Skip to content
OpenPIV is an open source Particle Image Velocimetry analysis software written in Python and Cython
Jupyter Notebook Python Other
Branch: master
Clone or download

Latest commit

Fetching latest commit…
Cannot retrieve the latest commit at this time.


Type Name Latest commit message Commit time
Failed to load latest commit information.
openpiv Update process.pyx Feb 12, 2020
recipe Delete conda_build_config.yaml Dec 7, 2019
synimage adopted SIG Oct 9, 2019
.gitignore updated readme and gitignore Jul 13, 2019
.travis.yml Update .travis.yml Dec 6, 2019
CHANGES.txt check-manifest suggests to add these two files Aug 9, 2015
INSTALL complete reshufle of the tutorials Jul 10, 2019
LICENSE.txt fixed Dec 5, 2019
MILESTONES Modified MILESTONES file Apr 27, 2011 Update Dec 7, 2019
TODO v 0.12 updates, new package on PyPI using Jun 27, 2014
appveyor.yml Update appveyor.yml Dec 6, 2019
pyproject.toml Update pyproject.toml Dec 7, 2019 Update Dec 7, 2019


Build Status Build status DOI

Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge

OpenPIV consists in a Python and Cython modules for scripting and executing the analysis of a set of PIV image pairs. In addition, a Qt graphical user interface is in development, to ease the use for those users who don't have python skills.


The OpenPIV python version is still in beta state. This means that it still might have some bugs and the API may change. However, testing and contributing is very welcome, especially if you can contribute with new algorithms and features.

Development is currently done on a Linux/Mac OSX environment, but as soon as possible Windows will be tested. If you have access to one of these platforms please test the code.

Test it without installation

Click the link - thanks to BinderHub, Jupyter and Conda you can now get it in your browser with zero installation: Binder


Use PyPI:

pip install cython numpy 
pip install openpiv --pre

--pre because sometimes we push pre-releases

Or conda

conda install -c conda-forge openpiv

To build from source

Download the package from the Github: or clone using git

git clone

Using distutils create a local (in the same directory) compilation of the Cython files:

python build_ext --inplace

Or for the global installation, use:

python install 

Latest developments

Latest developments go into @alexlib repository


The OpenPIV documentation is available on the project web page at

Demo notebooks

  1. Tutorial Notebook 1
  2. Tutorial notebook 2
  3. Dynamic masking tutorial
  4. Multipass tutorial with WiDiM
  5. Multipass with Windows Deformation


  1. Alex Liberzon
  2. Roi Gurka
  3. Zachary J. Taylor
  4. David Lasagna
  5. Mathias Aubert
  6. Pete Bachant
  7. Cameron Dallas
  8. Cecyl Curry
  9. Theo Käufer

Copyright statement: is a Python version of smoothn.m originally created by D. Garcia [], written by Prof. Lewis and available on Github []. We include a version of it in the openpiv folder for convenience and preservation. We are thankful to the original authors for releasing their work as an open source. OpenPIV license does not relate to this code. Please communicate with the authors regarding their license.

You can’t perform that action at this time.