Frigate MySQL - Too many connections

merci ngrataloup, je vais éplucher ma config frigate, je ne savais pas qu’il y avait une incidence sur l’ordre de détection. Pour ce qui est du flux SUB, j’ai désactivé sur toutes mes caméras l’an passé, celà m’a permis déjà d’économiser du CPU. je ne travaille donc plus que sur un flux par camera…

Pour l’instant, j’ai désactivé le docker frigate et basculé toutes mes caméras sur mon autre frigate. Le plugin a été réactivé, pour voir si le système se comporte à nouveau normalement.

Pour les 5% de disque restant, rien d’alarmant, j’ai des purges programmées sur mon système … mais bon, je vais tout de même passer un coup de balai :wink: .

Voici ce que j’ai en conso coté frigate sur mon secondaire (j’ai tout basculé dessus, sauf deux cameras que j’ai désactivées car CPU à 96%) :



Ma config Frigate secondaire :
#ui:

use_experimental: true

version: 0.14

mqtt:
enabled: true
host: 10.0.0.18
port: 1883
topic_prefix: frigate
user: jeedom
password: xxxxxxxxxx

detectors: # <---- add detectors
coral:
type: edgetpu
device: pci

logger:
default: info
logs:
frigate.mqtt: info

audio: # ← enable audio events for all camera
enabled: false
listen:
- bark
- fire_alarm
- scream

- speech

- yell
- crying
- laughter
- dog
- car_alarm

- explosion

- gunshot
- fusillade
- glass
- bark
- honk

- thunderstorm

- thunder

- wind

- alarm
- siren
- civil_defense_siren
- smoke_detector
- fire_alarm

- television

record:
enabled: true
retain:
days: 0
mode: active_objects
events:
pre_capture: 5
post_capture: 5
retain:
default: 1
mode: active_objects

snapshots:
enabled: true
clean_copy: true
timestamp: true
bounding_box: true
crop: false
retain:
default: 2

detect:
fps: 5
width: 1280
height: 720

Optional: Number of consecutive detection hits required for an object to be initialized in the tracker. (default: 1/2 the frame rate)

min_initialized: 2

Optional: Number of frames without a detection before Frigate considers an object to be gone. (default: 5x the frame rate)

max_disappeared: 25

Optional: Configuration for stationary object tracking

stationary:
# Optional: Frequency for confirming stationary objects (default: same as threshold)
# When set to 1, object detection will run to confirm the object still exists on every frame.
# If set to 10, object detection will run to confirm the object still exists on every 10th frame.
interval: 50
# Optional: Number of frames without a position change for an object to be considered stationary (default: 10x the frame rate or 10s)
threshold: 250
# Optional: Define a maximum number of frames for tracking a stationary object (default: not set, track forever)
# This can help with false positives for objects that should only be stationary for a limited amount of time.
# It can also be used to disable stationary object tracking. For example, you may want to set a value for person, but leave
# car at the default.
# WARNING: Setting these values overrides default behavior and disables stationary object tracking.
# There are very few situations where you would want it disabled. It is NOT recommended to
# copy these values from the example config into your config unless you know they are needed.
max_frames:
# Optional: Default for all object types (default: not set, track forever)
default: 3000
# Optional: Object specific values
objects:
person: 1000

model:
#path: /docker/frigate/config/model.yml
width: 320
height: 320
input_tensor: nhwc
input_pixel_format: bgr
labelmap:
0: person
1: bicycle
2: car
3: motorcycle
7: car
16: animal
17: dog
#22: shoe
#23: handbag
#24: suitcase
#29: laptop
#25: bootle
#26: chair
#27: door
#71: tv
#0: person #1: bicycle #2: car #3: motorcycle #4: airplane #5: bus
#6: train #7: car #8: boat #9: traffic light #10: fire hydrant
#11: street sign #12: stop sign #13: parking meter #14: bench #15: bird
#16: cat #17: dog #18: horse #19: sheep
#20: cow #21: elephant #22: bear #23: zebra #24: giraffe
#25: hat #26: backpack #27: umbrella #28: shoe #29: eye glasses
#30: handbag #31: tie #32: suitcase #33: frisbee #34: skis
#35: snowboard #36: sports ball #37: kite #38: baseball bat #39: baseball glove
#40: skateboard #41: surfboard #42: tennis racket #43: bottle #44: plate
#45: wine glass #46: cup #47: fork #48: knife #49: spoon
#50: bowl #51: banana #52: apple #53: sandwich #54: orange
#55: broccoli #56: carrot #57: hot dog #58: pizza #59: donut
#60: cake #61: chair #62: couch #63: potted plant #64: bed
#65: mirror #66: dining table #67: window #68: desk #69: toilet
#70: door #71: tv #72: laptop #73: mouse #74: remote
#75: keyboard #76: cell phone #77: microwave #78: oven #79: toaster
#80: sink #81: refrigerator #82: blender #83: book #84: clock
#85: vase #86: scissors #87: teddy bear #88: hair drier #89: toothbrush
#90: hair brush

go2rtc:
streams:
portail:
- ffmpeg:https://10.3.17.71/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

portail_sub:

