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Clijpy

GPU-accelerated image processing using CLIJ via pyimagej in python

Install / Use

/learn @clij/Clijpy
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

NOTE: Development of CLIJPY is on halt. Check out py-clEsperanto for OpenCL-based GPU-accelerated image processing from python.

CLIJPY

CLIPY is a bridge between CLIJ and python via pyimagej

Image

Right now, this is very preliminary.

Installation

  • Download and install Fiji

  • In Fiji, activate the clij and clij2 (experimental) update sites as described here.

  • Restart Fiji. You will need to specify an ImageJ location later in your pyimagej scripts. Specify the installation directory of Fiji.

  • Futhermore, install pyimagej as described on its github page:

conda config --add channels conda-forge
conda config --set channel_priority strict

conda create -n pyimagej pyimagej openjdk=8

conda activate pyimagej
pip install scikit-image scipy numpy matplotlib gputools

If installation of gputools doesn't work because of issues with pyopencl for Windows, consider downloading a precompiled wheel (e.g. from here ) and installing it manually:

pip install pyopencl-2019.1.1+cl12-cp37-cp37m-win_amd64.whl
pip install gputools

Example code

Examples are available in the python folder.

After installation, you can call the examples like this:

conda activate imagej
python demo.py

Please note that you need to update the path to your Fiji installation in order to make the scripts run.

Please note

It is recommended to use clij from Fiji. Python support is under development.

Back to CLIJ documentation

Imprint

View on GitHub
GitHub Stars10
CategoryDevelopment
Updated4y ago
Forks0

Languages

Jupyter Notebook

Security Score

75/100

Audited on Feb 9, 2022

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