Learning OPENCV--HOG+SVM

#include"cv.h"#include"highgui.h"#include"stdafx.h"#include<ml.h>#include<iostream>#include<fstream>#include<string>#include<vector>using namespaceCV;using namespacestd;intMainintargcChar**argv) {Vector<string>Img_path; Vector<int>IMG_CATG; intNLine =0; stringbuf; Ifstream Svm_data ("E:/svm_data.txt" ); unsignedLongN;  while(svm_data) {if(Getline (Svm_data, buf)) {NLine++; if(NLine%2==0) {img_catg.push_back (Atoi (Buf.c_str () ));//atoi converting strings to integers, flags (0,1)            }            Else{img_path.push_back (BUF);//Image Path}}} svm_data.close ();//Close FileCvmat*data_mat, *Res_mat; intNimgnum = nLine/2;//number of read-in Samples    ////Sample Matrix, Nimgnum: Horizontal axis is the number of samples, WIDTH * HEIGHT: Sample eigenvector, that is, image sizeData_mat = Cvcreatemat (Nimgnum,1764, CV_32FC1);    Cvsetzero (Data_mat); //type matrix, which stores the type flags for each sampleRes_mat = Cvcreatemat (Nimgnum,1, CV_32FC1);    Cvsetzero (Res_mat); Iplimage*src; Iplimage* Trainimg=cvcreateimage (Cvsize ( -, -),8,3);//images that need to be analyzed     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:"<Endl; Continue; } cout<<"processing"<Endl;   Cvresize (SRC,TRAINIMG); //Reading PicturesHogdescriptor *hog=NewHogdescriptor (Cvsize ( -, -), Cvsize ( -, -), Cvsize (8,8), Cvsize (8,8),9);//See reference article for specific meaningsvector<float>descriptors;//result ArrayHog->compute (Trainimg, Descriptors,size (1,1), Size (0,0));//call the calculation function to start the calculationcout<<"HOG dims:"<<descriptors.size () <<Endl; //cvmat* Svmtrainmat=cvcreatemat (Descriptors.size (), 1,CV_32FC1);n=0;  for(vector<float>::iterator Iter=descriptors.begin (); Iter!=descriptors.end (); iter++) {Cvmset (Data_mat,i,n,*ITER); N++; }                //cout<<svmtrainmat->rows<<endl;Cvmset (Res_mat, I,0, Img_catg[i]); cout<<"End Processing"<" "<Endl; } CVSVM SVM=CVSVM ();      Cvsvmparams param;      Cvtermcriteria criteria; Criteria= Cvtermcriteria (Cv_termcrit_eps, +, Flt_epsilon); Param= Cvsvmparams (Cvsvm::c_svc, CVSVM::RBF,10.0,0.09,1.0,10.0,0.5,1.0, NULL, criteria); /*Type of SVM: Cvsvm::c_svc kernel type: CVSVM::RBF degree:10.0 (not used this time) gamma:8.0 coef0:1.0 (not used this time)                                                           c:10.0 nu:0.5 (not used this time) p:0.1 (not used this time) then normalizes the training data and places it in an array of cvmat types. */         //☆☆☆☆☆☆☆☆☆ (5) SVM Learning ☆☆☆☆☆☆☆☆☆☆☆☆Svm.train (Data_mat, res_mat, null, NULL, param); //★ ☆ Using training data and determined learning parameters, the SVM learning ☆☆☆☆Svm.save ("Svm_data.xml" ); //test SampleIplimage *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); Charline[ +]; 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:"<Endl; Continue;        } cvzero (TRAINIMG);   Cvresize (TEST,TRAINIMG); //Reading PicturesHogdescriptor *hog=NewHogdescriptor (Cvsize ( -, -), Cvsize ( -, -), Cvsize (8,8), Cvsize (8,8),9);//See reference article for specific meaningsvector<float>descriptors;//result ArrayHog->compute (Trainimg, Descriptors,size (1,1), Size (0,0));//call the calculation function to start the calculationcout<<"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++; }        intRET =svm.predict (Svmtrainmat); sprintf (line,"%s%d\r\n", Img_tst_path[j].c_str (), ret); Predict_txt<<Line ; } predict_txt.close ();//cvreleaseimage (&SRC);//cvreleaseimage (&sampleimg);//cvreleaseimage (&TST);//cvreleaseimage (&tst_tmp);Cvreleasemat (&Data_mat); Cvreleasemat (&Res_mat);return 0;}

from:http://blog.csdn.net/yangtrees/article/details/7471222

Learning OPENCV--HOG+SVM