# -*- coding: utf-8 -*-__author__ = "小柒"__blog__ = "https://blog.52itstyle.vip/"import cv2import os# 保存好的视频检测人脸并截图def CatchPICFromVideo(window_name, camera_idx, catch_pic_num, path_name): cv2.namedWindow(window_name) # 视频来源 cap = cv2.VideoCapture(camera_idx) # 告诉OpenCV使用人脸识别分类器 classfier = cv2.CascadeClassifier(os.getcwd()+"//haarcascade//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 CatchPICFromVideo("get face", os.getcwd()+"//video//kelake.mp4", 100, "E://VideoCapture") 
