Deep Attention Network (DAN)

The repository mainly records how to use VIT to code the airfoil geometry and how to use the encoded information to reconstruct the flow field of the airfoil. 🖐

1、Airfoil Visual Transformer (VIT) geometry encoding

1、timm_ V2.py is implemented using the timm visual algorithm function library. The traditional implementation method can refer to VIT_author.py file.

pytorch-image-models references：

author_home_page：https://github.com/rwightman

pytorch-image-models open source code：https://github.com/rwightman/pytorch-image-models

Zhi hu：https://zhuanlan.zhihu.com/p/350837279

2、Visual Transformer Code Reference for Attention Visualization：https://github.com/zuokuijun/Transformer-Explainability

3、 VIT_ Airfoil_ Encoder is a Pycharm engineering file that uses Transformer to encode geometric parameters for UIUC airfoil database

How to use ?👉👉👉👉👉

cd VIT_Airfoil_Encoder
run python plot_airfoil.py generate airfoil images.
run python get_gray_images.py generate airfoil gray images
run python get_airfoil_map.py generate airfoil three channel airfoil heat-map images
run python vit_explain.py get airfoil geometry encoding information

e1412 airfoil attention visualization

naca4412 airfoil attention visualization

2、 Airfoil flow field prediction