开源软件名称（OpenSource Name）：

开源软件地址(OpenSource Url)：

开源编程语言(OpenSource Language)：

开源软件介绍(OpenSource Introduction)：

PaDiM-Anomaly-Detection-Localization-master

This is an implementation of the paper PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization.

This code is heavily borrowed from both SPADE-pytorch(https://github.com/byungjae89/SPADE-pytorch) and MahalanobisAD-pytorch(https://github.com/byungjae89/MahalanobisAD-pytorch) projects

Requirement

• python == 3.7
• pytorch == 1.5
• tqdm
• sklearn
• matplotlib

Datasets

MVTec AD datasets : Download from MVTec website

Results

Implementation results on MVTec

• Image-level anomaly detection accuracy (ROCAUC)

• Pixel-level anomaly detection accuracy (ROCAUC)

ROC Curve

• ResNet18

• Wide_ResNet50_2

Localization examples

Reference

[1] Thomas Defard, Aleksandr Setkov, Angelique Loesch, Romaric Audigier. PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization. https://arxiv.org/pdf/2011.08785

[2] https://github.com/byungjae89/SPADE-pytorch

[3] https://github.com/byungjae89/MahalanobisAD-pytorch