1. cloudComPy module, functions

cloudComPy is the Python module interfacing cloudCompare library. Python3 access to cloudCompare objects is done like this:

import cloudComPy as cc 
cc.initCC()  # to do once before using plugins
cloud = cc.loadPointCloud("/home/paul/CloudComPy/Data/boule.bin")

cloudComPy.computeApproxLocalDensity(arg0: _cloudComPy.Density, arg1: float, arg2: list[_cloudComPy.ccHObject]) → bool

Computes the local density (approximate) on a list of points clouds (create a scalarField).

Old method (based only on the distance to the nearest neighbor).

Warning As only one neighbor is extracted, the DENSITY_KNN type corresponds in fact to the (inverse) distance to the nearest neighbor.

The density output can be:

the number of neighbors N (only available in ‘Precise’ mode)
a surface density: number of neighbors divided by the neighborhood surface = N / (Pi.R2)
a volume density: number of neighbors divided by the neighborhood volume = N / (4/3.Pi.R3)

Parameters:

density (Density) – from Density enum
radius (float) – try value obtained by GetPointCloudRadius().
clouds (list of ccHObject) – list of clouds

Returns:

True if OK, else False

Return type:

bool

cloudComPy.computeCurvature(arg0: _cloudComPy.CurvatureType, arg1: float, arg2: list[_cloudComPy.ccHObject]) → bool

Compute the curvature on a list of point clouds (create a scalarField).

The curvature at each point is estimated by best fitting a quadric around it. If there’s not enough neighbors to compute a quadric (i.e. less than 6) an invalid scalar value (NaN) is set for this point. This point will appear in grey (or not at all if you uncheck the ‘display NaN values in grey’ option of the scalar field parameters).

Parameters:

cvt (CurvatureType) – from CurvatureType.GAUSSIAN_CURV, CurvatureType.MEAN_CURV, CurvatureType.NORMAL_CHANGE_RATE.
radius (float) – try value obtained by GetPointCloudRadius().
clouds (list of ccHObject) – list of clouds

Returns:

True if OK, else False

Return type:

bool

cloudComPy.computeFeature(arg0: _cloudComPy.GeomFeature, arg1: float, arg2: list[_cloudComPy.ccHObject]) → bool

Compute a geometric characteristic on a list of points clouds (create a scalarField).

Geometric feature computed from eigen values/vectors. Most of them are defined in “Contour detection in unstructured 3D point clouds”, Hackel et al, 2016. PCA1 and PCA2 are defined in “3D terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: Applications in geomorphology”, Brodu and Lague, 2012.

Parameters:

feature (GeomFeature) – from GeomFeature enum
radius (float) – try value obtained by GetPointCloudRadius().
clouds (list of ccHObject) – list of clouds

Returns:

True if OK, else False

Return type:

bool

cloudComPy.computeLocalDensity(arg0: _cloudComPy.Density, arg1: float, arg2: list[_cloudComPy.ccHObject]) → bool

Computes the local density on a list of points clouds (create a scalarField).

The density output can be:

the number of neighbors N (only available in ‘Precise’ mode)
a surface density: number of neighbors divided by the neighborhood surface = N / (Pi.R2)
a volume density: number of neighbors divided by the neighborhood volume = N / (4/3.Pi.R3)

Parameters:

density (Density) – from Density enum
radius (float) – try value obtained by GetPointCloudRadius().
clouds (list of ccHObject) – list of clouds

Returns:

True if OK, else False

Return type:

bool

cloudComPy.computeMomentOrder1(arg0: float, arg1: list[_cloudComPy.ccHObject]) → bool

Computes the first order moment on a list of points clouds (create a scalarField).

Parameters:

radius (float) – try value obtained by GetPointCloudRadius().
clouds (list of ccHObject) – list of clouds

Returns:

True if OK, else False

Return type:

bool

cloudComPy.computeNormals(selectedEntities: list[_cloudComPy.ccHObject], model: _cloudComPy.LOCAL_MODEL_TYPES = <LOCAL_MODEL_TYPES.LS: 1>, useScanGridsForComputation: bool = True, defaultRadius: float = 0.0, minGridAngle_deg: float = 1.0, orientNormals: bool = True, useScanGridsForOrientation: bool = True, useSensorsForOrientation: bool = True, preferredOrientation: _cloudComPy.Orientation = <Orientation.UNDEFINED: 255>, orientNormalsMST: bool = True, mstNeighbors: int = 6, computePerVertexNormals: bool = True) → bool

Compute normals on a list of clouds and meshes.

Parameters:

selectedEntities (list of ccHObject) – list of entities (clouds, meshes)
model (LOCAL_MODEL_TYPES,optional) – default = LOCAL_MODEL_TYPES.LS (Least Square best fitting plane)
useScanGridsForComputation (bool,optional) – default True, whether to use ScanGrids when available
defaultRadius (float,optional) – default 0.0
minGridAngle_deg (float,optional) – default 1.0
orientNormals (bool,optional) – default True
useScanGridsForOrientation (bool,optional) – default True, when ScanGrids available
useSensorsForOrientation (bool,optional) – default True, when Sensors available
preferredOrientation (Orientation,optional) – default Orientation.UNDEFINED
orientNormalsMST (bool,optional) – default True, use Minimum Spanning Tree
mstNeighbors (int,optional) – default 6, for Minimum Spanning Tree
computePerVertexNormals (bool,optional) – default True, apply on mesh, if True, compute on vertices, if False, compute on triangles

Returns:

success

Return type:

bool

cloudComPy.computeRoughness(radius: float, clouds: list[_cloudComPy.ccHObject], roughnessUpDir: Vector3Tpl<T> = (0.0, 0.0, 0.0)) → bool

Computes the roughness on a list of points clouds (create a scalarField).

Roughness estimation is very… simple: for each point, the ‘roughness’ value is equal to the distance between this point and the best fitting plane computed on its nearest neighbors. If there’s not enough neighbors to compute a LS plane (i.e. less than 3) an invalid scalar value (NaN) is set for this point. This point will appear in grey (or not at all if you uncheck the ‘display NaN values in grey’ option in the scalar field properties).

Parameters:

radius (float) – try value obtained by GetPointCloudRadius().
clouds (list of ccHObject) – list of clouds
roughnessUpDir (vector,optional) – when defined, up direction allows a signed value of the roughness (up: positive, down: negative)

Returns:

True if OK, else False

Return type:

bool

cloudComPy.ComputeVolume25D(reportInfo: _cloudComPy.ReportInfoVol, ground: _cloudComPy.ccGenericPointCloud, ceil: _cloudComPy.ccGenericPointCloud, vertDim: int, gridStep: float, groundHeight: float, ceilHeight: float, projectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, groundEmptyCellFillStrategy: _cloudComPy.EmptyCellFillOption = <EmptyCellFillOption.LEAVE_EMPTY: 0>, groundMaxEdgeLength: float = 0.0, ceilEmptyCellFillStrategy: _cloudComPy.EmptyCellFillOption = <EmptyCellFillOption.LEAVE_EMPTY: 0>, ceilMaxEdgeLength: float = 0) → bool

Compute a 2.5D volume between a cloud and a ground plane,or two clouds,following a given direction (X, Y or Z).

If only one cloud is given, the direction (X, Y or Z) defines the normal to the plane used for calculation.

