A point cloud contains a list of 3D points. More...

#include <PointCloud.h>

Inheritance diagram for open3d::t::geometry::PointCloud:

Public Member Functions
	PointCloud (const core::Device &device=core::Device("CPU:0"))

	PointCloud (const core::Tensor &points)

	PointCloud (const std::unordered_map< std::string, core::Tensor > &map_keys_to_tensors)

virtual	~PointCloud () override

std::string	ToString () const
	Text description. More...

const TensorMap &	GetPointAttr () const
	Getter for point_attr_ TensorMap. Used in Pybind. More...

TensorMap &	GetPointAttr ()
	Getter for point_attr_ TensorMap. More...

core::Tensor &	GetPointAttr (const std::string &key)

core::Tensor &	GetPointPositions ()
	Get the value of the "positions" attribute. Convenience function. More...

core::Tensor &	GetPointColors ()
	Get the value of the "colors" attribute. Convenience function. More...

core::Tensor &	GetPointNormals ()
	Get the value of the "normals" attribute. Convenience function. More...

const core::Tensor &	GetPointAttr (const std::string &key) const

const core::Tensor &	GetPointPositions () const
	Get the value of the "positions" attribute. Convenience function. More...

const core::Tensor &	GetPointColors () const
	Get the value of the "colors" attribute. Convenience function. More...

const core::Tensor &	GetPointNormals () const
	Get the value of the "normals" attribute. Convenience function. More...

void	SetPointAttr (const std::string &key, const core::Tensor &value)

void	SetPointPositions (const core::Tensor &value)
	Set the value of the "positions" attribute. Convenience function. More...

void	SetPointColors (const core::Tensor &value)
	Set the value of the "colors" attribute. Convenience function. More...

void	SetPointNormals (const core::Tensor &value)
	Set the value of the "normals" attribute. Convenience function. More...

bool	HasPointAttr (const std::string &key) const

void	RemovePointAttr (const std::string &key)

bool	HasPointPositions () const

bool	HasPointColors () const

bool	HasPointNormals () const

PointCloud	To (const core::Device &device, bool copy=false) const

PointCloud	Clone () const
	Returns copy of the point cloud on the same device. More...

PointCloud &	Clear () override
	Clear all data in the point cloud. More...

bool	IsEmpty () const override
	Returns !HasPointPositions(). More...

core::Tensor	GetMinBound () const
	Returns the min bound for point coordinates. More...

core::Tensor	GetMaxBound () const
	Returns the max bound for point coordinates. More...

core::Tensor	GetCenter () const
	Returns the center for point coordinates. More...

PointCloud	Append (const PointCloud &other) const

PointCloud	operator+ (const PointCloud &other) const

PointCloud &	Transform (const core::Tensor &transformation)
	Transforms the PointPositions and PointNormals (if exist) of the PointCloud. More...

PointCloud &	Translate (const core::Tensor &translation, bool relative=true)
	Translates the PointPositions of the PointCloud. More...

PointCloud &	Scale (double scale, const core::Tensor &center)
	Scales the PointPositions of the PointCloud. More...

PointCloud &	Rotate (const core::Tensor &R, const core::Tensor &center)
	Rotates the PointPositions and PointNormals (if exists). More...

PointCloud &	PaintUniformColor (const core::Tensor &color)
	Assigns uniform color to the point cloud. More...

PointCloud	SelectByMask (const core::Tensor &boolean_mask, bool invert=false) const
	Select points from input pointcloud, based on boolean mask indices into output point cloud. More...

PointCloud	SelectByIndex (const core::Tensor &indices, bool invert=false, bool remove_duplicates=false) const
	Select points from input pointcloud, based on indices list into output point cloud. More...

PointCloud	VoxelDownSample (double voxel_size, const core::HashBackendType &backend=core::HashBackendType::Default) const
	Downsamples a point cloud with a specified voxel size. More...

PointCloud	UniformDownSample (size_t every_k_points) const
	Downsamples a point cloud by selecting every kth index point and its attributes. More...

PointCloud	RandomDownSample (double sampling_ratio) const
	Downsample a pointcloud by selecting random index point and its attributes. More...

PointCloud	FarthestPointDownSample (size_t num_samples) const
	Downsample a pointcloud into output pointcloud with a set of points has farthest distance. More...

std::tuple< PointCloud, core::Tensor >	RemoveRadiusOutliers (size_t nb_points, double search_radius) const
	Remove points that have less than `nb_points` neighbors in a sphere of a given radius. More...

std::tuple< PointCloud, core::Tensor >	RemoveStatisticalOutliers (size_t nb_neighbors, double std_ratio) const
	Remove points that are further away from their `nb_neighbor` neighbors in average. This function is not recommended to use on GPU. More...

std::tuple< PointCloud, core::Tensor >	RemoveDuplicatedPoints () const
	Remove duplicated points and there associated attributes. More...

std::tuple< PointCloud, core::Tensor >	RemoveNonFinitePoints (bool remove_nan=true, bool remove_infinite=true) const
	Remove all points from the point cloud that have a nan entry, or infinite value. It also removes the corresponding attributes. More...

core::Device	GetDevice () const override
	Returns the device attribute of this PointCloud. More...

std::tuple< TriangleMesh, core::Tensor >	HiddenPointRemoval (const core::Tensor &camera_location, double radius) const
	This is an implementation of the Hidden Point Removal operator described in Katz et. al. 'Direct Visibility of Point Sets', 2007. More...

core::Tensor	ClusterDBSCAN (double eps, size_t min_points, bool print_progress=false) const
	Cluster PointCloud using the DBSCAN algorithm Ester et al., "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise", 1996 This is a wrapper for a CPU implementation and a copy of the point cloud data and resulting labels will be made. More...

std::tuple< core::Tensor, core::Tensor >	SegmentPlane (const double distance_threshold=0.01, const int ransac_n=3, const int num_iterations=100, const double probability=0.99999999) const
	Segment PointCloud plane using the RANSAC algorithm. This is a wrapper for a CPU implementation and a copy of the point cloud data and resulting plane model and inlier indiecs will be made. More...

