Peach 原始数据存储

已经开发了一个基于真实世界果园种植环境的桃子成熟度分类综合数据集。该数据集利用了不同生长阶段的桃子图像，这些图像使用分辨率为 3024 x 4032 像素的智能手机拍摄。这些图像包括桃子的三个成熟阶段：硬熟、半熟和完全成熟。此外，该数据集还包括拍摄距离、照明条件和水果生长状态的变化。经过选择过程，原始数据集由 1,245 张图像组成。这些图像在水果周围用 3,493 个边界框进行了手动注释，并且注释文件以 Pascal VOC 和 YOLO 格式提供。该数据集旨在利用深度学习技术促进智能果园运营的进一步研究和开发。

A comprehensive dataset for peach maturity classification based on real-world orchard planting environments has been developed. This dataset employs images of peaches at different growth stages, which were captured using smartphones with a resolution of 3024 × 4032 pixels. The images cover three maturity stages of peaches: firm-ripe, semi-ripe, and fully-ripe. In addition, the dataset includes variations in shooting distance, lighting conditions, and fruit growth status. After a selection process, the original dataset consists of 1,245 images. These images were manually annotated with 3,493 bounding boxes around the peaches, and the annotation files are provided in Pascal VOC and YOLO formats. This dataset aims to facilitate further research and development of intelligent orchard operations using deep learning technologies.