Install Guide Ubuntu#

The easiest way to install Intel® Deep Learning Streamer (Intel® DL Streamer) Pipeline Framework is installing from pre-built Debian packages. If you prefer containerized environment based on Docker, the Intel® DL Streamer Pipeline Framework docker file is also available to build runtime docker image.

Alternatively, you can build Intel® DL Streamer Pipeline Framework from the source code provided in repository, either building directly on host system, or as a Docker image.

The following table summarizes installation options. You can find detailed instructions for each installation option by following the links in the first column of the table.

Option	Supported OS	Notes
Install Intel® DL Streamer Pipeline Framework pre-built Debian packages	Ubuntu 22.04 (kernel 6.6+ for NPU)	-
Create Docker image from Intel® DL Streamer Pipeline Framework Docker file and run it	Any Linux OS as host system	Recommended for containerized environment and when host OS is not supported by the Pipeline Framework installer
Compile Intel® DL Streamer Pipeline Framework from sources on host system	Ubuntu 22.04 (kernel 6.6+ for NPU)	If you want to build Pipeline Framework from source code on host system

Option #1: Install Intel® DL Streamer Pipeline Framework from Debian packages#

Available Debian packages#

Package name	Description
intel-dlstreamer-dev	Development package - installs runtime on CPU/GPU, C++/Python bindings, samples, development tools
intel-dlstreamer-cpu	Runtime on CPU - files required for execution on CPU
intel-dlstreamer-gpu	Runtime on GPU - files required for execution on GPU
intel-dlstreamer	Runtime on CPU/GPU - files required for execution on CPU and GPU
intel-dlstreamer-dpcpp	Additional runtime on GPU - runtime libraries built on Intel® oneAPI DPC++ Compiler. This package installs DPC++ runtime as dependency
python3-intel-dlstreamer	Python runtime - installs Intel® DL Streamer Pipeline Framework Python bindings and runtime on CPU/GPU
intel-dlstreamer-cpp	C++ bindings
intel-dlstreamer-samples	C++ and Python samples demonstrating the use of Intel® DL Streamer Pipeline Framework

Step 1: Install prerequisites#

Install dependencies and register additional APT repositories.

# Install dependencies
sudo apt-get update && sudo apt-get install curl wget gpg software-properties-common jq

# Register Intel® oneAPI APT repository
curl -fsSL https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | sudo gpg --dearmor --output /usr/share/keyrings/intel-sw-products.gpg
echo "deb [signed-by=/usr/share/keyrings/intel-sw-products.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/intel-oneapi.list

# Download Intel® Graphics APT repository key
curl -fsSL https://repositories.intel.com/graphics/intel-graphics.key | sudo gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg

For Intel® Graphics APT repository please use only one of following (more information https://dgpu-docs.intel.com/driver/installation.html):

For Intel® Data Center GPU Flex Series and Intel® Data Center GPU Max Series:

# Register Intel® Graphics APT repository
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/production/2350 unified" | sudo tee /etc/apt/sources.list.d/intel-graphics.list

For Intel® Client and Arc™ GPUs:

# Register Intel® Graphics APT repository
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | sudo tee /etc/apt/sources.list.d/intel-graphics.list

Run below commands for both above options:

sudo apt install -y linux-headers-$(uname -r) flex bison intel-fw-gpu intel-i915-dkms xpu-smi
sudo reboot

For Intel® Core™ Ultra processors please install NPU drivers as described in intel/linux-npu-driver (requires Ubuntu 22.04 with kernel version 6.6+).
Install Intel® oneAPI DPC++/C++ Compiler runtime package and Intel® DL Streamer features based on DPC++:

# Install
sudo apt-get update && sudo apt-get install intel-level-zero-gpu level-zero

[optional] You can additionally install full Intel® oneAPI DPC++/C++ Compiler (previous command installs runtime only):

sudo apt-get install intel-oneapi-compiler-dpcpp-cpp

Step 2: Install Intel® DL Streamer and OpenVINO™ toolkit#

Download pre-built Debian packages from GitHub Release page <https://github.com/dlstreamer/dlstreamer/releases>. You can manually download all packages from the release page or try to use following command:

wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains (".deb")) | .browser_download_url')

Install Intel® DL Streamer via apt install and OpenVINO™ via script install_openvino.sh.

