The goal of this repository is to capture the distribution of Steam banners with a StyleGAN2-ADA model (PyTorch).
Progression videos of the projection of Steam banners (Dog Trainer and My UnReal pet) with a network pre-trained by Nvidia on the LSUN DOG
dataset.
The Steam-OneFace
dataset,
obtained with the retinaface
face detection module:
- consists of 2.5k Steam banners (256x256 resolution) which should all feature exactly one face,
- can be downloaded (74 MB) with the following commands:
!gdown --id 1-0Nk7H6Cn3Nt60EdHG_NWSA8ohi2oBqr
!tar xf steam-oneface-lr_with_retinaface.tar.gz
- Run
training.ipynb
to train a model from scratch, - Run
image_sampling.ipynb
to generate images with a trained model, - To automatically resume training from the latest checkpoint, use my fork of StyleGAN2-ADA (PyTorch).
- Karras, Tero, et al. Training generative adversarial networks with limited data. NeurIPS 2020,
- Official implementation (PyTorch),
- Application to Steam banners using the TensorFlow implementation.