Backpack Sprayer Usage Detection Dataset

The current agricultural industry faces issues such as low efficiency in sprayer use and poor spray uniformity, which impact crop growth and yield. Existing monitoring solutions largely rely on manual inspections, which are inefficient and prone to errors. Therefore, establishing a dedicated sprayer usage detection dataset can improve the monitoring efficiency of sprayers using machine learning technologies. This dataset contains image data of various sprayers in different environments, aiming to automatically identify sprayer usage through object detection technology. Data collection is carried out using drones in farmland environments to ensure a diverse range of crops and sprayer types are covered. In terms of quality control, data undergo multiple rounds of annotation and expert review to ensure consistency and accuracy of the annotations. Data is stored in JPG format, organized as image files along with their corresponding annotation information for ease of future use.