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Project-AgML
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CWF788_weed_segmentation

image imagewidth (px) 400 400	mask imagewidth (px) 400 400	split stringclasses 3 values
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Cwf788 Weed Segmentation

This dataset provides real-world RGB imagery for semantic segmentation of weeds in agricultural fields. It captures diverse weed instances under natural field conditions, offering a practical resource for developing and evaluating computer vision models in precision agriculture applications. The dataset contains 788 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{li2019real,
  title={Real-time crop recognition in transplanted fields with prominent weed growth: a visual-attention-based approach},
  author={Li, Nan and Zhang, Xiaoguang and Zhang, Chunlong and Guo, Huiwen and Sun, Zhe and Wu, Xinyu},
  journal={IEEE Access},
  volume={7},
  pages={185310--185321},
  year={2019},
  publisher={IEEE}
}

https://github.com/ZhangXG001/Real-Time-Crop-Recognition

This dataset was reformatted from its original format to match HuggingFace standards.

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