Project-AgML/grape_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': Bacterial Leaf Spot21          '1': Downy Mildew22          '2': Healthy Leaves23          '3': Powdery Mildew24  splits:25  - name: train26    num_bytes: 2311572327    num_examples: 272628  download_size: 2603685929  dataset_size: 2311572330---31 32# Grape Leaf Disease Classification33 34A dataset for image classification of Grape Leaf Disease.  The dataset contains 2,726 images across 4 classes: Bacterial Leaf Spot, Downy Mildew, Healthy Leaves, Powdery Mildew.35Images per class:36- Bacterial Leaf Spot: 10037- Downy Mildew: 96638- Healthy Leaves: 1,25439- Powdery Mildew: 40640 41This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.42 43## Citation44 45```bibtex46@article{dharrao2025grapes,47  title={Grapes leaf disease dataset for precision agriculture},48  author={Dharrao, Madhuri and Zade, Nilima and Kamatchi, R and Sonawane, Rakesh and Henry, Rabinder and Dharrao, Deepak},49  journal={Data in Brief},50  volume={61},51  pages={111716},52  year={2025},53  publisher={Elsevier}54}```55 56Dharrao, Madhuri; Dharrao, Deepak; Sonawane, Rakesh; zade, Nilima (2025), “Niphad Grape Leaf Disease Dataset (NGLD)”, Mendeley Data, V5, doi: 10.17632/8nnd2ypcv3.5