这里总结网上自己找到的资料,搞一个简单的框架供大家参考一下。 OpenCV官方的SVM代码在http://www./opencvdoc/2.3.2/html/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.html 在http://blog.csdn.net/sangni007/article/details/7471222看到一段还不错的代码,结构清楚,虽然注释比较少,但很有参考价值,于是我添加了一些注释,看着更舒服。废话少说,直接上代码: - [cpp] view plaincopyprint
- #include "cv.h"
- #include "highgui.h"
- #include "stdafx.h"
- #include <ml.h>
- #include <iostream>
- #include <fstream>
- #include <string>
- #include <vector>
- using namespace cv;
- using namespace std;
-
-
- int main(int argc, char** argv)
- {
- vector<string> img_path;
- vector<int> img_catg;
- int nLine = 0;
- string buf;
- ifstream svm_data( "E:/SVM_DATA.txt" );
- unsigned long n;
-
- while( svm_data )
- {
- if( getline( svm_data, buf ) )
- {
- nLine ++;
- if( nLine % 2 == 0 )
- {
- img_catg.push_back( atoi( buf.c_str() ) );
- }
- else
- {
- img_path.push_back( buf );
- }
- }
- }
- svm_data.close();
-
- CvMat *data_mat, *res_mat;
- int nImgNum = nLine / 2;
-
- data_mat = cvCreateMat( nImgNum, 1764, CV_32FC1 );
- cvSetZero( data_mat );
-
- res_mat = cvCreateMat( nImgNum, 1, CV_32FC1 );
- cvSetZero( res_mat );
-
- IplImage* src;
- IplImage* trainImg=cvCreateImage(cvSize(64,64),8,3);
-
-
- for( string::size_type i = 0; i != img_path.size(); i++ )
- {
- src=cvLoadImage(img_path[i].c_str(),1);
- if( src == NULL )
- {
- cout<<" can not load the image: "<<img_path[i].c_str()<<endl;
- continue;
- }
-
- cout<<" processing "<<img_path[i].c_str()<<endl;
-
- cvResize(src,trainImg);
- HOGDescriptor *hog=new HOGDescriptor(cvSize(64,64),cvSize(16,16),cvSize(8,8),cvSize(8,8),9);
- vector<float>descriptors;
- hog->compute(trainImg, descriptors,Size(1,1), Size(0,0));
- cout<<"HOG dims: "<<descriptors.size()<<endl;
-
- n=0;
- for(vector<float>::iterator iter=descriptors.begin();iter!=descriptors.end();iter++)
- {
- cvmSet(data_mat,i,n,*iter);
- n++;
- }
-
- cvmSet( res_mat, i, 0, img_catg[i] );
- cout<<" end processing "<<img_path[i].c_str()<<" "<<img_catg[i]<<endl;
- }
-
-
- CvSVM svm = CvSVM();
- CvSVMParams param;
- CvTermCriteria criteria;
- criteria = cvTermCriteria( CV_TERMCRIT_EPS, 1000, FLT_EPSILON );
- param = CvSVMParams( CvSVM::C_SVC, CvSVM::RBF, 10.0, 0.09, 1.0, 10.0, 0.5, 1.0, NULL, criteria );
-
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- svm.train( data_mat, res_mat, NULL, NULL, param );
-
- svm.save( "SVM_DATA.xml" );
-
-
- IplImage *test;
- vector<string> img_tst_path;
- ifstream img_tst( "E:/SVM_TEST.txt" );
- while( img_tst )
- {
- if( getline( img_tst, buf ) )
- {
- img_tst_path.push_back( buf );
- }
- }
- img_tst.close();
-
-
-
- CvMat *test_hog = cvCreateMat( 1, 1764, CV_32FC1 );
- char line[512];
- ofstream predict_txt( "SVM_PREDICT.txt" );
- for( string::size_type j = 0; j != img_tst_path.size(); j++ )
- {
- test = cvLoadImage( img_tst_path[j].c_str(), 1);
- if( test == NULL )
- {
- cout<<" can not load the image: "<<img_tst_path[j].c_str()<<endl;
- continue;
- }
-
- cvZero(trainImg);
- cvResize(test,trainImg);
- HOGDescriptor *hog=new HOGDescriptor(cvSize(64,64),cvSize(16,16),cvSize(8,8),cvSize(8,8),9);
- vector<float>descriptors;
- hog->compute(trainImg, descriptors,Size(1,1), Size(0,0));
- cout<<"HOG dims: "<<descriptors.size()<<endl;
- CvMat* SVMtrainMat=cvCreateMat(1,descriptors.size(),CV_32FC1);
- n=0;
- for(vector<float>::iterator iter=descriptors.begin();iter!=descriptors.end();iter++)
- {
- cvmSet(SVMtrainMat,0,n,*iter);
- n++;
- }
-
- int ret = svm.predict(SVMtrainMat);
- std::sprintf( line, "%s %d\r\n", img_tst_path[j].c_str(), ret );
- predict_txt<<line;
- }
- predict_txt.close();
-
-
-
-
-
- cvReleaseMat( &data_mat );
- cvReleaseMat( &res_mat );
-
- return 0;
- }
