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

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BasicSR is an open source image and video super-resolution toolbox based on PyTorch (will extend to more restoration tasks in the future).
_{(ESRGAN, EDVR, DNI, SFTGAN)}

Dependencies and Installation

Python >= 3.7 (Recommend to use Anaconda or Miniconda)
PyTorch >= 1.3
NVIDIA GPU + CUDA

Please run the following commands in the BasicSR root path to install BasicSR:
(Make sure that your GCC version: gcc >= 5)

pip install -r requirements.txt
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).

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.

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

License and Acknowledgement

This project is released under the Apache 2.0 license. More details about license and acknowledgement are in LICENSE.

Contact

If you have any question, please email xintao.wang@outlook.com.

csjunxu/EDVR