Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.

Overview

EDVR has been merged into BasicSR. This GitHub repo is a mirror of BasicSR. Recommend to use BasicSR, and open issues, pull requests, etc in BasicSR.

Note that this version is not compatible with previous versions. If you want to use previous ones, please refer to the old_version branch.


🚀 BasicSR

English | 简体中文GitHub | Gitee码云

google colab logo Google Colab: GitHub Link | Google Drive Link
Ⓜ️ Model Zoo Google Drive: Pretrained Models | Reproduced Experiments 百度网盘: 预训练模型 | 复现实验
📁 Datasets Google Drive 百度网盘 (提取码:basr)
📈 Training curves in wandb
💻 Commands for training and testing
HOWTOs


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.
(ESRGAN, EDVR, DNI, SFTGAN) (HandyView, HandyFigure, HandyCrawler, HandyWriting)

New Features

  • Nov 29, 2020. Add ESRGAN and DFDNet colab demo.
  • Sep 8, 2020. Add blind face restoration inference codes: DFDNet.
  • Aug 27, 2020. Add StyleGAN2 training and testing codes: StyleGAN2.
More
  • Sep 8, 2020. Add blind face restoration inference codes: DFDNet.
    ECCV20: Blind Face Restoration via Deep Multi-scale Component Dictionaries
    Xiaoming Li, Chaofeng Chen, Shangchen Zhou, Xianhui Lin, Wangmeng Zuo and Lei Zhang
  • Aug 27, 2020. Add StyleGAN2 training and testing codes.
    CVPR20: Analyzing and Improving the Image Quality of StyleGAN
    Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen and Timo Aila
  • Aug 19, 2020. A brand-new BasicSR v1.0.0 online.

HOWTOs

We provides simple pipelines to train/test/inference models for 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
EDVR TODO TODO DUF - TODO
BasicVSR TODO TODO TOF - TODO
Deblurring
DeblurGANv2 - TODO
Denoise
RIDNet - TODO CBDNet - TODO

🔧 Dependencies and Installation

  1. Clone repo

    git clone https://github.com/xinntao/BasicSR.git
  2. Install dependent packages

    cd BasicSR
    pip install -r requirements.txt
  3. Install BasicSR

    Please run the following commands in the BasicSR root path to install BasicSR:
    (Make sure that your GCC version: gcc >= 5)
    If you do not need the cuda extensions:
    dcn for EDVR
    upfirdn2d and fused_act for StyleGAN2
    please add --no_cuda_ext when installing

    python setup.py develop --no_cuda_ext

    If you use the EDVR and StyleGAN2 model, the above cuda extensions are necessary.

    python setup.py develop

    You may also want to specify the CUDA paths:

    CUDA_HOME=/usr/local/cuda \
    CUDNN_INCLUDE_DIR=/usr/local/cuda \
    CUDNN_LIB_DIR=/usr/local/cuda \
    python setup.py develop

Note that BasicSR is only tested in Ubuntu, and may be not suitable for Windows. You may try Windows WSL with CUDA supports :-) (It is now only available for insider build with Fast ring).

TODO List

Please see project boards.

🐢 Dataset Preparation

  • Please refer to DatasetPreparation.md for more details.
  • The descriptions of currently supported datasets (torch.utils.data.Dataset classes) are in Datasets.md.

💻 Train and Test

  • Training and testing commands: Please see TrainTest.md for the basic usage.
  • Options/Configs: Please refer to Config.md.
  • Logging: Please refer to Logging.md.

🏰 Model Zoo and Baselines

  • The descriptions of currently supported models are in Models.md.
  • Pre-trained models and log examples are available in ModelZoo.md.
  • We also provide training curves in wandb:

📝 Codebase Designs and Conventions

Please see 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 | Models.md | Config.md | Logging.md

overall_structure

📜 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},
  howpublished = {\url{https://github.com/xinntao/BasicSR}},
  year =         {2020}
}

Xintao Wang, Ke Yu, Kelvin C.K. Chan, Chao Dong and Chen Change Loy. BasicSR. https://github.com/xinntao/BasicSR, 2020.

