---
license: cc-by-sa-4.0
task_categories:
- image-classification
tags:
- volumetric
- 3D
- X-ray_tomography
- mozzarella
- cheese
- food_science
size_categories:
- n<1K
---
# MozzaVID dataset - Small split
A dataset of synchrotron X-ray tomography scans of mozzarella microstructure, aimed for volumetric model benchmarking and food structure analysis.
### [[Paper](https://arxiv.org/abs/2412.04880)] [[Project website](https://papieta.github.io/MozzaVID/)]
This version is prepared in the WebDataset format, optimized for streaming. Check our [GitHub](https://github.com/PaPieta/MozzaVID) for details on how to use it. To download raw data instead, visit: [[LINK](https://archive.compute.dtu.dk/files/public/projects/MozzaVID/)].
## Dataset splits
This is a Small split of the dataset containing 591 volumes. We also provide a [Base split](https://huggingface.co/datasets/dtudk/MozzaVID_Base) (4 728 volumes) and a [Large split](https://huggingface.co/datasets/dtudk/MozzaVID_Large) (37 824 volumes).
## Citation
If you use the dataset in your work, please consider citing our publication:
```
@misc{pieta2024b,
title={MozzaVID: Mozzarella Volumetric Image Dataset},
author={Pawel Tomasz Pieta and Peter Winkel Rasmussen and Anders Bjorholm Dahl and Jeppe Revall Frisvad and Siavash Arjomand Bigdeli and Carsten Gundlach and Anders Nymark Christensen},
year={2024},
howpublished={arXiv:2412.04880 [cs.CV]},
eprint={2412.04880},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2412.04880},
}
```
## Visual overview
We provide two classification targets/granularities:
* 25 cheese types
* 149 cheese samples
Fig 1. Overview of slices from each cheese type, forming the 25 coarse-grained classes.
Fig 2. Example slices from the fine-grained classes. Each row represents a set of six samples from one cheese type (coarse-grained
class), forming six consecutive fine-grained classes.