klampt.model.geometry module

Utility functions for operating on geometry. See the Geometry3D documentation for the core geometry class.

New in version 0.8.6.

[functions moved here from klampt.model.sensing]

Working with geometric primitives

box() and sphere() are aliases for the functions in klampt.model.create.primitives.

Working with point clouds

point_cloud_normals() estimates normals from a normal-free PointCloud.

The fit_plane(), fit_plane3(), and PlaneFitter class help with plane estimation.

point_cloud_simplify() simplifies a PointCloud.

point_cloud_colors() and point_cloud_set_colors() sets / gets colors from a PointCloud.

class klampt.model.geometry.PlaneFitter(points=None)[source]

Bases: object

Online fitting of planes through 3D point clouds

normal

best-fit normal

Type

3-vector

centroid

centroid of points

Type

3-vector

count

# of points

Type

int

sse

fitting sum of squared errors

Type

float

cov

covariance of points

Type

3x3 array

add_point(pt)[source]

Online estimation of best fit plane

distance(pt)[source]

Returns the signed distance to this plane

goodness_of_fit()[source]

Returns corrected RMSE

merge(fitter, inplace=False)[source]

Online merging of two plane fitters.

If inplace = False, returns a new PlaneFitter. If inplace = True, self is updated with the result.

plane_equation()[source]

Returns (a,b,c,d) with ax+by+cz+d=0 the plane equation

klampt.model.geometry.box(width, depth, height, center=None, R=None, t=None, world=None, name=None, mass=inf, type='TriangleMesh')[source]

Alias for klampt.model.create.primitives.box()

klampt.model.geometry.fit_plane(points)[source]

Returns a 3D plane equation that is a least squares fit through the points (len(points) >= 3).

klampt.model.geometry.fit_plane3(point1, point2, point3)[source]

Returns a 3D plane equation fitting the 3 points.

The result is (a,b,c,d) with the plane equation ax+by+cz+d=0

klampt.model.geometry.fit_plane_centroid(points)[source]

Similar to fit_plane(), but returns a (centroid,normal) pair.

klampt.model.geometry.point_cloud_colors(pc, format='rgb')[source]

Returns the colors of the point cloud in the given format. If the point cloud has no colors, this returns None. If the point cloud has no colors but has opacity, this returns white colors.

Parameters

  • pc (PointCloud) – the point cloud

  • format –

    describes the output color format, either:

    • ’rgb’: packed 24bit int, with the hex format 0xrrggbb,

    • ’bgr’: packed 24bit int, with the hex format 0xbbggrr,

    • ’rgba’: packed 32bit int, with the hex format 0xrrggbbaa,

    • ’bgra’: packed 32bit int, with the hex format 0xbbggrraa,

    • ’argb’: packed 32bit int, with the hex format 0xaarrggbb,

    • ’abgr’: packed 32bit int, with the hex format 0xaabbggrr,

    • (‘r’,’g’,’b’): triple with each channel in range [0,1]

    • (‘r’,’g’,’b’,’a’): tuple with each channel in range [0,1]

    • ’channels’: returns a list of channels, in the form (r,g,b) or

      (r,g,b,a), where each value in the channel has range [0,1].

    • ’opacity’: returns opacity only, in the range [0,1].

Returns

A list of pc.numPoints() colors corresponding to the points

in the point cloud. If format=’channels’, the return value is a tuple (r,g,b) or (r,g,b,a).

Return type

list

klampt.model.geometry.point_cloud_normals(pc, estimation_radius=None, estimation_knn=None, estimation_viewpoint=None, add=True)[source]

Returns the normals of the point cloud. If pc has the standard normal_x, normal_y, normal_z properties, these will be returned. Otherwise, they will be estimated using plane fitting.

The plane fitting method uses scipy nearest neighbor detection if scipy is available. Otherwise it uses a spatial grid. The process is as follows:

  • If estimation_radius is provided, then it will use neighbors within this range. For a spatial grid, this is the grid size.

  • If estimation_knn is provided, then planes will be fit to these number of neighbors.

  • If neither is provided, then estimation_radius is set to 3 * max dimension of the point cloud / sqrt(N).

  • If not enough points are within a neighborhood (either 4 or estimation_knn, whichever is larger), then the normal is set to 0.

  • If estimation_viewpoint is provided, this must be a 3-list. The normals are oriented such that they point toward the viewpoint.

Returns

A list of N 3-lists, or an N x 3 numpy array if numpy is available.

If add=True, estimated normals will be added to the point cloud under the normal_x, normal_y, normal_z properties.

klampt.model.geometry.point_cloud_set_colors(pc, colors, color_format='rgb', pc_property='auto')[source]

Sets the colors of a point cloud.

Parameters

  • pc (PointCloud) – the point cloud

  • colors (list) – the list of colors, which can be either ints, tuples, or channels, depending on color_format.

  • color_format –

    describes the format of each element of colors, and can be:

    • ’rgb’: packed 24bit int, with the hex format 0xrrggbb,

    • ’bgr’: packed 24bit int, with the hex format 0xbbggrr,

    • ’rgba’: packed 32bit int, with the hex format 0xrrggbbaa,

    • ’bgra’: packed 32bit int, with the hex format 0xbbggrraa,

    • ’argb’: packed 32bit int, with the hex format 0xaarrggbb,

    • ’abgr’: packed 32bit int, with the hex format 0xaabbggrr,

    • (‘r’,’g’,’b’): triple with each channel in range [0,1]

    • (‘r’,’g’,’b’,’a’): tuple with each channel in range [0,1]

    • ’channels’: colors is a list of channels, in the form (r,g,b)

      or (r,g,b,a), where each value in the channel has range [0,1].

    • ’opacity’: opacity only, in the range [0,1].

  • pc_property (str) – describes to which property the colors should be set. ‘auto’ determines chooses the property from the point cloud if it’s already colored, or color_format if not. ‘channels’ sets the ‘r’, ‘g’, ‘b’, and optionally ‘a’ properties.

Returns

None

klampt.model.geometry.point_cloud_simplify(pc, radius)[source]

Simplifies a point cloud by averaging points within neighborhoods. Uses a fast hash grid data structure.

Parameters
klampt.model.geometry.sphere(radius, center=None, R=None, t=None, world=None, name=None, mass=inf, type='TriangleMesh')[source]

Alias for klampt.model.create.primitives.sphere()