#include <pcl/ml/densecrf.h>
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| DenseCrf (int N, int m) |
| Constructor for DenseCrf class.
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| ~DenseCrf () |
| Deconstructor for DenseCrf class.
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void | setDataVector (const std::vector< Eigen::Vector3i, Eigen::aligned_allocator< Eigen::Vector3i > > data) |
| Set the input data vector.
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void | setColorVector (const std::vector< Eigen::Vector3i, Eigen::aligned_allocator< Eigen::Vector3i > > color) |
| The associated color of the data.
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void | setUnaryEnergy (const std::vector< float > unary) |
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void | addPairwiseEnergy (const std::vector< float > &feature, const int feature_dimension, const float w) |
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void | addPairwiseGaussian (float sx, float sy, float sz, float w) |
| Add a pairwise gaussian kernel.
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void | addPairwiseBilateral (float sx, float sy, float sz, float sr, float sg, float sb, float w) |
| Add a bilateral gaussian kernel.
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void | addPairwiseNormals (std::vector< Eigen::Vector3i, Eigen::aligned_allocator< Eigen::Vector3i > > &coord, std::vector< Eigen::Vector3f, Eigen::aligned_allocator< Eigen::Vector3f > > &normals, float sx, float sy, float sz, float snx, float sny, float snz, float w) |
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void | inference (int n_iterations, std::vector< float > &result, float relax=1.0f) |
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void | mapInference (int n_iterations, std::vector< int > &result, float relax=1.0f) |
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void | expAndNormalize (std::vector< float > &out, const std::vector< float > &in, float scale, float relax=1.0f) const |
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void | expAndNormalizeORI (float *out, const float *in, float scale=1.0f, float relax=1.0f) |
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void | map (int n_iterations, std::vector< int > result, float relax=1.0f) |
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std::vector< float > | runInference (int n_iterations, float relax) |
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void | startInference () |
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void | stepInference (float relax) |
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void | runInference (float relax) |
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void | getBarycentric (int idx, std::vector< float > &bary) |
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void | getFeatures (int idx, std::vector< float > &features) |
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Definition at line 48 of file densecrf.h.
◆ DenseCrf()
pcl::DenseCrf::DenseCrf |
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int | N, |
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int | m ) |
◆ ~DenseCrf()
pcl::DenseCrf::~DenseCrf |
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◆ addPairwiseBilateral()
Add a bilateral gaussian kernel.
◆ addPairwiseEnergy()
◆ addPairwiseGaussian()
Add a pairwise gaussian kernel.
◆ addPairwiseNormals()
void pcl::DenseCrf::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 ) |
◆ expAndNormalize()
◆ expAndNormalizeORI()
◆ getBarycentric()
void pcl::DenseCrf::getBarycentric |
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int | idx, |
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std::vector< float > & | bary ) |
◆ getFeatures()
void pcl::DenseCrf::getFeatures |
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int | idx, |
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std::vector< float > & | features ) |
◆ inference()
void pcl::DenseCrf::inference |
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int | n_iterations, |
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std::vector< float > & | result, |
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float | relax = 1.0f ) |
◆ map()
void pcl::DenseCrf::map |
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int | n_iterations, |
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std::vector< int > | result, |
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float | relax = 1.0f ) |
◆ mapInference()
void pcl::DenseCrf::mapInference |
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int | n_iterations, |
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std::vector< int > & | result, |
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float | relax = 1.0f ) |
◆ runInference() [1/2]
void pcl::DenseCrf::runInference |
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float | relax | ) |
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◆ runInference() [2/2]
std::vector< float > pcl::DenseCrf::runInference |
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int | n_iterations, |
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float | relax ) |
◆ setColorVector()
void pcl::DenseCrf::setColorVector |
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const std::vector< Eigen::Vector3i, Eigen::aligned_allocator< Eigen::Vector3i > > | color | ) |
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The associated color of the data.
◆ setDataVector()
void pcl::DenseCrf::setDataVector |
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const std::vector< Eigen::Vector3i, Eigen::aligned_allocator< Eigen::Vector3i > > | data | ) |
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Set the input data vector.
The input data vector holds the measurements coordinates as ijk of the voxel grid.
◆ setUnaryEnergy()
void pcl::DenseCrf::setUnaryEnergy |
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const std::vector< float > | unary | ) |
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◆ startInference()
void pcl::DenseCrf::startInference |
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◆ stepInference()
void pcl::DenseCrf::stepInference |
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float | relax | ) |
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◆ color_
std::vector<Eigen::Vector3i, Eigen::aligned_allocator<Eigen::Vector3i> > pcl::DenseCrf::color_ |
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◆ current_
std::vector<float> pcl::DenseCrf::current_ |
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◆ data_
std::vector<Eigen::Vector3i, Eigen::aligned_allocator<Eigen::Vector3i> > pcl::DenseCrf::data_ |
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◆ M_
◆ N_
Number of variables and labels.
Definition at line 138 of file densecrf.h.
◆ next_
std::vector<float> pcl::DenseCrf::next_ |
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◆ normal_
bool pcl::DenseCrf::normal_ |
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◆ pairwise_potential_
◆ rgb_
◆ tmp_
std::vector<float> pcl::DenseCrf::tmp_ |
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◆ unary_
std::vector<float> pcl::DenseCrf::unary_ |
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CRF unary potentials.
TODO: double might use to much memory
Definition at line 148 of file densecrf.h.
◆ xyz_
The documentation for this class was generated from the following file: