Opencv 3 SVM training

Question

As you may know, many things changed in OpenCV 3 (in comparision to the openCV2 or the old first version).

In the old days, to train SVM one would use:

Answer 1

with opencv3.0, it's definitely different , but not difficult:

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::POLY);
svm->setGamma(3); 

Mat trainData; // one row per feature
Mat labels;    
svm->train( trainData , ml::ROW_SAMPLE , labels );
// ...
Mat query; // input, 1channel, 1 row (apply reshape(1,1) if nessecary)
Mat res;   // output
svm->predict(query, res);

Answer 2

I was porting my code from OpenCV 2.4.9 to 3.0.0-rc1 and had the same issue. Unfortunately the API has changes since the answer was posted, so I would like to update it accordingly:

Ptr<ml::SVM> svm = ml::SVM::create();
svm->setType(ml::SVM::C_SVC);
svm->setKernel(ml::SVM::POLY);
svm->setGamma(3);

Mat trainData; // one row per feature
Mat labels;    
Ptr<ml::TrainData> tData = ml::TrainData::create(trainData, ml::SampleTypes::ROW_SAMPLE, labels);
svm->train(tData);
// ...
Mat query; // input, 1channel, 1 row (apply reshape(1,1) if nessecary)
Mat res;   // output
svm->predict(query, res);

Answer 3

I know this is an old post, but i came across it looking for the same solution. This tutorial is extremely helpful: http://docs.opencv.org/3.0-beta/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.html