#include <opencv2/core.hpp>#include <opencv2/imgproc.hpp>#include "opencv2/imgcodecs.hpp"#include <opencv2/highgui.hpp>#include <opencv2/ml.hpp>using namespace cv;using namespace cv::ml;int main(int, char**){ // Data for visual representation int width = 512, height = 512; Mat image = Mat::zeros(height, width, CV_8UC3); // Set up training data int labels[4] = {1, -1, -1, -1}; Mat labelsMat(4, 1, CV_32SC1, 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 SVM::Params params; params.svmType = SVM::C_SVC; params.kernelType = SVM::LINEAR; params.termCrit = TermCriteria(TermCriteria::MAX_ITER, 100, 1e-6); // Train the SVM Ptr<SVM> svm = StatModel::train<SVM>(trainingDataMat, ROW_SAMPLE, labelsMat, 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; Mat sv = svm->getSupportVectors(); for (int i = 0; i < sv.rows; ++i) { const float* v = sv.ptr<float>(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);} 1 0
