DL Streamer Samples

Samples are simple applications that demonstrate how to use the DL Streamer. The samples are available in the <INSTALL_DIR>/data_processing/dl_streamer/samples directory.

Samples separated into several categories

  1. gst_launch command-line samples (samples construct GStreamer pipeline via gst-launch-1.0 command-line utility)

  2. C++ samples

  3. Python samples

  4. Benchmark

    • Benchmark Sample - measures overall performance of single-channel or multi-channel video analytics pipelines

How To Build And Run

Samples with C/C++ code provide build_and_run.sh shell script to build application via cmake before execution.

Other samples (without C/C++ code) provide .sh script for constucting and executing gst-launch or Python command line.

DL Models

DL Streamer samples use pre-trained models from OpenVINO™ Toolkit Open Model Zoo

Before running samples, run script download_models.sh once to download all models required for samples. The script located in samples top folder.


To install all necessary requirements for download_models.sh script run this command:

pip3 install -r $INTEL_OPENVINO_DIR/deployment_tools/open_model_zoo/tools/downloader/requirements.in

Input video

First command-line parameter in DL Streamer samples specifies input video and supports

  • local video file

  • web camera device (ex. /dev/video0)

  • RTSP camera (URL starting with rtsp://) or other streaming source (ex URL starting with `http:// <http://>`__)

If command-line parameter not specified, most samples by default stream video example from predefined HTTPS link, so require internet conection.


Most samples set property sync=false in video sink element to disable real-time synchronization and run pipeline as fast as possible. Change to sync=true to run pipeline with real-time speed.