Awesome

PromptAD Few-Shot Anomaly Detection

Official implementation of PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection (CVPR2024)

Install

conda create -n prompt_ad python==3.10
conda activate prompt_ad
bash install.sh

Data

Download the dataset from MvTec.

Download the dataset from VisA.

VisA preprocessing

Modify the source and target paths for the VisA dataset in ./dataset/prepare_visa_public.py

python ./dataset/prepare_visa_public.py

Modify the source paths for MvTec and VisA in ./dataset/mvtec.py and ./dataset/visa.py

Run

python run_cls.py  # image-level
python run_seg.py  # pixel-level

Citation

Please cite the following paper if this work helps your project:

@article{li2024promptad,
  title={PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection},
  author={Li, Xiaofan and Zhang, Zhizhong and Tan, Xin and Chen, Chengwei and Qu, Yanyun and Xie, Yuan and Ma, Lizhuang},
  journal={arXiv preprint arXiv:2404.05231},
  year={2024}
}

Acknowledge

We thank the great works WinCLIP and CoOp for assisting with our work.