| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Alternaria |
| '1': Apple_Mosaic |
| '2': Healthy |
| splits: |
| - name: train |
| num_bytes: 64844454 |
| num_examples: 5612 |
| download_size: 66907339 |
| dataset_size: 64844454 |
| 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 |
| --- |
| |
| # Apple Leaf Disease Classification |
|
|
| A dataset for image classification of Apple Leaf Disease Classification. The dataset contains 7,505 images across 3 classes: Alternaria, Apple_Mosaic, Healthy. |
| Images per class: |
| - Alternaria: 2,523 |
| - Apple_Mosaic: 2,523 |
| - Healthy: 2,459 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{yatoo2024indigenous, |
| title={An indigenous dataset for the detection and classification of apple leaf diseases}, |
| author={Yatoo, Arshad Ahmad and Sharma, Amit}, |
| journal={Data in Brief}, |
| volume={53}, |
| pages={110165}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Yatoo, Arshad; Sharma, Amit (2024), “Indigenous Dataset for Apple Leaf Disease Detection and Classification”, Mendeley Data, V3, doi: 10.17632/9m2dcb5mmr.3 |
