cloudViewer.ml.torch.datasets.Electricity3D#
- class cloudViewer.ml.torch.datasets.Electricity3D(dataset_path, name='Electricity3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, class_weights=[635262, 1881335, 3351389, 135650, 1132024, 282850, 3384, 102379, 357589, 20374, 332435, 42973, 164957, 8626, 7962, 11651, 64765, 26884, 42479], ignored_label_inds=[0], val_files=['1_9_local_a', '7_29_local'], test_result_folder='./test', **kwargs)[source]#
This class is used to create a dataset based on the Electricity3D dataset, and used in visualizer, training, or testing. The dataset includes 19 semantic classes and covers a variety of electricity outdoor scenes.
- __init__(dataset_path, name='Electricity3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, class_weights=[635262, 1881335, 3351389, 135650, 1132024, 282850, 3384, 102379, 357589, 20374, 332435, 42973, 164957, 8626, 7962, 11651, 64765, 26884, 42479], ignored_label_inds=[0], val_files=['1_9_local_a', '7_29_local'], test_result_folder='./test', **kwargs)[source]#
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 (Electricity3D 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.
val_files – The files with the data.
test_result_folder – The folder where the test results should be stored.
- Returns:
The corresponding class.
- Return type:
class
- static get_label_to_names()[source]#
Returns a label to names dictonary object.
- Returns:
A dict where keys are label numbers and values are the corresponding names.
- get_split(split)[source]#
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)[source]#
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)[source]#
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.