Python基于OpenCV实现人脸检测并保存

import cv2

cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")

#-*- coding: utf-8 -*-# import openCV的库import cv2import os, math, operatorfrom PIL import Imagefrom functools import reduce###调用电脑摄像头检测人脸并截图def CatchPICFromVideo(window_name, path_name): cv2.namedWindow(window_name) #电脑摄像头 cap = cv2.VideoCapture(0) #告诉OpenCV使用人脸识别分类器 classfier = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") #检测人脸后要画的边框的颜色 color = (0, 255, 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   #画出矩形框  cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)    k = cv2.waitKey(100) #每0.1秒读一次键盘  if k == ord("z") or k == ord("Z"): #如果输入z   #将当前帧保存为图片   img_name = path_name   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])   break     #显示图像 cv2.imshow(window_name, frame) #退出摄像头界面 c = cv2.waitKey(100) if c == ord("q") or c == ord("Q"):   break #释放摄像头并销毁所有窗口 cap.release() cv2.destroyAllWindows()os.system("cls") #清屏recogname = "recogface.jpg" #预存的人脸文件CatchPICFromVideo("get face",recogname)