Awesome
UDL (Make Available on PyPI :tada:)
UDL is a unified Pytorch framework for vision research:
- UDL has a faster library loading speed and a more convenient reflection mechanism to call different methods.
- UDL is based on MMCV which provides the following functionalities.
- UDL is based on NNI to perform automatic machine learning.
See the repo for more detailed descriptions.
Note
For the implementation of DCFNet as described in the ICCV paper "Dynamic Cross Feature Fusion for Remote Sensing Pansharpening," please refer to the branch in the this repository.
Requirements
- Python3.7+, Pytorch>=1.9.0
- NVIDIA GPU + CUDA
- Run
python setup.py develop
Note: Our project is based on MMCV, but you needn't to install it currently.
Quick Start
pip install udl-vis -i https://pypi.org/simple
Also, you can quick start from PanCollection, which is remote sensing pansharpening and is one of our applications.
pip install pancollection -i https://pypi.org/simple
Quick Start for developer
Step0. We use UDL in PanCollection, first please set your Python environment.
git clone https://github.com/XiaoXiao-Woo/UDL
Then,
python setup.py develop
Plannings
Please expect more tasks and models
-
- models
-
derain (not available on PyPI)
- models
-
HISR
- models
-
VIS-IR
- models
-
Improve MMCV repo to simplify expensive hooks.
Contribution
We appreciate all contributions to improving PanCollection. Looking forward to your contribution to PanCollection.
Citation
Please cite this project if you use datasets or the toolbox in your research.
@misc{PanCollection,
author = {Xiao Wu, Liang-Jian Deng and Ran Ran},
title = {"PanCollection" for Remote Sensing Pansharpening},
url = {https://github.com/XiaoXiao-Woo/PanCollection/},
year = {2022},
}
@InProceedings{Wu_2021_ICCV,
author = {Wu, Xiao and Huang, Ting-Zhu and Deng, Liang-Jian and Zhang, Tian-Jing},
title = {Dynamic Cross Feature Fusion for Remote Sensing Pansharpening},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2021},
pages = {14687-14696}
}
Acknowledgement
- MMCV: OpenMMLab foundational library for computer vision.
License & Copyright
This project is open sourced under GNU General Public License v3.0.