Point Cloud Library (PCL)  1.12.1-dev
conditional_euclidean_clustering.h
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37 
38 #pragma once
39 
40 #include <pcl/memory.h>
41 #include <pcl/pcl_base.h>
42 #include <pcl/pcl_macros.h>
43 #include <pcl/console/print.h> // for PCL_WARN
44 #include <pcl/search/search.h> // for Search
45 
46 #include <functional>
47 
48 namespace pcl
49 {
50  using IndicesClusters = std::vector<pcl::PointIndices>;
51  using IndicesClustersPtr = shared_ptr<std::vector<pcl::PointIndices> >;
52 
53  /** \brief @b ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined clustering condition.
54  * \details The condition that need to hold is currently passed using a function pointer.
55  * For more information check the documentation of setConditionFunction() or the usage example below:
56  * \code
57  * bool
58  * enforceIntensitySimilarity (const pcl::PointXYZI& point_a, const pcl::PointXYZI& point_b, float squared_distance)
59  * {
60  * if (std::abs (point_a.intensity - point_b.intensity) < 0.1f)
61  * return (true);
62  * else
63  * return (false);
64  * }
65  * // ...
66  * // Somewhere down to the main code
67  * // ...
68  * pcl::ConditionalEuclideanClustering<pcl::PointXYZI> cec (true);
69  * cec.setInputCloud (cloud_in);
70  * cec.setConditionFunction (&enforceIntensitySimilarity);
71  * // Points within this distance from one another are going to need to validate the enforceIntensitySimilarity function to be part of the same cluster:
72  * cec.setClusterTolerance (0.09f);
73  * // Size constraints for the clusters:
74  * cec.setMinClusterSize (5);
75  * cec.setMaxClusterSize (30);
76  * // The resulting clusters (an array of pointindices):
77  * cec.segment (*clusters);
78  * // The clusters that are too small or too large in size can also be extracted separately:
79  * cec.getRemovedClusters (small_clusters, large_clusters);
80  * \endcode
81  * \author Frits Florentinus
82  * \ingroup segmentation
83  */
84  template<typename PointT>
85  class ConditionalEuclideanClustering : public PCLBase<PointT>
86  {
87  protected:
89 
94 
95  public:
96  /** \brief Constructor.
97  * \param[in] extract_removed_clusters Set to true if you want to be able to extract the clusters that are too large or too small (default = false)
98  */
99  ConditionalEuclideanClustering (bool extract_removed_clusters = false) :
100  searcher_ (),
101  condition_function_ (),
102  cluster_tolerance_ (0.0f),
103  min_cluster_size_ (1),
104  max_cluster_size_ (std::numeric_limits<int>::max ()),
105  extract_removed_clusters_ (extract_removed_clusters),
106  small_clusters_ (new pcl::IndicesClusters),
107  large_clusters_ (new pcl::IndicesClusters)
108  {
109  }
110 
111  /** \brief Provide a pointer to the search object.
112  * \param[in] tree a pointer to the spatial search object.
113  */
114  inline void
116  {
117  searcher_ = tree;
118  }
119 
120  /** \brief Get a pointer to the search method used.
121  */
122  inline const SearcherPtr&
124  {
125  return searcher_;
126  }
127 
128  /** \brief Set the condition that needs to hold for neighboring points to be considered part of the same cluster.
129  * \details Any two points within a certain distance from one another will need to evaluate this condition in order to be made part of the same cluster.
130  * The distance can be set using setClusterTolerance().
131  * <br>
132  * Note that for a point to be part of a cluster, the condition only needs to hold for at least 1 point pair.
133  * To clarify, the following statement is false:
134  * Any two points within a cluster always evaluate this condition function to true.
135  * <br><br>
136  * The input arguments of the condition function are:
137  * <ul>
138  * <li>PointT The first point of the point pair</li>
139  * <li>PointT The second point of the point pair</li>
140  * <li>float The squared distance between the points</li>
141  * </ul>
142  * The output argument is a boolean, returning true will merge the second point into the cluster of the first point.
143  * \param[in] condition_function The condition function that needs to hold for clustering
144  */
145  inline void
146  setConditionFunction (bool (*condition_function) (const PointT&, const PointT&, float))
147  {
148  condition_function_ = condition_function;
149  }
150 
151  /** \brief Set the condition that needs to hold for neighboring points to be considered part of the same cluster.
152  * This is an overloaded function provided for convenience. See the documentation for setConditionFunction(). */
153  inline void
154  setConditionFunction (std::function<bool (const PointT&, const PointT&, float)> condition_function)
155  {
156  condition_function_ = condition_function;
157  }
158 
159  /** \brief Set the spatial tolerance for new cluster candidates.
160  * \details Any two points within this distance from one another will need to evaluate a certain condition in order to be made part of the same cluster.
161  * The condition can be set using setConditionFunction().
162  * \param[in] cluster_tolerance The distance to scan for cluster candidates (default = 0.0)
163  */
164  inline void
165  setClusterTolerance (float cluster_tolerance)
166  {
167  cluster_tolerance_ = cluster_tolerance;
168  }
169 
170  /** \brief Get the spatial tolerance for new cluster candidates.*/
171  inline float
173  {
174  return (cluster_tolerance_);
175  }
176 
177  /** \brief Set the minimum number of points that a cluster needs to contain in order to be considered valid.
