Python-StarGAN的简单Tensorflow实现CVPR2018Oral

<p align="center"><img width="40%" src="./assests/logo.jpg" /></p> -------------------------------------------------------------------------------- ## Requirements * Tensorflow 1.8 * Python 3.6 ## Usage ### Downloading the dataset ```python > python download.py celebA ``` ``` ├── dataset    └── celebA    ├── train           ├── 000001.jpg ├── 000002.jpg └── ... ├── test (It is not celebA) ├── a.jpg (The test image that you wanted) ├── b.png └── ... ├── list_attr_celeba.txt (For attribute information) ``` ### Train * python main.py --phase train ### Test * python main.py --phase test * The celebA test image and the image you wanted run simultaneously ### Pretrained model * Download [checkpoint for 128x128](https://drive.google.com/open?id=1ezwtU1O_rxgNXgJaHcAynVX8KjMt0Ua-) ## Summary  ## Results (128x128, wgan-gp) ### Women  ### Men  ## Related works * [CycleGAN-Tensorflow](https://github.com/taki0112/CycleGAN-Tensorflow) * [DiscoGAN-Tensorflow](https://github.com/taki0112/DiscoGAN-Tensorflow) * [UNIT-Tensorflow](https://github.com/taki0112/UNIT-Tensorflow) * [MUNIT-Tensorflow](https://github.com/taki0112/MUNIT-Tensorflow) ## Reference * [StarGAN paper](https://arxiv.org/abs/1711.09020) * [Author pytorch code](https://github.com/yunjey/StarGAN) ## Author Junho Kim