Metadata-Version: 2.1
Name: vsgan
Version: 1.3.1
Summary: VapourSynth Single Image Super-Resolution Generative Adversarial Network (GAN)
Home-page: https://github.com/rlaphoenix/vsgan
License: MIT
Keywords: vapoursynth,upscaling,gan,deep-learning,esrgan
Author: PHOENiX
Author-email: rlaphoenix@pm.me
Requires-Python: >=3.6.2,<4.0
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Multimedia :: Video
Requires-Dist: numpy (==1.19.5)
Requires-Dist: torch (>=1.9.1,<2.0.0)
Project-URL: Repository, https://github.com/rlaphoenix/vsgan
Description-Content-Type: text/markdown

# VSGAN

VSGAN is a Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data.

[![Build Tests](https://img.shields.io/github/workflow/status/rlaPHOENiX/VSGAN/Version%20test?label=Python%203.6%2B%20builds)](https://github.com/rlaPHOENiX/VSGAN/actions?query=workflow%3A%22Version+test%22)
[![License](https://img.shields.io/github/license/rlaPHOENiX/VSGAN?style=flat)](https://github.com/rlaPHOENiX/VSGAN/blob/master/LICENSE)
[![DeepSource](https://deepsource.io/gh/rlaPHOENiX/VSGAN.svg/?label=active+issues)](https://deepsource.io/gh/rlaPHOENiX/VSGAN/?ref=repository-badge)
[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/rlaPHOENiX/VSGAN/blob/master/VSGAN.ipynb)

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## Documentation

More information, installation, building, quick start, and more, is available at [rlaphoenix.github.io/VSGAN](https://rlaphoenix.github.io/VSGAN).

The source code to the Documentation page is available on the [gh-pages branch](https://github.com/rlaPHOENiX/VSGAN/tree/gh-pages) and can be built and deployed locally.  
You could also just read the markdown files found in the [_docs folder](https://github.com/rlaPHOENiX/VSGAN/tree/gh-pages/_docs).

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## License

This project is released under the MIT license.
Please read and agree to the license before use, it can be found in the [LICENSE](LICENSE) file.

