Rice High Throughput Phenotyping Computer Vision Toolkit
Project description
phenocv
Introduction
phenocv is a toolkits for handling preporecess and postprocess for rice high-throught phenotyping images.
phenocv is still under development. We will keep refactoring the code and add more features. Any contribution is welcome. If you encounter any problems when using phenocv, please feel free to raise an issue
For label-studio semi-automatic annotation, please refer to playground.
For mmdetection training, please refer to mmdetection.
For yolo training, please refer to Ultralytics.
Installation
Pip install the phenocv package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.
Install for developer
if you wish to modify the code, you can install phenocv in developer mode.
git clone https://github.com/r1cheu/phenocv.git
cd phenocv
pip install -e .
License
This project is released under the AGPL-3.0 license.
Citation
If you find this project useful in your research, please consider cite:
@misc{2023phenocv,
title={Rice high-throught phenotyping computer vision toolkits},
author={RuLei Chen},
howpublished = {\url{https://github.com/r1cheu/phenocv}},
year={2023}
}
Project details
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