---
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

```bibtex
@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.*