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RaspGrade
RaspGrade is a dataset of high-resolution RGB images of raspberry punnets, collected using a top-down camera and LED lighting setup. Each raspberry is manually annotated with segmentation and expert-assigned quality grade labels, enabling training and evaluation of fruit grading models.
RaspGrade is published with the paper
Mekhalfi, M.L., Chippendale, P., Poiesi, F., Bonecher, S., Osler, G., and Zancanella, N. (2025). The RaspGrade Dataset: Towards Automatic Raspberry Ripeness Grading with Deep Learning. Under review. [arXiv version]
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Copyright: The RaspGrade Dataset is published under the Creative Commons Attribution Non Commercial 4.0 License (CC BY NC 4.0). This means that you are required to attribute the work in the manner specified by the authors (e.g., citing the paper in the reference above). You are not allowed to use this work for commercial purposes. Additionally, if you choose to alter, transform, or build upon this dataset, you may distribute the resulting work under the same CC BY NC 4.0 license.
Aknowledgements
This work is supported by European Union’s Horizon Europe research and innovation programme under grant agreement No 101092043, project AGILEHAND (Smart Grading, Handling and Packaging Solutions for Soft and Deformable Products in Agile and Reconfigurable Lines).
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