Point Cloud Library (PCL)  1.14.1-dev
model_outlier_removal.h
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37 
38 #pragma once
39 
40 #include <pcl/filters/filter_indices.h>
41 #include <pcl/ModelCoefficients.h>
42 
43 // Sample Consensus models
44 #include <pcl/sample_consensus/model_types.h>
45 #include <pcl/sample_consensus/sac_model.h>
46 
47 namespace pcl
48 {
49  /** \brief @b ModelOutlierRemoval filters points in a cloud based on the distance between model and point.
50  * \details Iterates through the entire input once, automatically filtering non-finite points and the points outside
51  * <br><br>
52  * Usage example:
53  * \code
54  *
55  * pcl::ModelCoefficients model_coeff;
56  * model_coeff.values.resize(4);
57  * model_coeff.values[0] = 0;
58  * model_coeff.values[1] = 0;
59  * model_coeff.values[2] = 1;
60  * model_coeff.values[3] = 0.5;
61  * pcl::ModelOutlierRemoval<pcl::PointXYZ> filter;
62  * filter.setModelCoefficients (model_coeff);
63  * filter.setThreshold (0.1);
64  * filter.setModelType (pcl::SACMODEL_PLANE);
65  * filter.setInputCloud (*cloud_in);
66  * filter.setNegative (false);
67  * filter.filter (*cloud_out);
68 
69  * \endcode
70  */
71  template <typename PointT>
72  class ModelOutlierRemoval : public FilterIndices<PointT>
73  {
74  protected:
76  using PointCloudPtr = typename PointCloud::Ptr;
79 
80  public:
83 
84  /** \brief Constructor.
85  * \param[in] extract_removed_indices Set to true if you want to be able to extract the indices of points being removed (default = false).
86  */
87  inline
88  ModelOutlierRemoval (bool extract_removed_indices = false) :
89  FilterIndices<PointT> (extract_removed_indices)
90  {
91  thresh_ = 0;
93  filter_name_ = "ModelOutlierRemoval";
95  }
96 
97  /** \brief sets the models coefficients */
98  inline void
99  setModelCoefficients (const pcl::ModelCoefficients& model_coefficients)
100  {
101  model_coefficients_.resize (model_coefficients.values.size ());
102  for (std::size_t i = 0; i < model_coefficients.values.size (); i++)
103  {
104  model_coefficients_[i] = model_coefficients.values[i];
105  }
106  }
107 
108  /** \brief returns the models coefficients
109  */
112  {
114  mc.values.resize (model_coefficients_.size ());
115  for (std::size_t i = 0; i < mc.values.size (); i++)
116  mc.values[i] = model_coefficients_[i];
117  return (mc);
118  }
119 
120  /** \brief Set the type of SAC model used. */
121  inline void
123  {
124  model_type_ = model;
125  }
126 
127  /** \brief Get the type of SAC model used. */
128  inline pcl::SacModel
129  getModelType () const
130  {
131  return (model_type_);
132  }
133 
134  /** \brief Set the thresholdfunction*/
135  inline void
136  setThreshold (float thresh)
137  {
138  thresh_ = thresh;
139  }
140 
141  /** \brief Get the thresholdfunction*/
142  inline float
143  getThreshold () const
144  {
145  return (thresh_);
146  }
147 
148  /** \brief Set the normals cloud*/
149  inline void
151  {
152  cloud_normals_ = normals_ptr;
153  }
154 
155  /** \brief Get the normals cloud*/
156  inline PointCloudNConstPtr
158  {
159  return (cloud_normals_);
160  }
161 
162  /** \brief Set the normals distance weight*/
163  inline void
164  setNormalDistanceWeight (const double weight)
165  {
166  normals_distance_weight_ = weight;
167  }
168 
169  /** \brief get the normal distance weight*/
170  inline double
172  {
173  return (normals_distance_weight_);
174  }
175 
176  /** \brief Register a different threshold function
177  * \param[in] thresh pointer to a threshold function
178  */
179  void
180  setThresholdFunction (std::function<bool (double)> thresh)
181  {
182  threshold_function_ = thresh;
183  }
184 
185  /** \brief Register a different threshold function
186  * \param[in] thresh_function pointer to a threshold function
187  * \param[in] instance
188  */
189  template <typename T> void
190  setThresholdFunction (bool (T::*thresh_function) (double), T& instance)
191  {
192  setThresholdFunction ([=, &instance] (double threshold) { return (instance.*thresh_function) (threshold); });
193  }
194 
195  protected:
205 
206  /** \brief Filtered results are indexed by an indices array.
