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 property
=value
.
This sample builds GStreamer pipeline of the following elements
filesrc
or urisourcebin
or v4l2src
for input from file/URL/web-cameradecodebin
for video decodingvideoconvert
for converting video frame into different color formatsfpsdisplaysink
for rendering output video into screen NOTE:
sync=false
property infpsdisplaysink
element 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.sh
once (the script located insamples
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.
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
/dev/video0
)rtsp://
) or other streaming source (ex URL starting with http://
)The sample