HDNet: Hybrid Distance Network for semantic segmentation
A deep neural network with attention mechanism for semantic segmentation task.
Requirements
- Install PASCAL in Detail
- Install
requirements.txt
How to use
- To train HDNet:
python train.py --dataset pcontext_detail --out_dir /out_dir --pretrained_home /pretrained_home --data-folder /data-folder
The model and log are saved in --out_dir
- To test HDNet:
python test.py --dataset pcontext_detail --resume-dir /resume-dir --data-folder /data-folder --pretrained_home /pretrained_home --eval --multi-scales
Citation
if you find HDNet useful in your research, please consider citing:
@article{li2021hdnet,
title={HDNet: Hybrid Distance Network for semantic segmentation},
author={Li, Chunpeng and Kang, Xuejing and Zhu, Lei and Ye, Lizhu and Feng, Panhe and Ming, Anlong},
journal={Neurocomputing},
volume={447},
pages={129-144},
year={2021},
publisher={Elsevier}
}
Acknowledgement
Thanks for DANet, PyTorch-Encoding, timm