Point Cloud Library (PCL)
1.14.1-dev
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search::FlannSearch is a generic FLANN wrapper class for the new search interface. More...
#include <pcl/search/flann_search.h>
Classes | |
class | FlannIndexCreator |
Helper class that creates a FLANN index from a given FLANN matrix. More... | |
class | KdTreeIndexCreator |
Creates a FLANN KdTreeSingleIndex from the given input data. More... | |
class | KdTreeMultiIndexCreator |
Creates a FLANN KdTreeIndex of multiple randomized trees from the given input data, suitable for feature matching. More... | |
class | KMeansIndexCreator |
Creates a FLANN KdTreeSingleIndex from the given input data. More... | |
Public Member Functions | |
FlannSearch (bool sorted=true, FlannIndexCreatorPtr creator=FlannIndexCreatorPtr(new KdTreeIndexCreator())) | |
~FlannSearch () override | |
Destructor for FlannSearch. More... | |
void | setEpsilon (double eps) |
Set the search epsilon precision (error bound) for nearest neighbors searches. More... | |
double | getEpsilon () |
Get the search epsilon precision (error bound) for nearest neighbors searches. More... | |
void | setChecks (int checks) |
Set the number of checks to perform during approximate searches in multiple randomized trees. More... | |
int | getChecks () |
Get the number of checks to perform during approximate searches in multiple randomized trees. More... | |
bool | setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr()) override |
Provide a pointer to the input dataset. More... | |
int | nearestKSearch (const PointT &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override |
Search for the k-nearest neighbors for the given query point. More... | |
void | nearestKSearch (const PointCloud &cloud, const Indices &indices, int k, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const override |
Search for the k-nearest neighbors for the given query point. More... | |
int | radiusSearch (const PointT &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override |
Search for all the nearest neighbors of the query point in a given radius. More... | |
void | radiusSearch (const PointCloud &cloud, const Indices &indices, double radius, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances, unsigned int max_nn=0) const override |
Search for the k-nearest neighbors for the given query point. More... | |
void | setPointRepresentation (const PointRepresentationConstPtr &point_representation) |
Provide a pointer to the point representation to use to convert points into k-D vectors. More... | |
PointRepresentationConstPtr const | getPointRepresentation () |
Get a pointer to the point representation used when converting points into k-D vectors. More... | |
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Search (const std::string &name="", bool sorted=false) | |
Constructor. More... | |
virtual | ~Search ()=default |
Destructor. More... | |
virtual const std::string & | getName () const |
Returns the search method name. More... | |
virtual void | setSortedResults (bool sorted) |
sets whether the results should be sorted (ascending in the distance) or not More... | |
virtual bool | getSortedResults () |
Gets whether the results should be sorted (ascending in the distance) or not Otherwise the results may be returned in any order. More... | |
virtual PointCloudConstPtr | getInputCloud () const |
Get a pointer to the input point cloud dataset. More... | |
virtual IndicesConstPtr | getIndices () const |
Get a pointer to the vector of indices used. More... | |
template<typename PointTDiff > | |
int | nearestKSearchT (const PointTDiff &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const |
Search for k-nearest neighbors for the given query point. More... | |
virtual int | nearestKSearch (const PointCloud &cloud, index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const |
Search for k-nearest neighbors for the given query point. More... | |
virtual int | nearestKSearch (index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const |
Search for k-nearest neighbors for the given query point (zero-copy). More... | |
template<typename PointTDiff > | |
void | nearestKSearchT (const pcl::PointCloud< PointTDiff > &cloud, const Indices &indices, int k, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const |
Search for the k-nearest neighbors for the given query point. More... | |
template<typename PointTDiff > | |
int | radiusSearchT (const PointTDiff &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const |
Search for all the nearest neighbors of the query point in a given radius. More... | |
virtual int | radiusSearch (const PointCloud &cloud, index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const |
Search for all the nearest neighbors of the query point in a given radius. More... | |
virtual int | radiusSearch (index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const |
Search for all the nearest neighbors of the query point in a given radius (zero-copy). More... | |
template<typename PointTDiff > | |
void | radiusSearchT (const pcl::PointCloud< PointTDiff > &cloud, const Indices &indices, double radius, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances, unsigned int max_nn=0) const |
Search for all the nearest neighbors of the query points in a given radius. More... | |
Protected Member Functions | |
void | convertInputToFlannMatrix () |
converts the input data to a format usable by FLANN More... | |
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void | sortResults (Indices &indices, std::vector< float > &distances) const |
Protected Attributes | |
IndexPtr | index_ |
The FLANN index. More... | |
FlannIndexCreatorPtr | creator_ |
The index creator, used to (re-) create the index when the search data is passed. More... | |
MatrixPtr | input_flann_ |
Input data in FLANN format. More... | |
float | eps_ {0.0f} |
Epsilon for approximate NN search. More... | |
int | checks_ {32} |
Number of checks to perform for approximate NN search using the multiple randomized tree index. More... | |
bool | input_copied_for_flann_ {false} |
PointRepresentationConstPtr | point_representation_ {nullptr} |
int | dim_ {0} |
Indices | index_mapping_ |
bool | identity_mapping_ {false} |
std::size_t | total_nr_points_ {0} |
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PointCloudConstPtr | input_ |
IndicesConstPtr | indices_ |
bool | sorted_results_ |
std::string | name_ |
search::FlannSearch is a generic FLANN wrapper class for the new search interface.