其中,关于HOG函数HOGDescriptor,见博客http://blog.csdn.net/raocong2010/article/details/6239431另外,自己需要把这个程序嵌入到另外一个工程中去,因为那里数据类型是Mat,不是cvMat,所以我又修改了上面的程序,并且图片大小也不是固定的64*64,需要自己设置一下图片大小,因为太懒,直接把改好的程序放过来: - #include "stdafx.h"
-
- #include "cv.h"
- #include "highgui.h"
- #include "stdafx.h"
- #include <ml.h>
- #include <iostream>
- #include <fstream>
- #include <string>
- #include <vector>
- using namespace cv;
- using namespace std;
-
-
- int main(int argc, char** argv)
- {
- int ImgWidht = 120;
- int ImgHeight = 120;
- vector<string> img_path;
- vector<int> img_catg;
- int nLine = 0;
- string buf;
- ifstream svm_data( "E:/apple/SVM_DATA.txt" );
- unsigned long n;
-
- while( svm_data )
- {
- if( getline( svm_data, buf ) )
- {
- nLine ++;
- if( nLine < 5 )
- {
- img_catg.push_back(1);
- img_path.push_back( buf );
- }
- else
- {
- img_catg.push_back(0);
- img_path.push_back( buf );
- }
- }
- }
- svm_data.close();
-
- Mat data_mat, res_mat;
- int nImgNum = nLine;
-
-
-
- res_mat = Mat::zeros( nImgNum, 1, CV_32FC1 );
-
- Mat src;
- Mat trainImg = Mat::zeros(ImgHeight, ImgWidht, CV_8UC3);
-
- for( string::size_type i = 0; i != img_path.size(); i++ )
- {
- src = imread(img_path[i].c_str(), 1);
-
- cout<<" processing "<<img_path[i].c_str()<<endl;
-
- resize(src, trainImg, cv::Size(ImgWidht,ImgHeight), 0, 0, INTER_CUBIC);
- HOGDescriptor *hog=new HOGDescriptor(cvSize(ImgWidht,ImgHeight),cvSize(16,16),cvSize(8,8),cvSize(8,8), 9);
- vector<float>descriptors;
- hog->compute(trainImg, descriptors, Size(1,1), Size(0,0));
- if (i==0)
- {
- data_mat = Mat::zeros( nImgNum, descriptors.size(), CV_32FC1 );
- }
- cout<<"HOG dims: "<<descriptors.size()<<endl;
- n=0;
- for(vector<float>::iterator iter=descriptors.begin();iter!=descriptors.end();iter++)
- {
- data_mat.at<float>(i,n) = *iter;
- n++;
- }
-
- res_mat.at<float>(i, 0) = img_catg[i];
- cout<<" end processing "<<img_path[i].c_str()<<" "<<img_catg[i]<<endl;
- }
-
- CvSVM svm = CvSVM();
- CvSVMParams param;
- CvTermCriteria criteria;
- criteria = cvTermCriteria( CV_TERMCRIT_EPS, 1000, FLT_EPSILON );
- param = CvSVMParams( CvSVM::C_SVC, CvSVM::RBF, 10.0, 0.09, 1.0, 10.0, 0.5, 1.0, NULL, criteria );
-
-
-
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-
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- svm.train( data_mat, res_mat, Mat(), Mat(), param );
-
- svm.save( "E:/apple/SVM_DATA.xml" );
-
-
- vector<string> img_tst_path;
- ifstream img_tst( "E:/apple/SVM_TEST.txt" );
- while( img_tst )
- {
- if( getline( img_tst, buf ) )
- {
- img_tst_path.push_back( buf );
- }
- }
- img_tst.close();
-
- Mat test;
- char line[512];
- ofstream predict_txt( "E:/apple/SVM_PREDICT.txt" );
- for( string::size_type j = 0; j != img_tst_path.size(); j++ )
- {
- test = imread( img_tst_path[j].c_str(), 1);
- resize(test, trainImg, cv::Size(ImgWidht,ImgHeight), 0, 0, INTER_CUBIC);
- HOGDescriptor *hog=new HOGDescriptor(cvSize(ImgWidht,ImgHeight),cvSize(16,16),cvSize(8,8),cvSize(8,8),9);
- vector<float>descriptors;
- hog->compute(trainImg, descriptors,Size(1,1), Size(0,0));
- cout<<"The Detection Result:"<<endl;
- cout<<"HOG dims: "<<descriptors.size()<<endl;
- Mat SVMtrainMat = Mat::zeros(1,descriptors.size(),CV_32FC1);
- n=0;
- for(vector<float>::iterator iter=descriptors.begin();iter!=descriptors.end();iter++)
- {
- SVMtrainMat.at<float>(0,n) = *iter;
- n++;
- }
-
- int ret = svm.predict(SVMtrainMat);
- std::sprintf( line, "%s %d\r\n", img_tst_path[j].c_str(), ret );
- printf("%s %d\r\n", img_tst_path[j].c_str(), ret);
- getchar();
- predict_txt<<line;
- }
- predict_txt.close();
-
- return 0;
- }
就到这里吧,再整理一下思路。 如果运行的时候出现Link错误,有可能是没有附加依赖项,要添加opencv_objdetect230d.lib,我的OpenCV是2.3版本,所以这里是230.
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