XPixelGroup / BasicSR

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

Home Page:https://basicsr.readthedocs.io/en/latest/

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🚀 We add BasicSR-Examples, which provides guidance and templates of using BasicSR as a python package. 🚀
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BasicSR (Basic Super Restoration) is an open-source image and video restoration toolbox based on PyTorch, such as super-resolution, denoise, deblurring, JPEG artifacts removal, etc.
BasicSR (Basic Super Restoration) 是一个基于 PyTorch 的开源 图像视频复原工具箱, 比如 超分辨率, 去噪, 去模糊, 去 JPEG 压缩噪声等.

🚩 New Features/Updates

  • July 26, 2022. Add plot scripts 📊Plot.
  • May 9, 2022. BasicSR joins XPixel.
  • Oct 5, 2021. Add ECBSR training and testing codes: ECBSR.

    ACMMM21: Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices

  • Sep 2, 2021. Add SwinIR training and testing codes: SwinIR by Jingyun Liang. More details are in HOWTOs.md
  • Aug 5, 2021. Add NIQE, which produces the same results as MATLAB (both are 5.7296 for tests/data/baboon.png).
  • July 31, 2021. Add bi-directional video super-resolution codes: BasicVSR and IconVSR.

    CVPR21: BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

  • More

If BasicSR helps your research or work, please help to this repo or recommend it to your friends. Thanks😊
Other recommended projects:
▶️ Real-ESRGAN: A practical algorithm for general image restoration
▶️ GFPGAN: A practical algorithm for real-world face restoration
▶️ facexlib: A collection that provides useful face-relation functions.
▶️ HandyView: A PyQt5-based image viewer that is handy for view and comparison.
▶️ HandyFigure: Open source of paper figures
(ESRGAN, EDVR, DNI, SFTGAN) (HandyCrawler, HandyWriting)


HOWTOs

We provide simple pipelines to train/test/inference models for a quick start. These pipelines/commands cannot cover all the cases and more details are in the following sections.

GAN
StyleGAN2 Train Inference
Face Restoration
DFDNet - Inference
Super Resolution
ESRGAN TODO TODO SRGAN TODO TODO
EDSR TODO TODO SRResNet TODO TODO
RCAN TODO TODO SwinIR Train Inference
EDVR TODO TODO DUF - TODO
BasicVSR TODO TODO TOF - TODO
Deblurring
DeblurGANv2 - TODO
Denoise
RIDNet - TODO CBDNet - TODO

Projects that use BasicSR

  • Real-ESRGAN: A practical algorithm for general image restoration
  • GFPGAN: A practical algorithm for real-world face restoration

If you use BasicSR in your open-source projects, welcome to contact me (by email or opening an issue/pull request). I will add your projects to the above list 😊

📜 License and Acknowledgement

This project is released under the Apache 2.0 license.
More details about license and acknowledgement are in LICENSE.

🌏 Citations

If BasicSR helps your research or work, please cite BasicSR.
The following is a BibTeX reference. The BibTeX entry requires the url LaTeX package.

@misc{basicsr,
  author =       {Xintao Wang and Liangbin Xie and Ke Yu and Kelvin C.K. Chan and Chen Change Loy and Chao Dong},
  title =        {{BasicSR}: Open Source Image and Video Restoration Toolbox},
  howpublished = {\url{https://github.com/XPixelGroup/BasicSR}},
  year =         {2022}
}

Xintao Wang, Liangbin Xie, Ke Yu, Kelvin C.K. Chan, Chen Change Loy and Chao Dong. BasicSR: Open Source Image and Video Restoration Toolbox. https://github.com/xinntao/BasicSR, 2022.

📧 Contact

If you have any questions, please email xintao.alpha@gmail.com, xintao.wang@outlook.com.


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visitors (start from 2022-11-06)

About

Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

https://basicsr.readthedocs.io/en/latest/

License:Apache License 2.0


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Language:Python 88.7%Language:Cuda 6.3%Language:C++ 4.2%Language:MATLAB 0.6%Language:Shell 0.1%