Datasets:

Project-AgML
/

mulberry_leaf_variety_classification

configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': BlackAustralia
            '1': BlackOodTurkey
            '2': Buriram60
            '3': ChiangMai60
            '4': ChiangMaiBuriram60
            '5': Kamphaengsaeng42
            '6': RedKing
            '7': TaiwanMeacho
            '8': TaiwanStraberry
            '9': WhiteKing
  splits:
    - name: train
      num_bytes: 88392775
      num_examples: 5262
  download_size: 101694449
  dataset_size: 88392775

Mulberry Leaf Variety Classification

A dataset for variety classification of mulberry leaves. The dataset contains 5,262 images across 10 classes: BlackAustralia, BlackOodTurkey, Buriram60, ChiangMai60, ChiangMaiBuriram60, Kamphaengsaeng42, RedKing, TaiwanMeacho, TaiwanStraberry, WhiteKing.
Images per class:

BlackAustralia: 637
BlackOodTurkey: 500
Buriram60: 345
ChiangMai60: 500
ChiangMaiBuriram60: 761
Kamphaengsaeng42: 500
RedKing: 350
TaiwanMeacho: 640
TaiwanStraberry: 488
WhiteKing: 541

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

Citation

@article{choompookham2024mulberry,
  title={Mulberry leaf dataset for image classification task},
  author={Choompookham, Thipwimon and Okafor, Emmanuel and Surinta, Olarik},
  journal={Data in Brief},
  volume={54},
  pages={110281},
  year={2024},
  publisher={Elsevier}
}

Chom, thipwimon; surinta, olarik (2024), “Mulberry Leaf Dataset”, Mendeley Data, V3, doi: 10.17632/ds45yy9jrc.3