cloudViewer.ml.torch.vis.DatasetModel#

class cloudViewer.ml.torch.vis.DatasetModel(dataset, split, indices)[source]#

The class used to manage a dataset model.

Parameters:

  • 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.

__init__(dataset, split, indices)[source]#
is_loaded(name)[source]#

Check if the data is loaded.

load(name, fail_if_no_space=False)[source]#

Check if data is not loaded, and then load the data.

unload(name)[source]#

Unload the data (if it was loaded earlier).