Onion Classification and Segmentation Dataset

The current agricultural industry faces challenges of high cost and low efficiency in crop monitoring and pest and disease detection. Existing solutions often rely on manual inspection, which is inefficient and prone to errors. This dataset aims to enhance the application capability of computer vision models in agriculture by providing high-quality onion images and segmentation annotations. The dataset construction process includes using professional cameras to shoot onion images under natural light conditions, and ensuring annotation consistency and accuracy through multiple rounds of annotation and expert review. Data will be stored in JPG format for original images and in JSON format for the corresponding mask information, facilitating subsequent deep learning training.