Point Cloud Library (PCL)  1.14.1-dev
List of all members | Public Types | Public Member Functions | Protected Member Functions | Protected Attributes
pcl::EuclideanClusterExtraction< PointT > Class Template Reference

EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More...

#include <pcl/segmentation/extract_clusters.h>

+ Inheritance diagram for pcl::EuclideanClusterExtraction< PointT >:
+ Collaboration diagram for pcl::EuclideanClusterExtraction< PointT >:

Public Types

using PointCloud = pcl::PointCloud< PointT >
 
using PointCloudPtr = typename PointCloud::Ptr
 
using PointCloudConstPtr = typename PointCloud::ConstPtr
 
using KdTree = pcl::search::Search< PointT >
 
using KdTreePtr = typename KdTree::Ptr
 
using PointIndicesPtr = PointIndices::Ptr
 
using PointIndicesConstPtr = PointIndices::ConstPtr
 
- Public Types inherited from pcl::PCLBase< PointT >
using PointCloud = pcl::PointCloud< PointT >
 
using PointCloudPtr = typename PointCloud::Ptr
 
using PointCloudConstPtr = typename PointCloud::ConstPtr
 
using PointIndicesPtr = PointIndices::Ptr
 
using PointIndicesConstPtr = PointIndices::ConstPtr
 

Public Member Functions

 EuclideanClusterExtraction ()=default
 Empty constructor. More...
 
void setSearchMethod (const KdTreePtr &tree)
 Provide a pointer to the search object. More...
 
KdTreePtr getSearchMethod () const
 Get a pointer to the search method used. More...
 
void setClusterTolerance (double tolerance)
 Set the spatial cluster tolerance as a measure in the L2 Euclidean space. More...
 
double getClusterTolerance () const
 Get the spatial cluster tolerance as a measure in the L2 Euclidean space. More...
 
void setMinClusterSize (pcl::uindex_t min_cluster_size)
 Set the minimum number of points that a cluster needs to contain in order to be considered valid. More...
 
pcl::uindex_t getMinClusterSize () const
 Get the minimum number of points that a cluster needs to contain in order to be considered valid. More...
 
void setMaxClusterSize (pcl::uindex_t max_cluster_size)
 Set the maximum number of points that a cluster needs to contain in order to be considered valid. More...
 
pcl::uindex_t getMaxClusterSize () const
 Get the maximum number of points that a cluster needs to contain in order to be considered valid. More...
 
void extract (std::vector< PointIndices > &clusters)
 Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()> More...
 
- Public Member Functions inherited from pcl::PCLBase< PointT >
 PCLBase ()
 Empty constructor. More...
 
 PCLBase (const PCLBase &base)
 Copy constructor. More...
 
virtual ~PCLBase ()=default
 Destructor. More...
 
virtual void setInputCloud (const PointCloudConstPtr &cloud)
 Provide a pointer to the input dataset. More...
 
PointCloudConstPtr const getInputCloud () const
 Get a pointer to the input point cloud dataset. More...
 
virtual void setIndices (const IndicesPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (const IndicesConstPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (const PointIndicesConstPtr &indices)
 Provide a pointer to the vector of indices that represents the input data. More...
 
virtual void setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols)
 Set the indices for the points laying within an interest region of the point cloud. More...
 
IndicesPtr getIndices ()
 Get a pointer to the vector of indices used. More...
 
IndicesConstPtr const getIndices () const
 Get a pointer to the vector of indices used. More...
 
const PointToperator[] (std::size_t pos) const
 Override PointCloud operator[] to shorten code. More...
 

Protected Member Functions

virtual std::string getClassName () const
 Class getName method. More...
 
bool initCompute ()
 This method should get called before starting the actual computation. More...
 
bool deinitCompute ()
 This method should get called after finishing the actual computation. More...
 
- Protected Member Functions inherited from pcl::PCLBase< PointT >
bool initCompute ()
 This method should get called before starting the actual computation. More...
 
bool deinitCompute ()
 This method should get called after finishing the actual computation. More...
 

