Datasets:
metadata
configs:
- config_name: default
default: true
features:
- name: image
dtype: image
- name: mask
dtype: image
license: cc-by-4.0
task_categories:
- image-segmentation
size_categories:
- n<1K
Vineyard Pruning Detection
A segmentation dataset for determining where to prune vineyards. The dataset contains 536 images with with pixel-level mask annotations across 3 categories: trunk, shoot, and pruned shoot.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{pacioni2025vineyard,
title={Vineyard dataset for automatic pruning based on main parts localization},
author={Pacioni, Elia and Abeng{\'o}zar, Eugenio and Mac{\'\i}as Mac{\'\i}as, Miguel and Garc{\'\i}a Orellana, Carlos J and Gonz{\'a}lez Velasco, Horacio M and Garc{\'\i}a Manso, Antonio},
journal={Data in Brief},
volume={59},
pages={111335},
year={2025},
publisher={Elsevier}
}
Pacioni, Elia; Abengozar-García, Eugenio; Macías Macías, Miguel; García Orellana, Carlos J.; González Velasco, Horacio M.; García Manso, Antonio (2024), “Vineyard dataset for pruning”, Mendeley Data, V2, doi: 10.17632/n8cs4ns97p.2