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multi_ransac.h
/*
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#pragma once
#include <pcl/cuda/sample_consensus/sac.h>
#include <pcl/cuda/sample_consensus/sac_model.h>
namespace pcl
{
namespace cuda
{
/** \brief @b RandomSampleConsensus represents an implementation of the
* RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Random
* Sample Consensus: A Paradigm for Model Fitting with Applications to Image
* Analysis and Automated Cartography", Martin A. Fischler and Robert C. Bolles,
* Comm. Of the ACM 24: 381–395, June 1981.
* \author Radu Bogdan Rusu
*/
template <template <typename> class Storage>
class MultiRandomSampleConsensus : public SampleConsensus<Storage>
{
using SampleConsensus<Storage>::max_iterations_;
using SampleConsensus<Storage>::threshold_;
using SampleConsensus<Storage>::iterations_;
using SampleConsensus<Storage>::sac_model_;
using SampleConsensus<Storage>::model_;
using SampleConsensus<Storage>::model_coefficients_;
using SampleConsensus<Storage>::inliers_;
using SampleConsensus<Storage>::inliers_stencil_;
using SampleConsensus<Storage>::probability_;
using SampleConsensusModelPtr = typename SampleConsensusModel<Storage>::Ptr;
using Coefficients = typename SampleConsensusModel<Storage>::Coefficients;
using Hypotheses = typename SampleConsensusModel<Storage>::Hypotheses;
using Indices = typename SampleConsensusModel<Storage>::Indices;
using IndicesPtr = typename SampleConsensusModel<Storage>::IndicesPtr;
using IndicesConstPtr = typename SampleConsensusModel<Storage>::IndicesConstPtr;
public:
/** \brief RANSAC (RAndom SAmple Consensus) main constructor
* \param model a Sample Consensus model
*/
MultiRandomSampleConsensus (const SampleConsensusModelPtr &model) :
SampleConsensus<Storage> (model),
min_coverage_percent_ (0.9),
max_batches_ (5),
iterations_per_batch_ (1000)
{
// Maximum number of trials before we give up.
max_iterations_ = 10000;
}
/** \brief RANSAC (RAndom SAmple Consensus) main constructor
* \param model a Sample Consensus model
* \param threshold distance to model threshold
*/
MultiRandomSampleConsensus (const SampleConsensusModelPtr &model, double threshold) :
SampleConsensus<Storage> (model, threshold)
{
// Maximum number of trials before we give up.
max_iterations_ = 10000;
}
/** \brief Compute the actual model and find the inliers
* \param debug_verbosity_level enable/disable on-screen debug
* information and set the verbosity level
*/
bool
computeModel (int debug_verbosity_level = 0);
/** \brief how much (in percent) of the point cloud should be covered?
* If it is not possible to find enough planes, it will stop according to the regular ransac criteria
*/
void
setMinimumCoverage (float percent)
{
min_coverage_percent_ = percent;
}
/** \brief Sets the maximum number of batches that should be processed.
* Every Batch computes up to iterations_per_batch_ models and verifies them.
* If planes with a sufficiently high total inlier count are found earlier, the
* actual number of batch runs might be lower.
*/
void
setMaximumBatches (int max_batches)
{
max_batches_ = max_batches_;
}
/** \brief Sets the maximum number of batches that should be processed.
* Every Batch computes up to max_iterations_ models and verifies them.
* If planes with a sufficiently high total inlier count are found earlier, the
* actual number of batch runs might be lower.
*/
void
setIerationsPerBatch(int iterations_per_batch)
{
iterations_per_batch_ = iterations_per_batch;
}
inline std::vector<IndicesPtr>
getAllInliers () { return all_inliers_; }
inline std::vector<int>
getAllInlierCounts () { return all_inlier_counts_; }
/** \brief Return the model coefficients of the best model found so far.
*/
inline std::vector<float4>
getAllModelCoefficients ()
{
return all_model_coefficients_;
}
/** \brief Return the model coefficients of the best model found so far.
*/
inline std::vector<float3>
getAllModelCentroids ()
{
return all_model_centroids_;
}
private:
float min_coverage_percent_;
unsigned int max_batches_;
unsigned int iterations_per_batch_;
/** \brief The vector of the centroids of our models computed directly from the models found. */
std::vector<float3> all_model_centroids_;
/** \brief The vector of coefficients of our models computed directly from the models found. */
std::vector<float4> all_model_coefficients_;
std::vector<IndicesPtr> all_inliers_;
std::vector<int> all_inlier_counts_;
};
} // namespace
} // namespace
pcl::cuda::MultiRandomSampleConsensus
RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm,...
