The Growing Strawberries Dataset

doi: 10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7
Datacite citation style:
Wen, Junhan; Camiel Verschoor; Thomas Abeel; de Weerdt, M.M. (Mathijs) (2023): The Growing Strawberries Dataset. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

The Growing Strawberries Dataset (GSD) is a curated multiple-object tracking dataset inspired by the growth monitoring of strawberries. The frames were taken at hourly intervals by six cameras for in total of 16 months in 2021 and 2022, covering 12 plants in two greenhouses respectively. The dataset consists of hourly images collected during the cultivation period, bounding box (bbox) annotations of strawberry fruits, and precise identification and tracking of strawberries over time. GSD contains two types of images - RGB (color) and OCN (orange, cyan, near-infrared). These images were captured throughout the cultivation period. Each image sequence represents all the images captured by one camera during the year of cultivation. These sequences are named using the format "<RGB/OCN-1/2/3-2021/2022>." In addition, a small sample captured by one of the RGB cameras is included, featuring images and annotations from a two-day period, along with a demo video spanning seven days. The ground-truth annotations of the bbox and trajectories of strawberries are provided with a coco-format JSON file and a TXT file for compatibility with the MOT Challenge evaluation tools. Images that were too dark for annotations are also available upon request.

history
  • 2023-11-06 first online, published, posted
publisher
4TU.ResearchData
format
.jpg; .json; .txt.
funding
  • Topsector Tuinbouw & Uitgangsmaterialen
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Algorithmics group

DATA

files (4)