- ffmpeg:https://10.3.17.71/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

- ffmpeg:http://10.3.17.71/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

portail2:
  - ffmpeg:https://10.3.17.70/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

portail2_sub:

- ffmpeg:https://10.3.17.70/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

portail3:
  - ffmpeg:https://10.3.17.78/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

portail3_sub:

- ffmpeg:https://10.3.17.78/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

balance:
  - ffmpeg:https://10.3.17.73/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

balance_sub:

- ffmpeg:https://10.3.17.73/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

piscine:
  - ffmpeg:https://10.3.17.72/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

piscine_sub:

- ffmpeg:https://10.3.17.72/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

zoomst:

- ffmpeg:https://10.3.17.3/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

zoomst_sub:

- ffmpeg:https://10.3.17.3/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

zoomsalon:

- ffmpeg:https://10.3.17.2/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

zoomsalon_sub:

- ffmpeg:https://10.3.17.2/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

cuisine:
  - ffmpeg:https://10.3.17.75/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

cuisine_sub:

- ffmpeg:https://10.3.17.75/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

salon:
  - ffmpeg:https://10.3.17.74/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=jeedom_rdc&password=XXXXXXXXX;#video=copy#audio=copy#audio=opus

salon_sub:

- ffmpeg:https://10.3.17.74/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=jeedom_rdc&password=XXXXXXXXX;

Optional: Object configuration

NOTE: Can be overridden at the camera level

objects:

Optional: list of objects to track from labelmap.txt (default: shown below)

track:
- person
- dog
- car
- bicycle
- motorcycle
- vehicule

Optional: mask to prevent all object types from being detected in certain areas (default: no mask)

Checks based on the bottom center of the bounding box of the object.

NOTE: This mask is COMBINED with the object type specific mask below

#mask: 0,0,1000,0,1000,200,0,200

Optional: filters to reduce false positives for specific object types

filters:
person:
# Optional: minimum widthheight of the bounding box for the detected object (default: 0)
min_area: 5000
# Optional: maximum width
height of the bounding box for the detected object (default: 24000000)
max_area: 100000
# Optional: minimum width/height of the bounding box for the detected object (default: 0)
min_ratio: 0.5
# Optional: maximum width/height of the bounding box for the detected object (default: 24000000)
max_ratio: 2.0
# Optional: minimum score for the object to initiate tracking (default: shown below)
min_score: 0.5
# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)
threshold: 0.7
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object

Include all cameras by default in Birdseye view

birdseye:
enabled: true

width: 2550

height: 1280

mode: continuous

layout:

scaling_factor: 3.0

motion:

Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below)

Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive.

The value should be between 1 and 255.

threshold: 20
# Optional: Minimum size in pixels in the resized motion image that counts as motion (default: shown below)

Increasing this value will prevent smaller areas of motion from being detected. Decreasing will

make motion detection more sensitive to smaller moving objects.

As a rule of thumb:

- 10 - high sensitivity

- 30 - medium sensitivity

- 50 - low sensitivity

contour_area: 10
# Optional: The percentage of the image used to detect lightning or other substantial changes where motion detection

needs to recalibrate. (default: shown below)

Increasing this value will make motion detection more likely to consider lightning or ir mode changes as valid motion.

Decreasing this value will make motion detection more likely to ignore large amounts of motion such as a person approaching

a doorbell camera.

