sampling_surface_normal.cpp
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2 
4 
5 namespace python
6 {
7  namespace datapointsfilters
8  {
9  void pybindSamplingSurfaceNormal(py::module& p_module)
10  {
12  py::class_<SamplingSurfaceNormalDataPointsFilter, std::shared_ptr<SamplingSurfaceNormalDataPointsFilter>, DataPointsFilter>(p_module, "SamplingSurfaceNormalDataPointsFilter")
13 
14  .def_static("description", &SamplingSurfaceNormalDataPointsFilter::description)
15  .def_static("availableParameters", &SamplingSurfaceNormalDataPointsFilter::availableParameters)
16 
17  .def_readonly("ratio", &SamplingSurfaceNormalDataPointsFilter::ratio)
18  .def_readonly("knn", &SamplingSurfaceNormalDataPointsFilter::knn)
19  .def_readonly("samplingMethod", &SamplingSurfaceNormalDataPointsFilter::samplingMethod)
20  .def_readonly("maxBoxDim", &SamplingSurfaceNormalDataPointsFilter::maxBoxDim)
21  .def_readonly("averageExistingDescriptors", &SamplingSurfaceNormalDataPointsFilter::averageExistingDescriptors)
22  .def_readonly("keepNormals", &SamplingSurfaceNormalDataPointsFilter::keepNormals)
23  .def_readonly("keepDensities", &SamplingSurfaceNormalDataPointsFilter::keepDensities)
24  .def_readonly("keepEigenValues", &SamplingSurfaceNormalDataPointsFilter::keepEigenValues)
25  .def_readonly("keepEigenVectors", &SamplingSurfaceNormalDataPointsFilter::keepEigenVectors)
26 
27  .def(py::init<const Parameters&>(), py::arg("params") = Parameters(), "Constructor, uses parameter interface")
28 
31  }
32  }
33 }
Sampling surface normals. First decimate the space until there is at most knn points, then find the center of mass and use the points to estimate nromal using eigen-decomposition.
void pybindSamplingSurfaceNormal(py::module &p_module)
PM::Parameters Parameters
virtual DataPoints filter(const DataPoints &input)
virtual void inPlaceFilter(DataPoints &cloud)
static const ParametersDoc availableParameters()
PM::DataPointsFilter DataPointsFilter


libpointmatcher
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autogenerated on Sat May 27 2023 02:38:03