---
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

```bibtex
@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.*