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Pure Python optical flow: Horn-Schunck

Project description

https://zenodo.org/badge/DOI/10.5281/zenodo.1043971.svg https://travis-ci.org/scivision/pyoptflow.svg?branch=master https://coveralls.io/repos/github/scivision/pyoptflow/badge.svg?branch=master https://ci.appveyor.com/api/projects/status/9iv32q84vd3gbdde?svg=true Python versions (PyPI) Distribution format (PyPI) Maintainability

Optical Flow: Horn-Schunck

Python implementation of optical flow estimation using only the Scipy stack for:

  • Horn Schunck

Lucas-Kanade is also possible in the future, let me know if you’re interested in Lucas Kanade.

Install

Requires Python >= 3.6:

pip install -e .

optionally, to run self-tests:

pip install -e .[tests]

pytest -v

Examples

The program scripts expect <directory> <glob pattern> It uses [imageio](https://imageio.github.io/) to load a very wide varity of images and video.

Box

python HornSchunck.py data/box box*.bmp

Office

all time steps:

python HornSchunck.py data/office office*.bmp

or just the first 2 time steps:

python HornSchunck.py data/office office.[0-2].bmp

Rubic

python HornSchunck.py data/rubic rubic*.bmp

Sphere

python HornSchunck.py data/sphere sphere*.bmp

Comparision with Matlab Computer Vision toolbox

In Matlab directory, similar method in Octave and a comparison plot using Matlab Computer Vision toolbox.

Project details


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Filename, size & hash SHA256 hash help File type Python version Upload date
pyoptflow-1.3.0-py3-none-any.whl (9.4 kB) Copy SHA256 hash SHA256 Wheel py3 Mar 26, 2018
pyoptflow-1.3.0.tar.gz (5.7 kB) Copy SHA256 hash SHA256 Source None Mar 26, 2018

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