图片人脸识别

import cv2filepath = "img/xingye-1.png"img = cv2.imread(filepath) # 读取图片gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 转换灰色# OpenCV人脸识别分类器classifier = cv2.CascadeClassifier( "C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml")color = (0, 255, 0) # 定义绘制颜色# 调用识别人脸faceRects = classifier.detectMultiScale( gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))if len(faceRects): # 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 # 框出人脸 cv2.rectangle(img, (x, y), (x + h, y + w), color, 2) # 左眼 cv2.circle(img, (x + w // 4, y + h // 4 + 30), min(w // 8, h // 8), color) #右眼 cv2.circle(img, (x + 3 * w // 4, y + h // 4 + 30), min(w // 8, h // 8), color) #嘴巴 cv2.rectangle(img, (x + 3 * w // 8, y + 3 * h // 4), (x + 5 * w // 8, y + 7 * h // 8), color)cv2.imshow("image", img) # 显示图像c = cv2.waitKey(10)cv2.waitKey(0)cv2.destroyAllWindows()

视频人脸识别

# -*- coding:utf-8 -*-# OpenCV版本的视频检测import cv2# 图片识别方法封装def discern(img): gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) cap = cv2.CascadeClassifier( "C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml" ) faceRects = cap.detectMultiScale( gray, scaleFactor=1.2, minNeighbors=3, minSize=(50, 50)) if len(faceRects): for faceRect in faceRects: x, y, w, h = faceRect cv2.rectangle(img, (x, y), (x + h, y + w), (0, 255, 0), 2) # 框出人脸 cv2.imshow("Image", img)# 获取摄像头0表示第一个摄像头cap = cv2.VideoCapture(0)while (1): # 逐帧显示 ret, img = cap.read() # cv2.imshow("Image", img) discern(img) if cv2.waitKey(1) & 0xFF == ord('q'): breakcap.release() # 释放摄像头cv2.destroyAllWindows() # 释放窗口资源

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