UNIT-Tensorflow
Simple Tensorflow implementation of "Unsupervised Image to Image Translation Networks" (NIPS 2017 Spotlight)
Requirements
- Tensorflow 1.4
- Python 3.6
Usage
├── dataset
└── YOUR_DATASET_NAME
├── trainA
├── xxx.jpg (name, format doesn't matter)
├── yyy.png
└── ...
├── trainB
├── zzz.jpg
├── www.png
└── ...
├── testA
├── aaa.jpg
├── bbb.png
└── ...
└── testB
├── ccc.jpg
├── ddd.png
└── ...
> python main.py --phase train --dataset cat2tiger
- See
main.py
for other arguments - If you want to
multi_gpu_version
, then usemain_multi_gpu.py
(batch_size = The batch_size per gpu) - If you want to
faster_UNIT
, then useDatasetAPI
(code is more simple !)
Issue
Too much Slow !!!
- The slower reason is that it stores checkpoints
- If you want to speed up, do not save checkpoints per iteration
Arichitecture
Framework
Model
Training Objective
Result
Success
Fail
Related works
Reference
Author
Junho Kim