OpenCV  4.0.0
Open Source Computer Vision
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cvflann::KDTreeSingleIndex< Distance > Class Template Reference

#include "kdtree_single_index.h"

Inheritance diagram for cvflann::KDTreeSingleIndex< Distance >:
cvflann::NNIndex< Distance >

Public Types

typedef Distance::ResultType DistanceType
 
typedef Distance::ElementType ElementType
 

Public Member Functions

 KDTreeSingleIndex (const Matrix< ElementType > &inputData, const IndexParams &params=KDTreeSingleIndexParams(), Distance d=Distance())
 
 KDTreeSingleIndex (const KDTreeSingleIndex &)
 
 ~KDTreeSingleIndex ()
 
void buildIndex () CV_OVERRIDE
 
void findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const SearchParams &searchParams) CV_OVERRIDE
 
IndexParams getParameters () const CV_OVERRIDE
 
flann_algorithm_t getType () const CV_OVERRIDE
 
void knnSearch (const Matrix< ElementType > &queries, Matrix< int > &indices, Matrix< DistanceType > &dists, int knn, const SearchParams &params) CV_OVERRIDE
 Perform k-nearest neighbor search. More...
 
void loadIndex (FILE *stream) CV_OVERRIDE
 Loads the index from a stream. More...
 
KDTreeSingleIndexoperator= (const KDTreeSingleIndex &)
 
void saveIndex (FILE *stream) CV_OVERRIDE
 Saves the index to a stream. More...
 
size_t size () const CV_OVERRIDE
 
int usedMemory () const CV_OVERRIDE
 
size_t veclen () const CV_OVERRIDE
 
- Public Member Functions inherited from cvflann::NNIndex< Distance >
virtual ~NNIndex ()
 
virtual int radiusSearch (const Matrix< ElementType > &query, Matrix< int > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams &params)
 Perform radius search. More...
 

Detailed Description

template<typename Distance>
class cvflann::KDTreeSingleIndex< Distance >

Randomized kd-tree index

Contains the k-d trees and other information for indexing a set of points for nearest-neighbor matching.

Member Typedef Documentation

§ DistanceType

template<typename Distance>
typedef Distance::ResultType cvflann::KDTreeSingleIndex< Distance >::DistanceType

§ ElementType

template<typename Distance>
typedef Distance::ElementType cvflann::KDTreeSingleIndex< Distance >::ElementType

Constructor & Destructor Documentation

§ KDTreeSingleIndex() [1/2]

template<typename Distance>
cvflann::KDTreeSingleIndex< Distance >::KDTreeSingleIndex ( const Matrix< ElementType > &  inputData,
const IndexParams params = KDTreeSingleIndexParams(),
Distance  d = Distance() 
)
inline

KDTree constructor

Params: inputData = dataset with the input features params = parameters passed to the kdtree algorithm

§ KDTreeSingleIndex() [2/2]

template<typename Distance>
cvflann::KDTreeSingleIndex< Distance >::KDTreeSingleIndex ( const KDTreeSingleIndex< Distance > &  )

§ ~KDTreeSingleIndex()

template<typename Distance>
cvflann::KDTreeSingleIndex< Distance >::~KDTreeSingleIndex ( )
inline

Standard destructor

Member Function Documentation

§ buildIndex()

template<typename Distance>
void cvflann::KDTreeSingleIndex< Distance >::buildIndex ( )
inlinevirtual

Builds the index

Implements cvflann::NNIndex< Distance >.

§ findNeighbors()

template<typename Distance>
void cvflann::KDTreeSingleIndex< Distance >::findNeighbors ( ResultSet< DistanceType > &  result,
const ElementType vec,
const SearchParams searchParams 
)
inlinevirtual

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 maxCheck = the maximum number of restarts (in a best-bin-first manner)

Implements cvflann::NNIndex< Distance >.

§ getParameters()

template<typename Distance>
IndexParams cvflann::KDTreeSingleIndex< Distance >::getParameters ( ) const
inlinevirtual
Returns
The index parameters

Implements cvflann::NNIndex< Distance >.

§ getType()

template<typename Distance>
flann_algorithm_t cvflann::KDTreeSingleIndex< Distance >::getType ( ) const
inlinevirtual
Returns
The index type (kdtree, kmeans,...)

Implements cvflann::NNIndex< Distance >.

§ knnSearch()

template<typename Distance>
void cvflann::KDTreeSingleIndex< Distance >::knnSearch ( const Matrix< ElementType > &  queries,
Matrix< int > &  indices,
Matrix< DistanceType > &  dists,
int  knn,
const SearchParams params 
)
inlinevirtual

Perform k-nearest neighbor search.

Parameters
[in]queriesThe query points for which to find the nearest neighbors
[out]indicesThe indices of the nearest neighbors found
[out]distsDistances to the nearest neighbors found
[in]knnNumber of nearest neighbors to return
[in]paramsSearch parameters

Reimplemented from cvflann::NNIndex< Distance >.

§ loadIndex()

template<typename Distance>
void cvflann::KDTreeSingleIndex< Distance >::loadIndex ( FILE *  stream)
inlinevirtual

Loads the index from a stream.

Parameters
streamThe stream from which the index is loaded

Implements cvflann::NNIndex< Distance >.

§ operator=()

template<typename Distance>
KDTreeSingleIndex& cvflann::KDTreeSingleIndex< Distance >::operator= ( const KDTreeSingleIndex< Distance > &  )

§ saveIndex()

template<typename Distance>
void cvflann::KDTreeSingleIndex< Distance >::saveIndex ( FILE *  stream)
inlinevirtual

Saves the index to a stream.

Parameters
streamThe stream to save the index to

Implements cvflann::NNIndex< Distance >.

§ size()

template<typename Distance>
size_t cvflann::KDTreeSingleIndex< Distance >::size ( ) const
inlinevirtual

Returns size of index.

Implements cvflann::NNIndex< Distance >.

§ usedMemory()

template<typename Distance>
int cvflann::KDTreeSingleIndex< Distance >::usedMemory ( ) const
inlinevirtual

Computes the inde memory usage Returns: memory used by the index

Implements cvflann::NNIndex< Distance >.

§ veclen()

template<typename Distance>
size_t cvflann::KDTreeSingleIndex< Distance >::veclen ( ) const
inlinevirtual

Returns the length of an index feature.

Implements cvflann::NNIndex< Distance >.


The documentation for this class was generated from the following file: