Tomato Leaf Damage Progression

This dataset provides 8,596 images of tomato leaves focusing on the progression of three diseases: Fusarium spp., Leaf Miner, and Early Blight. It is designed to support the development and evaluation of deep learning models for object detection and severity stage classification under real field conditions.
The images are categorized into three severity levels (Initial, Intermediate, and Advanced), enabling the study of disease evolution. The dataset includes original field captures, manually cropped leaf instances, and synthetic images generated via Poisson blending to improve early-stage representation.
Additionally, selective median filtering was applied to the Early Blight class to enhance data quality. The dataset follows the YOLO annotation format, allowing direct use in object detection frameworks and facilitating reproducibility in agricultural computer vision research.