脸部识别实现（vs2013+opencv3.0）

第一种实现

1. 这种是通过研究源码 更改而来,第二种是第一种的简化,代码少了很多,而且逻辑比较清楚;具体的实现在代码里面有注释,虽然是英文的,还是比较简单,需要注意的一个api就是:cascade.detectMultiScale()

2. cascade.detectMultiScale()理解:

           #include "opencv2/objdetect.hpp"
           #include "opencv2/imgcodecs.hpp"
           #include "opencv2/videoio.hpp"
           #include "opencv2/highgui.hpp"
           #include "opencv2/imgproc.hpp"
           #include "opencv2/core/utility.hpp"
           
           #include "opencv2/videoio/videoio_c.h"
           #include "opencv2/highgui/highgui_c.h"
           
           #include <cctype>
           #include <iostream>
           #include <iterator>
           #include <stdio.h>
           
           using namespace std;
           using namespace cv; 
           void detectAndDraw(Mat& img, CascadeClassifier& cascade,
           CascadeClassifier& nestedCascade,
           double scale, bool tryflip);
       
       //要使用到的两个cascade文件,用于联合检测人脸,opencv自带了多个xml文件，在opencv安装目录下的/source/data/haarcascades/ 文件夹内
       string cascadeName = "D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
       //D:\opencv\opencv\sources\data\haarcascades
       string nestedCascadeName = "D:\\opencv\\opencv\\sources\\data\\haarcascades\\haarcascade_eye_tree_eyeglasses.xml";//检测眼睛
       
       int main()
       {
           CvCapture* capture = 0;
           Mat frame, frameCopy, image;
           CascadeClassifier cascade, nestedCascade;//D:\\code\\opencv\\face\\face\\face\\2.jpg
           char *srcImageFile = "D:\\code\\opencv\\face\\face\\face\\2.jpg";//测试图片
           double scale = 1.3;
           if (!cascade.load(cascadeName))//载入cascade文件
           {
               cerr << "ERROR: Could not load classifier cascade" << endl;
               return -1;
           }
       
           cv::VideoCapture camera(CV_CAP_ANY);
           if (!camera.isOpened())
               return -1;
       
           // 得到帧率  
           double rate = camera.get(CV_CAP_PROP_FPS);
       
           cvNamedWindow("result", 1);
           while (true)
           {
               if (!camera.read(image))
                   break;
               detectAndDraw(image, cascade, nestedCascade, scale, 0);//检测人脸
               int c = waitKey(20);
               if ((char)c == 27)break;
           }
           //以下部分为实现加载图片然后检测
           //image = imread(srcImageFile);
           //cout << "In image read" << endl;
           //if (!image.empty())
           //{
           //  detectAndDraw(image, cascade, nestedCascade, scale, 0);//检测人脸
           //  waitKey(0);
           //}
           cvDestroyWindow("result");
           camera.release();
           return 0;
       }
       
       void detectAndDraw(Mat& img, CascadeClassifier& cascade,CascadeClassifier& nestedCascade,double scale, bool tryflip)
       {
           int i = 0;
           double t = 0;
           vector<Rect> faces, faces2;
           const static Scalar colors[] = {
               CV_RGB(0, 0, 255),
               CV_RGB(0, 128, 255),
               CV_RGB(0, 255, 255),
               CV_RGB(0, 255, 0),
               CV_RGB(255, 128, 0),
               CV_RGB(255, 255, 0),
               CV_RGB(255, 0, 0),
               CV_RGB(255, 0, 255) };//用于画线
           Mat gray, smallImg(cvRound(img.rows / scale), cvRound(img.cols / scale), CV_8UC1);
       
           cvtColor(img, gray, COLOR_BGR2GRAY);
           resize(gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR);
           equalizeHist(smallImg, smallImg);
       
           t = (double)cvGetTickCount();
           cascade.detectMultiScale(smallImg, faces,
               1.1, 2, 0
               //|CASCADE_FIND_BIGGEST_OBJECT
               //|CASCADE_DO_ROUGH_SEARCH
               | CASCADE_SCALE_IMAGE,
               Size(30, 30));
           if (tryflip)
           {
               flip(smallImg, smallImg, 1);
               cascade.detectMultiScale(smallImg, faces2,
                   1.1, 2, 0
                   //|CASCADE_FIND_BIGGEST_OBJECT
                   //|CASCADE_DO_ROUGH_SEARCH
       
                   | CASCADE_SCALE_IMAGE,
                   Size(30, 30));
               for (vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++)
               {
                   faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
               }
           }
           t = (double)cvGetTickCount() - t;
           printf("detection time = %g ms\n", t / ((double)cvGetTickFrequency()*1000.));
           for (vector<Rect>::const_iterator r = faces.begin(); r != faces.end(); r++, i++)
           {
               Mat smallImgROI;
               vector<Rect> nestedObjects;
               Point center;
               Scalar color = colors[i % 8];
               int radius;
       
