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<p align="center"> <img src="assets/basicsr_xpixel_logo.png" height=120> </p><div align="center"><b><a href="README.md">English</a> | <a href="README_CN.md">简体中文</a></b></div>
<div align="center"> </div> <div align="center">⚡HowTo | 🔧Installation | 💻Training Commands | 🐢DatasetPrepare | 🏰Model Zoo
📕中文解读文档 | 📊 Plot scripts | 📝Introduction | <a href="https://github.com/XPixelGroup/BasicSR/tree/master/colab"><img src="https://colab.research.google.com/assets/colab-badge.svg" height="18" alt="google colab logo"></a> | ⏳TODO List | ❓FAQ
</div>🚀 We add BasicSR-Examples, which provides guidance and templates of using BasicSR as a python package. 🚀 <br> 📢 技术交流QQ群:320960100 入群答案:互帮互助共同进步 <br> 🧭 入群二维码 (QQ、微信) 入群指南 (腾讯文档) <br>
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.<br> 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😊 <br> Other recommended projects:<br> ▶️ Real-ESRGAN: A practical algorithm for general image restoration<br> ▶️ GFPGAN: A practical algorithm for real-world face restoration <br> ▶️ facexlib: A collection that provides useful face-relation functions.<br> ▶️ HandyView: A PyQt5-based image viewer that is handy for view and comparison. <br> ▶️ HandyFigure: Open source of paper figures <br> <sub>(ESRGAN, EDVR, DNI, SFTGAN)</sub> <sub>(HandyCrawler, HandyWriting)</sub>
⚡ 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.<br> More details about license and acknowledgement are in LICENSE.
🌏 Citations
If BasicSR helps your research or work, please cite BasicSR.<br>
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
.
- QQ群: 扫描左边二维码 或者 搜索QQ群号: 320960100 入群答案:互帮互助共同进步
- 微信群: 我们的一群已经满500人啦,二群也超过200人了;进群可以添加 Liangbin 的个人微信 (右边二维码),他会在空闲的时候拉大家入群~