CV2摄像头人脸、人眼、微笑等检测

import cv2face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')#人脸
eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')#人眼
smile_cascade=cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_smile.xml')#微笑#3打开摄像头
capture=cv2.VideoCapture(0)while True:#读取该帧的画面ret, img = capture.read()# 6灰度处理gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)# 7检查人脸faces = face_cascade.detectMultiScale(gray, 1.1, 3, 0, (120, 120))for (x, y, w, h) in faces:cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 3)face_area = img[y:y + h, x:x + w]eyes = eye_cascade.detectMultiScale(face_area,1.3,10)# 用人眼级联分类器引擎在人脸区域进行人眼识别，返回的eyes为眼睛坐标列表for (ex, ey, ew, eh) in eyes:# 画出人眼框，绿色，画笔宽度为1cv2.rectangle(face_area, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 1)smile = smile_cascade.detectMultiScale(face_area, scaleFactor=1.16, minNeighbors=50, minSize=(50, 50),flags=cv2.CASCADE_SCALE_IMAGE)# 用人眼级联分类器引擎在人脸区域进行人眼识别，返回的eyes为眼睛坐标列表for (ex, ey, ew, eh) in smile:# 画出人眼框，绿色，画笔宽度为1cv2.rectangle(face_area, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 1)cv2.putText(img, 'Smile', (x, y - 7), 3, 1.2, (0, 0, 255), 2, cv2.LINE_AA)# 9显示图片cv2.imshow("My_按q退出", img)# 10暂停窗口if cv2.waitKey(5) & 0xFF == ord('q'):break
#11释放资源
capture.release()
# #12销毁窗口
cv2.destoryAllWindows()