https://github.com/hereariim/deep-napari

This is a training tutorial to learn how to integrate deep learning model into napari plugin from scratch
https://github.com/hereariim/deep-napari

Last synced: 12 months ago
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This is a training tutorial to learn how to integrate deep learning model into napari plugin from scratch

• Host: GitHub
• URL: https://github.com/hereariim/deep-napari
• Owner: hereariim
• Created: 2023-10-18T09:14:47.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-11-20T10:34:39.000Z (over 2 years ago)
• Last Synced: 2023-11-20T11:38:47.625Z (over 2 years ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 50.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

          
# DEEP NAPARI : Napari as a tool for deep learning project management

![Alt text](images-credit/mifobio2023.png)

This document is part of the Hands on session of the MIFOBIO 2023. The aim of this document is to show the value of napari in Deep learning project managemeent

It is not intended to be a training session. That would require a lot of time to fully explore napari. The Hands on session for napari is a three-part discovery activity:

- Introducing the napari visualisation tools

- Getting started the design of a plugin

- Getting started the development of this plugin by adding a widget

## Prerequisites tools for this session Hands On

- Operating system : Windows

- [Anaconda distribution](https://www.anaconda.com/download)

- [Napari](https://napari.org/stable/tutorials/fundamentals/installation.html) as **bundle app** and **python library**

- [VS Code](https://code.visualstudio.com/)

- [Git](https://git-scm.com/download/win) (Standalone Installer)

- In conda environment napari : 

    * Tensorflow (v2.11.0)

    * opencv-python

    * numpy

    * skimage

## Useful links

- [Finding and installing a napari plugin](https://napari.org/stable/plugins/find_and_install_plugin.html) : Install napari

- [Your First Plugin](https://napari.org/stable/plugins/first_plugin.html) : Design your plugin

- [Napari hub](https://www.napari-hub.org/) : Napari hub is a service of the Chan Zuckerberg Initiative in collaboration with Napari. Here, you can discover, install, and share napari plugins 

- [Image.sc](https://forum.image.sc/tag/napari) : Help or support requests send to napari community partner

- [Github issues](https://github.com/napari/napari/issues) : Bug reports

- [FAQ](https://www.napari-hub.org/faq) : Reccurent questions about napari, napari-hub and the way for building and sharing plugins

Video tutorial (in french) : 

- [Installer NAPARI et faire son premier plugin](https://www.youtube.com/watch?v=lMEVJxIlkXw&ab_channel=ImHorPhenBioimagingresearchgroup)

- [NAPARI Plugin for deep segmentation and manual correction](https://www.youtube.com/watch?v=Wzgl1aDT504&t=872s&ab_channel=ImHorPhenBioimagingresearchgroup)

## Authors

Herearii Metuarea, Engineer at Université d'Angers

## Other contributors

Imhorphen team at Université d'Angers:

* David Rousseau, Full Professor, Université d'Angers

* Pejman Rasti, Assistant professor, Université d'Angers

* Valentin Gilet, PhD, Université d'Angers

## Contribution

This workshop is a part of MIFOBIO 2023 offered by Imhorphen team. It was written in the context of PHENET project.