It is able to wrap any FLANN index type, e.g. the kd tree as well as indices for high-dimensional searches and intended as a more powerful and cleaner successor to KdTreeFlann.
By default, this class creates a single kd tree for indexing the input data. However, for high dimensions (> 10), it is often better to use the multiple randomized kd tree index provided by FLANN in combination with the flann::L2 distance functor. During search in this type of index, the number of checks to perform before terminating the search can be controlled. Here is a code example if a high-dimensional 2-NN search:
Definition at line 100 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::ConstPtr = shared_ptr<const FlannSearch<PointT, FlannDistance> > |
Definition at line 108 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::FlannIndexCreatorPtr = shared_ptr<FlannIndexCreator> |
Definition at line 141 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::Index = flann::NNIndex<FlannDistance> |
Definition at line 116 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::IndexPtr = shared_ptr<flann::NNIndex<FlannDistance> > |
Definition at line 117 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::MatrixConstPtr = shared_ptr<const flann::Matrix<float> > |
Definition at line 114 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::MatrixPtr = shared_ptr<flann::Matrix<float> > |
Definition at line 113 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::PointCloud = typename Search<PointT>::PointCloud |
Definition at line 110 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::PointCloudConstPtr = typename Search<PointT>::PointCloudConstPtr |
Definition at line 111 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::PointRepresentation = pcl::PointRepresentation<PointT> |
Definition at line 119 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::PointRepresentationConstPtr = typename PointRepresentation::ConstPtr |
Definition at line 121 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::PointRepresentationPtr = typename PointRepresentation::Ptr |
Definition at line 120 of file flann_search.h.
using pcl::search::FlannSearch< PointT, FlannDistance >::Ptr = shared_ptr<FlannSearch<PointT, FlannDistance> > |
Definition at line 107 of file flann_search.h.
pcl::search::FlannSearch< PointT, FlannDistance >::FlannSearch | ( | bool | sorted = true , |
FlannIndexCreatorPtr | creator = FlannIndexCreatorPtr (new KdTreeIndexCreator ()) |
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Definition at line 78 of file flann_search.hpp.
References pcl::search::FlannSearch< PointT, FlannDistance >::dim_, and pcl::search::FlannSearch< PointT, FlannDistance >::point_representation_.
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Destructor for FlannSearch.
Definition at line 86 of file flann_search.hpp.
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converts the input data to a format usable by FLANN
Definition at line 372 of file flann_search.hpp.
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Get the number of checks to perform during approximate searches in multiple randomized trees.
Definition at line 248 of file flann_search.h.
References pcl::search::FlannSearch< PointT, FlannDistance >::checks_.
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Get the search epsilon precision (error bound) for nearest neighbors searches.
Definition at line 232 of file flann_search.h.
References pcl::search::FlannSearch< PointT, FlannDistance >::eps_.
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Get a pointer to the point representation used when converting points into k-D vectors.
Definition at line 326 of file flann_search.h.
References pcl::search::FlannSearch< PointT, FlannDistance >::point_representation_.
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Search for the k-nearest neighbors for the given query point.
