This repo contains the files for a project for the above-mentioned course at Singapore University of Technology and Design, Spring 2019.
The group members are Tenzin Chan and Chen Hui.
The project aims to explore the dynamics of Generative Adversarial Networks training. We have chosen to start with exploring the effects of using 2N output values for the discriminator, 2 neurons for each class, each specifying whether the output was real or fake for that class.
Install the requirements with pipenv install
To train the models, run python main.py
To generate the scores for the models, run python test.py
We have used code from the following sources (stars were given to respective repos):