template class cvflann::HierarchicalClusteringIndex
Overview
Hierarchical index
Contains a tree constructed through a hierarchical clustering and other information for indexing a set of points for nearest-neighbour matching. More…
#include <hierarchical_clustering_index.h> template <typename Distance> class HierarchicalClusteringIndex: public cvflann::NNIndex { public: // typedefs typedef Distance::ResultType DistanceType; typedef Distance::ElementType ElementType; // structs struct Node; // construction HierarchicalClusteringIndex( const Matrix<ElementType>& inputData, const IndexParams& index_params = HierarchicalClusteringIndexParams(), Distance d = Distance() ); HierarchicalClusteringIndex(const HierarchicalClusteringIndex&); // methods virtual void buildIndex(); virtual void findNeighbors( ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams ); void free_elements(); virtual IndexParams getParameters() const; virtual flann_algorithm_t getType() const; virtual void loadIndex(FILE* stream); HierarchicalClusteringIndex& operator=(const HierarchicalClusteringIndex&); virtual void saveIndex(FILE* stream); virtual size_t size() const; virtual int usedMemory() const; virtual size_t veclen() const; };
Inherited Members
public: // methods virtual void buildIndex() = 0; virtual void findNeighbors( ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams ) = 0; virtual IndexParams getParameters() const = 0; virtual flann_algorithm_t getType() const = 0; virtual void knnSearch( const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params ); virtual void loadIndex(FILE* stream) = 0; virtual int radiusSearch( const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params ); virtual void saveIndex(FILE* stream) = 0; virtual size_t size() const = 0; virtual int usedMemory() const = 0; virtual size_t veclen() const = 0;
Detailed Documentation
Hierarchical index
Contains a tree constructed through a hierarchical clustering and other information for indexing a set of points for nearest-neighbour matching.
Construction
HierarchicalClusteringIndex( const Matrix<ElementType>& inputData, const IndexParams& index_params = HierarchicalClusteringIndexParams(), Distance d = Distance() )
Index constructor
Params: inputData = dataset with the input features params = parameters passed to the hierarchical k-means algorithm
Methods
virtual void buildIndex()
Builds the index
virtual void findNeighbors( ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams )
Find set of nearest neighbors to vec. Their indices are stored inside the result object.
Params: result = the result object in which the indices of the nearest-neighbors are stored vec = the vector for which to search the nearest neighbors searchParams = parameters that influence the search algorithm (checks)
void free_elements()
Release the inner elements of indices[]
virtual IndexParams getParameters() const
Returns:
The index parameters
virtual flann_algorithm_t getType() const
Returns:
The index type (kdtree, kmeans,…)
virtual void loadIndex(FILE* stream)
Loads the index from a stream.
Parameters:
stream | The stream from which the index is loaded |
virtual void saveIndex(FILE* stream)
Saves the index to a stream.
Parameters:
stream | The stream to save the index to |
virtual size_t size() const
Returns size of index.
virtual int usedMemory() const
Computes the inde memory usage Returns: memory used by the index
virtual size_t veclen() const
Returns the length of an index feature.