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Cannot get the config names for the dataset.
Error code: ConfigNamesError Exception: DataFilesNotFoundError Message: No (supported) data files found in FcmC/E4SelfLearning Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 72, in compute_config_names_response config_names = get_dataset_config_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1904, in dataset_module_factory raise e1 from None File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1885, in dataset_module_factory return HubDatasetModuleFactoryWithoutScript( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1270, in get_module module_name, default_builder_kwargs = infer_module_for_data_files( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 597, in infer_module_for_data_files raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else "")) datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in FcmC/E4SelfLearning
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E4SelfLearning is a collection of the following open-access datasets recording with an Empatica E4:
- ADARP - Creative Commons Attribution 4.0 International
- BID IDEAS Lab - Open Data Commons Attribution License v1.0
- In-Gauge En-Gage - Open Data Commons Attribution License v1.0
- Nurses Stress Detection - ODC Database Contents License (DbCL) v1.0
- PPG-DaLiA - Creative Commons Attribution 4.0 International
- SPS - MIT License
- Toadstool - Creative Commons Attribution 4.0 International
- UE4W - Creative Commons Attribution 4.0 International
- WEEE - Creative Commons Attribution 4.0 International
- WESAD - licence details
- WESD - Open Data Commons Attribution License v1.0
E4SelfLearning was used in the following article: ''Wearable data from students, teachers or subjects with alcohol use disorder help detect acute mood episodes via self-supervised learning''.
The codebase to pre-process E4SelfLearning and use it for training an E4-tailored self-supervised learning Transformer model (E4mer) is available at APRIL lab.
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