 -*-import cv2import osimport timeimport base64import numpy as np save_path = 'E://opencv//2018-04-24OpenCv//RAR//savetest'faceCascade = cv2.CascadeClassifier(  './haarcascade_frontalface_alt.xml') cap = cv2.VideoCapture(0) count = 0 while True:  ret,frame = cap.read()  gray = cv2.cvtColor(frame,cv2.COLOR_RGB2GRAY)  rect = faceCascade.detectMultiScale(gray,                  scaleFactor=1.3,                  minNeighbors=9,                  minSize=(50,50),                  flags=cv2.CASCADE_SCALE_IMAGE                  )   if not rect is ():    for x,y,w,h in rect:      roiImg = frame[y:y+h,x:x+w]      # 以时间戳和读取的排序作为文件名称      listStr = [str(int(time.time())), str(count)]      fileName = ''.join(listStr)      # 图片存储      cv2.imwrite(save_path + os.sep + '%s.jpg' % fileName, roiImg)      # print (roiImg)      # roiTobase64 = cv2.imencode(roiImg,np.uint8)      # print (base64.b64encode(roiTobase64))      cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),2)        count += 1   cv2.imshow('opencvCut',frame)  k = cv2.waitKey(30) & 0xff  if k == 27:    breakcap.release()cv2.destroyAllWindows()

import cv2import sysimport osfrom PIL import ImagecascPath = "haarcascade_frontalface_default.xml" #训练参数文件faceCascade = cv2.CascadeClassifier(cascPath)#分类器 base = 'new_dir//'for img in os.listdir(base):  image = cv2.imread(base + img)#读取图片  gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)  gray = cv2.equalizeHist(gray) #直方图均衡化，提高分类效果  faces = faceCascade.detectMultiScale(    gray,    scaleFactor=1.1,    minNeighbors=5,    minSize=(10, 10)  )  num = 0  for (x, y, w, h) in faces:    cv2.imwrite("face_dir//" + img,image[y:y+h,x:x+w])    num += 1#   cv2.imshow("Faces found", image)  cv2.waitKey(0)