Datasets:
image imagewidth (px) 3.02k 4.03k | objects dict | disease stringclasses 3
values |
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... | viral | |
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End of preview. Expand in Data Studio
Tomato Disease Detection Greenhouse
1,026 iPhone 14 images of greenhouse tomatoes in Sichuan, China (2024) showing three diseases: viral disease (TYLCV and ToCV, 417 images), gray mold (82) and bacterial wilt (527), from about 175 plants photographed at different angles and distances. Plant pathologists drew bounding boxes around the diseased leaves, fruits and stems in LabelImg (Pascal VOC). Boxes are labelled by disease and plant part (for example wilt_stem, viral_top, graymold_fruit), and the disease folder is kept as a column; images are stored upright with their boxes rotated to match. The dataset contains 1,026 images with 3,167 bounding box annotations across 10 categories.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{liu2025labeled,
title={A labeled image dataset of common tomato diseases for classification and object detection},
author={Liu, Yongbo and Zhu, Yuhang and Hu, Liang and Huo, Yao and Gao, Wenbo and Hu, Rongping and He, Peng},
journal={Data in Brief},
volume={63},
pages={112032},
year={2025},
publisher={Elsevier}
}
The dataset itself can be cited as:
Liu, Y. (2025). Tomato Disease Dataset [Dataset]. Mendeley Data. https://doi.org/10.17632/C2X8RYNYBG.1
This dataset was reformatted from its original format to match HuggingFace standards.
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