Point Cloud Library (PCL) 1.15.0
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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
45namespace 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 /** \brief Provide a pointer to the search object.
113 * \param[in] tree a pointer to the spatial search object.
114 */
115 inline void
116 setSearchMethod (const KdTreePtr &tree) { tree_ = tree; }
117
118 /** \brief Get a pointer to the search method used. */
119 inline KdTreePtr
120 getSearchMethod () const { return (tree_); }
121
122 /** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space
123 * \param[in] tolerance the spatial cluster tolerance as a measure in the L2 Euclidean space
124 */
125 inline void
126 setClusterTolerance (double tolerance) { cluster_tolerance_ = tolerance; }
127
128 /** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space. */
129 inline double
131
132 /** \brief Set the tolerance on the hue
133 * \param[in] delta_hue the new delta hue
134 */
135 inline void
136 setDeltaHue (float delta_hue) { delta_hue_ = delta_hue; }
137
138 /** \brief Get the tolerance on the hue */
139 inline float
140 getDeltaHue () const { return (delta_hue_); }
141
142 /** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
143 * \param[in] indices_in
144 * \param[out] indices_out
145 */
146 void
147 segment (PointIndices &indices_in, PointIndices &indices_out);
148
149 protected:
150 // Members derived from the base class
155
156 /** \brief A pointer to the spatial search object. */
157 KdTreePtr tree_{nullptr};
158
159 /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */
161
162 /** \brief The allowed difference on the hue*/
163 float delta_hue_{0.0f};
164
165 /** \brief Class getName method. */
166 virtual std::string getClassName () const { return ("seededHueSegmentation"); }
167 };
168}
169
170#ifdef PCL_NO_PRECOMPILE
171#include <pcl/segmentation/impl/seeded_hue_segmentation.hpp>
172#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:175
PointCloud represents the base class in PCL for storing collections of 3D points.
shared_ptr< PointCloud< PointT > > Ptr
shared_ptr< const PointCloud< PointT > > ConstPtr
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
pcl::PointCloud< PointXYZRGB > PointCloud
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 tolerance 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 ()>
PointIndices::ConstPtr PointIndicesConstPtr
SeededHueSegmentation()=default
Empty constructor.
shared_ptr< pcl::search::Search< PointT > > 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
shared_ptr< const ::pcl::PointIndices > ConstPtr