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.gitignore 0 → 100644
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.idea/
damo/
training/
lightning_logs/
image_log/
*.pth
*.pt
*.ckpt
*.safetensors
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
pip-wheel-metadata/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
.python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
.vscode
/show_results/
*-ori.py
*.tar.gz
/tmp_dir/
/tmp_files/
/SaveImages/
/*.png
font/*.ttf
BasicSR/.github/workflows/publish-pip.yml 0 → 100644
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name: PyPI Publish
on: push
jobs:
build-n-publish:
runs-on: ubuntu-latest
if: startsWith(github.event.ref, 'refs/tags')
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.8
uses: actions/setup-python@v1
with:
python-version: 3.8
- name: Upgrade pip
run: pip install pip --upgrade
- name: Install PyTorch (cpu)
run: pip install torch==1.7.0+cpu torchvision==0.8.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install dependencies
run: pip install -r requirements.txt
- name: Build and install
run: rm -rf .eggs && pip install -e .
- name: Build for distribution
# remove bdist_wheel for pip installation with compiling cuda extensions
run: python setup.py sdist
- name: Publish distribution to PyPI
uses: pypa/gh-action-pypi-publish@master
with:
password: ${{ secrets.PYPI_API_TOKEN }}
BasicSR/.github/workflows/pylint.yml 0 → 100644
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name: PyLint
on: [push, pull_request]
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: [3.8]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install codespell flake8 isort yapf
- name: Lint
run: |
codespell
flake8 .
isort --check-only --diff basicsr/ options/ scripts/ tests/ inference/ setup.py
yapf -r -d basicsr/ options/ scripts/ tests/ inference/ setup.py
BasicSR/.github/workflows/release.yml 0 → 100644
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name: release
on:
push:
tags:
- '*'
jobs:
build:
permissions: write-all
name: Create Release
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v2
- name: Create Release
id: create_release
uses: actions/create-release@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
tag_name: ${{ github.ref }}
release_name: BasicSR ${{ github.ref }} Release Note
body: |
🚀 See you again 😸
🚀Have a nice day 😸 and happy everyday 😃
🚀 Long time no see ☄️
✨ **Highlights**
✅ [Features] Support ...
🐛 **Bug Fixes**
🌴 **Improvements**
📢📢📢
<p align="center">
<img src="https://raw.githubusercontent.com/XPixelGroup/BasicSR/master/assets/basicsr_xpixel_logo.png" height=150>
</p>
draft: true
prerelease: false
BasicSR/.gitignore 0 → 100644
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# ignored folders
datasets/*
experiments/*
results/*
tb_logger/*
wandb/*
tmp/*
docs/api
scripts/__init__.py
*.DS_Store
.idea
# ignored files
version.py
# ignored files with suffix
*.html
*.png
*.jpeg
*.jpg
*.gif
*.pth
*.zip
# template
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
.hypothesis/
.pytest_cache/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
target/
# Jupyter Notebook
.ipynb_checkpoints
# pyenv
.python-version
# celery beat schedule file
celerybeat-schedule
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
BasicSR/.pre-commit-config.yaml 0 → 100644
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repos:
# flake8
- repo: https://github.com/PyCQA/flake8
rev: 3.8.3
hooks:
- id: flake8
args: ["--config=setup.cfg", "--ignore=W504, W503"]
# modify known_third_party
- repo: https://github.com/asottile/seed-isort-config
rev: v2.2.0
hooks:
- id: seed-isort-config
# isort
- repo: https://github.com/timothycrosley/isort
rev: 5.2.2
hooks:
- id: isort
# yapf
- repo: https://github.com/pre-commit/mirrors-yapf
rev: v0.30.0
hooks:
- id: yapf
# codespell
- repo: https://github.com/codespell-project/codespell
rev: v2.1.0
hooks:
- id: codespell
# pre-commit-hooks
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.2.0
hooks:
- id: trailing-whitespace # Trim trailing whitespace
- id: check-yaml # Attempt to load all yaml files to verify syntax
- id: check-merge-conflict # Check for files that contain merge conflict strings
- id: double-quote-string-fixer # Replace double quoted strings with single quoted strings
- id: end-of-file-fixer # Make sure files end in a newline and only a newline
- id: requirements-txt-fixer # Sort entries in requirements.txt and remove incorrect entry for pkg-resources==0.0.0
- id: fix-encoding-pragma # Remove the coding pragma: # -*- coding: utf-8 -*-
