297 lines
11 KiB
C++
297 lines
11 KiB
C++
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2009, Willow Garage, Inc.
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* Copyright (c) 2012-, Open Perception, Inc.
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of the copyright holder(s) nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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*
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*/
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#pragma once
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#include <pcl/features/shot_omp.h>
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#include <pcl/common/point_tests.h> // for pcl::isFinite
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#include <pcl/common/time.h>
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#include <pcl/features/shot_lrf_omp.h>
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template<typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> bool
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pcl::SHOTEstimationOMP<PointInT, PointNT, PointOutT, PointRFT>::initCompute ()
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{
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if (!FeatureFromNormals<PointInT, PointNT, PointOutT>::initCompute ())
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{
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PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
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return (false);
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}
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// SHOT cannot work with k-search
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if (this->getKSearch () != 0)
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{
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PCL_ERROR(
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"[pcl::%s::initCompute] Error! Search method set to k-neighborhood. Call setKSearch(0) and setRadiusSearch( radius ) to use this class.\n",
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getClassName().c_str ());
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return (false);
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}
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// Default LRF estimation alg: SHOTLocalReferenceFrameEstimationOMP
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typename SHOTLocalReferenceFrameEstimationOMP<PointInT, PointRFT>::Ptr lrf_estimator(new SHOTLocalReferenceFrameEstimationOMP<PointInT, PointRFT>);
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lrf_estimator->setRadiusSearch ((lrf_radius_ > 0 ? lrf_radius_ : search_radius_));
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lrf_estimator->setInputCloud (input_);
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lrf_estimator->setIndices (indices_);
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lrf_estimator->setNumberOfThreads(threads_);
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if (!fake_surface_)
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lrf_estimator->setSearchSurface(surface_);
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if (!FeatureWithLocalReferenceFrames<PointInT, PointRFT>::initLocalReferenceFrames (indices_->size (), lrf_estimator))
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{
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PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
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return (false);
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}
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return (true);
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template<typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> bool
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pcl::SHOTColorEstimationOMP<PointInT, PointNT, PointOutT, PointRFT>::initCompute ()
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{
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if (!FeatureFromNormals<PointInT, PointNT, PointOutT>::initCompute ())
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{
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PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
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return (false);
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}
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// SHOT cannot work with k-search
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if (this->getKSearch () != 0)
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{
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PCL_ERROR(
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"[pcl::%s::initCompute] Error! Search method set to k-neighborhood. Call setKSearch(0) and setRadiusSearch( radius ) to use this class.\n",
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getClassName().c_str ());
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return (false);
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}
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// Default LRF estimation alg: SHOTLocalReferenceFrameEstimationOMP
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typename SHOTLocalReferenceFrameEstimationOMP<PointInT, PointRFT>::Ptr lrf_estimator(new SHOTLocalReferenceFrameEstimationOMP<PointInT, PointRFT>);
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lrf_estimator->setRadiusSearch ((lrf_radius_ > 0 ? lrf_radius_ : search_radius_));
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lrf_estimator->setInputCloud (input_);
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lrf_estimator->setIndices (indices_);
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lrf_estimator->setNumberOfThreads(threads_);
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if (!fake_surface_)
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lrf_estimator->setSearchSurface(surface_);
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if (!FeatureWithLocalReferenceFrames<PointInT, PointRFT>::initLocalReferenceFrames (indices_->size (), lrf_estimator))
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{
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PCL_ERROR ("[pcl::%s::initCompute] Init failed.\n", getClassName ().c_str ());
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return (false);
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}
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return (true);
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template<typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
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pcl::SHOTEstimationOMP<PointInT, PointNT, PointOutT, PointRFT>::setNumberOfThreads (unsigned int nr_threads)
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{
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if (nr_threads == 0)
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#ifdef _OPENMP
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threads_ = omp_get_num_procs();
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#else
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threads_ = 1;
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#endif
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else
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threads_ = nr_threads;
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template<typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
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pcl::SHOTEstimationOMP<PointInT, PointNT, PointOutT, PointRFT>::computeFeature (PointCloudOut &output)
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{
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descLength_ = nr_grid_sector_ * (nr_shape_bins_ + 1);
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sqradius_ = search_radius_ * search_radius_;
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radius3_4_ = (search_radius_ * 3) / 4;
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radius1_4_ = search_radius_ / 4;
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radius1_2_ = search_radius_ / 2;
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assert(descLength_ == 352);
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output.is_dense = true;
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// Iterating over the entire index vector
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#pragma omp parallel for \
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default(none) \
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shared(output) \
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num_threads(threads_)
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for (std::ptrdiff_t idx = 0; idx < static_cast<std::ptrdiff_t> (indices_->size ()); ++idx)
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{
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Eigen::VectorXf shot;
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shot.setZero (descLength_);
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bool lrf_is_nan = false;
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const PointRFT& current_frame = (*frames_)[idx];
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if (!std::isfinite (current_frame.x_axis[0]) ||
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!std::isfinite (current_frame.y_axis[0]) ||
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!std::isfinite (current_frame.z_axis[0]))
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{
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PCL_WARN ("[pcl::%s::computeFeature] The local reference frame is not valid! Aborting description of point with index %d\n",
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getClassName ().c_str (), (*indices_)[idx]);
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lrf_is_nan = true;
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}
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// Allocate enough space to hold the results
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// \note This resize is irrelevant for a radiusSearch ().
