---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Bacterial leaf blight
          '1': Brown spot
          '2': Leaf Blast
  - name: split
    dtype: string
  splits:
  - name: train
    num_bytes: 512417530
    num_examples: 1914
  download_size: 464347363
  dataset_size: 512417530
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Rice Leaf Disease Classification 2

This dataset provides real RGB images of rice leaves affected by various diseases, captured in typical agricultural field environments. The images reflect natural farming conditions and disease manifestations, offering a practical resource for developing computer vision models in crop health monitoring. The dataset contains 1,914 images across 3 classes: Bacterial leaf blight, Brown spot, Leaf Blast.  
Images per class:
- Bacterial leaf blight: 638
- Brown spot: 638
- Leaf Blast: 638

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

The original train/test/val split has been preserved in the `split` column.

## Citation

```bibtex
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```

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The dataset itself can be cited as:

Shakeel, U. (2025). *Rice Leaf Disease* [Dataset]. Zenodo. https://doi.org/10.5281/ZENODO.15817084


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