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image imagewidth (px) 640 640 | mask imagewidth (px) 640 640 | num_instances int32 1 8 | split stringclasses 3
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Occpepseg Yolo Occluded Segmentation
This dataset provides RGB images of pepper plants in field environments, specifically focusing on the challenge of segmenting occluded peppers within natural agricultural settings. Captured using an ORBBEC Gemini 335L camera during June-July 2025 in Inner Mongolia, China, the images depict real-world field conditions with varying degrees of foliage occlusion affecting pepper visibility. The dataset contains raw and augmented versions. The raw split contains 1,500 images with pixel-level mask annotations.
The augmented split contains 6,000 images with pixel-level mask annotations.
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{yu2026occpepseg,
title={OccPepSeg-YOLO for Instance Segmentation of Occluded Peppers in Field Images},
author={Yu, Xinran and Jiang, Mingxi and Gao, Fei and Fan, Yize and Bai, Yanyan and Peng, Zhigang and Lu, Qi and Liu, Qian and Xu, Shengyong},
journal={Agronomy},
volume={16},
pages={1646},
year={2026},
publisher={MDPI}
}
This dataset was reformatted from its original format to match HuggingFace standards.
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