Point Cloud Library (PCL)
1.15.1
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segmentation
include
pcl
gpu
segmentation
gpu_extract_clusters.h
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2010-2011, Willow Garage, Inc.
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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* $Id:$
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* @author: Koen Buys
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*/
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#pragma once
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#include <pcl/gpu/containers/device_array.h>
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#include <pcl/gpu/octree/octree.hpp>
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#include <
pcl/pcl_macros.h
>
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#include <pcl/point_cloud.h>
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#include <
pcl/point_types.h
>
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#include <pcl/PointIndices.h>
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namespace
pcl
{
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namespace
gpu
{
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template
<
typename
Po
int
T>
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void
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extractEuclideanClusters
(
const
typename
pcl::PointCloud<PointT>::Ptr
& host_cloud_,
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const
pcl::gpu::Octree::Ptr
& tree,
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float
tolerance,
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std::vector<PointIndices>& clusters,
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unsigned
int
min_pts_per_cluster,
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unsigned
int
max_pts_per_cluster);
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/** \brief @b EuclideanClusterExtraction represents a segmentation class for cluster
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* extraction in an Euclidean sense, depending on pcl::gpu::octree
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* \author Koen Buys, Radu Bogdan Rusu
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* \ingroup segmentation
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*/
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template
<
typename
Po
int
T>
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class
EuclideanClusterExtraction
{
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public
:
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using
PointCloudHost
=
pcl::PointCloud<PointT>
;
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using
PointCloudHostPtr
=
typename
PointCloudHost::Ptr
;
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using
PointCloudHostConstPtr
=
typename
PointCloudHost::ConstPtr
;
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using
PointIndicesPtr
=
PointIndices::Ptr
;
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using
PointIndicesConstPtr
=
PointIndices::ConstPtr
;
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using
GPUTree
=
pcl::gpu::Octree
;
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using
GPUTreePtr
=
pcl::gpu::Octree::Ptr
;
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using
CloudDevice
=
pcl::gpu::Octree::PointCloud
;
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/** \brief Empty constructor. */
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EuclideanClusterExtraction
() =
default
;
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/** \brief Default virtual destructor. */
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virtual
~EuclideanClusterExtraction
() =
default
;
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/** \brief the destructor */
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/* ~EuclideanClusterExtraction ()
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{
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tree_.clear();
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};
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*/
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/** \brief Provide a pointer to the search object.
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* \param tree a pointer to the spatial search object.
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*/
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inline
void
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setSearchMethod
(
GPUTreePtr
& tree)
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{
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tree_
= tree;
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}
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/** \brief Get a pointer to the search method used.
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* @todo fix this for a generic search tree
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*/
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inline
GPUTreePtr
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getSearchMethod
()
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{
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return
(
tree_
);
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}
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/** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
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* \param tolerance the spatial cluster tolerance as a measure in the L2 Euclidean
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* space
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*/
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inline
void
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setClusterTolerance
(
double
tolerance)
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{
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cluster_tolerance_
= tolerance;
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}
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/** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
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*/
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inline
double
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getClusterTolerance
()
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{
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return
(
cluster_tolerance_
);
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}
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/** \brief Set the minimum number of points that a cluster needs to contain in order
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* to be considered valid.
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* \param min_cluster_size the minimum cluster size
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*/
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inline
void
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setMinClusterSize
(
int
min_cluster_size)
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{
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min_pts_per_cluster_
= min_cluster_size;
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}
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/** \brief Get the minimum number of points that a cluster needs to contain in order
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* to be considered valid. */
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inline
int
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getMinClusterSize
()
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{
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return
(
min_pts_per_cluster_
);
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}
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/** \brief Set the maximum number of points that a cluster needs to contain in order
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* to be considered valid.
