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wGrapeUNIPD-DL: An open dataset for white grape bunch detection
National and international Vitis variety catalogues can be used as image datasets for computer vision in viticulture. These databases archive ampelographic features and phenology of several grape varieties and plant structures images (e.g. leaf, bunch, shoots). Although these archives represent a po...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304721/ https://www.ncbi.nlm.nih.gov/pubmed/35873279 http://dx.doi.org/10.1016/j.dib.2022.108466 |
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author | Sozzi, Marco Cantalamessa, Silvia Cogato, Alessia Kayad, Ahmed Marinello, Francesco |
author_facet | Sozzi, Marco Cantalamessa, Silvia Cogato, Alessia Kayad, Ahmed Marinello, Francesco |
author_sort | Sozzi, Marco |
collection | PubMed |
description | National and international Vitis variety catalogues can be used as image datasets for computer vision in viticulture. These databases archive ampelographic features and phenology of several grape varieties and plant structures images (e.g. leaf, bunch, shoots). Although these archives represent a potential database for computer vision in viticulture, plant structure images are acquired singularly and mostly not directly in the vineyard. Localization computer vision models would take advantage of multiple objects in the same image, allowing more efficient training. The present images and labels dataset was designed to overcome such limitations and provide suitable images for multiple cluster identification in white grape varieties. A group of 373 images were acquired from later view in vertical shoot position vineyards in six different Italian locations at different phenological stages. Images were then labelled in YOLO labelling format. The dataset was made available both in terms of images and labels. The real number of bunches counted in the field, and the number of bunches visible in the image (not covered by other vine structures) was recorded for a group of images in this dataset. |
format | Online Article Text |
id | pubmed-9304721 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-93047212022-07-23 wGrapeUNIPD-DL: An open dataset for white grape bunch detection Sozzi, Marco Cantalamessa, Silvia Cogato, Alessia Kayad, Ahmed Marinello, Francesco Data Brief Data Article National and international Vitis variety catalogues can be used as image datasets for computer vision in viticulture. These databases archive ampelographic features and phenology of several grape varieties and plant structures images (e.g. leaf, bunch, shoots). Although these archives represent a potential database for computer vision in viticulture, plant structure images are acquired singularly and mostly not directly in the vineyard. Localization computer vision models would take advantage of multiple objects in the same image, allowing more efficient training. The present images and labels dataset was designed to overcome such limitations and provide suitable images for multiple cluster identification in white grape varieties. A group of 373 images were acquired from later view in vertical shoot position vineyards in six different Italian locations at different phenological stages. Images were then labelled in YOLO labelling format. The dataset was made available both in terms of images and labels. The real number of bunches counted in the field, and the number of bunches visible in the image (not covered by other vine structures) was recorded for a group of images in this dataset. Elsevier 2022-07-13 /pmc/articles/PMC9304721/ /pubmed/35873279 http://dx.doi.org/10.1016/j.dib.2022.108466 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article Sozzi, Marco Cantalamessa, Silvia Cogato, Alessia Kayad, Ahmed Marinello, Francesco wGrapeUNIPD-DL: An open dataset for white grape bunch detection |
title | wGrapeUNIPD-DL: An open dataset for white grape bunch detection |
title_full | wGrapeUNIPD-DL: An open dataset for white grape bunch detection |
title_fullStr | wGrapeUNIPD-DL: An open dataset for white grape bunch detection |
title_full_unstemmed | wGrapeUNIPD-DL: An open dataset for white grape bunch detection |
title_short | wGrapeUNIPD-DL: An open dataset for white grape bunch detection |
title_sort | wgrapeunipd-dl: an open dataset for white grape bunch detection |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304721/ https://www.ncbi.nlm.nih.gov/pubmed/35873279 http://dx.doi.org/10.1016/j.dib.2022.108466 |
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