Parameters:

reportInfo (ReportInfoVol) – the object instance to be completed with results
ground (ccPointCloud) – either a point cloud or None
ceil (ccPointCloud) – either a point cloud or None
vertDim (int) – direction from (0,1,2): 0: X, 1: Y, 2: Z
gridStep (float) – size of the grid step
groundHeight (float) – altitude of the ground plane along the direction, if ground is None
ceilHeight (float) – altitude of the ceil plane along the direction, if ceil is None
projectionType (ProjectionType,optional) – default PROJ_AVERAGE_VALUE
groundEmptyCellFillStrategy (EmptyCellFillOption,optional) – default LEAVE_EMPTY
groundMaxEdgeLength (float,optional) – default 0
ceilEmptyCellFillStrategy (EmptyCellFillOption,optional) – default LEAVE_EMPTY
ceilMaxEdgeLength (float,optional) – default 0

Returns:

True if success, False if problem detected in parameters

Return type:

bool

cloudComPy.deleteEntity(arg0: _cloudComPy.ccHObject) → None

Delete an entity and its children (mesh, cloud…)

Warning No automatic action on the Python side on the variables referencing the C++ object!

cc.deleteEntity(anEntity)
anEntity = None

Parameters:: entity (ccHObject) – the entity to remove

cloudComPy.ExtractConnectedComponents(clouds: list[_cloudComPy.ccHObject], octreeLevel: int = 8, minComponentSize: int = 100, maxNumberComponents: int = 100, randomColors: bool = False) → tuple

Extracts connected components from a set of clouds.

There are 2 tools relative to connected components: ExtractConnectedComponents and LabelConnectedComponents. ExtractConnectedComponents Creates separate clouds and LabelConnectedComponents creates a scalar field. ExtractConnectedComponents segments the clouds in smaller parts separated by a minimum distance. Each part is a connected component (i.e. a set of ‘connected’ points). CloudCompare uses a 3D grid to extract the connected components. This grid is deduced from the octree structure. By selecting on octree level you define how small is the minimum gap between two components. If n is the octree level and d the dimension of the clouds (Bounding box side), the gap is roughly d/2**n.

Parameters:

clouds (list[ccPointCloud]) – the set of clouds
octreeLevel (int,optional) – the octree level used to define the connection between nodes, default 8.
minComponentSize (int,optional) – the minimum number of nodes to constitute a component, default 100. The residual nodes are regrouped in a “residual component” (one per input cloud).
maxNumberComponents (int,optional) – maximum number of components accepted (default 100): The process stops when this number is reached. The return gives the number of clouds already processed. Check this number to see if some clouds have not been processed.
randomColors (bool optional) – whether to color randomly the components or not, default False.

Returns:

a tuple (number of clouds processed, list of components, list of residual components)

Return type:

tuple

cloudComPy.extractPointsAlongSections(clouds: list[_cloudComPy.ccGenericPointCloud], sections: list[_cloudComPy.ccPolyline], defaultSectionThickness: float = -1.0, envelopeMaxEdgeLength: float = 0, extractSectionsAsClouds: bool = False, extractSectionsAsEnvelopes: bool = True, multipass: bool = False, splitEnvelope: bool = False, s_extractSectionsType: _cloudComPy.EnvelopeType = <EnvelopeType.ENV_LOWER: 0>, vertDim: int = 2) → list[_cloudComPy.ccHObject]

Extract clouds slices along sections or generate vertical profiles.

Either the points are kept where they are (result are clouds slices), or the points are projected on a plane formed by section and the vertical direction (result are polylines).

Parameters:

clouds (list[ccPointCloud]) – list of clouds
sections (list[ccPolyline]) – list of sections
defaultSectionThickness (double,optional) – point are kept if distance from section < defaultSectionThickness/2 default -1, meaning clouds bounding box / 500
envelopeMaxEdgeLength (double,optional) – maximum edge length for split edges operation default 0 meaning clouds bounding box / 500
extractSectionsAsClouds (bool,optional) – get the result as clouds, default False
extractSectionsAsEnvelopes (bool,optional) – get the result as polylines, default True
multipass (bool,optional) – default False
splitEnvelope (bool,optional) – default false, split envelope following clouds
EnvelopeType (int,optional) – from fCloudComPy.EnvelopeType, default ENV_LOWER
vertDim (int,optional) – vertical direction, value in O (oX), 1 (oY), 2 (oZ), default 2

Returns:

list of entities (cloud or polyline)

Return type:

list of ccPointClouds or ccPolylines

cloudComPy.ExtractSlicesAndContours(entities: list[_cloudComPy.ccHObject], bbox: _cloudComPy.ccBBox, bboxTrans: _cloudComPy.ccGLMatrix = <_cloudComPy.ccGLMatrix object at 0x14a619ff0>, singleSliceMode: bool = True, processRepeatX: bool = False, processRepeatY: bool = False, processRepeatZ: bool = True, extractEnvelopes: bool = False, maxEdgeLength: float = 0, envelopeType: int = 0, extractLevelSet: bool = False, levelSetGridStep: float = 0, levelSetMinVertCount: int = 0, gap: float = 0, multiPass: bool = False, splitEnvelopes: bool = False, projectOnBestFitPlane: bool = False, generateRandomColors: bool = False) → tuple

Extract slices, envelopes and contours from a set of clouds and meshes (Cross section).

Slices are the part of cloud or mesh contained in the bounding box used as a tool to cut. Slicing can be repeated selectively along the 3 directions X, Y, Z, with optional gaps between slices. Optional envelopes are closed polylines defining a concave external boundary of the slices. Optional contours are closed polylines defining boundaries (external and internal) of the slices. The contours are built via a rasterisation process.

Parameters:

entities (list[ccHObjects]) – the list of point clouds and meshes to slice.
bbox (ccBBox) – the bounding box used as a slice tool.
bboxTrans (ccGLMatrix,optional) – optional transformation (rotation translation) of the bounding box, default identity.
singleSliceMode (boolean,optional) – whether to cut just one slice or repeat the process, default True, i.e. only one slice.
processRepeatX (boolean,optional) – whether to repeat along the X direction (if singleSliceMode False), default False.
processRepeatY (boolean,optional) – whether to repeat along the Y direction (if singleSliceMode False), default False.
processRepeatZ (boolean,optional) – whether to repeat along the Z direction (if singleSliceMode False), default True.
extractEnvelopes (boolean,optional) – whether to extract the envelopes or not, default False.
maxEdgeLength (double,optional) – maximum edge length for the envelope, default 0=convex envelope.
envelopeType (int,optional) – type of envelope, default 0. 0: envelope built on the lower part of the slice, 1: upper part, 2: all the slice.
extractLevelSet (boolean,optional) – whether to extract contours or not, default False.
levelSetGridStep (double,optional) – grid step to use for the rasterisation needed to build the contours
levelSetMinVertCount (int,optional) – number of points required to define a contour, default 0 (change it!).
gap (double,optional) – gap between slices, default 0.
multiPass (boolean,optional) – Multi-pass process where longer edges may be temporarily created to obtain a better fit… or a worst one! Default False.
splitEnvelopes (boolean,optional) – split the generated contour(s) in smaller parts to avoid creating edges longer than the specified max edge length. Default False.
projectOnBestFitPlane (boolean,optional) – Before extracting the contour, points can be projected along the repeat dimension (if only one is defined) or on the best fit plane. Default False.
boolean,optionalgenerateRandomColors – whether to define random colors per slice (will overwrite existing colors!) or not. Default False.

