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
#include
using namespace std;
class CBrowseDir
{
protected:
char m_szInitDir[_MAX_PATH];
public:
CBrowseDir();
bool SetInitDir(const char *dir);
bool BeginBrowse(const char *filespec);
vector BeginBrowseFilenames(const char *filespec);
protected:
bool BrowseDir(const char *dir,const char *filespec);
vector 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
#include
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;
}
vectorCBrowseDir:: 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 CBrowseDir::GetDirFilenames(const char *dir,const char *filespec)
{
_chdir(dir);
vectorfilename_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++]!='\0');
strcat(filename,fileinfo.name); //filename[st]='\0';
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
#include
#include
using namespace cv;
using namespace std;
void normalizeone(const char* dir,IplImage* standard);
void CutImg(IplImage* src, CvRect rect,IplImage* res);
vector 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 &images);
vector> read_img(const string& dir);
2.2 Prehelper.cpp
#include "Prehelper.h"
#include "BrowseDir.h"
#include "StatDir.h"
#include
#include
#include
using namespace cv;
void normalizeone(const char* dir,IplImage* standard)
{
CStatDir statdir;
if (!statdir.SetInitDir(dir))
{
puts("Dir not exist");
return;
}
vectorfile_vec = statdir.BeginBrowseFilenames("*.*");
int i;
for (i=0;idepth,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 &images)
{
CStatDir statdir;
if (!statdir.SetInitDir(dir.c_str()))
{
cout<<"Direct "<file_vec = statdir.BeginBrowseFilenames("*.*");
int i,s = file_vec.size();
for (i=0;i> read_img(const string& dir)
{
CStatDir statdir;
pair pfi;
vector> Vp;
if (!statdir.SetInitDir(dir.c_str()))
{
cout<<"Direct "<file_vec = statdir.BeginBrowseFilenames("*.*");
int i,s = file_vec.size();
for (i=0;i detectAndDraw( Mat& img, CascadeClassifier& cascade,
CascadeClassifier& nestedCascade,
double scale, bool tryflip, bool draw )
{
int i = 0;
double t = 0;
vector 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::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.) );
if(draw)
{
for( vector::const_iterator r = faces.begin(); r != faces.end(); r++, i++ )
{
Mat smallImgROI;
vector 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::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 Rvec = detectAndDraw(img,cascade,nestedCascade,scale,tryflip,0);
int i,maxxsize=0,id=-1,area;
for (i=0;idepth,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
#include
#include
#include
#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: \n1: from picture\t 2: from camera\n");
// scanf("%d",&mode);
char** pics = (char**) malloc(sizeof*pics);
/************************************************************************/
/* detect face and save */
/************************************************************************/
int i,j;
cout<<"detect and save..."<> imgs=read_img(cur_dir);
for(j=0;j 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
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