TriangleMesh	ComputeConvexHull (bool joggle_inputs=false) const

std::tuple< PointCloud, core::Tensor >	ComputeBoundaryPoints (double radius, int max_nn=30, double angle_threshold=90.0) const
	Compute the boundary points of a point cloud. The implementation is inspired by the PCL implementation. Reference: https://pointclouds.org/documentation/classpcl_1_1_boundary_estimation.html. More...

PointCloud &	NormalizeNormals ()
	Normalize point normals to length 1. More...

void	EstimateNormals (const utility::optional< int > max_nn=30, const utility::optional< double > radius=utility::nullopt)
	Function to estimate point normals. If the point cloud normals exist, the estimated normals are oriented with respect to the same. It uses KNN search (Not recommended to use on GPU) if only max_nn parameter is provided, Radius search (Not recommended to use on GPU) if only radius is provided and Hybrid Search (Recommended) if radius parameter is also provided. More...

void	OrientNormalsToAlignWithDirection (const core::Tensor &orientation_reference=core::Tensor::Init< float >({0, 0, 1}, core::Device("CPU:0")))
	Function to orient the normals of a point cloud. More...

void	OrientNormalsTowardsCameraLocation (const core::Tensor &camera_location=core::Tensor::Zeros({3}, core::Float32, core::Device("CPU:0")))
	Function to orient the normals of a point cloud. More...

void	OrientNormalsConsistentTangentPlane (size_t k)
	Function to consistently orient estimated normals based on consistent tangent planes as described in Hoppe et al., "Surface Reconstruction from Unorganized Points", 1992. More...

void	EstimateColorGradients (const utility::optional< int > max_nn=30, const utility::optional< double > radius=utility::nullopt)
	Function to compute point color gradients. If radius is provided, then HybridSearch is used, otherwise KNN-Search is used. Reference: Park, Q.-Y. Zhou, and V. Koltun, Colored Point Cloud Registration Revisited, ICCV, 2017. It uses KNN search (Not recommended to use on GPU) if only max_nn parameter is provided, Radius search (Not recommended to use on GPU) if only radius is provided and Hybrid Search (Recommended) if radius parameter is also provided. More...

open3d::geometry::PointCloud	ToLegacy () const
	Convert to a legacy Open3D PointCloud. More...

geometry::Image	ProjectToDepthImage (int width, int height, const core::Tensor &intrinsics, const core::Tensor &extrinsics=core::Tensor::Eye(4, core::Float32, core::Device("CPU:0")), float depth_scale=1000.0f, float depth_max=3.0f)
	Project a point cloud to a depth image. More...

geometry::RGBDImage	ProjectToRGBDImage (int width, int height, const core::Tensor &intrinsics, const core::Tensor &extrinsics=core::Tensor::Eye(4, core::Float32, core::Device("CPU:0")), float depth_scale=1000.0f, float depth_max=3.0f)
	Project a point cloud to an RGBD image. More...

AxisAlignedBoundingBox	GetAxisAlignedBoundingBox () const
	Create an axis-aligned bounding box from attribute "positions". More...

OrientedBoundingBox	GetOrientedBoundingBox () const
	Create an oriented bounding box from attribute "positions". More...

PointCloud	Crop (const AxisAlignedBoundingBox &aabb, bool invert=false) const
	Function to crop pointcloud into output pointcloud. More...

PointCloud	Crop (const OrientedBoundingBox &obb, bool invert=false) const
	Function to crop pointcloud into output pointcloud. More...

LineSet	ExtrudeRotation (double angle, const core::Tensor &axis, int resolution=16, double translation=0.0, bool capping=true) const

LineSet	ExtrudeLinear (const core::Tensor &vector, double scale=1.0, bool capping=true) const

int	PCAPartition (int max_points)

Public Member Functions inherited from open3d::t::geometry::Geometry
virtual	~Geometry ()

GeometryType	GetGeometryType () const
	Returns one of registered geometry types. More...

int	Dimension () const
	Returns whether the geometry is 2D or 3D. More...

std::string	GetName () const

void	SetName (const std::string &name)

Public Member Functions inherited from open3d::core::IsDevice
	IsDevice ()=default

virtual	~IsDevice ()=default

bool	IsCPU () const

bool	IsCUDA () const

Public Member Functions inherited from open3d::t::geometry::DrawableGeometry
	DrawableGeometry ()

	~DrawableGeometry ()

bool	HasMaterial () const
	Check if a material has been applied to this Geometry with SetMaterial. More...

visualization::rendering::Material &	GetMaterial ()
	Get material associated with this Geometry. More...

const visualization::rendering::Material &	GetMaterial () const
	Get const reference to material associated with this Geometry. More...

void	SetMaterial (const visualization::rendering::Material &material)
	Set the material properties associate with this Geometry. More...

