github.com/kaydxh/golang@v0.0.131/pkg/gocv/cgo/third_path/opencv4/include/opencv2/flann/all_indices.h (about) 1 /*********************************************************************** 2 * Software License Agreement (BSD License) 3 * 4 * Copyright 2008-2009 Marius Muja (mariusm@cs.ubc.ca). All rights reserved. 5 * Copyright 2008-2009 David G. Lowe (lowe@cs.ubc.ca). All rights reserved. 6 * 7 * Redistribution and use in source and binary forms, with or without 8 * modification, are permitted provided that the following conditions 9 * are met: 10 * 11 * 1. Redistributions of source code must retain the above copyright 12 * notice, this list of conditions and the following disclaimer. 13 * 2. Redistributions in binary form must reproduce the above copyright 14 * notice, this list of conditions and the following disclaimer in the 15 * documentation and/or other materials provided with the distribution. 16 * 17 * THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR 18 * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES 19 * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. 20 * IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, 21 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT 22 * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, 23 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY 24 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 25 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF 26 * THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 27 *************************************************************************/ 28 29 30 #ifndef OPENCV_FLANN_ALL_INDICES_H_ 31 #define OPENCV_FLANN_ALL_INDICES_H_ 32 33 //! @cond IGNORED 34 35 #include "general.h" 36 37 #include "nn_index.h" 38 #include "kdtree_index.h" 39 #include "kdtree_single_index.h" 40 #include "kmeans_index.h" 41 #include "composite_index.h" 42 #include "linear_index.h" 43 #include "hierarchical_clustering_index.h" 44 #include "lsh_index.h" 45 #include "autotuned_index.h" 46 47 48 namespace cvflann 49 { 50 51 template<typename KDTreeCapability, typename VectorSpace, typename Distance> 52 struct index_creator 53 { 54 static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) 55 { 56 flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm"); 57 58 NNIndex<Distance>* nnIndex; 59 switch (index_type) { 60 case FLANN_INDEX_LINEAR: 61 nnIndex = new LinearIndex<Distance>(dataset, params, distance); 62 break; 63 case FLANN_INDEX_KDTREE_SINGLE: 64 nnIndex = new KDTreeSingleIndex<Distance>(dataset, params, distance); 65 break; 66 case FLANN_INDEX_KDTREE: 67 nnIndex = new KDTreeIndex<Distance>(dataset, params, distance); 68 break; 69 case FLANN_INDEX_KMEANS: 70 nnIndex = new KMeansIndex<Distance>(dataset, params, distance); 71 break; 72 case FLANN_INDEX_COMPOSITE: 73 nnIndex = new CompositeIndex<Distance>(dataset, params, distance); 74 break; 75 case FLANN_INDEX_AUTOTUNED: 76 nnIndex = new AutotunedIndex<Distance>(dataset, params, distance); 77 break; 78 case FLANN_INDEX_HIERARCHICAL: 79 nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); 80 break; 81 case FLANN_INDEX_LSH: 82 nnIndex = new LshIndex<Distance>(dataset, params, distance); 83 break; 84 default: 85 FLANN_THROW(cv::Error::StsBadArg, "Unknown index type"); 86 } 87 88 return nnIndex; 89 } 90 }; 91 92 template<typename VectorSpace, typename Distance> 93 struct index_creator<False,VectorSpace,Distance> 94 { 95 static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) 96 { 97 flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm"); 98 99 NNIndex<Distance>* nnIndex; 100 switch (index_type) { 101 case FLANN_INDEX_LINEAR: 102 nnIndex = new LinearIndex<Distance>(dataset, params, distance); 103 break; 104 case FLANN_INDEX_KMEANS: 105 nnIndex = new KMeansIndex<Distance>(dataset, params, distance); 106 break; 107 case FLANN_INDEX_HIERARCHICAL: 108 nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); 109 break; 110 case FLANN_INDEX_LSH: 111 nnIndex = new LshIndex<Distance>(dataset, params, distance); 112 break; 113 default: 114 FLANN_THROW(cv::Error::StsBadArg, "Unknown index type"); 115 } 116 117 return nnIndex; 118 } 119 }; 120 121 template<typename Distance> 122 struct index_creator<False,False,Distance> 123 { 124 static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) 125 { 126 flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm"); 127 128 NNIndex<Distance>* nnIndex; 129 switch (index_type) { 130 case FLANN_INDEX_LINEAR: 131 nnIndex = new LinearIndex<Distance>(dataset, params, distance); 132 break; 133 case FLANN_INDEX_KMEANS: 134 nnIndex = new KMeansIndex<Distance>(dataset, params, distance); 135 break; 136 case FLANN_INDEX_HIERARCHICAL: 137 nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); 138 break; 139 case FLANN_INDEX_LSH: 140 nnIndex = new LshIndex<Distance>(dataset, params, distance); 141 break; 142 default: 143 FLANN_THROW(cv::Error::StsBadArg, "Unknown index type"); 144 } 145 146 return nnIndex; 147 } 148 }; 149 150 template<typename Distance> 151 NNIndex<Distance>* create_index_by_type(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) 152 { 153 return index_creator<typename Distance::is_kdtree_distance, 154 typename Distance::is_vector_space_distance, 155 Distance>::create(dataset, params,distance); 156 } 157 158 } 159 160 //! @endcond 161 162 #endif /* OPENCV_FLANN_ALL_INDICES_H_ */