I am unable to start the add-on. I get the following error is the Supervisor Log:
21-04-28 07:20:43 ERROR (SyncWorker_5) [supervisor.docker] Can’t start addon_ccab4aaf_frigate: 500 Server Error for http+docker://localhost/v1.41/containers/dd9eacd7ee8db5eee7889870ab035d7307e7185b3eda88652b2c2aaaf31160a5/start: Internal Server Error ("driver failed programming external connectivity on endpoint addon_ccab4aaf_frigate (09d24995e8e6a564e6453d9a6efe77eed595814c38fce80807
Did you tryed supervisor->system->reboot host?
source
Yes, still does seem to have ay affect 
I’ll continue my fault finding
Hi,
so I tried lowering the “max_disappeared” setting with no visible change. Also the lowering the “best_image” did not produce more snapshots.
Could you post your node-red code for me please? Have not worked with node red before, this is new land for me.
Thank you very much.
Cheers Chris
Do you know where I can get a copy of the firmware? The original firmware it was shipped with only gave me the option for h265 too, which is one of the reasons I swapped.
How would I go about transcoding the stream to include the frigate detection boxes? I have tried this:
ffmpeg:
global_args:
-hide_banner
-loglevel warning
input_args:
-avoid_negative_ts make_zero
-fflags +genpts+discardcorrupt
-rtsp_transport tcp
-stimeout 5000000
output_args:
clips:
-f segment
-segment_time 300
-segment_format mp4
-reset_timestamps 1
-strftime 1
-c copy
-an
but that give me the error:
Unable to create clip for 04_Side_Gate and event 1619622504.318758-5yi399. There were no cache files for this event.
I can’t find the information to tell me what each of the arguments do, or what the options are to change them too. I’ve looked here. Configuration | Frigate (blakeblackshear.github.io)
Also my camera is quite high up, and some objects can be quite small, is there a way of increasing person detection when they are smaller in the frame? I have the following at the moment:
min_area: 0
min_score: 0.2
threshold: 0.3
Increase the ‘-detect’ resolution stream worked for me in a similar situation, I ended up using 3072x2048 (max resolution mode from hikvision fisheye). This way, a person can easily fill 300x300px.
Thanks. I’ll wait for my coral adaptor to arrive tomorrow before doing that.
I’m trying to reencode the stream, but i’m getting these errors:
ffmpeg.06_Rear_Garden.clips ERROR : Guessed Channel Layout for Input Stream #0.1 : mono
ffmpeg.07_West_Fence.clips ERROR : [rtsp @ 0x5630f1244840] max delay reached. need to consume packet
ffmpeg.06_Rear_Garden.clips ERROR : [hevc @ 0x5584da18b700] Could not find ref with POC 0
ffmpeg.07_West_Fence.clips ERROR : [rtsp @ 0x5630f1244840] RTP: missed -63704 packets
ffmpeg.07_West_Fence.clips ERROR : Guessed Channel Layout for Input Stream #0.1 : mono
ffmpeg.07_West_Fence.clips ERROR : [hevc @ 0x5630f12cec40] Could not find ref with POC 4
ffmpeg.07_West_Fence.clips ERROR : [rtsp @ 0x5630f1244840] max delay reached. need to consume packet
ffmpeg.07_West_Fence.clips ERROR : [rtsp @ 0x5630f1244840] RTP: missed 1864 packets
my current ffmpeg looks like this:
ffmpeg:
global_args:
-hide_banner
-loglevel warning
input_args:
- -avoid_negative_ts
- make_zero
- -fflags
- nobuffer
# - -rtsp_transport tcp
# - -stimeout 5000000
output_args:
clips:
-f segment
-segment_time 300
-segment_format mp4
-reset_timestamps 1
-strftime 1
-c:v libx264
-an
first, awesome work!
Everything works with only CPU processing, but I have a problem with the USB Coral Stick.
I’m not sure if the Coral stick is damaged or if it’s some other kind of error.
I am using Proxmox as host system running HassOS.
lsusb on the host looks like this:
in the log, it doesn’t look very good, anyway:
* Starting nginx nginx
...done.
frigate.app INFO : Creating directory: /tmp/cache
Starting migrations
peewee_migrate INFO : Starting migrations
There is nothing to migrate
peewee_migrate INFO : There is nothing to migrate
frigate.app INFO : Camera processor started for back: 49
frigate.app INFO : Capture process started for back: 50
detector.coral INFO : Starting detection process: 46
frigate.mqtt INFO : MQTT connected
Process detector:coral:
frigate.edgetpu INFO : Attempting to load TPU as usb
frigate.edgetpu INFO : No EdgeTPU detected.
