# BasicSR **Repository Path**: tcexeexe/BasicSR ## Basic Information - **Project Name**: BasicSR - **Description**: 开源图像和视频复原工具包（超分辨率，去噪，去模糊等）. 目前包括: EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR 等模型. 也支持了 StyleGAN2 和 DFDNet. - **Primary Language**: Python - **License**: Not specified - **Default Branch**: master - **Homepage**: http://xinntao.gitee.io/ - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 44 - **Created**: 2021-10-27 - **Last Updated**: 2024-11-23 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # :rocket: BasicSR [![LICENSE](https://img.shields.io/github/license/xinntao/basicsr.svg)](https://github.com/xinntao/BasicSR/blob/master/LICENSE/LICENSE) [![PyPI](https://img.shields.io/pypi/v/basicsr)](https://pypi.org/project/basicsr/) [![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/xinntao/BasicSR.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/xinntao/BasicSR/context:python) [![python lint](https://github.com/xinntao/BasicSR/actions/workflows/pylint.yml/badge.svg)](https://github.com/xinntao/BasicSR/blob/master/.github/workflows/pylint.yml) [![Publish-pip](https://github.com/xinntao/BasicSR/actions/workflows/publish-pip.yml/badge.svg)](https://github.com/xinntao/BasicSR/blob/master/.github/workflows/publish-pip.yml) [![gitee mirror](https://github.com/xinntao/BasicSR/actions/workflows/gitee-mirror.yml/badge.svg)](https://github.com/xinntao/BasicSR/blob/master/.github/workflows/gitee-mirror.yml) [English](README.md) **|** [简体中文](README_CN.md) [GitHub](https://github.com/xinntao/BasicSR) **|** [Gitee码云](https://gitee.com/xinntao/BasicSR) :rocket: We add [BasicSR-Examples](https://github.com/xinntao/BasicSR-examples), which provides guidance and templates of using BasicSR as a python package. :rocket: :loudspeaker: **技术交流QQ群**：**320960100** 入群答案：**互帮互助共同进步** :compass: [入群二维码](#e-mail-contact) (QQ、微信) [入群指南 (腾讯文档)](https://docs.qq.com/doc/DYXBSUmxOT0xBZ05u) ---

Google Colab: [GitHub Link](colab) **|** [Google Drive Link](https://drive.google.com/drive/folders/1G_qcpvkT5ixmw5XoN6MupkOzcK1km625?usp=sharing)
:m: [Model Zoo](docs/ModelZoo.md): :arrow_double_down: Google Drive: [Pretrained Models](https://drive.google.com/drive/folders/15DgDtfaLASQ3iAPJEVHQF49g9msexECG?usp=sharing) **|** [Reproduced Experiments](https://drive.google.com/drive/folders/1XN4WXKJ53KQ0Cu0Yv-uCt8DZWq6uufaP?usp=sharing) :arrow_double_down: 百度网盘: [预训练模型](https://pan.baidu.com/s/1R6Nc4v3cl79XPAiK0Toe7g) **|** [复现实验](https://pan.baidu.com/s/1UElD6q8sVAgn_cxeBDOlvQ)
:file_folder: [Datasets](docs/DatasetPreparation.md): :arrow_double_down: [Google Drive](https://drive.google.com/drive/folders/1gt5eT293esqY0yr1Anbm36EdnxWW_5oH?usp=sharing) :arrow_double_down: [百度网盘](https://pan.baidu.com/s/1AZDcEAFwwc1OC3KCd7EDnQ) (提取码:basr)
:chart_with_upwards_trend: [Training curves in wandb](https://app.wandb.ai/xintao/basicsr)
:computer: [Commands for training and testing](docs/TrainTest.md)
:zap: [HOWTOs](#zap-howtos) --- BasicSR (**Basic** **S**uper **R**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 **R**estoration) 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. :triangular_flag_on_post: **New Features/Updates** - :white_check_mark: Oct 5, 2021. Add **ECBSR training and testing** codes: [ECBSR](https://github.com/xindongzhang/ECBSR). > ACMMM21: Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices - :white_check_mark: Sep 2, 2021. Add **SwinIR training and testing** codes: [SwinIR](https://github.com/JingyunLiang/SwinIR) by [Jingyun Liang](https://github.com/JingyunLiang). More details are in [HOWTOs.md](docs/HOWTOs.md#how-to-train-swinir-sr) - :white_check_mark: Aug 5, 2021. Add NIQE, which produces the same results as MATLAB (both are 5.7296 for tests/data/baboon.png). - :white_check_mark: