Bean Leaf Detection Dataset

The current agricultural sector faces the challenge of crop pest and disease detection. Due to the lack of efficient and accurate detection technologies, crops suffer severe losses. Existing solutions often rely on manual detection, which is not only inefficient but also prone to errors. The Bean Leaf Detection Dataset aims to provide high-quality annotated image data to help researchers and developers develop more precise computer vision algorithms to automatically identify and detect pests and diseases on bean leaves. The data is collected by professionals in various field environments, using high-resolution cameras to ensure that image details are clearly distinguishable. Multiple rounds of annotation and consistency checks are implemented during data processing to ensure the accuracy and consistency of annotations. The data is stored in JPEG format, organized such that each image file corresponds to an annotation file, facilitating subsequent applications.