Datasets:

Project-AgML
/

PhenoBench_segmentation

dataset_info:
  features:
    - name: image
      dtype: image
    - name: mask
      dtype: image
    - name: date
      dtype: string
    - name: plant_id
      dtype: string
  splits:
    - name: train
      num_bytes: 6080410063
      num_examples: 2179
  download_size: 5667035818
  dataset_size: 6080410063
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
license: cc-by-sa-4.0
task_categories:
  - image-segmentation
size_categories:
  - 1K<n<10K

Phenobench Segmentation

The PhenoBench_segmentation dataset provides real RGB images and pixel-level segmentation masks for agricultural plant phenotyping. It was collected using standard RGB cameras in typical field and controlled agricultural environments, capturing diverse plant structures and growth stages across multiple phenological stages. The dataset contains 2,179 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{weyler2024phenobench,
  title={Phenobench: A large dataset and benchmarks for semantic image interpretation in the agricultural domain},
  author={Weyler, Jan and Magistri, Federico and Marks, Elias and Chong, Yue Linn and Sodano, Matteo and Roggiolani, Gianmarco and Chebrolu, Nived and Stachniss, Cyrill and Behley, Jens},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={46},
  number={12},
  pages={9583--9594},
  year={2024},
  publisher={IEEE}
}

https://www.phenobench.org/dataset.html

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