Datasets:

Project-AgML
/

rice_leaf_disease_classification_2

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

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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.