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Applying clang-format on the files touched
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‎segmentation/include/pcl/segmentation/extract_labeled_clusters.h

Lines changed: 204 additions & 162 deletions
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@@ -35,175 +35,217 @@
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#pragma once
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#include <pcl/search/pcl_search.h>
3839
#include <pcl/pcl_base.h>
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#include <pcl/search/search.h> // for Search
4040

41-
namespace pcl
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{
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namespace pcl {
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/** \brief Decompose a region of space into clusters based on the Euclidean distance
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* between points \param[in] cloud the point cloud message \param[in] tree the spatial
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* locator (e.g., kd-tree) used for nearest neighbors searching \note the tree has to be
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* created as a spatial locator on \a cloud \param[in] tolerance the spatial cluster
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* tolerance as a measure in L2 Euclidean space \param[out] labeled_clusters the
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* resultant clusters containing point indices (as a vector of PointIndices) \param[in]
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* min_pts_per_cluster minimum number of points that a cluster may contain (default: 1)
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* \param[in] max_pts_per_cluster maximum number of points that a cluster may contain
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* (default: max int) \param[in] max_label \ingroup segmentation
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*/
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template <typename PointT>
54+
PCL_DEPRECATED(1, 14, "Use of max_label is deprecated")
55+
void extractLabeledEuclideanClusters(
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const PointCloud<PointT>& cloud,
57+
const typename search::Search<PointT>::Ptr& tree,
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float tolerance,
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std::vector<std::vector<PointIndices>>& labeled_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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unsigned int max_label);
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/** \brief Decompose a region of space into clusters based on the Euclidean distance
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* between points \param[in] cloud the point cloud message \param[in] tree the spatial
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* locator (e.g., kd-tree) used for nearest neighbors searching \note the tree has to be
67+
* created as a spatial locator on \a cloud \param[in] tolerance the spatial cluster
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* tolerance as a measure in L2 Euclidean space \param[out] labeled_clusters the
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* resultant clusters containing point indices (as a vector of PointIndices) \param[in]
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* min_pts_per_cluster minimum number of points that a cluster may contain (default: 1)
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* \param[in] max_pts_per_cluster maximum number of points that a cluster may contain
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* (default: max int) \ingroup segmentation
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*/
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template <typename PointT>
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void
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extractLabeledEuclideanClusters(
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const PointCloud<PointT>& cloud,
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const typename search::Search<PointT>::Ptr& tree,
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float tolerance,
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std::vector<std::vector<PointIndices>>& labeled_clusters,
81+
unsigned int min_pts_per_cluster = 1,
82+
unsigned int max_pts_per_cluster = std::numeric_limits<unsigned int>::max());
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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/** \brief @b LabeledEuclideanClusterExtraction represents a segmentation class for
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* cluster extraction in an Euclidean sense, with label info. \author Koen Buys \ingroup
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* segmentation
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*/
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template <typename PointT>
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class LabeledEuclideanClusterExtraction : public PCLBase<PointT> {
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using BasePCLBase = PCLBase<PointT>;
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public:
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using PointCloud = pcl::PointCloud<PointT>;
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using PointCloudPtr = typename PointCloud::Ptr;
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using PointCloudConstPtr = typename PointCloud::ConstPtr;
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100+
using KdTree = pcl::search::Search<PointT>;
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using KdTreePtr = typename KdTree::Ptr;
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103+
using PointIndicesPtr = PointIndices::Ptr;
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using PointIndicesConstPtr = PointIndices::ConstPtr;
105+
43106
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
44-
/** \brief Decompose a region of space into clusters based on the Euclidean distance between points
45-
* \param[in] cloud the point cloud message
46-
* \param[in] tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching
47-
* \note the tree has to be created as a spatial locator on \a cloud
48-
* \param[in] tolerance the spatial cluster tolerance as a measure in L2 Euclidean space
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* \param[out] labeled_clusters the resultant clusters containing point indices (as a vector of PointIndices)
50-
* \param[in] min_pts_per_cluster minimum number of points that a cluster may contain (default: 1)
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* \param[in] max_pts_per_cluster maximum number of points that a cluster may contain (default: max int)
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* \param[in] max_label
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* \ingroup segmentation
54-
*/
55-
template <typename PointT>
56-
PCL_DEPRECATED(1, 14, "Use of max_label is deprecated")
57-
void
58-
extractLabeledEuclideanClusters (
59-
const PointCloud<PointT> &cloud, const typename search::Search<PointT>::Ptr &tree,
60-
float tolerance, std::vector<std::vector<PointIndices> > &labeled_clusters,
61-
unsigned int min_pts_per_cluster, unsigned int max_pts_per_cluster,
62-
unsigned int max_label);
63-
64-
/** \brief Decompose a region of space into clusters based on the Euclidean distance between points
65-
* \param[in] cloud the point cloud message
66-
* \param[in] tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching
67-
* \note the tree has to be created as a spatial locator on \a cloud
68-
* \param[in] tolerance the spatial cluster tolerance as a measure in L2 Euclidean space
69-
* \param[out] labeled_clusters the resultant clusters containing point indices (as a vector of PointIndices)
70-
* \param[in] min_pts_per_cluster minimum number of points that a cluster may contain (default: 1)
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* \param[in] max_pts_per_cluster maximum number of points that a cluster may contain (default: max int)
72-
* \ingroup segmentation
73-
*/
74-
template <typename PointT> void
75-
extractLabeledEuclideanClusters (
76-
const PointCloud<PointT> &cloud, const typename search::Search<PointT>::Ptr &tree,
77-
float tolerance, std::vector<std::vector<PointIndices> > &labeled_clusters,
78-
unsigned int min_pts_per_cluster = 1, unsigned int max_pts_per_cluster = std::numeric_limits<unsigned int>::max ());
79-
80-
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
81-
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
82-
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
83-
/** \brief @b LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info.
