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CherrySet -- A comprehensive dataset of three cherry trees throughout the 2023 season
  • +6
  • Andreas Gilson,
  • Lukas Meyer,
  • Franz Uhrmann,
  • Annika Killer,
  • Oliver Scholz,
  • Fabian Keil,
  • Marc Stamminger,
  • Dominikus Kittemann,
  • Patrick Noack
Andreas Gilson
Lukas Meyer
Franz Uhrmann
Annika Killer
Oliver Scholz

Corresponding Author:[email protected]

Author Profile
Fabian Keil
Marc Stamminger
Dominikus Kittemann
Patrick Noack


We present CherrySet, a comprehensive dataset comprising observations of three cherry trees throughout an entire vegetation period. This publication is part of the For5G: Digital Twin project, where we aim to develop an end-to-end pipeline for the creation of digital twins in horticulture, from data acquisition up to end-user applications. For this purpose, we have developed a methodology for precise scanning and capturing of high-resolution image data of trees using UAV technology. Now we are releasing the dataset and preliminary findings of the 2023 season to encourage fellow researchers to leverage the data for their own research and contribute to the scientific community.
CherrySet encompasses a collection of 2D images covering three sweet cherry trees at 12 distinct time points, spanning from dormancy in March through blooming and growth until harvest in July 2023. In addition to the image data, CherrySet offers manually recorded ground truth information obtained from reference branches throughout the growing season, which includes comprehensive bud, blossoms and fruit counts during all vegetation phases, as well as the total number of cherries gathered at harvest. The combination of visual and ground truth trait data allows insights into intra-seasonal analysis of tree and fruit development, providing valuable data for conventional or AI based follow-up research.
We are committed to refining our image acquisition pipeline and intend to provide corresponding data for these trees throughout the 2024 season. This expansion will open up opportunities for inter-seasonal research.
19 Oct 2023Submitted to NAPPN 2024
19 Oct 2023Published in NAPPN 2024