OpenCV  2.4.13.3
Open Source Computer Vision
cvflann::LshIndex< Distance > Class Template Reference

#include <lsh_index.h>

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

Public Types

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

Public Member Functions

 LshIndex (const Matrix< ElementType > &input_data, const IndexParams &params=LshIndexParams(), Distance d=Distance())
 
 LshIndex (const LshIndex &)
 
LshIndexoperator= (const LshIndex &)
 
void addIndex (const Matrix< ElementType > &wholeData, const Matrix< ElementType > &additionalData)
 
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
 
IndexParams getParameters () const
 
virtual void knnSearch (const Matrix< ElementType > &queries, Matrix< int > &indices, Matrix< DistanceType > &dists, int knn, const SearchParams &params)
 Perform k-nearest neighbor search. More...
 
void findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const 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::LshIndex< 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::LshIndex< Distance >::DistanceType

§ ElementType

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

Constructor & Destructor Documentation

§ LshIndex() [1/2]

template<typename Distance>
cvflann::LshIndex< Distance >::LshIndex ( const Matrix< ElementType > &  input_data,
const IndexParams params = LshIndexParams(),
Distance  d = Distance() 
)
inline

Constructor

Parameters
input_datadataset with the input features
paramsparameters passed to the LSH algorithm
dthe distance used

§ LshIndex() [2/2]

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

Member Function Documentation

§ addIndex()

template<typename Distance>
void cvflann::LshIndex< Distance >::addIndex ( const Matrix< ElementType > &  wholeData,
const Matrix< ElementType > &  additionalData 
)
inlinevirtual

Implementation for the LSH addable indexes after that.

Parameters
wholeDatawhole dataset with the input features
additionalDataadditional dataset with the input features

Implements cvflann::NNIndex< Distance >.

§ buildIndex()

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

Builds the index

Implements cvflann::NNIndex< Distance >.

§ findNeighbors()

template<typename Distance>
void cvflann::LshIndex< Distance >::findNeighbors ( ResultSet< DistanceType > &  result,
const ElementType vec,
const 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::LshIndex< Distance >::getParameters ( ) const
inlinevirtual
Returns
The index parameters

Implements cvflann::NNIndex< Distance >.

§ getType()

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

Implements cvflann::NNIndex< Distance >.

§ knnSearch()

template<typename Distance>
virtual void cvflann::LshIndex< 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::LshIndex< 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>
LshIndex& cvflann::LshIndex< Distance >::operator= ( const LshIndex< Distance > &  )

§ saveIndex()

template<typename Distance>
void cvflann::LshIndex< 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::LshIndex< Distance >::size ( ) const
inlinevirtual

Returns size of index.

Implements cvflann::NNIndex< Distance >.

§ usedMemory()

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

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

Implements cvflann::NNIndex< Distance >.

§ veclen()

template<typename Distance>
size_t cvflann::LshIndex< 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: