• 04/03/2020
  • Public Content
Contents

Computer Vision Application Development Flow Using OpenVX*

The core of an OpenVX-based application is a graph with computer vision kernels as processing nodes. The typical steps for application development are as follows:
  1. Build an OpenVX* graph for all or some of your computer vision pipeline using the supplied standard kernels and extensions. Standard OpenVX code can be written with any code editor.
  2. Add your own algorithms to the processing pipeline. Code may be wrapped as OpenVX
    user kernels
    (section Wrapping User Code as OpenVX* User Kernels) or
    custom kernels
    (see the Intel's Extensions to the OpenVX* API: OpenCL(TM) Custom Kernels section).
  3. Integrate the OpenVX* Graph code with code written in other frameworks such as OpenCV.

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804