用已经训练好的xml文件实现人脸识别。
先在图像中寻找脸,找到人脸后将脸部作为ROI进行眼睛的寻找,降低了运算量和出错率。
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
cap = cv2.VideoCapture(0)
while True:
ret,img = cap.read()
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray,1.3,5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray = gray[y:y+h,x:x+w] #设定ROI缩小眼睛匹配范围
roi_color = img[y:y+h,x:x+w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
k = cv2.waitKey(10) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()