Randomized kd-tree index. More...

#include <opencv2/flann/kdtree_single_index.h>

Inheritance diagram for cvflann::KDTreeSingleIndex< Distance >:

Collaboration diagram for cvflann::KDTreeSingleIndex< 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())
	KDTree constructor. More...

	KDTreeSingleIndex (const KDTreeSingleIndex &)

	~KDTreeSingleIndex ()
	Standard destructor. More...

void	buildIndex () CV_OVERRIDE
	Builds the index. More...

void	findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const SearchParams &searchParams) CV_OVERRIDE
	Find set of nearest neighbors to vec. More...

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...

KDTreeSingleIndex &	operator= (const KDTreeSingleIndex &)

virtual int	radiusSearch (const Matrix< ElementType > &query, Matrix< int > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams &params)
	Perform radius search. More...

void	saveIndex (FILE *stream) CV_OVERRIDE
	Saves the index to a stream. More...

size_t	size () const CV_OVERRIDE
	Returns size of index. More...

int	usedMemory () const CV_OVERRIDE
	Computes the inde memory usage Returns: memory used by the index. More...

size_t	veclen () const CV_OVERRIDE
	Returns the length of an index feature. 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

References cvflann::get_param().

Here is the call graph for this function:

◆ 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 >.

References cvflann::ResultSet< DistanceType >::addPoint(), cvflann::get_param(), cvflann::load_value(), cv::max(), cv::min(), cvflann::save_value(), cv::swap(), and cvflann::ResultSet< DistanceType >::worstDist().

Here is the call graph for this function:

◆ 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 >.

References cvflann::FLANN_INDEX_KDTREE_SINGLE.

◆ 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 >.

References cvflann::KNNSimpleResultSet< DistanceType >::init().

Here is the call graph for this function:

◆ 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 >.

References cvflann::load_value().

Here is the call graph for this function:

◆ operator=()

template<typename Distance>

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

◆ radiusSearch()

template<typename Distance>

virtual int cvflann::NNIndex< Distance >::radiusSearch	(	const Matrix< ElementType > &	query,
		Matrix< int > &	indices,
		Matrix< DistanceType > &	dists,
		float	radius,
		const SearchParams &	params
	)

inlinevirtualinherited

Perform radius search.

Parameters

[in]	query	The query point
[out]	indices	The indinces of the neighbors found within the given radius
[out]	dists	The distances to the nearest neighbors found
[in]	radius	The radius used for search
[in]	params	Search parameters

Returns: Number of neighbors found

Reimplemented in cvflann::Index< Distance >, cvflann::Index< cv::L2< ElementType > >, and cvflann::Index< cv::L1< ElementType > >.

◆ 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 >.

References cvflann::save_value().

Here is the call graph for this function:

◆ 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:

opencv2/flann/kdtree_single_index.h

Public Types

Public Member Functions

Detailed Description

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

Member Typedef Documentation

◆ DistanceType

◆ ElementType

Constructor & Destructor Documentation

◆ KDTreeSingleIndex() [1/2]

◆ KDTreeSingleIndex() [2/2]

◆ ~KDTreeSingleIndex()

Member Function Documentation

◆ buildIndex()

◆ findNeighbors()

◆ getParameters()

◆ getType()

◆ knnSearch()

◆ loadIndex()

◆ operator=()

◆ radiusSearch()

◆ saveIndex()

◆ size()

◆ usedMemory()

◆ veclen()

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