Static Public Member Functions
static PointCloud	CreateFromDepthImage (const Image &depth, const core::Tensor &intrinsics, const core::Tensor &extrinsics=core::Tensor::Eye(4, core::Float32, core::Device("CPU:0")), float depth_scale=1000.0f, float depth_max=3.0f, int stride=1, bool with_normals=false)
	Factory function to create a point cloud from a depth image and a camera model. More...

static PointCloud	CreateFromRGBDImage (const RGBDImage &rgbd_image, const core::Tensor &intrinsics, const core::Tensor &extrinsics=core::Tensor::Eye(4, core::Float32, core::Device("CPU:0")), float depth_scale=1000.0f, float depth_max=3.0f, int stride=1, bool with_normals=false)
	Factory function to create a point cloud from an RGB-D image and a camera model. More...

static PointCloud	FromLegacy (const open3d::geometry::PointCloud &pcd_legacy, core::Dtype dtype=core::Float32, const core::Device &device=core::Device("CPU:0"))
	Create a PointCloud from a legacy Open3D PointCloud. More...

Protected Attributes
core::Device	device_ = core::Device("CPU:0")

TensorMap	point_attr_

Additional Inherited Members
Public Types inherited from open3d::t::geometry::Geometry
enum class	GeometryType { Unspecified = 0 , PointCloud = 1 , VoxelGrid = 2 , Octree = 3 , LineSet = 4 , MeshBase = 5 , TriangleMesh = 6 , HalfEdgeTriangleMesh = 7 , Image = 8 , RGBDImage = 9 , TetraMesh = 10 , OrientedBoundingBox = 11 , AxisAlignedBoundingBox = 12 }
	Specifies possible geometry types. More...

Protected Member Functions inherited from open3d::t::geometry::Geometry
	Geometry (GeometryType type, int dimension)
	Parameterized Constructor. More...

Detailed Description

A point cloud contains a list of 3D points.

The point cloud class stores the attribute data in key-value maps, where the key is a string representing the attribute name and the value is a Tensor containing the attribute data. In most cases, the length of an attribute should be equal to the length of the point cloud's "positions".

Default attribute: "positions".
- Usage
  - PointCloud::GetPointPositions()
  - PointCloud::SetPointPositions(const Tensor& positions)
  - PointCloud::HasPointPositions()
- Created by default, required for all pointclouds.
- Value tensor must have shape {N, 3}.
- The device of "positions" determines the device of the point cloud.
Common attributes: "normals", "colors".
- Usage
  - PointCloud::GetPointNormals()
  - PointCloud::SetPointNormals(const Tensor& normals)
  - PointCloud::HasPointNormals()
  - PointCloud::GetPointColors()
  - PointCloud::SetPointColors(const Tensor& colors)
  - PointCloud::HasPointColors()
- Not created by default.
- Value tensor must have shape {N, 3}.
- Value tensor must be on the same device as the point cloud.
- Value tensor can have any dtype.
Custom attributes, e.g., "labels", "intensities".
- Usage
  - PointCloud::GetPointAttr(const std::string& key)
  - PointCloud::SetPointAttr(const std::string& key, const Tensor& value)
  - PointCloud::HasPointAttr(const std::string& key)
- Not created by default. Users can add their own custom attributes.
- Value tensor must be on the same device as the point cloud.
- Value tensor can have any dtype.

PointCloud::GetPointAttr(), PointCloud::SetPointAttr(), PointCloud::HasPointAttr() also work for default attribute "position" and common attributes "normals" and "colors", e.g.,

PointCloud::GetPointPositions() is the same as PointCloud::GetPointAttr("positions")
PointCloud::HasPointNormals() is the same as PointCloud::HasPointAttr("normals")

Constructor & Destructor Documentation

◆ PointCloud() [1/3]

open3d::t::geometry::PointCloud::PointCloud ( const core::Device & device = core::Device("CPU:0") )

Construct an empty point cloud on the provided device.

Parameters

device The device on which to initialize the point cloud (default: 'CPU:0').

◆ PointCloud() [2/3]

open3d::t::geometry::PointCloud::PointCloud ( const core::Tensor & points )

Construct a point cloud from points.

The input tensor will be directly used as the underlying storage of the point cloud (no memory copy).

Parameters

points A tensor with element shape {3}.

◆ PointCloud() [3/3]

open3d::t::geometry::PointCloud::PointCloud ( const std::unordered_map< std::string, core::Tensor > & map_keys_to_tensors )

Construct from points and other attributes of the points.

Parameters

map_keys_to_tensors A map of string to Tensor containing points and their attributes. point_dict must contain at least the "positions" key.

◆ ~PointCloud()

virtual open3d::t::geometry::PointCloud::~PointCloud ( )

inlineoverridevirtual

Member Function Documentation

◆ Append()

PointCloud open3d::t::geometry::PointCloud::Append ( const PointCloud & other ) const

Append a point cloud and returns the resulting point cloud.

The point cloud being appended, must have all the attributes present in the point cloud it is being appended to, with same dtype, device and same shape other than the first dimension / length.

◆ Clear()

PointCloud& open3d::t::geometry::PointCloud::Clear ( )

inlineoverridevirtual

Clear all data in the point cloud.

Implements open3d::t::geometry::Geometry.

◆ Clone()

PointCloud open3d::t::geometry::PointCloud::Clone ( ) const

Returns copy of the point cloud on the same device.

◆ ClusterDBSCAN()

core::Tensor open3d::t::geometry::PointCloud::ClusterDBSCAN	(	double	eps,
		size_t	min_points,
		bool	print_progress = `false`
	)		const

Cluster PointCloud using the DBSCAN algorithm Ester et al., "A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise", 1996 This is a wrapper for a CPU implementation and a copy of the point cloud data and resulting labels will be made.

Parameters

eps	Density parameter that is used to find neighbouring points.
min_points	Minimum number of points to form a cluster.
print_progress	If `true` the progress is visualized in the console.

