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C++

/*
* Software License Agreement (BSD License)
*
* Point Cloud Library (PCL) - www.pointclouds.org
* Copyright (c) 2012, Willow Garage, Inc.
* Copyright (c) 2012-, Open Perception, Inc.
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* $Id$
*/
#ifndef PCL_FEATURES_IMPL_SHOT_LRF_OMP_H_
#define PCL_FEATURES_IMPL_SHOT_LRF_OMP_H_
#include <pcl/features/shot_lrf_omp.h>
#include <pcl/features/shot_lrf.h>
//////////////////////////////////////////////////////////////////////////////////////////////
template<typename PointInT, typename PointOutT> void
pcl::SHOTLocalReferenceFrameEstimationOMP<PointInT, PointOutT>::setNumberOfThreads (unsigned int nr_threads)
{
if (nr_threads == 0)
#ifdef _OPENMP
threads_ = omp_get_num_procs();
#else
threads_ = 1;
#endif
else
threads_ = nr_threads;
}
//////////////////////////////////////////////////////////////////////////////////////////////
template<typename PointInT, typename PointOutT> void
pcl::SHOTLocalReferenceFrameEstimationOMP<PointInT, PointOutT>::computeFeature (PointCloudOut &output)
{
//check whether used with search radius or search k-neighbors
if (this->getKSearch () != 0)
{
PCL_ERROR(
"[pcl::%s::computeFeature] Error! Search method set to k-neighborhood. Call setKSearch(0) and setRadiusSearch( radius ) to use this class.\n",
getClassName().c_str ());
return;
}
tree_->setSortedResults (true);
#pragma omp parallel for \
default(none) \
shared(output) \
num_threads(threads_)
for (std::ptrdiff_t i = 0; i < static_cast<std::ptrdiff_t> (indices_->size ()); ++i)
{
// point result
Eigen::Matrix3f rf;
PointOutT& output_rf = output[i];
//output_rf.confidence = getLocalRF ((*indices_)[i], rf);
//if (output_rf.confidence == std::numeric_limits<float>::max ())
pcl::Indices n_indices;
std::vector<float> n_sqr_distances;
this->searchForNeighbors ((*indices_)[i], search_parameter_, n_indices, n_sqr_distances);
if (getLocalRF ((*indices_)[i], rf) == std::numeric_limits<float>::max ())
{
output.is_dense = false;
}
for (int d = 0; d < 3; ++d)
{
output_rf.x_axis[d] = rf.row (0)[d];
output_rf.y_axis[d] = rf.row (1)[d];
output_rf.z_axis[d] = rf.row (2)[d];
}
}
}
#define PCL_INSTANTIATE_SHOTLocalReferenceFrameEstimationOMP(T,OutT) template class PCL_EXPORTS pcl::SHOTLocalReferenceFrameEstimationOMP<T,OutT>;
#endif // PCL_FEATURES_IMPL_SHOT_LRF_H_