https://github.com/zrr1999/eeg-networks-pytorch
Implementation of various simple networks based on PyTorch to classify EEG signals.
https://github.com/zrr1999/eeg-networks-pytorch
deep-learning eeg eeg-classification eeg-net eeg-signals pytorch
Last synced: 6 months ago
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Implementation of various simple networks based on PyTorch to classify EEG signals.
- Host: GitHub
- URL: https://github.com/zrr1999/eeg-networks-pytorch
- Owner: zrr1999
- Created: 2022-06-01T14:04:59.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-11-21T14:45:14.000Z (11 months ago)
- Last Synced: 2025-03-25T14:39:03.596Z (7 months ago)
- Topics: deep-learning, eeg, eeg-classification, eeg-net, eeg-signals, pytorch
- Language: Python
- Homepage:
- Size: 50.8 KB
- Stars: 8
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.en_US.md
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README
English | [简体中文](README.zh-CN.md)
# EEG-PyTorch
Implementation of various simple networks for EEG classification tasks based on PyTorch.
## Implemented Networks
- [x] eeg-inception
- [x] eeg-lstm
- [ ] eeg-gcn
## Usage
### Installation
Install using PYPI.
```sh
pip install eeg-networks
```
If you do not want to install the package, you can also clone this project and install the required packages.
```sh
git clone https://github.com/zrr1999/eeg-networks-pytorch
cd eeg-networks-pytorch
pip install -r requirements.txt
```
### Training
You can train the model using the following command.
```sh
python train.py --model_name inception --device cpu --dataset_path ./GIB-UVA ERP-BCI.hdf5 --model_path ./weights
```
Use the following command to get more detailed information.
```sh
python train.py --help
```
### Validation
You can validate the model using the following command.
```sh
python val.py --model_path ./weights/last.pth --model_name inception
```
Use the following command to get more detailed information.
```sh
python val.py --help
```
## References
[GIB-UVa ERP-BCI dataset](https://www.kaggle.com/datasets/esantamaria/gibuva-erpbci-dataset?resource=download)