That CPU has UHD Graphics 750 which is newer than mine which has 730. Should work quite nicely.
Are you using Proxmox, too?
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.
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.


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.


I may have gotten sucked into the .ml user’s what-about-ism, but I started off by just trying to point out the flaw in their logic.
System, personal choice, whatever – it doesn’t really matter because .ml user is trying to spin facts to support their agenda. I don’t know what their agenda is other than just being contentious.


Ah, so you do understand there’s a difference in why someone would chose one type of transportation over another.


I think your logic is flawed. The discussion is about a specific form of transportation. By your own logic, you should be suggesting that people fly everywhere.
I haven’t heard of v3, I’ll have to check it out.
Depending on the group using it, you can apply for a Community plan to enable mobile push notifications. I do wish Zulip would use UnifiedPush or something like that, or even allow your own ntfy setup, but I’m placated by the Community plan.
Zulip paywalls mobile notifications, but you can apply for a Community subscription which is free, and includes mobile notifications.
IRC is too difficult for normal people to figure out. Normals don’t know how to /join, /nick, and all that other stuff. People want a username and password, because that’s a standard thing that everyone knows.
Even Matrix is too complicated for most people.
IRC serves a purpose, but judging by the success of Discord there’s obviously something lacking from IRC.
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.
I guess I see your point, but at the same time I don’t.
Tiny yes, but IMO getting the attention of computer gamers needs to be the next step if a Linux flavor is going to become a household name.
Even if it’s “SteamOS” that becomes the household name instead of “Linux” that’s still good overall. Maybe it’ll turn into how people used to say they had “Droid” smartphones, not Android.


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 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/renderD128I’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: hostand 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.config.yaml
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