Exemplo n.º 1
0
 /// <summary>
 /// Add the model descriptors
 /// </summary>
 /// <param name="modelDescriptors">The model discriptors</param>
 public void Add(Matrix <Byte> modelDescriptors)
 {
     if (!(_distanceType == DistanceType.Hamming || _distanceType == DistanceType.HammingLUT))
     {
         throw new ArgumentException("Hamming distance type requires model descriptor to be Matrix<Byte>");
     }
     DescriptorMatcherInvoke.CvDescriptorMatcherAdd(_ptr, modelDescriptors);
 }
Exemplo n.º 2
0
 /// <summary>
 /// Add the model descriptors
 /// </summary>
 /// <param name="modelDescriptors">The model discriptors</param>
 public void Add(Matrix <float> modelDescriptors)
 {
     if (!(_distanceType == DistanceType.L2F32 || _distanceType == DistanceType.L1F32))
     {
         throw new ArgumentException("L1 / L2 distance type requires model descriptor to be Matrix<float>");
     }
     DescriptorMatcherInvoke.CvDescriptorMatcherAdd(_ptr, modelDescriptors);
 }
Exemplo n.º 3
0
 /// <summary>
 /// Add the model descriptors
 /// </summary>
 /// <param name="modelDescriptors">The model descriptors</param>
 public void Add(IInputArray modelDescriptors)
 {
     using (InputArray iaModelDescriptors = modelDescriptors.GetInputArray())
         DescriptorMatcherInvoke.CvDescriptorMatcherAdd(_descriptorMatcherPtr, iaModelDescriptors);
 }
Exemplo n.º 4
0
 /// <summary>
 /// Find the k-nearest match
 /// </summary>
 /// <param name="queryDescriptor">An n x m matrix of descriptors to be query for nearest neighbours. n is the number of descriptor and m is the size of the descriptor</param>
 /// <param name="k">Number of nearest neighbors to search for</param>
 /// <param name="mask">Can be null if not needed. An n x 1 matrix. If 0, the query descriptor in the corresponding row will be ignored.</param>
 /// <param name="matches">Matches. Each matches[i] is k or less matches for the same query descriptor.</param>
 public void KnnMatch(IInputArray queryDescriptor, VectorOfVectorOfDMatch matches, int k, IInputArray mask)
 {
     using (InputArray iaQueryDesccriptor = queryDescriptor.GetInputArray())
         using (InputArray iaMask = mask == null ? InputArray.GetEmpty() : mask.GetInputArray())
             DescriptorMatcherInvoke.CvDescriptorMatcherKnnMatch(_descriptorMatcherPtr, iaQueryDesccriptor, matches, k, iaMask);
 }
Exemplo n.º 5
0
 /// <summary>
 /// Find the k-nearest match for DistanceType of Hamming or HammingLUT
 /// </summary>
 /// <param name="queryDescriptor">An n x m matrix of descriptors to be query for nearest neighbours. n is the number of descriptor and m is the size of the descriptor</param>
 /// <param name="trainIdx">The resulting n x <paramref name="k"/> matrix of descriptor index from the training descriptors</param>
 /// <param name="distance">The resulting n x <paramref name="k"/> matrix of distance value from the training descriptors</param>
 /// <param name="k">Number of nearest neighbors to search for</param>
 /// <param name="mask">Can be null if not needed. An n x 1 matrix. If 0, the query descriptor in the corresponding row will be ignored.</param>
 public void KnnMatch(Matrix <Byte> queryDescriptor, Matrix <int> trainIdx, Matrix <float> distance, int k, Matrix <Byte> mask)
 {
     Debug.Assert(_distanceType == DistanceType.Hamming || _distanceType == DistanceType.HammingLUT);
     DescriptorMatcherInvoke.CvDescriptorMatcherKnnMatch(Ptr, queryDescriptor, trainIdx, distance, k, mask);
 }