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[tombox]

@hagst probier mal die GitHub version ob das da geht

[hagst]

@tombox sagte in Frigate Adapter für ioBroker:

probier mal die GitHub version

Gerade mal neu installiert, jetzt muss ich warten bis jemand vor der Kamera rumrennt, hier regnet es und ich will nicht nass werden

[tombox]

@hagst Bitte nochmal installieren
@QuesT bitte mal die GitHub installieren die könnten mit iobroker.ntfy oder iobroker.gotify funktionieren

[hagst]

@tombox

Mir ist gerade wieder etwas aufgefallen.
Ich habe um den Fehler nachvollziehen zu können, nochmal die Version 1.0.0 installiert.

In der Version 1.0.0 wird der detaillierte Screenshot per Telegram versendet. Nach einem Update auf die 1.0.2 wird er nicht mehr gesendet.
Nach einem downgrade auf die 1.0.0 wird er wieder versendet. Der andere Fehler ist mit der De- und Neuinstallation verschwunden.

[tombox]

@hagst Danke für den Hinweis bitte nochmal GitHub version testen

[hagst]

@tombox sagte in Frigate Adapter für ioBroker:

nochmal GitHub version testen

Klappt, jetzt kommt auch in der GitHub Version der detaillierte Screenshot per Telegram. Was mir noch aufgefallen ist (ich hoffe es nervt nicht). ist der Text der Meldung unter den Screenshots bei Telegram:
In der original Config wurde, bis auf die mqtt Einstellungen, nichts verändert.

Bildunterschrift bei den normalen Screenshots: "Terrasse person erkannt end 0.84375"
Bildunterschrift bei den detaillierte Screenshots:Terrasse person erkannt undefined undefined"
Bildunterschift unter den Videoclips: Terrasse person erkannt end 0.84375"

Vielleicht verschwindet ja das undefined, wenn der ioBroker / frigate neu gestartet wurde, mal schauen.

Edit:
Neustart vom ioBroker und frigate:

[tombox]

@hagst ist korrigiert

[hagst]

@tombox sagte in Frigate Adapter für ioBroker:

ist korrigiert

Sieht gut aus.

[QuesT]

@tombox

2024-02-04 11:45:40.075 - error: ntfy.0 (1189) Ntfy error: AxiosError: Request failed with status code 400
2024-02-04 11:45:40.075 - error: ntfy.0 (1189) Ntfy error: {"code":40009,"http":400,"error":"invalid request: topic invalid"}
2024-02-04 11:45:40.075 - error: ntfy.0 (1189) Ntfy with config: {}

[tombox]

@quest was wäre denn eine korrekte topic

[QuesT]

@tombox

Hatte nur kein standart Topic gesetzt im Adapter. Geht nun aber es wird kein Bild mitgesendet.

cam1 person erkannt end 0.80859375

/tmp/8d9cb83e-3f51-44b5-b704-0af816bbcabe.jpg

[Tschaeens]

@tombox

Erstmal danke für das Update. Bei mir läuft alles tiptop. Ich würde gern den Wert motion weiterverarbeiten. Leider geht dieser bei jedem motion auf ON. Gibt es einen state der nur auf ON geht, wenn Frigate eine Person erkennt und der Wert über meinen eingestellten Wert ist? Also dann wenn Frigate auch einen snapshot erstellt. Danke dir.

VG

[tombox]

@quest kann der adapter denn Bilder verarbeiten?

[tombox]

@tschaeens

Es gib Anzahl der personen
frigate.0.camera.person
oder halt
frigate.0.events.after.label = person

[Tschaeens]

@tombox
danke! Genau danach habe ich gesucht.

[PrinzEisenherz1]

Hi zusammen.
Ich habe da mal ne frage. Ihr nutzt bestimmt die frigate Version 0.13?
Für mich gäbe es da eine interessante interessante Neuerung.
Das manuelle Triggern von Aufnahmen.

https://docs.frigate.video/integrations/api

Hat das von euch schon mal jemand ausprobiert?
Wird die Möglichkeit zum manuellen Auslösen einer Aufnahme im frigate-Adapter integriert?

Gruß
Johnny

[bongsao]

Hallo,
zuerst mal Danke für die tolle Arbeit. Der Adapter läuft so weit und macht was er soll. Beim Erstellen einer Vis ist mir aufgefallen, das in den History-Einträgen die Timestrings start_time und end_time fehlerhaft sind. Das sind Kommazahlen. Wenn man rundet, passt es. Das ist halt nur in der Vis ein riesen Aufwand. Ich gehe davon aus, dass das auch so nicht erwünscht ist.
Ansonsten läuft alles super stabil.

