filter.hpp
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#pragma once
#include <pcl/pcl_exports.h> // for PCL_EXPORTS
#include <pcl/common/point_tests.h> // for pcl::isFinite
#include <pcl/filters/filter.h>
//////////////////////////////////////////////////////////////////////////
template <typename PointT> void
pcl::removeNaNFromPointCloud (const pcl::PointCloud<PointT> &cloud_in,
pcl::PointCloud<PointT> &cloud_out,
Indices &index)
{
// If the clouds are not the same, prepare the output
if (&cloud_in != &cloud_out)
{
cloud_out.header = cloud_in.header;
cloud_out.resize (cloud_in.size ());
cloud_out.sensor_origin_ = cloud_in.sensor_origin_;
cloud_out.sensor_orientation_ = cloud_in.sensor_orientation_;
}
// Reserve enough space for the indices
index.resize (cloud_in.size ());
// If the data is dense, we don't need to check for NaN
if (cloud_in.is_dense)
{
// Simply copy the data
cloud_out = cloud_in;
for (std::size_t j = 0; j < cloud_out.size (); ++j)
index[j] = j;
}
else
{
std::size_t j = 0;
for (std::size_t i = 0; i < cloud_in.size (); ++i)
{
if (!std::isfinite (cloud_in[i].x) ||
!std::isfinite (cloud_in[i].y) ||
!std::isfinite (cloud_in[i].z))
continue;
cloud_out[j] = cloud_in[i];
index[j] = i;
j++;
}
if (j != cloud_in.size ())
{
// Resize to the correct size
cloud_out.resize (j);
index.resize (j);
}
cloud_out.height = 1;
cloud_out.width = static_cast<std::uint32_t>(j);
// Removing bad points => dense (note: 'dense' doesn't mean 'organized')
cloud_out.is_dense = true;
}
}
//////////////////////////////////////////////////////////////////////////
template <typename PointT> void
pcl::removeNaNNormalsFromPointCloud (const pcl::PointCloud<PointT> &cloud_in,
pcl::PointCloud<PointT> &cloud_out,
Indices &index)
{
// If the clouds are not the same, prepare the output
if (&cloud_in != &cloud_out)
{
cloud_out.header = cloud_in.header;
cloud_out.resize (cloud_in.size ());
cloud_out.sensor_origin_ = cloud_in.sensor_origin_;
cloud_out.sensor_orientation_ = cloud_in.sensor_orientation_;
}
// Reserve enough space for the indices
index.resize (cloud_in.size ());
std::size_t j = 0;
// Assume cloud is dense
cloud_out.is_dense = true;
for (std::size_t i = 0; i < cloud_in.size (); ++i)
{
if (!std::isfinite (cloud_in[i].normal_x) ||
!std::isfinite (cloud_in[i].normal_y) ||
!std::isfinite (cloud_in[i].normal_z))
continue;
if (cloud_out.is_dense && !pcl::isFinite(cloud_in[i]))
cloud_out.is_dense = false;
cloud_out[j] = cloud_in[i];
index[j] = i;
j++;
}
if (j != cloud_in.size ())
{
// Resize to the correct size
cloud_out.resize (j);
index.resize (j);
}
cloud_out.height = 1;
cloud_out.width = j;
}
#define PCL_INSTANTIATE_removeNaNFromPointCloud(T) template PCL_EXPORTS void pcl::removeNaNFromPointCloud<T>(const pcl::PointCloud<T>&, pcl::PointCloud<T>&, Indices&);
#define PCL_INSTANTIATE_removeNaNNormalsFromPointCloud(T) template PCL_EXPORTS void pcl::removeNaNNormalsFromPointCloud<T>(const pcl::PointCloud<T>&, pcl::PointCloud<T>&, Indices&);
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points.
Definition: point_cloud.h:173
pcl::PointCloud::is_dense
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).
Definition: point_cloud.h:403
pcl::PointCloud::resize
void resize(std::size_t count)
Resizes the container to contain count elements.
Definition: point_cloud.h:462
pcl::PointCloud::sensor_orientation_
Eigen::Quaternionf sensor_orientation_
Sensor acquisition pose (rotation).
Definition: point_cloud.h:408
pcl::PointCloud::width
std::uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:398
pcl::PointCloud::header
pcl::PCLHeader header
The point cloud header.
Definition: point_cloud.h:392
pcl::PointCloud::height
std::uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:400
pcl::PointCloud::size
std::size_t size() const
Definition: point_cloud.h:443
pcl::PointCloud::sensor_origin_
Eigen::Vector4f sensor_origin_
Sensor acquisition pose (origin/translation).
Definition: point_cloud.h:406
pcl::removeNaNNormalsFromPointCloud
void removeNaNNormalsFromPointCloud(const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, Indices &index)
Removes points that have their normals invalid (i.e., equal to NaN)
Definition: filter.hpp:99
pcl::removeNaNFromPointCloud
void removeNaNFromPointCloud(const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, Indices &index)
Removes points with x, y, or z equal to NaN.
Definition: filter.hpp:46
pcl::isFinite
bool isFinite(const PointT &pt)
Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if f...
Definition: point_tests.h:55
pcl::Indices
IndicesAllocator<> Indices
Type used for indices in PCL.
Definition: types.h:133