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End of preview. Expand in Data Studio
Paddy Weed Target Detection
This dataset provides real-world RGB images captured in rice paddy fields during the seedling stage, focusing on the detection of weeds within rice crops under natural field conditions. Images were collected using a handheld Canon IXUS 1000 HS camera with a telephoto lens, offering close-up field-level perspectives for agricultural computer vision applications. The dataset contains 358 images with 840 bounding box annotations across 1 category.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{deng2023weed,
title={Weed target detection at seedling stage in paddy fields based on YOLOX},
author={Deng, Xiangwu and Qi, Long and Liu, Zhuwen and Liang, Song and Gong, Kunsong and Qiu, Guangjun},
journal={PLOS ONE},
volume={18},
pages={e0294709},
year={2023},
publisher={Public Library of Science}
}
This dataset was reformatted from its original format to match HuggingFace standards.
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