人脸检测

import cv2
import numpy as np
#第一步，创建Haar级联器
# facer = cv2.CascadeClassifier('./haarcascades/haarcascade_frontalface_default.xml')
facer = cv2.CascadeClassifier('./haarcascades/haarcascade_frontalface_alt2.xml')
eye = cv2.CascadeClassifier('./haarcascades/haarcascade_eye.xml')
# mouth = cv2.CascadeClassifier( './ haarcascades/haarcascade_mcs_mouth.xml')
# nose = cv2.CascadeClassifier( './haarcascades/haarcascade_mcs_nose.xml ')
#第二步，导入人脸识别的图片并将其灰度化
img = cv2.imread('./image/rl.jpg')
#第三步，进行人脸识别
#[[×,y,w,h]]
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

#检测出的人脸上再检测眼睛
# faces = facer.detectMultiScale(gray,1.1,3)
faces = facer.detectMultiScale(gray)

i = 0
j = 0
for (x,y,w,h) in faces:
    cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2)
    roi_img = img[y:y+h,x:x+w]
    eyes = eye.detectMultiScale(roi_img, 1.1,3)
    for (x,y,w,h) in eyes:
        cv2.rectangle(roi_img,(x, y),(x+w,y+h),(0,255,0),2)
        roi_eye=roi_img[y:y+h,x:x+w]
        eyename = 'eye' + str(j)
        j = j+1
        # cv2.imshow(eyename,roi_eye)

cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllwindows()