Pumpkin Leaf and Fruit Joint Detection Dataset

The current agricultural sector faces challenges in detecting and managing crop pests and diseases, especially in pumpkin cultivation where they directly affect yield and quality. Existing monitoring methods largely rely on manual inspection, which is inefficient and error-prone. Therefore, there is an urgent need for an efficient target detection dataset to support intelligent pest and disease identification and warning systems. This dataset aims to provide agricultural researchers and enterprises with accurate and comprehensive pumpkin leaf and fruit detection data, thereby promoting the development of automated monitoring technology. The dataset includes 5000 high-quality images of pumpkin leaves and fruits, collected from various growing environments, and has undergone multiple rounds of annotation and consistency checks to ensure data reliability. The data is stored in JPG format and organized into fields such as image ID, bounding box, labels, and confidence, facilitating subsequent machine learning model training and evaluation.