open3d.ml.torch.vis.DatasetModel

class open3d.ml.torch.vis.DatasetModel(dataset, split, indices)

The class used to manage a dataset model. Args:

dataset: The 3D ML dataset to use. You can use the base dataset, sample datasets , or a custom dataset. split: A string identifying the dataset split that is usually one of ‘training’, ‘test’, ‘validation’, or ‘all’. indices: The indices to be used for the datamodel. This may vary based on the split used.

class BoundingBoxData(name, boxes)

The class to define a bounding box that is used to describe the target location. Args:

name: The name of the pointcloud array. boxes: The array of pointcloud that define the bounding box.

__init__(name, boxes)

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

__init__(dataset, split, indices)

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

calc_bounds_for(name)

create_point_cloud(data)

get_attr(name, attr_name)

get_attr_minmax(attr_name, channel)

get_attr_shape(name, attr_name)

get_available_attrs(names)

is_loaded(name)

load(name, fail_if_no_space=False)

unload(name)

bounding_box_prefix = 'Bounding Boxes/'