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I would like to learn svm implementation by using opencv 3.00 library in C++ and Visual Studio 2013. My code:

#include<stdio.h>
#include<math.h>
#include<opencv\cv.h>
#include<opencv\highgui.h>
#include<opencv2\objdetect\objdetect.hpp>
#include<opencv2\highgui\highgui.hpp>
#include<opencv2\imgproc\imgproc.hpp>
#include<vector>
#include <windows.h>
#include <atlstr.h>
#include <iostream>
#include <sstream>
#include <iomanip>
#include <opencv2\imgproc\imgproc.hpp>
#include <opencv2\core\core.hpp>
#include <opencv2\highgui\highgui.hpp>
#include <opencv\cvaux.hpp>

using namespace cv;
using namespace std;

#include <opencv2\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

    Ptr<ml::SVM> svm = ml::SVM::create();
    // edit: the params struct got removed,
    // we use setter/getter now:
    svm->setType(ml::SVM::C_SVC);
    svm->setKernel(ml::SVM::LINEAR);
    svm->setGamma(3);

    svm->train(trainingDataMat, ml::ROW_SAMPLE, labelsMat);

    Mat res;   // output


    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, res);

        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);

}

After running this code, I got that error:

OpenCV Error: Bad argument < in the case of classification problem the responses must be categorical; 
either specify varType when creating TrainData, or pass integer responses > in cv::ml::SVMImpl::train, 
file C:\builds\master_PackSlave-win64-vc12-shared\opencv\modules\ml\src\svm.cpp, line 1610

I debugged that code. The debugger stops at this line: svm->train(trainingDataMat, ml::ROW_SAMPLE, labelsMat); It says:

First-chance exception at 0x000007FEFDA5AAAD in train.exe: Microsoft C++ exception: cv::Exception at memory location 0x00000000001CEE50.
    Unhandled exception at 0x000007FEFDA5AAAD in train.exe: Microsoft C++ exception: cv::Exception at memory location 0x00000000001CEE50

Actually, what I understand is that the problem is related to the memory.