Awesome
IRSTD-Benchmark
Paper
- IR-TransDet: Infrared Dim and Small Target Detection With IR-Transformer
- Infrared dim and small target detection based on U-Transformer
This repository is a benchmark tool for weak small target detection, aiming to provide a platform that integrates typical weak small target detection algorithms and unified evaluation metrics. This tool can help researchers and developers evaluate the performance of different algorithms on weak small target detection tasks.
Features
- Provides standard evaluation metrics for weak small target detection to objectively evaluate algorithm performance, including but not limited to:
- Precision-Recall
- F1 score
- Simple and easy-to-use interface and sample code for users to quickly get started and integrate their own algorithms or conduct evaluation experiments.
| IRSTD1K | MDFA |
|---|---|
 |  |
| Merged | SirstAUG |
|---|---|
 |  |
Dataset
| Dataset | Link |
|---|---|
| Sirst AUG | Link |
| MDFA | Link |
| IRSTD1K | Link |
The above datasets have been organized and uploaded to Google Drive, and users can download and use them directly.
Installation and Usage
Install Matlab Python API
pip install -r requirements.txt
Usage
python method.py --dataset mdfa > mdfa.txt
irstd > istd1k.txt
sirstaug > sirstaug.txt
merged > merged.txt
Plot ROC curve
python plot_curve.py
Add custom model
Please refer to model.md for add custom model.
Contribution
Contributions to this repository are welcome! If you have new algorithm implementations, improvements, or suggestions for other feature enhancements, please submit a pull request. We are happy to accept new contributions and continuously improve this tool.
Cite
@article{lin2022infrared,
title={Infrared dim and small target detection based on U-Transformer},
author={Lin, Jian and Zhang, Kai and Yang, Xi and Cheng, Xiangzheng and Li, Chenhui},
journal={Journal of Visual Communication and Image Representation},
pages={103684},
year={2022},
publisher={Elsevier}
}
@ARTICLE{10295542,
author={Lin, Jian and Li, Shaoyi and Zhang, Liang and Yang, Xi and Yan, Binbin and Meng, Zhongjie},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={IR-TransDet: Infrared Dim and Small Target Detection With IR-Transformer},
year={2023},
volume={61},
number={},
pages={1-13},
doi={10.1109/TGRS.2023.3327317}}