OOGAN-pytorch

Model overview:

OOGAN based on vanilla GAN

code to define the networks: oogan_models.py, oogan_modules.py
to train the model on your data, first prepare your images inside a root folder with subfolders containing your images, then edit the "config.py" for all hyperparameter settings, templetes are provided inside, then run
```
python train.py
```
the training will print log on terminal, and save the generated models and images during training.
to generate images from trained model, first edit the model path in "generate.py", then run:
```
python generate.py
```

On celebA:

On 3D chair:

On MNIST:

On dSprite:

This implementation is based on the stylegan implementation from here, please refer to that repo for updated code and usage.

code: ./oogan_stylegan/oo_stylegan_train.py, ./oogan_stylegan/oo_stylegan_modules.py
to train the model on your data
```
python oo_stylegan_train.py /path/to/image_root
```
the training will print log on terminal and save the generated models and images during training.

Name		Name	Last commit message	Last commit date
Latest commit History 16 Commits
demo		demo
metrics		metrics
oo_stylegan		oo_stylegan
README.md		README.md
config.py		config.py
dist.py		dist.py
generate.py		generate.py
helper_functions.py		helper_functions.py
oogan_models.py		oogan_models.py
oogan_modules.py		oogan_modules.py
train.py		train.py