Protected Attributes

KdTreePtr tree_ {nullptr}
 A pointer to the spatial search object. More...
 
double cluster_tolerance_ {0.0}
 The spatial cluster tolerance as a measure in the L2 Euclidean space. More...
 
pcl::uindex_t min_pts_per_cluster_ {1}
 The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). More...
 
pcl::uindex_t max_pts_per_cluster_ {std::numeric_limits<pcl::uindex_t>::max()}
 The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). More...
 
PointCloudConstPtr input_
 The input point cloud dataset. More...
 
IndicesPtr indices_
 A pointer to the vector of point indices to use. More...
 
- Protected Attributes inherited from pcl::PCLBase< PointT >
PointCloudConstPtr input_
 The input point cloud dataset. More...
 
IndicesPtr indices_
 A pointer to the vector of point indices to use. More...
 
bool use_indices_
 Set to true if point indices are used. More...
 
bool fake_indices_
 If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More...
 

Detailed Description

template<typename PointT>
class pcl::EuclideanClusterExtraction< PointT >

EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense.

Author
Radu Bogdan Rusu

Definition at line 327 of file extract_clusters.h.

Member Typedef Documentation

◆ KdTree

template<typename PointT >
using pcl::EuclideanClusterExtraction< PointT >::KdTree = pcl::search::Search<PointT>

Definition at line 336 of file extract_clusters.h.

◆ KdTreePtr

template<typename PointT >
using pcl::EuclideanClusterExtraction< PointT >::KdTreePtr = typename KdTree::Ptr

Definition at line 337 of file extract_clusters.h.

◆ PointCloud

template<typename PointT >
using pcl::EuclideanClusterExtraction< PointT >::PointCloud = pcl::PointCloud<PointT>

Definition at line 332 of file extract_clusters.h.

◆ PointCloudConstPtr

template<typename PointT >
using pcl::EuclideanClusterExtraction< PointT >::PointCloudConstPtr = typename PointCloud::ConstPtr

Definition at line 334 of file extract_clusters.h.

◆ PointCloudPtr

template<typename PointT >
using pcl::EuclideanClusterExtraction< PointT >::PointCloudPtr = typename PointCloud::Ptr

Definition at line 333 of file extract_clusters.h.

◆ PointIndicesConstPtr

Definition at line 340 of file extract_clusters.h.

◆ PointIndicesPtr

Definition at line 339 of file extract_clusters.h.

Constructor & Destructor Documentation

◆ EuclideanClusterExtraction()

template<typename PointT >
pcl::EuclideanClusterExtraction< PointT >::EuclideanClusterExtraction ( )
default

Empty constructor.

Member Function Documentation

◆ deinitCompute()

template<typename PointT >
bool pcl::PCLBase< PointT >::deinitCompute
protected

This method should get called after finishing the actual computation.

Definition at line 173 of file pcl_base.hpp.

◆ extract()

template<typename PointT >
void pcl::EuclideanClusterExtraction< PointT >::extract ( std::vector< PointIndices > &  clusters)

Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>

Parameters
[out]clustersthe resultant point clusters

Definition at line 224 of file extract_clusters.hpp.

References pcl::gpu::comparePointClusters(), and pcl::extractEuclideanClusters().

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ getClassName()

template<typename PointT >
virtual std::string pcl::EuclideanClusterExtraction< PointT >::getClassName ( ) const
inlineprotectedvirtual

Class getName method.

Definition at line 438 of file extract_clusters.h.

◆ getClusterTolerance()

template<typename PointT >
double pcl::EuclideanClusterExtraction< PointT >::getClusterTolerance ( ) const
inline

Get the spatial cluster tolerance as a measure in the L2 Euclidean space.

Definition at line 375 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::cluster_tolerance_.

◆ getMaxClusterSize()

template<typename PointT >
pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::getMaxClusterSize ( ) const
inline

Get the maximum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 407 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::max_pts_per_cluster_.