Returns: A Tensor list of point labels on the same device as the point cloud, -1 indicates noise according to the algorithm.

◆ ComputeBoundaryPoints()

std::tuple< PointCloud, core::Tensor > open3d::t::geometry::PointCloud::ComputeBoundaryPoints	(	double	radius,
		int	max_nn = `30`,
		double	angle_threshold = `90.0`
	)		const

Compute the boundary points of a point cloud. The implementation is inspired by the PCL implementation. Reference: https://pointclouds.org/documentation/classpcl_1_1_boundary_estimation.html.

Parameters

radius	Neighbor search radius parameter.
max_nn	Neighbor search max neighbors parameter [Default = 30].
angle_threshold	Angle threshold to decide if a point is on the boundary [Default = 90.0].

Returns: Tensor of boundary points and its boolean mask tensor.

◆ ComputeConvexHull()

TriangleMesh open3d::t::geometry::PointCloud::ComputeConvexHull ( bool joggle_inputs = false ) const

Compute the convex hull of a point cloud using qhull.

This runs on the CPU.

Parameters

joggle_inputs (default False). Handle precision problems by randomly perturbing the input data. Set to True if perturbing the input iis acceptable but you need convex simplicial output. If False, neighboring facets may be merged in case of precision problems. See QHull docs for more details.

Returns: TriangleMesh representing the convexh hull. This contains an extra vertex property "point_map" that contains the index of the corresponding vertex in the original mesh.

◆ CreateFromDepthImage()

PointCloud open3d::t::geometry::PointCloud::CreateFromDepthImage	(	const Image &	depth,
		const core::Tensor &	intrinsics,
		const core::Tensor &	extrinsics = `core::Tensor::Eye(4, core::Float32, core::Device("CPU:0"))`,
		float	depth_scale = `1000.0f`,
		float	depth_max = `3.0f`,
		int	stride = `1`,
		bool	with_normals = `false`
	)

static

Factory function to create a point cloud from a depth image and a camera model.

Given depth value d at (u, v) image coordinate, the corresponding 3d point is:

z = d / depth_scale
x = (u - cx) * z / fx
y = (v - cy) * z / fy

Parameters

depth	The input depth image should be a uint16_t or float image.
intrinsics	Intrinsic parameters of the camera.
extrinsics	Extrinsic parameters of the camera.
depth_scale	The depth is scaled by 1 / `depth_scale`.
depth_max	Truncated at `depth_max` distance.
stride	Sampling factor to support coarse point cloud extraction. Unless `with_normals=true`, there is no low pass filtering, so aliasing is possible for `stride>1`.
with_normals	Also compute normals for the point cloud. If True, the point cloud will only contain points with valid normals. If normals are requested, the depth map is first filtered to ensure smooth normals.

Returns: Created point cloud with the 'points' property set. Thus is empty if the conversion fails.

◆ CreateFromRGBDImage()

PointCloud open3d::t::geometry::PointCloud::CreateFromRGBDImage	(	const RGBDImage &	rgbd_image,
		const core::Tensor &	intrinsics,
		const core::Tensor &	extrinsics = `core::Tensor::Eye(4, core::Float32, core::Device("CPU:0"))`,
		float	depth_scale = `1000.0f`,
		float	depth_max = `3.0f`,
		int	stride = `1`,
		bool	with_normals = `false`
	)

static

Factory function to create a point cloud from an RGB-D image and a camera model.

Given depth value d at (u, v) image coordinate, the corresponding 3d point is:

z = d / depth_scale
x = (u - cx) * z / fx
y = (v - cy) * z / fy

Parameters

rgbd_image	The input RGBD image should have a uint16_t or float depth image and RGB image with any DType and the same size.
intrinsics	Intrinsic parameters of the camera.
extrinsics	Extrinsic parameters of the camera.
depth_scale	The depth is scaled by 1 / `depth_scale`.
depth_max	Truncated at `depth_max` distance.
stride	Sampling factor to support coarse point cloud extraction. Unless `with_normals=true`, there is no low pass filtering, so aliasing is possible for `stride>1`.
with_normals	Also compute normals for the point cloud. If True, the point cloud will only contain points with valid normals. If normals are requested, the depth map is first filtered to ensure smooth normals.

Returns: Created point cloud with the 'points' and 'colors' properties set. This is empty if the conversion fails.

◆ Crop() [1/2]

PointCloud open3d::t::geometry::PointCloud::Crop	(	const AxisAlignedBoundingBox &	aabb,
		bool	invert = `false`
	)		const

Function to crop pointcloud into output pointcloud.

Parameters

aabb	AxisAlignedBoundingBox to crop points.
invert	Crop the points outside of the bounding box or inside of the bounding box.

◆ Crop() [2/2]

PointCloud open3d::t::geometry::PointCloud::Crop	(	const OrientedBoundingBox &	obb,
		bool	invert = `false`
	)		const

Function to crop pointcloud into output pointcloud.

Parameters

obb	OrientedBoundingBox to crop points.
invert	Crop the points outside of the bounding box or inside of the bounding box.

◆ EstimateColorGradients()

void open3d::t::geometry::PointCloud::EstimateColorGradients	(	const utility::optional< int >	max_nn = `30`,
		const utility::optional< double >	radius = `utility::nullopt`
	)

Function to compute point color gradients. If radius is provided, then HybridSearch is used, otherwise KNN-Search is used. Reference: Park, Q.-Y. Zhou, and V. Koltun, Colored Point Cloud Registration Revisited, ICCV, 2017. It uses KNN search (Not recommended to use on GPU) if only max_nn parameter is provided, Radius search (Not recommended to use on GPU) if only radius is provided and Hybrid Search (Recommended) if radius parameter is also provided.

