pycharm工程python调用OpenCV实现USB摄像头实时人脸检测

# -*- coding: utf-8 -*- import cv2 import sys import time from PIL import Image 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("./data/haarcascade_frontalface_alt2.xml") # 识别出人脸后要画的边框的颜色，RGB格式 color = (0, 255, 0) num = 0 while cap.isOpened(): start_time = time.time() 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) image = frame[y - 10: y + h + 10, x - 10: x + w + 10] cv2.imwrite(img_name, image) 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' % (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 print '每帧人脸检测消耗时间： %fs!' % (time.time() - start_time) 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__': CatchPICFromVideo("FaceDect", 0,1000, "./image_save")