◆ getMinClusterSize()

template<typename PointT >
pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::getMinClusterSize ( ) const
inline

Get the minimum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 391 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::min_pts_per_cluster_.

◆ getSearchMethod()

template<typename PointT >
KdTreePtr pcl::EuclideanClusterExtraction< PointT >::getSearchMethod ( ) const
inline

Get a pointer to the search method used.

Todo:
fix this for a generic search tree

Definition at line 359 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::tree_.

◆ initCompute()

template<typename PointT >
bool pcl::PCLBase< PointT >::initCompute
protected

This method should get called before starting the actual computation.

Internally, initCompute() does the following:

  • checks if an input dataset is given, and returns false otherwise
  • checks whether a set of input indices has been given. Returns true if yes.
  • if no input indices have been given, a fake set is created, which will be used until:
    • either a new set is given via setIndices(), or
    • a new cloud is given that has a different set of points. This will trigger an update on the set of fake indices

Definition at line 168 of file pcl_base.hpp.

◆ setClusterTolerance()

template<typename PointT >
void pcl::EuclideanClusterExtraction< PointT >::setClusterTolerance ( double  tolerance)
inline

Set the spatial cluster tolerance as a measure in the L2 Euclidean space.

Parameters
[in]tolerancethe spatial cluster tolerance as a measure in the L2 Euclidean space

Definition at line 368 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::cluster_tolerance_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ setMaxClusterSize()

template<typename PointT >
void pcl::EuclideanClusterExtraction< PointT >::setMaxClusterSize ( pcl::uindex_t  max_cluster_size)
inline

Set the maximum number of points that a cluster needs to contain in order to be considered valid.

Parameters
[in]max_cluster_sizethe maximum cluster size

Definition at line 400 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::max_pts_per_cluster_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ setMinClusterSize()

template<typename PointT >
void pcl::EuclideanClusterExtraction< PointT >::setMinClusterSize ( pcl::uindex_t  min_cluster_size)
inline

Set the minimum number of points that a cluster needs to contain in order to be considered valid.

Parameters
[in]min_cluster_sizethe minimum cluster size

Definition at line 384 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::min_pts_per_cluster_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ setSearchMethod()

template<typename PointT >
void pcl::EuclideanClusterExtraction< PointT >::setSearchMethod ( const KdTreePtr tree)
inline

Provide a pointer to the search object.

Parameters
[in]treea pointer to the spatial search object.

Definition at line 350 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::tree_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

Member Data Documentation

◆ cluster_tolerance_

template<typename PointT >
double pcl::EuclideanClusterExtraction< PointT >::cluster_tolerance_ {0.0}
protected

The spatial cluster tolerance as a measure in the L2 Euclidean space.

Definition at line 429 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getClusterTolerance(), and pcl::EuclideanClusterExtraction< PointT >::setClusterTolerance().

◆ indices_

template<typename PointT >
IndicesPtr pcl::PCLBase< PointT >::indices_
protected

A pointer to the vector of point indices to use.

Definition at line 150 of file pcl_base.h.

◆ input_

template<typename PointT >
PointCloudConstPtr pcl::PCLBase< PointT >::input_
protected

The input point cloud dataset.

Definition at line 147 of file pcl_base.h.

◆ max_pts_per_cluster_

template<typename PointT >
pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::max_pts_per_cluster_ {std::numeric_limits<pcl::uindex_t>::max()}
protected

The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT).

Definition at line 435 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getMaxClusterSize(), and pcl::EuclideanClusterExtraction< PointT >::setMaxClusterSize().

◆ min_pts_per_cluster_

template<typename PointT >
pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::min_pts_per_cluster_ {1}
protected

The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1).

Definition at line 432 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getMinClusterSize(), and pcl::EuclideanClusterExtraction< PointT >::setMinClusterSize().

◆ tree_

template<typename PointT >
KdTreePtr pcl::EuclideanClusterExtraction< PointT >::tree_ {nullptr}
protected

The documentation for this class was generated from the following files: