Oui pour la vue live c’est l’idéal pour paramétrer le caméra et notre config.
Mais là je pense qu’il parlait des snapshots, dans l’espace de stockage pour une détection on a deux snapshots, un clair sans cadre et un autre avec le cadre. Et côté Frigate seul l’affichage sans cadre est dispo il me semble. Il faut aller dans l’espace de stockage pour avoir celui avec cadre.
Mais il y a peut-être un paramétrage pour ça que je ne connais pas.
C’est ça, j’aimerais afficher le clip avec cadre dans HA.
Bonjour,
Je reviens ici pour de nouvelles questions 
(J’édite le titre du sujet ^^)
D’abord ce que j’ai fait de nouveau, et mon nouveau fichier de configuration.
J’ai activé le mqtt dans Frigate, et j’ai bien les remontées dans le broker mqtt de HA.
# yaml-language-server: $schema=http://192.168.2.64:5000/api/config/schema.json
mqtt:
enabled: True
host: 192.168.2.140
port: 1883
user: "{FRIGATE_MQTT_USER}"
password: "{FRIGATE_MQTT_PASSWORD}"
stats_interval: 60
# Optional: Detectors configuration. Defaults to a single CPU detector
detectors:
# Required: name of the detector
coral:
# Required: type of the detector
# Frigate provided types include 'cpu', 'edgetpu', 'openvino' and 'tensorrt' (default: shown below)
# Additional detector types can also be plugged in.
# Detectors may require additional configuration.
# Refer to the Detectors configuration page for more information.
type: edgetpu
device: usb
# Optional: Database configuration
database:
# The path to store the SQLite DB (default: shown below)
path: /config/frigate.db
# Optional: TLS configuration
tls:
# Optional: Enable TLS for port 8971 (default: shown below)
enabled: true
# Optional: Authentication configuration
auth:
# Optional: Enable authentication
enabled: true
# Optional: Reset the admin user password on startup (default: shown below)
# New password is printed in the logs
reset_admin_password: false
# Optional: Cookie to store the JWT token for native auth (default: shown below)
#cookie_name: "frigate_token"
# Optional: Set secure flag on cookie. (default: False)
# NOTE: This should be set to True if you are using TLS
cookie_secure: true
# Optional: Session length in seconds (default: shown below)
session_length: 86400 # 24 hours
# Optional: Refresh time in seconds (default: shown below)
# When the session is going to expire in less time than this setting,
# it will be refreshed back to the session_length.
refresh_time: 43200 # 12 hours
# Optional: Rate limiting for login failures to help prevent brute force
# login attacks (default: None)
# See the docs for more information on valid values
failed_login_rate_limit: 1/second;5/minute;20/hour
# Optional: Trusted proxies for determining IP address to rate limit
# NOTE: This is only used for rate limiting login attempts and does not bypass
# authentication. See the authentication docs for more details.
trusted_proxies:
- 172.18.0.0/16 # <---- this is the subnet for the internal docker compose network
- 192.168.2.141/32 # <---- SWAG Reverse Proxy
# Optional: Number of hashing iterations for user passwords
# As of Feb 2023, OWASP recommends 600000 iterations for PBKDF2-SHA256
# NOTE: changing this value will not automatically update password hashes, you
# will need to change each user password for it to apply
hash_iterations: 600000
ffmpeg:
global_args: -hide_banner -loglevel warning
hwaccel_args: preset-vaapi
output_args:
record: preset-record-generic-audio-copy
birdseye:
enabled: false
snapshots:
# Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
enabled: True
# Optional: save a clean PNG copy of the snapshot image (default: shown below)
clean_copy: False
# Optional: print a timestamp on the snapshots (default: shown below)
timestamp: False
# Optional: draw bounding box on the snapshots (default: shown below)
bounding_box: True
# Optional: crop the snapshot (default: shown below)
crop: false
# Optional: height to resize the snapshot to (default: original size)
height: 720
# Optional: Restrict snapshots to objects that entered any of the listed zones (default: no required zones)
required_zones: []
# Optional: Camera override for retention settings (default: global values)
retain:
# Required: Default retention days (default: shown below)
default: 5
# Optional: Per object retention days
objects:
person: 5
# Optional: quality of the encoded jpeg, 0-100 (default: shown below)
quality: 100
# Optional: Record configuration
# NOTE: Can be overridden at the camera level
record:
# Optional: Enable recording (default: shown below)
# WARNING: If recording is disabled in the config, turning it on via
# the UI or MQTT later will have no effect.
enabled: True
# Optional: Number of minutes to wait between cleanup runs (default: shown below)
# This can be used to reduce the frequency of deleting recording segments from disk if you want to minimize i/o
expire_interval: 60
# Optional: Sync recordings with disk on startup and once a day (default: shown below).
sync_recordings: False
# Optional: Retention settings for recording
retain:
# Optional: Number of days to retain recordings regardless of events (default: shown below)
# NOTE: This should be set to 0 and retention should be defined in events section below
# if you only want to retain recordings of events.
days: 5 # <- number of days to keep continuous recordings -- mettre 0 pour purger
# Optional: Mode for retention. Available options are: all, motion, and active_objects
# all - save all recording segments regardless of activity
# motion - save all recordings segments with any detected motion
# active_objects - save all recording segments with active/moving objects
# NOTE: this mode only applies when the days setting above is greater than 0
#mode: active_objects
mode: all
export:
# Optional: Timelapse Output Args (default: shown below).
# NOTE: The default args are set to fit 24 hours of recording into 1 hour playback.
# See https://stackoverflow.com/a/58268695 for more info on how these args work.
# As an example: if you wanted to go from 24 hours to 30 minutes that would be going
# from 86400 seconds to 1800 seconds which would be 1800 / 86400 = 0.02.
# The -r (framerate) dictates how smooth the output video is.
# So the args would be -vf setpts=0.02*PTS -r 30 in that case.
timelapse_args: "-vf setpts=0.04*PTS -r 30"
# Optional: Recording Preview Settings
preview:
# Optional: Quality of recording preview (default: shown below).
# Options are: very_low, low, medium, high, very_high
quality: medium
# Optional: Event recording settings
events:
# Optional: Number of seconds before the event to include (default: shown below)
pre_capture: 5
# Optional: Number of seconds after the event to include (default: shown below)
post_capture: 5
# Optional: Objects to save recordings for. (default: all tracked objects)
objects:
- person
# Optional: Retention settings for recordings of events
retain:
# Required: Default retention days (default: shown below)
default: 5 # <- number of days to keep event recordings -- mettre 0 pour purger
# Optional: Mode for retention. (default: shown below)
# all - save all recording segments for events regardless of activity
# motion - save all recordings segments for events with any detected motion
# active_objects - save all recording segments for event with active/moving objects
#
# NOTE: If the retain mode for the camera is more restrictive than the mode configured
# here, the segments will already be gone by the time this mode is applied.
# For example, if the camera retain mode is "motion", the segments without motion are
# never stored, so setting the mode to "all" here won't bring them back.
mode: motion
# Optional: Per object retention days
objects:
person: 5
cat: 5
# Optional: Review configuration
# NOTE: Can be overridden at the camera level
review:
# Optional: alerts configuration
alerts:
# Optional: labels that qualify as an alert (default: shown below)
labels:
- person
# Optional: required zones for an object to be marked as an alert (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones: []
# Optional: detections configuration
detections:
# Optional: labels that qualify as a detection (default: all labels that are tracked / listened to)
labels:
- cat
# Optional: required zones for an object to be marked as a detection (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones: []
# Optional: Motion configuration
# NOTE: Can be overridden at the camera level
motion:
# Optional: enables detection for the camera (default: True)
# NOTE: Motion detection is required for object detection,
# setting this to False and leaving detect enabled
# will result in an error on startup.
enabled: True
# 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 #30
# 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
# 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: Alpha value passed to cv2.accumulateWeighted when averaging frames to determine the background (default: shown below)
# Higher values mean the current frame impacts the average a lot, and a new object will be averaged into the background faster.
# Low values will cause things like moving shadows to be detected as motion for longer.
# https://www.geeksforgeeks.org/background-subtraction-in-an-image-using-concept-of-running-average/
frame_alpha: 0.01
# Optional: Height of the resized motion frame (default: 100)
# Higher values will result in more granular motion detection at the expense of higher CPU usage.
# Lower values result in less CPU, but small changes may not register as motion.
frame_height: 100
# Optional: motion mask
# NOTE: see docs for more detailed info on creating masks
# mask: 0.000,0.469,1.000,0.469,1.000,1.000,0.000,1.000
# Optional: improve contrast (default: shown below)
# Enables dynamic contrast improvement. This should help improve night detections at the cost of making motion detection more sensitive
# for daytime.
improve_contrast: True
# Optional: Delay when updating camera motion through MQTT from ON -> OFF (default: shown below).
mqtt_off_delay: 30
# 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
- cat
# Optional: filters to reduce false positives for specific object types
filters:
person:
# Optional: minimum width*height 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: 0.4 #0.6
# Optional: maximum width/height of the bounding box for the detected object (default: 24000000)
max_ratio: 1 #2.0
# Optional: minimum score for the object to initiate tracking (default: shown below)
min_score: 0.7 #0.5
# Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
threshold: 0.7 #0.7
cat: # Voir ici : https://community.home-assistant.io/t/frigate-detecting-small-objects-birds-cats-etc/565386/10?u=milesteg
min_area: 2000 # Adjust depending on the size and distance of the object in view
max_area: 10000 # Limit larger object detections
min_score: 0.6 # Confidence score for detection
threshold: 0.7 # Higher threshold to avoid false positives
min_ratio: 0.4 # Cat's body tends to be longer than it is tall
max_ratio: 2.0 # Allow for a longer body, so the width can be up to twice the height
go2rtc:
streams:
Camera_Salon_RLC-510A:
- rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.2.163:554/Preview_01_main
- ffmpeg:Camera_Salon_RLC-510A#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
# Autre méthode :
# - "ffmpeg:http://192.168.2.163/flv?port=1935&app=bcs&stream=channel0_main.bcs&user={FRIGATE_RTSP_USER}&password={FRIGATE_RTSP_PASSWORD}#video=copy#audio=copy#audio=opus"
# - rtmp://192.168.2.163:1935/bcs/channel0_main.bcs?channel=0&stream=0&user={FRIGATE_RTSP_USER}&password={FRIGATE_RTSP_PASSWORD}
Camera_Salon_RLC-510A_sub:
- rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.2.163:554/Preview_01_sub
- ffmpeg:Camera_Salon_RLC-510A#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
# Autre méthode :
# - rtmp://192.168.2.163:1935/bcs/channel0_main.bcs?channel=0&stream=0&user={FRIGATE_RTSP_USER}&password={FRIGATE_RTSP_PASSWORD}
# - "ffmpeg:http://192.168.2.163/flv?port=1935&app=bcs&stream=channel0_main.bcs&user={FRIGATE_RTSP_USER}&password={FRIGATE_RTSP_PASSWORD}#video=copy#audio=copy#audio=opus"
cameras:
Camera_Salon_RLC-510A:
enabled: true
ffmpeg:
hwaccel_args: preset-vaapi
inputs:
- path: rtsp://127.0.0.1:8554/Camera_Salon_RLC-510A # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles:
- record
- detect
- path: rtsp://127.0.0.1:8554/Camera_Salon_RLC-510A_sub # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles: []
detect:
enabled: true # <---- disable detection until you have a working camera feed
fps: 10
width: 1280 # 640 <---- update for your camera's resolution
height: 720 # 480 <---- update for your camera's resolution
record: # <----- Enable recording
enabled: true
snapshots:
enabled: true
motion:
mask:
- 0.154,0.451,0.147,0.587,0.305,0.59,0.312,0.461
- 0.044,0.221,0,0,1,0,1,0.289,0.949,0.288,0.983,0.333,0.981,0.398,0.931,0.393,0.879,0.367,0.773,0.359,0.763,0.373,0.678,0.369,0.641,0.34
threshold: 30
contour_area: 10
improve_contrast: true
zones:
Salon:
coordinates:
0,0.012,0,0.619,0,1,1,1,1,0.292,0.952,0.291,0.985,0.338,0.931,0.824,0.769,0.732,0.66,0.691,0.679,0.371,0.642,0.344,0.156,0.245,0.15,0.445,0.314,0.462,0.305,0.596,0.143,0.596,0.156,0.243,0.043,0.226
inertia: 3
loitering_time: 0
Entrée:
coordinates: 0.681,0.372,0.66,0.69,0.772,0.733,0.807,0.365,0.773,0.362,0.765,0.376
loitering_time: 0
inertia: 3
Cuisine:
coordinates: 0.809,0.368,0.775,0.735,0.931,0.823,0.976,0.399,0.932,0.397,0.881,0.37
loitering_time: 0
inertia: 3
objects:
mask: 0.153,0.448,0.146,0.591,0.306,0.593,0.313,0.461
# Optional
ui:
