flann.hpp

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 *
 * 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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#ifndef FLANN_HPP_
#define FLANN_HPP_
 
 
#include <vector>
#include <string>
#include <cassert>
#include <cstdio>
 
#include "FLANN/general.h"
#include "FLANN/util/matrix.h"
#include "FLANN/util/params.h"
#include "FLANN/util/saving.h"
 
#include "FLANN/algorithms/all_indices.h"
 
namespace flann
{
 
inline void log_verbosity(int level)
{
    if (level >= 0) {
        Logger::setLevel(level);
    }
}
 
struct SavedIndexParams : public IndexParams
{
    SavedIndexParams(std::string filename)
    {
        (*this)["algorithm"] = FLANN_INDEX_SAVED;
        (*this)["filename"] = filename;
    }
};
 
 
 
template<typename Distance>
class Index
{
public:
    typedef typename Distance::ElementType ElementType;
    typedef typename Distance::ResultType DistanceType;
    typedef NNIndex<Distance> IndexType;
 
    Index(const IndexParams& params, Distance distance = Distance() )
        : index_params_(params)
    {
        flann_algorithm_t index_type = get_param<flann_algorithm_t>(params,"algorithm");
        loaded_ = false;
 
        Matrix<ElementType> features;
        if (index_type == FLANN_INDEX_SAVED) {
            nnIndex_ = load_saved_index(features, get_param<std::string>(params,"filename"), distance);
            loaded_ = true;
        }
        else {
            flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm");
            nnIndex_ = create_index_by_type<Distance>(index_type, features, params, distance);
        }
    }
 
 
    Index(const Matrix<ElementType>& features, const IndexParams& params, Distance distance = Distance() )
        : index_params_(params)
    {
        flann_algorithm_t index_type = get_param<flann_algorithm_t>(params,"algorithm");
        loaded_ = false;
 
        if (index_type == FLANN_INDEX_SAVED) {
            nnIndex_ = load_saved_index(features, get_param<std::string>(params,"filename"), distance);
            loaded_ = true;
        }
        else {
            flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm");
            nnIndex_ = create_index_by_type<Distance>(index_type, features, params, distance);
        }
    }
 
 
    Index(const Index& other) : loaded_(other.loaded_), index_params_(other.index_params_)
    {
        nnIndex_ = other.nnIndex_->clone();
    }
 
    Index& operator=(Index other)
    {
        this->swap(other);
        return *this;
    }
 
    virtual ~Index()
    {
        delete nnIndex_;
    }
 
    void buildIndex()
    {
        if (!loaded_) {
            nnIndex_->buildIndex();
        }
    }
 
    void buildIndex(const Matrix<ElementType>& points)
    {
        nnIndex_->buildIndex(points);
    }
 
    void addPoints(const Matrix<ElementType>& points, float rebuild_threshold = 2)
    {
        nnIndex_->addPoints(points, rebuild_threshold);
    }
 
    void removePoint(size_t point_id)
    {
        nnIndex_->removePoint(point_id);
    }
 
    ElementType* getPoint(size_t point_id)
    {
        return nnIndex_->getPoint(point_id);
    }
 
    void save(std::string filename)
    {
        FILE* fout = fopen(filename.c_str(), "wb");
        if (fout == NULL) {
            throw FLANNException("Cannot open file");
        }
        nnIndex_->saveIndex(fout);
        fclose(fout);
    }
 
    size_t veclen() const
    {
        return nnIndex_->veclen();
    }
 
    size_t size() const
    {
        return nnIndex_->size();
    }
 
    flann_algorithm_t getType() const
    {
        return nnIndex_->getType();
    }
 
    int usedMemory() const
    {
        return nnIndex_->usedMemory();
    }
 
 
    IndexParams getParameters() const
    {
        return nnIndex_->getParameters();
    }
 
