Point Cloud Library (PCL)
1.9.1
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40 #ifndef PCL_SEGMENTATION_SAC_SEGMENTATION_H_
41 #define PCL_SEGMENTATION_SAC_SEGMENTATION_H_
43 #include <pcl/pcl_base.h>
44 #include <pcl/PointIndices.h>
45 #include <pcl/ModelCoefficients.h>
48 #include <pcl/sample_consensus/method_types.h>
49 #include <pcl/sample_consensus/sac.h>
51 #include <pcl/sample_consensus/model_types.h>
52 #include <pcl/sample_consensus/sac_model.h>
54 #include <pcl/search/search.h>
64 template <
typename Po
intT>
226 inline Eigen::Vector3f
257 initSAC (
const int method_type);
310 template <
typename Po
intT,
typename Po
intNT>
429 #ifdef PCL_NO_PRECOMPILE
430 #include <pcl/segmentation/impl/sac_segmentation.hpp>
433 #endif //#ifndef PCL_SEGMENTATION_SAC_SEGMENTATION_H_
This file defines compatibility wrappers for low level I/O functions.
boost::shared_ptr< PointCloud< PointT > > Ptr
PointCloudN::ConstPtr PointCloudNConstPtr
boost::shared_ptr< SampleConsensusModel > Ptr
virtual std::string getClassName() const
Class get name method.
void getMinMaxOpeningAngle(double &min_angle, double &max_angle)
Get the opening angle which we need minimum to validate a cone model.
boost::shared_ptr< pcl::search::Search< PointT > > Ptr
int max_iterations_
Maximum number of iterations before giving up (user given parameter).
double min_angle_
The minimum and maximum allowed opening angle of valid cone model.
SACSegmentation(bool random=false)
Empty constructor.
virtual bool initSACModel(const int model_type)
Initialize the Sample Consensus model and set its parameters.
SampleConsensus< PointT >::Ptr SampleConsensusPtr
PointCloud::Ptr PointCloudPtr
double eps_angle_
The maximum allowed difference between the model normal and the given axis.
PointCloudN::Ptr PointCloudNPtr
SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
boost::shared_ptr< SampleConsensusModelFromNormals > Ptr
SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
PointCloud represents the base class in PCL for storing collections of 3D points.
double getDistanceThreshold() const
Get the distance to the model threshold.
void setRadiusLimits(const double &min_radius, const double &max_radius)
Set the minimum and maximum allowable radius limits for the model (applicable to models that estimate...
double radius_min_
The minimum and maximum radius limits for the model.
A point structure representing Euclidean xyz coordinates, and the RGB color.
double getEpsAngle() const
Get the epsilon (delta) model angle threshold in radians.
SampleConsensusModelPtr model_
The model that needs to be segmented.
double samples_radius_
The maximum distance of subsequent samples from the first (radius search)
pcl::PointCloud< PointT > PointCloud
PointCloudNConstPtr normals_
A pointer to the input dataset that contains the point normals of the XYZ dataset.
PointCloud::ConstPtr PointCloudConstPtr
PointCloud::ConstPtr PointCloudConstPtr
SampleConsensusModelFromNormals< PointT, PointNT >::Ptr SampleConsensusModelFromNormalsPtr
virtual std::string getClassName() const
Class get name method.
int method_type_
The type of sample consensus method to use (user given parameter).
SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods...
PointCloud::Ptr PointCloudPtr
bool optimize_coefficients_
Set to true if a coefficient refinement is required.
SACSegmentationFromNormals(bool random=false)
Empty constructor.
int model_type_
The type of model to use (user given parameter).
void setProbability(double probability)
Set the probability of choosing at least one sample free from outliers.
void setMethodType(int method)
The type of sample consensus method to use (user given parameter).
void setEpsAngle(double ea)
Set the angle epsilon (delta) threshold.
virtual bool initSACModel(const int model_type)
Initialize the Sample Consensus model and set its parameters.
void setInputNormals(const PointCloudNConstPtr &normals)
Provide a pointer to the input dataset that contains the point normals of the XYZ dataset.
SearchPtr samples_radius_search_
The search object for picking subsequent samples using radius search.
int getMaxIterations() const
Get maximum number of iterations before giving up.
double probability_
Desired probability of choosing at least one sample free from outliers (user given parameter).
pcl::PointCloud< PointNT > PointCloudN
SACSegmentation< PointT >::PointCloud PointCloud
void setSamplesMaxDist(const double &radius, SearchPtr search)
Set the maximum distance allowed when drawing random samples.
virtual ~SACSegmentation()
Empty destructor.
void setNormalDistanceWeight(double distance_weight)
Set the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point n...
void setMaxIterations(int max_iterations)
Set the maximum number of iterations before giving up.
double distance_from_origin_
The distance from the template plane to the origin.
double distance_weight_
The relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point norma...
void setModelType(int model)
The type of model to use (user given parameter).
void setAxis(const Eigen::Vector3f &ax)
Set the axis along which we need to search for a model perpendicular to.
void getRadiusLimits(double &min_radius, double &max_radius)
Get the minimum and maximum allowable radius limits for the model as set by the user.
virtual void segment(PointIndices &inliers, ModelCoefficients &model_coefficients)
Base method for segmentation of a model in a PointCloud given by <setInputCloud (),...
bool getOptimizeCoefficients() const
Get the coefficient refinement internal flag.
pcl::search::Search< PointT >::Ptr SearchPtr
void setOptimizeCoefficients(bool optimize)
Set to true if a coefficient refinement is required.
void getSamplesMaxDist(double &radius)
Get maximum distance allowed when drawing random samples.
virtual void initSAC(const int method_type)
Initialize the Sample Consensus method and set its parameters.
double getNormalDistanceWeight() const
Get the relative weight (between 0 and 1) to give to the angular distance (0 to pi/2) between point n...
double getDistanceFromOrigin() const
Get the distance of a plane model from the origin.
boost::shared_ptr< const PointCloud< PointT > > ConstPtr
void setDistanceFromOrigin(const double d)
Set the distance we expect a plane model to be from the origin.
SampleConsensusPtr sac_
The sample consensus segmentation method.
Eigen::Vector3f axis_
The axis along which we need to search for a model perpendicular to.
void setDistanceThreshold(double threshold)
Distance to the model threshold (user given parameter).
Eigen::Vector3f getAxis() const
Get the axis along which we need to search for a model perpendicular to.
PointCloudNConstPtr getInputNormals() const
Get a pointer to the normals of the input XYZ point cloud dataset.
int getMethodType() const
Get the type of sample consensus method used.
SampleConsensus represents the base class.
double getProbability() const
Get the probability of choosing at least one sample free from outliers.
int getModelType() const
Get the type of SAC model used.
double threshold_
Distance to the model threshold (user given parameter).
SampleConsensusPtr getMethod() const
Get a pointer to the SAC method used.
SampleConsensus< PointT >::Ptr SampleConsensusPtr
SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models,...
void setMinMaxOpeningAngle(const double &min_angle, const double &max_angle)
Set the minimum opning angle for a cone model.
bool random_
Set to true if we need a random seed.
SampleConsensusModelPtr getModel() const
Get a pointer to the SAC model used.