This fork modifies Deepak Pathak's (@pathak22)original implementation so that it can properly build on Windows. Based on the OS, setup.py
sets the proper compiler flags. If setting up on Windows, make sure the Visual C++ build tools are on your path (see below).
This fork also picks up changes made by Michael Williams (@mpwillia). See here for details.
This is a Python wrapper for Ce Liu's C++ implementation of Coarse2Fine Optical Flow. It's super fast and accurate optical flow method based on Coarse2Fine warping method from Thomas Brox. This python wrapper has minimal dependencies, and it also eliminates the need for C++ OpenCV library. For real time performance, one can additionally resize the images to a smaller size.
For more information about Deepak's wrapper, see here.
First, make sure the cython
package has been installed as part of your virtualenv
or conda
environment.
Then, to install this version of pyflow
, use pip
as follows:
(dlwin36tfvos) pferr@MSI E:\repos
$ pip install git+https://github.com/philferriere/pyflow.git
Collecting git+https://github.com/philferriere/pyflow.git
Cloning https://github.com/philferriere/pyflow.git to c:\users\pferr\appdata\local\temp\pip-amvdc0ec-build
Installing collected packages: pyflow
Running setup.py install for pyflow ... done
Successfully installed pyflow-1.0
Note: If distutils
uses a different compiler than cl.exe
, modify its configuration file as follows:
(dlwin36tfvos) pferr@MSI E:\repos
$ cat %CONDA_PREFIX%\Lib\distutils\distutils.cfg
[build]
compiler=msvc
For this package to build, you must have the Visual C++ 2015 build tools on your path. If you don't, install them from here:
Then, run visualcppbuildtools_full.exe
and select default options: