The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 83, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 294, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MVTec Anomaly Detection Dataset (MVTec AD)
Dataset description
The MVTec Anomaly Detection (MVTec AD) dataset is a large-scale real-world dataset for unsupervised anomaly detection in industrial inspection scenarios.
It contains high-resolution images of multiple object and texture categories, including normal samples and various defect types with pixel-level ground truth masks.
Official website:
https://www.mvtec.com/company/research/datasets/mvtec-ad
Dataset format
In this repository, the dataset is provided as a single compressed archive:
mvtec_anomaly_detection.tar.xz
After downloading, the archive must be extracted locally:
tar -xJf mvtec_anomaly_detection.tar.xz
Dataset structure
Each category follows the structure:
category/
├── train/
│ └── good/
├── test/
│ ├── good/
│ └── defect_type/
└── ground_truth/
└── defect_type/
- Training set: only normal images
- Test set: normal and anomalous images
- Ground truth: pixel-level defect masks
Categories
The dataset includes objects and textures such as:
bottle, cable, capsule, carpet, grid, hazelnut, leather, metal_nut, pill, screw, tile, toothbrush, transistor, wood, zipper, and others.
License
This dataset is distributed under:
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
(CC BY-NC-SA 4.0)
You may:
- Share and redistribute the dataset
- Adapt and build upon the dataset
Under the conditions:
- Attribution required
- Non-commercial use only
- Share-alike under the same license
Full license text:
https://creativecommons.org/licenses/by-nc-sa/4.0/
Citation
If you use this dataset in academic work, please cite:
@inproceedings{bergmann2019mvtec,
title={MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection},
author={Bergmann, Paul and Fauser, Michael and Sattlegger, David and Steger, Carsten},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}
Source and attribution
This dataset is originally provided by:
MVTec Software GmbH https://www.mvtec.com
All rights remain with the original authors.
Intended use
This dataset is intended for:
- Academic research
- Educational purposes
- Benchmarking anomaly detection algorithms
Commercial use is not permitted.
Disclaimer
This repository is not affiliated with MVTec Software GmbH. It is provided only for research and educational purposes.
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