Returns:

a tuple of 3 lists ([slices], [envelopes], [contours])

Return type:

tuple

cloudComPy.filterBySFValue(*args, **kwargs)

Overloaded function.

filterBySFValue(arg0: float, arg1: float, arg2: _cloudComPy.ccPointCloud) -> _cloudComPy.ccPointCloud

Create a new point cloud by filtering points using the current out ScalarField (see cloud.setCurrentOutScalarField). Keep the points whose ScalarField value is between the min and max parameters.

Parameters:

min (float) – minimum value to keep
max (float) – maximum value to keep
cloud (ccPointCloud) – the input cloud

Returns:

a ccPointCloud object.

Return type:

ccPointCloud

filterBySFValue(arg0: float, arg1: float, arg2: _cloudComPy.ccMesh) -> _cloudComPy.ccMesh

Create a new mesh by filtering points using the current out ScalarField (see getAssociatedCloud().setCurrentOutScalarField). Keep the points whose ScalarField value is between the min and max parameters.

Parameters:

min (float) – minimum value to keep
max (float) – maximum value to keep
mesh (ccMesh) – the input mesh

Returns:

a ccMesh object.

Return type:

ccMesh

cloudComPy.GetPointCloudRadius(clouds: list[_cloudComPy.ccHObject], nodes: int = 12) → float

Compute an estimate radius to use in computeCurvature.

Parameters:

clouds (list) – list of clouds(list of ccHObject)
nodes (int,optional) – number of nodes wanted within the radius, default 12

Returns:

estimated radius

Return type:

float

cloudComPy.getScalarType() → str

Get the scalar type used in cloudCompare under the form defined in Numpy: ‘float32’ or ‘float64’

Returns:: scalar type
Return type:: str

cloudComPy.ICP(data: _cloudComPy.ccHObject, model: _cloudComPy.ccHObject, minRMSDecrease: float = 1e-05, maxIterationCount: int = 20, randomSamplingLimit: int = 50000, removeFarthestPoints: bool = False, method: _cloudComPy.CONVERGENCE_TYPE = <CONVERGENCE_TYPE.MAX_ITER_CONVERGENCE: 1>, adjustScale: bool = False, finalOverlapRatio: float = 1.0, useDataSFAsWeights: bool = False, useModelSFAsWeights: bool = False, transformationFilters: int = <TRANSFORMATION_FILTERS.SKIP_NONE: 0>, maxThreadCount: int = 0, useC2MSignedDistances: bool = False, robustC2MSignedDistances: bool = True, normalMatching: _cloudComPy.normalMatching = <normalMatching.NO_NORMAL: 0>) → _cloudComPy.ICPres

Applies ICP registration on two entities.

Parameters:

data (ccHObject) – cloud to align.
model (ccHObject) – reference cloud.
minRMSDecrease (float,optional) – The minimum error (RMS) reduction between two consecutive steps to continue process, if CONVERGENCE_TYPE == MAX_ERROR_CONVERGENCE. Default 1.E-5.
maxIterationCount (int,optional) – Stop after this number of iterations, if CONVERGENCE_TYPE == MAX_ITER_CONVERGENCE. Default 20.
randomSamplingLimit (int,optional) – Limit above which clouds should be randomly resampled. Default 50000.
removeFarthestPoints (bool,optional) – If True, the algorithm will automatically ignore farthest points from the reference. This is a trick to improve registration for slightly different clouds. Default False.
method (CONVERGENCE_TYPE,optional) – Mode of convergence, CONVERGENCE_TYPE.MAX_ITER_CONVERGENCE or CONVERGENCE_TYPE.MAX_ERROR_CONVERGENCE. Default CONVERGENCE_TYPE.MAX_ITER_CONVERGENCE
adjustScale (bool) – Whether to release the scale parameter during the registration procedure or not. Default False.
finalOverlapRatio (float,optional) – Theoretical overlap ratio (at each iteration, only this percentage (between 0 and 1). Will be used for registration (default 1.0).
useDataSFAsWeights (bool,optional) – Weights for data points (default False). The scalar field must be the current SF in data (see setCurrentScalarField)
useModelSFAsWeights (bool,optional) – Weights for model points (default False). The scalar field must be the current SF in model (see setCurrentScalarField)
transformationFilters (TRANSFORMATION_FILTERS,optional) –
Filters to be applied on the resulting transformation at each step (default 0).
- SKIP_NONE = 0
- SKIP_RXY = 1
- SKIP_RYZ = 2
- SKIP_RXZ = 4
- SKIP_ROTATION = 7
- SKIP_TX = 8
- SKIP_TY = 16
- SKIP_TZ = 32
- SKIP_TRANSLATION = 56
maxThreadCount (int,optional) – Maximum number of threads to use (default 0 = max)
useC2MSignedDistances (bool,optional) – use signed distances (default False)
robustC2MSignedDistances (bool,optional) – use robust signed distances (default True)
normalMatching (normalMatching,optional) – type of normal matching, default NO_NORMAL values from (NO_NORMAL, OPPOSITE_NORMALS, SAME_SIDE_NORMALS, DOUBLE_SIDED_NORMALS)

Returns:

ICPres structure ICPres

cloudComPy.importFile(filename: str, mode: _cloudComPy.CC_SHIFT_MODE = <CC_SHIFT_MODE.AUTO: 0>, x: float = 0, y: float = 0, z: float = 0, extraData: QString = '') → tuple

Load the entities (cloud or mesh) from a file containing several entities, and get file structure (some files as .E57 provide structured information on content, given here as a list of strings).

WARNING Shift parameters are not always taken into account, depending on the type of file, shift values, following the internal rules of CloudCompare: when using the CloudCompare GUI, shift dialog at import is not always available. When the shift dialog is not proposed in the GUI, shift parameters are likely not taken into account in CloudCompare.

Optional string extraData can be used in ply file, for instance, to select extra fields for import as scalarFields (by default, all extra fields are imported as scalar fields). Here, the filter is a regular expression that works on the field name in uppercase.

Optional string extraData can also be used to filter (regular expression) the scans to import in a .E57 file (without the parameter, all the scans are imported).

Parameters:

filename (str) – file Name
mode (CC_SHIFT_MODE,optional) – default AUTO, value from AUTO, XYZ, FIRST_GLOBAL_SHIFT, NO_GLOBAL_SHIFT
x (float,optional) – default 0
y (float,optional) – default 0
z (float,optional) – default 0
extraData (string,optional) – default empty string

Returns:

a tuple (list of meshes, list of clouds, file structure)

Return type:

tuple

cloudComPy.initCC() → None: Done at module init, should be done once before using plugins!

cloudComPy.initCloudCompare() → None: Done at module init, should be done once after initCC before using plugins!

cloudComPy.interpolateScalarFieldsFrom(destCloud: _cloudComPy.ccPointCloud, srcCloud: _cloudComPy.ccPointCloud, sfIndexes: list[int], params: _cloudComPy.interpolatorParameters, octreeLevel: int = 0) → bool

Interpolate scalar fields from a source cloud to a destination cloud.