Traceback (most recent call last):
File "/usr/local/lib/python3.8/dist-packages/tflite_runtime/interpreter.py", line 152, in load_delegate
delegate = Delegate(library, options)
File "/usr/local/lib/python3.8/dist-packages/tflite_runtime/interpreter.py", line 111, in __init__
raise ValueError(capture.message)
ValueError
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/usr/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/opt/frigate/frigate/edgetpu.py", line 124, in run_detector
object_detector = LocalObjectDetector(tf_device=tf_device, num_threads=num_threads)
File "/opt/frigate/frigate/edgetpu.py", line 63, in __init__
edge_tpu_delegate = load_delegate('libedgetpu.so.1.0', device_config)
File "/usr/local/lib/python3.8/dist-packages/tflite_runtime/interpreter.py", line 154, in load_delegate
raise ValueError('Failed to load delegate from {}\n{}'.format(
ValueError: Failed to load delegate from libedgetpu.so.1.0
frigate.watchdog INFO : Detection appears to have stopped. Exiting frigate...
frigate.app INFO : Stopping...
frigate.events INFO : Exiting event processor...
frigate.record INFO : Exiting recording maintenance...
frigate.object_processing INFO : Exiting object processor...
frigate.watchdog INFO : Exiting watchdog...
frigate.events INFO : Exiting event cleanup...
frigate.stats INFO : Exiting watchdog...
peewee.sqliteq INFO : writer received shutdown request, exiting.
root INFO : Waiting for detection process to exit gracefully...
the config file I have changed to that:
detectors:
coral:
type: edgetpu
device: usb
mqtt:
........
is there anything I could check? or is it possibly the host machine?
thanks a lot.
Haven’t tried it myself, but I want to if the PCIe corals ever come back in stock. I also run proxmox and HassOS and from what I’ve read in the past you need to install the drivers on the proxmox host. I never did understand if the passthrough to HassOS worked without any other modifications though.
I can’t find it on the fly, only in use with the PCIE card.
do you know where you read that?
does not make much sense for me… i mean the deconz USB stick you can also simply pass through.
@sender - While I’m not on LXC, I am running Frigate on Unraid/Docker and HA in a VM with Frigate addon. I am thinking though your problem lies somewhere within the Frigate deployment and i can share my working configuration config.yml file if you like to compare. I started from scratch and now have pretty much every option turned on and working. I also use 2 cpu option (no Coral or any such device). Let me know.
Yes please share, I can use all help I can get 
Hi @basejob,
and what is the ram size of the pi?
Thanks!
I guess the first thing to do is access your rtsp streams directly in VLC and make sure you have continuous stream with correct frames from the cameras giving you grief just to rule out any network bottlenecks etc.
mqtt:
host: 192.168.200.132
# Optional: port (default: shown below)
port: 1883
# Optional: topic prefix (default: shown below)
# WARNING: must be unique if you are running multiple instances
topic_prefix: frigate
# Optional: client id (default: shown below)
# WARNING: must be unique if you are running multiple instances
client_id: frigate
# Optional: user
user: mqtt-user
# Optional: password
# NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {}.
# eg. password: '{FRIGATE_MQTT_PASSWORD}'
password: mqtt-user
# Optional: interval in seconds for publishing stats (default: shown below)
stats_interval: 60
cameras:
backyard:
ffmpeg:
inputs:
- path: rtsp://192.168.200.50:554/s1
roles:
- detect
- clips
- path: rtsp://192.168.200.50:554/s2
roles:
- rtmp
- path: rtsp://192.168.200.50:554/s0
roles:
- record
output_args:
record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy
width: 640
height: 360
fps: 5
motion:
mask: 320,106,640,209,640,0,191,0,0,0,0,65
threshold: 10
contour_area: 50
clips:
enabled: true
pre_capture: 5
post_capture: 5
record:
enabled: true
retain_days: 15
objects:
track:
- person
- dog
filters:
dog:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.6
person:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.7
Deck:
ffmpeg:
inputs:
- path: rtsp://192.168.200.51:554/s1
roles:
- detect
- clips
- path: rtsp://192.168.200.51:554/s2
roles:
- rtmp
- path: rtsp://192.168.200.51:554/s0
roles:
- record
output_args:
record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy
width: 640
height: 360
fps: 5
motion:
mask: 368,51,640,205,640,0,0,0,0,62
threshold: 10
contour_area: 50
clips:
enabled: true
pre_capture: 5
post_capture: 5
record:
enabled: true
retain_days: 15
objects:
track:
- person
- dog
filters:
dog:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.6
person:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.7
Side:
ffmpeg:
inputs:
- path: rtsp://192.168.200.52:554/s1
roles:
- detect
- clips
- path: rtsp://192.168.200.52:554/s2
roles:
- rtmp
- path: rtsp://192.168.200.52:554/s0
roles:
- record
output_args:
record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy
width: 640
height: 360
fps: 5
motion:
mask: 399,40,640,0,378,0,257,0,0,0,0,117
threshold: 10
clips:
enabled: true
pre_capture: 5
post_capture: 5
record:
enabled: true
retain_days: 15
objects:
track:
- person
- dog
- car
- bus
filters:
dog:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.6
person:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.7
Frontyard:
ffmpeg:
inputs:
- path: rtsp://192.168.200.53:554/s1
roles:
- detect
- clips
- path: rtsp://192.168.200.53:554/s2
roles:
- rtmp
- path: rtsp://192.168.200.53:554/s0
roles:
- record
output_args:
record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy
width: 640
height: 360
fps: 5
motion:
mask:
- 640,0,640,70,0,57,0,0,0,0,0,0
- 610,161,604,201,640,227,640,138
- 410,360,468,304,519,276,569,311,610,360
- 52,287,104,255,173,282,195,318,218,360,24,360
threshold: 10
contour_area: 50
zones:
yard:
coordinates: 0,360,640,360,640,91,640,91,0,79
road:
coordinates: 0,73,640,85,640,0,0,0
clips:
enabled: true
pre_capture: 5
post_capture: 5
record:
enabled: true
retain_days: 15
snapshots:
enabled: true
mqtt:
enabled: true
crop: false
objects:
track:
- person
- dog
- car
- bus
filters:
dog:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.6
person:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.7
Driveway:
ffmpeg:
inputs:
- path: rtsp://192.168.200.54:554/s1
roles:
- detect
- clips
- path: rtsp://192.168.200.54:554/s2
roles:
- rtmp
- path: rtsp://192.168.200.54:554/s0
roles:
- record
output_args:
record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy
width: 640
height: 360
fps: 5
motion:
mask: 640,78,640,0,0,0,0,76
threshold: 10
contour_area: 50
zones:
drive:
coordinates: 640,267,470,209,275,162,108,157,0,156,0,360,387,360,640,360
road:
coordinates: 0,145,375,153,389,73,0,72
clips:
enabled: true
pre_capture: 5
post_capture: 5
record:
enabled: true
retain_days: 15
snapshots:
enabled: true
mqtt:
enabled: true
crop: false
objects:
track:
- person
- dog
- car
- bus
filters:
dog:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.6
person:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.7
detectors:
cpu1:
type: cpu
cpu2:
type: cpu
Did you ever get this to deploy on portainer? Can’t seem to find the right settings.
Frigate:
How do I change mode to CPU? Seems to be trying to find TPU.
I’m running it in docker desktop.
sneighbour/frigate
Starting detection process: 36
ffmpeg_input = get_ffmpeg_input(ffmpeg['input'])
Attempting to load TPU as usb
KeyError: 'input'
I did… but not using it anymore.
Sorry but i dont have the setup anymore. So I cant be of much help.
Have 2 cams running in the homeassistant addon successfully but want to offload them to an ubuntu vm (or lxc).
Yeah if this not the config.yaml (check mine against your setup) and those cameras work fine with the addon directly in HA, then possibly something to do with your virtual NICs / drivers on your LXC perhaps or allocation of memory/ vCpu to the VM/container. I would start troubleshooting there first -transfer a large file over the network to that container (10-15GB) and see if you get a sustained 100/MB per sec.
Needed the detectors:
detectors:
cpu1:
type: cpu
cpu2:
type: cpu
But now plenty of other errors. entry endpoint for api is missing for a start