349 lines
14 KiB
C++
349 lines
14 KiB
C++
/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of the copyright holder(s) nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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* Author : Sergey Ushakov
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* Email : mine_all_mine@bk.ru
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*
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*/
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#pragma once
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#include <pcl/memory.h>
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#include <pcl/pcl_base.h>
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#include <pcl/pcl_macros.h>
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#include <pcl/search/search.h>
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#include <pcl/point_cloud.h>
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#include <pcl/point_types.h>
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namespace pcl
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{
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/** \brief
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* Implements the well known Region Growing algorithm used for segmentation.
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* Description can be found in the article
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* "Segmentation of point clouds using smoothness constraint"
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* by T. Rabbania, F. A. van den Heuvelb, G. Vosselmanc.
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* In addition to residual test, the possibility to test curvature is added.
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* \ingroup segmentation
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*/
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template <typename PointT, typename NormalT>
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class PCL_EXPORTS RegionGrowing : public pcl::PCLBase<PointT>
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{
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public:
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using KdTree = pcl::search::Search<PointT>;
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using KdTreePtr = typename KdTree::Ptr;
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using Normal = pcl::PointCloud<NormalT>;
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using NormalPtr = typename Normal::Ptr;
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using PointCloud = pcl::PointCloud<PointT>;
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using PCLBase <PointT>::input_;
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using PCLBase <PointT>::indices_;
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using PCLBase <PointT>::initCompute;
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using PCLBase <PointT>::deinitCompute;
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public:
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/** \brief Constructor that sets default values for member variables. */
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RegionGrowing ();
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/** \brief This destructor destroys the cloud, normals and search method used for
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* finding KNN. In other words it frees memory.
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*/
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~RegionGrowing ();
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/** \brief Get the minimum number of points that a cluster needs to contain in order to be considered valid. */
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pcl::uindex_t
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getMinClusterSize ();
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/** \brief Set the minimum number of points that a cluster needs to contain in order to be considered valid. */
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void
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setMinClusterSize (pcl::uindex_t min_cluster_size);
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/** \brief Get the maximum number of points that a cluster needs to contain in order to be considered valid. */
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pcl::uindex_t
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getMaxClusterSize ();
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/** \brief Set the maximum number of points that a cluster needs to contain in order to be considered valid. */
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void
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setMaxClusterSize (pcl::uindex_t max_cluster_size);
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/** \brief Returns the flag value. This flag signalizes which mode of algorithm will be used.
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* If it is set to true than it will work as said in the article. This means that
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* it will be testing the angle between normal of the current point and it's neighbours normal.
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* Otherwise, it will be testing the angle between normal of the current point
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* and normal of the initial point that was chosen for growing new segment.
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*/
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bool
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getSmoothModeFlag () const;
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/** \brief This function allows to turn on/off the smoothness constraint.
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* \param[in] value new mode value, if set to true then the smooth version will be used.
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*/
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void
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setSmoothModeFlag (bool value);
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/** \brief Returns the flag that signalize if the curvature test is turned on/off. */
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bool
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getCurvatureTestFlag () const;
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/** \brief Allows to turn on/off the curvature test. Note that at least one test
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* (residual or curvature) must be turned on. If you are turning curvature test off
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* then residual test will be turned on automatically.
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* \param[in] value new value for curvature test. If set to true then the test will be turned on
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*/
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virtual void
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setCurvatureTestFlag (bool value);
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/** \brief Returns the flag that signalize if the residual test is turned on/off. */
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bool
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getResidualTestFlag () const;
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/** \brief
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* Allows to turn on/off the residual test. Note that at least one test
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* (residual or curvature) must be turned on. If you are turning residual test off
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* then curvature test will be turned on automatically.
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* \param[in] value new value for residual test. If set to true then the test will be turned on
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*/
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virtual void
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setResidualTestFlag (bool value);
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/** \brief Returns smoothness threshold. */
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float
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getSmoothnessThreshold () const;
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/** \brief Allows to set smoothness threshold used for testing the points.
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* \param[in] theta new threshold value for the angle between normals
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*/
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void
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setSmoothnessThreshold (float theta);
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/** \brief Returns residual threshold. */
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float
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getResidualThreshold () const;
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/** \brief Allows to set residual threshold used for testing the points.
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* \param[in] residual new threshold value for residual testing
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*/
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void
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setResidualThreshold (float residual);
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/** \brief Returns curvature threshold. */
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float
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getCurvatureThreshold () const;
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/** \brief Allows to set curvature threshold used for testing the points.
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* \param[in] curvature new threshold value for curvature testing
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*/
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void
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setCurvatureThreshold (float curvature);
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/** \brief Returns the number of nearest neighbours used for KNN. */
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unsigned int
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getNumberOfNeighbours () const;
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/** \brief Allows to set the number of neighbours. For more information check the article.
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* \param[in] neighbour_number number of neighbours to use
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*/
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void
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setNumberOfNeighbours (unsigned int neighbour_number);
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/** \brief Returns the pointer to the search method that is used for KNN. */
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KdTreePtr
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getSearchMethod () const;
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/** \brief Allows to set search method that will be used for finding KNN.
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* \param[in] tree pointer to a KdTree
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*/
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void
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setSearchMethod (const KdTreePtr& tree);
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/** \brief Returns normals. */
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NormalPtr
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getInputNormals () const;
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/** \brief This method sets the normals. They are needed for the algorithm, so if
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* no normals will be set, the algorithm would not be able to segment the points.