Gruß

[tombox]

@bongsao In der Vis kannst du es mit dem widget Timestamp anzeigen
@PrinzEisenherz1 bitte GitHub version testen camera.remote.createEvent

[bongsao]

@tombox
Danke, muss ich ne neue Version installieren. Die stable 1.02 funktioniert ja nicht.

[PrinzEisenherz1]

Hi @tombox erstmal danke das Du das in den Adapter integriert hast und für den tollen Adapter.
Aber irgendwas funktioniert da bei mir nicht so richtig.
Das triggern einer Aufnahme erfolgt wenn ich z.B. das Label ändere, richtig?
Wie ist denn mit den neu erzeugten Datenpunkten für das manuelle Recording verfahren?
Wie befülle ich dann den Body? z.B. duration, usw
Wenn ich den Body wie beim Beispiel von frigate befülle

{
  "sub_label": "some_string", // add sub label to event
  "duration": 30, // predetermined length of event (default: 30 seconds) or can be to null for indeterminate length event
  "include_recording": true, // whether the event should save recordings along with the snapshot that is taken
  "draw": {
    // optional annotations that will be drawn on the snapshot
    "boxes": [
      {
        "box": [0.5, 0.5, 0.25, 0.25], // box consists of x, y, width, height which are on a scale between 0 - 1
        "color": [255, 0, 0], // color of the box, default is red
        "score": 100 // optional score associated with the box
      }
    ]
  }
}

dann bekomme ich in ioBroker folgende Fehlermeldung

frigate.0 2024-02-23 16:33:59.932	error	SyntaxError: Unexpected number in JSON at position 128
frigate.0 2024-02-23 16:33:59.931	error	Cannot parse createEventBody. Please use valid JSON https://docs.frigate.video/integrations/api/#post-apieventscamera_namelabelcreate

Es wird zwar eine Aufnahme gestartet, diese ist aber fehlerhaft.
Die lässt sich nicht abspielen. Da kommt n weißes X.
Wenn ich sie herunterladen möchte dann wird ein clips.json downgeloadet.
Der erzeugte Snapshot wird aber richtig erstellt.
Muss ich da eventuell noch an meiner Config was einstellen?
Hier mal meine config.yml

Spoiler

database:
    path: /db/frigate.db
mqtt:
  host: 192.168.122.25
  port: 2083
detectors:
    coral:
        type: edgetpu
        device: usb
go2rtc:
  streams:
    haustuer_cam: 
      - rtsp://XXXXXXXXX@192.168.122.15:88/videoMain
      - "ffmpeg:haustuer_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
    haustuer_cam_sub:
      - rtsp://XXXXXXXXX@192.168.122.15:88/videoSub # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
      - "ffmpeg:haustuer_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
    garage_cam: 
      - rtsp://XXXXXXXXX@192.168.122.19:554/h264Preview_01_main
      - "ffmpeg:garage_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
    garage_cam_sub:
      - rtsp://XXXXXXXXX@192.168.122.19:554/h264Preview_01_sub # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
      - "ffmpeg:garage_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
    garten_cam: 
      - rtsp://XXXXXXXXX@192.168.122.17:88/videoMain
      - "ffmpeg:garten_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
    garten_cam_sub:
      - rtsp://XXXXXXXXX@192.168.122.17:88/videoSub # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
      - "ffmpeg:garten_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
    garten_links_cam: 
      - rtsp://XXXXXXXXX@192.168.122.16/11
      - "ffmpeg:garten_links_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
    garten_links_cam_sub:
      - rtsp://XXXXXXXXX@192.168.122.16/12 # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
      - "ffmpeg:garten_links_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
    wohnzimmer_cam: 
      - rtsp://XXXXXXXXX@192.168.122.18:88/videoMain
      - "ffmpeg:wohnzimmer_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
    wohnzimmer_cam_sub:
      - rtsp://XXXXXXXXX@192.168.122.18:88/videoSub # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
      - "ffmpeg:wohnzimmer_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
ffmpeg:
    output_args:
        record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy
    hwaccel_args: # This is the section for the H/W Accelaration, you will need to figure out what settings you need to enable - https://docs.frigate.video/configuration/hardware_acceleration
        #- -hwaccel
        #- qsv
        #- -qsv_device
        #- /dev/dri/renderD128
        - -hwaccel
        - vaapi 
        - -hwaccel_device
        - /dev/dri/renderD128 
        #- -hwaccel_output_format
        #- yuv420p
        #- -hwaccel
        #- vaapi
        #- -hwaccel_device
        #- /dev/dri/renderD128
        #- -hwaccel_output_format
        #- yuv420p
record: # how long to record before and after motion
    events:
        pre_capture: 7
        post_capture: 10
cameras:
  haustuer: # <------ Name the camera
    ffmpeg:
      hwaccel_args: preset-vaapi
      output_args:
        record: preset-record-generic-audio-copy
      inputs:
        - path: rtsp://127.0.0.1:8554/haustuer_cam_sub # <----- The stream you want to use for detection
          roles:
            - detect
        - path: rtsp://127.0.0.1:8554/haustuer_cam
          roles:
            - record
            - rtmp
    rtmp:
      enabled: false # <-- RTMP should be disabled if your stream is not H264
    detect:
      enabled: True # <---- disable detection until you have a working camera feed
      width: 1280 # <---- update for your camera's resolution
      height: 720 # <---- update for your camera's resolution
      fps: 5
    objects:
      track:
        - person
        - car
        - dog
        - cat
      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: mask to prevent this object type from being detected in certain areas (default: no mask)
          # Checks based on the bottom center of the bounding box of the object
          #mask: 0,0,1000,0,1000,200,0,200
    record: # what you want Frigate to record
        enabled: True
        #retain: # uncomment this section if you want Frigate to record this camera 24/7. This can use a lot of space, you have been warned!
          #days: 1
          #mode: all
        events: # this is the default recording mode where events are recorded, the number of days it saves events for is 10.
            retain:
                mode: active_objects
                default: 10
    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: true
      # 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
    motion:
      mask:
        - 858,215,847,176,746,145,754,115,557,74,528,34,396,37,297,38,349,720,0,720,0,0,1280,0,1280,370

