Install Guide Ubuntu#

The easiest way to install Deep Learning Streamer Pipeline Framework is installation from Debian packages using APT repository.

If you prefer containerized environment based on Docker, use the Docker image as well as the Dockerfile to build runtime Docker image. Regardless of a chosen installation path, make sure to set up the prerequisites first.

For a detailed description of installation process, including the option with building Deep Learning Streamer Pipeline Framework from the source code provided in Open Edge Platform repository, follow the instructions.

Prerequisites#

To use GPU and/or NPU as an inference device or to use graphics hardware encoding/decoding capabilities, you need to install appropriate drivers. Use the script below to detect available device(s) and install the drivers. Also, pay attention to the displayed information, as the script uses multiple references to other Intel® resources when additional configuration is required.

Step 1: Download the installation script#

mkdir -p ~/intel/dlstreamer_gst
cd ~/intel/dlstreamer_gst/
wget -O DLS_install_prerequisites.sh https://raw.githubusercontent.com/open-edge-platform/edge-ai-libraries/main/libraries/dl-streamer/scripts/DLS_install_prerequisites.sh && chmod +x DLS_install_prerequisites.sh

Step 2: Execute the script and follow its instructions#

./DLS_install_prerequisites.sh

The essential packages needed for most Intel® Client GPU users are installed:

GPU:
   libze-intel-gpu1
   libze1
   intel-opencl-icd
   clinfo
   intel-gsc
Media:
   intel-media-va-driver-non-free
NPU:
   intel-driver-compiler-npu
   intel-fw-npu
   intel-level-zero-npu
   level-zero

More details about the packages can be found in:

Running Deep Learning Streamer on Intel® Data Center GPU (Flex) requires specific drivers, and you need to follow the instructions on Intel® Data Center GPU website.

Option #1: Install Deep Learning Streamer Pipeline Framework from Debian packages using APT repository#

This option provides the simplest installation flow using apt-get install command.

Step 1: Installing prerequisites#

Run the script DLS_install_prerequisites.sh to install required GPU/NPU drivers. For more details see prerequisites.

./DLS_install_prerequisites.sh

Step 2: Setup repositories#

  • In Ubuntu 22

    sudo -E wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
sudo -E wget -O- https://apt.repos.intel.com/edgeai/dlstreamer/GPG-PUB-KEY-INTEL-DLS.gpg | sudo tee /usr/share/keyrings/dls-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/dls-archive-keyring.gpg] https://apt.repos.intel.com/edgeai/dlstreamer/ubuntu22 ubuntu22 main" | sudo tee /etc/apt/sources.list.d/intel-dlstreamer.list
sudo bash -c 'echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/openvino/2025 ubuntu22 main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2025.list'

  • Ubuntu 24

    sudo -E wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
sudo -E wget -O- https://apt.repos.intel.com/edgeai/dlstreamer/GPG-PUB-KEY-INTEL-DLS.gpg | sudo tee /usr/share/keyrings/dls-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/dls-archive-keyring.gpg] https://apt.repos.intel.com/edgeai/dlstreamer/ubuntu24 ubuntu24 main" | sudo tee /etc/apt/sources.list.d/intel-dlstreamer.list
sudo bash -c 'echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/openvino/2025 ubuntu24 main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2025.list'

    NOTE: If you have OpenVINO™ installed in a version different from 2025.2.0, please uninstall the OpenVINO™ packages using the following commands.

    sudo apt remove -y openvino* libopenvino-* python3-openvino*
sudo apt-get autoremove

Step 3: Install Deep Learning Streamer Pipeline Framework#

NOTE: This step will also install the required dependencies, including OpenVINO™ Toolkit and GStreamer.

sudo apt update
sudo apt-get install intel-dlstreamer

Congratulations! Deep Learning Streamer is now installed and ready for use!

To see the full list of installed components check the Dockerfile content for Ubuntu 24

[Optional] Step 4: Python dependencies#

The Python packages required to run Deep Learning Streamer python elements or samples are not installed by default. You can install them using commands from Advanced Install Guide Compilation / Install Python dependencies.

[Optional] Step 5: Post installation steps#

Download model and run hello_dlstreamer script#

Before executing any scripts, ensure you have set the MODELS_PATH environment variable to the directory where the model will be downloaded or where it already exists. The hello_dlstreamer.sh script assumes the availability of the YOLO11s model. If you do not have it, download it using the following command:

NOTE:

  • The download_public_models.sh script will download the YOLO11s model from the Ultralytics website along with other required components and convert it to the OpenVINO™ format.

  • If you add the coco128 argument to the script, the downloaded model will also be quantized to the INT8 precision.

  • If you already have the model, skip this step and simply export the MODELS_PATH and execute the hello_dlstreamer.sh script.

mkdir -p /home/${USER}/models
export MODELS_PATH=/home/${USER}/models
/opt/intel/dlstreamer/samples/download_public_models.sh yolo11s coco128

The hello_dlstreamer.sh will set up the required environment variables and runs a sample pipeline to confirm that Deep Learning Streamer is installed correctly. To run the hello_dlstreamer.sh script, execute the following command:

/opt/intel/dlstreamer/scripts/hello_dlstreamer.sh

NOTE: To set up Linux with the relevant environment variables every time a new terminal is opened, open ~/.bashrc and add the following lines:

