open3d.ml.torch.datasets.Semantic3D¶
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class
open3d.ml.torch.datasets.Semantic3D(dataset_path, name='Semantic3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, class_weights=[5181602, 5012952, 6830086, 1311528, 10476365, 946982, 334860, 269353], ignored_label_inds=[0], val_files=['bildstein_station3_xyz_intensity_rgb', 'sg27_station2_intensity_rgb'], test_result_folder='./test', **kwargs)¶ This class is used to create a dataset based on the Semantic3D dataset, and used in visualizer, training, or testing.
The dataset includes 8 semantic classes and covers a variety of urban outdoor scenes.
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__init__(dataset_path, name='Semantic3D', cache_dir='./logs/cache', use_cache=False, num_points=65536, class_weights=[5181602, 5012952, 6830086, 1311528, 10476365, 946982, 334860, 269353], ignored_label_inds=[0], val_files=['bildstein_station3_xyz_intensity_rgb', 'sg27_station2_intensity_rgb'], 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.
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
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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.
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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.
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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'. –
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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.
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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.
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