GVLiD: GrapeVine Leaf identification of the Diseases

Grapes are one of the most important crops in global agriculture, primarily used for wine, fresh fruit, and raisins. Nevertheless, grapevines are prone to various diseases that can significantly impact their yield and quality. Early detection and treatment of these diseases is essential. We introduce the "GVLiD: GrapeVine Leaf identification of the Diseases", which has 4 classes of 3,477 high-resolution images of grape leaves. The dataset covers the following common grapevine diseases: 1) Healthy, 2) Black rot, 3) Esca, and 4) Leaf blight. The dimensions of the images are 1080 × 1080. Images are in JPG format. Images having 120 DPI collected through a field visit and captured from different angles. Unlike existing datasets, GVLiD incorporates high-resolution field-acquired images with structured metadata, enabling real-world disease detection

葡萄是全球农业的重要作物之一，主要用于酿酒、鲜食及制作葡萄干。然而，葡萄藤极易感染多种病害，此类病害会严重影响其产量与品质。及早检测与防治此类病害至关重要。本研究发布GVLiD：葡萄叶片病害识别数据集（GrapeVine Leaf identification of the Diseases），该数据集包含4个分类下的3477张高分辨率葡萄叶片图像。数据集涵盖以下常见葡萄病害：1) 健康叶片，2) 黑腐病，3) 埃斯卡病（Esca），4) 叶枯病。图像像素尺寸为1080×1080，格式为JPG。所有图像均通过实地考察采集，拍摄角度多样，分辨率为120 DPI。与现有数据集不同，GVLiD整合了高分辨率实地采集图像与结构化元数据，可支持真实场景下的病害检测任务。

搜集汇总

背景与挑战

背景概述

GVLiD数据集包含3,477张高分辨率（1080×1080）的葡萄叶图像，涵盖4类常见葡萄病害：健康、黑腐病、Esca病和叶枯病。该数据集专为现实世界病害检测设计，图像以JPG格式存储，具有结构化元数据，适用于机器学习和深度学习研究。