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{ "label_cheese": "9", "label_sample": "57" }
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image0005
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image0008
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{ "label_cheese": "19", "label_sample": "119" }
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image0009
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End of preview.

MozzaVID dataset - Large split

A dataset of synchrotron X-ray tomography scans of mozzarella microstructure, aimed for volumetric model benchmarking and food structure analysis.

[Paper] [Project website]

This version is prepared in the WebDataset format, optimized for streaming. Check our GitHub for details on how to use it. To download raw data instead, visit: [LINK].

Dataset splits

This is a Large split of the dataset containing 37 824 volumes. We also provide a Base split (4 728 volumes) and a Small split (591 volumes).

!!! The above numbers are not exact at the moment as we have not released the test dataset yet.

dataset_instance_creation.png

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
cheese_slices.png Fig 1. Overview of slices from each cheese type, forming the 25 coarse-grained classes. sample_slices.png 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.
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