Face Service_電腦視覺-Face Service

# _*_ coding:utf-8 _*_#人臉定位技術#Face Service原理：首先將映像轉換為灰階圖，然後載入OpenCV提供的面部特徵庫，

接著調用HaarDetectObjects找到人臉的位置

#實現方法1

import cv2import cv2.cv as cvdef findface(image):    grayscale=cv.CreateImage((image.width,image.height),8,1)    cv.CvtColor(image,grayscale,cv.CV_BGR2GRAY)    cascade=cv.Load("D:\Python\opencv\opencv\sources\data\haarcascades

    \haarcascade_frontalface_default.xml")    rect=cv.HaarDetectObjects(grayscale,cascade,cv.CreateMemStorage(),1.015,2,cv.CV_HAAR_DO_CANNY_PRUNING)    result=[]    for r in rect:        result.append([(r[0][0],r[0][1]),(r[0][0]+r[0][2],r[0][1]+r[0][3])])    return resultfn='17310582.jpg'my_img=cv.LoadImage(fn)#擷取臉在映像中的座標faceresult=findface(my_img)myimg=cv2.imread(fn)for ii in range(0,len(faceresult)):    cv2.rectangle(myimg,faceresult[ii][0],faceresult[ii][1],(0,0,255))cv2.namedWindow('img')cv2.imshow()cv2.waitKey()cv2.destroyAllWindows()

實現方法二：

import numpyimport cv2#識別人臉face_cascade = cv2.CascadeClassifier("D:\Python\opencv\opencv\sources

              \data\haarcascades\haarcascade_frontalface_default.xml")#識別眼睛和嘴eye_cascade = cv2.CascadeClassifier("D:\Python\opencv\opencv\sources

             \data\haarcascades\haarcascade_eye.xml")img = cv2.imread("17310620.jpg")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), (0, 0, 255), 2)    ro_gray = gray[y:y + h, x:x + w]    ro_color = img[y:y + h, x:x + w]    eyes = eye_cascade.detectMultiScale(ro_gray)    for (ex, ey, ew, eh) in eyes:        cv2.rectangle(ro_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)cv2.imshow('img', img)cv2.waitKey(0)cv2.destroyAllWindows()