Datasets:
File size: 1,891 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: split
dtype: string
- name: PipeID
dtype: string
- name: Position
dtype: string
- name: timestamp
dtype: string
splits:
- name: train
num_bytes: 69854775
num_examples: 438
download_size: 69911174
dataset_size: 69854775
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-segmentation
size_categories:
- n<1K
---
# Deeprootlab Root Segmentation
This dataset provides real RGB images of plant root systems captured in a controlled laboratory environment for agricultural root phenotyping. It focuses on root segmentation tasks, offering high-quality imagery suitable for developing semantic segmentation models in agricultural research contexts. The dataset contains 438 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
```bibtex
@article{han2026deep,
title={Deep roots through time and crops: insight from five seasons at DeepRootLab},
author={Han, Eusun and Cl{\'e}ment, Corentin and Czaban, Weronika and Smith, Abraham George and Dresb{\o}ll, Dorte Bodin and Thorup-Kristensen, Kristian},
journal={New Phytologist},
volume={250},
number={4},
pages={2670--2688},
year={2026},
publisher={Wiley Online Library}
}
```
Han, E., Clément, C., Czaban, W., Smith, A. G., Dresbøll, D. B., & Thorup-Kristensen, K. (2025). Dataset used in "Five seasons with DeepRootLab: A unique facility for easier deep root research in the field" [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.15213661
*This dataset was reformatted from its original format to match HuggingFace standards.*
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