Datasets:

Project-AgML
/

potato_leaf_disease_classification

configs:
  - config_name: default
    default: true
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Bacteria
              '1': Fungi
              '2': Healthy
              '3': Nematode
              '4': Pest
              '5': Phytopthora
              '6': Virus
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

Potato Leaf Disease Classification

A dataset for disease classification of potato leaves. The dataset contains 3,076 images across 7 classes: Bacteria, Fungi, Healthy, Nematode, Pest, Phytopthora, Virus.
Images per class:

Bacteria: 569
Fungi: 748
Healthy: 201
Nematode: 68
Pest: 611
Phytopthora: 347
Virus: 532

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{shabrina2024novel,
  title={A novel dataset of potato leaf disease in uncontrolled environment},
  author={Shabrina, Nabila Husna and Indarti, Siwi and Maharani, Rina and Kristiyanti, Dinar Ajeng and Prastomo, Niki and others},
  journal={Data in brief},
  volume={52},
  pages={109955},
  year={2024},
  publisher={Elsevier}
}

Shabrina, Nabila Husna; Indarti, Siwi; Maharani, Rina; Kristiyanti, Dinar Ajeng; Irmawati, Irmawati; Prastomo, Niki; M, Tika Adillah (2023), “Potato Leaf Disease Dataset in Uncontrolled Environment”, Mendeley Data, V1, doi: 10.17632/ptz377bwb8.1