Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking
Counting the number of grape bunches at an early stage of development offers relevant information to the winegrower about the potential yield to be harvested. However, manual counting on the fields is laborious and time-consuming. Remote sensing, and more precisely unmanned aerial vehicles mounted w...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-02-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922010514 |
| _version_ | 1797938083475226624 |
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| author | Mar Ariza-Sentís Sergio Vélez João Valente |
| author_facet | Mar Ariza-Sentís Sergio Vélez João Valente |
| author_sort | Mar Ariza-Sentís |
| collection | DOAJ |
| description | Counting the number of grape bunches at an early stage of development offers relevant information to the winegrower about the potential yield to be harvested. However, manual counting on the fields is laborious and time-consuming. Remote sensing, and more precisely unmanned aerial vehicles mounted with RGB or multispectral cameras, facilitate this task rapidly and accurately. This dataset contains 40 RGB videos from a 1.06-ha vineyard located in northern Spain. Moreover, the dataset includes mask labels of visible grape bunches. The videos were acquired throughout four UAV flights with an RGB camera tilted at 60 degrees. Each flight recorded one side of a row of the vineyard. The grape berries were between pea-size (BBCH75) and bunch closure (BBCH79) stage, which is two months before harvesting. No operations other than those usual in a commercial vineyard, such as pruning, cane tying, fertilization, and pest treatment, have been carried out, hence, the dataset presents leaf occlusion. The dataset was gathered and labelled to train object detection and tracking algorithms for grape bunch counting. Furthermore, it eases the work of winegrowers to check the sanitary status of the vineyard. |
| first_indexed | 2024-04-10T18:55:13Z |
| format | Article |
| id | doaj.art-e9c5b75892904a8b86b2322c6fcc559d |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-10T18:55:13Z |
| publishDate | 2023-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-e9c5b75892904a8b86b2322c6fcc559d2023-02-01T04:26:29ZengElsevierData in Brief2352-34092023-02-0146108848Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and trackingMar Ariza-Sentís0Sergio Vélez1João Valente2Corresponding author..; Information Technology Group, Wageningen University & Research, 6708 PB Wageningen, the NetherlandsInformation Technology Group, Wageningen University & Research, 6708 PB Wageningen, the NetherlandsInformation Technology Group, Wageningen University & Research, 6708 PB Wageningen, the NetherlandsCounting the number of grape bunches at an early stage of development offers relevant information to the winegrower about the potential yield to be harvested. However, manual counting on the fields is laborious and time-consuming. Remote sensing, and more precisely unmanned aerial vehicles mounted with RGB or multispectral cameras, facilitate this task rapidly and accurately. This dataset contains 40 RGB videos from a 1.06-ha vineyard located in northern Spain. Moreover, the dataset includes mask labels of visible grape bunches. The videos were acquired throughout four UAV flights with an RGB camera tilted at 60 degrees. Each flight recorded one side of a row of the vineyard. The grape berries were between pea-size (BBCH75) and bunch closure (BBCH79) stage, which is two months before harvesting. No operations other than those usual in a commercial vineyard, such as pruning, cane tying, fertilization, and pest treatment, have been carried out, hence, the dataset presents leaf occlusion. The dataset was gathered and labelled to train object detection and tracking algorithms for grape bunch counting. Furthermore, it eases the work of winegrowers to check the sanitary status of the vineyard.http://www.sciencedirect.com/science/article/pii/S2352340922010514ViticulturePrecision agricultureObject detectionObject trackingRemote sensingUAV |
| spellingShingle | Mar Ariza-Sentís Sergio Vélez João Valente Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking Data in Brief Viticulture Precision agriculture Object detection Object tracking Remote sensing UAV |
| title | Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking |
| title_full | Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking |
| title_fullStr | Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking |
| title_full_unstemmed | Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking |
| title_short | Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking |
| title_sort | dataset on uav rgb videos acquired over a vineyard including bunch labels for object detection and tracking |
| topic | Viticulture Precision agriculture Object detection Object tracking Remote sensing UAV |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922010514 |
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