Datasets:
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End of preview. Expand in Data Studio
Wheat Disease Detection
This dataset provides real RGB images of wheat crops in field environments from Yuanyang, Henan Province, China, captured during the 2023 growing season. Collected using smartphone and DSLR cameras under natural field conditions, it offers diverse observations for object detection of wheat diseases in agricultural settings. The dataset contains 4,156 images with 5,845 bounding box annotations across 7 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{qian2025gdfc,
title={GDFC-YOLO: An Efficient Perception Detection Model for Precise Wheat Disease Recognition},
author={Qian, Jiawei and Dai, Chenxu and Ji, Zhanlin and Liu, Jinyun},
journal={Agriculture},
volume={15},
pages={1526},
year={2025},
publisher={MDPI}
}
The dataset itself can be cited as:
Ma, C. (2024). Wheat Dataset [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.15621359
This dataset was reformatted from its original format to match HuggingFace standards.
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