https://github.com/znxlwm/pytorch-conditional-image-to-image-translation
Pytorch implementation of Conditional image-to-image translation (CVPR 2018)
https://github.com/znxlwm/pytorch-conditional-image-to-image-translation
Last synced: 3 months ago
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Pytorch implementation of Conditional image-to-image translation (CVPR 2018)
- Host: GitHub
- URL: https://github.com/znxlwm/pytorch-conditional-image-to-image-translation
- Owner: znxlwm
- License: mit
- Created: 2018-07-25T05:21:10.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-01-25T11:50:46.000Z (over 6 years ago)
- Last Synced: 2024-09-05T15:48:30.138Z (about 1 year ago)
- Language: Python
- Homepage:
- Size: 886 KB
- Stars: 48
- Watchers: 3
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# pytorch-Conditional-image-to-image-translation
Pytorch implementation of Conditional image-to-image translation [1] (CVPR 2018)
* Parameters without information in the paper were set arbitrarily. (I could not find the supplementary document)
## Usage
```
python train.py --dataset dataset
```
### Folder structure
The following shows basic folder structure.
```
├── data
├── dataset # not included in this repo
├── trainA
├── aaa.png
├── bbb.jpg
└── ...
├── trainB
├── ccc.png
├── ddd.jpg
└── ...
├── testA
├── eee.png
├── fff.jpg
└── ...
└── testB
├── ggg.png
├── hhh.jpg
└── ...
├── train.py # training code
├── utils.py
├── networks.py
└── name_results # results to be saved here
```
## Resutls
### paper results
### celebA gender translation results (100 epoch)
InputA - InputB - A2B - B2A (this repo)
## Development Environment
* NVIDIA GTX 1080 ti
* cuda 8.0
* python 3.5.3
* pytorch 0.4.0
* torchvision 0.2.1
## Reference
[1] Lin, Jianxin, et al. "Conditional image-to-image translation." The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(July 2018). 2018.
(Full paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Conditional_Image-to-Image_Translation_CVPR_2018_paper.pdf)