/CSE

Implementation of the paper : CSE: Surface Anomaly Detection with Contrastively Selected Embedding

Primary LanguagePython

CSE

Official implementation of the paper : "CSE: Surface Anomaly Detection with Contrastively Selected Embedding"

Article : https://arxiv.org/pdf/2403.01859.pdf

Getting Started

You will need Python 3.10+ and the packages specified in requirements.txt.

Install packages with:

$ pip install -r requirements.txt

Configure and Run

To run the code, please download the MVTEC AD dataset and place it in dataset/MVTEC
Link to download the dataset : https://www.mvtec.com/company/research/datasets/mvtec-ad

To run train and test the model :

python trainCSE.py

To modify the object categories or hyperparameters, you can modify the config.yaml file.

Citation

Please cite our paper in your publications if it helps your research. Even if it does not, you are welcome to cite us.

    @inproceedings {thomine2024cse,
    title={CSE: Surface Anomaly Detection with Contrastively Selected Embedding},
    author={Thomine, Simon and Snoussi, Hichem},
    booktitle={2024 International Conference on Computer Vision Theory and Applications (VISAPP 2024)},
    year={2024}
    }

License

This project is licensed under the MIT License.