composite_index.h

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 * Copyright 2008-2009  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
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#ifndef OPENCV_FLANN_COMPOSITE_INDEX_H_
#define OPENCV_FLANN_COMPOSITE_INDEX_H_
 
 
#include "nn_index.h"
#include "kdtree_index.h"
#include "kmeans_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 )
    {
        (*this)["algorithm"] = FLANN_INDEX_KMEANS;
        // number of randomized trees to use (for kdtree)
        (*this)["trees"] = trees;
        // branching factor
        (*this)["branching"] = branching;
        // max iterations to perform in one kmeans clustering (kmeans tree)
        (*this)["iterations"] = iterations;
        // algorithm used for picking the initial cluster centers for kmeans tree
        (*this)["centers_init"] = centers_init;
        // cluster boundary index. Used when searching the kmeans tree
        (*this)["cb_index"] = cb_index;
    }
};
 
 
template <typename Distance>
class CompositeIndex : public NNIndex<Distance>
{
public:
    typedef typename Distance::ElementType ElementType;
    typedef typename Distance::ResultType DistanceType;
 
    CompositeIndex(const Matrix<ElementType>& inputData, const IndexParams& params = CompositeIndexParams(),
                   Distance d = Distance()) : index_params_(params)
    {
        kdtree_index_ = new KDTreeIndex<Distance>(inputData, params, d);
        kmeans_index_ = new KMeansIndex<Distance>(inputData, params, d);
 
    }
 
    CompositeIndex(const CompositeIndex&);
    CompositeIndex& operator=(const CompositeIndex&);
 
    virtual ~CompositeIndex()
    {
        delete kdtree_index_;
        delete kmeans_index_;
    }
 
    flann_algorithm_t getType() const CV_OVERRIDE
    {
        return FLANN_INDEX_COMPOSITE;
    }
 
    size_t size() const CV_OVERRIDE
    {
        return kdtree_index_->size();
    }
 
    size_t veclen() const CV_OVERRIDE
    {
        return kdtree_index_->veclen();
    }
 
    int usedMemory() const CV_OVERRIDE
    {
        return kmeans_index_->usedMemory() + kdtree_index_->usedMemory();
    }
 
    void buildIndex() CV_OVERRIDE
    {
        Logger::info("Building kmeans tree...\n");
        kmeans_index_->buildIndex();
        Logger::info("Building kdtree tree...\n");
        kdtree_index_->buildIndex();
    }
 
    void saveIndex(FILE* stream) CV_OVERRIDE
    {
        kmeans_index_->saveIndex(stream);
        kdtree_index_->saveIndex(stream);
    }
 
    void loadIndex(FILE* stream) CV_OVERRIDE
    {
        kmeans_index_->loadIndex(stream);
        kdtree_index_->loadIndex(stream);
    }
 
    IndexParams getParameters() const CV_OVERRIDE
    {
        return index_params_;
    }
 
    void findNeighbors(ResultSet<DistanceType>& result, const ElementType* vec, const SearchParams& searchParams) CV_OVERRIDE
    {
        kmeans_index_->findNeighbors(result, vec, searchParams);
        kdtree_index_->findNeighbors(result, vec, searchParams);
    }
 
private:
    KMeansIndex<Distance>* kmeans_index_;
 
    KDTreeIndex<Distance>* kdtree_index_;
 
    const IndexParams index_params_;
};
 
}
 
 
#endif //OPENCV_FLANN_COMPOSITE_INDEX_H_