opencv 人脸识别 （一）训练样本的处理

本文实现基于eigenface的人脸检测与识别。给定一个图像数据库，进行以下步骤：

• 进行人脸检测，将检测出的人脸存入数据库2
• 对数据库2进行人脸建模
• 在测试集上进行recognition

 

本篇实现第一步：

• 进行人脸检测，将检测出的人脸存入数据库2

环境：vs2010+opencv 2.4.6.0

特征：eigenface

Input：一个人脸数据库，15个人，每人20个样本（左右）。

Output：人脸检测，并识别出每张检测到的人脸。

===============================

本文完成第一步，数据预处理：自动检测所有文件夹中每个sample中的人脸，作为训练数据。

Input：一个color文件夹，每个文件夹中有1~N这N个子文件夹，每个子文件夹内有n张包括第n类人的照片，如图。

最终结果：

核心：face detection（detectAndDraw）

辅助：截图并保存部分图片(CutImg)，文件夹内图片遍历(read_img)，图片转换成相同大小（normalizeone）

括号内分别是函数名，下面分别给出代码及说明。

1. 遍历文件夹：CBrowseDir类和CStatDir类（具体见这篇），三个文件如下：

1.1 BrowseDir.h

#pragma once
#include "direct.h"
#include "string.h"
#include "io.h"
#include "stdio.h"
#include <vector>
#include <iostream>
using namespace std;
class CBrowseDir
{
protected:
    char m_szInitDir[_MAX_PATH];

public:
    CBrowseDir();
    bool SetInitDir(const char *dir);
    bool BeginBrowse(const char *filespec);
    vector<char*> BeginBrowseFilenames(const char *filespec);

protected:
    bool BrowseDir(const char *dir,const char *filespec);
    vector<char*> GetDirFilenames(const char *dir,const char *filespec);
    virtual bool ProcessFile(const char *filename);
    virtual void ProcessDir(const char *currentdir,const char *parentdir);
};

1.2 BrowseDir.cpp

#include "BrowseDir.h"
#include "direct.h"
#include "string.h"
#include "io.h"
#include "stdio.h"
#include <vector>
#include <iostream>
using namespace std;

CBrowseDir::CBrowseDir()
{
    getcwd(m_szInitDir,_MAX_PATH);
    int len=strlen(m_szInitDir);
    if (m_szInitDir[len-1] != '\')
        strcat(m_szInitDir,"\");
}

bool CBrowseDir::SetInitDir(const char *dir)
{
    if (_fullpath(m_szInitDir,dir,_MAX_PATH) == NULL)
        return false;

    if (_chdir(m_szInitDir) != 0)
        return false;
    int len=strlen(m_szInitDir);
    if (m_szInitDir[len-1] != '\')
        strcat(m_szInitDir,"\");

    return true;
}

vector<char*>CBrowseDir:: BeginBrowseFilenames(const char *filespec)
{
    ProcessDir(m_szInitDir,NULL);
    return GetDirFilenames(m_szInitDir,filespec);
}

bool CBrowseDir::BeginBrowse(const char *filespec)
{
    ProcessDir(m_szInitDir,NULL);
    return BrowseDir(m_szInitDir,filespec);
}

bool CBrowseDir::BrowseDir(const char *dir,const char *filespec)
{
    _chdir(dir);
    long hFile;
    _finddata_t fileinfo;
    if ((hFile=_findfirst(filespec,&fileinfo)) != -1)
    {
        do
        {
            if (!(fileinfo.attrib & _A_SUBDIR))
            {
                char filename[_MAX_PATH];
                strcpy(filename,dir);
                strcat(filename,fileinfo.name);
                cout << filename << endl;
                if (!ProcessFile(filename))
                    return false;
            }
        } while (_findnext(hFile,&fileinfo) == 0);
        _findclose(hFile);
    }
    _chdir(dir);
    if ((hFile=_findfirst("*.*",&fileinfo)) != -1)
    {
        do
        {
            if ((fileinfo.attrib & _A_SUBDIR))
            {
                if (strcmp(fileinfo.name,".") != 0 && strcmp
                    (fileinfo.name,"..") != 0)
                {
                    char subdir[_MAX_PATH];
                    strcpy(subdir,dir);
                    strcat(subdir,fileinfo.name);
                    strcat(subdir,"\");
                    ProcessDir(subdir,dir);
                    if (!BrowseDir(subdir,filespec))
                        return false;
                }
            }
        } while (_findnext(hFile,&fileinfo) == 0);
        _findclose(hFile);
    }
    return true;
}

vector<char*> CBrowseDir::GetDirFilenames(const char *dir,const char *filespec)
{
    _chdir(dir);
    vector<char*>filename_vec;
    filename_vec.clear();