  garage: # <------ Name the camera
    ffmpeg:
      hwaccel_args: preset-vaapi
      output_args:
        record: preset-record-generic-audio-copy
      inputs:
        - path: rtsp://127.0.0.1:8554/garage_cam_sub # <----- The stream you want to use for detection
          roles:
            - detect
        - path: rtsp://127.0.0.1:8554/garage_cam
          roles:
            - record
            - rtmp
    rtmp:
      enabled: false # <-- RTMP should be disabled if your stream is not H264
    detect:
      enabled: True # <---- disable detection until you have a working camera feed
      width: 640 # <---- update for your camera's resolution
      height: 480 # <---- update for your camera's resolution
      fps: 5
    objects:
      track:
        - person
        - car
        - truck
        - bicycle
        - motorcycle
        - dog
        - cat
      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: mask to prevent this object type from being detected in certain areas (default: no mask)
          # Checks based on the bottom center of the bounding box of the object
          #mask: 0,0,1000,0,1000,200,0,200
    record: # what you want Frigate to record
        enabled: True
        #retain: # uncomment this section if you want Frigate to record this camera 24/7. This can use a lot of space, you have been warned!
          #days: 1
          #mode: all
        events: # this is the default recording mode where events are recorded, the number of days it saves events for is 10.
            retain:
                mode: active_objects
                default: 10
    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: true
      # 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: []
      required_zones:
        - hof
        - einfahrt
      # 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
    motion:
      mask:
        #- 0,195,40,158,104,104,158,72,180,21,259,21,393,27,408,62,426,91,448,107,476,100,532,105,582,95,591,0,0,0
        - 0,480,199,480,199,450,0,450
    zones:
      hof:
        coordinates: 640,480,640,204,640,74,556,68,503,92,400,79,388,144,189,136,181,70,73,144,0,207,0,480
        objects:
          - car
          - person
      einfahrt:
        coordinates: 204,128,389,140,383,34,231,26
        objects:
          - car
          - person

