wGrapeUNIPD-DL: An open dataset for white grape bunch detection.

Abstract

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.

Plant phenotyping relevance

ブドウ房を対象とする画像・ラベル dataset の構築と公開が中心で、房の検出・可視数の記録という植物器官の表現型取得に直接関係するため。

Code and data availability

The paper is a data descriptor for wGrapeUNIPD-DL, an open dataset of 373 vineyard images with YOLO-format bunch bounding-box labels, publicly deposited on Zenodo (10.5281/zenodo.4066730). The Yolo_Label GitHub link is a generic third-party annotation tool, not a paper-specific asset.