    long hFile;
    _finddata_t fileinfo;
    if ((hFile=_findfirst(filespec,&fileinfo)) != -1)
    {
        do
        {
            if (!(fileinfo.attrib & _A_SUBDIR))
            {
                char *filename = new char[_MAX_PATH];
                strcpy(filename,dir);
                //int st = 0;   while (dir[st++]!='');
                strcat(filename,fileinfo.name); //filename[st]='';
                filename_vec.push_back(filename);
            }
        } while (_findnext(hFile,&fileinfo) == 0);
        _findclose(hFile);
    }
    _chdir(dir);
    if ((hFile=_findfirst("*.*",&fileinfo)) != -1)
    {
        do
        {
            if ((fileinfo.attrib & _A_SUBDIR))
            {
                if (strcmp(fileinfo.name,".") != 0 && strcmp
                    (fileinfo.name,"..") != 0)
                {
                    char subdir[_MAX_PATH];
                    strcpy(subdir,dir);
                    strcat(subdir,fileinfo.name);
                    strcat(subdir,"\");
                    ProcessDir(subdir,dir);
                    return GetDirFilenames(subdir,filespec);
                }
            }
        } while (_findnext(hFile,&fileinfo) == 0);
        _findclose(hFile);
    }
    return filename_vec;
}

bool CBrowseDir::ProcessFile(const char *filename)
{
    return true;
}

void CBrowseDir::ProcessDir(const char
    *currentdir,const char *parentdir)
{
}

1.3 StatDir.h

#pragma once
#include "browsedir.h"
class CStatDir:public CBrowseDir
{
protected:
    int m_nFileCount;   //保存文件个数
    int m_nSubdirCount; //保存子目录个数

public:
    CStatDir()
    {
        m_nFileCount=m_nSubdirCount=0;
    }

    int GetFileCount()
    {
        return m_nFileCount;
    }

    int GetSubdirCount()
    {
        return m_nSubdirCount-1;
    }

protected:
    virtual bool ProcessFile(const char *filename)
    {
        m_nFileCount++;
        return CBrowseDir::ProcessFile(filename);
    }

    virtual void ProcessDir
        (const char *currentdir,const char *parentdir)
    {
        m_nSubdirCount++;
        CBrowseDir::ProcessDir(currentdir,parentdir);
    }
};

2. 辅助函数Prehelper.h, Prehelper.cpp：负责返回文件夹内所有图片（read_img），检测人脸（detectAndDraw并可以在原图中画出），截图（CutImg），提取(DetectandExtract)

2.1 Prehelper.h

//preprocessing helper
//@ Author : Rachel-Zhang

#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/contrib/contrib.hpp"
#include <cv.h>
#include <vector>
#include <utility>
using namespace cv;
using namespace std;

void normalizeone(const char* dir,IplImage* standard);

void CutImg(IplImage* src, CvRect rect,IplImage* res);

vector<Rect> detectAndDraw( Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip,bool draw );

IplImage* DetectandExtract(Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip);

int read_img(const string& dir, vector<Mat> &images);

vector<pair<char*,Mat>>  read_img(const string& dir);

2.2 Prehelper.cpp

#include "Prehelper.h"
#include "BrowseDir.h"
#include "StatDir.h"

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <cv.h>
using namespace cv;

void normalizeone(const char* dir,IplImage* standard)
{
    CStatDir statdir;
    if (!statdir.SetInitDir(dir))
    {
        puts("Dir not exist");
        return;
    }
    vector<char*>file_vec = statdir.BeginBrowseFilenames("*.*");
    int i;
    for (i=0;i<file_vec.size();i++)
    {
        IplImage* cur_img = cvLoadImage(file_vec[i],CV_LOAD_IMAGE_GRAYSCALE);
        //IplImage*cur_gray = cvCreateImage(cvGetSize(cur_img),cur_img->depth,1);
        cvResize(cur_img,standard,CV_INTER_AREA);
        //cvCvtColor(standard,cur_gray,CV_RGB2GRAY);
        //      cvNamedWindow("cur_img",CV_WINDOW_AUTOSIZE);
        //      cvNamedWindow("standard",CV_WINDOW_AUTOSIZE);
        //      cvShowImage("cur_img",cur_img);
        //      cvShowImage("standard",standard);
        //      cvWaitKey();
        cvSaveImage(file_vec[i],cur_img);
    }
}

void CutImg(IplImage* src, CvRect rect,IplImage* res)
{
    CvSize imgsize;
    imgsize.height = rect.height;
    imgsize.width = rect.width;
    cvSetImageROI(src,rect);
    cvCopy(src,res);
    cvResetImageROI(res);
}

int read_img(const string& dir, vector<Mat> &images)
{
    CStatDir statdir;
    if (!statdir.SetInitDir(dir.c_str()))
    {
        cout<<"Direct "<<dir<<"  not exist!"<<endl;
        return 0;
    }
    int cls_id = dir[dir.length()-1]-'0';
    vector<char*>file_vec = statdir.BeginBrowseFilenames("*.*");
    int i,s = file_vec.size();
    for (i=0;i<s;i++)
    {
        Mat graymat = imread(file_vec[i],0);
        //graymat.reshape(1,1);//flatten to one row
        images.push_back(graymat);
    }
    return s;
}

