Point Cloud Library (PCL)  1.3.1
kdtree.h
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00001 /*
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00036  * $Id: kdtree.h 3015 2011-11-01 02:47:42Z svn $
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00038 
00039 #ifndef PCL_SEARCH_KDTREE_H_
00040 #define PCL_SEARCH_KDTREE_H_
00041 
00042 #include <pcl/search/search.h>
00043 #include <pcl/kdtree/kdtree.h>
00044 #include <pcl/kdtree/kdtree_flann.h>
00045 
00046 namespace pcl
00047 {
00048   namespace search
00049   {
00058     template<typename PointT>
00059     class KdTree: public Search<PointT>
00060     {
00061       typedef typename Search<PointT>::PointCloud PointCloud;
00062       typedef typename Search<PointT>::PointCloudConstPtr PointCloudConstPtr;
00063 
00064       typedef boost::shared_ptr<std::vector<int> > IndicesPtr;
00065       typedef boost::shared_ptr<const std::vector<int> > IndicesConstPtr;
00066 
00067       public:
00068         typedef boost::shared_ptr<KdTree<PointT> > Ptr;
00069         typedef boost::shared_ptr<const KdTree<PointT> > ConstPtr;
00070 
00071         typedef boost::shared_ptr<pcl::KdTreeFLANN<PointT> > KdTreeFLANNPtr;
00072         typedef boost::shared_ptr<const pcl::KdTreeFLANN<PointT> > KdTreeFLANNConstPtr;
00073 
00081         KdTree (bool sorted = true)
00082         {
00083           tree_.reset (new pcl::KdTreeFLANN<PointT> (sorted));
00084         }
00085 
00087         virtual
00088         ~KdTree ()
00089         {
00090         }
00091 
00095         inline void
00096         setEpsilon (double eps)
00097         {
00098           tree_->setEpsilon (eps);
00099         }
00100 
00102         inline double
00103         getEpsilon ()
00104         {
00105           return (tree_->getEpsilon ());
00106         }
00107 
00112         inline void
00113         setInputCloud (const PointCloudConstPtr& cloud, const IndicesConstPtr& indices)
00114         {
00115           tree_->setInputCloud (cloud, indices);
00116         }
00117 
00121         inline void
00122         setInputCloud (const PointCloudConstPtr& cloud)
00123         {
00124           const IndicesConstPtr& indices = IndicesConstPtr ();
00125           setInputCloud (cloud, indices);
00126         }
00127 
00129         PointCloudConstPtr
00130         getInputCloud ()
00131         {
00132           return (tree_->getInputCloud ());
00133         }
00134 
00136         virtual IndicesConstPtr const
00137         getIndices ()
00138         {
00139           return (tree_->getIndices ());
00140         }
00141 
00150         int
00151         nearestKSearch (const PointT &point, int k, std::vector<int> &k_indices, std::vector<float> &k_distances)
00152         {
00153           return (tree_->nearestKSearch (point, k, k_indices, k_distances));
00154         }
00155 
00165         inline int
00166         nearestKSearch (const PointCloud &cloud, int index, int k, std::vector<int> &k_indices,
00167                         std::vector<float> &k_distances)
00168         {
00169           return (tree_->nearestKSearch (cloud, index, k, k_indices, k_distances));
00170         }
00171 
00183         inline int
00184         nearestKSearch (int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances)
00185         {
00186           return (tree_->nearestKSearch (index, k, k_indices, k_distances));
00187         }
00188 
00197         int
00198         radiusSearch (const PointT& point, double radius, 
00199                       std::vector<int> &k_indices, std::vector<float> &k_sqr_distances,
00200                       int max_nn = -1) const
00201         {
00202           return (tree_->radiusSearch (point, radius, k_indices, k_sqr_distances, max_nn));
00203         }
00204 
00214         inline int
00215         radiusSearch (const PointCloud& cloud, int index, double radius, std::vector<int> &k_indices,
00216                       std::vector<float> &k_distances, int max_nn = -1)
00217         {
00218           return (tree_->radiusSearch (cloud, index, radius, k_indices, k_distances, max_nn));
00219         }
00220 
00230         inline int
00231         radiusSearch (int index, double radius, std::vector<int> &k_indices, std::vector<float> &k_distances,
00232                       int max_nn = -1) const
00233         {
00234           return (tree_->radiusSearch (index, radius, k_indices, k_distances, max_nn));
00235         }
00236 
00237       protected:
00239         KdTreeFLANNPtr tree_;
00240     };
00241   }
00242 }
00243 
00244 #define PCL_INSTANTIATE_KdTree(T) template class PCL_EXPORTS pcl::search::KdTree<T>;
00245 
00246 #endif    // PCL_SEARCH_KDTREE_H_
00247 
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