38 #ifndef PCL_SEGMENTATION_IMPL_EXTRACT_CLUSTERS_H_
39 #define PCL_SEGMENTATION_IMPL_EXTRACT_CLUSTERS_H_
41 #include <pcl/segmentation/extract_clusters.h>
42 #include <pcl/search/organized.h>
45 template <
typename Po
intT>
void
48 float tolerance, std::vector<PointIndices> &clusters,
49 unsigned int min_pts_per_cluster,
50 unsigned int max_pts_per_cluster)
54 PCL_ERROR(
"[pcl::extractEuclideanClusters] Tree built for a different point cloud "
55 "dataset (%zu) than the input cloud (%zu)!\n",
57 static_cast<std::size_t>(cloud.
size()));
63 std::vector<bool> processed (cloud.
size (),
false);
66 std::vector<float> nn_distances;
68 for (
int i = 0; i < static_cast<int> (cloud.
size ()); ++i)
75 seed_queue.push_back (i);
79 while (sq_idx < static_cast<int> (seed_queue.size ()))
82 if (!tree->
radiusSearch (seed_queue[sq_idx], tolerance, nn_indices, nn_distances))
88 for (std::size_t j = nn_start_idx; j < nn_indices.size (); ++j)
90 if (nn_indices[j] == UNAVAILABLE || processed[nn_indices[j]])
94 seed_queue.push_back (nn_indices[j]);
95 processed[nn_indices[j]] =
true;
102 if (seed_queue.size () >= min_pts_per_cluster && seed_queue.size () <= max_pts_per_cluster)
105 r.
indices.resize (seed_queue.size ());
106 for (std::size_t j = 0; j < seed_queue.size (); ++j)
113 clusters.push_back (r);
117 PCL_DEBUG(
"[pcl::extractEuclideanClusters] This cluster has %zu points, which is not between %u and %u points, so it is not a final cluster\n",
118 seed_queue.size (), min_pts_per_cluster, max_pts_per_cluster);
124 template <
typename Po
intT>
void
128 float tolerance, std::vector<PointIndices> &clusters,
129 unsigned int min_pts_per_cluster,
130 unsigned int max_pts_per_cluster)
135 PCL_ERROR(
"[pcl::extractEuclideanClusters] Tree built for a different point cloud "
136 "dataset (%zu) than the input cloud (%zu)!\n",
138 static_cast<std::size_t>(cloud.
size()));
141 if (tree->
getIndices()->size() != indices.size()) {
142 PCL_ERROR(
"[pcl::extractEuclideanClusters] Tree built for a different set of "
143 "indices (%zu) than the input set (%zu)!\n",
144 static_cast<std::size_t>(tree->
getIndices()->size()),
152 std::vector<bool> processed (cloud.
size (),
false);
155 std::vector<float> nn_distances;
157 for (
const auto &index : indices)
159 if (processed[index])
164 seed_queue.push_back (index);
166 processed[index] =
true;
168 while (sq_idx < static_cast<int> (seed_queue.size ()))
171 int ret = tree->
radiusSearch (cloud[seed_queue[sq_idx]], tolerance, nn_indices, nn_distances);
174 PCL_ERROR(
"[pcl::extractEuclideanClusters] Received error code -1 from radiusSearch\n");
183 for (std::size_t j = nn_start_idx; j < nn_indices.size (); ++j)
185 if (nn_indices[j] == UNAVAILABLE || processed[nn_indices[j]])
189 seed_queue.push_back (nn_indices[j]);
190 processed[nn_indices[j]] =
true;
197 if (seed_queue.size () >= min_pts_per_cluster && seed_queue.size () <= max_pts_per_cluster)
200 r.
indices.resize (seed_queue.size ());
201 for (std::size_t j = 0; j < seed_queue.size (); ++j)
209 clusters.push_back (r);
213 PCL_DEBUG(
"[pcl::extractEuclideanClusters] This cluster has %zu points, which is not between %u and %u points, so it is not a final cluster\n",
214 seed_queue.size (), min_pts_per_cluster, max_pts_per_cluster);
223 template <
typename Po
intT>
void
226 if (!initCompute () ||
227 (input_ && input_->points.empty ()) ||
228 (indices_ && indices_->empty ()))
237 if (input_->isOrganized ())
244 tree_->setInputCloud (input_, indices_);
245 extractEuclideanClusters (*input_, *indices_, tree_, static_cast<float> (cluster_tolerance_), clusters, min_pts_per_cluster_, max_pts_per_cluster_);
256 #define PCL_INSTANTIATE_EuclideanClusterExtraction(T) template class PCL_EXPORTS pcl::EuclideanClusterExtraction<T>;
257 #define PCL_INSTANTIATE_extractEuclideanClusters(T) template void PCL_EXPORTS pcl::extractEuclideanClusters<T>(const pcl::PointCloud<T> &, const typename pcl::search::Search<T>::Ptr &, float , std::vector<pcl::PointIndices> &, unsigned int, unsigned int);
258 #define PCL_INSTANTIATE_extractEuclideanClusters_indices(T) template void PCL_EXPORTS pcl::extractEuclideanClusters<T>(const pcl::PointCloud<T> &, const pcl::Indices &, const typename pcl::search::Search<T>::Ptr &, float , std::vector<pcl::PointIndices> &, unsigned int, unsigned int);
260 #endif // PCL_EXTRACT_CLUSTERS_IMPL_H_
virtual bool getSortedResults()
Gets whether the results should be sorted (ascending in the distance) or not Otherwise the results ma...
virtual int radiusSearch(const PointT &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const =0
Search for all the nearest neighbors of the query point in a given radius.
void extractEuclideanClusters(const PointCloud< PointT > &cloud, const typename search::Search< PointT >::Ptr &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
Decompose a region of space into clusters based on the Euclidean distance between points...
virtual IndicesConstPtr getIndices() const
Get a pointer to the vector of indices used.
bool comparePointClusters(const pcl::PointIndices &a, const pcl::PointIndices &b)
Sort clusters method (for std::sort).
virtual PointCloudConstPtr getInputCloud() const
Get a pointer to the input point cloud dataset.
IndicesAllocator<> Indices
Type used for indices in PCL.
PointCloud represents the base class in PCL for storing collections of 3D points. ...
pcl::PCLHeader header
The point cloud header.
OrganizedNeighbor is a class for optimized nearest neighbor search in organized projectable point clo...
shared_ptr< pcl::search::Search< PointT > > Ptr