SVM_Linear.cpp

/*
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/ml/ml.hpp>

using namespace cv;

int main()
{
	// Data for visual representation
	int width = 512, height = 512;
	Mat image = Mat::zeros(height, width, CV_8UC3);

	// Set up training data
	float labels[4] = { 1.0, -1.0, -1.0, -1.0 };
	Mat labelsMat(4, 1, CV_32FC1, labels);

	float trainingData[4][2] = { { 501, 10 },{ 255, 10 },{ 501, 255 },{ 10, 501 } };
	Mat trainingDataMat(4, 2, CV_32FC1, trainingData);

	// Set up SVM's parameters
	CvSVMParams params;
	params.svm_type = CvSVM::C_SVC;
	params.kernel_type = CvSVM::LINEAR;
	params.term_crit = cvTermCriteria(CV_TERMCRIT_ITER, 100, 1e-6);

	// Train the SVM
	CvSVM SVM;
	SVM.train(trainingDataMat, labelsMat, Mat(), Mat(), params);

	Vec3b green(0, 255, 0), blue(255, 0, 0);
	// Show the decision regions given by the SVM
	for (int i = 0; i < image.rows; ++i)
		for (int j = 0; j < image.cols; ++j)
		{
			Mat sampleMat = (Mat_<float>(1, 2) << j, i);
			float response = SVM.predict(sampleMat);

			if (response == 1)
				image.at<Vec3b>(i, j) = green;
			else if (response == -1)
				image.at<Vec3b>(i, j) = blue;
		}

	// Show the training data
	int thickness = -1;
	int lineType = 8;
	circle(image, Point(501, 10), 5, Scalar(0, 0, 0), thickness, lineType);
	circle(image, Point(255, 10), 5, Scalar(255, 255, 255), thickness, lineType);
	circle(image, Point(501, 255), 5, Scalar(255, 255, 255), thickness, lineType);
	circle(image, Point(10, 501), 5, Scalar(255, 255, 255), thickness, lineType);

	// Show support vectors
	thickness = 2;
	lineType = 8;
	int c = SVM.get_support_vector_count();

	for (int i = 0; i < c; ++i)
	{
		const float* v = SVM.get_support_vector(i);
		circle(image, Point((int)v[0], (int)v[1]), 6, Scalar(128, 128, 128), thickness, lineType);
	}

	imwrite("result.png", image);        // save the image

	imshow("SVM Simple Example", image); // show it to the user
	waitKey(0);

}
*/