Apple
Detection of apple based on YOLOv4 model
Detection of apple based on YOLOv4 model
This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.
Installation¶
First, please note that this module only works on a Linux Ubuntu system. Indeed, the launch of the YOLO module is a command that is executed on a Linux Ubuntu system.
Before you can operate the module, you must install the napari-apple
module and Darknet on your machine.
Instruction for napari-module¶
You can install napari-apple
via pip:
pip install napari-apple
To install latest development version :
pip install git+https://github.com/hereariim/napari-apple.git
Instruction Darknet¶
Darknet is the module where the pre-trained YOLO model is located. You can install Darknet by running this command:
git clone https://github.com/pjreddie/darknet
cd darknet
make
When Darknet is installed, you have to put the weights of the apple detection model in the cfg subfolder. You find the weights in the weight-darknet folder.
Contributing¶
Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.
License¶
Distributed under the terms of the BSD-3 license, "napari-apple" is free and open source software
Issues¶
If you encounter any problems, please file an issue along with a detailed description.
Version:
- 0.0.2
Last updated:
- 08 December 2022
First released:
- 23 June 2022
License:
- BSD-3-Clause
Supported data:
- Information not submitted
Plugin type:
Open extension:
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GitHub activity:
- Stars: 2
- Forks: 0
- Issues + PRs: 0