Parameters:

destCloud (ccPointCloud) – the cloud receiving the interpolatated scalar fields.
srcCloud (ccPointCloud) – the source cloud containing the scalar fields to interpolate.
sfIndexes (list) – the list of indexes of scalar fields in the source cloud, to interpolate.
params (interpolatorParameters) – interpolation parameter structure
octreeLevel (int,optional) – octree level, default 0

Returns:

success

Return type:

bool

cloudComPy.invertNormals(arg0: list[_cloudComPy.ccHObject]) → bool

Invert normals on a list of clouds and meshes.

Returns:: success
Return type:: bool

cloudComPy.isPluginCanupo() → bool

returns True if CloudComPy is built with the CANUPO plugin.

Returns:: True if CloudComPy is built with the CANUPO plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginCSF() → bool

returns True if CloudComPy is built with the CSF plugin.

Returns:: True if CloudComPy is built with the CSF plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginCork() → bool

returns True if CloudComPy is built with the Cork plugin.

Returns:: True if CloudComPy is built with the Cork plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginDraco() → bool

returns True if CloudComPy is built with the Draco plugin.

Returns:: True if CloudComPy is built with the Draco plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginFbx() → bool

returns True if CloudComPy is built with the Fbx plugin.

Returns:: True if CloudComPy is built with the Fbx plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginHPR() → bool

returns True if CloudComPy is built with the HPR plugin.

Returns:: True if CloudComPy is built with the HPR plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginM3C2() → bool

returns True if CloudComPy is built with the M3C2 plugin.

Returns:: True if CloudComPy is built with the M3C2 plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginMeshBoolean() → bool

returns True if CloudComPy is built with the MeshBoolean plugin.

Returns:: True if CloudComPy is built with the MeshBoolean plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginPCL() → bool

returns True if CloudComPy is built with the PCL plugin.

Returns:: True if CloudComPy is built with the PCL plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginPCV() → bool

returns True if CloudComPy is built with the PCV plugin.

Returns:: True if CloudComPy is built with the PCV plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginPoissonRecon() → bool

returns True if CloudComPy is built with the PoisssonRecon plugin.

Returns:: True if CloudComPy is built with the PoissonRecon plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginRANSAC_SD() → bool

returns True if CloudComPy is built with the RANSAC_SD plugin.

Returns:: True if CloudComPy is built with the RANSAC_SD plugin, False otherwise.
Return type:: bool

cloudComPy.isPluginSRA() → bool

returns True if CloudComPy is built with the SRA plugin.

Returns:: True if CloudComPy is built with the SRA plugin, False otherwise.
Return type:: bool

cloudComPy.LabelConnectedComponents(clouds: list[_cloudComPy.ccHObject], octreeLevel: int = 8) → int

Label connected components in a set of clouds.

There are 2 tools relative to connected components: ExtractConnectedComponents and LabelConnectedComponents. ExtractConnectedComponents Creates separate clouds and LabelConnectedComponents creates a scalar field in each cloud examined, assigning an integer value to each node. Nodes sharing the same value are connected and form a component. The function returns the number of components. The clouds are segmented in smaller parts separated by a minimum distance. Each part is a connected component (i.e. a set of ‘connected’ points). CloudCompare uses a 3D grid to extract the connected components. This grid is deduced from the octree structure. By selecting on octree level you define how small is the minimum gap between two components. If n is the octree level and d the dimension of the clouds (Bounding box side), the gap is roughly d/2**n.

Parameters:

clouds (list[ccPointCloud]) – the set of clouds
octreeLevel (int,optional) – the octree level used to define the connection between nodes, default 8.

Returns:

number of found connected components

Return type:

int

cloudComPy.loadMesh(filename: str, mode: _cloudComPy.CC_SHIFT_MODE = <CC_SHIFT_MODE.AUTO: 0>, skip: int = 0, x: float = 0, y: float = 0, z: float = 0, extraData: QString = '') → _cloudComPy.ccMesh

Load a Mesh from a file.

WARNING Shift parameters are not always taken into account, depending on the type of file, shift values, following the internal rules of CloudCompare: when using the CloudCompare GUI, shift dialog at import is not always available. When the shift dialog is not proposed in the GUI, shift parameters are likely not taken into account in CloudCompare.

Optional string extraData can be used in ply file, for instance, to select extra fields for import as scalarFields (by default, all extra fields are imported as scalar fields). Here, the filter is a regular expression that works on the field name in uppercase.

Parameters:

filename (str) – file name
shiftMode (CC_SHIFT_MODE,optional) –
shift mode from CC_SHIFT_MODE enum, default AUTO.
- CC_SHIFT_MODE.AUTO: automatic shift of coordinates
- CC_SHIFT_MODE.XYZ: coordinates shift given by x, y, z parameters
- CC_SHIFT_MODE.FIRST_GLOBAL_SHIFT: use the first encountered global shift value (if any)
- CC_SHIFT_MODE.NO_GLOBAL_SHIFT: no shift at all
skip (int,optional) – parameter not used yet! default 0
x (float,optional) – shift value for coordinates (mode XYZ), default 0
y (float,optional) – shift value for coordinates (mode XYZ), default 0
z (float,optional) – shift value for coordinates (mode XYZ), default 0
extraData (string,optional) – default empty string

Returns:

a ccMesh object. Usage: see ccMesh doc.

Return type:

ccMesh

cloudComPy.loadPointCloud(filename: str, mode: _cloudComPy.CC_SHIFT_MODE = <CC_SHIFT_MODE.AUTO: 0>, skip: int = 0, x: float = 0, y: float = 0, z: float = 0, extraData: QString = '') → _cloudComPy.ccPointCloud

Load a 3D cloud from a file.

WARNING Shift parameters are not always taken into account, depending on the type of file, shift values, following the internal rules of CloudCompare: when using the CloudCompare GUI, shift dialog at import is not always available. When the shift dialog is not proposed in the GUI, shift parameters are likely not taken into account in CloudCompare.

Optional string extraData can be used in ply file, for instance, to select extra fields for import as scalarFields (by default, all extra fields are imported as scalar fields). Here, the filter is a regular expression that works on the field name in uppercase.

Parameters:

filename (str) – file name
shiftMode (CC_SHIFT_MODE,optional) –
shift mode from CC_SHIFT_MODE enum, default AUTO.
- CC_SHIFT_MODE.AUTO: automatic shift of coordinates
- CC_SHIFT_MODE.XYZ: coordinates shift given by x, y, z parameters
- CC_SHIFT_MODE.FIRST_GLOBAL_SHIFT: use the first encountered global shift value (if any)
- CC_SHIFT_MODE.NO_GLOBAL_SHIFT: no shift at all
skip (int,optional) – parameter not used yet! default 0
x (float,optional) – shift value for coordinates (mode XYZ), default 0
y (float,optional) – shift value for coordinates (mode XYZ), default 0
z (float,optional) – shift value for coordinates (mode XYZ), default 0
extraData (string,optional) – default empty string

Returns:

a ccPointCloud object. Usage: see ccPointCloud doc.

Return type:

ccPointCloud

cloudComPy.loadPolyline(filename: str, mode: _cloudComPy.CC_SHIFT_MODE = <CC_SHIFT_MODE.AUTO: 0>, skip: int = 0, x: float = 0, y: float = 0, z: float = 0) → _cloudComPy.ccPolyline

Load a polyline from a file.