July 31, 2021. Add **bi-directional video super-resolution** codes: [**BasicVSR** and IconVSR](https://arxiv.org/abs/2012.02181). > CVPR21: BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond - **[More](docs/history_updates.md)** :sparkles: **Projects that use BasicSR** - [**Real-ESRGAN**](https://github.com/xinntao/Real-ESRGAN): A practical algorithm for general image restoration - [**GFPGAN**](https://github.com/TencentARC/GFPGAN): A practical algorithm for real-world face restoration If you use `BasicSR` in your open-source projects, welcome to contact me (by [email](#e-mail-contact) or opening an issue/pull request). I will add your projects to the above list :blush: --- If BasicSR helps your research or work, please help to :star: this repo or recommend it to your friends. Thanks:blush:
Other recommended projects:
:arrow_forward: [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN): A practical algorithm for general image restoration
:arrow_forward: [GFPGAN](https://github.com/TencentARC/GFPGAN): A practical algorithm for real-world face restoration
:arrow_forward: [facexlib](https://github.com/xinntao/facexlib): A collection that provides useful face-relation functions.
:arrow_forward: [HandyView](https://github.com/xinntao/HandyView): A PyQt5-based image viewer that is handy for view and comparison.
_{([ESRGAN](https://github.com/xinntao/ESRGAN), [EDVR](https://github.com/xinntao/EDVR), [DNI](https://github.com/xinntao/DNI), [SFTGAN](https://github.com/xinntao/SFTGAN))} _{([HandyView](https://github.com/xinntao/HandyView), [HandyFigure](https://github.com/xinntao/HandyFigure), [HandyCrawler](https://github.com/xinntao/HandyCrawler), [HandyWriting](https://github.com/xinntao/HandyWriting))} --- ## :zap: 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*| ## :wrench: Dependencies and Installation For detailed instructions refer to [INSTALL.md](INSTALL.md). ## :hourglass_flowing_sand: TODO List Please see [project boards](https://github.com/xinntao/BasicSR/projects). ## :turtle: Dataset Preparation - Please refer to **[DatasetPreparation.md](docs/DatasetPreparation.md)** for more details. - The descriptions of currently supported datasets (`torch.utils.data.Dataset` classes) are in [Datasets.md](docs/Datasets.md). ## :computer: Train and Test - **Training and testing commands**: Please see **[TrainTest.md](docs/TrainTest.md)** for the basic usage. - **Options/Configs**: Please refer to [Config.md](docs/Config.md). - **Logging**: Please refer to [Logging.md](docs/Logging.md). ## :european_castle: Model Zoo and Baselines - The descriptions of currently supported models are in [Models.md](docs/Models.md). - **Pre-trained models and log examples** are available in **[ModelZoo.md](docs/ModelZoo.md)**. - We also provide **training curves** in [wandb](https://app.wandb.ai/xintao/basicsr):

## :memo: Codebase Designs and Conventions Please see [DesignConvention.md](docs/DesignConvention.md) for the designs and conventions of the BasicSR codebase.
The figure below shows the overall framework. More descriptions for each component:
**[Datasets.md](docs/Datasets.md)** | **[Models.md](docs/Models.md)** | **[Config.md](Config.md)** | **[Logging.md](docs/Logging.md)** ![overall_structure](./assets/overall_structure.png) ## :scroll: License and Acknowledgement This project is released under the Apache 2.0 license.
More details about **license** and **acknowledgement** are in [LICENSE](LICENSE/README.md). ## :earth_asia: 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. ``` latex @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 = {2020} } ``` > 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, 2020. ## :e-mail: Contact If you have any questions, please email `xintao.wang@outlook.com`.