Datasets:

Project-AgML
/

soybean_damage_classification

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': Broken
            '1': Immature
            '2': Intact
            '3': Skin-damaged
            '4': Spotted
  splits:
    - name: train
      num_bytes: 89884943
      num_examples: 5513
  download_size: 90329805
  dataset_size: 89884943
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

Soybean Damage Classification

A dataset for damage classification of soybean seeds. The dataset contains 5,513 images across 5 classes: Broken, Immature, Intact, Skin-damaged, Spotted.
Images per class:

Broken: 1,002
Immature: 1,125
Intact: 1,201
Skin-damaged: 1,127
Spotted: 1,058

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

Citation

@article{lin2023soybean,
  title={Soybean image dataset for classification},
  author={Lin, Wei and Fu, Youhao and Xu, Peiquan and Liu, Shuo and Ma, Daoyi and Jiang, Zitian and Zang, Siyang and Yao, Heyang and Su, Qin},
  journal={Data in Brief},
  volume={48},
  pages={109300},
  year={2023},
  publisher={Elsevier}
}

Lin, Wei; Fu, Youhao; Xu, Peiquan; Liu, Shuo; Ma, Daoyi; Jiang, Zitian; zang, siyang; Yao, Heyang; Su, Qin (2023), “Soybean Seeds”, Mendeley Data, V6, doi: 10.17632/v6vzvfszj6.6

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