Open Source Image and Video Super-Resolution Toolbox
⚡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
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:
▶️ 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)
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 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.
If you have any questions, please email xintao.wang@outlook.com
.