The steps you need are very simple.
StarGAN2 for practice
This version of StarGAN2 (coined as 'Post-modern Style Transfer') is intended mostly for fellow artists, who rarely look at scientific metrics, but rather need a working creative tool. At least, this is what I use nearly daily myself.
Here are few pieces, made with it: Terminal Blink, Occurro, etc.
Tested on Pytorch 1.4-1.8. Sequence-to-video conversions require FFMPEG. For more explicit details refer to the original implementation.
- streamlined workflow, focused on practical tasks [TBA]
- cleaned up and simplified code for better readability
- stricter memory management to fit bigger batches on consumer GPUs
- models mixing (SWA) for better stability
NB: In the meantime here's only training code and some basic inference (processing). More various methods & use cases may be added later.
Presumed file structure
|├ _in||input data for processing|
|├ _out||generation output (sequences & videos)|
|├ data||datasets for|