vector<pair<char*,Mat>>  read_img(const string& dir)
{
    CStatDir statdir;
    pair<char*,Mat> pfi;
    vector<pair<char*,Mat>> Vp;
    if (!statdir.SetInitDir(dir.c_str()))
    {
        cout<<"Direct "<<dir<<"  not exist!"<<endl;
        return Vp;
    }
    int cls_id = dir[dir.length()-1]-'0';
    vector<char*>file_vec = statdir.BeginBrowseFilenames("*.*");
    int i,s = file_vec.size();
    for (i=0;i<s;i++)
    {
        pfi.first = file_vec[i];
        pfi.second = imread(file_vec[i]);
        Vp.push_back(pfi);
    }
    return Vp;
}

vector<Rect> detectAndDraw( Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip, bool draw )
{
    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)} ;
    Mat gray, smallImg( cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );

    cvtColor( img, gray, CV_BGR2GRAY );
    resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
    equalizeHist( smallImg, smallImg );

    t = (double)cvGetTickCount();
    cascade.detectMultiScale( smallImg, faces,
        1.1, 2, 0
        |CV_HAAR_FIND_BIGGEST_OBJECT
        //|CV_HAAR_DO_ROUGH_SEARCH
        //|CV_HAAR_SCALE_IMAGE
        ,
        Size(30, 30) );
    if( tryflip )
    {
        flip(smallImg, smallImg, 1);
        cascade.detectMultiScale( smallImg, faces2,
            1.1, 2, 0
            |CV_HAAR_FIND_BIGGEST_OBJECT
            //|CV_HAAR_DO_ROUGH_SEARCH
            //|CV_HAAR_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
", t/((double)cvGetTickFrequency()*1000.) );
    if(draw)
    {
        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;
            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
                |CV_HAAR_FIND_BIGGEST_OBJECT
                //|CV_HAAR_DO_ROUGH_SEARCH
                //|CV_HAAR_DO_CANNY_PRUNING
                //|CV_HAAR_SCALE_IMAGE
                ,
                Size(30, 30) );
            //draw eyes
            //         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 );
    }
    return faces;
}

IplImage* DetectandExtract(Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip)
{
    vector<Rect> Rvec = detectAndDraw(img,cascade,nestedCascade,scale,tryflip,0);
    int i,maxxsize=0,id=-1,area;
    for (i=0;i<Rvec.size();i++)
    {
        area = Rvec[i].width*Rvec[i].height;
        if(maxxsize<area)
        {
            maxxsize = area;
            id = i;
        }
    }
    IplImage* transimg = cvCloneImage(&(IplImage)img);
    if(id!=-1)
    {
        CvSize imgsize;
        imgsize.height = Rvec[id].height;
        imgsize.width = Rvec[id].width;
        IplImage* res = cvCreateImage(imgsize,transimg->depth,transimg->nChannels);
        CutImg(transimg,Rvec[id],res);

        return res;
    }
    return NULL;
}

3. 主函数

//Detect.cpp
//Preprocessing - Detect, Cut and Save
//@Author : Rachel-Zhang

#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"

#include <cctype>
#include <iostream>
#include <iterator>
#include <stdio.h>
#include "BrowseDir.h"
#include "StatDir.h"
#include "Prehelper.h"

using namespace std;
using namespace cv;
#define CAM 2
#define PHO 1
#define K 5

string cascadeName = "E:/software/opencv2.4.6.0/data/haarcascades/haarcascade_frontalface_alt.xml";
string nestedCascadeName = "E:/software/opencv2.4.6.0/data/haarcascades/haarcascade_eye_tree_eyeglasses.xml";

int main( )
{
    CvCapture* capture = 0;
    Mat frame, frameCopy, image;
    string inputName;
    bool tryflip = false;
    int mode;
    CascadeClassifier cascade, nestedCascade;
    double scale = 1.0;
    if( !cascade.load( cascadeName ) ||!nestedCascade.load( nestedCascadeName))
    {
        cerr << "ERROR: Could not load classifier cascade or nestedCascade" << endl;//若出现该问题请去检查cascadeName，可能是opencv版本路径问题
        return -1;
    }

//  printf("select the mode of detection: 
1: from picture	 2: from camera
");
//  scanf("%d",&mode);
    char** pics = (char**) malloc(sizeof*pics);

    /************************************************************************/
    /*                                  detect face and save                                    */
    /************************************************************************/
    int i,j;
    cout<<"detect and save..."<<endl;
    const char dir[256] = "D:\Face_recognition\pic\";
        string cur_dir;
        char id[5];
    for(i=1; i<=K; i++)
    {
        cur_dir = dir;
        _itoa(i,id,10);
        cur_dir.append("color\");
        cur_dir.append(id);
        vector<pair<char*,Mat>> imgs=read_img(cur_dir);
        for(j=0;j<imgs.size();j++)
        {
            IplImage* res = DetectandExtract(imgs[j].second,cascade,nestedCascade,scale,tryflip);
            if(res)
                cvSaveImage(imgs[j].first,res);
        }
    }
    return 0;
}

正确的输出就是一系列人脸检测时间，且原文件夹内的图片变成了检测出的人脸（如上面结果图所示）。

文章所用代码打包链接：http://download.csdn.net/detail/abcjennifer/7047853

from: http://blog.csdn.net/abcjennifer/article/details/20396869