Open Source Image and Video Super-Resolution Toolbox
Project description
⚡HowTo | 🔧Installation | 💻Training Commands | 🐢DatasetPrepare | 🏰Model Zoo
📕中文解读文档 | 📊 Plot scripts | 📝Introduction | | ⏳TODO List | ❓FAQ
🚀 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 consider citing BasicSR.
The following is a BibTeX reference. The BibTeX entry requires the url
LaTeX package.
@misc{wang2020basicsr,
author = {Xintao Wang and Ke Yu and Kelvin C.K. Chan and
Chao Dong and Chen Change Loy},
title = {{BasicSR}: Open Source Image and Video Restoration Toolbox},
howpublished = {\url{https://github.com/xinntao/BasicSR}},
year = {2018}
}
Xintao Wang, Ke Yu, Kelvin C.K. Chan, Chao Dong and Chen Change Loy. BasicSR: Open Source Image and Video Restoration Toolbox. https://github.com/xinntao/BasicSR, 2018.
📧 Contact
If you have any questions, please email 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
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