How to change Deep Learning Streamer pipeline

Steps

DL Streamer Pipeline Server supports dynamic update of pipeline parameters using REST API. Users are required to provide required placeholders in [WORKDIR]/configs/default/config.json to make it configurable at run-time of DL Streamer Pipeline Server container. Follow instruction in the Prerequisite section to create a sample configuration file.

In case users want to update default pipeline, they need to update the same in configuration file that DL Streamer Pipeline Server loads. Users can mount updated config files from host systems on to DL Streamer Pipeline Server containers by updating [WORKDIR]/docker/docker-compose.yml. To get you started, instruction to create sample docker compose file is available here. Refer below snippets:

    volumes:
      # Volume mount [WORDDIR]/configs/default/config.json to config file that DL Streamer Pipeline Server container loads."
      - "../configs/default/config.json:/home/pipeline-server/config.json"

As an example we are creating video-ingestion and resize pipeline. We need to update pipeline key in [WORKDIR]/configs/default/config.json as shown below. It would create DL Streamer pipeline that reads user provided video file, decodes it, and resize to 1280x720. Note: Follow instruction in the Prerequisite section to create a sample configuration file.

"pipeline": "{auto_source} name=source  ! decodebin ! videoscale ! video/x-raw, width=1280,height=720 ! gvametapublish name=destination ! appsink name=appsink",

Note: If needed users can change pipeline name by updating name key in config.json. If user is updating this field, accordingly endpoint in curl request needs to be changed to <SERVER-IP>:<PORT>/pipelines/user_defined_pipelines/<NEW-NAME>. In this example, we are only changing pipeline.

Once update, user needs to restart DL Streamer Pipeline Server containers to reflect this change. Run these commands from [WORKDIR]/docker/ folder. Note: To get you started, instruction to create sample docker compose file is available here

docker compose down

docker compose up

Above steps will restart DL Streamer Pipeline Server and load video-ingestion and resize pipeline. Now to start this pipeline, run below Curl request. It would start DL Streamer pipeline that reads classroom.avi video file with resolution of 1920x1080 and after resizing to 1280x720, it would stream over RTSP. Users can view this on any media player e.g. vlc, ffplay etc.

RTSP Stream will be accessible at rtsp://<SYSTEM_IP_ADDRESS>:8554/classroom-video-streaming.

curl localhost:8080/pipelines/user_defined_pipelines/pallet_defect_detection -X POST -H 'Content-Type: application/json' -d '{
                "source": {
                    "uri": "file:///home/pipeline-server/resources/videos/classroom.avi",
                    "type": "uri"
                },
                "destination": {
                   "metadata": {
                        "type": "file",
                        "path": "/tmp/results.jsonl",
                        "format": "json-lines"
                    },
                    "frame": {
                        "type": "rtsp",
                        "path": "classroom-video-streaming"
                    }
                }
}'