Farmland Irrigation Mist Segmentation Dataset

The current agricultural sector faces challenges of water resource wastage and low irrigation efficiency. Traditional irrigation methods often rely on human experience and lack scientific basis. Existing solutions are mostly rule-based technologies, which are difficult to adapt to complex field environments, and insufficient labeled data leads to poor algorithm performance. This dataset aims to support the research and development of intelligent irrigation decisions by providing high-quality farmland irrigation mist images and their segmentation annotations, promoting the development of precision agriculture. Data is collected using high-resolution cameras under various environmental conditions to ensure coverage of different mist states. For quality control, a method combining multiple rounds of labeling and expert review is adopted to ensure consistency and accuracy of annotations. Data storage uses JPG format images and JSON format annotation information, facilitating subsequent processing and analysis.