Point Cloud Library (PCL) 1.12.1
gpu_extract_clusters.h
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39
40#pragma once
41
42#include <pcl/gpu/containers/device_array.h>
43#include <pcl/gpu/octree/octree.hpp>
44#include <pcl/PointIndices.h>
45#include <pcl/pcl_macros.h>
46#include <pcl/point_cloud.h>
47#include <pcl/point_types.h>
48
49namespace pcl {
50namespace gpu {
51template <typename PointT>
52void
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 EuclideanClusterExtraction represents a segmentation class for cluster
61 * 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:
71
74
77
79
80 //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
81 /** \brief Empty constructor. */
83
84 /** \brief the destructor */
85 /* ~EuclideanClusterExtraction ()
86 {
87 tree_.clear();
88 };
89 */
90 /** \brief Provide a pointer to the search object.
91 * \param tree a pointer to the spatial search object.
92 */
93 inline void
95 {
96 tree_ = tree;
97 }
98
99 /** \brief Get a pointer to the search method used.
100 * @todo fix this for a generic search tree
101 */
102 inline GPUTreePtr
104 {
105 return (tree_);
106 }
107
108 /** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
109 * \param tolerance the spatial cluster tolerance as a measure in the L2 Euclidean
110 * space
111 */
112 inline void
113 setClusterTolerance(double tolerance)
114 {
115 cluster_tolerance_ = tolerance;
116 }
117
118 /** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
119 */
120 inline double
122 {
123 return (cluster_tolerance_);
124 }
125
126 /** \brief Set the minimum number of points that a cluster needs to contain in order
127 * to be considered valid.
128 * \param min_cluster_size the minimum cluster size
129 */
130 inline void
131 setMinClusterSize(int min_cluster_size)
132 {
133 min_pts_per_cluster_ = min_cluster_size;
134 }
135
136 /** \brief Get the minimum number of points that a cluster needs to contain in order
137 * to be considered valid. */
138 inline int
140 {
141 return (min_pts_per_cluster_);
142 }
143
144 /** \brief Set the maximum number of points that a cluster needs to contain in order
145 * to be considered valid.
146 * \param max_cluster_size the maximum cluster size
147 */
148 inline void
149 setMaxClusterSize(int max_cluster_size)
150 {
151 max_pts_per_cluster_ = max_cluster_size;
152 }
153
154 /** \brief Get the maximum number of points that a cluster needs to contain in order
155 * to be considered valid. */
156 inline int
158 {
159 return (max_pts_per_cluster_);
160 }
161
162 inline void
164 {
165 input_ = input;
166 }
167
168 inline void
170 {
171 host_cloud_ = host_cloud;
172 }
173
174 /** \brief extract clusters of a PointCloud given by <setInputCloud(), setIndices()>
175 * \param clusters the resultant point clusters
176 */
177 void
178 extract(std::vector<pcl::PointIndices>& clusters);
179
180protected:
181 /** \brief the input cloud on the GPU */
183
184 /** \brief the original cloud the Host */
186
187 /** \brief A pointer to the spatial search object. */
189
190 /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
192
193 /** \brief The minimum number of points that a cluster needs to contain in order to be
194 * considered valid (default = 1). */
196
197 /** \brief The maximum number of points that a cluster needs to contain in order to be
198 * considered valid (default = MAXINT). */
199 int max_pts_per_cluster_{std::numeric_limits<int>::max()};
200
201 /** \brief Class getName method. */
202 virtual std::string
204 {
205 return ("gpu::EuclideanClusterExtraction");
206 }
207};
208/** \brief Sort clusters method (for std::sort).
209 * \ingroup segmentation
210 */
211inline bool
213{
214 return (a.indices.size() < b.indices.size());
215}
216} // namespace gpu
217} // namespace pcl
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:413
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:414
EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sen...
virtual std::string getClassName() const
Class getName method.
GPUTreePtr tree_
A pointer to the spatial search object.
EuclideanClusterExtraction()=default
Empty constructor.
CloudDevice input_
the input cloud on the GPU
int getMinClusterSize()
Get the minimum number of points that a cluster needs to contain in order to be considered valid.
typename PointCloudHost::Ptr PointCloudHostPtr
void setSearchMethod(GPUTreePtr &tree)
the destructor
typename PointCloudHost::ConstPtr PointCloudHostConstPtr
int min_pts_per_cluster_
The minimum number of points that a cluster needs to contain in order to be considered valid (default...
double getClusterTolerance()
Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
void extract(std::vector< pcl::PointIndices > &clusters)
extract clusters of a PointCloud given by <setInputCloud(), setIndices()>
void setClusterTolerance(double tolerance)
Set the spatial cluster tolerance as a measure in the L2 Euclidean space.
void setMinClusterSize(int min_cluster_size)
Set the minimum number of points that a cluster needs to contain in order to be considered valid.
int getMaxClusterSize()
Get the maximum number of points that a cluster needs to contain in order to be considered valid.
void setMaxClusterSize(int max_cluster_size)
Set the maximum 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.
int max_pts_per_cluster_
The maximum number of points that a cluster needs to contain in order to be considered valid (default...
PointCloudHostPtr host_cloud_
the original cloud the Host
void setHostCloud(PointCloudHostPtr host_cloud)
GPUTreePtr getSearchMethod()
Get a pointer to the search method used.
Octree implementation on GPU.
Definition: octree.hpp:58
shared_ptr< Octree > Ptr
Types.
Definition: octree.hpp:68
DeviceArray< PointType > PointCloud
Point cloud supported.
Definition: octree.hpp:75
Defines all the PCL implemented PointT point type structures.
bool comparePointClusters(const pcl::PointIndices &a, const pcl::PointIndices &b)
Sort clusters method (for std::sort).
void extractEuclideanClusters(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
Definition: PointIndices.h:13
shared_ptr< const ::pcl::PointIndices > ConstPtr
Definition: PointIndices.h:14