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 image is available as well as Dockerfile 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. Before running chosen installations process, please follow prerequisites.

Prerequisite	Notes
Install Intel® GPU drivers for computing and media runtimes	-
Install Intel® NPU drivers	Optional step only for Intel® Core™ Ultra processors with NPU AI accelerator.

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 24.04 , 22.04 (kernel 6.6+ for NPU)	-
Install Docker image from Docker Hub 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 24.04, 22.04 (kernel 6.6+ for NPU)	If you want to build Pipeline Framework from source code on host system

Prerequisite 1 - Intel® GPU drivers for computing and media runtimes#

To use GPU as an inference device or to use graphics hardware encoding/decoding capabilities, it is required to install GPU computing and media runtime drivers.

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

Please cheek that you can see a renderD* device in /dev/dri directory before installation. You should be able to see a renderD128 for the integrated GPU or renderD129 for the discrete GPU.
```
user@my-host:~$ ll /dev/dri | grep renderD
crw-rw----  1 root render 226, 128 Aug  6 22:41 renderD128
```
If you can see see the device, please follow the next step C. If you cannot see it, please follow instructions to the full installation processes, including Kernel Mode drivers:
- For Intel® Data Center GPU Flex Series and Intel® Data Center GPU Max Series
- For Intel® Arc™ GPUs
To register Intel® Graphics APT repository, please use only one of the following according to your hardware:

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

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

# Download Intel® Graphics APT repository
# [Ubuntu 24.04]
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/graphics/ubuntu noble flex" | sudo tee /etc/apt/sources.list.d/intel-graphics.list
# [Ubuntu 22.04]
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/graphics/ubuntu jammy flex" | sudo tee /etc/apt/sources.list.d/intel-graphics.list

For Intel® Client and Arc™ GPUs:

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

# Download Intel® Graphics APT repository
# [Ubuntu 24.04]
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu noble client" | sudo tee /etc/apt/sources.list.d/intel-graphics.list
# [Ubuntu 22.04]
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

Install or update packages responsible for computing and media runtimes:

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

Prerequisite 2 - Install Intel® NPU drivers#

Note

Optional step for Intel® Core™ Ultra processors

If you want to use NPU AI accelerator, you need to have Intel® NPU drivers installed.

Before installation, please make sure that intel_vpu.ko module is enabled on your host:

user@your-host:~$ lsmod | grep intel_vpu
intel_vpu             245760  0

Installing the driver requires the device to be recognized by your system - Kernel Mode driver should be available. It means you can see a accel device in /dev/dri directory. If you don’t see it, please reboot the host.
```
user@my-host:~$ ll /dev/accel/ | grep accel
crw-rw----  1 root render 261, 0   Aug  6 22:41 accel0
```
Install the newest Intel® NPU driver. Please follow ‘Installation procedure’ for the newest available driver version described in: intel/linux-npu-driver

Note

If you are experiencing issues with installation process, check all notes and tips in the release note for the newest Intel® NPU driver version: intel/linux-npu-driver. Please pay attention to access to the device as a non-root user.

Note

The following error can be reported when running Intel® DL Streamer on NPU device:

Setting pipeline to PLAYING ...
New clock: GstSystemClock
Caught SIGSEGV
Spinning.

In such case, please use the following setting as a temporary workaround:

export ZE_ENABLE_ALT_DRIVERS=libze_intel_vpu.so

The issue should be fixed with newer versions of Intel® NPU drivers and Intel® OpenVINO™ NPU plugins.

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

Step 1: Preprare the installation environment#

For Ubuntu 24.04:

Download pre-built Debian packages:

mkdir -p ~/intel/dlstreamer_gst
cd ~/intel/dlstreamer_gst
wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains ("ubuntu_24.04_amd64.deb")) | .browser_download_url')

For Ubuntu 22.04:

Download Ninja build system and use it to build OpenCV library:

mkdir -p ~/intel/dlstreamer_gst
cd ~/intel/dlstreamer_gst
sudo apt-get install ninja-build unzip
wget -q --no-check-certificate -O opencv.zip https://github.com/opencv/opencv/archive/4.10.0.zip
unzip opencv.zip && rm opencv.zip && mv opencv-4.10.0 opencv && mkdir -p opencv/build
cd ./opencv/build
cmake -DBUILD_TESTS=OFF -DBUILD_PERF_TESTS=OFF -DBUILD_EXAMPLES=OFF -DBUILD_opencv_apps=OFF -GNinja .. \
&& ninja -j "$(nproc)" && sudo ninja install

Download pre-built Debian packages:

cd ~/intel/dlstreamer_gst
wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains ("ubuntu_22.04_amd64.deb")) | .browser_download_url')

Step 2: Install Intel® DL Streamer#

Install Intel® DL Streamer from pre-built Debian packages:

sudo apt install ./*.deb

Step 3: Install OpenVINO™ toolkit#

Install Intel® OpenVINO™ via script install_openvino.sh.

sudo -E /opt/intel/dlstreamer/install_dependencies/install_openvino.sh

Step 4: 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

Step 5: Add user to groups#

When using Media, GPU or NPU devices as non-root user, please add your user to video and render groups:

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

Step 6: Set up the environment for Intel® DL Streamer#

Source required environment variables to run GStreamer and Intel® DL Streamer:

# Setup OpenVINO™ Toolkit environment
source /opt/intel/openvino_2024/setupvars.sh
# Setup GStreamer and Intel® DL Streamer Pipeline Framework environments
source /opt/intel/dlstreamer/setupvars.sh

Note

The environment variables are removed when you close the shell. Before each run of Intel® DL Streamer you need to setup the environment with the 2 scripts listed in this step. As an option, you can set the environment variables in file ~/.bashrc for automatic enabling.

