Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection [AAAI 2025]
December 20, 2024 ยท View on GitHub
Fenfang Tao, Guo-Sen Xie1, Fang Zhao, Xiangbo Shu.
Overview of KAG-prompt

How to Run
Environment installation
Install the required packages:
pip install -r requirements.txt
Prepare your dataset
You can download MVTec-AD dataset from [this link] and VisA from [this link]. After downloading, please modify the corresponding data loading path.
Prepare checkpoint
You can download the pre-trained ImageBind model using [this link]. After downloading, put the downloaded file (imagebind_huge.pth) in [./pretrained_ckpt/imagebind_ckpt/] directory.
You can download the the pre-trained weights using [this link] and [this link]. After downloading, place them into [./code/ckpt/train_mvtec] and [./data//ckpt/train_visa] directory respectively.
Test
- Quick start (use the pre-trained weights)
cd /KAG-prompt/code
python test_visa.py
pyhton test_mvtec.py
Train your KAG-prompt
bash ./scripts/train_mvtec.sh
bash ./scripts/train_visa.sh