207  * \param[out] indices The resultant indices.
208  */
209  void
210  applyFilter (Indices &indices) override
211  {
212  applyFilterIndices (indices);
213  }
214 
215  /** \brief Filtered results are indexed by an indices array.
216  * \param[out] indices The resultant indices.
217  */
218  void
219  applyFilterIndices (Indices &indices);
220 
221  protected:
224 
225  /** \brief The model used to calculate distances */
227 
228  /** \brief The threshold used to separate outliers (removed_indices) from inliers (indices) */
229  float thresh_;
230 
231  /** \brief The model coefficients */
232  Eigen::VectorXf model_coefficients_;
233 
234  /** \brief The type of model to use (user given parameter). */
236  std::function<bool (double)> threshold_function_;
237 
238  inline bool
239  checkSingleThreshold (double value)
240  {
241  return (value < thresh_);
242  }
243 
244  private:
245  virtual bool
246  initSACModel (pcl::SacModel model_type);
247  };
248 }
249 
250 #ifdef PCL_NO_PRECOMPILE
251 #include <pcl/filters/impl/model_outlier_removal.hpp>
252 #endif
Filter represents the base filter class.
Definition: filter.h:81
std::string filter_name_
The filter name.
Definition: filter.h:158
FilterIndices represents the base class for filters that are about binary point removal.
ModelOutlierRemoval filters points in a cloud based on the distance between model and point.
typename SampleConsensusModel< PointT >::Ptr SampleConsensusModelPtr
Eigen::VectorXf model_coefficients_
The model coefficients.
void setInputNormals(const PointCloudNConstPtr normals_ptr)
Set the normals cloud.
std::function< bool(double)> threshold_function_
void applyFilterIndices(Indices &indices)
Filtered results are indexed by an indices array.
void setModelType(pcl::SacModel model)
Set the type of SAC model used.
float thresh_
The threshold used to separate outliers (removed_indices) from inliers (indices)
float getThreshold() const
Get the thresholdfunction.
pcl::SacModel model_type_
The type of model to use (user given parameter).
pcl::PointCloud< pcl::Normal >::Ptr PointCloudNPtr
double getNormalDistanceWeight() const
get the normal distance weight
pcl::PointCloud< pcl::Normal >::ConstPtr PointCloudNConstPtr
ModelOutlierRemoval(bool extract_removed_indices=false)
Constructor.
void applyFilter(Indices &indices) override
Filtered results are indexed by an indices array.
void setThresholdFunction(bool(T::*thresh_function)(double), T &instance)
Register a different threshold function.
pcl::ModelCoefficients getModelCoefficients() const
returns the models coefficients
PointCloudNConstPtr getInputNormals() const
Get the normals cloud.
void setNormalDistanceWeight(const double weight)
Set the normals distance weight.
SampleConsensusModelPtr model_
The model used to calculate distances.
void setThresholdFunction(std::function< bool(double)> thresh)
Register a different threshold function.
pcl::SacModel getModelType() const
Get the type of SAC model used.
void setModelCoefficients(const pcl::ModelCoefficients &model_coefficients)
sets the models coefficients
PointCloudNConstPtr cloud_normals_
bool checkSingleThreshold(double value)
void setThreshold(float thresh)
Set the thresholdfunction.
PCL base class.
Definition: pcl_base.h:70
typename PointCloud::Ptr PointCloudPtr
Definition: pcl_base.h:73
typename PointCloud::ConstPtr PointCloudConstPtr
Definition: pcl_base.h:74
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
shared_ptr< PointCloud< PointT > > Ptr
Definition: point_cloud.h:413
shared_ptr< const PointCloud< PointT > > ConstPtr
Definition: point_cloud.h:414
shared_ptr< SampleConsensusModel< PointT > > Ptr
Definition: sac_model.h:78
SacModel
Definition: model_types.h:46
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133
std::vector< float > values
A point structure representing Euclidean xyz coordinates, and the RGB color.