| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - 10K<n<100K |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Cerscospora |
| '1': Healthy |
| '2': Leaf_rust |
| '3': Miner |
| '4': Phoma |
| splits: |
| - name: train |
| num_bytes: 1923533109 |
| num_examples: 58549 |
| download_size: 1840319580 |
| dataset_size: 1923533109 |
| --- |
| |
| # Arabica Coffee Leaf Disease Classification |
|
|
| A dataset for disease classification of Arabica Coffee Leaf. The dataset contains 58,549 images across 5 classes: Cerscospora, Healthy, Leaf_rust, Miner, Phoma. |
| Images per class: |
| - Cerscospora: 7,681 |
| - Healthy: 18,983 |
| - Leaf_rust: 8,336 |
| - Miner: 16,978 |
| - Phoma: 6,571 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{jepkoech2021arabica, |
| title={Arabica coffee leaf images dataset for coffee leaf disease detection and classification}, |
| author={Jepkoech, Jennifer and Mugo, David Muchangi and Kenduiywo, Benson K and Too, Edna Chebet}, |
| journal={Data in brief}, |
| volume={36}, |
| pages={107142}, |
| year={2021}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Jepkoech, jennifer; Kenduiywo, Benson; Mugo, David; Chebet, Edna (2021), “JMuBEN”, Mendeley Data, V1, doi: 10.17632/t2r6rszp5c.1 |
| Jepkoech, Jennifer; Mugo, David; Kenduiywo, Benson; Chebet, Edna (2021), “JMuBEN2”, Mendeley Data, V1, doi: 10.17632/tgv3zb82nd.1 |
|
|
