[Support]:

Describe the problem you are having

I have upgraded to the newest version today and I have a setup where Home Assistant pushes me a notification when an object has been detected. The new version has Stationary objects feature. At the moment I don’t have any use for it but I think there will be some use cases when I have time to think about it! So, thank you for that but it’s making me trouble:

There a two stationary cars from my neighbour at the moment . One of them is causing me headache. It’s usually not there all the time but today it is. It’s a silver one (side view). Unfortunately I can’t post the picture of the car (privacy), but it’s 15 meters away from my cam. Another dark blue car (front view) is 5 meters to the right of the silver one This isn’t making any trouble.

I have set contour_area: 125 and also tried up to 1000.

The area where the two cars are is also completely masked.

I don’t know hot to solve that issue. So I have to deactivate frigate for now. My config worked for more than 6 months now without such an issue.

Thank you for your time and help!

Version

0.10.0-BFECEE9

Frigate config file

detectors:
  coral:
    type: edgetpu
    device: usb

cameras:
  hof:
    ffmpeg:
      inputs:
        # Main stream (1920x1080)
        - path: ***
          roles:
            - record
            - rtmp
        # Sub stream (640x352)
        - path: ***
          roles:
            - detect
    motion:
      contour_area: 125 # reduce the sensitivity for motion detection
    detect:
      width: 640
      height: 352
      fps: 5
    #record:
      # Optional: Enable recording (default: shown below)
      #enabled: True
    #snapshots:
      #enabled: True
      # Optional: Configuration for stationary object tracking
      stationary:
        # Optional: Frequency for running detection on stationary objects (default: shown below)
        # When set to 0, object detection will never be run on stationary objects. If set to 10, 
        # it will be run on every 10th frame.
        interval: 0
        # Optional: Number of frames without a position change for an object to be considered 
        # stationary (default: 10x the frame rate or 10s)
        threshold: 50
        # Optional: Define a maximum number of frames for tracking a stationary object (default: not set, track forever)
        # This can help with false positives for objects that should only be stationary for a limited amount of time.
        # It can also be used to disable stationary object tracking. For example, you may want to set a value for person,
        # but leave car at the default.
        max_frames:
          # Optional: Default for all object types (default: not set, track forever)
          default: 3000
          # Optional: Object specific values
          objects:
            person: 1000

  doorbird:
    ffmpeg:
      inputs:
        # It's not possible to run two seperate streams from a doorbird!
        # Main stream (1920x1080)
        # - path: ***
        #   roles:
        # Sub stream (1280x720)
        - path: ***
          roles:
            - detect
            - record
            - rtmp
    motion:
      mask:
        - 1280,0,1280,315,1280,521,1020,459,740,473,378,454,374,317,437,315,435,289,0,147,0,0,625,0
      # reduce the sensitivity for motion detection
      contour_area: 125 
    detect:
      width: 1280
      height: 720
      fps: 5
      # Optional: Configuration for stationary object tracking
      stationary:
        # Optional: Frequency for running detection on stationary objects (default: shown below)
        # When set to 0, object detection will never be run on stationary objects. If set to 10, 
        # it will be run on every 10th frame.
        interval: 0
        # Optional: Number of frames without a position change for an object to be considered 
        # stationary (default: 10x the frame rate or 10s)
        threshold: 100
        # Optional: Define a maximum number of frames for tracking a stationary object (default: not set, track forever)
        # This can help with false positives for objects that should only be stationary for a limited amount of time.
        # It can also be used to disable stationary object tracking. For example, you may want to set a value for person,
        # but leave car at the default.
        max_frames:
          # Optional: Default for all object types (default: not set, track forever)
          default: 3000
          # Optional: Object specific values
          objects:
            person: 1000

objects:
  track:
    - car
    - person
    - bicycle
  filters:
    person:
      # Optional: minimum width*height of the bounding box for the detected object (default: 0)
      min_area: 5000
      # Optional: maximum width*height of the bounding box for the detected object (default: 24000000)
      max_area: 100000
      # Optional: minimum score for the object to initiate tracking (default: shown below)
      min_score: 0.5
      # Optional: minimum decimal percentage for tracked object's computed score to be considered a True positive (default: shown below)
      threshold: 0.7

# Optional: Record configuration
# NOTE: Can be overridden at the camera level
record:
  # Optional: Enable recording (default: shown below)
  enabled: True
  # Optional: Number of days to retain recordings regardless of events (default: shown below)
  # NOTE: This should be set to 0 and retention should be defined in events section below
  #       if you only want to retain recordings of events.
  retain:
    days: 7
    mode: motion
  # Optional: Event recording settings
  events:
    # Optional: Maximum length of time to retain video during long events. (default: shown below)
    # NOTE: If an object is being tracked for longer than this amount of time, the retained recordings
    #       will be the last x seconds of the event unless retain_days under record is > 0.
    max_seconds: 300
    # Optional: Number of seconds before the event to include (default: shown below)
    pre_capture: 5
    # Optional: Number of seconds after the event to include (default: shown below)
    post_capture: 5
    # Optional: Objects to save recordings for. (default: all tracked objects)
    # objects:
      # - person
    # Optional: Restrict recordings to objects that entered any of the listed zones (default: no required zones)
    # required_zones: []
    # Optional: Retention settings for recordings of events
    retain:
      # Required: Default retention days (default: shown below)
      default: 10
      mode: active_objects

