Close feedback loop

[dcmartin]

1. Close feedback loop from front-end (end-user interaction) to annotation capture and curation platform.
   a. Enable labelstud.io as additional Home Assistant add-on [X]
   b. Enable min.io as additional Home Assistant add-on [X]
   c. Enable end-user feedback through HA persistent_notification with link to yes/no, including all relevant metadata [X]
   d. Capture feedback from MQTT topic, store object in minio and store metadata in labelstudio add-ons

2. Present captured feedback for end-user interaction
   a. review & approve
   b. inspect, create, update, delete putative annotations

3. Present training results
   a. review & approve
   b. inspect, delete training results

4. Deploy updated trained models
   a. Add modelmanager service to control OH edge-sync-service
   b. Add hzn::ess and hzn::modmgr SDK components to base containers
   c. Modify AI containers to utilize hzn::modmgr SDK for model weights, labels, etc..

[dcmartin]

1. Completed end-user interaction for Home Assistant to notify through standard persistent notifications.
2. Added functionality to Motion Classic add-on to provide API to respond to predict.yes and predict.no which bundle up jpeg, mp4, and metadata for non-legacy events and post to MQTT as <group>/predict/{yes,no}

[dcmartin]

3. Implemented labelstudio add-on for Home Assistant as OH service base with bashio extensions; amd64
4. Implemented minio add-on for HA as OH service using base with bashio extensions; amd64 and aarch64