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Merge remote-tracking branch 'origin/master' into dev

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Blake Blackshear 2025-07-11 20:20:31 -05:00
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11
docs/docs/troubleshooting/edgetpu.md
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@ -46,6 +46,17 @@ Some users have reported that this older device runs an older kernel causing iss
6. Open the control panel - info scree. The coral TPU will now be recognised as a USB Device - google inc 6. Open the control panel - info scree. The coral TPU will now be recognised as a USB Device - google inc
7. Start the frigate container. Everything should work now! 7. Start the frigate container. Everything should work now!
### QNAP NAS
QNAP NAS devices, such as the TS-253A, may use connected Coral TPU devices if [QuMagie](https://www.qnap.com/en/software/qumagie) is installed along with its QNAP AI Core extension. If any of the features—`facial recognition`, `object recognition`, or `similar photo recognition`—are enabled, Container Station applications such as `Frigate` or `CodeProject.AI Server` will be unable to initialize the TPU device in use.
To allow the Coral TPU device to be discovered, the you must either:
1. [Disable the AI recognition features in QuMagie](https://docs.qnap.com/application/qumagie/2.x/en-us/configuring-qnap-ai-core-settings-FB13CE03.html),
2. Remove the QNAP AI Core extension or
3. Manually start the QNAP AI Core extension after Frigate has fully started (not recommended).
It is also recommended to restart the NAS once the changes have been made.
## USB Coral Detection Appears to be Stuck ## USB Coral Detection Appears to be Stuck
The USB Coral can become stuck and need to be restarted, this can happen for a number of reasons depending on hardware and software setup. Some common reasons are: The USB Coral can become stuck and need to be restarted, this can happen for a number of reasons depending on hardware and software setup. Some common reasons are:

4
frigate/app.py
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@ -73,6 +73,7 @@ from frigate.track.object_processing import TrackedObjectProcessor
from frigate.util.builtin import empty_and_close_queue from frigate.util.builtin import empty_and_close_queue
from frigate.util.image import SharedMemoryFrameManager, UntrackedSharedMemory from frigate.util.image import SharedMemoryFrameManager, UntrackedSharedMemory
from frigate.util.object import get_camera_regions_grid from frigate.util.object import get_camera_regions_grid
from frigate.util.services import set_file_limit
from frigate.version import VERSION from frigate.version import VERSION
from frigate.video import capture_camera, track_camera from frigate.video import capture_camera, track_camera
from frigate.watchdog import FrigateWatchdog from frigate.watchdog import FrigateWatchdog
@ -632,6 +633,9 @@ class FrigateApp:
# Ensure global state. # Ensure global state.
self.ensure_dirs() self.ensure_dirs()
# Set soft file limits.
set_file_limit()
# Start frigate services. # Start frigate services.
self.init_camera_metrics() self.init_camera_metrics()
self.init_queues() self.init_queues()

17
frigate/util/services.py
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@ -5,6 +5,7 @@ import json
import logging import logging
import os import os
import re import re
import resource
import signal import signal
import subprocess as sp import subprocess as sp
import traceback import traceback
@ -751,3 +752,19 @@ def process_logs(
log_lines.append(dedup_message) log_lines.append(dedup_message)
return len(log_lines), log_lines[start:end] return len(log_lines), log_lines[start:end]
def set_file_limit() -> None:
# Newer versions of containerd 2.X+ impose a very low soft file limit of 1024
# This applies to OSs like HA OS (see https://github.com/home-assistant/operating-system/issues/4110)
# Attempt to increase this limit
soft_limit = int(os.getenv("SOFT_FILE_LIMIT", "65536") or "65536")
current_soft, current_hard = resource.getrlimit(resource.RLIMIT_NOFILE)
logger.debug(f"Current file limits - Soft: {current_soft}, Hard: {current_hard}")
new_soft = min(soft_limit, current_hard)
resource.setrlimit(resource.RLIMIT_NOFILE, (new_soft, current_hard))
logger.debug(
f"File limit set. New soft limit: {new_soft}, Hard limit remains: {current_hard}"
)