Human Pose Estimation Sample (gst-launch command line)

This sample demonstrates human pose estimation pipeline constructed via gst-launch-1.0 command-line utility.

How It Works

The sample utilizes GStreamer command-line tool gst-launch-1.0 which can build and run GStreamer pipeline described in a string format. The string contains a list of GStreamer elements separated by exclamation mark !, each element may have properties specified in the format property = value.

This sample builds GStreamer pipeline of the following elements

  • filesrc or urisourcebin or v4l2src for input from file/URL/web-camera

  • decodebin for video decoding

  • videoconvert for converting video frame into different color formats

  • gvaclassify uses for full-frame inference and post-processing of OpenPose’s output

  • gvawatermark for points and theirs connections visualization

  • fpsdisplaysink for rendering output video into screen


    sync=false property in fpsdisplaysink element disables real-time synchronization so pipeline runs as fast as possible

The sample uses by default the following pre-trained models from OpenVINO™ Toolkit Open Model Zoo

  • human-pose-estimation-0001 generates poses keypoints


Before running samples (including this one), run script once (the script located in samples top folder) to download all models required for this and other samples.

The sample contains model_proc subfolder with .json files for each model with description of model input/output formats and post-processing rules for classification models.



The sample takes three command-line optional parameters:

  1. [INPUT_VIDEO] to specify input video file.

    The input could be

  • 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 parameter is not specified, the sample by default streams video example from HTTPS link (utilizing urisourcebin element) so requires internet conection.

  1. [DEVICE] to specify device for detection and classification.

    Please refer to OpenVINO™ toolkit documentation for supported devices.

    You can find what devices are supported on your system by running following OpenVINO™ toolkit sample:

  2. [SINK_ELEMENT] to choose between render mode and fps throughput mode:

    • display - render (default)

    • fps - FPS only

Sample Output

The sample

  • prints gst-launch-1.0 full command line into console

  • starts the command and either visualizes video with people’s skeleton or prints out fps if you set SINK_ELEMENT = fps