首个提供五阶段成熟度标注的温室蓝莓图像数据集。
AerialYield-B2D: A Greenhouse Blueberry Dataset with Five-Stage Ripeness Masks and Fruit Counts
- 构建包含514张图片、30195个果实实例的蓝莓数据集，标注五阶段成熟度。
- 提供逐果二值掩码、语义标签图及图像级计数表，支持成熟度分割与计数研究。
- 适合开展温室蓝莓成熟度分析、类别不平衡问题研究的科研人员使用。
蓝莓成熟度由果实颜色、簇状结构及植株内成熟阶段分布决定，但公开的温室图像资源中带有密集成熟度标注的数据仍有限。我们提出AerialYield-B2D，其中B2D代表蓝莓数据集，是一个基于真实图像的精准资源，包含514张RGB图像和30,195个标注的蓝莓实例，覆盖五个成熟阶段：绿色未熟、淡粉、粉转紫、完全成熟及过熟。该数据集提供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、源元数据、推荐训练/验证/测试划分及技术验证。AerialYield是更广泛的项目名称；本次发布不包含收获重量、果实质量或单位面积产量测量，因此计数标签应理解为图像级果实数量，而非产量估计。图像来源包括424张智能手机拍摄的温室图像、67帧视频提取图像及23帧DJI Fly视频采样，可复现用于成熟度分割、果实计数及类别不平衡分析的控制环境蓝莓生产研究。
原文摘要 · Abstract (English)
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.
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