Datasets:

Project-AgML
/

grapevine_esca_classification

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

@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.