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Hi,

I have three classes: 0,1 and 2. These three classes basically consist of a vector of 2D Points. I am trying to train them and use SVM For predicting a correct class,for a given set of 2D Points.

So, basically my input is std::vector<point2d> and output is just a label (like 0,1,2). I am using openCv 3.4 and I wrote the below code. I am getting lot of errors like "channels is not a member of cv:;DataType"

void getSCMCategoryClass( std::vector<Point2d> Tn, std::vector<Point2d> R1n, std::vector<Point2d> R2n, std::vector<Point2d> R3n)
{
    // 1. we need to setup the traindata (a Mat of N rows, and 8 cols, each feature on a row) 
    // and trainlabels (a Mat with N rows, and 1 col):
    std::vector<std::vector<Point2d>> trainingList;
    trainingList.push_back( R1n );
    trainingList.push_back( R2n );
    trainingList.push_back( R3n );
    Mat trainData( 3, 1, CV_32F );
    Mat trainLabels( 3, 1, CV_32S );

for ( int r = 0; r < 3; r++ )
{
    trainData.at<std::vector<Point2d>>( r, 0 ) = trainingList.at(r); 
    trainLabels.at<int>( r, 0 ) = r; 
}

//// 2. now we can setup the SVM, and train it:
Ptr<SVM> svm = SVM::create();
svm->setType( SVM::C_SVC );
svm->setKernel( SVM::LINEAR );
svm->train( trainData, ROW_SAMPLE, trainLabels );

//// 3. now to the prediction (on a single sample):
Mat testData( 1, 1, CV_32F );
testData.at<std::vector<Point2d>>( 0, 0 ) = Tn; 

int predicted_label = ( int )svm->predict( testData );

}

I understand that,while inserting the elements inside training Data,I cannot use data types like "point2d". How do I make the code workable?