Project-AgML/DeepCanola_br11

Deepcanola Br11

This dataset contains unlabeled RGB images of canola (Brassica napus) plants in field environments, featuring a mix of real field captures and synthetic data. It provides a diverse resource for agricultural computer vision research focused on crop segmentation tasks within natural farming settings. The dataset contains 70 images with no classification, segmentation, or bounding-box annotations.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{vanvliet2025deepcanola,
  title={DeepCanola: Phenotyping brassica pods using semi-synthetic data and active learning},
  author={van Vliet, Larissa J.J. and Atkins, Kieran and Kurup, Smita and Siles, Laura and Hepworth, Jo and Corke, Fiona M.K. and Doonan, John H. and Lu, Chuan},
  journal={Computers and Electronics in Agriculture},
  volume={237},
  pages={110470},
  year={2025},
  publisher={Elsevier}
}

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