Cabbage Leaf Integrity Analysis Dataset

Currently, the agricultural sector faces challenges such as untimely crop health monitoring and inaccurate pest identification. Traditional manual detection methods are inefficient and prone to errors. Existing solutions, like rule-based detection systems, often fail to adapt to complex field environments, resulting in frequent missed or incorrect detections. This dataset aims to assist researchers and developers in building more accurate target detection models by providing high-quality images of cabbage leaves, enabling automated crop health monitoring and pest detection. The dataset is constructed using high-resolution cameras in diverse field environments and annotated with the expertise of professional agricultural personnel, ensuring data reliability and effectiveness. We have implemented strict quality control measures, including consistency checks and multiple rounds of review, to ensure the accuracy of information in each image. The data is stored in JPG format, organized in a directory structure for easy access and processing.