Parameters

max_nn	[optional] Neighbor search max neighbors parameter [Default = 30].
radius	[optional] Neighbor search radius parameter to use HybridSearch. [Recommended ~1.4x voxel size].

◆ EstimateNormals()

void open3d::t::geometry::PointCloud::EstimateNormals	(	const utility::optional< int >	max_nn = `30`,
		const utility::optional< double >	radius = `utility::nullopt`
	)

Function to estimate point normals. If the point cloud normals exist, the estimated normals are oriented with respect to the same. It uses KNN search (Not recommended to use on GPU) if only max_nn parameter is provided, Radius search (Not recommended to use on GPU) if only radius is provided and Hybrid Search (Recommended) if radius parameter is also provided.

Parameters

max_nn	[optional] Neighbor search max neighbors parameter [Default = 30].
radius	[optional] Neighbor search radius parameter. [Recommended ~1.4x voxel size].

◆ ExtrudeLinear()

LineSet open3d::t::geometry::PointCloud::ExtrudeLinear	(	const core::Tensor &	vector,
		double	scale = `1.0`,
		bool	capping = `true`
	)		const

Sweeps the point cloud along a direction vector.

Parameters

vector	The direction vector.
scale	Scalar factor which essentially scales the direction vector.
capping	If true adds caps to the mesh.

Returns: A line set with the result of the sweep operation.

◆ ExtrudeRotation()

LineSet open3d::t::geometry::PointCloud::ExtrudeRotation	(	double	angle,
		const core::Tensor &	axis,
		int	resolution = `16`,
		double	translation = `0.0`,
		bool	capping = `true`
	)		const

Sweeps the point cloud rotationally about an axis.

Parameters

angle	The rotation angle in degree.
axis	The rotation axis.
resolution	The resolution defines the number of intermediate sweeps about the rotation axis.
translation	The translation along the rotation axis.
capping	If true adds caps to the mesh.

Returns: A line set with the result of the sweep operation.

◆ FarthestPointDownSample()

PointCloud open3d::t::geometry::PointCloud::FarthestPointDownSample ( size_t num_samples ) const

Downsample a pointcloud into output pointcloud with a set of points has farthest distance.

The sampling is performed by selecting the farthest point from previous selected points iteratively.

Parameters

num_samples Number of points to be sampled.

◆ FromLegacy()

PointCloud open3d::t::geometry::PointCloud::FromLegacy	(	const open3d::geometry::PointCloud &	pcd_legacy,
		core::Dtype	dtype = `core::Float32`,
		const core::Device &	device = `core::Device("CPU:0")`
	)

static

Create a PointCloud from a legacy Open3D PointCloud.

◆ GetAxisAlignedBoundingBox()

AxisAlignedBoundingBox open3d::t::geometry::PointCloud::GetAxisAlignedBoundingBox ( ) const

Create an axis-aligned bounding box from attribute "positions".

◆ GetCenter()

core::Tensor open3d::t::geometry::PointCloud::GetCenter ( ) const

Returns the center for point coordinates.

◆ GetDevice()

core::Device open3d::t::geometry::PointCloud::GetDevice ( ) const

inlineoverridevirtual

Returns the device attribute of this PointCloud.

Implements open3d::t::geometry::Geometry.

◆ GetMaxBound()

core::Tensor open3d::t::geometry::PointCloud::GetMaxBound ( ) const

Returns the max bound for point coordinates.

◆ GetMinBound()

core::Tensor open3d::t::geometry::PointCloud::GetMinBound ( ) const

Returns the min bound for point coordinates.

◆ GetOrientedBoundingBox()

OrientedBoundingBox open3d::t::geometry::PointCloud::GetOrientedBoundingBox ( ) const

Create an oriented bounding box from attribute "positions".

◆ GetPointAttr() [1/4]

TensorMap& open3d::t::geometry::PointCloud::GetPointAttr ( )

inline

Getter for point_attr_ TensorMap.

◆ GetPointAttr() [2/4]

const TensorMap& open3d::t::geometry::PointCloud::GetPointAttr ( ) const

inline

Getter for point_attr_ TensorMap. Used in Pybind.

◆ GetPointAttr() [3/4]

core::Tensor& open3d::t::geometry::PointCloud::GetPointAttr ( const std::string & key )

inline

Get attributes. Throws exception if the attribute does not exist.

Parameters

key	Attribute name.

◆ GetPointAttr() [4/4]

const core::Tensor& open3d::t::geometry::PointCloud::GetPointAttr ( const std::string & key ) const

inline

Get attributes. Throws exception if the attribute does not exist.

Parameters

key	Attribute name.

◆ GetPointColors() [1/2]

core::Tensor& open3d::t::geometry::PointCloud::GetPointColors ( )

inline

Get the value of the "colors" attribute. Convenience function.

◆ GetPointColors() [2/2]

const core::Tensor& open3d::t::geometry::PointCloud::GetPointColors ( ) const

inline

Get the value of the "colors" attribute. Convenience function.

◆ GetPointNormals() [1/2]

core::Tensor& open3d::t::geometry::PointCloud::GetPointNormals ( )

inline

Get the value of the "normals" attribute. Convenience function.

◆ GetPointNormals() [2/2]

const core::Tensor& open3d::t::geometry::PointCloud::GetPointNormals ( ) const

inline

Get the value of the "normals" attribute. Convenience function.

◆ GetPointPositions() [1/2]

core::Tensor& open3d::t::geometry::PointCloud::GetPointPositions ( )

inline

Get the value of the "positions" attribute. Convenience function.

