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195 lines
5.8 KiB
C++
195 lines
5.8 KiB
C++
/***********************************************************************
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* Software License Agreement (BSD License)
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*
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* Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
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* Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
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*
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* THE BSD LICENSE
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
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* IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
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* NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
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* THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*************************************************************************/
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#ifndef OPENCV_FLANN_COMPOSITE_INDEX_H_
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#define OPENCV_FLANN_COMPOSITE_INDEX_H_
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#include "general.h"
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#include "nn_index.h"
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#include "kdtree_index.h"
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#include "kmeans_index.h"
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namespace cvflann
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{
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/**
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* Index parameters for the CompositeIndex.
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*/
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struct CompositeIndexParams : public IndexParams
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{
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CompositeIndexParams(int trees = 4, int branching = 32, int iterations = 11,
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flann_centers_init_t centers_init = FLANN_CENTERS_RANDOM, float cb_index = 0.2 )
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{
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(*this)["algorithm"] = FLANN_INDEX_KMEANS;
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// number of randomized trees to use (for kdtree)
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(*this)["trees"] = trees;
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// branching factor
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(*this)["branching"] = branching;
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// max iterations to perform in one kmeans clustering (kmeans tree)
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(*this)["iterations"] = iterations;
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// algorithm used for picking the initial cluster centers for kmeans tree
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(*this)["centers_init"] = centers_init;
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// cluster boundary index. Used when searching the kmeans tree
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(*this)["cb_index"] = cb_index;
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}
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};
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/**
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* This index builds a kd-tree index and a k-means index and performs nearest
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* neighbour search both indexes. This gives a slight boost in search performance
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* as some of the neighbours that are missed by one index are found by the other.
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*/
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template <typename Distance>
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class CompositeIndex : public NNIndex<Distance>
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{
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public:
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typedef typename Distance::ElementType ElementType;
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typedef typename Distance::ResultType DistanceType;
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/**
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* Index constructor
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* @param inputData dataset containing the points to index
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* @param params Index parameters
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* @param d Distance functor
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* @return
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*/
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CompositeIndex(const Matrix<ElementType>& inputData, const IndexParams& params = CompositeIndexParams(),
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Distance d = Distance()) : index_params_(params)
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{
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kdtree_index_ = new KDTreeIndex<Distance>(inputData, params, d);
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kmeans_index_ = new KMeansIndex<Distance>(inputData, params, d);
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}
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CompositeIndex(const CompositeIndex&);
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CompositeIndex& operator=(const CompositeIndex&);
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virtual ~CompositeIndex()
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{
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delete kdtree_index_;
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delete kmeans_index_;
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}
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/**
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* @return The index type
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*/
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flann_algorithm_t getType() const
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{
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return FLANN_INDEX_COMPOSITE;
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}
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/**
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* @return Size of the index
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*/
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size_t size() const
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{
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return kdtree_index_->size();
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}
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/**
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* \returns The dimensionality of the features in this index.
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*/
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size_t veclen() const
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{
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return kdtree_index_->veclen();
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}
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/**
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* \returns The amount of memory (in bytes) used by the index.
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*/
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int usedMemory() const
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{
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return kmeans_index_->usedMemory() + kdtree_index_->usedMemory();
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}
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/**
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* \brief Builds the index
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*/
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void buildIndex()
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{
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Logger::info("Building kmeans tree...\n");
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kmeans_index_->buildIndex();
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Logger::info("Building kdtree tree...\n");
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kdtree_index_->buildIndex();
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}
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/**
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* \brief Saves the index to a stream
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* \param stream The stream to save the index to
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*/
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void saveIndex(FILE* stream)
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{
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kmeans_index_->saveIndex(stream);
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kdtree_index_->saveIndex(stream);
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}
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/**
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* \brief Loads the index from a stream
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* \param stream The stream from which the index is loaded
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*/
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void loadIndex(FILE* stream)
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{
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kmeans_index_->loadIndex(stream);
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kdtree_index_->loadIndex(stream);
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}
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/**
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* \returns The index parameters
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*/
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IndexParams getParameters() const
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{
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return index_params_;
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}
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/**
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* \brief Method that searches for nearest-neighbours
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*/
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void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams)
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{
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kmeans_index_->findNeighbors(result, vec, searchParams);
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kdtree_index_->findNeighbors(result, vec, searchParams);
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}
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private:
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/** The k-means index */
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KMeansIndex<Distance>* kmeans_index_;
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/** The kd-tree index */
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KDTreeIndex<Distance>* kdtree_index_;
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/** The index parameters */
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const IndexParams index_params_;
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};
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}
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#endif //OPENCV_FLANN_COMPOSITE_INDEX_H_
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