Obtain runtimes to execute OpenCL™ applications on Intel® processors.
The Intel® Integrated Native Developer Experience (Intel® INDE) suite has been discontinued.
Webinar - Learn tips & tricks for adding hardware acceleration to your media code - get fast performance & quality for media applications.
You can use LibRealSense and OpenCV* to stream RGB and depth data from your connected Intel® RealSense™ camera. This tutorial and code sample shows how to do this, based on the Ubuntu* operating system. In the end you will have a nice starting point where you use this code base to build upon to create your own LibRealSense / OpenCV applications.
This article shows you how you can use LibRealSense and OpenCV to stream RGB and depth data. In the end you will have a nice starting point where you use this code base to build upon to create your own LibRealSense / OpenCV applications.
Intel offers a range of hardware options for IoT deployments. Computing power progresses in order from the Intel Atom® processor,to the Intel® Core™ processor and finally to the Intel® Xeon® processor. As IoT demand drives increases in data volume, a more powerful processor is required, as well as additional storage.
Celebrating the FIRST EVER Global IoT DevFest! Registration is Still Open to Watch Replays! ATTENTION – There’s still time to sign up for the latest edition of our Intel Global IoT DevFest II on Nov 7-8th 2017.
In support of computer vision development efforts, we've created a GitHub* repository of twelve computer vision code samples. These code samples are a good starting point for developers who wish to develop more robust computer vision and analytic solutions. We use the Retail, Digital Signage market in these examples but the technology can be used in a variety of different markets.
Select hardware accelerators from Intel for your computer vision application.