               double aspect_ratio = (double)r->width / r->height;
               if (0.75 < aspect_ratio && aspect_ratio < 1.3)
               {
                   center.x = cvRound((r->x + r->width*0.5)*scale);
                   center.y = cvRound((r->y + r->height*0.5)*scale);
                   radius = cvRound((r->width + r->height)*0.25*scale);
                   circle(img, center, radius, color, 3, 8, 0);
               }
               else
                   rectangle(img, cvPoint(cvRound(r->x*scale), cvRound(r->y*scale)),
                   cvPoint(cvRound((r->x + r->width - 1)*scale), cvRound((r->y + r->height - 1)*scale)),
                   color, 3, 8, 0);
               if (nestedCascade.empty())
                   continue;
               smallImgROI = smallImg(*r);
               nestedCascade.detectMultiScale(smallImgROI, nestedObjects,
                   1.1, 2, 0
                   //|CASCADE_FIND_BIGGEST_OBJECT
                   //|CASCADE_DO_ROUGH_SEARCH
                   //|CASCADE_DO_CANNY_PRUNIN
       
                   | CASCADE_SCALE_IMAGE
                   ,
                   Size(30, 30));
               for (vector<Rect>::const_iterator nr = nestedObjects.begin(); nr != nestedObjects.end(); nr++)
               {
                   center.x = cvRound((r->x + nr->x + nr->width*0.5)*scale);
                   center.y = cvRound((r->y + nr->y + nr->height*0.5)*scale);
                   radius = cvRound((nr->width + nr->height)*0.25*scale);
                   circle(img, center, radius, color, 3, 8, 0);
               }
           }
           cv::imshow("result", img);
       }
   

第二种实现形式

    #include "opencv2/objdetect.hpp"
    #include "opencv2/highgui.hpp"
    #include "opencv2/imgproc.hpp"
    
    #include <iostream>
    #include <stdio.h>
    
    using namespace std;
    using namespace cv;
    
    
    void detectAndDisplay(Mat frame);
    
    String face_cascade_name = "D://opencv//opencv//sources//data//haarcascades//haarcascade_frontalface_alt.xml";
    String eyes_cascade_name = "D://opencv//opencv//sources//data//haarcascades//haarcascade_eye_tree_eyeglasses.xml";
    CascadeClassifier face_cascade;
    CascadeClassifier eyes_cascade;
    String window_name = "Capture - Face detection";
    
    int main(void)
    {
        VideoCapture capture;
        Mat frame;
    
    
        if (!face_cascade.load(face_cascade_name)){ printf("--(!) Error loading face casecade\n"); return -1; }
        if (!eyes_cascade.load(eyes_cascade_name)){ printf("--(!) Error loading eyes cascade\n");  return -1;}
    
    
        //cv::VideoCapture camera(CV_CAP_ANY);
        //if (!camera.isOpened())
        //  return -1;
    
        //open the capture ;and pay attation the CV_CAP_ANY,when you input 0.it' failed ,it appears the device parm is not 0,it convient input CV_CAP_ANY;
        capture.open(CV_CAP_ANY);
        if (!capture.isOpened()){printf("-- Error opening video capture \n");return -1;}
        
        //capture read the frame;
        while (capture.read(frame))
        {
            if (frame.empty()){printf(" -- (!)Error No Capture frame --break"); break;}
            detectAndDisplay(frame);
            int c = waitKey(20);
            if ((char)c == 27){ break; }
    
        }
        return 0;
    }
    
    
    void detectAndDisplay(Mat frame)
    {
        std::vector<Rect> faces;
        Mat frame_gray;
    
        //convert to gray image,and equailzehist 
        cvtColor(frame, frame_gray, COLOR_BGR2GRAY);
        equalizeHist(frame_gray, frame_gray);
    
        //detect face
        face_cascade.detectMultiScale(frame_gray, faces, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));
    
    
        for (size_t i = 0; i < faces.size(); i++)
        {
            //gain the face center coordinate 
            Point center(faces[i].x + faces[i].width / 2, faces[i].y + faces[i].height / 2);
            ellipse(frame, center, Size(faces[i].width / 2, faces[i].height / 2), 0, 0, 360, Scalar(255, 0, 255), 2, 8, 0);
    
    
            Mat faceROI = frame_gray(faces[i]);
            std::vector<Rect> eyes;
            eyes_cascade.detectMultiScale(faceROI, eyes, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));
    
            for (size_t j = 0; j < eyes.size(); j++)
            {
                Point eye_center(faces[i].x + eyes[j].x + eyes[j].width / 2, faces[i].y + eyes[j].y + eyes[j].height / 2);
                int radius = cvRound((eyes[j].width + eyes[j].height)*0.25);
                circle(frame, eye_center, radius, Scalar(255, 0, 0), 4, 8, 0);
            }
        }
        imshow(window_name, frame);
    }