Apple

Detection of apple based on YOLOv4 model

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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.