GANsForVirtualEye: Time Series Generation Package

GANsForVirtualEye is a Python package that implements Generative Adversarial Networks (GANs) for time series data generation, offering flexible architecture options with CNN and LSTM models for both generators and discriminators.

Architecture

Installation

Prerequisites

• Python 3.6 or higher
• pip package manager

Steps

1. Clone the Repository

   git clone https://github.com/shailendrabhandari/GANsForVirtualEye.git
   cd GANsForVirtualEye
   

2. Install Required Packages

   It's recommended to use a virtual environment.

   pip install -r requirements.txt
   

3. Install the Package

   pip install .
   

Documentation

Detailed documentation is available at Read the Docs.

Author

• Shailendra Bhandari
  GitHub | Email

Citation

If you use this package in your research or projects, please cite it as:

@misc{bhandari2024modelingeyegazevelocity,
      title={Modeling Eye Gaze Velocity Trajectories using GANs with Spectral Loss for Enhanced Fidelity}, 
      author={Shailendra Bhandari and Pedro Lencastre and Rujeena Mathema and Alexander Szorkovszky and Anis Yazidi and Pedro Lind},
      year={2024},
      eprint={2412.04184},
      archivePrefix={arXiv},
      primaryClass={cs.NE},
      url={https://arxiv.org/abs/2412.04184}, 
}

Acknowledgment

Thank You for Using GAN Time Series Generation Package!

We hope this package helps you in your research or projects involving time series data generation.