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End of preview. Expand in Data Studio
Truss Tomato Detection Greenhouse
Greenhouse truss tomato images from the 2022 Shanxi Agricultural Valley Tomato Town dataset, used to train the PHDT-DETR detector for harvesting robots. Trusses were photographed in July-August 2022 in Taigu, Shanxi, China with four smartphones under sunny and overcast skies from morning to dusk, about eight images per truss. Objects are boxed in LabelImg as mature truss, raw (unripe) truss or stem; this TGTomato-Balanced release holds 4,505 640x640 images (4,504 here; one source PNG is corrupt), the 3,665 originals mixed with the authors' class-balancing augmentations (which the file names do not distinguish), in the published train, validation and test splits. The dataset contains 4,504 images with 8,251 bounding box annotations across 3 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
The original train/test/val split has been preserved in the split column.
Citation
@article{yang2026phdt,
title={PHDT-DETR: A lightweight end-to-end detector for on-device truss tomato detection in greenhouses},
author={Yang, Nengwei and Ji, Peng and Lin, Sen and Xiong, Ya},
journal={Smart Agricultural Technology},
volume={13},
pages={101742},
year={2026},
publisher={Elsevier}
}
The dataset itself can be cited as:
yang, nengwei, & Lin, S. (2025). TGTomato-Balanced: A Class-Balanced Derivative Dataset for Truss Tomato Detection [Dataset]. Mendeley Data. https://doi.org/10.17632/344HXX5RKF.1
This dataset was reformatted from its original format to match HuggingFace standards.
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