open3d.ml.torch.datasets.ShapeNet

class open3d.ml.torch.datasets.ShapeNet(dataset_path, name='ShapeNet', class_weights=[2690, 76, 55, 1824, 3746, 69, 787, 392, 1546, 445, 202, 184, 275, 66, 152, 5266], ignored_label_inds=[], test_result_folder='./test', task='classification', **kwargs)

__init__(dataset_path, name='ShapeNet', class_weights=[2690, 76, 55, 1824, 3746, 69, 787, 392, 1546, 445, 202, 184, 275, 66, 152, 5266], ignored_label_inds=[], test_result_folder='./test', task='classification', **kwargs)

” Initialize the class by passing the dataset path.

static get_label_to_names(task='classification')

Returns a label to names dictonary object.

Returns

A dict where keys are label numbers and values are the corresponding names.

get_split(split)

Returns a dataset split.

Parameters

• split – A string identifying the dataset split that is usually one of

• 'test', 'validation', or 'all'. ('training',) –

Returns

A dataset split object providing the requested subset of the data.

get_split_list(split)

is_tested(attr)

Checks whether a datum has been tested.

Parameters

attr – The attributes associated with the datum.

Returns

This returns True if the test result has been stored for the datum with the specified attribute; else returns False.

save_test_result(results, attr)

Saves the output of a model.

Parameters

• results – The output of a model for the datum associated with the attribute passed.

• attr – The attributes that correspond to the outputs passed in results.