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1 yr. ago

  • The port on the device has flat metal contacts which a needle shouldn't hurt.

    I've never heard of people cleaning out the cable part of the plug since it isn't kept in your pocket, but that part has small springy wire contacts which are probably fragile.

    I think most people who go digging in their usb-c port know enough to be sort of gentle.

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  • Liberals have a much better track record with this sort of thing.

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  • They asked the deceased, too.

  • I had similar problems for a long time and finally ditched the Coral. I even made a post about it, and you may find it helpful https://wetshav.ing/post/93365

    Also Proxmox does not recommend running Docker in LXC and instead they recommend a VM.

    Edit: actually you commented on that post of mine, so that's funny!

  • This might be a little overkill, but Home Assistant can do this.

    1. Add the calendar to Home Assistant. You don't have to manage it there, but it'll have access.
    2. Under Settings - > Devices & services -> Helpers add a helper of the type History Stats.
    3. For the Entity, select the calendar you want to track, and the Type would be Time.
    4. Next it'll ask you which State to track. Depending on the specifics, you'll probably want to track if the calendar is On, meaning there's something on the calendar. You can track multiple States, but you probably only need On.
    5. On the last page of the wizard you'll put start and end times. If you want to track from Midnight until Now, here's what it would look like:

    Start: {{ now().replace(hour=0, minute=0, second=0) }}End: {{ now() }}

    You can probably adjust the end time to 23:59 if you want to see what's in store for the day looking ahead, but I haven't tried it.

  • Was it windy? How did it end up behind the conveyor?

  • Sweet!

  • I don't have an external GPU either, just the onboard Intel graphics is what I use now. Also worth mentioning to use integrated graphics your Docker Compose needs:

     
        
    devices:
          - /dev/dri/renderD128:/dev/dri/renderD128
    
      

    I'm not using substreams. I have 2 cameras and the motion detection doesn't stress the CPU too much. If I add more cameras I'd consider using substreams for motion detection to reduce the load.

    Your still frames in Home Assistant are the exact problem I was having. If your cameras really do need go2rtc to reduce connections (my wifi camera doesn't seem to care), you might try changing your Docker container to network_mode: host and see if that fixes it.

    Here's my config. Most of the notations were put there by Frigate and I've de-identified everything. Notice at the bottom go2rtc is all commented out, so if I want to add it back in I can just remove the #s. Hope it helps.

     
        
    mqtt:
      enabled: true
      host: <ip of Home Assistant>
      port: 1883
      topic_prefix: frigate
      client_id: frigate
      user: mqtt username
      password: mqtt password
      stats_interval: 60
      qos: 0
    
    cameras:     # No cameras defined, UI wizard should be used
      baby_cam:
        enabled: true
        friendly_name: Baby Cam
        ffmpeg:
          inputs:
            - path: 
                rtsp://user:pw@<ip-addr>:554/cam/realmonitor?channel=1&subtype=0&unicast=true&proto=Onvif
              roles:
                - detect
                - record
          hwaccel_args: preset-vaapi
        detect:
          enabled: true # <---- disable detection until you have a working camera feed
          width: 1920 # <---- update for your camera's resolution
          height: 1080 # <---- update for your camera's resolution
        record:
          enabled: true
          continuous:
            days: 150
          sync_recordings: true
          alerts:
            retain:
              days: 150
              mode: all
          detections:
            retain:
              days: 150
              mode: all
        snapshots:
          enabled: true
        motion:
          mask: 0.691,0.015,0.693,0.089,0.965,0.093,0.962,0.019
          threshold: 14
          contour_area: 20
          improve_contrast: true
        objects:
          track:
            - person
            - cat
            - dog
            - toothbrush
            - train
    
      front_cam:
        enabled: true
        friendly_name: Front Cam
        ffmpeg:
          inputs:
            - path: 
                rtsp://user:pw@<ip-addr>:554/cam/realmonitor?channel=1&subtype=0&unicast=true&proto=Onvif
              roles:
                - detect
                - record
          hwaccel_args: preset-vaapi
        detect:
          enabled: true # <---- disable detection until you have a working camera feed
          width: 2688 # <---- update for your camera's resolution
          height: 1512 # <---- update for your camera's resolution
        record:
          enabled: true
          continuous:
            days: 150
          sync_recordings: true
          alerts:
            retain:
              days: 150
              mode: all
          detections:
            retain:
              days: 150
              mode: all
        snapshots:
          enabled: true
        motion:
          mask:
            - 0.765,0.003,0.765,0.047,0.996,0.048,0.992,0.002
            - 0.627,0.998,0.619,0.853,0.649,0.763,0.713,0.69,0.767,0.676,0.819,0.707,0.839,0.766,0.869,0.825,0.889,0.87,0.89,0.956,0.882,1
            - 0.29,0,0.305,0.252,0.786,0.379,1,0.496,0.962,0.237,0.925,0.114,0.879,0
            - 0,0,0,0.33,0.295,0.259,0.289,0
          threshold: 30
          contour_area: 10
          improve_contrast: true
        objects:
          track:
            - person
            - cat
            - dog
            - car
            - bicycle
            - motorcycle
            - airplane
            - boat
            - bird
            - horse
            - sheep
            - cow
            - elephant
            - bear
            - zebra
            - giraffe
            - skis
            - sports ball
            - kite
            - baseball bat
            - skateboard
            - surfboard
            - tennis racket
          filters:
            car:
              mask:
                - 0.308,0.254,0.516,0.363,0.69,0.445,0.769,0.522,0.903,0.614,1,0.507,1,0,0.294,0.003
                - 0,0.381,0.29,0.377,0.284,0,0,0
        zones:
          Main_Zone:
            coordinates: 0,0,0,1,1,1,1,0
            loitering_time: 0
    
