| --- |
| 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': healthy |
| '1': segatoka |
| '2': xamthomonas |
| splits: |
| - name: train |
| num_bytes: 6672019 |
| num_examples: 1288 |
| download_size: 6920645 |
| dataset_size: 6672019 |
| --- |
| |
| # Banana Leaf Disease Classification |
|
|
| A dataset for disease classification of Banana Leaves. The dataset contains 1,288 images across 3 classes: healthy, segatoka, xamthomonas. |
| Images per class: |
| - healthy: 154 |
| - segatoka: 320 |
| - xamthomonas: 814 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{genet2024sigatoka, |
| title={Sigatoka and xanthomonas banana leaf disease detection via transfer learning}, |
| author={Genet, Yordanos Hailu and Sinshaw, Natnael Tilahun and Assefa, Beakal Gizachew and Mohapatra, Sudhir Kumar}, |
| journal={Scientia Iranica}, |
| volume={31}, |
| number={21}, |
| pages={1939--1947}, |
| year={2024}, |
| publisher={Sharif University of Technology} |
| } |
| ``` |
|
|
| hailu, yordanos (2021), “Banana Leaf Disease Images”, Mendeley Data, V1, doi: 10.17632/rjykr62kdh.1 |
