flann.hpp

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#ifndef OPENCV_FLANN_HPP
#define OPENCV_FLANN_HPP
 
#include "opencv2/core.hpp"
#include "opencv2/flann/miniflann.hpp"
#include "opencv2/flann/flann_base.hpp"
 
namespace cvflann
{
    CV_EXPORTS flann_distance_t flann_distance_type();
    CV_DEPRECATED CV_EXPORTS void set_distance_type(flann_distance_t distance_type, int order);
}
 
 
namespace cv
{
namespace flann
{
 
 
 
template <typename T> struct CvType {};
template <> struct CvType<unsigned char> { static int type() { return CV_8U; } };
template <> struct CvType<char> { static int type() { return CV_8S; } };
template <> struct CvType<unsigned short> { static int type() { return CV_16U; } };
template <> struct CvType<short> { static int type() { return CV_16S; } };
template <> struct CvType<int> { static int type() { return CV_32S; } };
template <> struct CvType<float> { static int type() { return CV_32F; } };
template <> struct CvType<double> { static int type() { return CV_64F; } };
 
 
// bring the flann parameters into this namespace
using ::cvflann::get_param;
using ::cvflann::print_params;
 
// bring the flann distances into this namespace
using ::cvflann::L2_Simple;
using ::cvflann::L2;
using ::cvflann::L1;
using ::cvflann::MinkowskiDistance;
using ::cvflann::MaxDistance;
using ::cvflann::HammingLUT;
using ::cvflann::Hamming;
using ::cvflann::Hamming2;
using ::cvflann::DNAmmingLUT;
using ::cvflann::DNAmming2;
using ::cvflann::HistIntersectionDistance;
using ::cvflann::HellingerDistance;
using ::cvflann::ChiSquareDistance;
using ::cvflann::KL_Divergence;
 
 
template <typename Distance>
class GenericIndex
{
public:
        typedef typename Distance::ElementType ElementType;
        typedef typename Distance::ResultType DistanceType;
 
        GenericIndex(const Mat& features, const ::cvflann::IndexParams& params, Distance distance = Distance());
 
        ~GenericIndex();
 
        void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
                       std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
        void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
 
        int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
                         std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
        int radiusSearch(const Mat& query, Mat& indices, Mat& dists,
                         DistanceType radius, const ::cvflann::SearchParams& params);
 
        void save(String filename) { nnIndex->save(filename); }
 
        int veclen() const { return nnIndex->veclen(); }
 
        int size() const { return (int)nnIndex->size(); }
 
        ::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); }
 
        CV_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); }
 
private:
        ::cvflann::Index<Distance>* nnIndex;
        Mat _dataset;
};
 
 
#define FLANN_DISTANCE_CHECK \
    if ( ::cvflann::flann_distance_type() != cvflann::FLANN_DIST_L2) { \
        printf("[WARNING] You are using cv::flann::Index (or cv::flann::GenericIndex) and have also changed "\
        "the distance using cvflann::set_distance_type. This is no longer working as expected "\
        "(cv::flann::Index always uses L2). You should create the index templated on the distance, "\
        "for example for L1 distance use: GenericIndex< L1<float> > \n"); \
    }
 
 
template <typename Distance>
GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance)
: _dataset(dataset)
{
    CV_Assert(dataset.type() == CvType<ElementType>::type());
    CV_Assert(dataset.isContinuous());
    ::cvflann::Matrix<ElementType> m_dataset((ElementType*)_dataset.ptr<ElementType>(0), _dataset.rows, _dataset.cols);
 
    nnIndex = new ::cvflann::Index<Distance>(m_dataset, params, distance);
 
    FLANN_DISTANCE_CHECK
 
    nnIndex->buildIndex();
}
 
template <typename Distance>
GenericIndex<Distance>::~GenericIndex()
{
    delete nnIndex;
}
 
template <typename Distance>
void GenericIndex<Distance>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
    ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
    ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
    ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
 
    FLANN_DISTANCE_CHECK
 
    nnIndex->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
}
 
 
template <typename Distance>
void GenericIndex<Distance>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
{
    CV_Assert(queries.type() == CvType<ElementType>::type());
    CV_Assert(queries.isContinuous());
    ::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
 
    CV_Assert(indices.type() == CV_32S);
    CV_Assert(indices.isContinuous());
    ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
 
    CV_Assert(dists.type() == CvType<DistanceType>::type());
    CV_Assert(dists.isContinuous());
    ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
 
    FLANN_DISTANCE_CHECK
 
    nnIndex->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
}
 
template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
    ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
    ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
    ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
 
    FLANN_DISTANCE_CHECK
 
    return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
 
template <typename Distance>
int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
{
    CV_Assert(query.type() == CvType<ElementType>::type());
    CV_Assert(query.isContinuous());
    ::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
 
    CV_Assert(indices.type() == CV_32S);
    CV_Assert(indices.isContinuous());
    ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
 