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* \param max_cluster_size the maximum cluster size
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*/
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inline
void
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setMaxClusterSize
(
int
max_cluster_size)
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{
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max_pts_per_cluster_
= max_cluster_size;
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}
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/** \brief Get the maximum number of points that a cluster needs to contain in order
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* to be considered valid. */
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inline
int
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getMaxClusterSize
()
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{
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return
(
max_pts_per_cluster_
);
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}
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inline
void
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setInput
(
CloudDevice
input)
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{
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input_
= input;
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}
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inline
void
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setHostCloud
(
PointCloudHostPtr
host_cloud)
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{
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host_cloud_
= host_cloud;
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}
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/** \brief extract clusters of a PointCloud given by <setInputCloud(), setIndices()>
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* \param clusters the resultant point clusters
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*/
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void
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extract
(std::vector<pcl::PointIndices>& clusters);
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protected
:
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/** \brief the input cloud on the GPU */
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CloudDevice
input_
;
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/** \brief the original cloud the Host */
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PointCloudHostPtr
host_cloud_
;
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/** \brief A pointer to the spatial search object. */
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GPUTreePtr
tree_
;
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/** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
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double
cluster_tolerance_
{0.0};
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/** \brief The minimum number of points that a cluster needs to contain in order to be
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* considered valid (default = 1). */
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int
min_pts_per_cluster_
{1};
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/** \brief The maximum number of points that a cluster needs to contain in order to be
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* considered valid (default = MAXINT). */
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int
max_pts_per_cluster_
{std::numeric_limits<int>::max()};
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/** \brief Class getName method. */
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virtual
std::string
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getClassName
()
const
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{
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return
(
"gpu::EuclideanClusterExtraction"
);
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}
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};
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/** \brief Sort clusters method (for std::sort).
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* \ingroup segmentation
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*/
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inline
bool
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comparePointClusters
(
const
pcl::PointIndices
& a,
const
pcl::PointIndices
& b)
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{
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return
(a.
indices
.size() < b.
indices
.size());
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}
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}
// namespace gpu
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}
// namespace pcl
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition
point_cloud.h:174
pcl::PointCloud::Ptr
shared_ptr< PointCloud< PointT > > Ptr
Definition
point_cloud.h:414
pcl::PointCloud::ConstPtr
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition
point_cloud.h:415
pcl::gpu::EuclideanClusterExtraction::getClassName
virtual std::string getClassName() const
Class getName method.
Definition
gpu_extract_clusters.h:206
pcl::gpu::EuclideanClusterExtraction::GPUTree
pcl::gpu::Octree GPUTree
Definition
gpu_extract_clusters.h:75
pcl::gpu::EuclideanClusterExtraction::tree_
GPUTreePtr tree_
A pointer to the spatial search object.
Definition
gpu_extract_clusters.h:191
pcl::gpu::EuclideanClusterExtraction::EuclideanClusterExtraction
EuclideanClusterExtraction()=default
Empty constructor.
pcl::gpu::EuclideanClusterExtraction::PointCloudHost
pcl::PointCloud< PointT > PointCloudHost
Definition
gpu_extract_clusters.h:68
pcl::gpu::EuclideanClusterExtraction::input_
CloudDevice input_
the input cloud on the GPU
Definition
gpu_extract_clusters.h:185
pcl::gpu::EuclideanClusterExtraction::getMinClusterSize
int getMinClusterSize()
Get the minimum number of points that a cluster needs to contain in order to be considered valid.
Definition
gpu_extract_clusters.h:142
pcl::gpu::EuclideanClusterExtraction::PointCloudHostPtr
typename PointCloudHost::Ptr PointCloudHostPtr
Definition
gpu_extract_clusters.h:69
pcl::gpu::EuclideanClusterExtraction::setSearchMethod
void setSearchMethod(GPUTreePtr &tree)
the destructor
Definition
gpu_extract_clusters.h:97
pcl::gpu::EuclideanClusterExtraction::PointCloudHostConstPtr
typename PointCloudHost::ConstPtr PointCloudHostConstPtr
Definition
gpu_extract_clusters.h:70
pcl::gpu::EuclideanClusterExtraction::min_pts_per_cluster_
int min_pts_per_cluster_
The minimum number of points that a cluster needs to contain in order to be considered valid (default...
Definition
gpu_extract_clusters.h:198
pcl::gpu::EuclideanClusterExtraction::getClusterTolerance
double getClusterTolerance()
Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
Definition
gpu_extract_clusters.h:124
pcl::gpu::EuclideanClusterExtraction::extract
void extract(std::vector< pcl::PointIndices > &clusters)
extract clusters of a PointCloud given by <setInputCloud(), setIndices()>
Definition
gpu_extract_clusters.hpp:189
pcl::gpu::EuclideanClusterExtraction::CloudDevice
pcl::gpu::Octree::PointCloud CloudDevice
Definition
gpu_extract_clusters.h:78
pcl::gpu::EuclideanClusterExtraction::setClusterTolerance
void setClusterTolerance(double tolerance)
Set the spatial cluster tolerance as a measure in the L2 Euclidean space.
