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⚡[**HowTo**](#-HOWTOs) **|** 🔧[**Installation**](docs/INSTALL.md) **|** 💻[**Training Commands**](docs/TrainTest.md) **|** 🐢[**DatasetPrepare**](docs/DatasetPreparation.md) **|** 🏰[**Model Zoo**](docs/ModelZoo.md) 📕[**中文解读文档**](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) 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.

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.

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(start from 2022-11-06)