MFR-PGC-Net

This is the implementation of the paper "Utilizing Bounding Box Annotations for Weakly Supervised Building Extraction from Remote Sensing Images".

For more information, please checkout the paper.

Requirements

• Python >= 3.6
• PyTorch >= 1.3.0
• yacs (https://github.com/rbgirshick/yacs)

Getting started

The folder data should be like this

datasets   
└── WHU
    ├── train
    ├── BgMaskfromBoxes_train
    └── multi633_g3
        ├── Y_crf
        └── Y_ret

git https://gitee.com/labiao/mfr-pgc-net.git
cd MFR-PGC-Net
bash train_multi.sh # For training a classification network
# To transform the weights of the Repvgg backbone into deployment.
python transform_to_deploy.py --NAME multi633_g3_deploy --config-file configs/grad_cam_repvgg.yml --WEIGHTS multi633_g3.pt 
bash generation_multi.sh # For generating pseudo labels

Bibtex

@ARTICLE{10113662,
  author={Zheng, Daoyuan and Li, Shengwen and Fang, Fang and Zhang, Jiahui and Feng, Yuting and Wan, Bo and Liu, Yuanyuan},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={Utilizing Bounding Box Annotations for Weakly Supervised Building Extraction From Remote-Sensing Images}, 
  year={2023},
  volume={61},
  number={},
  pages={1-17},
  doi={10.1109/TGRS.2023.3271986}}

Acknowledgment

This code is heavily borrowed from BANA, thanks!