Point Cloud Library (PCL)  1.8.1-dev
extract_labeled_clusters.h
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35 
36 #ifndef PCL_EXTRACT_LABELED_CLUSTERS_H_
37 #define PCL_EXTRACT_LABELED_CLUSTERS_H_
38 
39 #include <pcl/pcl_base.h>
40 #include <pcl/search/pcl_search.h>
41 
42 namespace pcl
43 {
44  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
45  /** \brief Decompose a region of space into clusters based on the Euclidean distance between points
46  * \param[in] cloud the point cloud message
47  * \param[in] tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching
48  * \note the tree has to be created as a spatial locator on \a cloud
49  * \param[in] tolerance the spatial cluster tolerance as a measure in L2 Euclidean space
50  * \param[out] labeled_clusters the resultant clusters containing point indices (as a vector of PointIndices)
51  * \param[in] min_pts_per_cluster minimum number of points that a cluster may contain (default: 1)
52  * \param[in] max_pts_per_cluster maximum number of points that a cluster may contain (default: max int)
53  * \param[in] max_label
54  * \ingroup segmentation
55  */
56  template <typename PointT> void
58  const PointCloud<PointT> &cloud, const boost::shared_ptr<search::Search<PointT> > &tree,
59  float tolerance, std::vector<std::vector<PointIndices> > &labeled_clusters,
60  unsigned int min_pts_per_cluster = 1, unsigned int max_pts_per_cluster = std::numeric_limits<unsigned int>::max (),
61  unsigned int max_label = std::numeric_limits<unsigned int>::max ());
62 
63  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
64  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
65  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
66  /** \brief @b LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info.
67  * \author Koen Buys
68  * \ingroup segmentation
69  */
70  template <typename PointT>
72  {
74 
75  public:
77  typedef typename PointCloud::Ptr PointCloudPtr;
79 
82 
85 
86  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
87  /** \brief Empty constructor. */
89  tree_ (),
92  max_pts_per_cluster_ (std::numeric_limits<int>::max ()),
93  max_label_ (std::numeric_limits<int>::max ())
94  {};
95 
96  /** \brief Provide a pointer to the search object.
97  * \param[in] tree a pointer to the spatial search object.
98  */
99  inline void
100  setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
101 
102  /** \brief Get a pointer to the search method used. */
103  inline KdTreePtr
104  getSearchMethod () const { return (tree_); }
105 
106  /** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
107  * \param[in] tolerance the spatial cluster tolerance as a measure in the L2 Euclidean space
108  */
109  inline void
110  setClusterTolerance (double tolerance) { cluster_tolerance_ = tolerance; }
111 
112  /** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space. */
113  inline double
115 
116  /** \brief Set the minimum number of points that a cluster needs to contain in order to be considered valid.
117  * \param[in] min_cluster_size the minimum cluster size
118  */
119  inline void
120  setMinClusterSize (int min_cluster_size) { min_pts_per_cluster_ = min_cluster_size; }
121 
122  /** \brief Get the minimum number of points that a cluster needs to contain in order to be considered valid. */
123  inline int
125 
126  /** \brief Set the maximum number of points that a cluster needs to contain in order to be considered valid.
127  * \param[in] max_cluster_size the maximum cluster size
128  */
129  inline void
130  setMaxClusterSize (int max_cluster_size) { max_pts_per_cluster_ = max_cluster_size; }
131 
132  /** \brief Get the maximum number of points that a cluster needs to contain in order to be considered valid. */
133  inline int
135 
136  /** \brief Set the maximum number of labels in the cloud.
137  * \param[in] max_label the maximum
138  */
139  inline void
140  setMaxLabels (unsigned int max_label) { max_label_ = max_label; }
141 
142  /** \brief Get the maximum number of labels */
143  inline unsigned int
144  getMaxLabels () const { return (max_label_); }
145 
146  /** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
147  * \param[out] labeled_clusters the resultant point clusters
148  */
149  void
150  extract (std::vector<std::vector<PointIndices> > &labeled_clusters);
151 
152  protected:
153  // Members derived from the base class
154  using BasePCLBase::input_;
155  using BasePCLBase::indices_;
158 
159  /** \brief A pointer to the spatial search object. */
161 
162  /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
164 
165  /** \brief The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). */
167 
168  /** \brief The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). */
170 
171  /** \brief The maximum number of labels we can find in this pointcloud (default = MAXINT)*/
172  unsigned int max_label_;
173 
174  /** \brief Class getName method. */
175  virtual std::string getClassName () const { return ("LabeledEuclideanClusterExtraction"); }
176 
177  };
178 
179  /** \brief Sort clusters method (for std::sort).
180  * \ingroup segmentation
181  */
182  inline bool
184  {
185  return (a.indices.size () < b.indices.size ());
186  }
187 }
188 
189 #ifdef PCL_NO_PRECOMPILE
190 #include <pcl/segmentation/impl/extract_labeled_clusters.hpp>
191 #endif
192 
193 #endif //#ifndef PCL_EXTRACT_LABELED_CLUSTERS_H_
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:429
KdTreePtr getSearchMethod() const
Get a pointer to the search method used.
double cluster_tolerance_
The spatial cluster tolerance as a measure in the L2 Euclidean space.
bool compareLabeledPointClusters(const pcl::PointIndices &a, const pcl::PointIndices &b)
Sort clusters method (for std::sort).
double getClusterTolerance() const
Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
boost::shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:428
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition: pcl_base.h:153
std::vector< int > indices
Definition: PointIndices.h:19
int min_pts_per_cluster_
The minimum 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...
pcl::search::Search< PointT >::Ptr KdTreePtr
LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclid...
bool initCompute()
This method should get called before starting the actual computation.
Definition: pcl_base.hpp:139
unsigned int getMaxLabels() const
Get the maximum number of labels.
KdTreePtr tree_
A pointer to the spatial search object.
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
Definition: search.h:81
PCL base class.
Definition: pcl_base.h:68
virtual std::string getClassName() const
Class getName method.
void setClusterTolerance(double tolerance)
Set the spatial cluster tolerance as a measure in the L2 Euclidean space.
bool deinitCompute()
This method should get called after finishing the actual computation.
Definition: pcl_base.hpp:174
int getMaxClusterSize() const
Get the maximum number of points that a cluster needs to contain in order to be considered valid...
int max_pts_per_cluster_
The maximum number of points that a cluster needs to contain in order to be considered valid (default...
int getMinClusterSize() const
Get the minimum number of points that a cluster needs to contain in order to be considered valid...
boost::shared_ptr< ::pcl::PointIndices > Ptr
Definition: PointIndices.h:22
void setMaxClusterSize(int max_cluster_size)
Set the maximum number of points that a cluster needs to contain in order to be considered valid...
void extract(std::vector< std::vector< PointIndices > > &labeled_clusters)
Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
PointCloudConstPtr input_
The input point cloud dataset.
Definition: pcl_base.h:150
void setMaxLabels(unsigned int max_label)
Set the maximum number of labels in the cloud.
unsigned int max_label_
The maximum number of labels we can find in this pointcloud (default = MAXINT)
boost::shared_ptr< ::pcl::PointIndices const > ConstPtr
Definition: PointIndices.h:23
void extractLabeledEuclideanClusters(const PointCloud< PointT > &cloud, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< std::vector< PointIndices > > &labeled_clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=std::numeric_limits< unsigned int >::max(), unsigned int max_label=std::numeric_limits< unsigned int >::max())
Decompose a region of space into clusters based on the Euclidean distance between points...
Generic search class.
Definition: search.h:74