Qu is an attempt to make the full deep learning workflow more interactive by providing a user interface that abstracts all steps from ground truth generation and curation to training and prediction.
Qu is released under the terms of the Apache License version 2.0 (see LICENSE). All libraries used by Qu have their own licenses.
Create an environment and install napari
Install napari as explained in the official documentation. It is recommended to create a dedicated environment:
conda create -y -n napari-env python=3.9
conda activate napari-env
pip install "napari[all]"
The next steps assume that we activated the
It is recommented to install PyTorch using the selection tool on https://pytorch.org/get-started/locally/#start-locally. This will ensure that PyTorch is installed with GPU acceleration and with the correct version of the CUDA libraries.
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
Adapt the example as needed.
Qu cannot be installed from the napari-hub yet. Instead, clone Qu and install it manually as a napari plug in as follows:
git clone https://github.com/aarpon/qu
pip install -e .
Note: Qu still uses the first generation
napari-plugin-engine: a migration to
Qu can be started from the
Plugins menu. The Qu main menu can be opened right-clicking on the Qu main widget.
Demos menu, choose
Segmentation dataset: 2|3 classes or
Note: Qu cannot be installed from the napari-hub yet.
Detailed instructions will follow soon.