◆ GetPointPositions() [2/2]

const core::Tensor& open3d::t::geometry::PointCloud::GetPointPositions ( ) const

inline

Get the value of the "positions" attribute. Convenience function.

◆ HasPointAttr()

bool open3d::t::geometry::PointCloud::HasPointAttr ( const std::string & key ) const

inline

Returns true if all of the following are true: 1) attribute key exist 2) attribute's length as points' length 3) attribute's length > 0

◆ HasPointColors()

bool open3d::t::geometry::PointCloud::HasPointColors ( ) const

inline

Returns true if all of the following are true: 1) attribute "colors" exist 2) attribute "colors"'s length as points' length 3) attribute "colors"'s length > 0 This is a convenience function.

◆ HasPointNormals()

bool open3d::t::geometry::PointCloud::HasPointNormals ( ) const

inline

Returns true if all of the following are true: 1) attribute "normals" exist 2) attribute "normals"'s length as points' length 3) attribute "normals"'s length > 0 This is a convenience function.

◆ HasPointPositions()

bool open3d::t::geometry::PointCloud::HasPointPositions ( ) const

inline

Check if the "positions" attribute's value has length > 0. This is a convenience function.

◆ HiddenPointRemoval()

std::tuple< TriangleMesh, core::Tensor > open3d::t::geometry::PointCloud::HiddenPointRemoval	(	const core::Tensor &	camera_location,
		double	radius
	)		const

This is an implementation of the Hidden Point Removal operator described in Katz et. al. 'Direct Visibility of Point Sets', 2007.

Additional information about the choice of radius for noisy point clouds can be found in Mehra et. al. 'Visibility of Noisy Point Cloud Data', 2010.

This is a wrapper for a CPU implementation and a copy of the point cloud data and resulting visible triangle mesh and indiecs will be made.

Parameters

camera_location	All points not visible from that location will be removed.
radius	The radius of the spherical projection.

Returns: Tuple of visible triangle mesh and indices of visible points on the same device as the point cloud.

◆ IsEmpty()

bool open3d::t::geometry::PointCloud::IsEmpty ( ) const

inlineoverridevirtual

Returns !HasPointPositions().

Implements open3d::t::geometry::Geometry.

◆ NormalizeNormals()

PointCloud & open3d::t::geometry::PointCloud::NormalizeNormals ( )

Normalize point normals to length 1.

◆ operator+()

PointCloud open3d::t::geometry::PointCloud::operator+ ( const PointCloud & other ) const

inline

operator+ for t::PointCloud appends the compatible attributes to the point cloud.

◆ OrientNormalsConsistentTangentPlane()

void open3d::t::geometry::PointCloud::OrientNormalsConsistentTangentPlane ( size_t k )

Function to consistently orient estimated normals based on consistent tangent planes as described in Hoppe et al., "Surface Reconstruction from Unorganized Points", 1992.

Parameters

k	k nearest neighbour for graph reconstruction for normal propagation.

◆ OrientNormalsToAlignWithDirection()

void open3d::t::geometry::PointCloud::OrientNormalsToAlignWithDirection ( const core::Tensor & orientation_reference = core::Tensor::Init<float>({0, 0, 1}, core::Device("CPU:0")) )

Function to orient the normals of a point cloud.

Parameters

orientation_reference Normals are oriented with respect to orientation_reference.

◆ OrientNormalsTowardsCameraLocation()

void open3d::t::geometry::PointCloud::OrientNormalsTowardsCameraLocation ( const core::Tensor & camera_location = core::Tensor::Zeros( {3}, core::Float32, core::Device("CPU:0")) )

Function to orient the normals of a point cloud.

Parameters

camera_location Normals are oriented with towards the camera_location.

◆ PaintUniformColor()

PointCloud & open3d::t::geometry::PointCloud::PaintUniformColor ( const core::Tensor & color )

Assigns uniform color to the point cloud.

Parameters

color RGB color for the point cloud. {3,} shaped Tensor. Floating color values are clipped between 0.0 and 1.0.

◆ PCAPartition()

int open3d::t::geometry::PointCloud::PCAPartition ( int max_points )

Partition the point cloud by recursively doing PCA. This function creates a new point attribute with the name "partition_ids".

Parameters

max_points The maximum allowed number of points in a partition.

Returns: The number of partitions.

◆ ProjectToDepthImage()

geometry::Image open3d::t::geometry::PointCloud::ProjectToDepthImage	(	int	width,
		int	height,
		const core::Tensor &	intrinsics,
		const core::Tensor &	extrinsics = `core::Tensor::Eye(4, core::Float32, core::Device("CPU:0"))`,
		float	depth_scale = `1000.0f`,
		float	depth_max = `3.0f`
	)

Project a point cloud to a depth image.

◆ ProjectToRGBDImage()

geometry::RGBDImage open3d::t::geometry::PointCloud::ProjectToRGBDImage	(	int	width,
		int	height,
		const core::Tensor &	intrinsics,
		const core::Tensor &	extrinsics = `core::Tensor::Eye(4, core::Float32, core::Device("CPU:0"))`,
		float	depth_scale = `1000.0f`,
		float	depth_max = `3.0f`
	)

Project a point cloud to an RGBD image.

◆ RandomDownSample()

PointCloud open3d::t::geometry::PointCloud::RandomDownSample ( double sampling_ratio ) const

Downsample a pointcloud by selecting random index point and its attributes.

Parameters

sampling_ratio Sampling ratio, the ratio of sample to total number of points in the pointcloud.