# Install Intel® DL Streamer
sudo apt install ./*.deb

# Install OpenVINO™ toolkit (if not installed)
sudo -E /opt/intel/dlstreamer/install_dependencies/install_openvino.sh

Configure the environment after installing Intel® DL Streamer and OpenVINO™:

# Setup OpenVINO™ and Intel® DL Streamer environment
source /opt/intel/openvino_2024/setupvars.sh
source /opt/intel/dlstreamer/setupvars.sh

Step 3: Install MQTT and Kafka clients for element gvametapublish#

Note

Optional step

In order to enable all gvametapublish backends install required dependencies with scripts:

sudo -E /opt/intel/dlstreamer/install_dependencies/install_mqtt_client.sh
sudo -E /opt/intel/dlstreamer/install_dependencies/install_kafka_client.sh

Next Steps:#

When using Media, GPU or NPU devices as non-root user, please configure:

sudo usermod -a -G video <username>
sudo usermod -a -G render <username>

You are ready to use Intel® DL Streamer. For further instructions please go to: Tutorial

Option #2: Create Docker image from Intel® DL Streamer Pipeline Framework Docker file and run it#

Step 1: Install Docker#

Get Docker for your host OS: To prevent file permission issues please follow ‘Manage Docker as a non-root user’ section steps described here <https://docs.docker.com/engine/install/linux-postinstall/>

Step 2: Allow connection to X server#

Some Pipeline Framework samples use display. Hence, first run the following commands to allow connection from Docker container to X server on host:

xhost local:root
setfacl -m user:1000:r ~/.Xauthority

Step 3: Download the Intel® DL Streamer Dockerfile#

# Install dependencies
sudo apt-get update && sudo apt-get install curl wget gpg software-properties-common jq

wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains ("dlstreamer.Dockerfile")) | .browser_download_url')

Step 4: Build Intel® DL Streamer Pipeline Framework image#

docker build -t dlstreamer -f dlstreamer.Dockerfile .

Step 5: Run Intel® DL Streamer Pipeline Framework container#

docker run -it --privileged --net=host \
   --device=/dev/dri \
   --device=/dev/accel \
   -v ~/.Xauthority:/home/dlstreamer/.Xauthority \
   -v /tmp/.X11-unix \
   -e DISPLAY=$DISPLAY \
   -v /dev/bus/usb \
   --rm dlstreamer /bin/bash

Intel® Graphics Compute Runtime for oneAPI Level Zero and OpenCL™ Driver configuration on Ubuntu* 22.04#

Intel® Graphics Compute Runtime for oneAPI Level Zero and OpenCL™ Driver components are required to use a GPU device. The driver is installed in the Intel® DL Streamer Pipeline Framework Docker image but you need to activate it in the container for a non-root user if you have Ubuntu 22.04 on your host.

To access GPU capabilities, you need to have correct permissions on the host and Docker container. Run the following command to list the group assigned ownership of the render nodes on your host:

stat -c "group_name=%G group_id=%g" /dev/dri/render*

Intel® DL Streamer Pipeline Framework Docker images do not contain a render group for dlstreamer non-root user because the render group does not have a strict group ID, unlike the video group. To run container as non-root with access to a GPU device, specify the render group ID from your host:

docker run -it --device /dev/dri --group-add=<render_group_id_on_host> <other_args> <image_name>

For example, get the render group ID on your host:

docker run -it --device /dev/dri --group-add=$(stat -c "%g" /dev/dri/render*) <other_args> <image_name>

Now you can use the container with GPU access under the non-root user.

Next Steps:#

You are ready to use Intel® DL Streamer. For further instructions please go to: Tutorial

Option #3: Compile Intel® DL Streamer Pipeline Framework from sources on host system#

Note

These instructions are verified on Ubuntu 22.04

Step 1: Clone this repository#

First, clone this repository into folder ~/intel/dlstreamer_gst:

mkdir -p ~/intel
git clone --recursive https://github.com/dlstreamer/dlstreamer.git ~/intel/dlstreamer_gst
cd ~/intel/dlstreamer_gst

Step 2: Install Intel® Distribution of OpenVINO™ Toolkit#

Follow OpenVINO™ Toolkit instruction guide here to install OpenVINO™ on Linux.

