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Dataset Open Access

Odeuropa Dataset of Smell-Related Objects

Zinnen, Mathias; Madhu, Prathmesh; Kosti, Ronak; Bell, Peter; Maier, Andreas; Christlein, Vincent


Dublin Core Export

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  <dc:contributor>Tran, Hang</dc:contributor>
  <dc:contributor>Hussian, Azhar</dc:contributor>
  <dc:contributor>Marx, Lizzie</dc:contributor>
  <dc:contributor>Ehrich, Sofia</dc:contributor>
  <dc:contributor>Tullett, William</dc:contributor>
  <dc:contributor>Bosse, Arno</dc:contributor>
  <dc:contributor>van Erp, Marieke</dc:contributor>
  <dc:contributor>Leemans, Inger</dc:contributor>
  <dc:contributor>Odeuropa Team</dc:contributor>
  <dc:creator>Zinnen, Mathias</dc:creator>
  <dc:creator>Madhu, Prathmesh</dc:creator>
  <dc:creator>Kosti, Ronak</dc:creator>
  <dc:creator>Bell, Peter</dc:creator>
  <dc:creator>Maier, Andreas</dc:creator>
  <dc:creator>Christlein, Vincent</dc:creator>
  <dc:date>2022-03-31</dc:date>
  <dc:description>Odeuropa Dataset of Olfactory Objects

This dataset is released as part of the Odeuropa project. The annotations are identical to the training set of the ICPR2022-ODOR Challenge.
It contains bounding box annotations for smell-active objects in historical artworks gathered from various digital connections.
The smell-active objects annotated in the dataset either carry smells themselves or hint at the presence of smells.
The dataset provides 15484 bounding boxes on 2116 artworks in 87 object categories.
An additional csv file contains further image-level metadata such as artist, collection, or year of creation.

How to use


	Due to licensing issues, we cannot provide the images directly, but instead provide a collection of links and a download script.
	To get the images, just run the `download_imgs.py` script which loads the images using the links from the `metadata.csv` file. The downloaded images can then be found in the `images` subfolder. The overall size of the downloaded images is c. 200MB.
	The bounding box annotations can be found in the `annotations.json`. The annotations follow the COCO JSON format, the definition is available here.
	The mapping between the `images` array of the `annotations.json` and the `metadata.csv` file can be accomplished via the `file_name` attribute of the elements of the `images` array and the unique `File Name` column of the `metadata.csv` file, respectively.
	Additional image-level metadata is available in the `metadata.csv` file.
</dc:description>
  <dc:identifier>https://zenodo.org/record/6367776</dc:identifier>
  <dc:identifier>10.5281/zenodo.6367776</dc:identifier>
  <dc:identifier>oai:zenodo.org:6367776</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Research and Innovation action/101004469/</dc:relation>
  <dc:relation>doi:10.5281/zenodo.6362951</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Object Detection</dc:subject>
  <dc:subject>Smell</dc:subject>
  <dc:subject>Olfaction</dc:subject>
  <dc:subject>Artworks</dc:subject>
  <dc:subject>Odor</dc:subject>
  <dc:title>Odeuropa Dataset of Smell-Related Objects</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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