Point Cloud Library (PCL)  1.12.1-dev
seeded_hue_segmentation.h
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38 
39 #pragma once
40 
41 #include <pcl/pcl_base.h>
42 #include <pcl/point_types_conversion.h>
43 #include <pcl/search/search.h> // for Search
44 
45 namespace pcl
46 {
47  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
48  /** \brief Decompose a region of space into clusters based on the Euclidean distance between points
49  * \param[in] cloud the point cloud message
50  * \param[in] tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching
51  * \note the tree has to be created as a spatial locator on \a cloud
52  * \param[in] tolerance the spatial cluster tolerance as a measure in L2 Euclidean space
53  * \param[in] indices_in the cluster containing the seed point indices (as a vector of PointIndices)
54  * \param[out] indices_out
55  * \param[in] delta_hue
56  * \todo look how to make this templated!
57  * \ingroup segmentation
58  */
59  void
62  float tolerance,
63  PointIndices &indices_in,
64  PointIndices &indices_out,
65  float delta_hue = 0.0);
66 
67  /** \brief Decompose a region of space into clusters based on the Euclidean distance between points
68  * \param[in] cloud the point cloud message
69  * \param[in] tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching
70  * \note the tree has to be created as a spatial locator on \a cloud
71  * \param[in] tolerance the spatial cluster tolerance as a measure in L2 Euclidean space
72  * \param[in] indices_in the cluster containing the seed point indices (as a vector of PointIndices)
73  * \param[out] indices_out
74  * \param[in] delta_hue
75  * \todo look how to make this templated!
76  * \ingroup segmentation
77  */
78  void
81  float tolerance,
82  PointIndices &indices_in,
83  PointIndices &indices_out,
84  float delta_hue = 0.0);
85 
86  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
87  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
88  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
89  /** \brief SeededHueSegmentation
90  * \author Koen Buys
91  * \ingroup segmentation
92  */
93  class SeededHueSegmentation: public PCLBase<PointXYZRGB>
94  {
96 
97  public:
101 
104 
107 
108  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
109  /** \brief Empty constructor. */
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
132 
133  /** \brief Set the tollerance on the hue
134  * \param[in] delta_hue the new delta hue
135  */
136  inline void
137  setDeltaHue (float delta_hue) { delta_hue_ = delta_hue; }
138 
139  /** \brief Get the tolerance on the hue */
140  inline float
141  getDeltaHue () const { return (delta_hue_); }
142 
143  /** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
144  * \param[in] indices_in
145  * \param[out] indices_out
146  */
147  void
148  segment (PointIndices &indices_in, PointIndices &indices_out);
149 
150  protected:
151  // Members derived from the base class
152  using BasePCLBase::input_;
153  using BasePCLBase::indices_;
156 
157  /** \brief A pointer to the spatial search object. */
159 
160  /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
162 
163  /** \brief The allowed difference on the hue*/
164  float delta_hue_;
165 
166  /** \brief Class getName method. */
167  virtual std::string getClassName () const { return ("seededHueSegmentation"); }
168  };
169 }
170 
171 #ifdef PCL_NO_PRECOMPILE
172 #include <pcl/segmentation/impl/seeded_hue_segmentation.hpp>
173 #endif
PCL base class.
Definition: pcl_base.h:70
PointCloudConstPtr input_
The input point cloud dataset.
Definition: pcl_base.h:147
IndicesPtr indices_
A pointer to the vector of point indices to use.
Definition: pcl_base.h:150
bool initCompute()
This method should get called before starting the actual computation.
Definition: pcl_base.hpp:138
bool deinitCompute()
This method should get called after finishing the actual computation.
Definition: pcl_base.hpp:174
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:413
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:414
KdTreePtr tree_
A pointer to the spatial search object.
void setSearchMethod(const KdTreePtr &tree)
Provide a pointer to the search object.
KdTreePtr getSearchMethod() const
Get a pointer to the search method used.
virtual std::string getClassName() const
Class getName method.
pcl::search::Search< PointXYZRGB >::Ptr KdTreePtr
PointCloud::ConstPtr PointCloudConstPtr
float delta_hue_
The allowed difference on the hue.
void setClusterTolerance(double tolerance)
Set the spatial cluster tolerance as a measure in the L2 Euclidean space.
float getDeltaHue() const
Get the tolerance on the hue.
double cluster_tolerance_
The spatial cluster tolerance as a measure in the L2 Euclidean space.
void setDeltaHue(float delta_hue)
Set the tollerance on the hue.
double getClusterTolerance() const
Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
void segment(PointIndices &indices_in, PointIndices &indices_out)
Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
SeededHueSegmentation()
Empty constructor.
PointIndices::ConstPtr PointIndicesConstPtr
shared_ptr< pcl::search::Search< PointXYZRGB > > Ptr
Definition: search.h:81
void seededHueSegmentation(const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGB >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)
Decompose a region of space into clusters based on the Euclidean distance between points.
shared_ptr< ::pcl::PointIndices > Ptr
Definition: PointIndices.h:13
shared_ptr< const ::pcl::PointIndices > ConstPtr
Definition: PointIndices.h:14