PhenoTrack3D can be used to track leaf organs over time, in a time-series of 3D maize plant reconstructions. Such 3D reconstructions can be obtained from sets of RGB images with the Phenomenal pipeline (https://github.com/openalea/phenomenal)
- Daviet Benoit ([email protected])
- Fournier Christian ([email protected])
- Pradal Christophe ([email protected])
Our code is released under Cecill-C (https://cecill.info/licences/Licence_CeCILL_V1.1-US.txt) licence. See LICENSE file for details.
install dependencies with conda:
conda create -n phenotrack -c conda-forge -c openalea3 openalea.phenomenal skan=0.9
conda activate phenotrack
Clone repo and run setup
git clone https://github.com/openalea/phenotrack3d.git
cd phenotrack3d
If you use PhenoTrack3D to your research, cite:
Daviet, B., Fernandez, R., Cabrera-Bosquet, L. et al. PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time. Plant Methods 18, 130 (2022). https://doi.org/10.1186/s13007-022-00961-4
@article {daviet22,
author = {Daviet, Benoit and Fernandez, Romain and Cabrera-Bosquet, Lloren{\c c} and Pradal, Christophe and Fournier, Christian},
title = {PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time},
elocation-id = @article{daviet2022phenotrack3d,
title={PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time},
author={Daviet, Benoit and Fernandez, Romain and Cabrera-Bosquet, Lloren{\c{c}} and Pradal, Christophe and Fournier, Christian},
journal={Plant Methods},
volume={18},
number={1},
pages={1--14},
year={2022},
publisher={Springer}
}