TomatoWUR: an annotated dataset of 3D tomato plants to quantitatively evaluate segmentation, skeletonisation, and plant trait extraction algorithms for 3D plant phenotyping
DOI: 10.4121/e2c59841-4653-45de-a75e-4994b2766a2f
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Dataset
In this research, we created a dataset of 44 annotated 3D point clouds of tomato plants. Images were captured using fifteen cameras surrounding a single plant. Those images were used to create a point cloud using the shape-from silhouette methodology (Golbach et al., 2016). The resulting dataset was annotated and separated into three parts. 1) Annotated point clouds and corresponding RGB images with semantic and instance labels , 2) annotated skeletons to analyse plant architecture, and 3) manual reference measurements of internode length, internode diameter, leaf angle, and phyllotactic angle to evaluate phenotyping algorithms from point cloud to plant traits.
History
- 2025-03-27 first online
- 2025-04-30 published, posted
Publisher
4TU.ResearchDataFormat
Raw images: PNG; Annotated RGB images: PNG; Camera calibration: json; Point clouds: csv, including coordinates (xyz), colour (r,g,b), normals (nx, ny, nz), Annotated point clouds: csv; Annotated skeletons including manual measurements: csvFunding
- Test and Experiment Facilities for the Agri-Food Domain (grant code 101100622) [more info...] Digital Europe Programme (DIGITAL)
Organizations
Greenhouse Horticulture Business Unit, Wageningen University & ResearchDATA
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