Point Cloud Library (PCL) 1.14.0
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octree.h
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38
39#pragma once
40
41#include <pcl/search/search.h>
42#include <pcl/octree/octree_search.h>
43
44namespace pcl
45{
46 namespace search
47 {
48 /** \brief @b search::Octree is a wrapper class which implements nearest neighbor search operations based on the
49 * pcl::octree::Octree structure.
50 *
51 * The octree pointcloud class needs to be initialized with its voxel
52 * resolution. Its bounding box is automatically adjusted according to the
53 * pointcloud dimension or it can be predefined. Note: The tree depth
54 * equates to the resolution and the bounding box dimensions of the
55 * octree.
56 *
57 * \note typename: PointT: type of point used in pointcloud
58 * \note typename: LeafT: leaf node class (usuallt templated with integer indices values)
59 * \note typename: OctreeT: octree implementation ()
60 *
61 * \author Julius Kammerl
62 * \ingroup search
63 */
64 template<typename PointT,
66 typename BranchTWrap = pcl::octree::OctreeContainerEmpty,
68 class Octree: public Search<PointT>
69 {
70 public:
71 // public typedefs
72 using Ptr = shared_ptr<pcl::search::Octree<PointT,LeafTWrap,BranchTWrap,OctreeT> >;
73 using ConstPtr = shared_ptr<const pcl::search::Octree<PointT,LeafTWrap,BranchTWrap,OctreeT> >;
74
78
79 // Boost shared pointers
83
87
88 /** \brief Octree constructor.
89 * \param[in] resolution octree resolution at lowest octree level
90 */
91 Octree (const double resolution)
92 : Search<PointT> ("Octree")
93 , tree_ (new pcl::octree::OctreePointCloudSearch<PointT, LeafTWrap, BranchTWrap> (resolution))
94 {
95 }
96
97 /** \brief Empty Destructor. */
98
99 ~Octree () override = default;
100
101 /** \brief Provide a pointer to the input dataset.
102 * \param[in] cloud the const boost shared pointer to a PointCloud message
103 */
104 inline void
106 {
107 tree_->deleteTree ();
108 tree_->setInputCloud (cloud);
109 tree_->addPointsFromInputCloud ();
110 input_ = cloud;
111 }
112
113 /** \brief Provide a pointer to the input dataset.
114 * \param[in] cloud the const boost shared pointer to a PointCloud message
115 * \param[in] indices the point indices subset that is to be used from \a cloud
116 */
117 inline bool
118 setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr& indices) override
119 {
120 tree_->deleteTree ();
121 tree_->setInputCloud (cloud, indices);
122 tree_->addPointsFromInputCloud ();
123 input_ = cloud;
124 indices_ = indices;
125 return true;
126 }
127
128 /** \brief Search for the k-nearest neighbors for the given query point.
129 * \param[in] cloud the point cloud data
130 * \param[in] index the index in \a cloud representing the query point
131 * \param[in] k the number of neighbors to search for
132 * \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
133 * \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
134 * a priori!)
135 * \return number of neighbors found
136 */
137 inline int
138 nearestKSearch (const PointCloud &cloud, index_t index, int k, Indices &k_indices,
139 std::vector<float> &k_sqr_distances) const override
140 {
141 return (tree_->nearestKSearch (cloud, index, k, k_indices, k_sqr_distances));
142 }
143
144 /** \brief Search for the k-nearest neighbors for the given query point.
145 * \param[in] point the given query point
146 * \param[in] k the number of neighbors to search for
147 * \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
148 * \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
149 * a priori!)
150 * \return number of neighbors found
151 */
152 inline int
153 nearestKSearch (const PointT &point, int k, Indices &k_indices,
154 std::vector<float> &k_sqr_distances) const override
155 {
156 return (tree_->nearestKSearch (point, k, k_indices, k_sqr_distances));
157 }
158
159 /** \brief Search for the k-nearest neighbors for the given query point (zero-copy).
160 *
161 * \param[in] index the index representing the query point in the
162 * dataset given by \a setInputCloud if indices were given in
163 * setInputCloud, index will be the position in the indices vector
164 * \param[in] k the number of neighbors to search for
165 * \param[out] k_indices the resultant indices of the neighboring points (must be resized to \a k a priori!)
166 * \param[out] k_sqr_distances the resultant squared distances to the neighboring points (must be resized to \a k
167 * a priori!)
