AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks
AA_TransUNet Architecture.
If you are interesed in the dataset(precipitation maps & cloud cover dataset) used in this paper,please visit SmaAt-UNet for further details.
For the pre-trained AA_TransUNet models, please contact us: [email protected] or [email protected]
Please put the dataset into "\dataset" directory for training and testing, and put the pre-trained models into "\results\Model_Saved" directory for future loading.
Required Dependencies:
pip install -r requirements.txt
Training precipitation maps dataset:
python train_precipitation.py
Training cloud cover dataset:
python train_cloud_cover.py
After training or loading pre-trained models, you can evaluate model's performance by:
Evaluating precipitation maps dataset:
python evaluate_precipitation.py
Evaluating cloud cover dataset:
python evaluate_cloud_cover.py
For easier training, we also provide a colab demo:
Colab training demo for cloud cover dataset.
- Yimin Yang: [email protected]
- Siamak Mehrkanoon: [email protected]
@inproceedings{
yang2022aa,
title={Aa-transunet: Attention augmented transunet for nowcasting tasks},
author={Yang, Yimin and Mehrkanoon, Siamak},
booktitle={2022 International Joint Conference on Neural Networks (IJCNN)},
pages={01--08},
year={2022},
organization={IEEE}
}