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

Published: 29 November 2021| Version 2 | DOI: 10.17632/j4xs3kh3fd.2


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.



Manisa Celal Bayar Universitesi


Agricultural Science, Image Processing, Viticulture, Artificial Intelligence Applications, Plant Pathology