168 * \return number of neighbors found
169 */
170 inline int
171 nearestKSearch (index_t index, int k, Indices &k_indices, std::vector<float> &k_sqr_distances) const override
172 {
173 return (tree_->nearestKSearch (index, k, k_indices, k_sqr_distances));
174 }
175
176 /** \brief search for all neighbors of query point that are within a given radius.
177 * \param cloud the point cloud data
178 * \param index the index in \a cloud representing the query point
179 * \param radius the radius of the sphere bounding all of p_q's neighbors
180 * \param k_indices the resultant indices of the neighboring points
181 * \param k_sqr_distances the resultant squared distances to the neighboring points
182 * \param max_nn if given, bounds the maximum returned neighbors to this value
183 * \return number of neighbors found in radius
184 */
185 inline int
186 radiusSearch (const PointCloud &cloud,
187 index_t index,
188 double radius,
189 Indices &k_indices,
190 std::vector<float> &k_sqr_distances,
191 unsigned int max_nn = 0) const override
192 {
193 tree_->radiusSearch (cloud, index, radius, k_indices, k_sqr_distances, max_nn);
194 if (sorted_results_)
195 this->sortResults (k_indices, k_sqr_distances);
196 return (static_cast<int> (k_indices.size ()));
197 }
198
199 /** \brief search for all neighbors of query point that are within a given radius.
200 * \param p_q the given query point
201 * \param radius the radius of the sphere bounding all of p_q's neighbors
202 * \param k_indices the resultant indices of the neighboring points
203 * \param k_sqr_distances the resultant squared distances to the neighboring points
204 * \param max_nn if given, bounds the maximum returned neighbors to this value
205 * \return number of neighbors found in radius
206 */
207 inline int
208 radiusSearch (const PointT &p_q,
209 double radius,
210 Indices &k_indices,
211 std::vector<float> &k_sqr_distances,
212 unsigned int max_nn = 0) const override
213 {
214 tree_->radiusSearch (p_q, radius, k_indices, k_sqr_distances, max_nn);
215 if (sorted_results_)
216 this->sortResults (k_indices, k_sqr_distances);
217 return (static_cast<int> (k_indices.size ()));
218 }
219
220 /** \brief search for all neighbors of query point that are within a given radius.
221 * \param index index representing the query point in the dataset given by \a setInputCloud.
222 * If indices were given in setInputCloud, index will be the position in the indices vector
223 * \param radius radius of the sphere bounding all of p_q's neighbors
224 * \param k_indices the resultant indices of the neighboring points
225 * \param k_sqr_distances the resultant squared distances to the neighboring points
226 * \param max_nn if given, bounds the maximum returned neighbors to this value
227 * \return number of neighbors found in radius
228 */
229 inline int
230 radiusSearch (index_t index, double radius, Indices &k_indices,
231 std::vector<float> &k_sqr_distances, unsigned int max_nn = 0) const override
232 {
233 tree_->radiusSearch (index, radius, k_indices, k_sqr_distances, max_nn);
234 if (sorted_results_)
235 this->sortResults (k_indices, k_sqr_distances);
236 return (static_cast<int> (k_indices.size ()));
237 }
238
239
240 /** \brief Search for approximate nearest neighbor at the query point.
241 * \param[in] cloud the point cloud data
242 * \param[in] query_index the index in \a cloud representing the query point
243 * \param[out] result_index the resultant index of the neighbor point
244 * \param[out] sqr_distance the resultant squared distance to the neighboring point
245 * \return number of neighbors found
246 */
247 inline void
248 approxNearestSearch (const PointCloudConstPtr &cloud, index_t query_index, index_t &result_index,
249 float &sqr_distance)
250 {
251 return (tree_->approxNearestSearch ((*cloud)[query_index], result_index, sqr_distance));
252 }
253
254 /** \brief Search for approximate nearest neighbor at the query point.
255 * \param[in] p_q the given query point
256 * \param[out] result_index the resultant index of the neighbor point
257 * \param[out] sqr_distance the resultant squared distance to the neighboring point
258 */
259 inline void
260 approxNearestSearch (const PointT &p_q, index_t &result_index, float &sqr_distance)
261 {
262 return (tree_->approxNearestSearch (p_q, result_index, sqr_distance));
263 }
264
265 /** \brief Search for approximate nearest neighbor at the query point.
266 * \param query_index index representing the query point in the dataset given by \a setInputCloud.
267 * If indices were given in setInputCloud, index will be the position in the indices vector.
