conda create -n dsp_env python=3.7
conda activate dsp_env
conda install pytorch=1.7 torchvision torchaudio cudatoolkit -c pytorch
pip install -r requirements.txt

git clone https://github.com/GaoLii/DSP/
cd DSP

├── ../../dataset/
│   ├── Cityscapes/     
|   |   ├── gtFine/
|   |   ├── leftImg8bit/
│   ├── GTA5/
|   |   ├── images/
|   |   ├── labels/
│   ├── RAND_CITYSCAPES/ 
|   |   ├── GT/
|   |   ├── RGB/
...

python train_DSP.py --config ./configs/configUDA_gta.json --name UDA_gta

python train_DSP.py --config ./configs/configUDA_syn.json --name UDA_syn

python evaluateUDA.py --model-path checkpoint.pth

@article{Gao_2021,
   title={DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation},
   url={https://arxiv.org/abs/2107.09600},
   DOI={10.1145/3474085.3475186},
   journal={Proceedings of the 29th ACM International Conference on Multimedia},
   publisher={ACM},
   author={Gao, Li and Zhang, Jing and Zhang, Lefei and Tao, Dacheng},
   year={2021},
   month={Oct}
}