---
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

```bibtex
@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