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.

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.

Yeah… I hesitated to hit “submit”, but figured the courts would rule in our favor because courts have a good sense of humor!

They are also very noisy, so a basement location might not be enough to suppress the humming and yelling from reaching your living areas.

Ah, maybe the max was 20GB for zip. I’d just do the max available for zip.

Do it again, but select 50GB chunks. This will produce fewer files.

Use immich-go to do the importing.

I’ve never had to restore a backup (yet), but to me this is the best feature of Restic.

I used Duplicati for a while (I think it was Duplicati, not Duplicacy) and although the backups seemed to work, I kept reading about people having trouble during the restore process.

Restic is a slight chore to get set up with the environmental variables, figuring out which directories to “–ignore”, etc… but man once it’s set up it’s just great.

I’m not sure I fully grasp what you want, but Restic is excellent. I use a cronjob to back up on a schedule. It’s command line only. I think there’s a tool to make it a GUI but I haven’t tried it. They have a Docker image available but it’s weird, you have to pass commands to it, it runs, then shuts down when it’s done. I love Docker but that didn’t quite work for me.

I use Backblaze B2 for storage, but any S3 will do. Restic supports all sorts of storage targets.

Credentials and things go in an .env file, or you can put everything into the command line every time.

When it’s time to restore things, you can fricken mount the whole backup you want and browse the files, copy and paste what you need, etc. That part is really cool to me.

Backblaze is $5 or $6 USD per TB per month, so 500GB will be about $36USD a year.