Start MQTT Publisher in Vision AI Detection Apps#

Bring the services up.

Note: If you are running multiple instances of the application, start the services using ./run.sh up instead.

docker compose up -d

The below CURL command publishes metadata to the MQTT broker and sends frames over WebRTC for streaming.

Assuming broker is running in the same host over port 1883, replace the <HOST_IP> field with your system IP address. WebRTC Stream will be accessible at https://<HOST_IP>/mediamtx/mqttstream/.

Note: If you are running multiple instances of the application, ensure to provide NGINX_HTTPS_PORT number in the URL for the app instance, i.e., replace <HOST_IP> with <HOST_IP>:<NGINX_HTTPS_PORT> If you are running a single instance and using an NGINX_HTTPS_PORT other than the default 443, replace <HOST_IP> with <HOST_IP>:<NGINX_HTTPS_PORT>.

curl -k https://<HOST_IP>/api/pipelines/user_defined_pipelines/pallet_defect_detection_mqtt -X POST -H 'Content-Type: application/json' -d '{
   "source": {
       "uri": "file:///home/pipeline-server/resources/videos/warehouse.avi",
       "type": "uri"
   },
   "destination": {
       "metadata": {
           "type": "mqtt",
           "publish_frame":true,
           "topic": "pallet_defect_detection"
       },
       "frame": {
           "type": "webrtc",
           "peer-id": "mqttstream",
           "overlay": false
       }
   },
   "parameters": {
       "detection-properties": {
           "model": "/home/pipeline-server/resources/models/pallet-defect-detection/deployment/Detection/model/model.xml",
           "device": "CPU"
       }
   }
}'

curl -k https://<HOST_IP>/api/pipelines/user_defined_pipelines/pcb_anomaly_detection_mqtt -X POST -H 'Content-Type: application/json' -d '{
   "source": {
       "uri": "file:///home/pipeline-server/resources/videos/anomalib_pcb_test.avi",
       "type": "uri"
   },
   "destination": {
       "metadata": {
           "type": "mqtt",
           "publish_frame":true,
           "topic": "pcb_anomaly_detection"
       },
       "frame": {
           "type": "webrtc",
           "peer-id": "mqttstream",
           "overlay": false
       }
   },
   "parameters": {
       "classification-properties": {
           "model": "/home/pipeline-server/resources/models/pcb-anomaly-detection/deployment/Anomaly classification/model/model.xml",
           "device": "CPU"
       }
   }
}'

In the above curl command set publish_frame to false if you do not want frames sent over MQTT. Metadata will be sent over MQTT.

Output can be viewed on MQTT subscriber as shown below.

docker run -it --rm \
 --network industrial-edge-insights-vision_industrial-edge-vision \
 --entrypoint mosquitto_sub \
 eclipse-mosquitto:latest \
 -h mqtt-broker -p 1883 -t pallet_defect_detection

# Note:
# Update --network above if it is different in your execution. Network can be found using: docker network ls
# Update --network as <INSTANCE_NAME>_industrial-edge-vision for multi-instance setup

docker run -it --rm \
 --network industrial-edge-insights-vision_industrial-edge-vision \
 --entrypoint mosquitto_sub \
 eclipse-mosquitto:latest \
 -h mqtt-broker -p 1883 -t pcb_anomaly_detection

# Note:
# Update --network above if it is different in your execution. Network can be found using: docker network ls
# Update --network as <INSTANCE_NAME>_industrial-edge-vision for multi-instance setup

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