Parameters:

filename (str) – The polyline file.
mode (CC_SHIFT_MODE,optional) –
from (AUTO, XYZ), optional, default AUTO.
- AUTO: automatic shift of coordinates
- XYZ: coordinates shift given by x, y, z parameters
skip (int,optional) – not used yet! default 0.
x (float,optional) – optional shift value for coordinates (mode XYZ), default 0
y (float,optional) – optional shift value for coordinates (mode XYZ), default 0
z (float,optional) – optional shift value for coordinates (mode XYZ), default 0

Returns:

a ccPolyline object.

Return type:

ccPolyline

Usage: see ccPolyline doc.

cloudComPy.MergeEntities(entities: list[_cloudComPy.ccHObject], deleteOriginalClouds: bool = False, createSFcloudIndex: bool = False, createSubMeshes: bool = False) → _cloudComPy.ccHObject

Merge a list of point clouds, or a list of meshes.

Parameters:

entities (tuple) – list of clouds or list of meshes (not mixed)
deleteOriginalClouds (bool,optional) – whether to delete the original clouds or not, default false WARNING No automatic action on the Python side to disable the variables referencing deleted objects! (same behavior as “deleteEntity” function).
createSFcloudIndex (bool,optional) – create a scalar field with the original cloud indexes, default false
createSubMeshes (bool,optional) – create submeshes with original meshes, default false

Returns:

merged entity

Return type:

ccHObject (cloud or mesh)

cloudComPy.RasterizeGeoTiffOnly(cloud: _cloudComPy.ccGenericPointCloud, gridStep: float, vertDir: _cloudComPy.CC_DIRECTION = <CC_DIRECTION.Z: 2>, outputRasterZ: bool = False, outputRasterSFs: bool = False, outputRasterRGB: bool = False, pathToImages: str = '.', resample: bool = False, projectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, sfProjectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, emptyCellFillStrategy: _cloudComPy.EmptyCellFillOption = <EmptyCellFillOption.LEAVE_EMPTY: 0>, DelaunayMaxEdgeLength: float = 1.0, KrigingParamsKNN: int = 8, customHeight: float = nan, gridBBox: _cloudComPy.ccBBox = <_cloudComPy.ccBBox object at 0x14a63a9f0>, percentile: float = 50.0, export_perCellCount: bool = False, export_perCellMinHeight: bool = False, export_perCellMaxHeight: bool = False, export_perCellAvgHeight: bool = False, export_perCellHeightStdDev: bool = False, export_perCellHeightRange: bool = False, export_perCellMedian: bool = False, export_perCellPercentile: bool = False, export_perCellUniqueCount: bool = False) → _cloudComPy.ccHObject

Compute a GeoTiff file from a point cloud, given a grid step and a direction.

GeoTiff files are only available with the GDAL plugin.

Parameters:

cloud (ccGenericPointCloud*) – the original cloud
gridStep (float) – the raster grid step
vertDir (CC_DIRECTION,optional) – default = CC_DIRECTION.Z, direction of projection
outputRasterZ (bool,optional) – default False, create a GeoTiff file (3D tiff with altitude)
outputRasterSFs (bool,optional) – default False, add scalar fields to the GeoTiff file (requires outputRasterZ)
outputRasterRGB (bool,optional) – default False, create a GeoTiff file with GRB values (choose either Z or RGB, not the two)
pathToImages (string,optional) – default “.” for current directory, directory for the GeoTiff file, name basesd on Cloud name plus suffix
resample (bool,optional) – default False, resample the point cloud
projectionType (ProjectionType,optional) – default ProjectionType.PROJ_AVERAGE_VALUE,
sfProjectionType (ProjectionType,optional) – default ProjectionType.PROJ_AVERAGE_VALUE,
emptyCellFillStrategy (EmptyCellFillOption,optional) – default EmptyCellFillOption.LEAVE_EMPTY
DelaunayMaxEdgeLength (double,optional) – used when EmptyCellFillOption is INTERPOLATE_DELAUNAY: maximum edge length, default 1.0
KrigingParamsKNN (int,optional) – used when EmptyCellFillOption is KRIGING: number of neighbour nodes, default 8
customHeight (float,optional) – default float(‘nan’)
gridBBox (ccBBox,optional) – default ccBBox() the bounding box used for the raster is by default the cloud bounding box
percentile (float,optional) – the percentile value to use for export percentile statistics, default 50.
export_perCellCount (bool,optional) – export scalarField, default False
export_perCellMinHeight (bool,optional) – export scalarField, default False
export_perCellMaxHeight (bool,optional) – export scalarField, default False
export_perCellAvgHeight (bool,optional) – export scalarField, default False
export_perCellHeightStdDev (bool,optional) – export scalarField, default False
export_perCellHeightRange (bool,optional) – export scalarField, default False
export_perCellMedian (bool,optional) – export scalarField, default False
export_perCellPercentile (bool,optional) – export scalarField, default False
export_perCellUniqueCount (bool,optional) – export scalarField, default False

Returns:

None

Return type:

None

cloudComPy.RasterizeToCloud(cloud: _cloudComPy.ccGenericPointCloud, gridStep: float, vertDir: _cloudComPy.CC_DIRECTION = <CC_DIRECTION.Z: 2>, outputRasterZ: bool = False, outputRasterSFs: bool = False, outputRasterRGB: bool = False, pathToImages: str = '.', resample: bool = False, projectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, sfProjectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, emptyCellFillStrategy: _cloudComPy.EmptyCellFillOption = <EmptyCellFillOption.LEAVE_EMPTY: 0>, DelaunayMaxEdgeLength: float = 1.0, KrigingParamsKNN: int = 8, customHeight: float = nan, gridBBox: _cloudComPy.ccBBox = <_cloudComPy.ccBBox object at 0x14a63a230>, percentile: float = 50.0, export_perCellCount: bool = False, export_perCellMinHeight: bool = False, export_perCellMaxHeight: bool = False, export_perCellAvgHeight: bool = False, export_perCellHeightStdDev: bool = False, export_perCellHeightRange: bool = False, export_perCellMedian: bool = False, export_perCellPercentile: bool = False, export_perCellUniqueCount: bool = False) → _cloudComPy.ccPointCloud

Compute a Raster cloud from a point cloud, given a grid step and a direction, plus an optional GeoTiff file.

GeoTiff files are only available with the GDAL plugin.

