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Kiriti Gowda edited this page Jan 28, 2023
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-
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 $(lspci | grep ' VGA ' | cut -d" " -f 1)
- CentOS / RedHat / SLES
cat /proc/cpuinfo && /sbin/lsmod | grep gpu
- Linux distribution
-
Ubuntu -
20.04
/22.04
-
CentOS -
7
/8
-
RedHat -
8
/9
-
SLES -
15-SP3
-
Ubuntu -
- Install ROCm
- CMake 2.8 or newer download
- ROCm MIOpen for
Neural Net Extensions
(vx_nn) - Qt Creator for Cloud Inference Client
-
Protobuf for inference generator & model compiler
- install
libprotobuf-dev
andprotobuf-compiler
needed for vx_nn
- install
-
OpenCV 4.6
- Set
OpenCV_DIR
environment variable toOpenCV/build
folder
- Set
-
FFMPEG n4.4.2 - Optional
- FFMPEG is required for amd_media & mv_deploy modules
- RALI Prerequisites
- ROCm supported hardware
- Install ROCm
- On
Ubuntu
sudo apt-get install mivisionx
- On
CentOS
/RedHat
sudo yum install mivisionx
- On
SLES
Note:sudo zypper install mivisionx
-
vx_winml
is not supported onlinux
- source code will not available with
apt-get
/yum
install - the installer will copy
- executables into
/opt/rocm/mivisionx/bin
- libraries into
/opt/rocm/mivisionx/lib
- OpenVX and module header files into
/opt/rocm/mivisionx/include
- model compiler, toolkit, & samples placed in
/opt/rocm/mivisionx
- executables into
- Package (.deb & .rpm) install requires
OpenCV v3.4.0
to executeAMD OpenCV extensions
-
-
Install ROCm
-
Use the below commands to set up and build MIVisionX
- Clone MIVisionX
git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git cd MIVisionX
- Run Setup
python MIVisionX-setup.py
mkdir build cd build cmake ../ make -j8 sudo make install
Note: vx_winml is not supported on Linux
-
The installer will copy
- executables into
/opt/rocm/bin
- libraries into
/opt/rocm/lib
- OpenVX and OpenVX module header files into
/opt/rocm/include/mivisionx
- Apps, Samples, Documents, Model Compiler, and Toolkit are placed into
/opt/rocm/libexec/mivisionx
- executables into
-
Run the below sample to verify the installation
Canny Edge Detection
export PATH=$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
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