◆ RemoveDuplicatedPoints()

std::tuple< PointCloud, core::Tensor > open3d::t::geometry::PointCloud::RemoveDuplicatedPoints ( ) const

Remove duplicated points and there associated attributes.

Returns: Tuple of filtered PointCloud and boolean indexing tensor w.r.t. input point cloud.

◆ RemoveNonFinitePoints()

std::tuple< PointCloud, core::Tensor > open3d::t::geometry::PointCloud::RemoveNonFinitePoints	(	bool	remove_nan = `true`,
		bool	remove_infinite = `true`
	)		const

Remove all points from the point cloud that have a nan entry, or infinite value. It also removes the corresponding attributes.

Parameters

remove_nan	Remove NaN values from the PointCloud.
remove_infinite	Remove infinite values from the PointCloud.

Returns: Tuple of filtered point cloud and boolean mask tensor for selected values w.r.t. input point cloud.

◆ RemovePointAttr()

void open3d::t::geometry::PointCloud::RemovePointAttr ( const std::string & key )

inline

Removes point attribute by key value. Primary attribute "positions" cannot be removed. Throws warning if attribute key does not exists.

Parameters

key	Attribute name.

◆ RemoveRadiusOutliers()

std::tuple< PointCloud, core::Tensor > open3d::t::geometry::PointCloud::RemoveRadiusOutliers	(	size_t	nb_points,
		double	search_radius
	)		const

Remove points that have less than nb_points neighbors in a sphere of a given radius.

Parameters

nb_points	Number of neighbor points required within the radius.
search_radius	Radius of the sphere.

Returns: Tuple of filtered point cloud and boolean mask tensor for selected values w.r.t. input point cloud.

◆ RemoveStatisticalOutliers()

std::tuple< PointCloud, core::Tensor > open3d::t::geometry::PointCloud::RemoveStatisticalOutliers	(	size_t	nb_neighbors,
		double	std_ratio
	)		const

Remove points that are further away from their nb_neighbor neighbors in average. This function is not recommended to use on GPU.

Parameters

nb_neighbors	Number of neighbors around the target point.
std_ratio	Standard deviation ratio.

Returns: Tuple of filtered point cloud and boolean mask tensor for selected values w.r.t. input point cloud.

◆ Rotate()

PointCloud & open3d::t::geometry::PointCloud::Rotate	(	const core::Tensor &	R,
		const core::Tensor &	center
	)

Rotates the PointPositions and PointNormals (if exists).

Parameters

R	Rotation [Tensor of dim {3,3}]. Should be on the same device as the PointCloud
center	Center [Tensor of dim {3}] about which the PointCloud is to be scaled. Should be on the same device as the PointCloud

Returns: Rotated point cloud

◆ Scale()

PointCloud & open3d::t::geometry::PointCloud::Scale	(	double	scale,
		const core::Tensor &	center
	)

Scales the PointPositions of the PointCloud.

Parameters

scale	Scale [double] of dimension
center	Center [Tensor of dim {3}] about which the PointCloud is to be scaled. Should be on the same device as the PointCloud

Returns: Scaled point cloud

◆ SegmentPlane()

std::tuple< core::Tensor, core::Tensor > open3d::t::geometry::PointCloud::SegmentPlane	(	const double	distance_threshold = `0.01`,
		const int	ransac_n = `3`,
		const int	num_iterations = `100`,
		const double	probability = `0.99999999`
	)		const

Segment PointCloud plane using the RANSAC algorithm. This is a wrapper for a CPU implementation and a copy of the point cloud data and resulting plane model and inlier indiecs will be made.

Parameters

distance_threshold	Max distance a point can be from the plane model, and still be considered an inlier.
ransac_n	Number of initial points to be considered inliers in each iteration.
num_iterations	Maximum number of iterations.
probability	Expected probability of finding the optimal plane.

Returns: Tuple of the plane model ax + by + cz + d = 0 and the indices of the plane inliers on the same device as the point cloud.

◆ SelectByIndex()

PointCloud open3d::t::geometry::PointCloud::SelectByIndex	(	const core::Tensor &	indices,
		bool	invert = `false`,
		bool	remove_duplicates = `false`
	)		const

Select points from input pointcloud, based on indices list into output point cloud.

Parameters

indices	Int64 indexing tensor of shape {n,} containing index value that is to be selected.
invert	Set to `True` to invert the selection of indices, and also ignore the duplicated indices.
remove_duplicates	Set to `True` to remove the duplicated indices.

◆ SelectByMask()

PointCloud open3d::t::geometry::PointCloud::SelectByMask	(	const core::Tensor &	boolean_mask,
		bool	invert = `false`
	)		const

Select points from input pointcloud, based on boolean mask indices into output point cloud.

Parameters

boolean_mask	Boolean indexing tensor of shape {n,} containing true value for the indices that is to be selected.
invert	Set to `True` to invert the selection of indices.

◆ SetPointAttr()

void open3d::t::geometry::PointCloud::SetPointAttr	(	const std::string &	key,
		const core::Tensor &	value
	)

inline

Set attributes. If the attribute key already exists, its value will be overwritten, otherwise, the new key will be created.

Parameters

key	Attribute name.
value	A tensor.

◆ SetPointColors()

void open3d::t::geometry::PointCloud::SetPointColors ( const core::Tensor & value )

inline

Set the value of the "colors" attribute. Convenience function.

◆ SetPointNormals()

void open3d::t::geometry::PointCloud::SetPointNormals ( const core::Tensor & value )

inline

Set the value of the "normals" attribute. Convenience function.

◆ SetPointPositions()

void open3d::t::geometry::PointCloud::SetPointPositions ( const core::Tensor & value )

inline

Set the value of the "positions" attribute. Convenience function.