84-
* \author Koen Buys
85-
* \ingroup segmentation
86-
*/
87-
template <typename PointT>
88-
class LabeledEuclideanClusterExtraction: public PCLBase<PointT>
107+
/** \brief Empty constructor. */
108+
LabeledEuclideanClusterExtraction()
109+
: tree_()
110+
, cluster_tolerance_(0)
111+
, min_pts_per_cluster_(1)
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, max_pts_per_cluster_(std::numeric_limits<int>::max())
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, max_label_(std::numeric_limits<int>::max()){};
114+
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/** \brief Provide a pointer to the search object.
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* \param[in] tree a pointer to the spatial search object.
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*/
118+
inline void
119+
setSearchMethod(const KdTreePtr& tree)
89120
{
90-
using BasePCLBase = PCLBase<PointT>;
91-
92-
public:
93-
using PointCloud = pcl::PointCloud<PointT>;
94-
using PointCloudPtr = typename PointCloud::Ptr;
95-
using PointCloudConstPtr = typename PointCloud::ConstPtr;
96-
97-
using KdTree = pcl::search::Search<PointT>;
98-
using KdTreePtr = typename KdTree::Ptr;
99-
100-
using PointIndicesPtr = PointIndices::Ptr;
101-
using PointIndicesConstPtr = PointIndices::ConstPtr;
102-
103-
//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
104-
/** \brief Empty constructor. */
105-
LabeledEuclideanClusterExtraction () :
106-
tree_ (),
107-
cluster_tolerance_ (0),
108-
min_pts_per_cluster_ (1),
109-
max_pts_per_cluster_ (std::numeric_limits<int>::max ()),
110-
max_label_ (std::numeric_limits<int>::max ())
111-
{};
112-
113-
/** \brief Provide a pointer to the search object.
114-
* \param[in] tree a pointer to the spatial search object.
115-
*/
116-
inline void
117-
setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
118-
119-
/** \brief Get a pointer to the search method used. */
120-
inline KdTreePtr
121-
getSearchMethod () const { return (tree_); }
122-
123-
/** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
124-
* \param[in] tolerance the spatial cluster tolerance as a measure in the L2 Euclidean space
125-
*/
126-
inline void
127-
setClusterTolerance (double tolerance) { cluster_tolerance_ = tolerance; }
128-
129-
/** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space. */
130-
inline double
131-
getClusterTolerance () const { return (cluster_tolerance_); }
132-
133-
/** \brief Set the minimum number of points that a cluster needs to contain in order to be considered valid.
134-
* \param[in] min_cluster_size the minimum cluster size
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*/
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inline void
137-
setMinClusterSize (int min_cluster_size) { min_pts_per_cluster_ = min_cluster_size; }
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139-
/** \brief Get the minimum number of points that a cluster needs to contain in order to be considered valid. */
140-
inline int
141-
getMinClusterSize () const { return (min_pts_per_cluster_); }
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143-
/** \brief Set the maximum number of points that a cluster needs to contain in order to be considered valid.
144-
* \param[in] max_cluster_size the maximum cluster size
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*/
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inline void
147-
setMaxClusterSize (int max_cluster_size) { max_pts_per_cluster_ = max_cluster_size; }
148-
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/** \brief Get the maximum number of points that a cluster needs to contain in order to be considered valid. */
150-
inline int
151-
getMaxClusterSize () const { return (max_pts_per_cluster_); }
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153-
/** \brief Set the maximum number of labels in the cloud.
154-
* \param[in] max_label the maximum
155-
*/
156-
PCL_DEPRECATED(1, 14, "Max label is being deprecated")
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inline void
158-
setMaxLabels (unsigned int max_label) { max_label_ = max_label; }
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/** \brief Get the maximum number of labels */
161-
PCL_DEPRECATED(1, 14, "Max label is being deprecated")
162-
inline unsigned int
163-
getMaxLabels () const { return (max_label_); }
164-
165-
/** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
166-
* \param[out] labeled_clusters the resultant point clusters
167-
*/
168-
void
169-
extract (std::vector<std::vector<PointIndices> > &labeled_clusters);
170-
171-
protected:
172-
// Members derived from the base class
173-
using BasePCLBase::input_;
174-
using BasePCLBase::indices_;
175-
using BasePCLBase::initCompute;
176-
using BasePCLBase::deinitCompute;
177-
178-
/** \brief A pointer to the spatial search object. */
179-
KdTreePtr tree_;
180-
181-
/** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
182-
double cluster_tolerance_;
183-
184-
/** \brief The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). */
185-
int min_pts_per_cluster_;
186-
187-
/** \brief The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). */
188-
int max_pts_per_cluster_;
189-
190-
/** \brief The maximum number of labels we can find in this pointcloud (default = MAXINT)*/
191-
unsigned int max_label_;
192-
193-
/** \brief Class getName method. */
194-
virtual std::string getClassName () const { return ("LabeledEuclideanClusterExtraction"); }
195-
196-
};
197-
198-
/** \brief Sort clusters method (for std::sort).
