github roflcoopter/viseron v1.6.0.b1
1.6.0b1 - Face recognition and MQTT changes

latest releases: v3.0.0b11, v3.0.0b10, v3.0.0b9...
pre-release4 years ago

Breaking changes

  • Detectors now supply their own configuration validators which might break existing configs.
    If you used type: edgetpu and supplied an unsupported configuration option, such as suppression,
    Viseron would think that was okay. That is no longer the case and has to be removed.
    The README is updated accordingly.
  • A new config block has been created for Home Assistant Discovery. It is still enabled by default but if you previously set your own discovery_prefix you now have to move this under home_assistant like this:
    mqtt:
      broker: <ip address or hostname of broker>
      port: <port the broker listens on>
      home_assistant:
        discovery_prefix: <yourcustomprefix>
  • Pretty much all MQTT topics have changed. Have a look at the updated documentation to see how they are structured.

Changes and new Features

  • Face detection is here! See the documentation for how to set this up.
    Here is an example config to get you started
    object_detection:
      labels:
        - label: person
          confidence: 0.8
          post_processor: face_recognition
    
    post_processors:
      face_recognition:
  • Unique ID and Device registry information is now included in the Home Assistant discovery setup.
    This means that you can now customize the entities created in Home Assistant via its interface.
  • The binary sensors created for each label now includes a count attribute which tells you the number of detected objects.
  • Include support for h265 in ffmpeg for all containers
  • vaapi and generic image now default to YOLOv3 model.
    Previously the default was YOLOv3-tiny, which is a lot faster but very inaccurate.
    If you wanna go back to using the tiny version for the sake of reduced CPU you can change these settings:
    object_detection:
      model_path: /detectors/models/darknet/yolov3-tiny.weights
      model_config: /detectors/models/darknet/yolov3-tiny.cfg
  • Labels drawn on the image that is sent when publish_image: true is now clearer

Fixes

  • Fix a crash when publish_image: true and trigger_detector: false
  • Fix interval under motion_detection and object_detection not allowing floats

Docker images are available on Docker Hub
roflcoopter/viseron:1.6.0b1
roflcoopter/viseron-cuda:1.6.0b1
roflcoopter/viseron-vaapi:1.6.0b1
roflcoopter/viseron-rpi:1.6.0b1

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