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Metadata Publishing Sample (gst-launch command line)

This sample demonstrates how gvametaconvert and gvametapublish elements are used in a typical pipeline constructed with Intel® Deep Learning Streamer (Intel® DL Streamer) and GStreamer elements. By placing these elements to the end of a pipeline that performs face detection and emotion classification, you will quickly see how these elements enable publishing of pipeline metadata to an output file, in-memory fifo, or a popular message bus.

These elements are useful for cases where you need to record outcomes (e.g., emitting inferences) of your Intel® DL Streamer pipeline to applications running locally or across distributed systems.

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.

Overall 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
  • gvadetect for detecting faces using the OpenVINO™ Toolkit Inference Engine
  • gvaclassify for recognizing the age and gender of detected faces using the the OpenVINO™ Toolkit Inference Engine.
  • gvametaconvert for conversion of tensor and inference metadata to JSON format.
  • gvametapublish for publishing the JSON metadata as output to console, file, fifo, MQTT or Kafka.
  • fakesink to terminate the pipeline output without actually rendering video frames.

NOTE: The sample sets property 'json-indent=4' in gvametaconvert element for generating JSON in pretty print format with 4 spaces indent. Remove this property to generate JSON without pretty print.

Models

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

  • face-detection-adas-0001 is primary detection network for detecting faces that appear within video frames.
  • age-gender-recognition-retail-0013 classifies age and gender of detected face(s).

NOTE: Before running samples (including this one), run script download_models.sh 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.

Running

This sample takes up to four command-line parameters. If no parameters specified, the sample displays pretty printed JSON messages to console (METHOD=file, OUTPUT=stdout)

NOTE: Before running this sample with output to MQTT or Kafka, refer to this page how to set up a MQTT or Kafka listener to consume and review results in the console.

```sh
./metapublish.sh [INPUT] [METHOD] [OUTPUT] [FORMAT] [TOPIC]
```
  1. [INPUT] is full path to the source video. The input could be
    • URI to web based streaming source (Default)
    • local video file path
    • path to RTSP camera (URL starts with rtsp://)
    • web camera device (ex. /dev/video0)
  2. [METHOD] to specify which output method to use when publishing inferences. The method could be
    • file (Default)
    • kafka
    • mqtt
  3. [OUTPUT] Indicates the path to the 'file' or to specify the address of message bus broker. By default this is
    • stdout (Default if METHOD is File)
    • localhost:1883 (Default if METHOD is MQTT)
    • localhost:9092 (Default if METHOD is Kafka)
  4. [FORMAT] Passed to property 'file-format' in 'gvametapublish', could be
    • json
    • json-lines
  5. [TOPIC] (used only if METHOD is MQTT or Kafka) to specify the message bus topic to publish:
    • dlstreamer (Default)

Examples

  1. Launch sample with no parameters to see stdout with pretty json.

    ./metapublish.sh

  2. Override the file or absolute path of output file.

    ./metapublish.sh https://github.com/intel-iot-devkit/sample-videos/raw/master/head-pose-face-detection-female-and-male.mp4 \
file /tmp/output_inferences.json

  3. Output results to MQTT broker running at localhost:1883 with your listener subscribed to 'dlstreamer' topic.

    ./metapublish.sh https://github.com/intel-iot-devkit/sample-videos/raw/master/head-pose-face-detection-female-and-male.mp4 mqtt

Sample Output

The sample

  • prints gst-launch command line into console
  • starts the command and emits inference events that include the evaluated age and gender for each face detected within video input frames.

See also