Datasets¶
DCASE2020Task1A¶
-
class
dabstract.dataset.dbs.DCASE2020Task1A.DCASE2020Task1A(paths=None, test_only=0, **kwargs)¶ Bases:
dabstract.dataset.dataset.DatasetDCASE2020Task1A dataset
This class downloads the datasets and prepares it in the dabstract format.
- Parameters
- pathsdict or str:
Path configuration in the form of a dictionary. For example:
$ paths={ 'data': path_to_data, $ 'meta': path_to_meta, $ 'feat': path_to_feat}- test_onlybool
To specify if this dataset should be used for testing or both testing and train. This is only relevant if multiple datasets are combined and set_xval() is used. For example:
test_only = 0 -> use for both train and test test_only = 1 -> use only for test
- check dabstract.dataset.dataset.Dataset for more info
- Returns
- DCASE2020Task1B dataset class
-
prepare(paths)¶ Prepare the data
-
set_data(paths)¶ Set the data
DCASE2020Task1B¶
-
class
dabstract.dataset.dbs.DCASE2020Task1B.DCASE2020Task1B(paths=None, test_only=0, **kwargs)¶ Bases:
dabstract.dataset.dataset.DatasetDCASE2020Task1B dataset
This class downloads the datasets and prepares it in the dabstract format.
- Parameters
- pathsdict or str:
Path configuration in the form of a dictionary. For example:
$ paths={ 'data': path_to_data, $ 'meta': path_to_meta, $ 'feat': path_to_feat}- test_onlybool
To specify if this dataset should be used for testing or both testing and train. This is only relevant if multiple datasets are combined and set_xval() is used. For example:
test_only = 0 -> use for both train and test test_only = 1 -> use only for test
- check dabstract.dataset.dataset.Dataset for more info
- Returns
- DCASE2020Task1B dataset class
-
prepare(paths)¶ Prepare the data
-
set_data(paths)¶ Set the data