Parameters:

cloud (ccGenericPointCloud*) – the original cloud
gridStep (float) – the raster grid step
vertDir (CC_DIRECTION,optional) – default = CC_DIRECTION.Z, direction of projection
outputRasterZ (bool,optional) – default False, create also a GeoTiff file (3D tiff with altitude)
outputRasterSFs (bool,optional) – default False, add scalar fields to the GeoTiff file (requires outputRasterZ)
outputRasterRGB (bool,optional) – default False, create also a GeoTiff file with GRB values (choose either Z or RGB, not the two)
pathToImages (string,optional) – default “.” for current directory, directory for the GeoTiff file, name basesd on Cloud name plus suffix
resample (bool,optional) – default False, resample the point cloud
projectionType (ProjectionType,optional) – default ProjectionType.PROJ_AVERAGE_VALUE,
sfProjectionType (ProjectionType,optional) – default ProjectionType.PROJ_AVERAGE_VALUE,
emptyCellFillStrategy (EmptyCellFillOption,optional) – default EmptyCellFillOption.LEAVE_EMPTY
DelaunayMaxEdgeLength (double,optional) – used when EmptyCellFillOption is INTERPOLATE_DELAUNAY: maximum edge length, default 1.0
KrigingParamsKNN (int,optional) – used when EmptyCellFillOption is KRIGING: number of neighbour nodes, default 8
customHeight (float,optional) – default float(‘nan’)
gridBBox (ccBBox,optional) – default ccBBox() the bounding box used for the raster is by default the cloud bounding box
percentile (float,optional) – the percentile value to use for export percentile statistics, default 50.
export_perCellCount (bool,optional) – export scalarField, default False
export_perCellMinHeight (bool,optional) – export scalarField, default False
export_perCellMaxHeight (bool,optional) – export scalarField, default False
export_perCellAvgHeight (bool,optional) – export scalarField, default False
export_perCellHeightStdDev (bool,optional) – export scalarField, default False
export_perCellHeightRange (bool,optional) – export scalarField, default False
export_perCellMedian (bool,optional) – export scalarField, default False
export_perCellPercentile (bool,optional) – export scalarField, default False
export_perCellUniqueCount (bool,optional) – export scalarField, default False

Returns:

the raster cloud

Return type:

ccPointCloud

cloudComPy.RasterizeToMesh(cloud: _cloudComPy.ccGenericPointCloud, gridStep: float, vertDir: _cloudComPy.CC_DIRECTION = <CC_DIRECTION.Z: 2>, outputRasterZ: bool = False, outputRasterSFs: bool = False, outputRasterRGB: bool = False, pathToImages: str = '.', resample: bool = False, projectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, sfProjectionType: _cloudComPy.ProjectionType = <ProjectionType.PROJ_AVERAGE_VALUE: 1>, emptyCellFillStrategy: _cloudComPy.EmptyCellFillOption = <EmptyCellFillOption.LEAVE_EMPTY: 0>, DelaunayMaxEdgeLength: float = 1.0, KrigingParamsKNN: int = 8, customHeight: float = nan, gridBBox: _cloudComPy.ccBBox = <_cloudComPy.ccBBox object at 0x14a63a570>, percentile: float = 50.0, export_perCellCount: bool = False, export_perCellMinHeight: bool = False, export_perCellMaxHeight: bool = False, export_perCellAvgHeight: bool = False, export_perCellHeightStdDev: bool = False, export_perCellHeightRange: bool = False, export_perCellMedian: bool = False, export_perCellPercentile: bool = False, export_perCellUniqueCount: bool = False) → _cloudComPy.ccMesh

Compute a Raster mesh from a point cloud, given a grid step and a direction, plus an optional GeoTiff file.

GeoTiff files are only available with the GDAL plugin.

Parameters:

cloud (ccGenericPointCloud*) – the original cloud
gridStep (float) – the raster grid step
vertDir (CC_DIRECTION,optional) – default = CC_DIRECTION.Z, direction of projection
outputRasterZ (bool,optional) – default False, create also a GeoTiff file (3D tiff with altitude)
outputRasterSFs (bool,optional) – default False, add scalar fields to the GeoTiff file (requires outputRasterZ)
outputRasterRGB (bool,optional) – default False, create also a GeoTiff file with GRB values (choose either Z or RGB, not the two)
pathToImages (string,optional) – default “.” for current directory, directory for the GeoTiff file, name basesd on Cloud name plus suffix
resample (bool,optional) – default False, resample the point cloud
projectionType (ProjectionType,optional) – default ProjectionType.PROJ_AVERAGE_VALUE,
sfProjectionType (ProjectionType,optional) – default ProjectionType.PROJ_AVERAGE_VALUE,
emptyCellFillStrategy (EmptyCellFillOption,optional) – default EmptyCellFillOption.LEAVE_EMPTY
DelaunayMaxEdgeLength (double,optional) – used when EmptyCellFillOption is INTERPOLATE_DELAUNAY: maximum edge length, default 1.0
KrigingParamsKNN (int,optional) – used when EmptyCellFillOption is KRIGING: number of neighbour nodes, default 8
customHeight (float,optional) – default float(‘nan’)
gridBBox (ccBBox,optional) – default ccBBox() the bounding box used for the raster is by default the cloud bounding box
percentile (float,optional) – the percentile value to use for export percentile statistics, default 50.
export_perCellCount (bool,optional) – export scalarField, default False
export_perCellMinHeight (bool,optional) – export scalarField, default False
export_perCellMaxHeight (bool,optional) – export scalarField, default False
export_perCellAvgHeight (bool,optional) – export scalarField, default False
export_perCellHeightStdDev (bool,optional) – export scalarField, default False
export_perCellHeightRange (bool,optional) – export scalarField, default False
export_perCellMedian (bool,optional) – export scalarField, default False
export_perCellPercentile (bool,optional) – export scalarField, default False
export_perCellUniqueCount (bool,optional) – export scalarField, default False

Returns:

the raster mesh

Return type:

ccMesh

cloudComPy.SaveEntities(arg0: list[_cloudComPy.ccHObject], arg1: QString) → _cloudComPy.CC_FILE_ERROR

Save a list of entities (cloud, meshes, primitives…) in a file: use bin format!

Parameters:

entities (list of ccHObject) – list of entities
filename (str) – The entities file.

Returns:

0 or I/O error.

Return type:

CC_FILE_ERROR

cloudComPy.SaveMesh(arg0: _cloudComPy.ccMesh, arg1: QString) → _cloudComPy.CC_FILE_ERROR

Save a 3D mesh in a file.

The file name extension determines the format (.ma .dxf .off .stl .vtk .obj .ply .bin .fbx)

Parameters:

mesh (ccMesh) – the mesh to save.
filename (str) – The mesh file.

Returns:

0 or I/O error.

Return type:

CC_FILE_ERROR

cloudComPy.SavePointCloud(cloud: _cloudComPy.ccPointCloud, filename: QString, version: QString = '', pointFormat: int = -1, isAscii: bool = True) → _cloudComPy.CC_FILE_ERROR

Save a 3D cloud in a file.

The file name extension determines the format (.asc .las .E57 .sbf .ply .vtk .dxf .pcd .pn .pv .bin).

Optional values can be used to specify version and format, with the LAS plugin, for .las or .laz files:

version=”1.2” or “1.3” or “1.4” (without version, las or laz file are either saved in the version of the original file or in version 1.2)
pointFormat=N with N integer between 0 and 10

Optional ASCII file format, for ply plugin

Parameters:

cloud (ccPointCloud) – the cloud to save.
filename (str) – The cloud file.
version (string,optional) – optional string, default “”, used to specify a particular version. (for las plugin only)
pointFormat (int,optional) – optional point format valid values 0 to 10), default -1 (automatically set)(for las plugin only)
isAscii (bool,optional) – optional file format, ASCII or BINARY, default False = BINARY (for ply plugin)

Returns:

0 or I/O error.

Return type:

CC_FILE_ERROR

cloudComPy.setTraces(arg0: bool) → None

Activate or deactivate trace system.

Parameters:: isActive (bool) – whether to activate or deactivate the trace system.

cloudComPy.unfoldPointsAlongPolylines(clouds: list[_cloudComPy.ccGenericPointCloud], polylines: list[_cloudComPy.ccPolyline], thickness: float, vertDim: int = 2) → list[_cloudComPy.ccPointCloud]

Unfold the polylines and the clouds along the polylines, with a given thickness.

