6366362
doi
10.5281/zenodo.6366362
oai:zenodo.org:6366362
user-odeuropa
user-eu
Tran, Hang
Friedrich-Alexander-Universität Erlangen-Nürnberg
Hussian, Azhar
Friedrich-Alexander-Universität Erlangen-Nürnberg
Marx, Lizzie
University of Cambridge
Ehrich, Sofia
KNAW Humanities Cluster Amsterdam
Tullett, William
Anglia Ruskin University Cambridge
Bosse, Arno
KNAW Humanities Cluster Amsterdam
van Erp, Marieke
KNAW Humanities Cluster Amsterdam
Leemans, Inger
KNAW Humanities Cluster Amsterdam
Odeuropa Team
Madhu, Prathmesh
Friedrich-Alexander-Universität Erlangen-Nürnberg
Kosti, Ronak
Friedrich-Alexander-Universität Erlangen-Nürnberg
Bell, Peter
Philipps-Universität Marburg
Maier, Andreas
Friedrich-Alexander-Universität Erlangen-Nürnberg
Christlein, Vincent
Friedrich-Alexander-Universität Erlangen-Nürnberg
Odeuropa Dataset of Smell-Related Objects
Zinnen, Mathias
Friedrich-Alexander-Universität Erlangen-Nürnberg
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Object Detection
Smell
Olfaction
Artworks
Odor
<p><strong>Odeuropa Dataset of Olfactory Objects</strong></p>
<p>This dataset is released as part of the <a href="http://odeuropa.eu">Odeuropa project</a>. The annotations are identical to the training set of the <a href="http://odor-challenge.odeuropa.eu">ICPR2022-ODOR Challenge</a>.<br>
It contains bounding box annotations for smell-active objects in historical artworks gathered from various digital connections.<br>
The smell-active objects annotated in the dataset either carry smells themselves or hint at the presence of smells.<br>
The dataset provides 15484 bounding boxes on 2116 artworks in 87 object categories.<br>
An additional csv file contains further image-level metadata such as artist, collection, or year of creation.</p>
<p><strong>How to use</strong></p>
<ul>
<li>Due to licensing issues, we cannot provide the images directly, but instead provide a collection of links and a download script.</li>
<li>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.</li>
<li>The bounding box annotations can be found in the `annotations.json`. The annotations follow the COCO JSON format, the definition is available <a href="https://cocodataset.org/#format-data">here</a>.</li>
<li>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.</li>
<li>Additional image-level metadata is available in the `metadata.csv` file.</li>
</ul>
Zenodo
2022-03-31
info:eu-repo/semantics/other
6362951
user-odeuropa
user-eu
1.0.2
award_title=ODEUROPA: Negotiating Olfactory and Sensory Experiences in Cultural Heritage Practice and Research; award_number=101004469; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/101004469; funder_id=00k4n6c32; funder_name=European Commission;
1696766976.361007
816875
md5:16a3a63beab36db8f5d306613c3f794c
https://zenodo.org/records/6366362/files/odor-dataset.zip
public
10.5281/zenodo.6362951
isVersionOf
doi