We recommand to use the notebook (.ipynb) but the Python script (.py) is also provided if more convenient for you.
Filipe PENNA CERAVOLO SOARES
# How to submit your Work ?
## Part1: DC-GAN
This work must be done individually. The expected output is a 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. The last commit is due before 11:59 pm on Wednesday, March 29, 2023. Subsequent commits will not be considered.
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- In this part, generative adversarial network (GAN) has been trained to generate new handwritten digits, after feeding it with pictures from the [**MNIST database**](https://en.wikipedia.org/wiki/MNIST_database)
- To do so, the [**DCGAN tutorial**](https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html) of pytorch has been followed. This tutorial generate new celebrities after showing it pictures of many real celebrities.
- To adapt this tutorial to the MNIST database, the most relevant change in its implematation reflects the change of number of channels in the training images (from 3 [*RGB*] to 1 [*Black and White*]).
