cloudViewer.ml.torch.datasets.Toronto3D

class cloudViewer.ml.torch.datasets.Toronto3D(dataset_path, name='Toronto3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, class_weights=[35391894.0, 1449308.0, 4650919.0, 18252779.0, 589856.0, 743579.0, 4311631.0, 356463.0], ignored_label_inds=[0], train_files=['L001.ply', 'L003.ply', 'L004.ply'], val_files=['L002.ply'], test_files=['L002.ply'], test_result_folder='./test', **kwargs)

Toronto3D dataset, used in visualizer, training, or test.

__init__(dataset_path, name='Toronto3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, class_weights=[35391894.0, 1449308.0, 4650919.0, 18252779.0, 589856.0, 743579.0, 4311631.0, 356463.0], ignored_label_inds=[0], train_files=['L001.ply', 'L003.ply', 'L004.ply'], val_files=['L002.ply'], test_files=['L002.ply'], test_result_folder='./test', **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 (Semantic3D 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.

• class_weights – The class weights to use in 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.

Returns:

The corresponding class.

Return type:

class

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 the list of data splits available.

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:

attr – The attribute that needs to be checked.

Returns:

If the datum attribute is tested, then return 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.