423 lines
17 KiB
C++
423 lines
17 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef _OPENCV_FLANN_HPP_
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#define _OPENCV_FLANN_HPP_
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#include "opencv2/core.hpp"
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#include "opencv2/flann/miniflann.hpp"
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#include "opencv2/flann/flann_base.hpp"
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namespace cvflann
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{
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CV_EXPORTS flann_distance_t flann_distance_type();
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FLANN_DEPRECATED CV_EXPORTS void set_distance_type(flann_distance_t distance_type, int order);
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}
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namespace cv
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{
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namespace flann
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{
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template <typename T> struct CvType {};
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template <> struct CvType<unsigned char> { static int type() { return CV_8U; } };
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template <> struct CvType<char> { static int type() { return CV_8S; } };
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template <> struct CvType<unsigned short> { static int type() { return CV_16U; } };
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template <> struct CvType<short> { static int type() { return CV_16S; } };
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template <> struct CvType<int> { static int type() { return CV_32S; } };
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template <> struct CvType<float> { static int type() { return CV_32F; } };
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template <> struct CvType<double> { static int type() { return CV_64F; } };
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// bring the flann parameters into this namespace
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using ::cvflann::get_param;
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using ::cvflann::print_params;
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// bring the flann distances into this namespace
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using ::cvflann::L2_Simple;
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using ::cvflann::L2;
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using ::cvflann::L1;
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using ::cvflann::MinkowskiDistance;
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using ::cvflann::MaxDistance;
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using ::cvflann::HammingLUT;
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using ::cvflann::Hamming;
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using ::cvflann::Hamming2;
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using ::cvflann::HistIntersectionDistance;
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using ::cvflann::HellingerDistance;
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using ::cvflann::ChiSquareDistance;
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using ::cvflann::KL_Divergence;
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template <typename Distance>
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class GenericIndex
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{
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public:
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typedef typename Distance::ElementType ElementType;
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typedef typename Distance::ResultType DistanceType;
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GenericIndex(const Mat& features, const ::cvflann::IndexParams& params, Distance distance = Distance());
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~GenericIndex();
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void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
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std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
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void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
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int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices,
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std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
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int radiusSearch(const Mat& query, Mat& indices, Mat& dists,
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DistanceType radius, const ::cvflann::SearchParams& params);
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void save(String filename) { nnIndex->save(filename); }
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int veclen() const { return nnIndex->veclen(); }
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int size() const { return nnIndex->size(); }
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::cvflann::IndexParams getParameters() { return nnIndex->getParameters(); }
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FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters() { return nnIndex->getIndexParameters(); }
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private:
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::cvflann::Index<Distance>* nnIndex;
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};
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#define FLANN_DISTANCE_CHECK \
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if ( ::cvflann::flann_distance_type() != cvflann::FLANN_DIST_L2) { \
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printf("[WARNING] You are using cv::flann::Index (or cv::flann::GenericIndex) and have also changed "\
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"the distance using cvflann::set_distance_type. This is no longer working as expected "\
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"(cv::flann::Index always uses L2). You should create the index templated on the distance, "\
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"for example for L1 distance use: GenericIndex< L1<float> > \n"); \
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}
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template <typename Distance>
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GenericIndex<Distance>::GenericIndex(const Mat& dataset, const ::cvflann::IndexParams& params, Distance distance)
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{
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CV_Assert(dataset.type() == CvType<ElementType>::type());
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CV_Assert(dataset.isContinuous());
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::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
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nnIndex = new ::cvflann::Index<Distance>(m_dataset, params, distance);
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FLANN_DISTANCE_CHECK
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nnIndex->buildIndex();
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}
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template <typename Distance>
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GenericIndex<Distance>::~GenericIndex()
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{
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delete nnIndex;
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}
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template <typename Distance>
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void GenericIndex<Distance>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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FLANN_DISTANCE_CHECK
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nnIndex->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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}
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template <typename Distance>
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void GenericIndex<Distance>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(queries.type() == CvType<ElementType>::type());
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CV_Assert(queries.isContinuous());
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::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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FLANN_DISTANCE_CHECK
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nnIndex->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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}
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template <typename Distance>
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int GenericIndex<Distance>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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FLANN_DISTANCE_CHECK
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return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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template <typename Distance>
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int GenericIndex<Distance>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(query.type() == CvType<ElementType>::type());
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CV_Assert(query.isContinuous());
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::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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FLANN_DISTANCE_CHECK
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return nnIndex->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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/**
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* @deprecated Use GenericIndex class instead
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*/
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template <typename T>
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class
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#ifndef _MSC_VER
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FLANN_DEPRECATED
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#endif
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Index_ {
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public:
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typedef typename L2<T>::ElementType ElementType;
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typedef typename L2<T>::ResultType DistanceType;
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Index_(const Mat& features, const ::cvflann::IndexParams& params);
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~Index_();
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void knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
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void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
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int radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
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int radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& params);
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void save(String filename)
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{
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if (nnIndex_L1) nnIndex_L1->save(filename);
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if (nnIndex_L2) nnIndex_L2->save(filename);
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}
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int veclen() const
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{
