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Project-AgML/potato_leaf_disease_classification

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… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/potato_leaf_disease_classification.

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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

bibtex

@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