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you can try like this:

Mat trainData = ... // concatenated features, one per row

cv::Ptr<cv::flann::Index> index;

if (trainData.type() == CV_8U) // ORB
     index = makePtr<cv::flann::Index>(trainData, 
         cv::flann::LinearIndexParams(), cvflann::FLANN_DIST_HAMMING);
else // SIFT
     index =  makePtr<cv::flann::Index>(trainData, 
         cv::flann::LinearIndexParams(), cvflann::FLANN_DIST_L2);

// later...

int K=5;
cv::flann::SearchParams params;
cv::Mat dists;
cv::Mat indices;
index->knnSearch(testFeature, indices, dists, K, params);