[in] | cloud | the point cloud data |
[in] | indices | a vector of point cloud indices to query for nearest neighbors |
[in] | k | the number of neighbors to search for |
[out] | k_indices | the resultant indices of the neighboring points, k_indices[i] corresponds to the neighbors of the query point i |
[out] | k_sqr_distances | the resultant squared distances to the neighboring points, k_sqr_distances[i] corresponds to the neighbors of the query point i |
Reimplemented from pcl::search::Search< PointT >.
Definition at line 150 of file flann_search.hpp.
References pcl::knn_search().
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Search for the k-nearest neighbors for the given query point.
[in] | point | the given query point |
[in] | k | the number of neighbors to search for |
[out] | k_indices | the resultant indices of the neighboring points (must be resized to k a priori!) |
[out] | k_sqr_distances | the resultant squared distances to the neighboring points (must be resized to k a priori!) |
Implements pcl::search::Search< PointT >.
Definition at line 106 of file flann_search.hpp.
References pcl::knn_search().
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Search for the k-nearest neighbors for the given query point.
[in] | cloud | the point cloud data |
[in] | indices | a vector of point cloud indices to query for nearest neighbors |
[in] | radius | the radius of the sphere bounding all of p_q's neighbors |
[out] | k_indices | the resultant indices of the neighboring points, k_indices[i] corresponds to the neighbors of the query point i |
[out] | k_sqr_distances | the resultant squared distances to the neighboring points, k_sqr_distances[i] corresponds to the neighbors of the query point i |
[in] | max_nn | if given, bounds the maximum returned neighbors to this value |
Reimplemented from pcl::search::Search< PointT >.
Definition at line 282 of file flann_search.hpp.
References pcl::radius_search().
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Search for all the nearest neighbors of the query point in a given radius.
[in] | point | the given query point |
[in] | radius | the radius of the sphere bounding all of p_q's neighbors |
[out] | k_indices | the resultant indices of the neighboring points |
[out] | k_sqr_distances | the resultant squared distances to the neighboring points |
[in] | max_nn | if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned. |
Implements pcl::search::Search< PointT >.
Definition at line 240 of file flann_search.hpp.
References pcl::radius_search().
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Set the number of checks to perform during approximate searches in multiple randomized trees.
[in] | checks | number of checks to perform during approximate searches in multiple randomized trees. |
Definition at line 241 of file flann_search.h.
References pcl::search::FlannSearch< PointT, FlannDistance >::checks_.
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Set the search epsilon precision (error bound) for nearest neighbors searches.
[in] | eps | precision (error bound) for nearest neighbors searches |
Definition at line 225 of file flann_search.h.
References pcl::search::FlannSearch< PointT, FlannDistance >::eps_.
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Provide a pointer to the input dataset.
[in] | cloud | the const boost shared pointer to a PointCloud message |
[in] | indices | the point indices subset that is to be used from cloud |
Reimplemented from pcl::search::Search< PointT >.
Definition at line 94 of file flann_search.hpp.
Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::setPointRepresentation().
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Provide a pointer to the point representation to use to convert points into k-D vectors.
[in] | point_representation | the const boost shared pointer to a PointRepresentation |
Definition at line 316 of file flann_search.h.
References pcl::search::FlannSearch< PointT, FlannDistance >::dim_, pcl::search::Search< PointT >::indices_, pcl::search::Search< PointT >::input_, pcl::search::FlannSearch< PointT, FlannDistance >::point_representation_, and pcl::search::FlannSearch< PointT, FlannDistance >::setInputCloud().
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Number of checks to perform for approximate NN search using the multiple randomized tree index.
Definition at line 355 of file flann_search.h.
Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::getChecks(), and pcl::search::FlannSearch< PointT, FlannDistance >::setChecks().
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The index creator, used to (re-) create the index when the search data is passed.
Definition at line 343 of file flann_search.h.
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Definition at line 361 of file flann_search.h.
Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::FlannSearch(), and pcl::search::FlannSearch< PointT, FlannDistance >::setPointRepresentation().
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Epsilon for approximate NN search.
Definition at line 351 of file flann_search.h.
Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::getEpsilon(), and pcl::search::FlannSearch< PointT, FlannDistance >::setEpsilon().
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Definition at line 364 of file flann_search.h.
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The FLANN index.
Definition at line 339 of file flann_search.h.
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Definition at line 363 of file flann_search.h.
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Definition at line 357 of file flann_search.h.
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Input data in FLANN format.
Definition at line 347 of file flann_search.h.
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Definition at line 366 of file flann_search.h.