io.hpp

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#ifndef PCL_KDTREE_IO_IMPL_HPP_
#define PCL_KDTREE_IO_IMPL_HPP_
 
#include <pcl/kdtree/io.h>
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename Point1T, typename Point2T> void
pcl::getApproximateIndices (
    const typename pcl::PointCloud<Point1T>::ConstPtr &cloud_in,
    const typename pcl::PointCloud<Point2T>::ConstPtr &cloud_ref,
    Indices &indices)
{
  pcl::KdTreeFLANN<Point2T> tree;
  tree.setInputCloud (cloud_ref);
 
  Indices nn_idx (1);
  std::vector<float> nn_dists (1);
  indices.resize (cloud_in->size ());
  for (std::size_t i = 0; i < cloud_in->size (); ++i)
  {
    tree.nearestKSearchT ((*cloud_in)[i], 1, nn_idx, nn_dists);
    indices[i] = nn_idx[0];
  }
}
 
//////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointT> void
pcl::getApproximateIndices (
    const typename pcl::PointCloud<PointT>::ConstPtr &cloud_in,
    const typename pcl::PointCloud<PointT>::ConstPtr &cloud_ref,
    Indices &indices)
{
  pcl::KdTreeFLANN<PointT> tree;
  tree.setInputCloud (cloud_ref);
 
  Indices nn_idx (1);
  std::vector<float> nn_dists (1);
  indices.resize (cloud_in->size ());
  for (std::size_t i = 0; i < cloud_in->size (); ++i)
  {
    tree.nearestKSearch (*cloud_in, i, 1, nn_idx, nn_dists);
    indices[i] = nn_idx[0];
  }
}
 
#endif // PCL_KDTREE_IO_IMPL_H_