Datasets:
File size: 1,479 Bytes
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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.* |