cvflann::KDTreeSingleIndex< Distance > Class Template Reference

#include <kdtree_single_index.h>

Inheritance diagram for cvflann::KDTreeSingleIndex< Distance >:

Public Types
typedef Distance::ElementType	ElementType
typedef Distance::ResultType	DistanceType

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

addIndex()

template<typename Distance>

void cvflann::KDTreeSingleIndex< Distance >::addIndex ( const Matrix< ElementType > &  , const Matrix< ElementType > &    )

inlinevirtual

Dummy implementation for other algorithms of addable indexes after that.

Implements cvflann::NNIndex< Distance >.

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]	queries	The query points for which to find the nearest neighbors
[out]	indices	The indices of the nearest neighbors found
[out]	dists	Distances to the nearest neighbors found
[in]	knn	Number of nearest neighbors to return
[in]	params	Search 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

stream

The 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

stream

The 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 >.

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

• kdtree_single_index.h