Datasetpublic

alexsu52/mvtec_capsule

MVTec Capsule Category Dataset Labels {0: "normal", 1: "abnormal"} Number of Images {'train': 219, 'test': 132} How to Use Install datasets: pip install datasets Load the dataset: from datasets import load_dataset ds = load_dataset("alexsu52/mvtec_capsule") example = ds['train'][0] MVTEC Dataset Page https://www.mvtec.com/company/research/datasets/mvtec-ad Citation Paul Bergmann, Kilian Batzner… See the full description on the dataset page: https://huggingface.co/datasets/alexsu52/mvtec_capsule.

sourceHugging Facecc-by-nc-sa-4.0updated 3y agoView on Hugging Face

1likes443downloads

Dataset Card

MVTec Capsule Category

Dataset Labels

{0: "normal", 1: "abnormal"}

Number of Images

json

{'train': 219, 'test': 132}

How to Use

—Install datasets:

bash

pip install datasets

—Load the dataset:

python

from datasets import load_dataset
ds = load_dataset("alexsu52/mvtec_capsule")
example = ds['train'][0]

MVTEC Dataset Page

https://www.mvtec.com/company/research/datasets/mvtec-ad

Citation

Paul Bergmann, Kilian Batzner, Michael Fauser, David Sattlegger, Carsten Steger: The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection; in: International Journal of Computer Vision 129(4):1038-1059, 2021, DOI: 10.1007/s11263-020-01400-4.

Paul Bergmann, Michael Fauser, David Sattlegger, Carsten Steger: MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection; in: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 9584-9592, 2019, DOI: 10.1109/CVPR.2019.00982.

License

CC BY-NC-SA 4.0

Dataset Summary

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".