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pcl::Indices nn_indices (k_);
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std::vector<float> nn_dists (k_);
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if (!isFinite ((*input_)[(*indices_)[idx]]) || lrf_is_nan || this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices,
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nn_dists) == 0)
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{
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// Copy into the resultant cloud
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for (Eigen::Index d = 0; d < shot.size (); ++d)
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output[idx].descriptor[d] = std::numeric_limits<float>::quiet_NaN ();
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for (int d = 0; d < 9; ++d)
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output[idx].rf[d] = std::numeric_limits<float>::quiet_NaN ();
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output.is_dense = false;
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continue;
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}
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// Estimate the SHOT at each patch
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this->computePointSHOT (idx, nn_indices, nn_dists, shot);
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// Copy into the resultant cloud
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for (Eigen::Index d = 0; d < shot.size (); ++d)
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output[idx].descriptor[d] = shot[d];
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for (int d = 0; d < 3; ++d)
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{
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output[idx].rf[d + 0] = (*frames_)[idx].x_axis[d];
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output[idx].rf[d + 3] = (*frames_)[idx].y_axis[d];
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output[idx].rf[d + 6] = (*frames_)[idx].z_axis[d];
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}
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}
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
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pcl::SHOTColorEstimationOMP<PointInT, PointNT, PointOutT, PointRFT>::setNumberOfThreads (unsigned int nr_threads)
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{
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if (nr_threads == 0)
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#ifdef _OPENMP
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threads_ = omp_get_num_procs();
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#else
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threads_ = 1;
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#endif
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else
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threads_ = nr_threads;
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}
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointNT, typename PointOutT, typename PointRFT> void
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pcl::SHOTColorEstimationOMP<PointInT, PointNT, PointOutT, PointRFT>::computeFeature (PointCloudOut &output)
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{
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descLength_ = (b_describe_shape_) ? nr_grid_sector_ * (nr_shape_bins_ + 1) : 0;
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descLength_ += (b_describe_color_) ? nr_grid_sector_ * (nr_color_bins_ + 1) : 0;
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assert( (!b_describe_color_ && b_describe_shape_ && descLength_ == 352) ||
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(b_describe_color_ && !b_describe_shape_ && descLength_ == 992) ||
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(b_describe_color_ && b_describe_shape_ && descLength_ == 1344)
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);
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sqradius_ = search_radius_ * search_radius_;
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radius3_4_ = (search_radius_ * 3) / 4;
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radius1_4_ = search_radius_ / 4;
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radius1_2_ = search_radius_ / 2;
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output.is_dense = true;
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// Iterating over the entire index vector
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#pragma omp parallel for \
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default(none) \
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shared(output) \
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num_threads(threads_)
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for (std::ptrdiff_t idx = 0; idx < static_cast<std::ptrdiff_t> (indices_->size ()); ++idx)
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{
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Eigen::VectorXf shot;
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shot.setZero (descLength_);
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// Allocate enough space to hold the results
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// \note This resize is irrelevant for a radiusSearch ().
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pcl::Indices nn_indices (k_);
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std::vector<float> nn_dists (k_);
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bool lrf_is_nan = false;
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const PointRFT& current_frame = (*frames_)[idx];
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if (!std::isfinite (current_frame.x_axis[0]) ||
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!std::isfinite (current_frame.y_axis[0]) ||
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!std::isfinite (current_frame.z_axis[0]))
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{
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PCL_WARN ("[pcl::%s::computeFeature] The local reference frame is not valid! Aborting description of point with index %d\n",
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getClassName ().c_str (), (*indices_)[idx]);
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lrf_is_nan = true;
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}
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if (!isFinite ((*input_)[(*indices_)[idx]]) ||
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lrf_is_nan ||
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this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0)
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{
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// Copy into the resultant cloud
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for (Eigen::Index d = 0; d < shot.size (); ++d)
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output[idx].descriptor[d] = std::numeric_limits<float>::quiet_NaN ();
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for (int d = 0; d < 9; ++d)
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output[idx].rf[d] = std::numeric_limits<float>::quiet_NaN ();
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output.is_dense = false;
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continue;
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}
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// Estimate the SHOT at each patch
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this->computePointSHOT (idx, nn_indices, nn_dists, shot);
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// Copy into the resultant cloud
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for (Eigen::Index d = 0; d < shot.size (); ++d)
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output[idx].descriptor[d] = shot[d];
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for (int d = 0; d < 3; ++d)
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{
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output[idx].rf[d + 0] = (*frames_)[idx].x_axis[d];
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output[idx].rf[d + 3] = (*frames_)[idx].y_axis[d];
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output[idx].rf[d + 6] = (*frames_)[idx].z_axis[d];
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}
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}
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}
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#define PCL_INSTANTIATE_SHOTEstimationOMP(T,NT,OutT,RFT) template class PCL_EXPORTS pcl::SHOTEstimationOMP<T,NT,OutT,RFT>;
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#define PCL_INSTANTIATE_SHOTColorEstimationOMP(T,NT,OutT,RFT) template class PCL_EXPORTS pcl::SHOTColorEstimationOMP<T,NT,OutT,RFT>;
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