https://github.com/jmiller656/DiscoGAN-Tensorflow
An implementation of DiscoGAN in tensorflow
https://github.com/jmiller656/DiscoGAN-Tensorflow
discogan generative-adversarial-networks machine-learning neural-networks tensorflow
Last synced: 11 months ago
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An implementation of DiscoGAN in tensorflow
- Host: GitHub
- URL: https://github.com/jmiller656/DiscoGAN-Tensorflow
- Owner: jmiller656
- License: mit
- Created: 2017-03-29T04:35:56.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2017-06-26T00:29:42.000Z (almost 9 years ago)
- Last Synced: 2024-08-08T23:24:02.881Z (almost 2 years ago)
- Topics: discogan, generative-adversarial-networks, machine-learning, neural-networks, tensorflow
- Language: Python
- Size: 14.6 KB
- Stars: 79
- Watchers: 4
- Forks: 14
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DiscoGAN for Tensorflow
An implementation of [Learning to Discover Cross-Domain Relations with Generative Adversarial Networks](https://arxiv.org/abs/1703.05192) written in tensorflow.
## Requirements
- Tensorflow 1.0.1
- scipy
## Training
`python main.py`
## Training details
Currently the data utils file works on domains from the celeba dataset
## Remarks
As it currently stands, I have refactored much of the model and extracted it to `discoGAN.py`. I will soon be making it take command line arguments, download datasets automatically, etc. As mentioned before, there are now some barebones utilities to work with the celeba dataset.