105 lines
4.5 KiB
C++
105 lines
4.5 KiB
C++
/*
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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) 2012, Yani Ioannou <yani.ioannou@gmail.com>
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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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#ifndef PCL_FILTERS_DON_IMPL_H_
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#define PCL_FILTERS_DON_IMPL_H_
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#include <pcl/features/don.h>
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//////////////////////////////////////////////////////////////////////////////////////////////
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template <typename PointInT, typename PointNT, typename PointOutT> bool
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pcl::DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT>::initCompute ()
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{
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// Check if input normals are set
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if (!input_normals_small_)
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{
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PCL_ERROR ("[pcl::%s::initCompute] No input dataset containing small support radius normals was given!\n", getClassName().c_str ());
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Feature<PointInT, PointOutT>::deinitCompute();
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return (false);
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}
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if (!input_normals_large_)
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{
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PCL_ERROR ("[pcl::%s::initCompute] No input dataset containing large support radius normals was given!\n", getClassName().c_str ());
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Feature<PointInT, PointOutT>::deinitCompute();
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return (false);
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}
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// Check if the size of normals is the same as the size of the surface
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if (input_normals_small_->size () != input_->size ())
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{
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PCL_ERROR ("[pcl::%s::initCompute] ", getClassName().c_str ());
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PCL_ERROR ("The number of points in the input dataset differs from ");
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PCL_ERROR ("the number of points in the dataset containing the small support radius normals!\n");
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Feature<PointInT, PointOutT>::deinitCompute ();
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return (false);
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}
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if (input_normals_large_->size () != input_->size ())
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{
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PCL_ERROR ("[pcl::%s::initCompute] ", getClassName().c_str ());
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PCL_ERROR ("The number of points in the input dataset differs from ");
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PCL_ERROR ("the number of points in the dataset containing the large support radius normals!\n");
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Feature<PointInT, PointOutT>::deinitCompute ();
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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> void
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pcl::DifferenceOfNormalsEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output)
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{
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//perform DoN subtraction and return results
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for (std::size_t point_id = 0; point_id < input_->size (); ++point_id)
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{
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output[point_id].getNormalVector3fMap () = ((*input_normals_small_)[point_id].getNormalVector3fMap ()
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- (*input_normals_large_)[point_id].getNormalVector3fMap ()) / 2.0;
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if(!std::isfinite (output[point_id].normal_x) ||
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!std::isfinite (output[point_id].normal_y) ||
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!std::isfinite (output[point_id].normal_z)){
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output[point_id].getNormalVector3fMap () = Eigen::Vector3f(0,0,0);
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}
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output[point_id].curvature = output[point_id].getNormalVector3fMap ().norm();
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}
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}
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#define PCL_INSTANTIATE_DifferenceOfNormalsEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::DifferenceOfNormalsEstimation<T,NT,OutT>;
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#endif // PCL_FILTERS_DON_H_
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