args: ["--remove"]
- id: mixed-line-ending # Replace or check mixed line ending
args: ["--fix=lf"]
BasicSR/.readthedocs.yaml 0 → 100644
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# .readthedocs.yaml
# Read the Docs configuration file
# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
# Required
version: 2
# Set the version of Python and other tools you might need
build:
os: ubuntu-20.04
tools:
python: "3.8"
# You can also specify other tool versions:
# nodejs: "16"
# rust: "1.55"
# golang: "1.17"
# Build documentation in the docs/ directory with Sphinx
sphinx:
configuration: docs/conf.py
# If using Sphinx, optionally build your docs in additional formats such as PDF
# formats:
# - pdf
# Optionally declare the Python requirements required to build your docs
python:
install:
- requirements: docs/requirements.txt
BasicSR/CITATION.cff 0 → 100644
View file @ b95c05a9
cff-version: 1.2.0
message: "If you use this project, please cite it as below."
title: "BasicSR: Open Source Image and Video Restoration Toolbox"
version: 1.3.5
date-released: 2022-02-16
url: "https://github.com/XPixelGroup/BasicSR"
license: Apache-2.0
authors:
- family-names: Wang
given-names: Xintao
- family-names: Xie
given-names: Liangbin
- family-names: Yu
given-names: Ke
- family-names: Chan
given-names: Kelvin C.K.
- family-names: Loy
given-names: Chen Change
- family-names: Dong
given-names: Chao
BasicSR/LICENSE.txt 0 → 100644
View file @ b95c05a9
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
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"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
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"Source" form shall mean the preferred form for making modifications,
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source, and configuration files.
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transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
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"Derivative Works" shall mean any work, whether in Source or Object
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APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
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Copyright 2018-2022 BasicSR Authors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
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Unless required by applicable law or agreed to in writing, software
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BasicSR/LICENSE/LICENSE-NVIDIA 0 → 100644
View file @ b95c05a9
Copyright (c) 2019, NVIDIA Corporation. All rights reserved.
Nvidia Source Code License-NC
=======================================================================
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=======================================================================
BasicSR/LICENSE/LICENSE-stylegan2-pytorch 0 → 100644
View file @ b95c05a9
MIT License
Copyright (c) 2019 Kim Seonghyeon
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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SOFTWARE.
BasicSR/LICENSE/LICENSE_SwinIR 0 → 100644
View file @ b95c05a9
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
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# License and Acknowledgement
This BasicSR project is released under the Apache 2.0 license.
- StyleGAN2
- The codes are modified from the repository [stylegan2-pytorch](https://github.com/rosinality/stylegan2-pytorch). Many thanks to the author - [Kim Seonghyeon](https://rosinality.github.io/) :blush: for translating from the official TensorFlow codes to PyTorch ones. Here is the [license](LICENSE-stylegan2-pytorch) of stylegan2-pytorch.
- The official repository is <https://github.com/NVlabs/stylegan2>, and here is the [NVIDIA license](./LICENSE-NVIDIA).
- DFDNet
- The codes are largely modified from the repository [DFDNet](https://github.com/csxmli2016/DFDNet). Their license is [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/).
- DiffJPEG
- Modified from <https://github.com/mlomnitz/DiffJPEG>.
- [pytorch-image-models](https://github.com/rwightman/pytorch-image-models/)
- We use the implementation of `DropPath` and `trunc_normal_` from [pytorch-image-models](https://github.com/rwightman/pytorch-image-models/). The LICENSE is included as [LICENSE_pytorch-image-models](LICENSE/LICENSE_pytorch-image-models).
- [SwinIR](https://github.com/JingyunLiang/SwinIR)
- The arch implementation of SwinIR is from [SwinIR](https://github.com/JingyunLiang/SwinIR). The LICENSE is included as [LICENSE_SwinIR](LICENSE/LICENSE_SwinIR).
