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README

English | 简体中文

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

HowTo | 🔧Installation | 💻Training Commands | 🐢DatasetPrepare | 🏰Model Zoo

📕中文解读文档 | 📊 Plot scripts | 📝Introduction | google colab logo |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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Core symbols most depended-on inside this repo

get
called by 114
basicsr/utils/registry.py
get_root_logger
called by 35
basicsr/utils/logger.py
keys
called by 26
basicsr/utils/registry.py
backward
called by 22
basicsr/archs/dfdnet_util.py
scandir
called by 19
basicsr/utils/misc.py
imfrombytes
called by 17
basicsr/utils/img_util.py
close
called by 17
basicsr/utils/lmdb_util.py
img2tensor
called by 16
basicsr/utils/img_util.py

Shape

Method 489
Function 257
Class 173

Languages

Python100%

Modules by API surface

basicsr/archs/swinir_arch.py55 symbols
basicsr/archs/stylegan2_arch.py53 symbols
basicsr/utils/diffjpeg.py48 symbols
basicsr/data/degradations.py30 symbols
basicsr/models/base_model.py26 symbols
basicsr/archs/hifacegan_util.py25 symbols
basicsr/ops/dcn/deform_conv.py24 symbols
basicsr/losses/basic_loss.py19 symbols
basicsr/archs/dfdnet_util.py19 symbols
basicsr/utils/file_client.py18 symbols
basicsr/data/prefetch_dataloader.py17 symbols
basicsr/archs/ridnet_arch.py17 symbols

Dependencies from manifests, versioned

numpy1.17 · 1×
torch1.7 · 1×

For agents

$ claude mcp add BasicSR \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact