A tutorial explaining how to train and generate high-quality anime faces with StyleGAN 1+2 neural networks, and tips/scripts for effective StyleGAN use.
Generative neural networks, such as GANs, have struggled for years to generate decent-quality anime faces, despite their great success with photographic imagery such as real human faces. The task has now been effectively solved, for anime faces as well as many other domains, by the development of a new generative adversarial network, StyleGAN, whose source code was released in February 2019.
I show off my StyleGAN 1+2 CC-0-licensed anime faces & videos, provide downloads for the final models & anime portrait face dataset, provide the ‘missing manual’ & explain how I trained them based on Danbooru2017/2018 with source code for the data preprocessing, document installation & configuration & training tricks.
For application, I document various scripts for generating images & videos, briefly describe the website “This Waifu Does Not Exist” I set up as a public demo & its followup This Anime Does Not Exist.ai (TADNE) (see also Artbreeder), discuss how the trained models can be used for transfer learning such as generating high-quality faces of anime characters with small datasets (eg. Holo or Asuka Souryuu Langley), and touch on more advanced StyleGAN applications like encoders & controllable generation.
The anime face graveyard gives samples of my failures with earlier GANs for anime face generation, and I provide samples & model from a relatively large-scale BigGAN training run suggesting that BigGAN may be the next step forward to generating full-scale anime images.
A minute of reading could save an hour of debugging!
StyleGAN-2 Is Obsolete
- Examples
- Background
- FAQ
- Training Requirements
- Data Preparation
- Training
- Sampling
- Models
- Transfer Learning
- Reversing StyleGAN To Control & Modify Images
- StyleGAN 2
- Future Work
- BigGAN
- See Also
- External Links
- Appendix