GRAPE Leaf Diseases is a grape leaf image dataset specifically designed for precision agriculture target detection tasks. It aims to improve the ability of computer vision models to detect, classify, and locate diseases in real agricultural scenarios. It is widely used in YOLO series model training, agricultural disease detection, edge vision deployment, and intelligent grape planting management. This dataset contains 4,195 images of grape leaves, covering four categories: healthy grape leaves and three common diseases: black rot, Escafé fulva, and leaf blight. The dataset has been preprocessed and organized in standard YOLO format, divided into training and validation sets. Each image corresponds to a .txt annotation file containing the object's bounding box coordinates and class ID.

Dataset composition:

• Grape Black Rot: 1,244 images, 1,313 bounding boxes
• Grape__Esca (Grape Esca Disease/Black Measles): 1,383 images, 1,383 bounding boxes
• Grape__Healthy (Healthy Grape Leaves): 492 images, 643 bounding boxes
• Grape Leaf Blight: 1,076 images, 1,076 bounding boxes

  

Citations

• PlantVillage
• PlantDoc
• BioDome