# Optional: Set a timezone to use in the UI (default: use browser local time)
# timezone: America/Denver
# Optional: Set the time format used.
# Options are browser, 12hour, or 24hour (default: browser)
time_format: 24hour
# Optional: Set the date style for a specified length.
# Options are: full, long, medium, short
# Examples:
# short: 2/11/23
# medium: Feb 11, 2023
# full: Saturday, February 11, 2023
# (default: short).
date_style: short
# Optional: Set the time style for a specified length.
# Options are: full, long, medium, short
# Examples:
# short: 8:14 PM
# medium: 8:15:22 PM
# full: 8:15:22 PM Mountain Standard Time
# (default: medium).
time_style: medium
# Optional: Ability to manually override the date / time styling to use strftime format
# https://www.gnu.org/software/libc/manual/html_node/Formatting-Calendar-Time.html
# possible values are shown above (default: not set)
strftime_fmt: '%d/%m/%Y/ %H:%M:%S'
# Optional: Telemetry configuration
telemetry:
# Optional: Enabled network interfaces for bandwidth stats monitoring (default: empty list, let nethogs search all)
network_interfaces: []
# Optional: Configure system stats
stats:
# Enable AMD GPU stats (default: shown below)
amd_gpu_stats: false
# Enable Intel GPU stats (default: shown below)
intel_gpu_stats: true
# Enable network bandwidth stats monitoring for camera ffmpeg processes, go2rtc, and object detectors. (default: shown below)
# NOTE: The container must either be privileged or have cap_net_admin, cap_net_raw capabilities enabled.
network_bandwidth: false
# Optional: Enable the latest version outbound check (default: shown below)
# NOTE: If you use the HomeAssistant integration, disabling this will prevent it from reporting new versions
version_check: true
version: 0.14
J’ai fait quelques modifications pour affiner certaines détections (valeurs trouvées sur le net).
Maintenant, une poupée ne semble plus détectée comme personne…
Même ma fille de presque 3 ans est correctement détectée.
Mon chat aussi.
Bon par contre, la TV me génère toujours des alertes « person »…
@Integra Comment proposais-tu déjà de remédier à cela ?
Car j’ai déjà pleins de zones censées exclure la TV de ces détections…
Reste à voir si ce recadrage fait que les personnes dans la TV sont ou pas détectées en tant que tel par Frigate …
J’ai utilisé un blueprint trouvé sur le forum US : GitHub - SgtBatten/HA_blueprints: Somewhere to store automation blueprints
alias: Frigate Notification - Caméra Salon
description: ""
use_blueprint:
path: SgtBatten/Stable.yaml
input:
camera: camera.camera_salon_rlc_510a
notify_device: 880d7c7eec61e0d616854e6e1efca27f
message: >-
{{ label }} detected - {{ camera_name }} at
{{event['after']['start_time']|timestamp_custom('%H:%M')}}
attachment: snapshot.jpg?bbox=1
update_thumbnail: true
ios_live_view: camera.camera_salon_rlc_510a
base_url: https://ha.mon-ndd.fr/
presence_filter: person.milesteg
labels:
- person
state_entity: alarm_control_panel.alarme_maison
state_filter_states:
- armed_away
state_filter: true
Ça n’envoie une notification que si je ne suis pas chez moi et que l’alarme est enclenchée.
Si je suis chez moi je ne veux pas être spammé ^^
Si ma femme est chez nous, mais pas moi, l’alarme est désactivée, donc je ne serais pas spammé là aussi ^^
Les essais fait sans les conditions d’alarme et de personne présente, sont presque concluants. Les clips que je reçois ne sont pas toujours visible depuis mon iphone, surtout les notifications pour le chat XD (bon après, normalement ça ne devrait être que des détections de personnes.
