Starting Reidentifier

Starts reidentification on the frames of a previously configured video stream.

Prerequisites

It is assumed that Multi-Graph Runner (MGR) is running in fve mode, because feature vector records are necessary input. For more information on running MGR, see Starting Multi-Graph Runner.

Required input topics:

• If only one [STREAM_URI] was specified during configuration:

  fve.cam.0.fvecs.FeatureVectorRecord.json
  

  In this case, both registration and reidentification takes place in this process

• If multiple [STREAM_URI] were specified during configuration:

  fve.cam.0.fvecs.FeatureVectorRecord.json
  fve.cam.1.fvecs.FeatureVectorRecord.json
  ...
  

  In this case, the processor runs reidentification based on the feature vectors of reidentification topic (for example, cam.1), and collects the registration based on the feature vectors of registration topics (for example, cam.0).

For information on Reidentifier configuration, see Configuring Reidentifier.

Starting the Reidentifier service

To start Reidentifier:

1. Run the microservice

   Attention! Before starting this microservice, the command below silently stops and removes the Docker container named uvap_kafka_reid, if such already exists.

   $ "${UVAP_HOME}"/scripts/run_kafka_reid.sh -- --net=uvap
   

   The output of the above command contains the following:

   • Information about pulling the required Docker image
   • The ID of the Docker container created
   • The name of the Docker container created: uvap_kafka_reid

   There are more optional parameters for the run_kafka_reid.sh script to override defaults. Use the --help parameter to get more details.

2. Check if the uvap_kafka_reid container is running:

   $ docker container inspect --format '{{.State.Status}}' uvap_kafka_reid
   

   Expected output:

   running
   

   Note: If the status of the UVAP container is not running, send the output of the following command to support@ultinous.com:

   $ docker logs uvap_kafka_reid
   

   These Docker containers can be managed with standard Docker commands. For more information, see docker (base command) in docker docs.

3. Check if the fve.cam.99.reids.ReidRecord.json topic is created:

   $ docker exec kafka kafka-topics --list --zookeeper zookeeper:2181
   

   Expected output contains the following:

   fve.cam.99.reids.ReidRecord.json
   

4. Fetch data from the Kafka topic:

   $ docker exec kafka kafka-console-consumer \
     --bootstrap-server kafka:9092 \
     --topic fve.cam.99.reids.ReidRecord.json
   

The following output topic is created:

fve.cam.99.reids.ReidRecord.json

This is an aggregated topic, consuming feature vectors from every cameras and producing a single topic containing registration and reidentification entries.