| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': conf |
| '1': conf+ |
| '2': esca |
| '3': fd |
| - name: grape_variety |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 792632284 |
| num_examples: 611 |
| download_size: 792664214 |
| dataset_size: 792632284 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - image-classification |
| size_categories: |
| - n<1K |
| --- |
| # Grapevine Disease Classification |
|
|
| A dataset for disease classification of grapevines. The dataset contains 611 images across 4 classes and 4 grape varieties: |
| Images per class: |
| - conf: 199 |
| - conf+: 77 |
| - esca: 107 |
| - fd: 228 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{tardif2023expertized, |
| title={An expertized grapevine disease image database including five grape varieties focused on Flavescence dor{\'e}e and its confounding diseases, biotic and abiotic stresses}, |
| author={Tardif, Malo and Amri, Ahmed and Deshayes, Aymeric and Greven, Marc and Keresztes, Barna and Fontaine, Ga{\"e}l and Sicaud, Laetitia and Paulhac, Laetitia and Bentejac, Sophie and Da Costa, Jean-Pierre}, |
| journal={Data in Brief}, |
| volume={48}, |
| pages={109230}, |
| year={2023}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Tardif, Malo (2023), “An expertized grapevine disease image database focused on Flavescence dorée and its confounding diseases”, Mendeley Data, V2, doi: 10.17632/3dr9r3w3jn.2 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
