Opencv+SVM对HOG进行训练

想使用CvSVM进行训练和检测

自己写了个程序，训练的结果出来了，但检测达不到自己希望的程度

我希望说可以检测处一张图片的那个位置有人体

但是CvSVM似乎紧紧是返回1和0

使用hog.detectMultiScale(img, found, 0, Size(8,8), Size(32,32), 1.05, 2)

但这个函数需要一个检测算子，而不是XML文件

需要一个转换的过程，但没有弄懂怎么转换！还在研究中

这里贴出把图片读入并训练成xml文件的程序

如果谁知道怎么得到检测算子，请告诉我，万分感谢！

#include <fstream>
#include <string>
#include <cv.h>
#include <highgui.h>
#include <ml.h>
#include <iostream>
#include <fstream>
#include <string>
#include <vector>
#include "cvaux.h"
#include <iostream>

using namespace std;
using namespace cv;

int main()
{
CvSVM svm;
//CvMat *feature_vec_mat,*res_mat;
int size = 2416+1218;
CvMat *feature_vec_mat,*res_mat;
feature_vec_mat = cvCreateMat(size,3780,CV_32FC1);
cvSetZero(feature_vec_mat);
res_mat = cvCreateMat(size,1,CV_32FC1);
cvSetZero(res_mat);
int i;

////////////////////////////////////////正样本/////////////////////////////////////////////////
/////////////////////////////////read this picture filename///////////////////////////////////
ifstream readfile("D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/pos.lst",ios::in| ios::binary);
ifstream readfile1("D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/neg.lst",ios::in| ios::binary);
for(i=0;i<2416;i++)
{
//ifstream readfile("D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/pos.lst",ios::in| ios::binary);
char filename[100];
readfile.getline(filename,100);
cout<<filename<<endl;
char filename1[1024];
//sprintf(filename1,"D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/".filename);
strcpy(filename1,"D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/");
strcat(filename1,filename);

////////////////////////////////read the data of the picture///////////////////////////////////
Mat img;
img = imread(filename1);
//imshow("example",img);
//waitKey(1);

/////////////////////////////////chenge zhe picture to the 64*128////////////////////////////////
Mat imgtest(128,64,CV_8UC1);
for(int j=0;j<128;j++)
{
for(int n=0;n<64;n++)
{
*(imgtest.data+j*imgtest.step+n)=*(img.data+(j+16)*img.step+(n+16)*3);
}
}
//imshow("example",imgtest);
//waitKey(0);

/////////////////////////////////computer hog feature/////////////////////////////////////////
HOGDescriptor hog;
vector<float> descriptors;
hog.compute(imgtest,descriptors,Size(8,8));
int feature_vec_length = descriptors.size();          //int feature_vec_length = 3780;
for (int j=0;j<feature_vec_length;j++)
{
//feature_vec_mat->data.fl[j][i]=descriptors[i];
CV_MAT_ELEM(*feature_vec_mat, float, i, j ) = descriptors[j];
//feature_vec_mat->data.fl[j+i*feature_vec_mat->step]=descriptors[i];
}
//CV_MAT_ELEM(*res_mat, float, i, 1 ) = 1;
res_mat->data.fl[i] = 1;
}
//fclose(readfile);

//////////////////////////////////////////负样本///////////////////////////////////////////
for(int e=0;e<1218;e++)
{
//ifstream readfile("D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/pos.lst",ios::in| ios::binary);
char filename[100];
readfile1.getline(filename,100);
cout<<filename<<endl;
char filename1[1024];
//sprintf(filename1,"D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/".filename);
strcpy(filename1,"D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/");
strcat(filename1,filename);

////////////////////////////////read the data of the picture///////////////////////////////////
Mat img;
img = imread(filename1);
//imshow("example",img);
//waitKey(1);

/////////////////////////////////chenge zhe picture to the 64*128////////////////////////////////
Mat imgtest(128,64,CV_8UC1);
for(int j=0;j<128;j++)
{
for(int n=0;n<64;n++)
{
*(imgtest.data+j*imgtest.step+n)=*(img.data+(j+16)*img.step+(n+16)*3);
}
}
//imshow("example",imgtest);
//waitKey(0);

/////////////////////////////////computer hog feature/////////////////////////////////////////
HOGDescriptor hog;
vector<float> descriptors;
hog.compute(imgtest,descriptors,Size(8,8));
int feature_vec_length = descriptors.size();          //int feature_vec_length = 3780;
for (int j=0;j<feature_vec_length;j++)
{
//feature_vec_mat->data.fl[j][i]=descriptors[i];
CV_MAT_ELEM(*feature_vec_mat, float, e+2416, j ) = descriptors[j];
//feature_vec_mat->data.fl[j+i*feature_vec_mat->step]=descriptors[i];
}
//CV_MAT_ELEM(*res_mat, float, i+100, 1 ) = 0;
res_mat->data.fl[e+2416] = 0;
}

///////////////////////////////////////train SVM////////////////////////////////////////////////////
CvTermCriteria criteria;
criteria = cvTermCriteria(CV_TERMCRIT_EPS,1000,FLT_EPSILON);
svm.train(feature_vec_mat,res_mat,NULL,NULL,CvSVMParams(CvSVM::C_SVC,CvSVM::RBF,10.0,0.09,1.0,10.0,0.5,1.0,NULL,criteria));
svm.save("D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/result.xml");
//svm.load("D:/My Documents/Visual Studio 2008/Projects/hogjiance/Debug/result.xml");
//svm.get_support_vector
return 0;
}