Environment: Runtime
Operating System: Linux
Version: Latest
Distribution: OpenVINO™ Archives

After successful OpenVINO™ Toolkit package installation, run the following commands to install OpenVINO™ Toolkit dependencies and enable OpenVINO™ Toolkit development environment:

sudo -E /opt/intel/openvino_2024/install_dependencies/install_openvino_dependencies.sh
source /opt/intel/openvino_2024/setupvars.sh

Install Open Model Zoo tools:

python3 -m pip install --upgrade pip
python3 -m pip install openvino-dev[onnx,tensorflow,pytorch]

Note

Make sure your environment variable $PATH includes ‘$HOME/.local/bin’ .

Step 3: Install Intel® DL Streamer Pipeline Framework dependencies#

Install build dependencies:

# Install dependencies
sudo apt-get update && sudo apt-get install curl wget gpg software-properties-common cmake build-essential libpython3-dev python-gi-dev libopencv-dev jq

Download pre-built Debian packages for GStreamer from GitHub Release page <https://github.com/dlstreamer/dlstreamer/releases>. You can manually download all packages from the release page or try to use following command. Install GStreamer from dowloaded packages:

wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains (".deb")) | .browser_download_url')
sudo apt install -y ./intel-dlstreamer-gst*
sudo apt install -y ./intel-dlstreamer-ffmpeg*

Step 4: Install Python dependencies#

If you intend to use Python elements or samples, you need to install the necessary dependencies using the following commands:

If you want to set up a local environment follow this step (skip to install all the dependencies globally):

Install the virtualenv tool to create isolated Python environments

# you can install it within the global python interpreter
python3 -m pip install virtualenv
# or you can install it as a user package
python3 -m pip install --user virtualenv

Create a virtual environment and activate it

cd ~/intel/dlstreamer_gst
virtualenv -p /usr/bin/python3 .env3 --system-site-packages
source .env3/bin/activate

Install Python requirements:

cd ~/intel/dlstreamer_gst
python3 -m pip install --upgrade pip
python3 -m pip install -r requirements.txt

Step 5: Install OpenCL™#

Note

Optional step

# Download Intel® Graphics APT repository key
curl -fsSL https://repositories.intel.com/graphics/intel-graphics.key | sudo gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg

Then use only one of following (more information https://dgpu-docs.intel.com/driver/installation.html):

For Intel® Data Center GPU Flex Series and Intel® Data Center GPU Max Series:

# Register Intel® Graphics APT repository
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/production/2350 unified" | sudo tee /etc/apt/sources.list.d/intel-graphics.list

For Intel® Client and Arc™ GPUs:

# Register Intel® Graphics APT repository
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | sudo tee /etc/apt/sources.list.d/intel-graphics.list

Run the following commands to install OpenCL™ driver:

# Install
sudo apt-get update && sudo apt-get install -y intel-opencl-icd ocl-icd-opencl-dev opencl-clhpp-headers

Step 6: Install message brokers#

Note

Optional step

Installation of message brokers will enable capability of gvametapublish element to publish inference results to Kafka or MQTT. Note that gvametapublish element will be able to publish inference results to file even if you skip this step.

Run following script to install the message brokers:

cd ~/intel/dlstreamer_gst/scripts/
sudo -E ./install_metapublish_dependencies.sh

In order to enable one of these message brokers in Pipeline Framework, corresponding key should be passed to cmake in configuration step. To enable MQTT please pass -DENABLE_PAHO_INSTALLATION=ON option to cmake. To enable Kafka please pass -DENABLE_RDKAFKA_INSTALLATION=ON option to cmake.

Step 7: Install Intel® oneAPI DPC++/C++ Compiler#

Note

Optional step

OpenCL™ driver installation is required before continuing.

Intel® oneAPI DPC++ Compiler will enable execution of gvawatermark and gvatrack elements on GPU.

# Register Intel® oneAPI APT repository
curl -fsSL https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | sudo gpg --dearmor --output /usr/share/keyrings/intel-sw-products.gpg
echo "deb [signed-by=/usr/share/keyrings/intel-sw-products.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/intel-oneapi.list

# Install Intel® oneAPI DPC++/C++ Compiler
sudo apt-get update && sudo apt-get install -y intel-oneapi-compiler-dpcpp-cpp intel-level-zero-gpu level-zero-dev

# Set up environment
source /opt/intel/oneapi/compiler/latest/env/vars.sh

Step 8: Install VA-API dependencies#

Note

Optional step

OpenCL™ driver installation is required before continuing.

