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basetenlabs/BasicSR

Description: Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

Language: Python

License: Apache-2.0

Stars: 0

Forks: 0

Open issues: 0

Created: 2022-07-13T15:20:42Z

Pushed: 2022-07-13T15:39:58Z

Default branch: master

Fork: yes

Parent repository: XPixelGroup/BasicSR

Archived: no

README:

##

![python lint](https://github.com/xinntao/BasicSR/blob/master/.github/workflows/pylint.yml) ![Publish-pip](https://github.com/xinntao/BasicSR/blob/master/.github/workflows/publish-pip.yml) ![gitee mirror](https://github.com/xinntao/BasicSR/blob/master/.github/workflows/gitee-mirror.yml)

🚀 We add BasicSR-Examples, which provides guidance and templates of using BasicSR as a python package. 🚀

📢 技术交流QQ群：320960100   入群答案：互帮互助共同进步

🧭 [入群二维码](#-contact) (QQ、微信)    入群指南 (腾讯文档)

---

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

  • ✅ 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](docs/HOWTOs.md#how-to-train-swinir-sr)
  • ✅ 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](docs/history_updates.md)

---

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](docs/HOWTOs.md#How-to-train-StyleGAN2) | [Inference](docs/HOWTOs.md#How-to-inference-StyleGAN2) | | | | | Face Restoration | | | | | | | DFDNet | - | [Inference](docs/HOWTOs.md#How-to-inference-DFDNet) | | | | | Super Resolution | | | | | | | ESRGAN | *TODO* | *TODO* | SRGAN | *TODO* | *TODO* | | EDSR | *TODO* | *TODO* | SRResNet | *TODO* | *TODO* | | RCAN | *TODO* | *TODO* | SwinIR | [Train](docs/HOWTOs.md#how-to-train-swinir-sr) | [Inference](docs/HOWTOs.md#how-to-inference-swinir-sr) | | 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](#-contact) 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](LICENSE.txt).

More details about license and acknowledgement are in [LICENSE](LICENSE/README.md).

🌏 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. , 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
  • 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~