/*
* /// <summary>
* /// Add the model descriptors
* /// </summary>
* /// <param name="modelDescriptors">The model discriptors</param>
* public void Add(Matrix<Byte> modelDescriptors)
* {
* if (!(_distanceType == DistanceType.HammingDist))
* throw new ArgumentException("Hamming distance type requires model descriptor to be Matrix<Byte>");
* gpuBruteForceMatcherAdd(_ptr, modelDescriptors);
* }
*
* /// <summary>
* /// Add the model descriptors
* /// </summary>
* /// <param name="modelDescriptors">The model discriptors</param>
* public void Add(Matrix<float> modelDescriptors)
* {
* if (!(_distanceType == DistanceType.L2 || _distanceType == DistanceType.L1))
* throw new ArgumentException("L1 / L2 distance type requires model descriptor to be Matrix<float>");
* gpuBruteForceMatcherAdd(_ptr, modelDescriptors);
* }*/
/// <summary>
/// Find the k nearest neighbour using the brute force matcher.
/// </summary>
/// <param name="queryDescriptors">The query descriptors</param>
/// <param name="modelDescriptors">The model descriptors</param>
/// <param name="k">The number of nearest neighbours to be searched</param>
/// <param name="mask">The mask</param>
public void KnnMatch(GpuMat queryDescriptors, GpuMat modelDescriptors, VectorOfVectorOfDMatch matches, int k, GpuMat mask = null, bool compactResult = false)
{
CudaInvoke.cudaBruteForceMatcherKnnMatch(_ptr, queryDescriptors, modelDescriptors, matches, k, mask, compactResult);
}