| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: mask |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: float64 |
| - name: categories |
| list: |
| class_label: |
| names: |
| '0': healthy |
| '1': red_spider_mite |
| '2': rust_level_1 |
| '3': rust_level_2 |
| '4': rust_level_3 |
| '5': rust_level_4 |
| - name: segmentation |
| list: |
| list: |
| list: float64 |
| splits: |
| - name: train |
| num_bytes: 676707599 |
| num_examples: 1560 |
| download_size: 1580509740 |
| dataset_size: 676707599 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| - image-segmentation |
| size_categories: |
| - 1K<n<10K |
| --- |
| # RoCoLe Disease Detection |
|
|
| A dataset for detection of Robusta coffee leaf diseases. The dataset contains 1,560 images with 1,560 bounding box annotations across 6 categories, as well as segmentation masks. |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{parraga2019rocole, |
| title={RoCoLe: A robusta coffee leaf images dataset for evaluation of machine learning based methods in plant diseases recognition}, |
| author={Parraga-Alava, Jorge and Cusme, Kevin and Loor, Ang{\'e}lica and Santander, Esneider}, |
| journal={Data in brief}, |
| volume={25}, |
| pages={104414}, |
| year={2019}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Parraga-Alava, Jorge; Cusme, Kevin; Loor, Angélica; Santander, Esneider (2019), “RoCoLe: A robusta coffee leaf images dataset ”, Mendeley Data, V2, doi: 10.17632/c5yvn32dzg.2 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
