rknn-toolkit2-v2.1.0-2024-08-08
/
rknpu2
/examples
/3rdparty
/opencv
/opencv-linux-aarch64
/include
/opencv2
/flann
/all_indices.h
/*********************************************************************** | |
* Software License Agreement (BSD License) | |
* | |
* Copyright 2008-2009 Marius Muja ([email protected]). All rights reserved. | |
* Copyright 2008-2009 David G. Lowe ([email protected]). All rights reserved. | |
* | |
* Redistribution and use in source and binary forms, with or without | |
* modification, are permitted provided that the following conditions | |
* are met: | |
* | |
* 1. Redistributions of source code must retain the above copyright | |
* notice, this list of conditions and the following disclaimer. | |
* 2. Redistributions 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. | |
* | |
* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``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 AUTHOR 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. | |
*************************************************************************/ | |
namespace cvflann | |
{ | |
template<typename KDTreeCapability, typename VectorSpace, typename Distance> | |
struct index_creator | |
{ | |
static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) | |
{ | |
flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm"); | |
NNIndex<Distance>* nnIndex; | |
switch (index_type) { | |
case FLANN_INDEX_LINEAR: | |
nnIndex = new LinearIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_KDTREE_SINGLE: | |
nnIndex = new KDTreeSingleIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_KDTREE: | |
nnIndex = new KDTreeIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_KMEANS: | |
nnIndex = new KMeansIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_COMPOSITE: | |
nnIndex = new CompositeIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_AUTOTUNED: | |
nnIndex = new AutotunedIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_HIERARCHICAL: | |
nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_LSH: | |
nnIndex = new LshIndex<Distance>(dataset, params, distance); | |
break; | |
default: | |
throw FLANNException("Unknown index type"); | |
} | |
return nnIndex; | |
} | |
}; | |
template<typename VectorSpace, typename Distance> | |
struct index_creator<False,VectorSpace,Distance> | |
{ | |
static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) | |
{ | |
flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm"); | |
NNIndex<Distance>* nnIndex; | |
switch (index_type) { | |
case FLANN_INDEX_LINEAR: | |
nnIndex = new LinearIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_KMEANS: | |
nnIndex = new KMeansIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_HIERARCHICAL: | |
nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_LSH: | |
nnIndex = new LshIndex<Distance>(dataset, params, distance); | |
break; | |
default: | |
throw FLANNException("Unknown index type"); | |
} | |
return nnIndex; | |
} | |
}; | |
template<typename Distance> | |
struct index_creator<False,False,Distance> | |
{ | |
static NNIndex<Distance>* create(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) | |
{ | |
flann_algorithm_t index_type = get_param<flann_algorithm_t>(params, "algorithm"); | |
NNIndex<Distance>* nnIndex; | |
switch (index_type) { | |
case FLANN_INDEX_LINEAR: | |
nnIndex = new LinearIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_HIERARCHICAL: | |
nnIndex = new HierarchicalClusteringIndex<Distance>(dataset, params, distance); | |
break; | |
case FLANN_INDEX_LSH: | |
nnIndex = new LshIndex<Distance>(dataset, params, distance); | |
break; | |
default: | |
throw FLANNException("Unknown index type"); | |
} | |
return nnIndex; | |
} | |
}; | |
template<typename Distance> | |
NNIndex<Distance>* create_index_by_type(const Matrix<typename Distance::ElementType>& dataset, const IndexParams& params, const Distance& distance) | |
{ | |
return index_creator<typename Distance::is_kdtree_distance, | |
typename Distance::is_vector_space_distance, | |
Distance>::create(dataset, params,distance); | |
} | |
} | |