| --- |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': esca |
| '1': healthy |
| splits: |
| - name: train |
| num_bytes: 1078870058 |
| num_examples: 1770 |
| download_size: 943817178 |
| dataset_size: 1078870058 |
| 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 |
| --- |
| # Grapevine Esca Classification |
|
|
| A dataset for disease classification of grapevine leaves. The dataset contains 1,770 images across 2 classes: esca, healthy. |
| Images per class: |
| - esca: 888 |
| - healthy: 882 |
|
|
| This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{alessandrini2021grapevine, |
| title={A grapevine leaves dataset for early detection and classification of esca disease in vineyards through machine learning}, |
| author={Alessandrini, M and Rivera, R Calero Fuentes and Falaschetti, L and Pau, D and Tomaselli, V and Turchetti, C}, |
| journal={Data in Brief}, |
| volume={35}, |
| pages={106809}, |
| year={2021}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| Alessandrini, Michele; Calero Fuentes Rivera, Romel ; Falaschetti, Laura; Pau, Danilo; Tomaselli, Valeria; Turchetti, Claudio (2021), “ESCA-dataset”, Mendeley Data, V1, doi: 10.17632/89cnxc58kj.1 |
|
|
| *This dataset was reformatted from its original format to match HuggingFace standards.* |
