open3d.ml.torch.datasets.Scannet#

class open3d.ml.torch.datasets.Scannet(dataset_path, name='Scannet', cache_dir='./logs/cache', use_cache=False, **kwargs)#

Scannet 3D dataset for Object Detection, used in visualizer, training, or test.

__init__(dataset_path, name='Scannet', cache_dir='./logs/cache', use_cache=False, **kwargs)#

Initialize the dataset by passing the dataset and other details.

Parameters:

  • dataset_path (str) – The path to the dataset to use.

  • name (str) – The name of the dataset (Scannet in this case).

  • cache_dir (str) – The directory where the cache is stored.

  • use_cache (bool) – Indicates if the dataset should be cached.

get_label_to_names()#

Returns a label to names dictionary 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

  • 'training' –

  • 'test' –

  • 'validation' –

  • 'all'. (or) –

Returns:

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

get_split_list(split)#
is_tested()#

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.

read_label(scene)#
static read_lidar(path)#
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.