À voir…
Maintenant, j’ai commencé à utiliser la carte Frigate :
type: custom:frigate-card
cameras:
- camera_entity: camera.camera_salon_rlc_510a
live_provider: auto
icon: phu:living-room
hide: false
dimensions:
layout:
fit: fill
go2rtc:
modes: []
webrtc_card: {}
dependencies:
cameras:
- camerasalon_fluent
performance:
profile: high
dimensions:
aspect_ratio_mode: dynamic
timeline:
style: ribbon
media: all
image:
mode: screensaver
layout: {}
menu:
style: outside
position: bottom
alignment: right
buttons:
frigate:
alignment: opposing
cameras:
alignment: opposing
priority: 100
screenshot:
enabled: true
substreams:
enabled: true
icon: mdi:quality-low
live:
enabled: true
icon: mdi:quality-high
clips:
enabled: true
recordings:
enabled: true
image:
enabled: false
camera_ui:
enabled: true
expand:
enabled: true
media_player:
enabled: false
microphone:
enabled: false
play:
enabled: true
mute:
enabled: true
view:
default: live
dark_mode: "on"
camera_select: live
media_gallery:
controls:
thumbnails:
show_details: true
filter: {}
live:
layout: {}
preload: true
grid_options:
columns: 24
rows: auto
Donc le live semble fonctionnel, et je n’ai vu aucune différence entre les différentes possibilités de configuration :
Pour ceux qui connaissent la carte Frigate, comment faut-il bien la configurer ?
Dois-je mettre quelque chose ici ?
Donc, le live fonctionne, dans la carte d’à côté, j’ai paramétré pour que ça n’affiche que le dernier snapshot avec cadre :
type: custom:frigate-card
cameras:
- camera_entity: camera.camera_salon_rlc_510a
live_provider: ha
icon: mdi:cctv
go2rtc:
modes:
- webrtc
webrtc_card:
entity: camera.camera_salon_rlc_510a
view:
default: snapshot
media_gallery:
controls:
thumbnails:
show_details: false
size: 175
image: {}
Jusque-là, ça fonctionne.
L’affichage dans la carte principal des snapshots semble bien fonctionner.
Mais pas les clips…
Je crois que la carte n’est pas à jour sur la terminologie nouvelle de Firgate…
Enfin c’est le basar : Frigate fait des snapshots qu’il enregistre dans le dossier clips… le dossier snapshots n’est plus utilisé… chercher la logique…
Car comme vous le voyez dans la capture précédente, j’ai du gris à la place d’un clip que j’ai voulu afficher :
Peut importe le clip, j’ai un écran gris.
Les boutons de téléchargement fonctionne bien eux, et me télécharge les .mp4 correspondant à ces clips.
Bref, je peux en faire fi, et ne pas utiliser ça, mais ça m’embête de ne pas pouvoir lire ces clips…
Une idée de comment je peux le faire ? sans télécharger le fichier ?
J’ai le même écran gris quand je veux lire les recordings :
Est-ce possible ?
Comment puis-je obtenir le flux secondaire de ma configuration Frigate dans la carte Frigate de HA ?
Sans passer par l’utilisation de l’intégration Reolink… c’est pas terrible… ça génère un autre flux depuis la caméra… Frigate permet de l’avoir, autant l’utiliser.
Merci pour ceux qui ont tout lu ^^ et pour quelconque aide que vous donnerez ^^
Bonjour @MilesTEG1,
Oui je pense que le problème vient de là. J’ai l’impression que la zone de masquage de la TV n’est pas assez grande verticalement. Comme expliqué un peu plus haut, et si j’ai bien compris la doc, la zone de détection est déterminée en se basant sur un point central situé sur la ligne inférieure du cadre de détection. Le point rouge ci-dessous doit être couvert par la zone de masquage :
Comme on peut le voir, le point déborde en bas de ta TV, donc je pense que ta zone de masquage TV doit également déborder vers le bas pour couvrir cette zone. Le mieux étant d’allumer la TV et de regarder dans la vue débug de Frigate, en affichant les cadres de détection et zones, pour voir comme cela se comporte chez toi. Et donc observer si la zone de masquage couvre bien se point centrale inférieur qui déborde.
