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 found in our corresponding paper.
For your convenience, we provide a download link for the whole dataset, as well as links for each object category.
For each object, the data consist of three folders:
- 'train', which contains the (defect-free) training images
- 'test', which contains the test images
- 'ground_truth', which contains the pixel-precise annotations of anomalous regions
Please note that our dataset is hosted on an FTP server. You need a browser that supports the File Transfer Protocol (e.g. Mozilla Firefox) or an FTP client software to download them.
Download the whole dataset (4.9 GB)
Download each object category separately:
If you use this dataset in scientific work, please cite our paper:
Paul Bergmann, Michael Fauser, David Sattlegger, Carsten Steger. MVTec AD - A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection; in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2019
The data is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). For using the data in a way that falls under the commercial use clause of the license, please contact us via the form below.