open3d.ml.tf.datasets.ParisLille3D

class open3d.ml.tf.datasets.ParisLille3D(dataset_path, name='ParisLille3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, test_result_folder='./test', val_files=['Lille2.ply'], **kwargs)

This class is used to create a dataset based on the ParisLille3D dataset, and used in visualizer, training, or testing.

The ParisLille3D dataset is best used to train models for urban infrastructure. You can download the dataset here.

__init__(dataset_path, name='ParisLille3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, test_result_folder='./test', val_files=['Lille2.ply'], **kwargs)

Initialize the function by passing the dataset and other details.

Parameters

• dataset_path – The path to the dataset to use.

• name – The name of the dataset (ParisLille3D in this case).

• cache_dir – The directory where the cache is stored.

• use_cache – Indicates if the dataset should be cached.

• num_points – The maximum number of points to use when splitting the dataset.

• ignored_label_inds – A list of labels that should be ignored in the dataset.

• test_result_folder – The folder where the test results should be stored.

• val_files – The files that include the values.

static get_label_to_names()

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

• 'training' –

• 'test' –

• 'validation' –

• 'all'. (or) –

Returns

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

get_split_list(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.

Raises

• ValueError – Indicates that the split name passed is incorrect. The split name should be one of

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

is_tested(attr)

Checks if a datum in the dataset has been tested.

Parameters

dataset – The current dataset to which the datum belongs to. attr: The attribute that needs to be checked.

Returns

If the dataum attribute is tested, then resturn the path where the attribute is stored; 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.