268 * \param result_index the resultant index of the neighbor point
269 * \param sqr_distance the resultant squared distance to the neighboring point
270 * \return number of neighbors found
271 */
272 inline void
273 approxNearestSearch (index_t query_index, index_t &result_index, float &sqr_distance)
274 {
275 return (tree_->approxNearestSearch (query_index, result_index, sqr_distance));
276 }
277 /** \brief Search for points within rectangular search area
278 * \param[in] min_pt lower corner of search area
279 * \param[in] max_pt upper corner of search area
280 * \param[out] k_indices the resultant point indices
281 * \return number of points found within search area
282 */
283 inline uindex_t
284 boxSearch(const Eigen::Vector3f &min_pt, const Eigen::Vector3f &max_pt, Indices &k_indices) const
285 {
286 return (tree_->boxSearch(min_pt, max_pt, k_indices));
287 }
288 };
289 }
290}
291
292#ifdef PCL_NO_PRECOMPILE
293#include <pcl/octree/impl/octree_search.hpp>
294#else
295#define PCL_INSTANTIATE_Octree(T) template class PCL_EXPORTS pcl::search::Octree<T>;
296#endif
PointCloud represents the base class in PCL for storing collections of 3D points.
shared_ptr< PointCloud< PointT > > Ptr
shared_ptr< const PointCloud< PointT > > ConstPtr
Octree container class that does not store any information.
Octree container class that does store a vector of point indices.
shared_ptr< const OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT > > ConstPtr
shared_ptr< OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT > > Ptr
search::Octree is a wrapper class which implements nearest neighbor search operations based on the pc...
Definition octree.h:69
shared_ptr< const pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT > > ConstPtr
Definition octree.h:73
uindex_t boxSearch(const Eigen::Vector3f &min_pt, const Eigen::Vector3f &max_pt, Indices &k_indices) const
Search for points within rectangular search area.
Definition octree.h:284
typename PointCloud::Ptr PointCloudPtr
Definition octree.h:76
int nearestKSearch(index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
Search for the k-nearest neighbors for the given query point (zero-copy).
Definition octree.h:171
void setInputCloud(const PointCloudConstPtr &cloud)
Provide a pointer to the input dataset.
Definition octree.h:105
int radiusSearch(const PointT &p_q, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override
search for all neighbors of query point that are within a given radius.
Definition octree.h:208
OctreePointCloudSearchPtr tree_
Definition octree.h:82
void approxNearestSearch(const PointCloudConstPtr &cloud, index_t query_index, index_t &result_index, float &sqr_distance)
Search for approximate nearest neighbor at the query point.
Definition octree.h:248
typename PointCloud::ConstPtr PointCloudConstPtr
Definition octree.h:77
int radiusSearch(index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override
search for all neighbors of query point that are within a given radius.
Definition octree.h:230
typename pcl::octree::OctreePointCloudSearch< PointT, LeafTWrap, BranchTWrap >::ConstPtr OctreePointCloudSearchConstPtr
Definition octree.h:81
void approxNearestSearch(index_t query_index, index_t &result_index, float &sqr_distance)
Search for approximate nearest neighbor at the query point.
Definition octree.h:273
Octree(const double resolution)
Octree constructor.
Definition octree.h:91
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 override
search for all neighbors of query point that are within a given radius.
Definition octree.h:186
typename pcl::octree::OctreePointCloudSearch< PointT, LeafTWrap, BranchTWrap >::Ptr OctreePointCloudSearchPtr
Definition octree.h:80
shared_ptr< pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT > > Ptr
Definition octree.h:72
void approxNearestSearch(const PointT &p_q, index_t &result_index, float &sqr_distance)
Search for approximate nearest neighbor at the query point.
Definition octree.h:260
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.
Definition octree.h:153
bool setInputCloud(const PointCloudConstPtr &cloud, const IndicesConstPtr &indices) override
Provide a pointer to the input dataset.
Definition octree.h:118
~Octree() override=default
Empty Destructor.
int nearestKSearch(const PointCloud &cloud, index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
Search for the k-nearest neighbors for the given query point.
Definition octree.h:138
Generic search class.
Definition search.h:75
PointCloudConstPtr input_
Definition search.h:402
void sortResults(Indices &indices, std::vector< float > &distances) const
Definition search.hpp:189
IndicesConstPtr indices_
Definition search.h:403
pcl::IndicesConstPtr IndicesConstPtr
Definition search.h:85
detail::int_type_t< detail::index_type_size, false > uindex_t
Type used for an unsigned index in PCL.
Definition types.h:120
detail::int_type_t< detail::index_type_size, detail::index_type_signed > index_t
Type used for an index in PCL.
Definition types.h:112
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition types.h:133
A point structure representing Euclidean xyz coordinates, and the RGB color.