Seedling Recognition Dataset

The current agricultural industry faces challenges such as inefficient crop management and insufficient monitoring of pests and diseases. Traditional manual monitoring methods are not only time-consuming and labor-intensive, but also prone to errors. Existing solutions often rely on simple image recognition technology, which fails to meet the high-precision demands of real-world applications. This dataset aims to support more advanced object detection models by providing high-quality seedling images and their accurate annotations, thereby improving the automation of crop monitoring. The dataset is constructed using high-resolution cameras in a greenhouse environment to ensure image clarity and accuracy. We conducted multiple rounds of annotation and expert review to ensure the consistency and accuracy of data annotations. The data is stored in JPEG format with annotations organized in JSON format, facilitating processing and analysis.