| --- |
| configs: |
| - config_name: default |
| default: true |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Dieback |
| '1': Fresh |
| '2': Holed |
| '3': Mosaic |
| '4': Stem Soft Rot |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Jute Disease Classification |
|
|
| A dataset for image classification of Jute Disease. The dataset contains 1,390 images across 5 classes: Dieback, Fresh, Holed, Mosaic, Stem Soft Rot. |
| Images per class: |
| - Dieback: 300 |
| - Fresh: 280 |
| - Holed: 300 |
| - Mosaic: 240 |
| - Stem Soft Rot: 270 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{islam2025comprehensive, |
| title={A comprehensive image dataset of jute diseases}, |
| author={Islam, Md Masudul and Sheikh, Md Ripon}, |
| journal={Data in Brief}, |
| pages={112334}, |
| year={2025}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Islam, Md. Masudul; Sheikh, Md Ripon, 2025, "Jute Disease Image Dataset", https://doi.org/10.7910/DVN/FJ1DM1, Harvard Dataverse, V1 |
|
|
