open3d.ml.tf.vis.Visualizer

class open3d.ml.tf.vis.Visualizer

Visualizer for Dataset objects and custom point clouds

class ColormapEdit(window, em)

__init__(window, em)

Initialize self. See help(type(self)) for accurate signature.

set_on_changed(callback)

update(colormap, min_val, max_val)

class LabelLUTEdit

__init__()

Initialize self. See help(type(self)) for accurate signature.

clear()

get_colors()

is_empty()

set_labels(labellut)

set_on_changed(callback)

class ProgressDialog(title, window, n_items)

__init__(title, window, n_items)

Initialize self. See help(type(self)) for accurate signature.

post_update(text=None)

set_text(text)

update()

__init__()

Initialize self. See help(type(self)) for accurate signature.

set_lut(attr_name, lut)

Sets the LUT for a specific attribute

Parameters

• attr_name – Attribute name as string.

• lut – A LabelLUT object.

setup_camera()

show_geometries_under(name, show)

visualize(data, width=1024, height=768)

Visualizes custom point cloud data

Example

Minimal example for visualizing a single point cloud with an attribute:

import numpy as np
import open3d.ml.torch as ml3d
# or import open3d.ml.tf as ml3d

data = [ {
    'name': 'my_point_cloud',
    'points': np.random.rand(100,3).astype(np.float32),
    'point_attr1': np.random.rand(100).astype(np.float32),
    } ]

vis = ml3d.vis.Visualizer()
vis.visualize(data)

Parameters

• data – A list of dictionaries. Each dictionary is a point cloud with attributes. Each dictionary must have the entries ‘name’ and ‘points’. Points and point attributes can be passed as numpy arrays, PyTorch tensors or TensorFlow tensors.

• width – window width.

• height – window height.

visualize_dataset(dataset, split, indices=None, width=1024, height=768)

Visualizes a dataset

Example

Minimal example for visualizing a dataset::

import open3d.ml.torch as ml3d # or open3d.ml.tf as ml3d

dataset = ml3d.datasets.SemanticKITTI(dataset_path=’/path/to/SemanticKITTI/’) vis = ml3d.vis.Visualizer() vis.visualize_dataset(dataset, ‘all’, indices=range(100))

Parameters

• dataset – A dataset object.

• split – A string that identifies the split, e.g., ‘test’.

• indices – An iterable with a subset of the data points to visualize. E.g., [0,2,3,4].

• width – window width.

• height – window height.

COLOR_NAME = 'RGB'

GREYSCALE_NAME = 'Colormap (Greyscale)'

LABELS_NAME = 'Label Colormap'

RAINBOW_NAME = 'Colormap (Rainbow)'

SOLID_NAME = 'Solid Color'

X_ATTR_NAME = 'x position'

Y_ATTR_NAME = 'y position'

Z_ATTR_NAME = 'z position'