snapshots:
  # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
  # This value can be set via MQTT and will be updated in startup based on retained value
  enabled: True
  # Optional: print a timestamp on the snapshots (default: shown below)
  timestamp: False
  # Optional: draw bounding box on the snapshots (default: shown below)
  bounding_box: False
  # Optional: crop the snapshot (default: shown below)
  crop: False
  # Optional: height to resize the snapshot to (default: original size)
  height: 175
  # Optional: Restrict snapshots to objects that entered any of the listed zones (default: no required zones)
  required_zones: []
  # Optional: Camera override for retention settings (default: global values)
  retain:
    # Required: Default retention days (default: shown below)
    default: 10
    # Optional: Per object retention days
    objects:
      person: 15

Relevant log output

---

FFprobe output from your camera

# ffprobe rtsp://***
ffprobe version 4.3.1 Copyright (c) 2007-2020 the FFmpeg developers
  built with gcc 9 (Ubuntu 9.3.0-17ubuntu1~20.04)
  configuration: --disable-debug --disable-doc --disable-ffplay --enable-shared --enable-avresample --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-gpl --enable-libfreetype --enable-libvidstab --enable-libmfx --enable-libmp3lame --enable-libopus --enable-libtheora --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libxcb --enable-libx265 --enable-libxvid --enable-libx264 --enable-nonfree --enable-openssl --enable-libfdk_aac --enable-postproc --enable-small --enable-version3 --enable-libzmq --extra-libs=-ldl --prefix=/opt/ffmpeg --enable-libopenjpeg --enable-libkvazaar --enable-libaom --extra-libs=-lpthread --enable-vaapi --extra-cflags=-I/opt/ffmpeg/include --extra-ldflags=-L/opt/ffmpeg/lib
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
  libpostproc    55.  7.100 / 55.  7.100
Input #0, rtsp, from 'rtsp://***':
  Metadata:
    title           : RTSP/RTP stream from DoorBird
    comment         : mpeg/1080p/media.amp
  Duration: N/A, start: 0.094633, bitrate: N/A
    Stream #0:0: Video: h264, yuvj420p(pc, bt709, progressive), 1920x1080, 10 fps, 10 tbr, 90k tbn, 180k tbc

Frigate stats

{"detection_fps":0.0,"detectors":{"coral":{"detection_start":0.0,"inference_speed":9.09,"pid":221}},"doorbird":{"camera_fps":5.0,"capture_pid":234,"detection_fps":0.0,"pid":230,"process_fps":5.0,"skipped_fps":0.0},"hof":{"camera_fps":5.1,"capture_pid":232,"detection_fps":0.0,"pid":228,"process_fps":5.1,"skipped_fps":0.0},"service":{"storage":{"/dev/shm":{"free":5366.0,"mount_type":"tmpfs","total":5368.7,"used":2.7},"/media/frigate/clips":{"free":5101658.4,"mount_type":"fuse.shfs","total":11997243.4,"used":6895584.9},"/media/frigate/recordings":{"free":5101658.4,"mount_type":"fuse.shfs","total":11997243.4,"used":6895584.9},"/tmp/cache":{"free":7337.1,"mount_type":"rootfs","total":8297.5,"used":960.4}},"temperatures":{},"uptime":53,"version":"0.10.0-bfecee9"}}

Operating system

UNRAID

Install method

Docker Compose

Coral version

USB

Network connection

Wired

Camera make and model

Doorbird D1101V

Any other information that may be helpful

I am using this Home Assistant config to push notifications when objects appear:

alias: Notification, Motion, Cam - Frigate object detected
trigger:
  - platform: mqtt
    topic: frigate/events
condition:
  - condition: state
    entity_id: input_boolean.disable_camera_hof_motion_notification_door_open
    state: 'off'
  - condition: state
    entity_id: input_boolean.disable_camera_hof_motion_notification
    state: 'off'
action:
  - service: notify.mobile_app_iphone_12_pro_max
    data_template:
      message: Ein {{trigger.payload_json["after"]["label"]}} wurde erkannt.
      data:
        image: >-
          https://***/api/frigate/notifications/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg?format=android
        tag: '{{trigger.payload_json["after"]["id"]}}'
        url: /lovelace/kameras
        clickAction: /lovelace/kameras
  - delay:
      hours: 0
      minutes: 0
      seconds: 30
      milliseconds: 0
mode: single

[NickM-27]

@Coolie1101

It’s documented here: https://docs.frigate.video/configuration/masks/#further-clarification

and here: https://docs.frigate.video/guides/stationary_objects/

[blakeblackshear]

I’m not sure why you are getting notifications there. You should look at the automation trace tools to see what is happening.