Rice High Throughput Phenotyping Computer Vision Toolkit
Project description
phenocv
Introduction
phenocv is a toolkits for rice high-throught phenotyping using computer vision.
phenocv is still in early development stage, and more features will be added in the future.
For label-studio semi-automatic annotation, please refer to playground.
For mmdetection training, please refer to mmdetection.
For yolo training, please refer to Ultralytics.
Support for mmdetection and label-studio will be added in the future.
Installation
Before install the package, make sure you have installed pytorch and install in the python environment with python>=3.8.
Install with pip:
pip install phenocv
Install in editable mode, allow changes to the source code to be immediately available:
git clone https://github.com/r1cheu/phenocv.git
cd phenocv
pip install -e .
Tutorial
| Getting Start |  |
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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}
}
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