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, Ghosts, Occurro, etc.
Tested on Pytorch 1.4-1.8. Sequence-to-video conversions require FFMPEG. For more explicit details refer to the original implementation.
Features
- streamlined workflow, focused on practical tasks
- cleaned up and simplified code for better readability
- stricter memory management to fit bigger batches on consumer GPUs
- models mixing (SWA) for better stability
Presumed file structure
stargan2 | root |
---|---|
├ _in | input data for processing |
├ _out | generation output (sequences & videos) |
├ data | datasets for training |
│ └ afhq | [example] some dataset |
│ ├ cats | [example] images for training |
│ │ └ test | [example] images for validation |
│ |