AI 中文总结
该研究推出AerialYield-B2D温室蓝莓数据集，含五成熟阶段掩码与30195个标注果实，可用于蓝莓成熟度分割、果实计数及类别不平衡分析。
AI 中文摘要
蓝莓的成熟度由果实颜色、果簇组成以及植株内成熟阶段的分布判断，但公开的带有密集成熟阶段掩码的温室图像资源仍有限。我们推出AerialYield-B2D，其中B2D指BlueBerry Dataset，这是一个精心整理的真实图像资源，包含514张RGB图像和30195个标注的蓝莓实例，涵盖五个成熟阶段：未成熟绿色、浅粉色、粉转紫色、完全成熟和过熟。该发布内容包括类别特定的二值掩码、整体果实掩码、语义标签图、图像级计数表、SHA-256哈希值、源元数据、推荐的训练/验证/测试划分以及技术验证。AerialYield是更广泛的项目名称；本次发布未提供收获重量、果实质量或单位面积产量测量值，因此计数标签应理解为图像级果实计数而非产量估计。图像包括424张智能手机拍摄的温室图像、67个视频帧和23个DJI Fly视频帧样本，为可控环境蓝莓生产中的成熟度分割、果实计数和类别不平衡分析提供了可复现的数据集。
英文摘要
Blueberry ripeness is judged by berry colour, cluster composition, and the distribution of maturity stages within a plant, however, public green house image resources with dense ripeness-stage masks remain limited. We present AerialYield-B2D, where B2D denotes BlueBerry Dataset, acurated real-image resource containing 514 RGB images and 30,195 annotated blueberry instances across five ripeness stages: green immature, pale pink, pink-turns-purple, fully ripe and over-ripe. The release provides class-specific binary masks, overall berry masks, semantic label maps, image-level count tables, SHA-256 hashes, source metadata, recommended train/validation/test splits and technical validations. AerialYield is the broader project name; this release does not provide harvest weight, fruit mass or per-area yield measurements, and the count labels should therefore be interpreted as image-level berry counts rather than yield estimates. The images include 424 smartphone greenhouse images, 67 video-derived frames, and 23 DJI Fly video-frame samples, providing a reproducible dataset for ripeness segmentation, berry counting, and class-imbalance analysis in controlled-environment blueberry production.
