| --- |
| license: cc-by-sa-4.0 |
| task_categories: |
| - image-classification |
| tags: |
| - volumetric |
| - 3D |
| - X-ray_tomography |
| - mozzarella |
| - cheese |
| - food_science |
| size_categories: |
| - 1K<n<10K |
| --- |
| # MozzaVID dataset - Base 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 Base split of the dataset containing 4 728 volumes. We also provide a [Small split](https://huggingface.co/datasets/dtudk/MozzaVID_Small) (591 volumes) and a [Large split](https://huggingface.co/datasets/dtudk/MozzaVID_Large) (37 824 volumes). |
|
|
| <img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F67e55a8b793bfd7642b6d84e%2FEz67h26Y6-cVUqlpx9mnj.png%26quot%3B%3C%2Fspan%3E alt="dataset_instance_creation.png" width="700"/> |
|
|
| ## 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 |
|
|
| <img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F67e55a8b793bfd7642b6d84e%2FvRtxBSCO6ML6hCpUs0fG5.png%26quot%3B%3C%2Fspan%3E alt="cheese_slices.png" width="1000"/> |
| Fig 1. Overview of slices from each cheese type, forming the 25 coarse-grained classes. |
|
|
| <img src="/static-proxy?url=https%3A%2F%2Fcdn-uploads.huggingface.co%2Fproduction%2Fuploads%2F67e55a8b793bfd7642b6d84e%2FY5xq74Z43h4MOlyHH3xPn.png%26quot%3B%3C%2Fspan%3E alt="sample_slices.png" width="1000"/> |
| 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. |
