SimpleNet: A Simple Network for Image Anomaly Detection and Localization

Zhikang Liu, Yiming Zhou, Yuansheng Xu, Zilei Wang*

Paper link

This repo contains source code for SimpleNet implemented with pytorch.

SimpleNet is a simple defect detection and localization network that built with a feature encoder, feature generator and defect discriminator. It is designed conceptionally simple without complex network deisng, training schemes or external data source.

Python3.8

Packages:

• torch==1.12.1
• torchvision==0.13.1
• numpy==1.22.4
• opencv-python==4.5.1

(Above environment setups are not the minimum requiremetns, other versions might work too.)

Edit run.sh to edit dataset class and dataset path.

Download the dataset from here.

The dataset folders/files follow its original structure.

Please specicy dataset path (line1) and log folder (line10) in run.sh before running.

run.sh gives the configuration to train models on MVTecAD dataset.

bash run.sh

@inproceedings{liu2023simplenet,
  title={SimpleNet: A Simple Network for Image Anomaly Detection and Localization},
  author={Liu, Zhikang and Zhou, Yiming and Xu, Yuansheng and Wang, Zilei},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={20402--20411},
  year={2023}
}

Thanks for great inspiration from PatchCore

All code within the repo is under MIT license