The aim of this assignment is to discover GANs, understand how they are implemented and then explore one specific architecture of GANs that allows us to perform image to image translation.
We recommand to use the notebook (.ipynb) but the Python script (.py) is also provided if more convenient for you.
My work for this project is available in the file : BE2_GAN_and_cGAN.ipynb.
# How to submit your Work ?
#Requirement
It requires torch, numpy, pillow, opencv-python, imageio
This work must be done individually. The expected output is a private repository named gan-cgan on https://gitlab.ec-lyon.fr. It must contain your notebook (or python files) and a README.md file that explains briefly the successive steps of the project. Don't forget to add your teacher as developer member of the project. The last commit is due before 11:59 pm on Monday, April 1st, 2024. Subsequent commits will not be considered.
#Author
Agnès Maassen - BE2 created by Dellandrea Emmanuel