- [ECBSR](https://github.com/xindongzhang/ECBSR)
- The arch implementation of ECBSR is from [ECBSR](https://github.com/xindongzhang/ECBSR). The LICENSE of ECBSR is [Apache License 2.0](https://github.com/xindongzhang/ECBSR/blob/main/LICENSE)
## References
1. NIQE metric: the codes are translated from the [official MATLAB codes](http://live.ece.utexas.edu/research/quality/niqe_release.zip)
> A. Mittal, R. Soundararajan and A. C. Bovik, "Making a Completely Blind Image Quality Analyzer", IEEE Signal Processing Letters, 2012.
1. FID metric: the codes are modified from [pytorch-fid](https://github.com/mseitzer/pytorch-fid) and [stylegan2-pytorch](https://github.com/rosinality/stylegan2-pytorch).
BasicSR/MANIFEST.in 0 → 100644
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include basicsr/ops/dcn/src/*.cu basicsr/ops/dcn/src/*.cpp
include basicsr/ops/fused_act/src/*.cu basicsr/ops/fused_act/src/*.cpp
include basicsr/ops/upfirdn2d/src/*.cu basicsr/ops/upfirdn2d/src/*.cpp
include basicsr/metrics/niqe_pris_params.npz
include VERSION
include requirements.txt
BasicSR/README.md 0 → 100644
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<p align="center">
<img src="assets/basicsr_xpixel_logo.png" height=120>
</p>
## <div align="center"><b><a href="README.md">English</a> | <a href="README_CN.md">简体中文</a></b></div>
<div align="center">
[![LICENSE](https://img.shields.io/github/license/xinntao/basicsr.svg)](https://github.com/xinntao/BasicSR/blob/master/LICENSE.txt)
[![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)
</div>
<div align="center">
⚡[**HowTo**](#-HOWTOs) **|** 🔧[**Installation**](docs/INSTALL.md) **|** 💻[**Training Commands**](docs/TrainTest.md) **|** 🐢[**DatasetPrepare**](docs/DatasetPreparation.md) **|** 🏰[**Model Zoo**](docs/ModelZoo.md)
📕[**中文解读文档**](https://github.com/XPixelGroup/BasicSR-docs) **|** 📊 [**Plot scripts**](scripts/plot) **|** 📝[Introduction](docs/introduction.md) **|** <a href="https://github.com/XPixelGroup/BasicSR/tree/master/colab"><img src="https://colab.research.google.com/assets/colab-badge.svg" height="18" alt="google colab logo"></a> **|** ⏳[TODO List](https://github.com/xinntao/BasicSR/projects) **|** ❓[FAQ](docs/FAQ.md)
</div>
🚀 We add [BasicSR-Examples](https://github.com/xinntao/BasicSR-examples), which provides guidance and templates of using BasicSR as a python package. 🚀 <br>
📢 **技术交流QQ群**：**320960100** &emsp; 入群答案：**互帮互助共同进步** <br>
🧭 [入群二维码](#-contact) (QQ、微信) &emsp;&emsp; [入群指南 (腾讯文档)](https://docs.qq.com/doc/DYXBSUmxOT0xBZ05u) <br>
---
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*.<br>
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.
🚩 **New Features/Updates**
- ✅ July 26, 2022. Add plot scripts 📊[Plot](scripts/plot).
- ✅ May 9, 2022. BasicSR joins [XPixel](http://xpixel.group/).
- ✅ 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
- ✅ 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)
- ✅ 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](https://arxiv.org/abs/2012.02181).