Definition
gpu_extract_clusters.h:116
pcl::gpu::EuclideanClusterExtraction::PointIndicesPtr
PointIndices::Ptr PointIndicesPtr
Definition
gpu_extract_clusters.h:72
pcl::gpu::EuclideanClusterExtraction::setMinClusterSize
void setMinClusterSize(int min_cluster_size)
Set the minimum number of points that a cluster needs to contain in order to be considered valid.
Definition
gpu_extract_clusters.h:134
pcl::gpu::EuclideanClusterExtraction::getMaxClusterSize
int getMaxClusterSize()
Get the maximum number of points that a cluster needs to contain in order to be considered valid.
Definition
gpu_extract_clusters.h:160
pcl::gpu::EuclideanClusterExtraction::~EuclideanClusterExtraction
virtual ~EuclideanClusterExtraction()=default
Default virtual destructor.
pcl::gpu::EuclideanClusterExtraction::setMaxClusterSize
void setMaxClusterSize(int max_cluster_size)
Set the maximum number of points that a cluster needs to contain in order to be considered valid.
Definition
gpu_extract_clusters.h:152
pcl::gpu::EuclideanClusterExtraction::cluster_tolerance_
double cluster_tolerance_
The spatial cluster tolerance as a measure in the L2 Euclidean space.
Definition
gpu_extract_clusters.h:194
pcl::gpu::EuclideanClusterExtraction::max_pts_per_cluster_
int max_pts_per_cluster_
The maximum number of points that a cluster needs to contain in order to be considered valid (default...
Definition
gpu_extract_clusters.h:202
pcl::gpu::EuclideanClusterExtraction::host_cloud_
PointCloudHostPtr host_cloud_
the original cloud the Host
Definition
gpu_extract_clusters.h:188
pcl::gpu::EuclideanClusterExtraction::setHostCloud
void setHostCloud(PointCloudHostPtr host_cloud)
Definition
gpu_extract_clusters.h:172
pcl::gpu::EuclideanClusterExtraction::setInput
void setInput(CloudDevice input)
Definition
gpu_extract_clusters.h:166
pcl::gpu::EuclideanClusterExtraction::GPUTreePtr
pcl::gpu::Octree::Ptr GPUTreePtr
Definition
gpu_extract_clusters.h:76
pcl::gpu::EuclideanClusterExtraction::getSearchMethod
GPUTreePtr getSearchMethod()
Get a pointer to the search method used.
Definition
gpu_extract_clusters.h:106
pcl::gpu::EuclideanClusterExtraction::PointIndicesConstPtr
PointIndices::ConstPtr PointIndicesConstPtr
Definition
gpu_extract_clusters.h:73
pcl::gpu::Octree
Octree implementation on GPU.
Definition
octree.hpp:59
pcl::gpu::Octree::Ptr
shared_ptr< Octree > Ptr
Types.
Definition
octree.hpp:69
pcl::gpu::Octree::PointCloud
DeviceArray< PointType > PointCloud
Point cloud supported.
Definition
octree.hpp:76
point_types.h
Defines all the PCL implemented PointT point type structures.
pcl::gpu::comparePointClusters
bool comparePointClusters(const pcl::PointIndices &a, const pcl::PointIndices &b)
Sort clusters method (for std::sort).
Definition
gpu_extract_clusters.h:215
pcl::gpu
Definition
device_array.h:45
pcl::gpu::extractEuclideanClusters
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)
Definition
gpu_extract_clusters.hpp:58
pcl
Definition
convolution.h:46
pcl_macros.h
Defines all the PCL and non-PCL macros used.
pcl::PointIndices
Definition
PointIndices.h:12
pcl::PointIndices::Ptr
shared_ptr< ::pcl::PointIndices > Ptr
Definition
PointIndices.h:13
pcl::PointIndices::ConstPtr
shared_ptr< const ::pcl::PointIndices > ConstPtr
Definition
PointIndices.h:14
pcl::PointIndices::indices
Indices indices
Definition
PointIndices.h:20