To enable VA-API preprocessing of Pipeline Framework’s inference elements run the following commands:

sudo apt-get install -y intel-dlstreamer-gst-vaapi libva-dev vainfo intel-media-va-driver-non-free
export LIBVA_DRIVER_NAME=iHD

# When using Media, GPU or NPU devices as non-root user, please configure:
sudo usermod -a -G video <username>
sudo usermod -a -G render <username>

# Check installation
vainfo

The output shouldn’t contain any error messages, iHD driver must be found. If no errors occur, please proceed further to the next step.

If you receive error message like the one below, please reboot your machine and try again.

libva info: va_openDriver() returns -1
vaInitialize failed with error code -1 (unknown libva error), exit

If you receive any other errors, please retry installation process. If it’s not resolved even after re-installation, please submit an issue for support on GitHub here.

Additionally, pass -DENABLE_VAAPI=ON option to cmake in configuration step.

Step 9: Install Intel® VPU drivers#

Note

Optional step for Intel® Core™ Ultra processors

Please follow instructions from intel/linux-npu-driver. Please note Ubuntu 22.04 with Linux kernel 6.6+ and intel_vpu.ko module enabled is required.

If you don’t have proper kernel, one can use https://kernel.ubuntu.com/mainline/v6.7.10 (kernel version Intel® DL Streamer was validated with), following Linux kernel installation steps from here: https://wiki.ubuntu.com/Kernel/MainlineBuilds.

Step 10: Build Intel® DL Streamer Pipeline Framework#

With all dependencies installed, proceed to build Pipeline Framework:

# OpenVINO™ Toolkit environment
source /opt/intel/openvino_2024/setupvars.sh
# GStreamer environment
source /opt/intel/dlstreamer/gstreamer/setupvars.sh
# Intel® oneAPI DPC++/C++ Compiler environment (if installed)
source /opt/intel/oneapi/compiler/latest/env/vars.sh

# cmake, remove -DENABLE_VAAPI option if VA-API not installed
mkdir ~/intel/dlstreamer_gst/build
cd ~/intel/dlstreamer_gst/build
cmake -DENABLE_VAAPI=ON ..

# make
make -j

# Setup Intel® DL Streamer Pipeline Framework environment
source ~/intel/dlstreamer_gst/scripts/setup_env.sh

When using Media, GPU or NPU devices as non-root user, please configure:

sudo usermod -a -G video <username>
sudo usermod -a -G render <username>

Intel® DL Streamer Pipeline Framework is now ready to use!

You can find samples in folder ~/intel/dlstreamer_gst/samples. Before using the samples, run the script download_models.sh (located in samples folder) to download the models required for samples.

Note

The environment variables are removed when you close the shell. As an option, you can set the environment variables in file ~/.bashrc for automatic enabling.

Note

The manual installation on the host machine may have environment issues. If this happened, please consider other ways. Also, you can create an issue on GitHub here.

Next Steps#

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Install Guide Ubuntu

Contents

Install Guide Ubuntu#

Option #1: Install Intel® DL Streamer Pipeline Framework from Debian packages#

Available Debian packages#

Step 1: Install prerequisites#

Step 2: Install Intel® DL Streamer and OpenVINO™ toolkit#

Step 3: Install MQTT and Kafka clients for element gvametapublish#

Next Steps:#

Option #2: Create Docker image from Intel® DL Streamer Pipeline Framework Docker file and run it#

Step 1: Install Docker#

Step 2: Allow connection to X server#

Step 3: Download the Intel® DL Streamer Dockerfile#

Step 4: Build Intel® DL Streamer Pipeline Framework image#

Step 5: Run Intel® DL Streamer Pipeline Framework container#

Intel® Graphics Compute Runtime for oneAPI Level Zero and OpenCL™ Driver configuration on Ubuntu* 22.04#

Next Steps:#

Option #3: Compile Intel® DL Streamer Pipeline Framework from sources on host system#

Step 1: Clone this repository#

Step 2: Install Intel® Distribution of OpenVINO™ Toolkit#

Step 3: Install Intel® DL Streamer Pipeline Framework dependencies#

Step 4: Install Python dependencies#

Step 5: Install OpenCL™#

Step 6: Install message brokers#

Step 7: Install Intel® oneAPI DPC++/C++ Compiler#

Step 8: Install VA-API dependencies#

Step 9: Install Intel® VPU drivers#

Step 10: Build Intel® DL Streamer Pipeline Framework#

Next Steps#