    int knnSearch(const Matrix<ElementType>& queries,
                                 Matrix<size_t>& indices,
                                 Matrix<DistanceType>& dists,
                                 size_t knn,
                           const SearchParams& params) const
    {
        return nnIndex_->knnSearch(queries, indices, dists, knn, params);
    }
 
    int knnSearch(const Matrix<ElementType>& queries,
                                 Matrix<int>& indices,
                                 Matrix<DistanceType>& dists,
                                 size_t knn,
                           const SearchParams& params) const
    {
        return nnIndex_->knnSearch(queries, indices, dists, knn, params);
    }
 
    int knnSearch(const Matrix<ElementType>& queries,
                                 std::vector< std::vector<size_t> >& indices,
                                 std::vector<std::vector<DistanceType> >& dists,
                                 size_t knn,
                           const SearchParams& params) const
    {
        return nnIndex_->knnSearch(queries, indices, dists, knn, params);
    }
 
    int knnSearch(const Matrix<ElementType>& queries,
                                 std::vector< std::vector<int> >& indices,
                                 std::vector<std::vector<DistanceType> >& dists,
                                 size_t knn,
                           const SearchParams& params) const
    {
        return nnIndex_->knnSearch(queries, indices, dists, knn, params);
    }
 
    int radiusSearch(const Matrix<ElementType>& queries,
                                    Matrix<size_t>& indices,
                                    Matrix<DistanceType>& dists,
                                    float radius,
                              const SearchParams& params) const
    {
        return nnIndex_->radiusSearch(queries, indices, dists, radius, params);
    }
 
    int radiusSearch(const Matrix<ElementType>& queries,
                                    Matrix<int>& indices,
                                    Matrix<DistanceType>& dists,
                                    float radius,
                              const SearchParams& params) const
    {
        return nnIndex_->radiusSearch(queries, indices, dists, radius, params);
    }
 
    int radiusSearch(const Matrix<ElementType>& queries,
                                    std::vector< std::vector<size_t> >& indices,
                                    std::vector<std::vector<DistanceType> >& dists,
                                    float radius,
                              const SearchParams& params) const
    {
        return nnIndex_->radiusSearch(queries, indices, dists, radius, params);
    }
 
    int radiusSearch(const Matrix<ElementType>& queries,
                                    std::vector< std::vector<int> >& indices,
                                    std::vector<std::vector<DistanceType> >& dists,
                                    float radius,
                              const SearchParams& params) const
    {
        return nnIndex_->radiusSearch(queries, indices, dists, radius, params);
    }
 
private:
    IndexType* load_saved_index(const Matrix<ElementType>& dataset, const std::string& filename, Distance distance)
    {
        FILE* fin = fopen(filename.c_str(), "rb");
        if (fin == NULL) {
            return NULL;
        }
        IndexHeader header = load_header(fin);
        if (header.h.data_type != flann_datatype_value<ElementType>::value) {
            throw FLANNException("Datatype of saved index is different than of the one to be loaded.");
        }
 
        IndexParams params;
        params["algorithm"] = header.h.index_type;
        IndexType* nnIndex = create_index_by_type<Distance>(header.h.index_type, dataset, params, distance);
        rewind(fin);
        nnIndex->loadIndex(fin);
        fclose(fin);
 
        return nnIndex;
    }
 
    void swap( Index& other)
    {
        std::swap(nnIndex_, other.nnIndex_);
        std::swap(loaded_, other.loaded_);
        std::swap(index_params_, other.index_params_);
    }
 
private:
    IndexType* nnIndex_;
    bool loaded_;
    IndexParams index_params_;
};
 
 
 
 
 
template <typename Distance>
int hierarchicalClustering(const Matrix<typename Distance::ElementType>& points, Matrix<typename Distance::ResultType>& centers,
                           const KMeansIndexParams& params, Distance d = Distance())
{
    KMeansIndex<Distance> kmeans(points, params, d);
    kmeans.buildIndex();
 
    int clusterNum = kmeans.getClusterCenters(centers);
    return clusterNum;
}
 
}
#endif /* FLANN_HPP_ */