This sample demonstrates face detection and classification pipeline constructed via
gst-launch-1.0 command-line utility.
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
This sample builds GStreamer pipeline of the following elements
v4l2srcfor input from file/URL/web-camera
decodebinfor video decoding
videoconvertfor converting video frame into different color formats
fpsdisplaysinkfor rendering output video into screen
fpsdisplaysinkelement disables real-time synchronization so pipeline runs as fast as possible
The sample uses by default the following pre-trained models from OpenVINO™ Open Model Zoo
NOTE: Before running samples (including this one), run script
download_models.shonce (the script located in
samplestop 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.
If command-line parameter not specified, the sample by default streams video example from HTTPS link (utilizing
urisourcebin element) so requires internet conection. The command-line parameter INPUT_VIDEO allows to change input video and supports
rtsp://) or other streaming source (ex URL starting with