  • Ubuntu 24

    export LIBVA_DRIVER_NAME=iHD
export GST_PLUGIN_PATH=/opt/intel/dlstreamer/lib:/opt/intel/dlstreamer/gstreamer/lib/gstreamer-1.0:/opt/intel/dlstreamer/streamer/lib/
export LD_LIBRARY_PATH=/opt/intel/dlstreamer/gstreamer/lib:/opt/intel/dlstreamer/lib:/opt/intel/dlstreamer/lib/gstreamer-1.0:/sr/lib:/opt/intel/dlstreamer/lib:/usr/local/lib/gstreamer-1.0:/usr/local/lib
export LIBVA_DRIVERS_PATH=/usr/lib/x86_64-linux-gnu/dri
export GST_VA_ALL_DRIVERS=1
export PATH=/opt/intel/dlstreamer/gstreamer/bin:/opt/intel/dlstreamer/bin:$PATH
export GST_PLUGIN_FEATURE_RANK=${GST_PLUGIN_FEATURE_RANK},ximagesink:MAX
export GI_TYPELIB_PATH=/opt/intel/dlstreamer/gstreamer/lib/girepository-1.0:/usr/lib/x86_64-linux-gnu/girepository-1.0

  • Ubuntu 22

    export LIBVA_DRIVER_NAME=iHD
export GST_PLUGIN_PATH=/opt/intel/dlstreamer/lib:/opt/intel/dlstreamer/gstreamer/lib/gstreamer-1.0:/opt/intel/dlstreamer/streamer/lib/
export LD_LIBRARY_PATH=/opt/intel/dlstreamer/gstreamer/lib:/opt/intel/dlstreamer/lib:/opt/intel/dlstreamer/lib/gstreamer-1.0:/sr/lib:/opt/intel/dlstreamer/lib:/usr/local/lib/gstreamer-1.0:/usr/local/lib:/opt/opencv:/opt/rdkafka
export LIBVA_DRIVERS_PATH=/usr/lib/x86_64-linux-gnu/dri
export GST_VA_ALL_DRIVERS=1
export PATH=/opt/intel/dlstreamer/gstreamer/bin:/opt/intel/dlstreamer/bin:$PATH
export GST_PLUGIN_FEATURE_RANK=${GST_PLUGIN_FEATURE_RANK},ximagesink:MAX
export GI_TYPELIB_PATH=/opt/intel/dlstreamer/gstreamer/lib/girepository-1.0:/usr/lib/x86_64-linux-gnu/girepository-1.0

  • Fedora 41

    export LIBVA_DRIVER_NAME=iHD
export GST_PLUGIN_PATH=/opt/intel/dlstreamer/lib:/opt/intel/dlstreamer/gstreamer/lib/gstreamer-1.0:/opt/intel/dlstreamer/gstreamer/lib/
export LD_LIBRARY_PATH=/opt/intel/dlstreamer/gstreamer/lib:/opt/intel/dlstreamer/lib:/opt/intel/dlstreamer/lib/gstreamer-1.0:/usr/lib:/opt/intel/dlstreamer/lib:/usr/local/lib/gstreamer-1.0:/usr/local/lib:/opt/opencv:/opt/rdkafka:/opt/ffmpeg
export LIBVA_DRIVERS_PATH=/usr/lib64/dri-nonfree
export GST_VA_ALL_DRIVERS=1
export PATH=/opt/intel/dlstreamer/gstreamer/bin:/opt/intel/dlstreamer/bin:$PATH
export GST_PLUGIN_FEATURE_RANK=${GST_PLUGIN_FEATURE_RANK},ximagesink:MAX
export GI_TYPELIB_PATH=/opt/intel/dlstreamer/gstreamer/lib/girepository-1.0:/usr/lib/x86_64-linux-gnu/girepository-1.0

    or run:

    source /opt/intel/dlstreamer/scripts/setup_dls_env.sh

    to configure environment variables for the current terminal session.

[Optional] Step 6: Auxiliary installation steps#

A. Check for installed packages and versions

apt list --installed | grep intel-dlstreamer

B. To install a specific version run the following command:

sudo apt install intel-dlstreamer=<VERSION>.<UPDATE>.<PATCH>

For example

sudo apt install intel-dlstreamer=2025.1.2

C. List available versions

sudo apt show -a intel-dlstreamer

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

Step 1: Installation of prerequisites#

Run the script DLS_install_prerequisites.sh to setup your environment. For more details see prerequisites.

./DLS_install_prerequisites.sh

Step 2: Installation of 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

Step 3: Allowing 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

NOTE: If you want to build Docker image from DLStreamer Dockerfiles, please follow the instructions.

Step 4: Pull the Deep Learning Streamer Docker image from Docker Hub#

Visit Deep Learning Streamer image docker hub to select the most appropriate version. By default , the latest docker image points to Ubuntu 24 version.

For Ubuntu 22.04 please specify tag e.g. 2025.1.2-ubuntu22. For Ubuntu 24.04 please use latest tag or specified version e.g. 2025.1.2-ubuntu24.

  • Ubuntu 22

    docker pull intel/dlstreamer:2025.1.2-ubuntu22

  • Ubuntu 24

    docker pull intel/dlstreamer:latest

Step 5: Run Deep Learning Streamer Pipeline Framework container#

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

  • Ubuntu 22

    docker run -it intel/dlstreamer:2025.1.2-ubuntu22

  • Ubuntu 24

    docker run -it intel/dlstreamer:latest

In the container, please run the gst-inspect-1.0 gvadetect to confirm that GStreamer and Deep Learning Streamer are running

gst-inspect-1.0 gvadetect

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

image

Next Steps#

You are ready to use Deep Learning Streamer. For further instructions to run sample pipeline(s), please go to the tutorial.

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