I have trained an SVM for image classification as shown below. The training seem to be going on well but when I predict a row (any row of the training vector), SVM return just one value (60). What could I have done wrong? Is my training and testing approach right as shown in the function below?
void trainSVM(Mat hists, vector labels){
Ptr trainData = TrainData::create(hists, ml::ROW_SAMPLE, labels);
Ptr svm = SVM::create();
svm->setKernel(SVM::LINEAR);
cout << "Training SVM..." << endl;
svm->train(trainData);
bool trained = svm->isTrained();
if (trained)
{
cout << "SVM Trained. Saving..." << endl;
svm->save(".\\Trained Models\\LBPSVM.yml");
cout << "SVM Model Saved." << endl;
}
Mat_ output;
svm->predict(hists, output);
float pred = svm->predict(hists.row(34));
cout << "SVM Output = " << output.at(0) << endl;
writeMatToFile(output, "SVNPredict.csv");
}
The value stored in variable **pred** is the same regardless of the row I try to predict. It is the same value I get in my single column matrix **output**. All rows are populated with same value. Kindly help.
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