Pour ignorer les Alerts & Detections 
:
Tu dois simplement rajouter tes 3 zones dans les parties « required_zones: » de ta config Frigate, dans les catégories « alerts » et « detections », comme cela :
review:
# Optional: alerts configuration
alerts:
# Optional: labels that qualify as an alert (default: shown below)
labels:
- person
# Optional: required zones for an object to be marked as an alert (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones:
- Salon
- Entrée
- Cuisine
# Optional: detections configuration
detections:
# Optional: labels that qualify as a detection (default: all labels that are tracked / listened to)
labels:
- cat
# Optional: required zones for an object to be marked as a detection (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones:
- Salon
- Entrée
- Cuisine
Mais je te conseille cette solution en dernier recours, tu dois d’abord traiter le point juste au dessus concernant la zone de masquage TV. Car cette solution traite uniquement le classement en « Alerts » ou « Detections » mais pas la détection en tant que telle. Si ta zone de masquage TV n’est pas bien configurée, certes tu n’auras rien s’y référant dans les menus « Alerts/Detections » mais ta clé Coral elle continuera malgré tout à travailler sur ta TV en fond = c’est un peu cacher la poussière sous le tapis 
.
Il y a des issues ouvertes sur le github de la carte, je crois que tu n’es pas le seul touché 
… .
Pour toi qui utilise la carte Frigate tu as simplement à rajouter le second flux dans les entrées caméras de la carte, tu pourras ensuite naviguer entre les 2 flux (Camera_Salon_RLC-510A & Camera_Salon_RLC-510A_sub), donc ça je pense, à tester :
type: custom:frigate-card
cameras:
- camera_entity: camera.camera_salon_rlc_510a
live_provider: ha
icon: mdi:cctv
go2rtc:
modes:
- webrtc
webrtc_card:
entity: camera.camera_salon_rlc_510a
- camera_entity: camera.camera_salon_rlc_510a_sub
live_provider: ha
icon: mdi:cctv
go2rtc:
modes:
- webrtc
webrtc_card:
entity: camera.camera_salon_rlc_510a_sub
Bonsoir,
J’ai testé, mais comme je le pensais, je n’ai pas d’entité camera.Camera_Salon_RLC-510A_sub, donc ça génère une erreur…
Je reprécise que mon Frigate est dans un conteneur Docker dans un LXC Proxmox, pas dans HAOS.
J’ai mis Frigate Proxy pour avoir la caméra et Frigate dans HA.
Je pense que tu as parfaitement raison, depuis que j’ai modifié les cadres, et redéfinie la zone salon, je n’ai plus les détections sur la TV 
Merci des conseils 
Du coup, ok, je garde sous le coude l’ajout des zones dans les champs required_zonesen dernier recours 
Ha oui ! c’est pas que chez moi que ça déconne ^^
J’ai fait un +1 là-bas ^^
En tout cas, merci pour ton aide 
Ah pardon, au temps pour moi, le substream ne génère pas d’entité non plus chez moi , je croyais… mais non
En regardant la doc de la carte pour un substream, tu pourrais essayer ceci :
type: custom:frigate-card
cameras:
- camera_entity: ta caméra qui fonctionne déjà
...
...
- camera_entity: camera.camera_salon_rlc_510a ### donc la même entité
title: Salon Substream
live_provider: go2rtc
id: Camera_Salon_RLC-510A_sub ### ID go2RTC du substream dans ta config Frigate
...
...
Sinon voir l’exemple dans la doc de la carte.
Parfait 
!
N’utilisant pas cette carte, je ne peux pas t’aider davantage sur ce point
Pas de soucis !
