MVTec AD

The MVTec Anomaly Detection Dataset

Abstract

MVTec AD is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection. It contains over 5000 high-resolution images divided into fifteen different object and texture categories. Each category comprises a set of defect-free training images and a test set of images with various kinds of defects as well as images without defects.

Pixel-precise annotations of all anomalies are also provided. More information can be in our paper "MVTec AD – A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection" and its extended version "The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection".

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Evaluation Code

In order to ensure a fair and consistent comparison of new and existing methods on our dataset, we provide python scripts that allow an easy evaluation. For details on how to use the script, please take a look at the included readme file. For details on the metrics used for the evaluation, we refer to our corresponding paper.

Download the evaluation code

License Terms

The data is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
In particular, it is not allowed to use the dataset for commercial purposes. If you are unsure whether or not your application violates the non-commercial use clause of the license, please contact us.

If you have any questions or comments about the dataset, feel free to contact us via email.

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