> 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😊 <br>
Other recommended projects:<br>
▶️ [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN): A practical algorithm for general image restoration<br>
▶️ [GFPGAN](https://github.com/TencentARC/GFPGAN): A practical algorithm for real-world face restoration <br>
▶️ [facexlib](https://github.com/xinntao/facexlib): A collection that provides useful face-relation functions.<br>
▶️ [HandyView](https://github.com/xinntao/HandyView): A PyQt5-based image viewer that is handy for view and comparison. <br>
▶️ [HandyFigure](https://github.com/xinntao/HandyFigure): Open source of paper figures <br>
<sub>([ESRGAN](https://github.com/xinntao/ESRGAN), [EDVR](https://github.com/xinntao/EDVR), [DNI](https://github.com/xinntao/DNI), [SFTGAN](https://github.com/xinntao/SFTGAN))</sub>
<sub>([HandyCrawler](https://github.com/xinntao/HandyCrawler), [HandyWriting](https://github.com/xinntao/HandyWriting))</sub>
---
## ⚡ 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**](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](#-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).<br>
More details about **license** and **acknowledgement** are in [LICENSE](LICENSE/README.md).
## 🌏 Citations
If BasicSR helps your research or work, please cite BasicSR.<br>
The following is a BibTeX reference. The BibTeX entry requires the `url` LaTeX package.
``` latex
@misc{basicsr,
author = {Xintao Wang and Liangbin Xie and Ke Yu and Kelvin C.K. Chan and Chen Change Loy and Chao Dong},
title = {{BasicSR}: Open Source Image and Video Restoration Toolbox},
howpublished = {\url{https://github.com/XPixelGroup/BasicSR}},
year = {2022}
}
```
> Xintao Wang, Liangbin Xie, Ke Yu, Kelvin C.K. Chan, Chen Change Loy and Chao Dong. BasicSR: Open Source Image and Video Restoration Toolbox. <https://github.com/xinntao/BasicSR>, 2022.
## 📧 Contact
If you have any questions, please email `xintao.alpha@gmail.com`, `xintao.wang@outlook.com`.
<br>
- **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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<img src="https://user-images.githubusercontent.com/17445847/134879983-6f2d663b-16e7-49f2-97e1-7c53c8a5f71a.jpg" height="300"> &emsp;
<img src="https://user-images.githubusercontent.com/17445847/139572512-8e192aac-00fa-432b-ac8e-a33026b019df.png" height="300">
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![visitors](https://visitor-badge.glitch.me/badge?page_id=XPixelGroup/BasicSR) (start from 2022-11-06)
BasicSR/README_CN.md 0 → 100644
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## <div align="center"><b><a href="README.md">English</a> | <a href="README_CN.md">简体中文</a></b></div>
[![LICENSE](https://img.shields.io/github/license/xinntao/basicsr.svg)](https://github.com/xinntao/BasicSR/blob/master/LICENSE.txt)
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<!-- [English](README.md) **|** [简体中文](README_CN.md) &emsp; [GitHub](https://github.com/xinntao/BasicSR) **|** [Gitee码云](https://gitee.com/xinntao/BasicSR) -->
:rocket: 我们添加了 [BasicSR-Examples](https://github.com/xinntao/BasicSR-examples), 它提供了使用BasicSR的指南以及模板 (以python package的形式) :rocket:
:loudspeaker: **技术交流QQ群**：**320960100** &emsp; 入群答案：**互帮互助共同进步**
:compass: [入群二维码](#e-mail-%E8%81%94%E7%B3%BB) (QQ、微信) &emsp;&emsp; [入群指南 (腾讯文档)](https://docs.qq.com/doc/DYXBSUmxOT0xBZ05u)
---