Parameters:

clouds (list[ccPointCloud]) – list of clouds
polylines (list[ccPolyline]) – list of polylines
thickness (double) – only points within the given distance to the polyline are kept
vertDim (int,optional) – vertical direction, value in O (oX), 1 (oY), 2 (oZ), default 2

Returns:

list of clouds

Return type:

list of ccPointClouds

cloudComPy.addToRenderScene(obj: _cloudComPy.ccHObject, showScalar: bool = True) → None

RenderViewToFile: add an entity to the scene view.

Parameters:: entity (ccHObject) – the entity to display

cloudComPy.removeFromRenderScene(arg0: _cloudComPy.ccHObject) → None

RenderViewToFile: remove an entity from the scene view.

WARNING: the entity is deleted! The Python variable is no more usable (set it to None)

Parameters:: entity (ccHObject) – the entity to remove

cloudComPy.render(filename: QString, width: int = 1500, height: int = 1000, isInteractive: bool = False) → None

RenderViewToFile: write the image file from the 3D scene.

Parameters:

filename (string) – the filename with it’s path and extension. The extension defines the image format (.png, .jpg, …)
width (int,optional) – the width of the image (pixels), default 1500
height (int,optional) – the height of the image (pixels), default 1000
isInteractive (bool,optional) – default False, whether to keep the IHM viewer active (and suspend Python script).

cloudComPy.setOrthoView() → None: RenderViewToFile: set the type of view to ortho (no perspective)

cloudComPy.setCenteredPerspectiveView() → None: RenderViewToFile: set the type of perspective to object centered

cloudComPy.setViewerPerspectiveView() → None: RenderViewToFile: set the type of perspective to viewer centered

cloudComPy.setGlobalZoom() → None: RenderViewToFile: zoom to the whole scene

cloudComPy.zoomOnSelectedEntity() → None: RenderViewToFile: zoom on the selected entity

cloudComPy.setFrontView() → None: RenderViewToFile: set front view

cloudComPy.setBottomView() → None: RenderViewToFile: set bottom view

cloudComPy.setTopView() → None: RenderViewToFile: set top view

cloudComPy.setBackView() → None: RenderViewToFile: set back view

cloudComPy.setLeftView() → None: RenderViewToFile: set left view

cloudComPy.setRightView() → None: RenderViewToFile: set right view

cloudComPy.setIsoView1() → None: RenderViewToFile: set iso view, first type

cloudComPy.setIsoView2() → None: RenderViewToFile: set iso view, second type

cloudComPy.setCustomView(arg0: Vector3Tpl<T>, arg1: Vector3Tpl<T>) → None

RenderViewToFile: set a custom view, defining a look vector and an up direction

Parameters:

forward (CCVector3d) – direction of view
up (CCVector3d) – up direction (to define “up” in the image

cloudComPy.setCameraPos(arg0: Vector3Tpl<T>) → None

RenderViewToFile: define a camera position.

Parameters:: P (CCVector3d) – camera position

cloudComPy.setBackgroundColor(gradient: bool = False, r: int = 255, g: int = 255, b: int = 255) → None

RenderViewToFile: define a background color.

Parameters:

gradient (bool,optional) – default false, draw a background gradient (between rgb and the opposite of foreground color)
r (int,optional) – red value (0..255), default 255
g (int,optional) – green value (0..255), default 255
b (int,optional) – blue value (0..255), default 255

cloudComPy.setTextDefaultCol(r: int = 0, g: int = 0, b: int = 0, a: int = 255) → None

RenderViewToFile: define a text default (foreground) color.

Parameters:

r (int,optional) – red value (0..255), default 0
g (int,optional) – green value (0..255), default 0
b (int,optional) – blue value (0..255), default 0
a (int,optional) – alpha value (0..255), default 255

cloudComPy.setColorScaleShowHistogram(showHist: bool = True) → None

RenderViewToFile: show the color scale histogram, when the color scale itself is shown (see ‘showSFColorsScale’ method of ‘ccPointCloud’).

Parameters:: showHist (bool,optional) – default true, whether to add the histogram to the color scale.

class cloudComPy.ccBBox

BoundingBox object.

Can be initialized with tuples of coordinates and a boolean (minCorner, maxCorner, True)

__init__(self: _cloudComPy.ccBBox, arg0: Vector3Tpl<T>, arg1: Vector3Tpl<T>, arg2: bool) → None

BoundingBox constructor, with tuples of coordinates and a boolean (minCorner, maxCorner, True)

Parameters:

minCorner (tuple) – min corner of the box
maxCorner (tuple) – max corner of the box
valid (bool) – use True

maxCorner(self: _cloudComPy.ccBBox) → Vector3Tpl<T>

Get the max corner of the bounding box

Returns:: max corner (tuple of coordinates)
Return type:: tuple

minCorner(self: _cloudComPy.ccBBox) → Vector3Tpl<T>

Get the min corner of the bounding box

Returns:: min corner (tuple of coordinates)
Return type:: tuple

class cloudComPy.CC_DIRECTION

Members:

X

Y

Z

X = <CC_DIRECTION.X: 0>

Y = <CC_DIRECTION.Y: 1>

Z = <CC_DIRECTION.Z: 2>

__init__(self: _cloudComPy.CC_DIRECTION, value: int) → None

property name

property value

class cloudComPy.CC_FILE_ERROR

Members:

