Datasets:

Project-AgML
/

chitrak_leaf_disease_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Dried
            '1': Healthy
            '2': Unhealthy
    - name: leaf_count
      dtype: string
    - name: leaf_side
      dtype: string
  splits:
    - name: train
      num_bytes: 2528902939
      num_examples: 10660
  download_size: 2125190071
  dataset_size: 2528902939
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 10K<n<100K

Chitrak Leaf Disease Classification

A dataset for disease classification of Chitrak Leaves. The dataset contains 10,660 images across 3 classes: dried, healthy, and unhealthy.

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

Citation

@article{patil2024plumbago,
  title={Plumbago Zeylanica (Chitrak) leaf image dataset: a comprehensive collection for botanical studies, herbal medicine research, and environmental analyses},
  author={Patil, Kailas and Suryawanshi, Yogesh and Dhoka, Amit and Chumchu, Prawit},
  journal={Data in Brief},
  volume={52},
  pages={109929},
  year={2024},
  publisher={Elsevier}
}

Dhoka, Amit; Suryawanshi, Yogesh; PATIL, Kailas (2023), “Plumbago Zeylanica (Chitrak) Leaf Image Dataset”, Mendeley Data, V2, doi: 10.17632/twpv7hhmgb.2

This dataset was reformatted from its original format to match HuggingFace standards.