Point Cloud Library (PCL)
1.7.0
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IN NO EVENT SHALL THE 00025 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00026 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00027 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00028 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00029 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00030 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00031 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00032 * POSSIBILITY OF SUCH DAMAGE. 00033 * 00034 */ 00035 00036 #ifndef PCL_EXTRACT_LABELED_CLUSTERS_H_ 00037 #define PCL_EXTRACT_LABELED_CLUSTERS_H_ 00038 00039 #include <pcl/pcl_base.h> 00040 #include <pcl/search/pcl_search.h> 00041 00042 namespace pcl 00043 { 00044 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00045 /** \brief Decompose a region of space into clusters based on the Euclidean distance between points 00046 * \param[in] cloud the point cloud message 00047 * \param[in] tree the spatial locator (e.g., kd-tree) used for nearest neighbors searching 00048 * \note the tree has to be created as a spatial locator on \a cloud 00049 * \param[in] tolerance the spatial cluster tolerance as a measure in L2 Euclidean space 00050 * \param[out] labeled_clusters the resultant clusters containing point indices (as a vector of PointIndices) 00051 * \param[in] min_pts_per_cluster minimum number of points that a cluster may contain (default: 1) 00052 * \param[in] max_pts_per_cluster maximum number of points that a cluster may contain (default: max int) 00053 * \param[in] max_label 00054 * \ingroup segmentation 00055 */ 00056 template <typename PointT> void 00057 extractLabeledEuclideanClusters ( 00058 const PointCloud<PointT> &cloud, const boost::shared_ptr<search::Search<PointT> > &tree, 00059 float tolerance, std::vector<std::vector<PointIndices> > &labeled_clusters, 00060 unsigned int min_pts_per_cluster = 1, unsigned int max_pts_per_cluster = std::numeric_limits<unsigned int>::max (), 00061 unsigned int max_label = std::numeric_limits<unsigned int>::max ()); 00062 00063 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00064 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00065 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00066 /** \brief @b LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info. 00067 * \author Koen Buys 00068 * \ingroup segmentation 00069 */ 00070 template <typename PointT> 00071 class LabeledEuclideanClusterExtraction: public PCLBase<PointT> 00072 { 00073 typedef PCLBase<PointT> BasePCLBase; 00074 00075 public: 00076 typedef pcl::PointCloud<PointT> PointCloud; 00077 typedef typename PointCloud::Ptr PointCloudPtr; 00078 typedef typename PointCloud::ConstPtr PointCloudConstPtr; 00079 00080 typedef typename pcl::search::Search<PointT> KdTree; 00081 typedef typename pcl::search::Search<PointT>::Ptr KdTreePtr; 00082 00083 typedef PointIndices::Ptr PointIndicesPtr; 00084 typedef PointIndices::ConstPtr PointIndicesConstPtr; 00085 00086 ////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 00087 /** \brief Empty constructor. */ 00088 LabeledEuclideanClusterExtraction () : 00089 tree_ (), 00090 cluster_tolerance_ (0), 00091 min_pts_per_cluster_ (1), 00092 max_pts_per_cluster_ (std::numeric_limits<int>::max ()), 00093 max_label_ (std::numeric_limits<int>::max ()) 00094 {}; 00095 00096 /** \brief Provide a pointer to the search object. 00097 * \param[in] tree a pointer to the spatial search object. 00098 */ 00099 inline void 00100 setSearchMethod (const KdTreePtr &tree) { tree_ = tree; } 00101 00102 /** \brief Get a pointer to the search method used. */ 00103 inline KdTreePtr 00104 getSearchMethod () const { return (tree_); } 00105 00106 /** \brief Set the spatial cluster tolerance as a measure in the L2 Euclidean space 00107 * \param[in] tolerance the spatial cluster tolerance as a measure in the L2 Euclidean space 00108 */ 00109 inline void 00110 setClusterTolerance (double tolerance) { cluster_tolerance_ = tolerance; } 00111 00112 /** \brief Get the spatial cluster tolerance as a measure in the L2 Euclidean space. */ 00113 inline double 00114 getClusterTolerance () const { return (cluster_tolerance_); } 00115 00116 /** \brief Set the minimum number of points that a cluster needs to contain in order to be considered valid. 00117 * \param[in] min_cluster_size the minimum cluster size 00118 */ 00119 inline void 00120 setMinClusterSize (int min_cluster_size) { min_pts_per_cluster_ = min_cluster_size; } 00121 00122 /** \brief Get the minimum number of points that a cluster needs to contain in order to be considered valid. */ 00123 inline int 00124 getMinClusterSize () const { return (min_pts_per_cluster_); } 00125 00126 /** \brief Set the maximum number of points that a cluster needs to contain in order to be considered valid. 00127 * \param[in] max_cluster_size the maximum cluster size 00128 */ 00129 inline void 00130 setMaxClusterSize (int max_cluster_size) { max_pts_per_cluster_ = max_cluster_size; } 00131 00132 /** \brief Get the maximum number of points that a cluster needs to contain in order to be considered valid. */ 00133 inline int 00134 getMaxClusterSize () const { return (max_pts_per_cluster_); } 00135 00136 /** \brief Set the maximum number of labels in the cloud. 00137 * \param[in] max_label the maximum 00138 */ 00139 inline void 00140 setMaxLabels (unsigned int max_label) { max_label_ = max_label; } 00141 00142 /** \brief Get the maximum number of labels */ 00143 inline unsigned int 00144 getMaxLabels () const { return (max_label_); } 00145 00146 /** \brief Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()> 00147 * \param[out] labeled_clusters the resultant point clusters 00148 */ 00149 void 00150 extract (std::vector<std::vector<PointIndices> > &labeled_clusters); 00151 00152 protected: 00153 // Members derived from the base class 00154 using BasePCLBase::input_; 00155 using BasePCLBase::indices_; 00156 using BasePCLBase::initCompute; 00157 using BasePCLBase::deinitCompute; 00158 00159 /** \brief A pointer to the spatial search object. */ 00160 KdTreePtr tree_; 00161 00162 /** \brief The spatial cluster tolerance as a measure in the L2 Euclidean space. */ 00163 double cluster_tolerance_; 00164 00165 /** \brief The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1). */ 00166 int min_pts_per_cluster_; 00167 00168 /** \brief The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT). */ 00169 int max_pts_per_cluster_; 00170 00171 /** \brief The maximum number of labels we can find in this pointcloud (default = MAXINT)*/ 00172 unsigned int max_label_; 00173 00174 /** \brief Class getName method. */ 00175 virtual std::string getClassName () const { return ("LabeledEuclideanClusterExtraction"); } 00176 00177 }; 00178 00179 /** \brief Sort clusters method (for std::sort). 00180 * \ingroup segmentation 00181 */ 00182 inline bool 00183 compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b) 00184 { 00185 return (a.indices.size () < b.indices.size ()); 00186 } 00187 } 00188 00189 #ifdef PCL_NO_PRECOMPILE 00190 #include <pcl/segmentation/impl/extract_labeled_clusters.hpp> 00191 #endif 00192 00193 #endif //#ifndef PCL_EXTRACT_LABELED_CLUSTERS_H_