SimpleNet: A Simple Network for Image Anomaly Detection and Localization
Zhikang Liu, Yiming Zhou, Yuansheng Xu, Zilei Wang*
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