    CV_Assert(dists.type() == CvType<DistanceType>::type());
    CV_Assert(dists.isContinuous());
    ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
 
    FLANN_DISTANCE_CHECK
 
    return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
}
 
template <typename T>
class Index_
{
public:
    typedef typename L2<T>::ElementType ElementType;
    typedef typename L2<T>::ResultType DistanceType;
 
    CV_DEPRECATED Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
    {
        printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
 
        CV_Assert(dataset.type() == CvType<ElementType>::type());
        CV_Assert(dataset.isContinuous());
        ::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
 
        if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
            nnIndex_L1 = NULL;
            nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
        }
        else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
            nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
            nnIndex_L2 = NULL;
        }
        else {
            printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
                   "For other distance types you must use cv::flann::GenericIndex<Distance>\n");
            CV_Assert(0);
        }
        if (nnIndex_L1) nnIndex_L1->buildIndex();
        if (nnIndex_L2) nnIndex_L2->buildIndex();
    }
    CV_DEPRECATED ~Index_()
    {
        if (nnIndex_L1) delete nnIndex_L1;
        if (nnIndex_L2) delete nnIndex_L2;
    }
 
    CV_DEPRECATED void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
    {
        ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
        ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
        ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
 
        if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
        if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
    }
    CV_DEPRECATED void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
    {
        CV_Assert(queries.type() == CvType<ElementType>::type());
        CV_Assert(queries.isContinuous());
        ::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
 
        CV_Assert(indices.type() == CV_32S);
        CV_Assert(indices.isContinuous());
        ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
 
        CV_Assert(dists.type() == CvType<DistanceType>::type());
        CV_Assert(dists.isContinuous());
        ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
 
        if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
        if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
    }
 
    CV_DEPRECATED int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
    {
        ::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
        ::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
        ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
 
        if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
        if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
    }
 
    CV_DEPRECATED int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
    {
        CV_Assert(query.type() == CvType<ElementType>::type());
        CV_Assert(query.isContinuous());
        ::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
 
        CV_Assert(indices.type() == CV_32S);
        CV_Assert(indices.isContinuous());
        ::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
 
        CV_Assert(dists.type() == CvType<DistanceType>::type());
        CV_Assert(dists.isContinuous());
        ::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
 
        if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
        if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
    }
 
    CV_DEPRECATED void save(String filename)
    {
        if (nnIndex_L1) nnIndex_L1->save(filename);
        if (nnIndex_L2) nnIndex_L2->save(filename);
    }
 
    CV_DEPRECATED int veclen() const
    {
        if (nnIndex_L1) return nnIndex_L1->veclen();
        if (nnIndex_L2) return nnIndex_L2->veclen();
    }
 
    CV_DEPRECATED int size() const
    {
        if (nnIndex_L1) return nnIndex_L1->size();
        if (nnIndex_L2) return nnIndex_L2->size();
    }
 
    CV_DEPRECATED ::cvflann::IndexParams getParameters()
    {
        if (nnIndex_L1) return nnIndex_L1->getParameters();
        if (nnIndex_L2) return nnIndex_L2->getParameters();
 
    }
 
    CV_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
    {
        if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
        if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
    }
 
private:
    // providing backwards compatibility for L2 and L1 distances (most common)
    ::cvflann::Index< L2<ElementType> >* nnIndex_L2;
    ::cvflann::Index< L1<ElementType> >* nnIndex_L1;
};
 
 
template <typename Distance>
int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params,
                           Distance d = Distance())
{
    typedef typename Distance::ElementType ElementType;
    typedef typename Distance::CentersType CentersType;
 
    CV_Assert(features.type() == CvType<ElementType>::type());
    CV_Assert(features.isContinuous());
    ::cvflann::Matrix<ElementType> m_features((ElementType*)features.ptr<ElementType>(0), features.rows, features.cols);
 
    CV_Assert(centers.type() == CvType<CentersType>::type());
    CV_Assert(centers.isContinuous());
    ::cvflann::Matrix<CentersType> m_centers((CentersType*)centers.ptr<CentersType>(0), centers.rows, centers.cols);
 
    return ::cvflann::hierarchicalClustering<Distance>(m_features, m_centers, params, d);
}
 
 
template <typename ELEM_TYPE, typename DIST_TYPE>
CV_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params)
{
    printf("[WARNING] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> is deprecated, use "
        "cv::flann::hierarchicalClustering<Distance> instead\n");
 
    if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
        return hierarchicalClustering< L2<ELEM_TYPE> >(features, centers, params);
    }
    else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
        return hierarchicalClustering< L1<ELEM_TYPE> >(features, centers, params);
    }
    else {
        printf("[ERROR] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> only provides backwards "
        "compatibility for the L1 and L2 distances. "
        "For other distance types you must use cv::flann::hierarchicalClustering<Distance>\n");
        CV_Assert(0);
    }
}
 
 
 
} } // namespace cv::flann
 
#endif