Definition multi_ransac.h:56
pcl::cuda::MultiRandomSampleConsensus::setMaximumBatches
void setMaximumBatches(int max_batches)
Sets the maximum number of batches that should be processed.
Definition multi_ransac.h:122
pcl::cuda::MultiRandomSampleConsensus::getAllInlierCounts
std::vector< int > getAllInlierCounts()
Definition multi_ransac.h:142
pcl::cuda::MultiRandomSampleConsensus::MultiRandomSampleConsensus
MultiRandomSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
RANSAC (RAndom SAmple Consensus) main constructor.
Definition multi_ransac.h:93
pcl::cuda::MultiRandomSampleConsensus::getAllModelCentroids
std::vector< float3 > getAllModelCentroids()
Return the model coefficients of the best model found so far.
Definition multi_ransac.h:155
pcl::cuda::MultiRandomSampleConsensus::setMinimumCoverage
void setMinimumCoverage(float percent)
how much (in percent) of the point cloud should be covered? If it is not possible to find enough plan...
Definition multi_ransac.h:111
pcl::cuda::MultiRandomSampleConsensus::setIerationsPerBatch
void setIerationsPerBatch(int iterations_per_batch)
Sets the maximum number of batches that should be processed.
Definition multi_ransac.h:133
pcl::cuda::MultiRandomSampleConsensus::getAllModelCoefficients
std::vector< float4 > getAllModelCoefficients()
Return the model coefficients of the best model found so far.
Definition multi_ransac.h:147
pcl::cuda::MultiRandomSampleConsensus::computeModel
bool computeModel(int debug_verbosity_level=0)
Compute the actual model and find the inliers.
pcl::cuda::MultiRandomSampleConsensus::MultiRandomSampleConsensus
MultiRandomSampleConsensus(const SampleConsensusModelPtr &model)
RANSAC (RAndom SAmple Consensus) main constructor.
Definition multi_ransac.h:79
pcl::cuda::MultiRandomSampleConsensus::getAllInliers
std::vector< IndicesPtr > getAllInliers()
Definition multi_ransac.h:139
pcl::cuda::SampleConsensus
Definition sac.h:51
pcl::cuda::SampleConsensus::inliers_stencil_
IndicesPtr inliers_stencil_
Definition sac.h:180
pcl::cuda::SampleConsensus::model_
Indices model_
The model found after the last computeModel () as point cloud indices.
Definition sac.h:176
pcl::cuda::SampleConsensus::probability_
float probability_
Desired probability of choosing at least one sample free from outliers.
Definition sac.h:186
pcl::cuda::SampleConsensus::threshold_
float threshold_
Distance to model threshold.
Definition sac.h:192
pcl::cuda::SampleConsensus::max_iterations_
int max_iterations_
Maximum number of iterations before giving up.
Definition sac.h:195
pcl::cuda::SampleConsensus::model_coefficients_
Coefficients model_coefficients_
The coefficients of our model computed directly from the model found.
Definition sac.h:183
pcl::cuda::SampleConsensus::inliers_
IndicesPtr inliers_
The indices of the points that were chosen as inliers after the last call.
Definition sac.h:179
pcl::cuda::SampleConsensus::sac_model_
SampleConsensusModelPtr sac_model_
The underlying data model used (what is it that we attempt to search for).
Definition sac.h:173
pcl::cuda::SampleConsensus::iterations_
int iterations_
Total number of internal loop iterations that we've done so far.
Definition sac.h:189
pcl::cuda::SampleConsensusModel::Hypotheses
typename Storage< float4 >::type Hypotheses
Definition sac_model.h:105
pcl::cuda::SampleConsensusModel::IndicesConstPtr
shared_ptr< const typename Storage< int >::type > IndicesConstPtr
Definition sac_model.h:99
pcl::cuda::SampleConsensusModel::IndicesPtr
shared_ptr< typename Storage< int >::type > IndicesPtr
Definition sac_model.h:98
pcl::cuda::SampleConsensusModel::Coefficients
typename Storage< float >::type Coefficients
Definition sac_model.h:101
pcl::cuda::SampleConsensusModel::Indices
typename Storage< int >::type Indices
Definition sac_model.h:97
pcl::cuda::SampleConsensusModel::Ptr
shared_ptr< SampleConsensusModel > Ptr
Definition sac_model.h:94
pcl
Definition convolution.h:46