Project-AgML/maize_tomato_weed_classification

Maize Tomato Weed Classification

A dataset for classification of weeds and crops in maize and tomato fields. The dataset contains 55,828 images across 12 classes:
Images per class:

• atriplex: 2,459
• chenopodium: 3,375
• convolvulus: 2,302
• cyperus: 3,215
• datura: 1,271
• lolium: 1,063
• maize: 25,273
• portulaca: 2,052
• salsola: 2,409
• solanum: 4,084
• sorghum: 1,703
• tomato: 6,622

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

Citation

@article{mesias2025drone,
  title={Drone imagery dataset for early-season weed classification in maize and tomato crops},
  author={Mes{\'\i}as-Ruiz, Gustavo A and Pe{\~n}a, Jos{\'e} M and de Castro, Ana I and Dorado, Jos{\'e}},
  journal={Data in Brief},
  volume={58},
  pages={111203},
  year={2025},
  publisher={Elsevier}
}

Mesías-Ruiz, G. A., Peña Barragán, J. M., Castro, A. I. D., & Dorado, J. (2024). DIWEED: Drone Imagery dataset for early-season WEED classification [Data set]. DIGITAL.CSIC. http://doi.org/10.20350/DIGITALCSIC/16559

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