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* \param[in] norm normals that will be used in the algorithm
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*/
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void
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setInputNormals (const NormalPtr& norm);
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/** \brief This method launches the segmentation algorithm and returns the clusters that were
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* obtained during the segmentation.
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* \param[out] clusters clusters that were obtained. Each cluster is an array of point indices.
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*/
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virtual void
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extract (std::vector <pcl::PointIndices>& clusters);
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/** \brief For a given point this function builds a segment to which it belongs and returns this segment.
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* \param[in] index index of the initial point which will be the seed for growing a segment.
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* \param[out] cluster cluster to which the point belongs.
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*/
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virtual void
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getSegmentFromPoint (pcl::index_t index, pcl::PointIndices& cluster);
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/** \brief If the cloud was successfully segmented, then function
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* returns colored cloud. Otherwise it returns an empty pointer.
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* Points that belong to the same segment have the same color.
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* But this function doesn't guarantee that different segments will have different
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* color(it all depends on RNG). Points that were not listed in the indices array will have red color.
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*/
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pcl::PointCloud<pcl::PointXYZRGB>::Ptr
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getColoredCloud ();
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/** \brief If the cloud was successfully segmented, then function
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* returns colored cloud. Otherwise it returns an empty pointer.
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* Points that belong to the same segment have the same color.
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* But this function doesn't guarantee that different segments will have different
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* color(it all depends on RNG). Points that were not listed in the indices array will have red color.
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*/
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pcl::PointCloud<pcl::PointXYZRGBA>::Ptr
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getColoredCloudRGBA ();
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protected:
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/** \brief This method simply checks if it is possible to execute the segmentation algorithm with
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* the current settings. If it is possible then it returns true.
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*/
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virtual bool
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prepareForSegmentation ();
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/** \brief This method finds KNN for each point and saves them to the array
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* because the algorithm needs to find KNN a few times.
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*/
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virtual void
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findPointNeighbours ();
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/** \brief This function implements the algorithm described in the article
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* "Segmentation of point clouds using smoothness constraint"
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* by T. Rabbania, F. A. van den Heuvelb, G. Vosselmanc.
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*/
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void
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applySmoothRegionGrowingAlgorithm ();
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/** \brief This method grows a segment for the given seed point. And returns the number of its points.
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* \param[in] initial_seed index of the point that will serve as the seed point
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* \param[in] segment_number indicates which number this segment will have
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*/
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int
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growRegion (int initial_seed, int segment_number);
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/** \brief This function is checking if the point with index 'nghbr' belongs to the segment.
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* If so, then it returns true. It also checks if this point can serve as the seed.
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* \param[in] initial_seed index of the initial point that was passed to the growRegion() function
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* \param[in] point index of the current seed point
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* \param[in] nghbr index of the point that is neighbour of the current seed
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* \param[out] is_a_seed this value is set to true if the point with index 'nghbr' can serve as the seed
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*/
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virtual bool
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validatePoint (pcl::index_t initial_seed, pcl::index_t point, pcl::index_t nghbr, bool& is_a_seed) const;
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/** \brief This function simply assembles the regions from list of point labels.
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* Each cluster is an array of point indices.
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*/
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void
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assembleRegions ();
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protected:
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/** \brief Stores the minimum number of points that a cluster needs to contain in order to be considered valid. */
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pcl::uindex_t min_pts_per_cluster_;
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/** \brief Stores the maximum number of points that a cluster needs to contain in order to be considered valid. */
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pcl::uindex_t max_pts_per_cluster_;
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/** \brief Flag that signalizes if the smoothness constraint will be used. */
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bool smooth_mode_flag_;
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/** \brief If set to true then curvature test will be done during segmentation. */
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bool curvature_flag_;
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/** \brief If set to true then residual test will be done during segmentation. */
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bool residual_flag_;
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/** \brief Thershold used for testing the smoothness between points. */
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float theta_threshold_;
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/** \brief Thershold used in residual test. */
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float residual_threshold_;
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/** \brief Thershold used in curvature test. */
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float curvature_threshold_;
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/** \brief Number of neighbours to find. */
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unsigned int neighbour_number_;
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/** \brief Serch method that will be used for KNN. */
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KdTreePtr search_;
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/** \brief Contains normals of the points that will be segmented. */
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NormalPtr normals_;
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/** \brief Contains neighbours of each point. */
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std::vector<pcl::Indices> point_neighbours_;
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/** \brief Point labels that tells to which segment each point belongs. */
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std::vector<int> point_labels_;
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/** \brief If set to true then normal/smoothness test will be done during segmentation.
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* It is always set to true for the usual region growing algorithm. It is used for turning on/off the test
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* for smoothness in the child class RegionGrowingRGB.*/
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bool normal_flag_;
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/** \brief Tells how much points each segment contains. Used for reserving memory. */
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std::vector<pcl::uindex_t> num_pts_in_segment_;
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/** \brief After the segmentation it will contain the segments. */
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std::vector <pcl::PointIndices> clusters_;
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/** \brief Stores the number of segments. */
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int number_of_segments_;
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public:
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PCL_MAKE_ALIGNED_OPERATOR_NEW
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};
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/** \brief This function is used as a comparator for sorting. */
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inline bool
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comparePair (std::pair<float, int> i, std::pair<float, int> j)
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{
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return (i.first < j.first);
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}
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}
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#ifdef PCL_NO_PRECOMPILE
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#include <pcl/segmentation/impl/region_growing.hpp>
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#endif
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