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[**HowTo**](#-HOWTOs) **|** [**Installation**](docs/INSTALL.md) **|** [**Training Commands**](docs/TrainTest.md) **|** [**DatasetPrepare**](docs/DatasetPreparation.md) **|** [**Model Zoo**](docs/ModelZoo.md) [****](https://github.com/XPixelGroup/BasicSR-docs) **|** [**Plot scripts**](scripts/plot) **|** [Introduction](docs/introduction.md) **|** **|** [TODO List](https://github.com/xinntao/BasicSR/projects) **|** [FAQ](docs/FAQ.md)

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) PyTorch , , , , JPEG .

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.

latex @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.

• QQ: QQ: 320960100
  
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