  garten: # <------ Name the camera
    ffmpeg:
      hwaccel_args: preset-vaapi
      output_args:
        record: preset-record-generic-audio-copy
      inputs:
        - path: rtsp://127.0.0.1:8554/garten_cam_sub # <----- The stream you want to use for detection
          roles:
            - detect
        - path: rtsp://127.0.0.1:8554/garten_cam
          roles:
            - record
            - rtmp
    rtmp:
      enabled: false # <-- RTMP should be disabled if your stream is not H264
    detect:
      enabled: True # <---- disable detection until you have a working camera feed
      width: 1280 # <---- update for your camera's resolution
      height: 720 # <---- update for your camera's resolution
      fps: 5
    objects:
      track:
        - person
        #- car
        - dog
        - cat
      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: mask to prevent this object type from being detected in certain areas (default: no mask)
          # Checks based on the bottom center of the bounding box of the object
          #mask: 0,0,1000,0,1000,200,0,200
    record: # what you want Frigate to record
        enabled: True
        #retain: # uncomment this section if you want Frigate to record this camera 24/7. This can use a lot of space, you have been warned!
          #days: 1
          #mode: all
        events: # this is the default recording mode where events are recorded, the number of days it saves events for is 10.
            retain:
                mode: active_objects
                default: 10
    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: true
      # 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
    motion:
      mask:
        - 487,699,485,720,1280,720,1280,373
        - 0,80,0,0,1280,0,1280,256,958,203,953,219,786,235,738,162,687,139,654,118,602,100,552,107,515,59,449,41,350,39,257,42,121,41,129,79

  garten_links: # <------ Name the camera
    ffmpeg:
      hwaccel_args: preset-vaapi
      output_args:
        record: preset-record-generic-audio-copy
      inputs:
        - path: rtsp://127.0.0.1:8554/garten_links_cam_sub # <----- The stream you want to use for detection
          roles:
            - detect
        - path: rtsp://127.0.0.1:8554/garten_links_cam
          roles:
            - record
            - rtmp
    rtmp:
      enabled: false # <-- RTMP should be disabled if your stream is not H264
    detect:
      enabled: True # <---- disable detection until you have a working camera feed
      width: 640 # <---- update for your camera's resolution
      height: 352 # <---- update for your camera's resolution
      fps: 5
    objects:
      track:
        - person
        #- car
        - dog
        - cat
      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: mask to prevent this object type from being detected in certain areas (default: no mask)
          # Checks based on the bottom center of the bounding box of the object
          #mask: 0,0,1000,0,1000,200,0,200
    record: # what you want Frigate to record
        enabled: True
        #retain: # uncomment this section if you want Frigate to record this camera 24/7. This can use a lot of space, you have been warned!
          #days: 1
          #mode: all
        events: # this is the default recording mode where events are recorded, the number of days it saves events for is 10.
            retain:
                mode: active_objects
                default: 10
    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: true
      # 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
    motion:
      mask:
        - 237,0,182,21,139,25,99,38,0,79,0,303,0,0
        - 469,0,468,21,640,21,640,0

  wohnzimmer: # <------ Name the camera
    ffmpeg:
      hwaccel_args: preset-vaapi
      output_args:
        record: preset-record-generic-audio-copy
      inputs:
        - path: rtsp://127.0.0.1:8554/wohnzimmer_cam_sub # <----- The stream you want to use for detection
          roles:
            - detect
        - path: rtsp://127.0.0.1:8554/wohnzimmer_cam
          roles:
            - record
            - rtmp
    rtmp:
      enabled: false # <-- RTMP should be disabled if your stream is not H264
    detect:
      enabled: True # <---- disable detection until you have a working camera feed
      width: 1280 # <---- update for your camera's resolution
      height: 720 # <---- update for your camera's resolution
      fps: 5
    objects:
      track:
        - person
        - car
        - truck
        - bicycle
        - motorcycle
        - dog
        - cat
      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: mask to prevent this object type from being detected in certain areas (default: no mask)
          # Checks based on the bottom center of the bounding box of the object
          #mask: 0,0,1000,0,1000,200,0,200
    record: # what you want Frigate to record
        enabled: True
        #retain: # uncomment this section if you want Frigate to record this camera 24/7. This can use a lot of space, you have been warned!
          #days: 1
          #mode: all
        events: # this is the default recording mode where events are recorded, the number of days it saves events for is 10.
            retain:
                mode: active_objects
                default: 10
    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: true
      # 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
    motion:
      mask:
        - 0,720,369,720,364,120,433,121,503,129,542,147,586,184,630,241,1280,632,1280,0,0,0

Dann hätte ich da noch eine Frage, wo ich aber jetzt nicht weiß ob es vom Adapter kommt oder von der 0.13er Version.
Starte ich nämlich den frigate-Container neu, sind alle Kameras automatisch auf Motion-Erkennung.
Bei der Adapter-Version 0.2.8 und Frigate 0.12.x war das nicht so. Da war nach einem Neustart die Einstellung so wie vor dem Neustart.

Noch eine Frage hätte ich da. Besteht vielleicht die Möglichkeit das man bei der neuen Version den integrierten MQTT-Broker deaktivieren kann? Bei mir läuft schon ein anderer.

So, ich hoffe ich das alles einigermaßen verständlich geschrieben