178  * \param[in] min_cluster_size The minimum cluster size (default = 1)
179  */
180  inline void
181  setMinClusterSize (int min_cluster_size)
182  {
183  min_cluster_size_ = min_cluster_size;
184  }
185 
186  /** \brief Get the minimum number of points that a cluster needs to contain in order to be considered valid.*/
187  inline int
189  {
190  return (min_cluster_size_);
191  }
192 
193  /** \brief Set the maximum number of points that a cluster needs to contain in order to be considered valid.
194  * \param[in] max_cluster_size The maximum cluster size (default = unlimited)
195  */
196  inline void
197  setMaxClusterSize (int max_cluster_size)
198  {
199  max_cluster_size_ = max_cluster_size;
200  }
201 
202  /** \brief Get the maximum number of points that a cluster needs to contain in order to be considered valid.*/
203  inline int
205  {
206  return (max_cluster_size_);
207  }
208 
209  /** \brief Segment the input into separate clusters.
210  * \details The input can be set using setInputCloud() and setIndices().
211  * <br>
212  * The size constraints for the resulting clusters can be set using setMinClusterSize() and setMaxClusterSize().
213  * <br>
214  * The region growing parameters can be set using setConditionFunction() and setClusterTolerance().
215  * <br>
216  * \param[out] clusters The resultant set of indices, indexing the points of the input cloud that correspond to the clusters
217  */
218  void
219  segment (IndicesClusters &clusters);
220 
221  /** \brief Get the clusters that are invalidated due to size constraints.
222  * \note The constructor of this class needs to be initialized with true, and the segment method needs to have been called prior to using this method.
223  * \param[out] small_clusters The resultant clusters that contain less than min_cluster_size points
224  * \param[out] large_clusters The resultant clusters that contain more than max_cluster_size points
225  */
226  inline void
227  getRemovedClusters (IndicesClustersPtr &small_clusters, IndicesClustersPtr &large_clusters)
228  {
229  if (!extract_removed_clusters_)
230  {
231  PCL_WARN("[pcl::ConditionalEuclideanClustering::getRemovedClusters] You need to set extract_removed_clusters to true (in this class' constructor) if you want to use this functionality.\n");
232  return;
233  }
234  small_clusters = small_clusters_;
235  large_clusters = large_clusters_;
236  }
237 
238  private:
239  /** \brief A pointer to the spatial search object */
240  SearcherPtr searcher_;
241 
242  /** \brief The condition function that needs to hold for clustering */
243  std::function<bool (const PointT&, const PointT&, float)> condition_function_;
244 
245  /** \brief The distance to scan for cluster candidates (default = 0.0) */
246  float cluster_tolerance_;
247 
248  /** \brief The minimum cluster size (default = 1) */
249  int min_cluster_size_;
250 
251  /** \brief The maximum cluster size (default = unlimited) */
252  int max_cluster_size_;
253 
254  /** \brief Set to true if you want to be able to extract the clusters that are too large or too small (default = false) */
255  bool extract_removed_clusters_;
256 
257  /** \brief The resultant clusters that contain less than min_cluster_size points */
258  pcl::IndicesClustersPtr small_clusters_;
259 
260  /** \brief The resultant clusters that contain more than max_cluster_size points */
261  pcl::IndicesClustersPtr large_clusters_;
262 
263  public:
265  };
266 }
267 
268 #ifdef PCL_NO_PRECOMPILE
269 #include <pcl/segmentation/impl/conditional_euclidean_clustering.hpp>
270 #endif
ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined c...
int getMaxClusterSize()
Get the maximum number of points that a cluster needs to contain in order to be considered valid.
void setMinClusterSize(int min_cluster_size)
Set the minimum number of points that a cluster needs to contain in order to be considered valid.
void setSearchMethod(const SearcherPtr &tree)
Provide a pointer to the search object.
void setConditionFunction(std::function< bool(const PointT &, const PointT &, float)> condition_function)
Set the condition that needs to hold for neighboring points to be considered part of the same cluster...
typename pcl::search::Search< PointT >::Ptr SearcherPtr
float getClusterTolerance()
Get the spatial tolerance for new cluster candidates.
void setConditionFunction(bool(*condition_function)(const PointT &, const PointT &, float))
Set the condition that needs to hold for neighboring points to be considered part of the same cluster...
void segment(IndicesClusters &clusters)
Segment the input into separate clusters.
void setMaxClusterSize(int max_cluster_size)
Set the maximum number of points that a cluster needs to contain in order to be considered valid.
const SearcherPtr & getSearchMethod() const
Get a pointer to the search method used.
void setClusterTolerance(float cluster_tolerance)
Set the spatial tolerance for new cluster candidates.
int getMinClusterSize()
Get the minimum number of points that a cluster needs to contain in order to be considered valid.
void getRemovedClusters(IndicesClustersPtr &small_clusters, IndicesClustersPtr &large_clusters)
Get the clusters that are invalidated due to size constraints.
ConditionalEuclideanClustering(bool extract_removed_clusters=false)
Constructor.
PCL base class.
Definition: pcl_base.h:70
shared_ptr< pcl::search::Search< PointT > > Ptr
Definition: search.h:81
#define PCL_MAKE_ALIGNED_OPERATOR_NEW
Macro to signal a class requires a custom allocator.
Definition: memory.h:63
Defines functions, macros and traits for allocating and using memory.
shared_ptr< std::vector< pcl::PointIndices > > IndicesClustersPtr
std::vector< pcl::PointIndices > IndicesClusters
Defines all the PCL and non-PCL macros used.
A point structure representing Euclidean xyz coordinates, and the RGB color.