◆ To()

PointCloud open3d::t::geometry::PointCloud::To	(	const core::Device &	device,
		bool	copy = `false`
	)		const

Transfer the point cloud to a specified device.

Parameters

device	The targeted device to convert to.
copy	If true, a new point cloud is always created; if false, the copy is avoided when the original point cloud is already on the targeted device.

◆ ToLegacy()

open3d::geometry::PointCloud open3d::t::geometry::PointCloud::ToLegacy ( ) const

Convert to a legacy Open3D PointCloud.

◆ ToString()

std::string open3d::t::geometry::PointCloud::ToString ( ) const

Text description.

◆ Transform()

PointCloud & open3d::t::geometry::PointCloud::Transform ( const core::Tensor & transformation )

Transforms the PointPositions and PointNormals (if exist) of the PointCloud.

Transformation matrix is a 4x4 matrix. T (4x4) = [[ R(3x3) t(3x1) ], [ O(1x3) s(1x1) ]] (s = 1 for Transformation without scaling)

It applies the following general transform to each positions and normals. |x'| | R(0,0) R(0,1) R(0,2) t(0)| |x| |y'| = | R(1,0) R(1,1) R(1,2) t(1)| @ |y| |z'| | R(2,0) R(2,1) R(2,2) t(2)| |z| |w'| | O(0,0) O(0,1) O(0,2) s | |1|

[x, y, z] = [x', y', z'] / w'

Parameters

transformation Transformation [Tensor of dim {4,4}].

Returns: Transformed point cloud

◆ Translate()

PointCloud & open3d::t::geometry::PointCloud::Translate	(	const core::Tensor &	translation,
		bool	relative = `true`
	)

Translates the PointPositions of the PointCloud.

Parameters

translation	translation tensor of dimension {3} Should be on the same device as the PointCloud
relative	if true (default): translates relative to Center

Returns: Translated point cloud

◆ UniformDownSample()

PointCloud open3d::t::geometry::PointCloud::UniformDownSample ( size_t every_k_points ) const

Downsamples a point cloud by selecting every kth index point and its attributes.

Parameters

every_k_points Sample rate, the selected point indices are [0, k, 2k, …].

◆ VoxelDownSample()

PointCloud open3d::t::geometry::PointCloud::VoxelDownSample	(	double	voxel_size,
		const core::HashBackendType &	backend = `core::HashBackendType::Default`
	)		const

Downsamples a point cloud with a specified voxel size.

Parameters

voxel_size Voxel size. A positive number.

Field Documentation

◆ device_

core::Device open3d::t::geometry::PointCloud::device_ = core::Device("CPU:0")

protected

◆ point_attr_

TensorMap open3d::t::geometry::PointCloud::point_attr_

protected

The documentation for this class was generated from the following files:

/home/runner/work/Open3D/Open3D/cpp/open3d/t/geometry/PointCloud.h (9238339 (Tue Mar 14 18:49:09 2023 -0700))
/home/runner/work/Open3D/Open3D/cpp/open3d/t/geometry/PointCloud.cpp (9238339 (Tue Mar 14 18:49:09 2023 -0700))

Public Member Functions

Static Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ PointCloud() [1/3]

◆ PointCloud() [2/3]

◆ PointCloud() [3/3]

◆ ~PointCloud()

Member Function Documentation

◆ Append()

◆ Clear()

◆ Clone()

◆ ClusterDBSCAN()

◆ ComputeBoundaryPoints()

◆ ComputeConvexHull()

◆ CreateFromDepthImage()

◆ CreateFromRGBDImage()

◆ Crop() [1/2]

◆ Crop() [2/2]

◆ EstimateColorGradients()

◆ EstimateNormals()

◆ ExtrudeLinear()

◆ ExtrudeRotation()

◆ FarthestPointDownSample()

◆ FromLegacy()

◆ GetAxisAlignedBoundingBox()

◆ GetCenter()

◆ GetDevice()

◆ GetMaxBound()

◆ GetMinBound()

◆ GetOrientedBoundingBox()

◆ GetPointAttr() [1/4]

◆ GetPointAttr() [2/4]

◆ GetPointAttr() [3/4]

◆ GetPointAttr() [4/4]

◆ GetPointColors() [1/2]

◆ GetPointColors() [2/2]

◆ GetPointNormals() [1/2]

◆ GetPointNormals() [2/2]

◆ GetPointPositions() [1/2]

◆ GetPointPositions() [2/2]

◆ HasPointAttr()

◆ HasPointColors()

◆ HasPointNormals()

◆ HasPointPositions()

◆ HiddenPointRemoval()

◆ IsEmpty()

◆ NormalizeNormals()

◆ operator+()

◆ OrientNormalsConsistentTangentPlane()

◆ OrientNormalsToAlignWithDirection()

◆ OrientNormalsTowardsCameraLocation()

◆ PaintUniformColor()

◆ PCAPartition()

◆ ProjectToDepthImage()

◆ ProjectToRGBDImage()

◆ RandomDownSample()

◆ RemoveDuplicatedPoints()

◆ RemoveNonFinitePoints()

◆ RemovePointAttr()

◆ RemoveRadiusOutliers()

◆ RemoveStatisticalOutliers()

◆ Rotate()

◆ Scale()

◆ SegmentPlane()

◆ SelectByIndex()

◆ SelectByMask()

◆ SetPointAttr()

◆ SetPointColors()

◆ SetPointNormals()

◆ SetPointPositions()

◆ To()

◆ ToLegacy()

◆ ToString()

◆ Transform()

◆ Translate()

◆ UniformDownSample()

◆ VoxelDownSample()