199-
* \ingroup segmentation
200-
*/
201-
inline bool
202-
compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
121+
tree_ = tree;
122+
}
123+
124+
/** \brief Get a pointer to the search method used. */
125+
inline KdTreePtr
126+
getSearchMethod() const
203127
{
204-
return (a.indices.size () < b.indices.size ());
128+
return (tree_);
205129
}
130+
131+
/** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
132+
* \param[in] tolerance the spatial cluster tolerance as a measure in the L2 Euclidean
133+
* space
134+
*/
135+
inline void
136+
setClusterTolerance(double tolerance)
137+
{
138+
cluster_tolerance_ = tolerance;
139+
}
140+
141+
/** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
142+
*/
143+
inline double
144+
getClusterTolerance() const
145+
{
146+
return (cluster_tolerance_);
147+
}
148+
149+
/** \brief Set the minimum number of points that a cluster needs to contain in order
150+
* to be considered valid. \param[in] min_cluster_size the minimum cluster size
151+
*/
152+
inline void
153+
setMinClusterSize(int min_cluster_size)
154+
{
155+
min_pts_per_cluster_ = min_cluster_size;
156+
}
157+
158+
/** \brief Get the minimum number of points that a cluster needs to contain in order
159+
* to be considered valid. */
160+
inline int
161+
getMinClusterSize() const
162+
{
163+
return (min_pts_per_cluster_);
164+
}
165+
166+
/** \brief Set the maximum number of points that a cluster needs to contain in order
167+
* to be considered valid. \param[in] max_cluster_size the maximum cluster size
168+
*/
169+
inline void
170+
setMaxClusterSize(int max_cluster_size)
171+
{
172+
max_pts_per_cluster_ = max_cluster_size;
173+
}
174+
175+
/** \brief Get the maximum number of points that a cluster needs to contain in order
176+
* to be considered valid. */
177+
inline int
178+
getMaxClusterSize() const
179+
{
180+
return (max_pts_per_cluster_);
181+
}
182+
183+
/** \brief Set the maximum number of labels in the cloud.
184+
* \param[in] max_label the maximum
185+
*/
186+
PCL_DEPRECATED(1, 14, "Max label is being deprecated")
187+
inline void
188+
setMaxLabels(unsigned int max_label)
189+
{
190+
max_label_ = max_label;
191+
}
192+
193+
/** \brief Get the maximum number of labels */
194+
PCL_DEPRECATED(1, 14, "Max label is being deprecated")
195+
inline unsigned int
196+
getMaxLabels() const
197+
{
198+
return (max_label_);
199+
}
200+
201+
/** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices
202+
* ()> \param[out] labeled_clusters the resultant point clusters
203+
*/
204+
void
205+
extract(std::vector<std::vector<PointIndices>>& labeled_clusters);
206+
207+
protected:
208+
// Members derived from the base class
209+
using BasePCLBase::deinitCompute;
210+
using BasePCLBase::indices_;
211+
using BasePCLBase::initCompute;
212+
using BasePCLBase::input_;
213+
214+
/** \brief A pointer to the spatial search object. */
215+
KdTreePtr tree_;
216+
217+
/** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
218+
double cluster_tolerance_;
219+
220+
/** \brief The minimum number of points that a cluster needs to contain in order to be
221+
* considered valid (default = 1). */
222+
int min_pts_per_cluster_;
223+
224+
/** \brief The maximum number of points that a cluster needs to contain in order to be
225+
* considered valid (default = MAXINT). */
226+
int max_pts_per_cluster_;
227+
228+
/** \brief The maximum number of labels we can find in this pointcloud (default =
229+
* MAXINT)*/
230+
unsigned int max_label_;
231+
232+
/** \brief Class getName method. */
233+
virtual std::string
234+
getClassName() const
235+
{
236+
return ("LabeledEuclideanClusterExtraction");
237+
}
238+
};
239+
240+
/** \brief Sort clusters method (for std::sort).
241+
* \ingroup segmentation
242+
*/
243+
inline bool
244+
compareLabeledPointClusters(const pcl::PointIndices& a, const pcl::PointIndices& b)
245+
{
246+
return (a.indices.size() < b.indices.size());
206247
}
248+
} // namespace pcl
207249

208250
#ifdef PCL_NO_PRECOMPILE
209251
#include <pcl/segmentation/impl/extract_labeled_clusters.hpp>

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