/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #ifndef _OPENCV_FLANN_HPP_ #define _OPENCV_FLANN_HPP_ #ifdef __cplusplus #include "opencv2/core/types_c.h" #include "opencv2/core/core.hpp" #include "opencv2/flann/flann_base.hpp" #include "opencv2/flann/miniflann.hpp" namespace cvflann { CV_EXPORTS flann_distance_t flann_distance_type(); FLANN_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::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 vector<ElementType>& query, vector<int>& indices, 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 vector<ElementType>& query, vector<int>& indices, 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(std::string filename) { nnIndex->save(filename); } int veclen() const { return nnIndex->veclen(); } int size() const { return nnIndex->size(); } ::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); } FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); } private: ::cvflann::Index<Distance>* nnIndex; }; #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) { 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 vector<ElementType>& query, vector<int>& indices, 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 vector<ElementType>& query, vector<int>& indices, 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); } /** * @deprecated Use GenericIndex class instead */ template <typename T> class Index_ { public: typedef typename L2<T>::ElementType ElementType; typedef typename L2<T>::ResultType DistanceType; FLANN_DEPRECATED Index_(const Mat& features, const ::cvflann::IndexParams& params); FLANN_DEPRECATED ~Index_(); FLANN_DEPRECATED void knnSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params); FLANN_DEPRECATED void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params); FLANN_DEPRECATED int radiusSearch(const vector<ElementType>& query, vector<int>& indices, vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params); FLANN_DEPRECATED int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params); FLANN_DEPRECATED void save(std::string filename) { if (nnIndex_L1) nnIndex_L1->save(filename); if (nnIndex_L2) nnIndex_L2->save(filename); } FLANN_DEPRECATED int veclen() const { if (nnIndex_L1) return nnIndex_L1->veclen(); if (nnIndex_L2) return nnIndex_L2->veclen(); } FLANN_DEPRECATED int size() const { if (nnIndex_L1) return nnIndex_L1->size(); if (nnIndex_L2) return nnIndex_L2->size(); } FLANN_DEPRECATED ::cvflann::IndexParams getParameters() { if (nnIndex_L1) return nnIndex_L1->getParameters(); if (nnIndex_L2) return nnIndex_L2->getParameters(); } FLANN_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 T> Index_<T>::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(); } template <typename T> Index_<T>::~Index_() { if (nnIndex_L1) delete nnIndex_L1; if (nnIndex_L2) delete nnIndex_L2; } template <typename T> void Index_<T>::knnSearch(const vector<ElementType>& query, vector<int>& indices, 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); } template <typename T> void Index_<T>::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); } template <typename T> int Index_<T>::radiusSearch(const vector<ElementType>& query, vector<int>& indices, 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); } template <typename T> int Index_<T>::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); } 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::ResultType DistanceType; 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<DistanceType>::type()); CV_Assert(centers.isContinuous()); ::cvflann::Matrix<DistanceType> m_centers((DistanceType*)centers.ptr<DistanceType>(0), centers.rows, centers.cols); return ::cvflann::hierarchicalClustering<Distance>(m_features, m_centers, params, d); } template <typename ELEM_TYPE, typename DIST_TYPE> FLANN_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 // __cplusplus #endif