CC_FERR_NO_ERROR

CC_FERR_BAD_ARGUMENT

CC_FERR_UNKNOWN_FILE

CC_FERR_WRONG_FILE_TYPE

CC_FERR_WRITING

CC_FERR_READING

CC_FERR_NO_SAVE

CC_FERR_NO_LOAD

CC_FERR_BAD_ENTITY_TYPE

CC_FERR_CANCELED_BY_USER

CC_FERR_NOT_ENOUGH_MEMORY

CC_FERR_MALFORMED_FILE

CC_FERR_CONSOLE_ERROR

CC_FERR_BROKEN_DEPENDENCY_ERROR

CC_FERR_FILE_WAS_WRITTEN_BY_UNKNOWN_PLUGIN

CC_FERR_THIRD_PARTY_LIB_FAILURE

CC_FERR_THIRD_PARTY_LIB_EXCEPTION

CC_FERR_NOT_IMPLEMENTED

CC_FERR_BAD_ARGUMENT = <CC_FILE_ERROR.CC_FERR_BAD_ARGUMENT: 1>

CC_FERR_BAD_ENTITY_TYPE = <CC_FILE_ERROR.CC_FERR_BAD_ENTITY_TYPE: 8>

CC_FERR_BROKEN_DEPENDENCY_ERROR = <CC_FILE_ERROR.CC_FERR_BROKEN_DEPENDENCY_ERROR: 13>

CC_FERR_CANCELED_BY_USER = <CC_FILE_ERROR.CC_FERR_CANCELED_BY_USER: 9>

CC_FERR_CONSOLE_ERROR = <CC_FILE_ERROR.CC_FERR_CONSOLE_ERROR: 12>

CC_FERR_FILE_WAS_WRITTEN_BY_UNKNOWN_PLUGIN = <CC_FILE_ERROR.CC_FERR_FILE_WAS_WRITTEN_BY_UNKNOWN_PLUGIN: 14>

CC_FERR_MALFORMED_FILE = <CC_FILE_ERROR.CC_FERR_MALFORMED_FILE: 11>

CC_FERR_NOT_ENOUGH_MEMORY = <CC_FILE_ERROR.CC_FERR_NOT_ENOUGH_MEMORY: 10>

CC_FERR_NOT_IMPLEMENTED = <CC_FILE_ERROR.CC_FERR_NOT_IMPLEMENTED: 17>

CC_FERR_NO_ERROR = <CC_FILE_ERROR.CC_FERR_NO_ERROR: 0>

CC_FERR_NO_LOAD = <CC_FILE_ERROR.CC_FERR_NO_LOAD: 7>

CC_FERR_NO_SAVE = <CC_FILE_ERROR.CC_FERR_NO_SAVE: 6>

CC_FERR_READING = <CC_FILE_ERROR.CC_FERR_READING: 5>

CC_FERR_THIRD_PARTY_LIB_EXCEPTION = <CC_FILE_ERROR.CC_FERR_THIRD_PARTY_LIB_EXCEPTION: 16>

CC_FERR_THIRD_PARTY_LIB_FAILURE = <CC_FILE_ERROR.CC_FERR_THIRD_PARTY_LIB_FAILURE: 15>

CC_FERR_UNKNOWN_FILE = <CC_FILE_ERROR.CC_FERR_UNKNOWN_FILE: 2>

CC_FERR_WRITING = <CC_FILE_ERROR.CC_FERR_WRITING: 4>

CC_FERR_WRONG_FILE_TYPE = <CC_FILE_ERROR.CC_FERR_WRONG_FILE_TYPE: 3>

__init__(self: _cloudComPy.CC_FILE_ERROR, value: int) → None

property name

property value

class cloudComPy.CC_SHIFT_MODE

Members:

AUTO

XYZ

FIRST_GLOBAL_SHIFT

NO_GLOBAL_SHIFT

AUTO = <CC_SHIFT_MODE.AUTO: 0>

FIRST_GLOBAL_SHIFT = <CC_SHIFT_MODE.FIRST_GLOBAL_SHIFT: 2>

NO_GLOBAL_SHIFT = <CC_SHIFT_MODE.NO_GLOBAL_SHIFT: 3>

XYZ = <CC_SHIFT_MODE.XYZ: 1>

__init__(self: _cloudComPy.CC_SHIFT_MODE, value: int) → None

property name

property value

class cloudComPy.CurvatureType

Members:

GAUSSIAN_CURV

MEAN_CURV

NORMAL_CHANGE_RATE

GAUSSIAN_CURV = <CurvatureType.GAUSSIAN_CURV: 1>

MEAN_CURV = <CurvatureType.MEAN_CURV: 2>

NORMAL_CHANGE_RATE = <CurvatureType.NORMAL_CHANGE_RATE: 3>

__init__(self: _cloudComPy.CurvatureType, value: int) → None

property name

property value

class cloudComPy.EmptyCellFillOption

Members:

LEAVE_EMPTY

FILL_MINIMUM_HEIGHT

FILL_MAXIMUM_HEIGHT

FILL_CUSTOM_HEIGHT

FILL_AVERAGE_HEIGHT

INTERPOLATE_DELAUNAY

KRIGING

FILL_AVERAGE_HEIGHT = <EmptyCellFillOption.FILL_AVERAGE_HEIGHT: 4>

FILL_CUSTOM_HEIGHT = <EmptyCellFillOption.FILL_CUSTOM_HEIGHT: 3>

FILL_MAXIMUM_HEIGHT = <EmptyCellFillOption.FILL_MAXIMUM_HEIGHT: 2>

FILL_MINIMUM_HEIGHT = <EmptyCellFillOption.FILL_MINIMUM_HEIGHT: 1>

INTERPOLATE_DELAUNAY = <EmptyCellFillOption.INTERPOLATE_DELAUNAY: 5>

KRIGING = <EmptyCellFillOption.KRIGING: 6>

LEAVE_EMPTY = <EmptyCellFillOption.LEAVE_EMPTY: 0>

__init__(self: _cloudComPy.EmptyCellFillOption, value: int) → None

property name

property value

class cloudComPy.ExportableFields

Members:

PER_CELL_HEIGHT

PER_CELL_COUNT

PER_CELL_MIN_HEIGHT

PER_CELL_MAX_HEIGHT

PER_CELL_AVG_HEIGHT

PER_CELL_HEIGHT_STD_DEV

PER_CELL_HEIGHT_RANGE

PER_CELL_INVALID

PER_CELL_AVG_HEIGHT = <ExportableFields.PER_CELL_AVG_HEIGHT: 4>

PER_CELL_COUNT = <ExportableFields.PER_CELL_COUNT: 1>

PER_CELL_HEIGHT = <ExportableFields.PER_CELL_HEIGHT: 0>

PER_CELL_HEIGHT_RANGE = <ExportableFields.PER_CELL_HEIGHT_RANGE: 6>

PER_CELL_HEIGHT_STD_DEV = <ExportableFields.PER_CELL_HEIGHT_STD_DEV: 5>

PER_CELL_INVALID = <ExportableFields.PER_CELL_INVALID: 10>

PER_CELL_MAX_HEIGHT = <ExportableFields.PER_CELL_MAX_HEIGHT: 3>

PER_CELL_MIN_HEIGHT = <ExportableFields.PER_CELL_MIN_HEIGHT: 2>

__init__(self: _cloudComPy.ExportableFields, value: int) → None

property name

property value

class cloudComPy.ICPres

Result values on ICP registration.

Variables:

aligned (ccPointCloud) – the point cloud on which the transformation must be applied
transMat (ccGLMatrix) – the resulting transformation to apply
finalScale (float) – calculated scale if rescale required
finalRMS (float) – final error (RMS)
finalPointCount (int) – number of points used to compute the final RMS

__init__(self: _cloudComPy.ICPres) → None: Default constructor

property aligned

property finalPointCount

Result values on ICP registration.

Variables:

aligned (ccPointCloud) – the point cloud on which the transformation must be applied
transMat (ccGLMatrix) – the resulting transformation to apply
finalScale (float) – calculated scale if rescale required
finalRMS (float) – final error (RMS)
finalPointCount (int) – number of points used to compute the final RMS

property finalRMS

Result values on ICP registration.

Variables:

aligned (ccPointCloud) – the point cloud on which the transformation must be applied
transMat (ccGLMatrix) – the resulting transformation to apply
finalScale (float) – calculated scale if rescale required
finalRMS (float) – final error (RMS)
finalPointCount (int) – number of points used to compute the final RMS

property finalScale

Result values on ICP registration.

Variables:

aligned (ccPointCloud) – the point cloud on which the transformation must be applied
transMat (ccGLMatrix) – the resulting transformation to apply
finalScale (float) – calculated scale if rescale required
finalRMS (float) – final error (RMS)
finalPointCount (int) – number of points used to compute the final RMS

property transMat

Result values on ICP registration.

Variables:

aligned (ccPointCloud) – the point cloud on which the transformation must be applied
transMat (ccGLMatrix) – the resulting transformation to apply
finalScale (float) – calculated scale if rescale required
finalRMS (float) – final error (RMS)
finalPointCount (int) – number of points used to compute the final RMS

class cloudComPy.interpolatorParameters