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End of preview. Expand in Data Studio
Jujube Disease Spot Detection
This dataset provides real-world RGB images of jujube fruits in field environments across Xinjiang, China, captured during autumn for disease spot detection. Images were acquired using a fixed industrial camera with high-resolution capabilities at two experimental cultivation sites. The collection offers a practical benchmark for object detection models targeting agricultural disease monitoring in real-world farming conditions. The dataset contains 127 images with 1,194 bounding box annotations across 2 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{yin2024high,
title={A high-precision jujube disease spot detection based on SSD during the sorting process},
author={Yin, Zhi-Ben and Liu, Fu-Yong and Geng, Hui and Xi, Ya-Jun and Zeng, De-Bin and Si, Chun-Jing and Shi, Ming-Deng},
journal={PLOS ONE},
volume={19},
pages={e0296314},
year={2024},
publisher={Public Library of Science}
}
The dataset itself can be cited as:
inchar, inchar. (2023). JujubeDataSet_mini.zip [Dataset]. figshare. https://doi.org/10.6084/M9.FIGSHARE.24454576.V1
This dataset was reformatted from its original format to match HuggingFace standards.
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