Datasets:

Project-AgML
/

soybean_harvest_damage_segmentation

dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype: image
  splits:
    - name: train
      num_bytes: 330125553
      num_examples: 800
  download_size: 330164111
  dataset_size: 330125553
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-4.0
task_categories:
  - image-segmentation
size_categories:
  - n<1K

Soybean Harvest Damage Segmentation

A dataset for semantic segmentation of damage during harvesting of soybeans. The dataset contains 800 images with pixel-level mask annotations.

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

Citation

@article{chen2024dataset,
  title={A dataset of the quality of soybean harvested by mechanization for deep-learning-based monitoring and analysis},
  author={Chen, Man and Jin, Chengqian and Ni, Youliang and Yang, Tengxiang and Xu, Jinshan},
  journal={Data in Brief},
  volume={52},
  pages={109833},
  year={2024},
  publisher={Elsevier}
}

Chen, Man (2023), “Mechanical-harvest Soybean Images Dataset”, Mendeley Data, V2, doi: 10.17632/hwdtghttp7.2

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