I want to make a image recognition program for rasberry pi. I started in OpenCV, however just discovered OpenVX, a hardware accelerator for OpenCV. Being that speed and efficiency are important on an embedded system I'm curious on how to take advantage of this new technology. Do I have to port over my code to OpenVX or is it a program that runs in conjunction with my OpenCV program?
OpenCV vs OpenVX for embedded system
14.7k views Asked by KamikazeStyle AtThere are 3 answers

Just to update this question with a bit more relevant info a year later for 2015. OpenVX is absolutely, definitely not now vapourware:-) There is a reference sample implementation and drivers are being rolled out by manufacturers for other chipsets.
And, whereas it is not yet fully accelerated, you can indeed get OpenVX onto a Raspberry Pi - as per the instructions here (which includes discussion/links on possibly making it faster). Bottom line with the Pi is that image processing is intensive irrespective of the libraries used and ultimately dictated by how "accessible" the Broadcom GPU chip is...

As mentioned on OpenVX's main page, OpenVX has a new role now. (compare to clifford 's answer at year 2014)
Now, OpenVX is targeted at low-power, real-time applications, we can't find the picture which implies OpenVX is a base component of Opencv any more either.
An compare chart pointed out their different scope at present:
- OpenCV: Very wide 1000s of imaging and vision functions Multiple camera APIs/interface
- OpenVX: Tight focus on core hardware accelerated functions for mobile vision – but extensible Uses external/native camera API
From the project's own website:
... which seems pretty clear to me - you can use OpenVX directly or as support for OpenCV.
However it is also clear that OpenVX is currently vapourware - it exists only as a specification and a set of header files (no actual library).
The above quote is from a helpfully undated page, but was originally in a press-release of November 19th 2013. So it may now be near completion as a specification, but perhaps a long way from code complete.
Also to be used there will need to be OpenVX support for RPi's GPU which may be a bigger barrier to use on RPi until some third party implements it.