Spray Droplet Coverage Segmentation Dataset

The current agricultural sector faces challenges such as irregular pesticide use and uneven spraying effects, leading to poor pest and disease control. Existing spraying technologies rely on human experience, resulting in inefficiencies and insufficient precision. This dataset aims to assist researchers and developers in training more precise image segmentation models by providing high-quality spray droplet coverage segmentation data, enabling intelligent spraying. Data collection primarily uses high-resolution cameras to capture crop images under different lighting and climatic conditions, along with professional spraying equipment for droplet coverage capture. At the same time, data quality control employs multiple rounds of annotation and expert review to ensure consistency and accuracy of annotation. Images are stored in JPG format, and related annotation information is recorded in JSON format, facilitating subsequent processing and analysis.