OpenCV的SVM用法

在OpenCV當中，SVM是作為一個類來定義介面的，其定義略顯複雜。不過，如果你對libSVM比較瞭解，就會發現，OpenCV的SVM介面與libSVM的介面非常接近。下面，我還利用前面介紹libSVM用法時的資料，通過一個簡單的例子程式來介紹OpenCV的SVM模組函式的用法。

// OpencvSVM.cpp : Defines the entry point for the console application.

//

#include "stdafx.h"

#include "cv.h"

#include "ml.h"

#include "iostream"

using namespace std;

double inputArr[10][13] = 

{

1,0.708333,1,1,-0.320755,-0.105023,-1,1,-0.419847,-1,-0.225806,0,1, 

-1,0.583333,-1,0.333333,-0.603774,1,-1,1,0.358779,-1,-0.483871,0,-1,

1,0.166667,1,-0.333333,-0.433962,-0.383562,-1,-1,0.0687023,-1,-0.903226,-1,-1,

-1,0.458333,1,1,-0.358491,-0.374429,-1,-1,-0.480916,1,-0.935484,0,-0.333333,

-1,0.875,-1,-0.333333,-0.509434,-0.347032,-1,1,-0.236641,1,-0.935484,-1,-0.333333,

-1,0.5,1,1,-0.509434,-0.767123,-1,-1,0.0534351,-1,-0.870968,-1,-1,

1,0.125,1,0.333333,-0.320755,-0.406393,1,1,0.0839695,1,-0.806452,0,-0.333333,

1,0.25,1,1,-0.698113,-0.484018,-1,1,0.0839695,1,-0.612903,0,-0.333333,

1,0.291667,1,1,-0.132075,-0.237443,-1,1,0.51145,-1,-0.612903,0,0.333333,

1,0.416667,-1,1,0.0566038,0.283105,-1,1,0.267176,-1,0.290323,0,1

};

double testArr[]=

{

0.25,1,1,-0.226415,-0.506849,-1,-1,0.374046,-1,-0.83871,0,-1

};

int _tmain(int argc, _TCHAR* argv[])

{

CvSVM svm;

CvSVMParams param;

param.svm_type = 100;

param.kernel_type = 1;

param.degree = 4;

param.gamma = 4;

param.coef0 = 1;

CvMat *dataMat = cvCreateMat(10, 12, CV_32FC1);

CvMat *labelMat = cvCreateMat(10, 1, CV_32SC1);

for (int i=0; i<10; i++)

{

for (int j=0; j<12; j++)

{

cvSetReal2D(dataMat, i, j, inputArr[i][j+1]);

}

cvSetReal2D(labelMat, i, 0, inputArr[i][0]);

}

svm.train(dataMat, labelMat, NULL, NULL, param);

svm.save("c:/svmResult.txt");

CvMat *testMat = cvCreateMat(1, 12, CV_32FC1);

for (int i=0; i<12; i++)

{

cvSetReal2D(testMat, 0, i, testArr[i]);

}

float flag = 0;

flag = svm.predict(testMat);

cout<<"testMat, flag = "<<flag<<endl;

system("pause");

cvReleaseMat(&dataMat);

cvReleaseMat(&labelMat);

cvReleaseMat(&testMat);

return 0;

}