Datasets:

Project-AgML
/

corn_leaf_disease_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Bipolaris_Maydis
            '1': Common_Rust
            '2': Curvularia_Lunata(wakker)boed_Spot
            '3': Northern-Leaf-Blight
            '4': Own-Spot
            '5': Sheath-Blight
  splits:
    - name: train
      num_bytes: 69223597
      num_examples: 600
  download_size: 69234645
  dataset_size: 69223597
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - n<1K

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.