Low-Rank Adaption on Transformer-based Oriented Object Detector for Satellite Onboard Processing of Remote Sensing Images

Xinyang Pu, Feng Xu

The Key Laboratory of Information Science of Electromagnetic Waves, Fudan University, Shanghai, China

Installation

This code was implemented with Python 3.8, PyTorch 1.13.0 and mmrotate. You can install all the requirements via the installation instruction of MMRotate.

MMRotate depends on PyTorch, MMCV and MMDetection. Below are quick steps for installation. Please refer to Install Guide for more detailed instruction.

conda create -n open-mmlab python=3.7 pytorch==1.7.0 cudatoolkit=10.1 torchvision -c pytorch -y
conda activate open-mmlab
pip install openmim
mim install mmcv-full
mim install mmdet
git clone https://github.com/open-mmlab/mmrotate.git
cd mmrotate
pip install -r requirements/build.txt
pip install -v -e .

Train

export PYTHONPATH=./

./tools/dist_train.sh configs/lora_oriented_rcnn/lora_backbone_roihead_oriented_rcnn_swin_tiny_fpn_1x_dota_val_test_classwise_fpn_rpn_ft.py 2

./tools/dist_train.sh configs/lora_oriented_rcnn/lora_backbone_roihead_oriented_rcnn_swin_tiny_fpn_1x_dior_val_test_classwise_fpn_rpn_ft.py 2 

./tools/dist_train.sh  configs/lora_oriented_rcnn/lora_backbone_roihead_oriented_rcnn_swin_tiny_fpn_3x_hrsc_val_test_classwise_fpn_ft.py 2

Test

DOTAv1.0 dataset online evaluation:

python ./tools/test.py  \
  configs/lora_oriented_rcnn/lora_backbone_roihead_oriented_rcnn_swin_tiny_fpn_1x_dota_val_test_classwise_fpn_rpn_ft.py \
  checkpoints/SOME_CHECKPOINT.pth --format-only \
  --eval-options submission_dir=work_dirs/Task1_results

DIOR-R dataset evaluation:

python ./tools/test.py  \
  configs/lora_oriented_rcnn/lora_backbone_roihead_oriented_rcnn_swin_tiny_fpn_1x_dior_val_test_classwise_fpn_rpn_ft.py \
  checkpoints/SOME_CHECKPOINT.pth --eval mAP

HRSC2016 dataset evaluation:

python ./tools/test.py  \
  configs/lora_oriented_rcnn/lora_backbone_roihead_oriented_rcnn_swin_tiny_fpn_3x_hrsc_val_test_classwise_fpn_ft.py \
  checkpoints/SOME_CHECKPOINT.pth --eval mAP

Citation

If you find our work useful in your research, please consider citing:

@misc{pu2024lowrank,
      title={Low-Rank Adaption on Transformer-based Oriented Object Detector for Satellite Onboard Processing of Remote Sensing Images}, 
      author={Xinyang Pu and Feng Xu},
      year={2024},
      eprint={2406.02385},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}