About Us Career Press Contact
Login
MVTec Software

Download the MVTec 3D-AD dataset

We provide a download link for the whole dataset, as well as links for each object category. For each object, the data consists of four folders:

  • 'train', which contains the defect-free training samples.
  • 'validation', which contains the defect-free validation samples.
  • 'test', which contains the defective and defect-free test samples.
  • 'calibration', which contains the internal camera parameters of the 3D sensor.

Each dataset split contains two subdirectories:

  • 'xyz', which contains 3-channel TIFF images that store the x,y, and z coordinates.
  • 'rgb', which contains 3-channel PNG images that store the corresponding RGB values for each 3D point.

The test split additionally includes a ground truth directory 'gt'. For each test sample, this directory contains a 1-channel PNG image. It indicates, for each image pixel, whether a defect is present or not. The defect type is reflected in the pixel value of the image. The mapping between defect names and pixel values is specified in the file class_ids.json.

Download the whole dataset

Since the whole dataset is about 13.2 GB in size, we also provide links to download each object category separately:

ANOMALY DETECTION

More datasets

Anomaly Detection

MVTec AD is a dataset for benchmarking anomaly detection methods with a focus on industrial inspection. It contains over 5,000 high-resolution images divided into fifteen different object and texture categories.

Go to dataset
Anomaly Detection 2

MVTec AD 2 is a dataset for benchmarking unsupervised anomaly detection methods on challenging use-cases from industrial inspection tasks. It expands existing benchmarks by eight new anomaly detection scenarios with more than 8,000 high-resolution images in total. 

Go to dataset
ANOMALY DETECTION
LOCO AD

The MVTec logical constraints anomaly detection (MVTec LOCO AD) dataset is intended for the evaluation of unsupervised anomaly localization algorithms. The dataset includes both structural and logical anomalies.

Go to dataset
MVTec Software