Linux

Linux Build Instructions

Identify Linux Components

• Linux Version Info

  • Ubuntu

  cat /etc/lsb-release && uname -a
  

  • CentOS / RedHat / SLES

  cat /etc/os-release && uname -a
  

• Linux CPU & GPU Info

  • Ubuntu

  cat /proc/cpuinfo && lspci  -v -s  $(lspci | grep ' VGA ' | cut -d" " -f 1)
  

  • CentOS / RedHat / SLES

  cat /proc/cpuinfo && /sbin/lsmod | grep gpu
  

Prerequisites

• Linux distribution
  • Ubuntu - 20.04 / 22.04
  • CentOS - 7 / 8
  • RedHat - 8 / 9
  • SLES - 15-SP3
• Install ROCm
• CMake 2.8 or newer download
• ROCm MIOpen for Neural Net Extensions (vx_nn)
• Qt Creator for Cloud Inference Client
• Protobuf for inference generator & model compiler
  • install libprotobuf-dev and protobuf-compiler needed for vx_nn
• OpenCV 4.6
  • Set OpenCV_DIR environment variable to OpenCV/build folder
• FFMPEG n4.4.2 - Optional
  • FFMPEG is required for amd_media & mv_deploy modules
• RALI Prerequisites

Build and Install

Using apt-get / yum

• ROCm supported hardware
• Install ROCm
• On Ubuntu

  sudo apt-get install mivisionx
  

• On CentOS / RedHat

  sudo yum install mivisionx
  

• On SLES

  sudo zypper install mivisionx
  

  Note:
  • vx_winml is not supported on linux
  • source code will not available with apt-get / yum install
  • the installer will copy
    • executables into /opt/rocm/mivisionx/bin
    • libraries into /opt/rocm/mivisionx/lib
    • OpenVX and module header files into /opt/rocm/mivisionx/include
    • model compiler, toolkit, & samples placed in /opt/rocm/mivisionx
  • Package (.deb & .rpm) install requires OpenCV v3.4.0 to execute AMD OpenCV extensions

Using MIVisionX-setup.py

• ROCm supported hardware

• Install ROCm

• Use the below commands to set up and build MIVisionX

  • Clone MIVisionX

  git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git
  cd MIVisionX
  

  • Run Setup

  python MIVisionX-setup.py
  

  mkdir build
  cd build
  cmake ../
  make -j8
  sudo make install
  

  Note: vx_winml is not supported on Linux

Verify the Installation

• The installer will copy

  • executables into /opt/rocm/bin
  • libraries into /opt/rocm/lib
  • OpenVX and OpenVX module header files into /opt/rocm/include/mivisionx
  • Apps, Samples, Documents, Model Compiler, and Toolkit are placed into /opt/rocm/libexec/mivisionx

• Run the below sample to verify the installation

  Canny Edge Detection

  export PATH=$PATH:/opt/rocm/mivisionx/bin
  export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/rocm/mivisionx/lib
  runvx /opt/rocm/mivisionx/samples/gdf/canny.gdf 
  

  Note: More samples are available in samples folder