opencv/modules/flann/include/opencv2/flann/composite_index.h

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C++

/***********************************************************************
* Software License Agreement (BSD License)
*
* Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
* Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
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* THE BSD LICENSE
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#ifndef _OPENCV_COMPOSITETREE_H_
#define _OPENCV_COMPOSITETREE_H_
#include "opencv2/flann/general.h"
#include "opencv2/flann/nn_index.h"
namespace cvflann
{
struct CompositeIndexParams : public IndexParams {
CompositeIndexParams(int trees_ = 4, int branching_ = 32, int iterations_ = 11,
flann_centers_init_t centers_init_ = FLANN_CENTERS_RANDOM, float cb_index_ = 0.2 ) :
IndexParams(FLANN_INDEX_COMPOSITE),
trees(trees_),
branching(branching_),
iterations(iterations_),
centers_init(centers_init_),
cb_index(cb_index_) {};
int trees; // number of randomized trees to use (for kdtree)
int branching; // branching factor (for kmeans tree)
int iterations; // max iterations to perform in one kmeans clustering (kmeans tree)
flann_centers_init_t centers_init; // algorithm used for picking the initial cluster centers for kmeans tree
float cb_index; // cluster boundary index. Used when searching the kmeans tree
void print() const
{
logger().info("Index type: %d\n",(int)algorithm);
logger().info("Trees: %d\n", trees);
logger().info("Branching: %d\n", branching);
logger().info("Iterations: %d\n", iterations);
logger().info("Centres initialisation: %d\n", centers_init);
logger().info("Cluster boundary weight: %g\n", cb_index);
}
};
template <typename ELEM_TYPE, typename DIST_TYPE = typename DistType<ELEM_TYPE>::type >
class CompositeIndex : public NNIndex<ELEM_TYPE>
{
KMeansIndex<ELEM_TYPE, DIST_TYPE>* kmeans;
KDTreeIndex<ELEM_TYPE, DIST_TYPE>* kdtree;
const Matrix<ELEM_TYPE> dataset;
const IndexParams& index_params;
CompositeIndex& operator=(const CompositeIndex&);
CompositeIndex(const CompositeIndex&);
public:
CompositeIndex(const Matrix<ELEM_TYPE>& inputData, const CompositeIndexParams& params = CompositeIndexParams() ) :
dataset(inputData), index_params(params)
{
KDTreeIndexParams kdtree_params(params.trees);
KMeansIndexParams kmeans_params(params.branching, params.iterations, params.centers_init, params.cb_index);
kdtree = new KDTreeIndex<ELEM_TYPE, DIST_TYPE>(inputData,kdtree_params);
kmeans = new KMeansIndex<ELEM_TYPE, DIST_TYPE>(inputData,kmeans_params);
}
virtual ~CompositeIndex()
{
delete kdtree;
delete kmeans;
}
flann_algorithm_t getType() const
{
return FLANN_INDEX_COMPOSITE;
}
size_t size() const
{
return dataset.rows;
}
size_t veclen() const
{
return dataset.cols;
}
int usedMemory() const
{
return kmeans->usedMemory()+kdtree->usedMemory();
}
void buildIndex()
{
logger().info("Building kmeans tree...\n");
kmeans->buildIndex();
logger().info("Building kdtree tree...\n");
kdtree->buildIndex();
}
void saveIndex(FILE* stream)
{
kmeans->saveIndex(stream);
kdtree->saveIndex(stream);
}
void loadIndex(FILE* stream)
{
kmeans->loadIndex(stream);
kdtree->loadIndex(stream);
}
void findNeighbors(ResultSet<ELEM_TYPE>& result, const ELEM_TYPE* vec, const SearchParams& searchParams)
{
kmeans->findNeighbors(result,vec,searchParams);
kdtree->findNeighbors(result,vec,searchParams);
}
const IndexParams* getParameters() const
{
return &index_params;
}
};
} // namespace cvflann
#endif //_OPENCV_COMPOSITETREE_H_