It's also against the NEC in the US, I think. People expect low voltage wires to be low voltage and handle them as such. If a high voltage somehow ends up touching a low voltage bare wire, your friendly Ethernet cable could turn deadly.
It sort of makes sense, though. Google Search has been a hot pile of garbage for years. Researching something simple used to be quick and easy, but now you have to sift through endless SEO trash websites to find half an answer (or use a better search engine).
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.
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.
Add the calendar to Home Assistant. You don't have to manage it there, but it'll have access.
Under Settings - > Devices & services -> Helpers add a helper of the type History Stats.
For the Entity, select the calendar you want to track, and the Type would be Time.
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.
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:
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:
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
