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153 lines
6.4 KiB
153 lines
6.4 KiB
// |
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
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// |
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// By downloading, copying, installing or using the software you agree to this license. |
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// If you do not agree to this license, do not download, install, |
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// copy or use the software. |
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// |
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// |
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// License Agreement |
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// For Open Source Computer Vision Library |
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// |
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// Copyright (C) 2014, OpenCV Foundation, all rights reserved. |
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// Third party copyrights are property of their respective owners. |
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// |
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// Redistribution and use in source and binary forms, with or without modification, |
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// are permitted provided that the following conditions are met: |
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// |
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// * Redistribution's of source code must retain the above copyright notice, |
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// this list of conditions and the following disclaimer. |
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// |
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// * Redistribution's in binary form must reproduce the above copyright notice, |
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// this list of conditions and the following disclaimer in the documentation |
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// and/or other materials provided with the distribution. |
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// |
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// * The name of the copyright holders may not be used to endorse or promote products |
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// derived 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 "as is" and |
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// any express or implied warranties, including, but not limited to, the implied |
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// warranties of merchantability and fitness for a particular purpose are disclaimed. |
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// In no event shall the Intel Corporation or contributors be liable for any direct, |
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// indirect, incidental, special, exemplary, or consequential damages |
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// (including, but not limited to, procurement of substitute goods or services; |
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// loss of use, data, or profits; or business interruption) however caused |
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// and on any theory of liability, whether in contract, strict liability, |
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// or tort (including negligence or otherwise) arising in any way out of |
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// the use of this software, even if advised of the possibility of such damage. |
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// |
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/** @file |
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@author Tolga Birdal <tbirdal AT gmail.com> |
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*/ |
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#ifndef __OPENCV_SURFACE_MATCHING_HELPERS_HPP__ |
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#define __OPENCV_SURFACE_MATCHING_HELPERS_HPP__ |
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#include <opencv2/core.hpp> |
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namespace cv |
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{ |
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namespace ppf_match_3d |
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{ |
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//! @addtogroup surface_matching |
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//! @{ |
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/** |
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* @brief Load a PLY file |
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* @param [in] fileName The PLY model to read |
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* @param [in] withNormals Flag wheather the input PLY contains normal information, |
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* and whether it should be loaded or not |
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* @return Returns the matrix on successfull load |
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*/ |
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CV_EXPORTS_W Mat loadPLYSimple(const char* fileName, int withNormals = 0); |
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/** |
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* @brief Write a point cloud to PLY file |
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* @param [in] PC Input point cloud |
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* @param [in] fileName The PLY model file to write |
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*/ |
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CV_EXPORTS_W void writePLY(Mat PC, const char* fileName); |
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/** |
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* @brief Used for debbuging pruposes, writes a point cloud to a PLY file with the tip |
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* of the normal vectors as visible red points |
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* @param [in] PC Input point cloud |
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* @param [in] fileName The PLY model file to write |
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*/ |
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CV_EXPORTS_W void writePLYVisibleNormals(Mat PC, const char* fileName); |
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Mat samplePCUniform(Mat PC, int sampleStep); |
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Mat samplePCUniformInd(Mat PC, int sampleStep, std::vector<int>& indices); |
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/** |
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* Sample a point cloud using uniform steps |
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* @param [in] pc Input point cloud |
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* @param [in] xrange X components (min and max) of the bounding box of the model |
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* @param [in] yrange Y components (min and max) of the bounding box of the model |
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* @param [in] zrange Z components (min and max) of the bounding box of the model |
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* @param [in] sample_step_relative The point cloud is sampled such that all points |
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* have a certain minimum distance. This minimum distance is determined relatively using |
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* the parameter sample_step_relative. |
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* @param [in] weightByCenter The contribution of the quantized data points can be weighted |
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* by the distance to the origin. This parameter enables/disables the use of weighting. |
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* @return Sampled point cloud |
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*/ |
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CV_EXPORTS_W Mat samplePCByQuantization(Mat pc, Vec2f& xrange, Vec2f& yrange, Vec2f& zrange, float sample_step_relative, int weightByCenter=0); |
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void computeBboxStd(Mat pc, Vec2f& xRange, Vec2f& yRange, Vec2f& zRange); |
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void* indexPCFlann(Mat pc); |
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void destroyFlann(void* flannIndex); |
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void queryPCFlann(void* flannIndex, Mat& pc, Mat& indices, Mat& distances); |
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void queryPCFlann(void* flannIndex, Mat& pc, Mat& indices, Mat& distances, const int numNeighbors); |
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Mat normalizePCCoeff(Mat pc, float scale, float* Cx, float* Cy, float* Cz, float* MinVal, float* MaxVal); |
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Mat transPCCoeff(Mat pc, float scale, float Cx, float Cy, float Cz, float MinVal, float MaxVal); |
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/** |
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* Transforms the point cloud with a given a homogeneous 4x4 pose matrix (in double precision) |
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* @param [in] pc Input point cloud (CV_32F family). Point clouds with 3 or 6 elements per |
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* row are expected. In the case where the normals are provided, they are also rotated to be |
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* compatible with the entire transformation |
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* @param [in] Pose 4x4 pose matrix, but linearized in row-major form. |
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* @return Transformed point cloud |
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*/ |
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CV_EXPORTS_W Mat transformPCPose(Mat pc, const Matx44d& Pose); |
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/** |
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* Generate a random 4x4 pose matrix |
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* @param [out] Pose The random pose |
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*/ |
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CV_EXPORTS_W void getRandomPose(Matx44d& Pose); |
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/** |
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* Adds a uniform noise in the given scale to the input point cloud |
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* @param [in] pc Input point cloud (CV_32F family). |
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* @param [in] scale Input scale of the noise. The larger the scale, the more noisy the output |
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*/ |
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CV_EXPORTS_W Mat addNoisePC(Mat pc, double scale); |
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/** |
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* @brief Compute the normals of an arbitrary point cloud |
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* computeNormalsPC3d uses a plane fitting approach to smoothly compute |
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* local normals. Normals are obtained through the eigenvector of the covariance |
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* matrix, corresponding to the smallest eigen value. |
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* If PCNormals is provided to be an Nx6 matrix, then no new allocation |
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* is made, instead the existing memory is overwritten. |
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* @param [in] PC Input point cloud to compute the normals for. |
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* @param [out] PCNormals Output point cloud |
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* @param [in] NumNeighbors Number of neighbors to take into account in a local region |
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* @param [in] FlipViewpoint Should normals be flipped to a viewing direction? |
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* @param [in] viewpoint |
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* @return Returns 0 on success |
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*/ |
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CV_EXPORTS_W int computeNormalsPC3d(const Mat& PC, CV_OUT Mat& PCNormals, const int NumNeighbors, const bool FlipViewpoint, const Vec3f& viewpoint); |
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//! @} |
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} // namespace ppf_match_3d |
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} // namespace cv |
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#endif
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