| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 1K<n<10K |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Cercospora leaf spot |
| '1': Healthy |
| '2': Insect |
| '3': Leaf Crinkle |
| '4': Yellow Mosaic |
| splits: |
| - name: train |
| num_bytes: 1789298506 |
| num_examples: 4038 |
| download_size: 1961483365 |
| dataset_size: 1789298506 |
| --- |
| |
| # Black Gram Disease Classification |
|
|
| A dataset for disease classification of Black Gram. The dataset contains 4,038 images across 5 classes: Cercospora leaf spot, Healthy, Insect, Leaf Crinkle, Yellow Mosaic. |
| Images per class: |
| - Cercospora leaf spot: 598 |
| - Healthy: 545 |
| - Insect: 408 |
| - Leaf Crinkle: 806 |
| - Yellow Mosaic: 1,681 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{shoib2025idbgl, |
| title={IDBGL: A unique image dataset of black gram (Vigna mungo) leaves for disease detection and classification}, |
| author={Shoib, Md Mehedi Hasan and Saeem, Shahnewaz and Tonima, Afia Benta Aziz and Mojumdar, Mayen Uddin}, |
| journal={Data in Brief}, |
| volume={59}, |
| pages={111347}, |
| year={2025}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Shoib, Md Mehedi Hasan; Saeem, Shahnewaz; Tonima, Afia Benta Aziz; Mojumdar, Mayen Uddin (2024), “Image Dataset for Disease Detection in Black Gram (Vigna mungo) Leaves: A Resource for Machine Learning Research”, Mendeley Data, V3, doi: 10.17632/z55yrbmn2d.3 |
