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dataset_info:
config_name: raw
features:
- name: plant_id
dtype: string
- name: points
dtype:
array2_d:
shape:
- -1
- 3
dtype: float32
- name: mask
dtype:
array2_d:
shape:
- -1
- 1
dtype: int32
- name: mask_2
dtype:
array2_d:
shape:
- -1
- 1
dtype: int32
splits:
- name: train
num_bytes: 7881680104
num_examples: 126
download_size: 5293657341
dataset_size: 7881680104
configs:
- config_name: raw
default: true
data_files:
- split: train
path: raw/train-*
license: cc-by-4.0
---
# Pheno4D Point Cloud Segmentation
A dataset for point cloud semantic segmentation of maize and tomato plants. The dataset contains 126 labeled 3D scans across two species, tomato (single label scheme) and maize (dual label scheme: collar-based and tip-based organ boundaries), with per-point labels identifying plant organs (e.g. stem, leaf).
Each sample includes:
- `points`: an (N, 3) array of x, y, z point coordinates, N varies per scan
- `mask`: an (N, 1) array of per-point organ labels (primary label scheme)
- `mask_2`: an (N, 1) array of per-point organ labels (secondary label scheme, maize only; -1 where not applicable)
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
**Note:** this is AgML's first point cloud dataset. Naming follows the `mask` convention used for 2D semantic segmentation datasets in this organization, adapted for 3D point data (stored as `Array2D` with a dynamic first dimension rather than image masks).
## Citation
```bibtex
@article{schunck2021pheno4d,
title={Pheno4D: A spatio-temporal dataset of maize and tomato plant point clouds for phenotyping and advanced plant analysis},
author={Schunck, David and Magistri, Federico and Rosu, Radu Alexandru and Corneli{\ss}en, Anne and Chebrolu, Nived and Paulus, Stefan and L{\'e}on, Jens and Behnke, Sven and Stachniss, Cyrill and Kuhlmann, Heiner and Klingbeil, Lasse},
journal={PLOS ONE},
volume={16},
number={8},
pages={1--18},
year={2021},
publisher={Public Library of Science},
doi={10.1371/journal.pone.0256340}
}
```
Original dataset: https://www.ipb.uni-bonn.de/data/pheno4d/
*This dataset was reformatted to match HuggingFace standards as part of AgML's point cloud dataset support.* |