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| CompositeIndex (const Matrix< ElementType > &inputData, const IndexParams ¶ms=CompositeIndexParams(), Distance d=Distance()) |
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| CompositeIndex (const CompositeIndex &) |
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virtual | ~CompositeIndex () |
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void | buildIndex () CV_OVERRIDE |
| Builds the index.
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void | findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const SearchParams &searchParams) CV_OVERRIDE |
| Method that searches for nearest-neighbours.
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IndexParams | getParameters () const CV_OVERRIDE |
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flann_algorithm_t | getType () const CV_OVERRIDE |
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void | loadIndex (FILE *stream) CV_OVERRIDE |
| Loads the index from a stream.
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CompositeIndex & | operator= (const CompositeIndex &) |
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void | saveIndex (FILE *stream) CV_OVERRIDE |
| Saves the index to a stream.
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size_t | size () const CV_OVERRIDE |
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int | usedMemory () const CV_OVERRIDE |
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size_t | veclen () const CV_OVERRIDE |
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virtual | ~NNIndex () |
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virtual void | knnSearch (const Matrix< ElementType > &queries, Matrix< int > &indices, Matrix< DistanceType > &dists, int knn, const SearchParams ¶ms) |
| Perform k-nearest neighbor search.
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virtual int | radiusSearch (const Matrix< ElementType > &query, Matrix< int > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams ¶ms) |
| Perform radius search.
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template<typename Distance>
class cvflann::CompositeIndex< Distance >
This index builds a kd-tree index and a k-means index and performs nearest neighbour search both indexes. This gives a slight boost in search performance as some of the neighbours that are missed by one index are found by the other.