---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': bacterial_leaf_blight
          '1': bacterial_leaf_streak
          '2': bacterial_panicle_blight
          '3': blast
          '4': brown_spot
          '5': dead_heart
          '6': downy_mildew
          '7': hispa
          '8': normal
          '9': tungro
  splits:
  - name: train
    num_bytes: 807799888
    num_examples: 10407
  download_size: 819745776
  dataset_size: 807799888
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Paddy Disease Classification

A dataset for disease classification of rice paddies. The dataset contains 10,407 images across 10 classes: bacterial_leaf_blight, bacterial_leaf_streak, bacterial_panicle_blight, blast, brown_spot, dead_heart, downy_mildew, hispa, normal, tungro.  
Images per class:
- bacterial_leaf_blight: 479
- bacterial_leaf_streak: 380
- bacterial_panicle_blight: 337
- blast: 1,738
- brown_spot: 965
- dead_heart: 1,442
- downy_mildew: 620
- hispa: 1,594
- normal: 1,764
- tungro: 1,088

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

## Citation

Petchiammal A, Briskline Kiruba S, Murugan D, Pandarasamy Arjunan. (2022). Paddy Doctor: A Visual Image Dataset for Automated Paddy Disease Classification and Benchmarking. IEEE Dataport. https://dx.doi.org/10.21227/hz4v-af08