<a href="https://drive.google.com/drive/folders/1G_qcpvkT5ixmw5XoN6MupkOzcK1km625?usp=sharing"><img src="https://colab.research.google.com/assets/colab-badge.svg" height="18" alt="google colab logo"></a> Google Colab: [GitHub Link](colab) **|** [Google Drive Link](https://drive.google.com/drive/folders/1G_qcpvkT5ixmw5XoN6MupkOzcK1km625?usp=sharing) <br>
:m: [模型库](docs/ModelZoo_CN.md): :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)
: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) <br>
:file_folder: [数据](docs/DatasetPreparation_CN.md): :arrow_double_down: [百度网盘](https://pan.baidu.com/s/1AZDcEAFwwc1OC3KCd7EDnQ) (提取码:basr) :arrow_double_down: [Google Drive](https://drive.google.com/drive/folders/1gt5eT293esqY0yr1Anbm36EdnxWW_5oH?usp=sharing) <br>
:chart_with_upwards_trend: [wandb的训练曲线](https://app.wandb.ai/xintao/basicsr) <br>
:computer: [训练和测试的命令](docs/TrainTest_CN.md) <br>
:zap: [HOWTOs](#zap-howtos)
---
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: **新的特性/更新**
- :white_check_mark: Oct 5, 2021. 添加 **ECBSR 训练和测试** 代码: [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. 添加 **SwinIR 训练和测试** 代码: [SwinIR](https://github.com/JingyunLiang/SwinIR) by [Jingyun Liang](https://github.com/JingyunLiang). 更多内容参见 [HOWTOs.md](docs/HOWTOs.md#how-to-train-swinir-sr)
- :white_check_mark: Aug 5, 2021. 添加了NIQE， 它输出和MATLAB一样的结果 (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
- **[更多](docs/history_updates.md)**
:sparkles: **使用 BasicSR 的项目**
- [**Real-ESRGAN**](https://github.com/xinntao/Real-ESRGAN): 通用图像复原的实用算法
- [**GFPGAN**](https://github.com/TencentARC/GFPGAN): 真实场景人脸复原的实用算法
如果你的开源项目中使用了`BasicSR`, 欢迎联系我 ([邮件](#e-mail-%E8%81%94%E7%B3%BB)或者开一个issue/pull request)。我会将你的开源项目添加到上面的列表中 :blush:
---
如果 BasicSR 对你有所帮助，欢迎 :star: 这个仓库或推荐给你的朋友。Thanks:blush: <br>
其他推荐的项目:<br>
:arrow_forward: [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN): 通用图像复原的实用算法<br>
:arrow_forward: [GFPGAN](https://github.com/TencentARC/GFPGAN): 真实场景人脸复原的实用算法<br>
:arrow_forward: [facexlib](https://github.com/xinntao/facexlib): 提供实用的人脸相关功能的集合<br>
:arrow_forward: [HandyView](https://github.com/xinntao/HandyView): 基于PyQt5的 方便的看图比图工具<br>
<sub>([ESRGAN](https://github.com/xinntao/ESRGAN), [EDVR](https://github.com/xinntao/EDVR), [DNI](https://github.com/xinntao/DNI), [SFTGAN](https://github.com/xinntao/SFTGAN))</sub>
<sub>([HandyView](https://gitee.com/xinntao/HandyView), [HandyFigure](https://gitee.com/xinntao/HandyFigure), [HandyCrawler](https://gitee.com/xinntao/HandyCrawler), [HandyWriting](https://gitee.com/xinntao/HandyWriting))</sub>
---
## :zap: HOWTOs
我们提供了简单的流程来快速上手 训练/测试/推理 模型. 这些命令并不能涵盖所有用法, 更多的细节参见下面的部分.
| GAN | | | | | |
| :------------------- | :------------------------------------------: | :------------------------------------------: | :------- | :--------------------------------------------: | :----------------------------------------------------: |
| StyleGAN2 | [训练](docs/HOWTOs_CN.md#如何训练-StyleGAN2) | [测试](docs/HOWTOs_CN.md#如何测试-StyleGAN2) | | | |
| **Face Restoration** | | | | | |
| DFDNet | - | [测试](docs/HOWTOs_CN.md#如何测试-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: 依赖和安装
For detailed instructions refer to [docs/INSTALL.md](docs/INSTALL.md).
## :hourglass_flowing_sand: TODO 清单
参见 [project boards](https://github.com/xinntao/BasicSR/projects).
## :turtle: 数据准备
- 数据准备步骤, 参见 **[DatasetPreparation_CN.md](docs/DatasetPreparation_CN.md)**.
- 目前支持的数据集 (`torch.utils.data.Dataset`类), 参见 [Datasets_CN.md](docs/Datasets_CN.md).
## :computer: 训练和测试
- **训练和测试的命令**, 参见 **[TrainTest_CN.md](docs/TrainTest_CN.md)**.
- **Options/Configs**配置文件的说明, 参见 [Config_CN.md](docs/Config_CN.md).
- **Logging**日志系统的说明, 参见 [Logging_CN.md](docs/Logging_CN.md).
