OpenCV bindings for Matlab - Readme

malcolm.reynolds@gmail.com
----------------------

This is a simple set of bindings for a *very* small subset of OpenCV functionality so
that it can be called from Matlab. I wrote these bindings for just the bits of OpenCV I 
needed for a specific project, which was mainly the Random Forest implementation. If you
need bindings for lots of other parts of the system, it's probably time to switch to Python
like I'm doing.

Anyway, the included Makefile works on OS X (64 bit) and with suitable modifications to the
configuration to the bits at the top I'm sure it can be made to work for any platform that 
matlab runs on.

Requirements:

* Matlab: Works on 2010rb and 2009aSV. In principle any version that includes MEX support
  should be fine.
* OpenCV: Tested on OpenCV 2.x. This library seems to get reorganised fairly frequently
  so some headers / includes might need changing at some point...
* C++ compiler: tested with GCC, but whatever Matlab wraps with the 'mex' command should be fine.

Matlab needs to be installed such that you can type "mex" to run it in a terminal. The actual
file should be in your matlab installation in the bin/ directory.

OpenCV's libraries and include files must be given to the makefile - I use a shell script to print
out the locations of this (in -I/some/include/directory -L/some/library/directory -lfirstlibrary
-lsecondlibrary format), which is the `opencv-comp` in the makefile. You can just manually enter
them here too if you like, but if you ever do any other opencv compilation on the command line the
shell script is handy.

One you're compiled you should have a bunch of .mexw32 / .mewx64 / .mexmaci64 / whatever files
sitting in the same directory as the source files. Point Matlab's PATH to them and you're good to
go.


Disclaimer
--------------
This was written for a single project, and it worked for me. No guarantees - I saw some particularly
gnarly crashing bugs on Windows XP 32 bit when I ported it over, but I simply do not have the inclination
to find out what's going on there. I was planning to expand this to cover more opencv functionality, but
I am switching my workflow to Python/Scipy/Numpy for the future. However, this is here just in case anyone
wants simple, high performance, reliable random forests in matlab.

All complaints to malcolm.reynolds@gmail.com - if you use this for something useful, I would love to hear
about it.