open3d.ml.torch.datasets.Toronto3D¶
-
class
open3d.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)¶ This class is used to create a dataset based on the Toronto3D dataset, and used in visualizer, training, or testing. The dataset is best used for semantic segmentation of urban roadways.
-
__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.
- Args:
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:
class: The corresponding 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
'test', 'validation', or 'all'. ('training',) –
- 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
'test', 'validation', or 'all'. ('training',) –
- 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.
-