165 lines
4.7 KiB
C++
165 lines
4.7 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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*
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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 Willow Garage, Inc. 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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* Author : Christian Potthast
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* Email : potthast@usc.edu
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*
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*/
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#pragma once
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#include <pcl/ml/pairwise_potential.h>
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#include <pcl/memory.h>
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#include <pcl/pcl_macros.h>
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namespace pcl {
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class PCL_EXPORTS DenseCrf {
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public:
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/** Constructor for DenseCrf class. */
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DenseCrf(int N, int m);
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/** Deconstructor for DenseCrf class. */
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~DenseCrf();
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/** Set the input data vector.
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*
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* The input data vector holds the measurements coordinates as ijk of the voxel grid.
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*/
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void
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setDataVector(const std::vector<Eigen::Vector3i,
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Eigen::aligned_allocator<Eigen::Vector3i>> data);
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/** The associated color of the data. */
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void
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setColorVector(const std::vector<Eigen::Vector3i,
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Eigen::aligned_allocator<Eigen::Vector3i>> color);
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void
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setUnaryEnergy(const std::vector<float> unary);
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void
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addPairwiseEnergy(const std::vector<float>& feature,
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const int feature_dimension,
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const float w);
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/** Add a pairwise gaussian kernel. */
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void
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addPairwiseGaussian(float sx, float sy, float sz, float w);
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/** Add a bilateral gaussian kernel. */
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void
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addPairwiseBilateral(
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float sx, float sy, float sz, float sr, float sg, float sb, float w);
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void
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addPairwiseNormals(
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std::vector<Eigen::Vector3i, Eigen::aligned_allocator<Eigen::Vector3i>>& coord,
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std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f>>& normals,
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float sx,
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float sy,
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float sz,
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float snx,
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float sny,
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float snz,
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float w);
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void
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inference(int n_iterations, std::vector<float>& result, float relax = 1.0f);
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void
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mapInference(int n_iterations, std::vector<int>& result, float relax = 1.0f);
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void
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expAndNormalize(std::vector<float>& out,
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const std::vector<float>& in,
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float scale,
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float relax = 1.0f) const;
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void
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expAndNormalizeORI(float* out,
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const float* in,
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float scale = 1.0f,
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float relax = 1.0f);
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void
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map(int n_iterations, std::vector<int> result, float relax = 1.0f);
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std::vector<float>
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runInference(int n_iterations, float relax);
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void
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startInference();
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void
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stepInference(float relax);
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void
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runInference(float relax);
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void
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getBarycentric(int idx, std::vector<float>& bary);
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void
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getFeatures(int idx, std::vector<float>& features);
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protected:
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/** Number of variables and labels */
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int N_, M_;
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/** Data vector */
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std::vector<Eigen::Vector3i, Eigen::aligned_allocator<Eigen::Vector3i>> data_;
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/** Color vector */
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std::vector<Eigen::Vector3i, Eigen::aligned_allocator<Eigen::Vector3i>> color_;
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/** CRF unary potentials */
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/** TODO: double might use to much memory */
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std::vector<float> unary_;
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std::vector<float> current_;
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std::vector<float> next_;
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std::vector<float> tmp_;
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/** Pairwise potentials */
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std::vector<PairwisePotential*> pairwise_potential_;
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/** Input types */
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bool xyz_, rgb_, normal_;
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public:
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PCL_MAKE_ALIGNED_OPERATOR_NEW
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};
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} // namespace pcl
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