Point Cloud Library (PCL) 1.14.0
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gpu_extract_labeled_clusters.h
1/*
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39
40#pragma once
41
42#include <pcl/gpu/octree/octree.hpp>
43#include <pcl/pcl_macros.h>
44#include <pcl/point_cloud.h>
45#include <pcl/point_types.h>
46#include <pcl/PointIndices.h>
47
48namespace pcl {
49namespace gpu {
50template <typename PointT>
51void
53 const typename pcl::PointCloud<PointT>::Ptr& host_cloud_,
54 const pcl::gpu::Octree::Ptr& tree,
55 float tolerance,
56 std::vector<PointIndices>& clusters,
57 unsigned int min_pts_per_cluster,
58 unsigned int max_pts_per_cluster);
59
60/** \brief @b EuclideanLabeledClusterExtraction represents a segmentation class for
61 * cluster extraction in an Euclidean sense, depending on pcl::gpu::octree
62 * \author Koen Buys, Radu Bogdan Rusu
63 * \ingroup segmentation
64 */
65template <typename PointT>
67public:
70 using PointCloudHostPtr = typename PointCloudHost::Ptr;
71 using PointCloudHostConstPtr = typename PointCloudHost::ConstPtr;
72
75
78
80
81 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
82 /** \brief Empty constructor. */
84
85 /** \brief Default virtual destructor. */
87
88 /** \brief Provide a pointer to the search object.
89 * \param tree a pointer to the spatial search object.
90 */
91 inline void
93 {
94 tree_ = tree;
95 }
96
97 /** \brief Get a pointer to the search method used.
98 * @todo fix this for a generic search tree
99 */
100 inline GPUTreePtr
102 {
103 return (tree_);
104 }
105
106 /** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
107 * \param tolerance the spatial cluster tolerance measured by L2 distance
108 */
109 inline void
110 setClusterTolerance(double tolerance)
111 {
112 cluster_tolerance_ = tolerance;
113 }
114
115 /** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
116 */
117 inline double
119 {
120 return (cluster_tolerance_);
121 }
122
123 /** \brief Set the minimum number of points that a cluster needs to contain in order
124 * to be considered valid.
125 * \param min_cluster_size the minimum cluster size
126 */
127 inline void
128 setMinClusterSize(int min_cluster_size)
129 {
130 min_pts_per_cluster_ = min_cluster_size;
131 }
132
133 /** \brief Get the minimum number of points that a cluster needs to contain in order
134 * to be considered valid. */
135 inline int
137 {
138 return (min_pts_per_cluster_);
139 }
140
141 /** \brief Set the maximum number of points that a cluster needs to contain in order
142 * to be considered valid.
143 * \param max_cluster_size the maximum cluster size
144 */
145 inline void
146 setMaxClusterSize(int max_cluster_size)
147 {
148 max_pts_per_cluster_ = max_cluster_size;
149 }
150
151 /** \brief Get the maximum number of points that a cluster needs to contain in order
152 * to be considered valid. */
153 inline int
155 {
156 return (max_pts_per_cluster_);
157 }
158
159 inline void
161 {
162 input_ = input;
163 }
164
165 inline void
167 {
168 host_cloud_ = host_cloud;
169 }
170
171 /** \brief extract clusters of a PointCloud given by <setInputCloud(), setIndices()>
172 * \param clusters the resultant point clusters
173 */
174 void
175 extract(std::vector<PointIndices>& clusters);
176
177protected:
178 /** \brief the input cloud on the GPU */
180
181 /** \brief the original cloud the Host */
183
184 /** \brief A pointer to the spatial search object. */
186
187 /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
189
190 /** \brief The minimum number of points that a cluster needs to contain in order to be
191 * considered valid (default = 1). */
193
194 /** \brief The maximum number of points that a cluster needs to contain in order to be
195 * considered valid (default = MAXINT). */
196 int max_pts_per_cluster_{std::numeric_limits<int>::max()};
197
198 /** \brief Class getName method. */
199 virtual std::string
201 {
202 return ("gpu::EuclideanLabeledClusterExtraction");
203 }
204};
205/** \brief Sort clusters method (for std::sort).
206 * \ingroup segmentation
207 */
208inline bool
210{
211 return (a.indices.size() < b.indices.size());
212}
213} // namespace gpu
214} // namespace pcl
PointCloud represents the base class in PCL for storing collections of 3D points.
shared_ptr< PointCloud< PointT > > Ptr
EuclideanLabeledClusterExtraction represents a segmentation class for cluster extraction in an Euclid...
void setClusterTolerance(double tolerance)
Set the spatial cluster tolerance as a measure in the L2 Euclidean space.
GPUTreePtr tree_
A pointer to the spatial search object.
virtual ~EuclideanLabeledClusterExtraction()=default
Default virtual destructor.
virtual std::string getClassName() const
Class getName method.
int min_pts_per_cluster_
The minimum number of points that a cluster needs to contain in order to be considered valid (default...
GPUTreePtr getSearchMethod()
Get a pointer to the search method used.
typename PointCloudHost::ConstPtr PointCloudHostConstPtr
void extract(std::vector< PointIndices > &clusters)
extract clusters of a PointCloud given by <setInputCloud(), setIndices()>
void setSearchMethod(const GPUTreePtr &tree)
Provide a pointer to the search object.
int getMinClusterSize()
Get the minimum number of points that a cluster needs to contain in order to be considered valid.
double cluster_tolerance_
The spatial cluster tolerance as a measure in the L2 Euclidean space.
PointCloudHostPtr host_cloud_
the original cloud the Host
void setMaxClusterSize(int max_cluster_size)
Set the maximum number of points that a cluster needs to contain in order to be considered valid.
EuclideanLabeledClusterExtraction()=default
Empty constructor.
int getMaxClusterSize()
Get the maximum number of points that a cluster needs to contain in order to be considered valid.
double getClusterTolerance()
Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
int max_pts_per_cluster_
The maximum number of points that a cluster needs to contain in order to be considered valid (default...
void setMinClusterSize(int min_cluster_size)
Set the minimum number of points that a cluster needs to contain in order to be considered valid.
Octree implementation on GPU.
Definition octree.hpp:59
shared_ptr< Octree > Ptr
Types.
Definition octree.hpp:69
DeviceArray< PointType > PointCloud
Point cloud supported.
Definition octree.hpp:76
Defines all the PCL implemented PointT point type structures.
bool compareLabeledPointClusters(const pcl::PointIndices &a, const pcl::PointIndices &b)
Sort clusters method (for std::sort).
void extractLabeledEuclideanClusters(const typename pcl::PointCloud< PointT >::Ptr &host_cloud_, const pcl::gpu::Octree::Ptr &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster, unsigned int max_pts_per_cluster)
Defines all the PCL and non-PCL macros used.
shared_ptr< ::pcl::PointIndices > Ptr
shared_ptr< const ::pcl::PointIndices > ConstPtr
A point structure representing Euclidean xyz coordinates.