/AugTarget

AugTarget data augmentation for infrared small target detection.

Primary LanguagePython

AugTarget Data Augmentation

Datasets

Usage

Train

python train.py --net-name agpcnet_1 --batch-size 8 --save-iter-step 20 --dataset mdfa --learning-rate 0.05
python train.py --net-name agpcnet_1 --batch-size 8 --save-iter-step 40 --dataset sirstaug --learning-rate 0.1
python train.py --net-name agpcnet_1 --batch-size 8 --save-iter-step 100 --dataset merged --learning-rate 0.05

Inference

python inference.py --pkl-path {checkpoint path} --image-path {image path}

Evaluation

python evaluation.py --dataset {dataset name} 
                     --sirstaug-dir {base dir of sirstaug}
                     --mdfa-dir {base dir of MDFA}
                     --pkl-path {checkpoint path}

Results

Methods Data Precision Recall mIoU Fmeasure AUC Download
AGPCNet MDFA 0.5939 0.7241 0.4843 0.6525 0.8682 model
AGPCNet SIRST Aug 0.8323 0.8542 0.7288 0.8431 0.9344 model
AGPCNet Merged 0.7453 0.8384 0.6517 0.7891 0.9194 model
AGPCNet+AugTarget MDFA 0.6482 0.7141 0.5146 0.6795 0.8699 model
AGPCNet+AugTarget SIRST Aug 0.8449 0.8704 0.7505 0.8574 0.9378 model
AGPCNet+AugTarget Merged 0.7576 0.8658 0.6780 0.8081 0.9395 model

Acknowledgement

Our Target Augmentation algorithm is based on the random strategy of Random-Erasing, thanks for their contributions. This repository is based on baseline model from AGPCNet and modified part of the code.

Contact

If any questions, kindly contact with Shengjia Chen via e-mail: csj_uestc@126.com.

References

  1. Zhong, Zhun, et al. "Random erasing data augmentation." Proceedings of the AAAI conference on artificial intelligence. Vol. 34. No. 07. 2020. [code]

  2. Zhang, Tianfang, et al. "AGPCNet: Attention-Guided Pyramid Context Networks for Infrared Small Target Detection." arXiv preprint arXiv:2111.03580 (2021). [code]

Citation

If you find this repo useful, please cite our paper.

@inproceedings{chen2023augtarget,
  title={AugTarget Data Augmentation for Infrared Small Target Detection},
  author={Chen, Shengjia and Zhu, Jiewen and Ji, Luping and Pan, Hongjun and Xu, Yuhao},
  booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={1--5},
  year={2023},
  organization={IEEE}
}