Datasets:

Project-AgML
/

strawberry_runner_segmentation

dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype: image
    - name: split
      dtype: string
  splits:
    - name: train
      num_bytes: 34450965
      num_examples: 3345
  download_size: 249337909
  dataset_size: 34450965
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc0-1.0
task_categories:
  - image-segmentation
size_categories:
  - 1K<n<10K

Strawberry Runner Segmentation

A dataset for semantic segmentation of strawberry runners. The dataset contains 3,345 images with pixel-level mask annotations.

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

The original train/test/val split has been preserved in the split column.

Citation

@article{zhou2025deep,
  title={Deep learning for strawberry runner detection integrating ground and aerial imaging},
  author={Zhou, Xue and Wang, Xu and Ji, Liyike and Daggubati, Santhi and Shen, Kai and Whitaker, Vance M.},
  journal={Smart Agricultural Technology},
  volume={12},
  pages={101290},
  year={2025},
  publisher={Elsevier}
}

Zhou, Xue; Wang, Xu; Whitaker, Vance et al. (2025). Ground and aerial imagery dataset for strawberry breeding trials: Training deep learning models for runner detection and segmentation [Dataset]. Dryad. https://doi.org/10.5061/dryad.bzkh189nw

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