unify preprocessing and data creation methods between different model training (Offline EEGNet, Riemannian Decoder) and model testing (raspy) pipelines
Please run each of the python file to get a grasp of how they work.
- dataset.py: contains everything relevant to creating a h5 dataset. The main function is create_dataset(config, h5_path)
- preprocessor.py: contains everything that has to do with preprocessing a piece of EEG data
- utils.py: contains standalone functions helpful to data reading in general