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if (nnIndex_L1) return nnIndex_L1->veclen();
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if (nnIndex_L2) return nnIndex_L2->veclen();
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}
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int size() const
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{
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if (nnIndex_L1) return nnIndex_L1->size();
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if (nnIndex_L2) return nnIndex_L2->size();
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}
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::cvflann::IndexParams getParameters()
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{
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if (nnIndex_L1) return nnIndex_L1->getParameters();
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if (nnIndex_L2) return nnIndex_L2->getParameters();
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}
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FLANN_DEPRECATED const ::cvflann::IndexParams* getIndexParameters()
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{
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if (nnIndex_L1) return nnIndex_L1->getIndexParameters();
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if (nnIndex_L2) return nnIndex_L2->getIndexParameters();
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}
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private:
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// providing backwards compatibility for L2 and L1 distances (most common)
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::cvflann::Index< L2<ElementType> >* nnIndex_L2;
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::cvflann::Index< L1<ElementType> >* nnIndex_L1;
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};
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#ifdef _MSC_VER
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template <typename T>
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class FLANN_DEPRECATED Index_;
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#endif
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template <typename T>
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Index_<T>::Index_(const Mat& dataset, const ::cvflann::IndexParams& params)
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{
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printf("[WARNING] The cv::flann::Index_<T> class is deperecated, use cv::flann::GenericIndex<Distance> instead\n");
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CV_Assert(dataset.type() == CvType<ElementType>::type());
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CV_Assert(dataset.isContinuous());
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::cvflann::Matrix<ElementType> m_dataset((ElementType*)dataset.ptr<ElementType>(0), dataset.rows, dataset.cols);
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if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
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nnIndex_L1 = NULL;
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nnIndex_L2 = new ::cvflann::Index< L2<ElementType> >(m_dataset, params);
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}
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else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
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nnIndex_L1 = new ::cvflann::Index< L1<ElementType> >(m_dataset, params);
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nnIndex_L2 = NULL;
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}
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else {
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printf("[ERROR] cv::flann::Index_<T> only provides backwards compatibility for the L1 and L2 distances. "
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"For other distance types you must use cv::flann::GenericIndex<Distance>\n");
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CV_Assert(0);
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}
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if (nnIndex_L1) nnIndex_L1->buildIndex();
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if (nnIndex_L2) nnIndex_L2->buildIndex();
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}
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template <typename T>
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Index_<T>::~Index_()
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{
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if (nnIndex_L1) delete nnIndex_L1;
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if (nnIndex_L2) delete nnIndex_L2;
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}
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template <typename T>
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void Index_<T>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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if (nnIndex_L1) nnIndex_L1->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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if (nnIndex_L2) nnIndex_L2->knnSearch(m_query,m_indices,m_dists,knn,searchParams);
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}
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template <typename T>
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void Index_<T>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(queries.type() == CvType<ElementType>::type());
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CV_Assert(queries.isContinuous());
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::cvflann::Matrix<ElementType> m_queries((ElementType*)queries.ptr<ElementType>(0), queries.rows, queries.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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if (nnIndex_L1) nnIndex_L1->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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if (nnIndex_L2) nnIndex_L2->knnSearch(m_queries,m_indices,m_dists,knn, searchParams);
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}
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template <typename T>
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int Index_<T>::radiusSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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::cvflann::Matrix<ElementType> m_query((ElementType*)&query[0], 1, query.size());
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::cvflann::Matrix<int> m_indices(&indices[0], 1, indices.size());
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::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
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if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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template <typename T>
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int Index_<T>::radiusSearch(const Mat& query, Mat& indices, Mat& dists, DistanceType radius, const ::cvflann::SearchParams& searchParams)
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{
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CV_Assert(query.type() == CvType<ElementType>::type());
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CV_Assert(query.isContinuous());
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::cvflann::Matrix<ElementType> m_query((ElementType*)query.ptr<ElementType>(0), query.rows, query.cols);
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CV_Assert(indices.type() == CV_32S);
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CV_Assert(indices.isContinuous());
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::cvflann::Matrix<int> m_indices((int*)indices.ptr<int>(0), indices.rows, indices.cols);
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CV_Assert(dists.type() == CvType<DistanceType>::type());
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CV_Assert(dists.isContinuous());
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::cvflann::Matrix<DistanceType> m_dists((DistanceType*)dists.ptr<DistanceType>(0), dists.rows, dists.cols);
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if (nnIndex_L1) return nnIndex_L1->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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if (nnIndex_L2) return nnIndex_L2->radiusSearch(m_query,m_indices,m_dists,radius,searchParams);
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}
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template <typename Distance>
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int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params,
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Distance d = Distance())
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{
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typedef typename Distance::ElementType ElementType;
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typedef typename Distance::ResultType DistanceType;
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CV_Assert(features.type() == CvType<ElementType>::type());
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CV_Assert(features.isContinuous());
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::cvflann::Matrix<ElementType> m_features((ElementType*)features.ptr<ElementType>(0), features.rows, features.cols);
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CV_Assert(centers.type() == CvType<DistanceType>::type());
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CV_Assert(centers.isContinuous());
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::cvflann::Matrix<DistanceType> m_centers((DistanceType*)centers.ptr<DistanceType>(0), centers.rows, centers.cols);
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return ::cvflann::hierarchicalClustering<Distance>(m_features, m_centers, params, d);
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}
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template <typename ELEM_TYPE, typename DIST_TYPE>
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FLANN_DEPRECATED int hierarchicalClustering(const Mat& features, Mat& centers, const ::cvflann::KMeansIndexParams& params)
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{
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printf("[WARNING] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> is deprecated, use "
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"cv::flann::hierarchicalClustering<Distance> instead\n");
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if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L2 ) {
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return hierarchicalClustering< L2<ELEM_TYPE> >(features, centers, params);
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}
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else if ( ::cvflann::flann_distance_type() == cvflann::FLANN_DIST_L1 ) {
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return hierarchicalClustering< L1<ELEM_TYPE> >(features, centers, params);
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}
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else {
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printf("[ERROR] cv::flann::hierarchicalClustering<ELEM_TYPE,DIST_TYPE> only provides backwards "
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"compatibility for the L1 and L2 distances. "
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"For other distance types you must use cv::flann::hierarchicalClustering<Distance>\n");
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CV_Assert(0);
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}
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}
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} } // namespace cv::flann
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#endif
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