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samples/cpp/tutorial_code/ml/introduction_to_svm/introduction_to_svm.cpp

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+#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**)
+{
+    // Set up training data
+    //! [setup1]
+    int labels[4] = {1, -1, -1, -1};
+    float trainingData[4][2] = { {501, 10}, {255, 10}, {501, 255}, {10, 501} };
+    //! [setup1]
+    //! [setup2]
+    Mat trainingDataMat(4, 2, CV_32F, trainingData);
+    Mat labelsMat(4, 1, CV_32SC1, labels);
+    //! [setup2]
+
+    // Train the SVM
+    //! [init]
+    Ptr<SVM> svm = SVM::create();
+    svm->setType(SVM::C_SVC);
+    svm->setKernel(SVM::LINEAR);
+    svm->setTermCriteria(TermCriteria(TermCriteria::MAX_ITER, 100, 1e-6));
+    //! [init]
+    //! [train]
+    svm->train(trainingDataMat, ROW_SAMPLE, labelsMat);
+    //! [train]
+
+    // Data for visual representation
+    int width = 512, height = 512;
+    Mat image = Mat::zeros(height, width, CV_8UC3);
+
+    // Show the decision regions given by the SVM
+    //! [show]
+    Vec3b green(0,255,0), blue(255,0,0);
+    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]
+
+    // Show the training data
+    //! [show_data]
+    int thickness = -1;
+    circle( image, Point(501,  10), 5, Scalar(  0,   0,   0), thickness );
+    circle( image, Point(255,  10), 5, Scalar(255, 255, 255), thickness );
+    circle( image, Point(501, 255), 5, Scalar(255, 255, 255), thickness );
+    circle( image, Point( 10, 501), 5, Scalar(255, 255, 255), thickness );
+    //! [show_data]
+
+    // Show support vectors
+    //! [show_vectors]
+    thickness = 2;
+    Mat sv = svm->getUncompressedSupportVectors();
+
+    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);
+    }
+    //! [show_vectors]
+
+    imwrite("result.png", image);        // save the image
+
+    imshow("SVM Simple Example", image); // show it to the user
+    waitKey();
+    return 0;
+}