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LICENSE PyPI Language grade: Python python lint Publish-pip gitee mirror

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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

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🚀 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


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
StyleGAN2TrainInference
Face Restoration
DFDNet-Inference
Super Resolution
ESRGANTODOTODOSRGANTODOTODO
EDSRTODOTODOSRResNetTODOTODO
RCANTODOTODOSwinIRTrainInference
EDVRTODOTODODUF-TODO
BasicVSRTODOTODOTOF-TODO
Deblurring
DeblurGANv2-TODO
Denoise
RIDNet-TODOCBDNet-TODO

Projects that use BasicSR

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.

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visitors (start from 2022-11-06)