| --- |
| 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 |
