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Towards Training-free Anomaly Detection with Vision and Language Foundation Models (CVPR 2025)

Installation

Install the required packages:

pip install -r requirements.txt

Download the checkpoint for ViT-H SAM model and put in the checkpoint folder.

Instructions for MVTEC LOCO dataset

Few-shot Protocol

Run the script for few-shot protocal:

python evaluation.py --module_path model_ensemble_few_shot --category CATEGORY  --dataset_path DATASET_PATH

Full-data Protocol

Run the script to compute coreset for full-data scenarios:

python compute_coreset.py --module_path model_ensemble --category CATEGORY  --dataset_path DATASET_PATH

Run the script for full-data protocol:

python evaluation.py --module_path model_ensemble --category CATEGORY  --dataset_path DATASET_PATH

Acknowledgement

We are grateful for the following awesome projects when implementing LogSAD:

Citation

If you find our paper is helpful in your research or applications, generously cite with

@inproceedings{zhang2025logsad,
      title={Towards Training-free Anomaly Detection with Vision and Language Foundation Models},
      author={Jinjin Zhang, Guodong Wang, Yizhou Jin, Di Huang},
      year={2025},
      booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    }

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