Datasets:

Project-AgML
/

IDDMSLD_spinach_leaf_disease_classification

configs:
  - config_name: default
    default: true
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Anthracnose
              '1': Bacterial-Spot
              '2': Downy-Mildew
              '3': Healthy-Leaf
              '4': Pest-Damage
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

IDDMSLD Spinach Leaf Disease Classification

A dataset for disease classification of spinach leaves. The dataset contains 3,006 images across 5 classes: Anthracnose, Bacterial-Spot, Downy-Mildew, Healthy-Leaf, Pest-Damage.
Images per class:

Anthracnose: 102
Bacterial-Spot: 752
Downy-Mildew: 240
Healthy-Leaf: 1,399
Pest-Damage: 513

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

Citation

@article{sayeem2025iddmsld,
  title={IDDMSLD: An image dataset for detecting Malabar spinach leaf diseases},
  author={Sayeem, Adnan Rahman and Omi, Jannatul Ferdous and Hasan, Mehedi and Mojumdar, Mayen Uddin and Chakraborty, Narayan Ranjan},
  journal={Data in Brief},
  volume={58},
  pages={111293},
  year={2025},
  publisher={Elsevier}
}

Sayeem , Adnan Rahman; Omi , Jannatul Ferdous; Hasan , Mehedi; Mojumdar, Mayen Uddin (2024), “Malabar Spinach Disease Detection Dataset”, Mendeley Data, V2, doi: 10.17632/sy69db2nz5.2