    detectors: # <---- add detectors
      ov:
        type: openvino
        device: GPU
    
    model:
      model_type: yolo-generic
      width: 320 # <--- should match the imgsize set during model export
      height: 320 # <--- should match the imgsize set during model export
      input_tensor: nchw
      input_dtype: float
      path: /config/model_cache/yolov9-t-320.onnx
      labelmap_path: /labelmap/coco-80.txt
    
    version: 0.17-0
    
    
    #go2rtc:
    #  streams:
    #    front_cam:
    #      - ffmpeg:rtsp://user:pw@<ip-addr>:554/cam/realmonitor?channel=1&subtype=0&unicast=true&proto=Onvif
    #    baby_cam:
    #      - ffmpeg:rtsp://user:pw@<ip-addr>:554/cam/realmonitor?channel=1&subtype=0&unicast=true&proto=Onvif
    
      
  • That CPU has UHD Graphics 750 which is newer than mine which has 730. Should work quite nicely.

    Are you using Proxmox, too?

  • Sounds like LXC is the way to go to pass a Coral through. Not sure why it's so flaky with the Debian VM.

  • I'll keep an eye out for that. So far the Inference Speed is holding stead at 8.47ms.

    Are you using OpenVINO with the onboard GPU, or CPU? I think it works with both so you need to make sure it's using the GPU if possible.

  • That's good to hear. That reinforces my suspicion that my problems were caused by passing it through to the virtual machine using Proxmox.

    You might be interested in trying to enable the YOLOv9 models. The developer claims they are more accurate, and so far I'm tempted to agree.

  • You seem a bit more network savvy than me. All I could figure is the Frigate integration (also HACS for me) talks to Frigate and asks it where to get the video from. If go2rtc is enabled in Frigate, the integration tries to stream from go2rtc. Without my Docker stack being in host network mode, it wouldn't work for me.

    With no go2rtc, the Frigate integration asks Frigate where to get the stream, and it's told to get it from the camera from what I can tell.

    All just guesses on my end. Hopefully I don't sound too sure of myself because I'm not really sure.

  • You're right. I've always just typed two hyphens and called it good but technically it should be one long dash.

  • An em dash is --, two dashes. It's a way to break up a sentence -- sort of like a comma.

    Apparently AI uses them a lot.

  • I had a similar progression except I haven't heard of Dockhand until now. I'll give it a look.

    1. Portainer is practical, but I switched to Dockge and have been much happier with it. It doesn't have all of the bells and whistles, but the simplicity makes the workflow much better for me. Give both a try!
    2. FreshRSS for RSS feeds, Lubelogger for tracking car (other other things) maintenance, Nginx Proxy Manager for a reverse proxy (or Caddy which is also popular). Whatever you fancy!
    3. Not sure.

    Regarding domain name, use what you have. It's super easy to change domain names, and some people do it regularly to take advantage of 1st year sales. Basically all you have to do is transfer your DNS entries to the new domain, and update your reverse proxy entries.

    Definitely put everything behind a reverse proxy. I followed this advice so I don't even have to expose ports using Docker. Everything runs through the reverse proxy, and Dockge makes it trivial add each container to the same network.

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  • Citronella candles and torches don't repel mosquitos, but they mask the scent of humans. This helps, but not 100%.

    DEET doesn't mask your scent, so mosquitos are still attracted to you. Once they land on your skin, though, they fly away immediately. Very effective.

    Propane based traps work very well for collecting large numbers of mosquitos. There isn't a definitive answer on whether they reduce the local mosquito population over time. The idea is that if large numbers are killed, it will reduce the local breeding.

    Thermacell brand mosquito repellers are, IMO, magic. At first I thought they were a gimmick, but my impression of them is very positive. They output a light chemical mist which keeps mosquitoes away. They only work with little to no wind, and they take 15 minutes to warm up and start working.

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  • You want to pick your own MAC? At least you can set it to not be random for a specific network.

  • Each instance admin can check a box to require email. It reduces spam accounts and reduces work for admins because users can perform password resets themselves.