## :european_castle: 模型库和基准
- 目前支持的模型描述, 参见 [Models_CN.md](docs/Models_CN.md).
- **预训练模型和log样例**, 参见 **[ModelZoo_CN.md](docs/ModelZoo_CN.md)**.
- 我们也在 [wandb](https://app.wandb.ai/xintao/basicsr) 上提供了**训练曲线**等:
<p align="center">
<a href="https://app.wandb.ai/xintao/basicsr" target="_blank">
<img src="./assets/wandb.jpg" height="280">
</a></p>
## :memo: 代码库的设计和约定
参见 [DesignConvention_CN.md](docs/DesignConvention_CN.md).<br>
下图概括了整体的框架. 每个模块更多的描述参见: <br>
**[Datasets_CN.md](docs/Datasets_CN.md)**&emsp;|&emsp;**[Models_CN.md](docs/Models_CN.md)**&emsp;|&emsp;**[Config_CN.md](docs/Config_CN.md)**&emsp;|&emsp;**[Logging_CN.md](docs/Logging_CN.md)**
![overall_structure](./assets/overall_structure.png)
## :scroll: 许可
本项目使用 Apache 2.0 license.<br>
更多关于**许可**和**致谢**, 请参见 [LICENSE](LICENSE/README.md).
## :earth_asia: 引用
如果 BasicSR 对你有帮助, 请引用BasicSR. <br>
下面是一个 BibTex 引用条目, 它需要 `url` LaTeX package.
``` latex
@misc{basicsr,
author = {Xintao Wang and Liangbin Xie and Ke Yu and Kelvin C.K. Chan and Chen Change Loy and Chao Dong},
title = {{BasicSR}: Open Source Image and Video Restoration Toolbox},
howpublished = {\url{https://github.com/XPixelGroup/BasicSR}},
year = {2022}
}
```
> Xintao Wang, Liangbin Xie, Ke Yu, Kelvin C.K. Chan, Chen Change Loy and Chao Dong. BasicSR: Open Source Image and Video Restoration Toolbox. <https://github.com/xinntao/BasicSR>, 2022.
## :e-mail: 联系
若有任何问题, 请电邮 `xintao.alpha@gmail.com`, `xintao.wang@outlook.com`.
<br>
- **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**: 我们的群一已经满500人啦，进群二可以扫描中间的二维码；如果进群遇到问题，也可以添加 Liangbin 的个人微信 (右边二维码)，他会在空闲的时候拉大家入群~
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<img src="https://user-images.githubusercontent.com/17445847/134879983-6f2d663b-16e7-49f2-97e1-7c53c8a5f71a.jpg" height="300"> &emsp;
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<img src="https://user-images.githubusercontent.com/17445847/139572512-8e192aac-00fa-432b-ac8e-a33026b019df.png" height="300">
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BasicSR/basicsr/__init__.py 0 → 100644
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# https://github.com/xinntao/BasicSR
# flake8: noqa
from .archs import *
from .data import *
from .losses import *
from .metrics import *
from .models import *
from .ops import *
from .test import *
from .train import *
from .utils import *
from .version import __gitsha__, __version__
BasicSR/basicsr/archs/__init__.py 0 → 100644
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import importlib
from copy import deepcopy
from os import path as osp
from basicsr.utils import get_root_logger, scandir
from basicsr.utils.registry import ARCH_REGISTRY
__all__ = ['build_network']
# automatically scan and import arch modules for registry
# scan all the files under the 'archs' folder and collect files ending with '_arch.py'
arch_folder = osp.dirname(osp.abspath(__file__))
arch_filenames = [osp.splitext(osp.basename(v))[0] for v in scandir(arch_folder) if v.endswith('_arch.py')]
# import all the arch modules
_arch_modules = [importlib.import_module(f'basicsr.archs.{file_name}') for file_name in arch_filenames]
def build_network(opt):
opt = deepcopy(opt)
network_type = opt.pop('type')
net = ARCH_REGISTRY.get(network_type)(**opt)
logger = get_root_logger()
logger.info(f'Network [{net.__class__.__name__}] is created.')
return net
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