Step 7: Verify Intel® DL Streamer installation#

Intel® DL Streamer has been installed. You can run the gst-inspect-1.0 gvadetect to confirm that GStreamer and Intel® DL Streamer are running:

gst-inspect-1.0 gvadetect

If your can see the documentation of gvadetect element, the installation process is completed.

Step 8: Next steps - running sample Intel® DL Streamer pipelines#

You are ready to use Intel® DL Streamer. For further instructions to run sample pipeline(s), please go to: Tutorial

Option #2: Install Docker image from Docker Hub 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: Pull the Intel® DL Streamer Docker image from Docker Hub#

Visit <https://hub.docker.com/r/intel/dlstreamer/> Intel® DL Streamer image docker hub to select the most appropriate version. By default , the latest docker image points to Ubuntu24 version.

For Ubuntu 24.04 please use latest tag or specified version e.g. 2024.1.2-ubuntu24

docker pull intel/dlstreamer:latest

For Ubuntu 22.04 please specify tag e.g. 2024.1.2-ubuntu22

docker pull intel/dlstreamer:2024.1.2-ubuntu22

Step 4: Run Intel® DL Streamer Pipeline Framework container#

To confirm that your installation is completed successfully, please run a container

docker run -it --rm intel/dlstreamer:latest

In the container, please run the gst-inspect-1.0 gvadetect to confirm that GStreamer and Intel® DL Streamer are running

dlstreamer@ea6445a05788:~$ gst-inspect-1.0 gvadetect

If your can see the documentation of gvadetect element, the installation process is completed.

Step 5: Next steps - running sample Intel® DL Streamer pipelines#

You are ready to use Intel® DL Streamer. For further instructions to run sample pipeline(s), 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 Intel® DL Streamer 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 libgflags-dev libdrm-dev

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 downloaded packages:

For Ubuntu 24.04:

wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains ("ubuntu_24.04_amd64.deb")) | .browser_download_url')
sudo apt install -y ./intel-dlstreamer-gst*
sudo apt install -y ./intel-dlstreamer-ffmpeg*

For Ubuntu 22.04:

wget $(wget -q -O - https://api.github.com/repos/dlstreamer/dlstreamer/releases/latest | \
  jq -r '.assets[] | select(.name | contains ("ubuntu_22.04_amd64.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

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: 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!

Note

The environment variables are removed when you close the shell. Before each run of Intel® DL Streamer you need to setup the environment with the following 3 scripts as above in this step: source /opt/intel/openvino_2024/setupvars.sh, source /opt/intel/dlstreamer/gstreamer/setupvars.sh and source ~/intel/dlstreamer_gst/scripts/setup_env.sh. 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.

Step 10: Intel® DL Streamer installation verification#

Intel® DL Streamer has been installed. Please run the gst-inspect-1.0 gvadetect to confirm that GStreamer and Intel® DL Streamer are running

user@my-host:~/intel/dlstreamer_gst/build$ gst-inspect-1.0 gvadetect

If your can see the documentation of gvadetect element, the installation process is completed.

Step 11: Next steps - running sample Intel® DL Streamer pipelines#

You are ready to use Intel® DL Streamer. For further instructions to run sample pipeline(s), please go to: Tutorial

* Other names and brands may be claimed as the property of others.

Install Guide Ubuntu

Contents

Install Guide Ubuntu#

Prerequisite 1 - Intel® GPU drivers for computing and media runtimes#

Prerequisite 2 - Install Intel® NPU drivers#

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

Step 1: Preprare the installation environment#

Step 2: Install Intel® DL Streamer#

Step 3: Install OpenVINO™ toolkit#

Step 4: Install MQTT and Kafka clients for element gvametapublish#

Step 5: Add user to groups#

Step 6: Set up the environment for Intel® DL Streamer#

Step 7: Verify Intel® DL Streamer installation#

Step 8: Next steps - running sample Intel® DL Streamer pipelines#

Option #2: Install Docker image from Docker Hub and run it#

Step 1: Install Docker#

Step 2: Allow connection to X server#

Step 3: Pull the Intel® DL Streamer Docker image from Docker Hub#

Step 4: Run Intel® DL Streamer Pipeline Framework container#

Step 5: Next steps - running sample Intel® DL Streamer pipelines#

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

Step 1: Clone Intel® DL Streamer 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: Build Intel® DL Streamer Pipeline Framework#

Step 10: Intel® DL Streamer installation verification#

Step 11: Next steps - running sample Intel® DL Streamer pipelines#