Project-AgML/corn_leaf_disease_classification

Corn Leaf Disease Classification

This dataset provides real RGB images of corn leaves affected by various diseases, captured in field environments across northern Anhui Province, China. Images were acquired using a NIKON D810 camera at 1001x1500 pixels resolution, delivering high-fidelity visual data for agricultural disease detection research. The dataset contains 600 images across 6 classes: Bipolaris_Maydis, Common_Rust, Curvularia_Lunata(wakker)boed_Spot, Northern-Leaf-Blight, Own-Spot, Sheath-Blight.
Images per class:

• Bipolaris_Maydis: 100
• Common_Rust: 100
• Curvularia_Lunata(wakker)boed_Spot: 100
• Northern-Leaf-Blight: 100
• Own-Spot: 100
• Sheath-Blight: 100

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

Citation

@article{bai2025lightweight,
  title={A lightweight model and corn leaf disease recognition},
  author={Bai, Lujie and Zhu, Shaoqiu and Gao, Haitao},
  journal={PLOS One},
  volume={20},
  pages={e0336945},
  year={2025},
  publisher={Public Library of Science}
}

The dataset itself can be cited as:

Bai, L. (2025). A lightweight model and corn leaf disease recognition [Dataset]. figshare. https://doi.org/10.6084/M9.FIGSHARE.30264037.V6

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