Pesticide Spraying Scene Classification Dataset

The current agricultural industry faces challenges such as low spraying efficiency and environmental pollution, especially during large-scale farmland spraying. Traditional methods rely on manual operations, which can lead to pesticide waste and uneven spraying. Existing solutions often lack efficient image recognition technology and cannot monitor spraying effectiveness and crop conditions in real-time. This dataset aims to support the intelligent development of agriculture by providing high-quality images of spraying scenes, thereby improving the efficiency and accuracy of spraying operations. Data collection uses high-resolution cameras in actual spraying environments to ensure images accurately reflect operational conditions. Quality control includes multiple rounds of annotation and expert review to ensure data consistency and accuracy. Image data is stored in JPG format, organized by category for easy subsequent processing and analysis.