Project-AgML/potato_leaf_disease_classification

1---2configs:3- config_name: default4  data_files:5  - split: train6    path: data/train-*7license: cc-by-4.08task_categories:9- image-classification10size_categories:11- 1K<n<10K12dataset_info:13  features:14  - name: image15    dtype: image16  - name: label17    dtype:18      class_label:19        names:20          '0': Bacteria21          '1': Fungi22          '2': Healthy23          '3': Nematode24          '4': Pest25          '5': Phytopthora26          '6': Virus27  splits:28  - name: train29    num_bytes: 78725280730    num_examples: 307631  download_size: 75447981332  dataset_size: 78725280733---34 35# Potato Leaf Disease Classification36 37A dataset for disease classification of potato leaves. The dataset contains 3,076 images across 7 classes: Bacteria, Fungi, Healthy, Nematode, Pest, Phytopthora, Virus.  38Images per class:39- Bacteria: 56940- Fungi: 74841- Healthy: 20142- Nematode: 6843- Pest: 61144- Phytopthora: 34745- Virus: 53246 47This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.48 49## Citation50 51```bibtex52@article{shabrina2024novel,53  title={A novel dataset of potato leaf disease in uncontrolled environment},54  author={Shabrina, Nabila Husna and Indarti, Siwi and Maharani, Rina and Kristiyanti, Dinar Ajeng and Prastomo, Niki and others},55  journal={Data in brief},56  volume={52},57  pages={109955},58  year={2024},59  publisher={Elsevier}60}61```62 63Shabrina, 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