lightning_threshold: 0.8

ffmpeg:
output_args:
record: preset-record-generic-audio-aac

cameras:
portail:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/portail
input_args: preset-rtsp-restream
roles:
- record
- audio
- detect
detect:
enabled: true
live:
stream_name: portail
birdseye:
enabled: true
order: 1
objects:
track:
- person
- vehicle
- animal
- dog
- car
filters:
person:
min_score: 0.7
# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)
threshold: 0.75
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object live:
motion:
mask: 0,0.006,0.39,0.006,0.296,0.119,0,0.307
threshold: 14
contour_area: 10
improve_contrast: ‹ true ›

portail2:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/portail2
input_args: preset-rtsp-restream
roles:
- record
#- audio
- detect
detect:
enabled: true
live:
stream_name: portail2
birdseye:
enabled: true
order: 2
objects:
track:
- person
- car
- vehicle
- animal
- dog
filters:
car:
mask:
- 906,121,889,506,1280,508,1205,131
person:
min_score: 0.7
# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)
threshold: 0.75
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object live:

portail3:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/portail3
input_args: preset-rtsp-restream
roles:
- record
- detect
detect:
enabled: true
live:
stream_name: portail3
birdseye:
enabled: true
order: 3
objects:
track:
- person
- vehicle
- animal
- dog
- car
filters:
person:
min_score: 0.7
# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)
threshold: 0.75
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object live:

balance:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/balance
input_args: preset-rtsp-restream
roles:
- record
- detect
detect:
enabled: true
live:
stream_name: rtsp_balance
birdseye:
enabled: true
order: 4
objects:
track:
- person
- animal
- dog
filters:
person:
min_score: 0.7
# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)
threshold: 0.75
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object live:

piscine:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/piscine
input_args: preset-rtsp-restream
roles:
- record
#- audio
- detect
# Optional: Configuration for the jpg snapshots published via MQTT
detect:
enabled: true
live:
stream_name: rtsp_piscine
birdseye:
enabled: true
order: 5
objects:
track:
- animal
- dog
filters:
person:
mask:
- 665,621,521,605,518,470,643,486
min_score: 0.7
# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)
threshold: 0.75
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object live:

zoomsalon:

ffmpeg:

inputs:

- path: rtsp://127.0.0.1:8554/zoomsalon

input_args: preset-rtsp-restream

roles:

- record

- audio

- path: rtsp://127.0.0.1:8554/zoomsalon_sub

input_args: preset-rtsp-restream

roles:

- detect

# Optional: Configuration for the jpg snapshots published via MQTT

detect:

enabled: true

live:

stream_name: rtsp_zoomsalon

birdseye:

enabled: true

order: 6

objects:

track:

- person

- animal

- dog

- bird

filters:

person:

min_score: 0.7

# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)

threshold: 0.75

# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)

# Checks based on the bottom center of the bounding box of the object live:

zoomst:

ffmpeg:

inputs:

- path: rtsp://127.0.0.1:8554/zoomst

input_args: preset-rtsp-restream

roles:

- record

- audio

- path: rtsp://127.0.0.1:8554/zoomst_sub

input_args: preset-rtsp-restream

roles:

- detect

# Optional: Configuration for the jpg snapshots published via MQTT

detect:

enabled: true

live:

stream_name: rtsp_zoomst

birdseye:

enabled: true

order: 7

objects:

track:

- person

- animal

- dog

filters:

person:

min_score: 0.7

# Optional: minimum decimal percentage for tracked object’s computed score to be considered a true positive (default: shown below)

threshold: 0.75

# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)

# Checks based on the bottom center of the bounding box of the object live:

cuisine:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/cuisine
input_args: preset-rtsp-restream
roles:
- record

- audio

- path: rtsp://127.0.0.1:8554/cuisine_sub

input_args: preset-rtsp-restream

roles:

        - detect

# Optional: Configuration for the jpg snapshots published via MQTT

detect:
  enabled: true
live:
  stream_name: rtsp_cuisine
birdseye:
  enabled: true
  order: 8
objects:
  track:
    - person
    - animal
    - dog

- bird

  filters:
    person:
      min_score: 0.7
    # Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
      threshold: 0.75
    # Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
    # Checks based on the bottom center of the bounding box of the object    live:

salon:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/salon
input_args: preset-rtsp-restream
roles:
- record
- audio

- path: rtsp://127.0.0.1:8554/salon_sub

input_args: preset-rtsp-restream

roles:

        - detect

# Optional: Configuration for the jpg snapshots published via MQTT

detect:
  enabled: true
live:
  stream_name: rtsp_salon
birdseye:
  enabled: true
  order: 9
objects:
  track:
    - person
    - animal
    - dog

- bird

  filters:
    person:
      min_score: 0.7
    # Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
      threshold: 0.75
    # Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
    # Checks based on the bottom center of the bounding box of the object    live:

camera_groups:
BirdsEye:
order: 1
icon: LuZoomIn
cameras: birdseye
Exterieur:
order: 2
icon: LuCloudSun
cameras:
- balance
- piscine
- portail
- portail2
- portail3
Interieur:
order: 3
icon: LuArmchair
cameras:
- cuisine

- zoomst

- zoomsalon

  - salon