HERMOS: An Annotated Image Dataset for Visual Detection of Grape Leaf Diseases

Vineyard powdery mildew (Uncinula necator), dead arm (Phomopsis viticola) and vineyard downy mildew (Plasmopara viticola) diseases are frequently seen in the vineyards in the Gediz River Basin, West Anatolia of Turkey and cause significant damage to the crop. These diseases can be detected early using artificial intelligence-based systems that can contribute to crop yields and also reduce the labor of the farmer and the amount of pesticides used. This article presents a dataset, for use in such AI-based systems. The dataset, namely Hermos, contains four classes of grapevine images; leaves with dead root, leaves with powdery mildew, leaves with downy mildew and healthy leaves. Diseased areas on the leaf pictures were labeled with the "bounding-box" method. The dataset contains a total of 914 images and 13,904 labels. Labels on the picture are stored in Pascal VOC format in an xml document with the same file name as the picture.

土耳其安纳托利亚西部杰伊德河（Gediz River）流域的葡萄园内，葡萄白粉病（Uncinula necator）、葡萄枝枯病（Phomopsis viticola）与葡萄霜霉病（Plasmopara viticola）频发，对葡萄产量造成严重损失。借助基于人工智能的系统可对上述病害实现早期检测，这既能提升作物产量，还可减少农户的劳作强度与农药使用量。本文针对此类人工智能系统的应用需求，推出了一款专用数据集。该数据集名为Hermos，涵盖四类葡萄叶片图像：带根腐症状的叶片、感染白粉病的叶片、感染霜霉病的叶片以及健康叶片。数据集内的叶片图像均采用边界框（bounding-box）法对病害区域进行标注，总计包含914张图像与13904个标注框。图像对应的标注信息以Pascal VOC格式存储于与图像文件名一致的XML文档中。

搜集汇总

背景与挑战

背景概述

HERMOS数据集是一个用于葡萄叶病害视觉检测的标注图像集，包含四类叶片图像：死臂病、白粉病、霜霉病和健康叶片，共914张图像和13,904个边界框标签，采用Pascal VOC格式存储，旨在支持基于人工智能的早期病害检测系统，以提高作物产量并减少农药使用。