Datasets:

Project-AgML
/

taro_leaf_disease_classification

dataset_info:
  - config_name: augmented
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Healthy
              '1': Leaf_Blight
              '2': Mosaic
              '3': Root_Rot
      - name: leaf_side
        dtype: string
    splits:
      - name: train
        num_bytes: 1058559313
        num_examples: 21740
    download_size: 1058966404
    dataset_size: 1058559313
  - config_name: raw
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Healthy
              '1': Leaf_Blight
              '2': Mosaic
              '3': Root_Rot
      - name: leaf_side
        dtype: string
    splits:
      - name: train
        num_bytes: 610741957
        num_examples: 4393
    download_size: 610866067
    dataset_size: 610741957
configs:
  - config_name: augmented
    data_files:
      - split: train
        path: augmented/train-*
  - config_name: raw
    data_files:
      - split: train
        path: raw/train-*
    default: true
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

Taro Leaf Disease Classification

Taro (Colocasia esculenta) leaf images labelled healthy, leaf blight, mosaic or root rot, photographed from the dorsal and ventral leaf sides, released with a comparison of Inception V3, ResNet-50 and ViT with SHAP explanations for taro disease identification. The raw config holds the 4,393 original images (all four classes) and the augmented config 21,740 augmented copies of the healthy and leaf-blight images. The leaf side is kept as a column (empty for root rot, which the record does not split by side). The dataset contains raw and augmented versions.
The raw dataset contains 4,393 images.
Images per class:

Healthy: 464
Leaf_Blight: 2,255
Mosaic: 894
Root_Rot: 780

The augmented dataset contains 21,740 images.
Images per class:

Healthy: 8,531
Leaf_Blight: 13,209
Mosaic: 0
Root_Rot: 0

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

Citation

@article{maedagutirrez2025ai,
  title={AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro},
  author={Maeda-Gutiérrez, Valeria and Oropeza-Valdez, Juan José and Reveles-Gómez, Luis C. and Padron-Manrique, Cristian and Resendis-Antonio, Osbaldo and Solís-Sánchez, Luis Octavio and Guerrero-Osuna, Hector A. and Olvera Olvera, Carlos Alberto},
  journal={Agronomy},
  volume={15},
  pages={77},
  year={2025},
  publisher={MDPI}
}

The dataset itself can be cited as:

Thite, S., Suryawanshi, Y., & PATIL, K. (2025). Colocasia esculenta Leaf Image Dataset [Dataset]. Mendeley Data. https://doi.org/10.17632/HMDR3DZ3V6.4

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