$ pip install -r requirements.txt

train data:
    dataset_path/class_name/train/good/any_filename.png
    [...]

test data:
    dataset_path/class_name/test/good/any_filename.png
    [...]

    dataset_path/class_name/test/defect_type/any_filename.png
    [...]

python trainer_cfa.py --class_name all --data_path [/path/to/dataset/] --cnn wrn50_2 --size 224 --gamma_c 1 --gamma_d 1

@article{lee2022cfa,
  title={CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization},
  author={Lee, Sungwook and Lee, Seunghyun and Song, Byung Cheol},
  journal={arXiv preprint arXiv:2206.04325},
  year={2022}
}