📧 Contact

If you have any question, please email [email protected].

Owner
Xintao
Researcher at Tencent ARC Lab, (Applied Research Center)
Xintao
ECCV2020 paper: Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards. Code and Data.

This repo contains some of the codes for the following paper Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards. Code

Xuewen Yang 56 Dec 08, 2022
Privacy-Preserving Portrait Matting [ACM MM-21]

Privacy-Preserving Portrait Matting [ACM MM-21] This is the official repository of the paper Privacy-Preserving Portrait Matting. Jizhizi Li∗, Sihan M

Jizhizi_Li 212 Dec 27, 2022
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow

Hao Lu 18 Nov 05, 2022
Label Studio is a multi-type data labeling and annotation tool with standardized output format

Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types

Heartex 11.7k Jan 09, 2023
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."

Spacetimeformer Multivariate Forecasting This repository contains the code for the paper, "Long-Range Transformers for Dynamic Spatiotemporal Forecast

QData 440 Jan 02, 2023
ICS 4u HD project, start before-wards. A curtain shooting game using python.

Touhou-Star-Salvation HDCH ICS 4u HD project, start before-wards. A curtain shooting game using python and pygame. By Jason Li For arts and gameplay,

15 Dec 22, 2022
Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".

Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".

66 Dec 15, 2022
IsoGCN code for ICLR2021

IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N

horiem 39 Nov 25, 2022
PyTorch implementation of "A Two-Stage End-to-End System for Speech-in-Noise Hearing Aid Processing"

Implementation of the Sheffield entry for the first Clarity enhancement challenge (CEC1) This repository contains the PyTorch implementation of "A Two

10 Aug 19, 2022
A python implementation of Deep-Image-Analogy based on pytorch.

Deep-Image-Analogy This project is a python implementation of Deep Image Analogy.https://arxiv.org/abs/1705.01088. Some results Requirements python 3

Peng Lu 171 Dec 14, 2022
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki

DeepCourse: Deep Learning for Computer Vision arthurdouillard.com/deepcourse/ This is a course I'm giving to the French engineering school EPITA each

Arthur Douillard 113 Nov 29, 2022
Tool for live presentations using manim

manim-presentation Tool for live presentations using manim Install pip install manim-presentation opencv-python Usage Use the class Slide as your sce

Federico Galatolo 146 Jan 06, 2023
Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021)

Tracing Versus Freehand for Evaluating Computer-Generated Drawings (SIGGRAPH 2021) Zeyu Wang, Sherry Qiu, Nicole Feng, Holly Rushmeier, Leonard McMill

Zach Zeyu Wang 23 Dec 09, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
Graph neural network message passing reframed as a Transformer with local attention

Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with

Phil Wang 49 Dec 28, 2022
Official implementation for: Blended Diffusion for Text-driven Editing of Natural Images.

Blended Diffusion for Text-driven Editing of Natural Images Blended Diffusion for Text-driven Editing of Natural Images Omri Avrahami, Dani Lischinski

328 Dec 30, 2022
Code + pre-trained models for the paper Keeping Your Eye on the Ball Trajectory Attention in Video Transformers

Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep

Facebook Research 192 Dec 23, 2022
KITTI-360 Annotation Tool is a framework that developed based on python(cherrypy + jinja2 + sqlite3) as the server end and javascript + WebGL as the front end.

KITTI-360 Annotation Tool is a framework that developed based on python(cherrypy + jinja2 + sqlite3) as the server end and javascript + WebGL as the front end.

86 Dec 12, 2022
Graduation Project

Gesture-Detection-and-Depth-Estimation This is my graduation project. (1) In this project, I use the YOLOv3 object detection model to detect gesture i

ChaosAT 1 Nov 23, 2021
Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

ood-text-emnlp Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them" Files fine_tune.py is used to finetune the GPT-2 mo

Udit Arora 19 Oct 28, 2022