ILNet: Low-level Matters for Salient Infrared Small Target Detection

Requirements

 Python 3.7.10
 torch 1.10.1

Training

python train.py --img_size 512 --batch_size 8 --epochs 600 --warm_up_epochs 10 --learning_rate 0.001 --dataset sirst --mode 'L' --amp True

In default, the '.pth' will be saved at ./results_sirst/ or ./results_IRSTD-1k/.

Valuating

python val.py --img_size 512 --dataset 'sirst' --batch-size 1 --mode 'L' --checkpoint ' .pth'

Demo

python demo.py --img_path ' .png' --mask_path ' .png' --mode 'L' --checkpoint ' .pth'

Datasets

Dataset folder should be like:

https://github.com/RuiZhang97/ISNet

IRSTD-1k
└───imges
│       │   XDU0.png
│       │   XDU1.png
│       │  ...
└───masks
│       │   XDU0.png
│       │   XDU1.png
│       │  ...
└───trainval.txt
└───test.txt

https://github.com/YimianDai/sirst

SIRST
└───idx_320
│       │   trainval.txt
│       │   test.txt
└───idx_427
│       │   trainval.txt
│       │   test.txt
└───imges
│       │   Misc_1.png
│       │   Misc_2.png
│       │  ...
└───masks
│       │   Misc_1_pixels0.png
│       │   Misc_2_pixels0.png
│       │  ...

Best Results

SIRST

Mode	Best IoU(%)	Best nIoU(%)	Best Pd(%)	Best Fa(1e-6)
ILNet-S	78.12	76.42	99.07	5.50
ILNet-M	79.57	77.19	98.15	3.02
ILNet-L	80.31	78.22	100	1.33
---	---	---	---	---
IRSTD-1k
Mode	Best IoU(%)	Best nIoU(%)	Best Pd(%)	Best Fa(1e-6)
---	---	---	---	---
ILNet-S	66.01	64.78	93.27	5.26
ILNet-M	67.86	68.40	94.61	5.09
ILNet-L	70.15	68.91	95.29	3.23

Thanks:

 Part of the code draws on the work of the following authors:
    https://github.com/Tianfang-Zhang/acm-pytorch
    https://github.com/WZMIAOMIAO/deep-learning-for-image-processing/tree/master/pytorch_segmentation/u2net
 
 Datasets:
    https://github.com/YimianDai/sirst
    https://github.com/RuiZhang97/ISNet

 Metrics:
    https://github.com/YimianDai/sirst
    https://github.com/Lliu666/DNANet_BatchFormer