⚡ HowTo | ? Installation | Training Commands | ? DatasetPrepare | ? Model Zoo
Chinese Interpretation Document | Plot scripts | Introduction | | ⏳TODO List | ❓FAQ
We add BasicSR-Examples, which provides guidance and templates of using BasicSR as a python package.
? Technical Exchange QQ Group : 320960100 Join the group Answer: Help each other and make progress together
? Group entry QR code (QQ, WeChat) Group entry guide (Tencent Document)
BasicSR ( Basic S uper Re estoration) is an open-source image and video restoration toolbox based on PyTorch, such as super-resolution, denoise, deblurring, JPEG artifacts removal, etc.
BasicSR ( Basic S uper Re estoration) is an open source image video recovery toolbox based on PyTorch, such as super resolution, denoising, defuzzing, decompressing JPEG noise, etc.
New Features/Updates
ACMMM21: Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices
CVPR21: BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
If BasicSR helps your research or work, please help to this repo or recommend it to your friends. Thanks?
Other recommended projects:
(ESRGAN, EDVR, DNI, SFTGAN) (HandyCrawler, HandyWriting)
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 |
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 ?
This project is released under the Apache 2.0 license.
More details about license and acknowledgement are in LICENSE.
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 CK Chan, Chen Change Loy and Chao Dong. BasicSR: Open Source Image and Video Restoration Toolbox. https://github.com/xinntao/BasicSR, 2022.
If you have any questions, please email [email protected] , [email protected] .


(start from 2022-11-06)