AMD OpenVX is now delivered in the MIVisionX. This content is archived for historical reference.

For the latest information on AMD OpenVX, go to https://gpuopen-professionalcompute-libraries.github.io/MIVisionX/

AMD OpenVX (AMDOVX)

AMD OpenVX (beta) is a highly optimized open source implementation of the Khronos OpenVX computer vision specification. It allows for rapid prototyping as well as fast execution on a wide range of computer hardware, including small embedded x86 CPUs and large workstation discrete GPUs.

IMPORTANT: amdovx-core is a part of https://github.com/GPUOpen-ProfessionalCompute-Libraries/amdovx-modules project that contain additional OpenVX modules, such as, neural network inference, 360 degree video stitching, etc.

The amdovx-core project consists of two components:

OpenVX: AMD OpenVX library
RunVX: command-line utility to execute OpenVX graph described in GDF text file
RunCL: command-line utility to build, execute, and debug OpenCL programs

The OpenVX framework provides a mechanism to add new vision functions to OpenVX by 3rd party vendors. Look into github amdovx-modules project for additional OpenVX modules and utilities.

vx_nn: OpenVX neural network module that was built on top of MIOpen
vx_loomsl: Radeon LOOM stitching library for live 360 degree video applications
loom_shell: an interpreter to prototype 360 degree video stitching applications using a script
vx_opencv: OpenVX module that implemented a mechanism to access OpenCV functionality as OpenVX kernels

This software is provided under a MIT-style license, see the file COPYRIGHT.txt for details.

Features

The code is highly optimized for both x86 CPU and OpenCL for GPU
Supported hardware spans the range from low power embedded APUs (like the new G series) to laptop, desktop and workstation graphics
Supports Windows, Linux, and OS X
Includes a “graph optimizer” that looks at the entire processing pipeline and removes/replaces/merges functions to improve performance and minimize bandwidth at runtime
Scripting support allows for rapid prototyping, without re-compiling at production performance levels

Pre-requisites

CPU: SSE4.1 or above CPU, 64-bit.
GPU: Radeon Professional Graphics Cards or Vega Family of Products (16GB required for vx_loomsl and vx_nn libraries)
- Windows: install the latest drivers and OpenCL SDK download
- Linux: install ROCm
OpenCV 3 (optional) download for RunVX
- Set OpenCV_DIR environment variable to OpenCV/build folder

Build Instructions

Build this project to generate AMD OpenVX library and RunVX executable.

Refer to openvx/include/VX for Khronos OpenVX standard header files.
Refer to openvx/include/vx_ext_amd.h for vendor extensions in AMD OpenVX library.
Refer to runvx/README.md for RunVX details.
Refer to runcl/README.md for RunCL details.

Build using Visual Studio Professional 2013 on 64-bit Windows 10/8.1/7

Install OpenCV 3 with contrib download for RunVX tool to support camera capture and image display (optional)
OpenCV_DIR environment variable should point to OpenCV/build folder
Use amdovx-core/amdovx.sln to build for x64 platform
If AMD GPU (or OpenCL) is not available, set build flag ENABLE_OPENCL=0 in openvx/openvx.vcxproj and runvx/runvx.vcxproj.

Build using CMake

Install CMake 2.8 or newer download.
Install OpenCV 3 with contrib download for RunVX tool to support camera capture and image display (optional)
OpenCV_DIR environment variable should point to OpenCV/build folder
Install libssl-dev on linux (optional)
Use CMake to configure and generate Makefile
If AMD GPU (or OpenCL) is not available, use build flag -DCMAKE_DISABLE_FIND_PACKAGE_OpenCL=TRUE.

License

GPUOpen-ProfessionalCompute-Libraries/amdovx-core

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