| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': citrus_canker |
| '1': citrus_greening |
| '2': citrus_mealybugs |
| '3': die_back |
| '4': foliage_damaged |
| '5': healthy_leaf |
| '6': powdery_mildew |
| '7': shot_hole |
| '8': spiny_whitefly |
| '9': yellow_dragon |
| '10': yellow_leaves |
| splits: |
| - name: train |
| num_bytes: 2923333962 |
| num_examples: 5813 |
| download_size: 3681067331 |
| dataset_size: 2923333962 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| |
| # Orange Leaf Disease Classification |
|
|
| A dataset for disease classification of orange leaves. The dataset contains 5,813 images across 11 classes: citrus_canker, citrus_greening, citrus_mealybugs, die_back, foliage_damaged, healthy_leaf, powdery_mildew, shot_hole, spiny_whitefly, yellow_dragon, yellow_leaves. |
| Images per class: |
| - citrus_canker: 588 |
| - citrus_greening: 254 |
| - citrus_mealybugs: 603 |
| - die_back: 642 |
| - foliage_damaged: 632 |
| - healthy_leaf: 547 |
| - powdery_mildew: 598 |
| - shot_hole: 560 |
| - spiny_whitefly: 672 |
| - yellow_dragon: 407 |
| - yellow_leaves: 310 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{emon2024multi, |
| title={Multi-format open-source sweet orange leaf dataset for disease detection, classification, and analysis}, |
| author={Emon, Yousuf Rayhan and Ahad, Md Taimur and Rabbany, Golam}, |
| journal={Data in Brief}, |
| volume={55}, |
| pages={110713}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Emon, Yousuf Rayhan; Ahad, Md Taimur; Khan, Shahrin ; Mustofa, Sumaya (2025), “Multi-format open-source sweet orange leaf dataset for disease detection, classification, and analysis.”, Mendeley Data, V2, doi: 10.17632/f7cr74mwpj.2 |
