opencv3视频中检测人脸python

# -*- coding: utf-8 -*- import cv2 import numpy as np cv2.namedWindow("test") # cap = cv2.VideoCapture(0) #加载摄像头录制 cap = cv2.VideoCapture("test.mp4") #打开视频文件 success, frame = cap.read() classifier = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml") # 确保此xml文件与该py文件在一个文件夹下，否则将这里改为绝对路径，此xml文件可在D:\My Documents\Downloads\opencv\sources\data\haarcascades下找到。 while success: success, frame = cap.read() size = frame.shape[:2] image = np.zeros(size, dtype=np.float16) image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.equalizeHist(image, image) divisor = 8 h, w = size minSize = (w / divisor, h / divisor) faceRects = classifier.detectMultiScale(image, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, minSize) if len(faceRects) > 0: for faceRect in faceRects: x, y, w, h = faceRect cv2.circle(frame, (x + w / 4, y + h / 4 + 30), min(w / 8, h / 8), (255, 0, 0)) cv2.circle(frame, (x + 3 * w / 4, y + h / 4 + 30), min(w / 8, h / 8), (255, 0, 0)) cv2.rectangle(frame, (x + 3 * w / 8, y + 3 * h / 4), (x + 5 * w / 8, y + 7 * h / 8), (255, 0, 0)) cv2.imshow("test", frame) key = cv2.waitKey(10) c = chr(key & 255) if c in ['q', 'Q', chr(27)]: break cv2.destroyWindow("test")