Vineyard dataset for automatic pruning based on main parts localization
This dataset provides a collection of labeled images related to different parts of the vineyard (trunk, shoot, and pruned shoot), collected in Badajoz, Spain, during 2021 and 2022. The labels were created with VGG Image Annotator (VIA) software. The dataset is particularly suitable for the development of object detection models, providing a solid basis for numerous applications in smart agriculture. Considering the growing importance of precision agriculture, this data provides a valuable starting point for implementing advanced solutions. In addition, the dataset has been used to train Mask R-CNN models for precise localization of plant parts, demonstrating its value for visual processing in agricultural settings.
Authors
- Horacio M. González–Velasco
- Miguel Macías Macías
- Antonio García‐Manso
- Carlos J. García–Orellana (ORCID: https://orcid.org/0000-0001-6089-1499)
- Elia Pacioni (ORCID: https://orcid.org/0000-0002-1557-4870)
- Eugenio Abengózar (ORCID: https://orcid.org/0000-0003-3301-2836)
Institutions
- Red de Investigación en Sida (ES)
- Instituto de Arqueología-Mérida (ES)
- Universidad de Extremadura (ES)
Publication Details
- Journal
- Data in Brief
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1016/j.dib.2025.111335
- Citations
- 1
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.24
Funders
- Ministerio de Ciencia e Innovación