Metadata-Version: 2.1
Name: dpeeg
Version: 0.4.1
Summary: Deep learning with EEG
Home-page: https://github.com/SheepTAO/dpeeg
Author: SheepTAO
Author-email: sheeptao@outlook.com
License: MIT
Keywords: eeg,deep learning,pytorch
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21.5
Requires-Dist: einops>=0.7.0
Requires-Dist: seaborn>=0.12.1
Requires-Dist: pooch>=1.6.0
Requires-Dist: mne>=1.6
Requires-Dist: scipy>=1.11.1
Requires-Dist: scikit-learn>=1.0.2
Requires-Dist: tqdm>=4.64.1
Requires-Dist: torchmetrics>=1.0.0
Requires-Dist: torchinfo>=1.5.0
Requires-Dist: tensorboard

![banner](/docs/source/_static/banner.svg)

**dpeeg** provides a complete workflow for deep learning decoding EEG tasks, 
including basic datasets (datasets can be easily customized), basic network 
models, model training, rich experiments, and detailed experimental result 
storage.

# Usage

1. Create a new virtual environment named "dpeeg" with 
[Python](https://www.python.org/) >= 3.10 using Anaconda3 and activate it：
```Shell
conda create --name dpeeg python
conda activate dpeeg
```

2. dpeeg depends on [Pytorch](https://pytorch.org/). Please refer to the 
corresponding official website for installation.

3. Complete the installation via `pip`:
```Shell
pip install dpeeg
``` 
