Final project in IDATT2502 Applied Machine Learning at the NTNU.
This project uses pipenv for managing dependencies.
To install dependencies locally use the command pipenv.
To add a new/remove project dependency use pipenv (un)install.
To run a command in the virtual environment use pipenv run <cmd>.
To open a shell to run commands in use pipenv shell.
There are several variants of GANs in this project. Some take image labels into consideration like cGAN and cDCGAN, while the rest just generate random images that could be in the dataset. To train a model run the [model]_train.py file. If you want to continue from a previous file, use the --timestamp option. To sample a model run the model_sample.py file (--timestamp is required for this).
The model files are located in a folder with the name of the model type. The util folder contains functions used by all the models, like getting available devices and loading/saving state.
This project uses black to format and lint source code and isort to sort imports.
Pull request pipelines will fail if code is not formatted correctly.
To run black use pipenv run black ..
To run isort use pipenv run isort ..
