Preprocessor-for-EEG-Signals

Resource

• BrainStorming
• Reading List
• Google Slide

Tutorial

1. Clone this project.
   • For Windows:

     git clone --recurse-submodules https://github.com/aisu-programming/Preprocessor-for-EEG-Signals.git

   • For Mac: (Unclear, need to test)

     git clone https://github.com/aisu-programming/Preprocessor-for-EEG-Signals.git
     cd Preprocessor-for-EEG-Signals
     git submodule init
     git submodule update

2. Download the datasets below and put them in directory "datasets".
3. Rename the file ".env_sample" to ".env".

Dataset

• Automatically download

  ./download_datasets.sh

Environment

• With pip:

  pip install -r requirements.txt
  pip install torch  # Based on your environment, see more in the requirements.txt

• Can also use conda.
  

Tip

When running MacOS on Apple Silicon, also install tensorflow-metal to utilize GPU usage:

pip install tensorflow-metal

You'll want to run with a higher batch size to get the benefits.

Example: Baselines

• For baseline program in TensorFlow version - baselines_tensorflow.py
  1. If you are working on a Mac platform, set TF_USE_LEGACY_KERAS to True by:

     export TF_USE_LEGACY_KERAS=True

  2. Run the script:

     python baselines_tensorflow.py

• For baseline program in PyTorch version - baselines_pytorch.py
  Simply run the script:

  python baselines_pytorch.py

• For running on HPC Greene
  Adjust the command with slurm command prefix

  srun -c 16 --mem=64GB --gres=gpu:1 --time=02:00:00 --pty python baselines_pytorch.py