Anomaly Detection via Reverse Distillation from One-Class Embedding

Anomaly Detection via Reverse Distillation from One-Class Embedding

Implementation (Official Code ⭐️ ⭐️ ⭐️ )

1. Environment

   pytorch == 1.91

   torchvision == 0.10.1

   numpy == 1.20.3

   scipy == 1.7.1

   sklearn == 1.0

   PIL == 8.3.2

2. Dataset

   You should download MVTec from MVTec AD: MVTec Software. The folder "mvtec" should be unpacked into the code folder.

3. Train and Test the Model We have write both training and evaluation function in the main.py, execute the following command to see the training and evaluation results.

   python main.py

Reference

@article{deng2022anomaly,    
title={Anomaly Detection via Reverse Distillation from One-Class Embedding},
author={Deng, Hanqiu and Li, Xingyu},
journal={arXiv preprint arXiv:2201.10703},
year={2022}
}