Haa ! J’avais essayé un truc similaire, sans succès…
J’ai réussi ^^ avec ceci :
type: custom:frigate-card
cameras:
- camera_entity: camera.camera_salon_rlc_510a
live_provider: go2rtc
icon: phu:living-room
hide: false
dimensions:
layout:
fit: fill
go2rtc:
modes:
- webrtc
webrtc_card:
entity: camera.camera_salon_rlc_510a
frigate:
camera_name: Camera_Salon_RLC-510A
labels:
- person
- cat
dependencies:
cameras:
- Camera_Salon_RLC-510A_sub
- camera_entity: camera.camera_salon_rlc_510a
id: Camera_Salon_RLC-510A_sub
live_provider: go2rtc
icon: phu:living-room
hide: true
dimensions:
layout:
fit: fill
go2rtc:
modes:
- webrtc
stream: Camera_Salon_RLC-510A_sub
webrtc_card: {}
frigate:
camera_name: Camera_Salon_RLC-510A_sub
labels:
- person
- cat
title: Camera Salon Rlc-510A Sub
capabilities:
disable_except:
- substream
performance:
profile: high
dimensions:
aspect_ratio_mode: dynamic
timeline:
style: ribbon
media: all
image:
mode: screensaver
layout: {}
menu:
style: outside
position: bottom
alignment: right
buttons:
frigate:
alignment: opposing
cameras:
alignment: opposing
priority: 100
screenshot:
enabled: true
substreams:
enabled: true
icon: mdi:quality-low
live:
enabled: true
icon: mdi:quality-high
clips:
enabled: false
recordings:
enabled: true
image:
enabled: false
camera_ui:
enabled: true
expand:
enabled: true
media_player:
enabled: false
microphone:
enabled: false
play:
enabled: true
mute:
enabled: true
view:
default: live
dark_mode: "on"
camera_select: live
media_gallery:
controls:
thumbnails:
show_details: true
filter: {}
live:
layout: {}
preload: true
grid_options:
columns: 24
rows: auto
Mais j’ai aussi modifié ma configuration de Frigate en même temps car d’une part j’avais une erreur dans le flux go2rtc substream (il manquait le _sub dans la ligne du ffmpeg…), mais cette modif. n’avait pas permi à la carte de fonctionner correctement.
J’ai aussi ajouté la partie sur le webrtc :
go2rtc:
webrtc:
candidates:
- 192.168.2.64:8555
- stun:8555
streams:
Camera_Salon_RLC-510A:
- rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.2.163:554/Preview_01_main
- ffmpeg:Camera_Salon_RLC-510A#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
Camera_Salon_RLC-510A_sub:
- rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.2.163:554/Preview_01_sub
- ffmpeg:Camera_Salon_RLC-510A_sub#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
et là ça semble fonctionner
J’ai accès via le bouton substream (dont j’ai mis l’icone SD) au flux substream en 640x480. (pas dit que je m’en serve souvent ^^).
Merci de ton aide
Bonsoir,
@Integra j’aurais encore besoin d’un peu d’aide pour les détections ^^
(Je ne sais pas s’il ne faudrait pas recréer un sujet… Mais comme c’est lié à ce que j’ai fait ici… @WarC0zes si tu estimes plus cohérent de refaire un autre sujet, voudrais-tu bien scinder ce sujet à partir de ce message ? Merci d’avance).
J’ai de nouvelles caméras, des Annke C800, dont j’ai réussi à configurer les flux.
J’en ai mise deux en tests avant déménagement le mois prochain.
L’une est dans le salon à côté et une dans le bureau.
Sur celle dans le salon pas de soucis, les réglages que j’ai mis initialement pour la Reolink fonctionnent bien. (je mettrais le fichier de configuration en fin de message).
Mais sur celle dans le bureau, je n’ai aucune détection.
Je suppose que c’est parce que la caméra est plus proche de ce qui est filmé et donc que les mêmes objets en mouvement apparaissent plus gros.
Mais du coup, je ne sais pas comment faire pour modifier les valeurs des paramètres de détection pour qu’un humain soit détecté comme tel, et que mon chat comme un chat.
Et bien sûr, j’espère qu’il est possible de définir des paramètres de détection différents sur une caméra que dans la section générale…
Voilà le fichier de configuration :
# yaml-language-server: $schema=http://192.168.2.64:5000/api/config/schema.json
mqtt:
enabled: true
host: 192.168.2.140
port: 1883
user: '{FRIGATE_MQTT_USER}'
password: '{FRIGATE_MQTT_PASSWORD}'
stats_interval: 60
# Optional: Detectors configuration. Defaults to a single CPU detector
detectors:
# Required: name of the detector
coral:
# Required: type of the detector
# Frigate provided types include 'cpu', 'edgetpu', 'openvino' and 'tensorrt' (default: shown below)
# Additional detector types can also be plugged in.
# Detectors may require additional configuration.
# Refer to the Detectors configuration page for more information.
type: edgetpu
device: usb
# Optional: Database configuration
database:
# The path to store the SQLite DB (default: shown below)
path: /config/frigate.db
# Optional: TLS configuration
tls:
# Optional: Enable TLS for port 8971 (default: shown below)
enabled: true
# Optional: Authentication configuration
auth:
# Optional: Enable authentication
enabled: true
# Optional: Reset the admin user password on startup (default: shown below)
# New password is printed in the logs
reset_admin_password: false
# Optional: Cookie to store the JWT token for native auth (default: shown below)
#cookie_name: "frigate_token"
# Optional: Set secure flag on cookie. (default: False)
# NOTE: This should be set to True if you are using TLS
cookie_secure: true
# Optional: Session length in seconds (default: shown below)
session_length: 86400 # 24 hours
# Optional: Refresh time in seconds (default: shown below)
# When the session is going to expire in less time than this setting,
# it will be refreshed back to the session_length.
refresh_time: 43200 # 12 hours
# Optional: Rate limiting for login failures to help prevent brute force
# login attacks (default: None)
# See the docs for more information on valid values
failed_login_rate_limit: 1/second;5/minute;20/hour
# Optional: Trusted proxies for determining IP address to rate limit
# NOTE: This is only used for rate limiting login attempts and does not bypass
# authentication. See the authentication docs for more details.
trusted_proxies:
- 172.18.0.0/16 # <---- this is the subnet for the internal docker compose network
- 192.168.2.141/32 # <---- SWAG Reverse Proxy
# Optional: Number of hashing iterations for user passwords
# As of Feb 2023, OWASP recommends 600000 iterations for PBKDF2-SHA256
# NOTE: changing this value will not automatically update password hashes, you
# will need to change each user password for it to apply
hash_iterations: 600000
ffmpeg:
global_args: -hide_banner -loglevel warning
hwaccel_args: preset-vaapi
output_args:
record: preset-record-generic-audio-copy
birdseye:
enabled: false
snapshots:
# Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
enabled: true
# Optional: save a clean PNG copy of the snapshot image (default: shown below)
clean_copy: false
# Optional: print a timestamp on the snapshots (default: shown below)
timestamp: false
# Optional: draw bounding box on the snapshots (default: shown below)
bounding_box: true
# Optional: crop the snapshot (default: shown below)
crop: false
# Optional: height to resize the snapshot to (default: original size)
height: 720
# Optional: Restrict snapshots to objects that entered any of the listed zones (default: no required zones)
required_zones: []
# Optional: Camera override for retention settings (default: global values)
retain:
# Required: Default retention days (default: shown below)
default: 4
# Optional: Per object retention days
objects:
person: 4
# Optional: quality of the encoded jpeg, 0-100 (default: shown below)
quality: 100
# Optional: Record configuration
# NOTE: Can be overridden at the camera level
record:
# Optional: Enable recording (default: shown below)
# WARNING: If recording is disabled in the config, turning it on via
# the UI or MQTT later will have no effect.
enabled: true
# Optional: Number of minutes to wait between cleanup runs (default: shown below)
# This can be used to reduce the frequency of deleting recording segments from disk if you want to minimize i/o
expire_interval: 60
# Optional: Sync recordings with disk on startup and once a day (default: shown below).
sync_recordings: false
# Optional: Retention settings for recording
retain:
# Optional: Number of days to retain recordings regardless of events (default: shown below)
# NOTE: This should be set to 0 and retention should be defined in events section below
# if you only want to retain recordings of events.
days: 3 # <- number of days to keep continuous recordings -- mettre 0 pour purger
# Optional: Mode for retention. Available options are: all, motion, and active_objects
# all - save all recording segments regardless of activity
# motion - save all recordings segments with any detected motion
# active_objects - save all recording segments with active/moving objects
# NOTE: this mode only applies when the days setting above is greater than 0
#mode: active_objects
mode: all
export:
# Optional: Timelapse Output Args (default: shown below).
# NOTE: The default args are set to fit 24 hours of recording into 1 hour playback.
# See https://stackoverflow.com/a/58268695 for more info on how these args work.
# As an example: if you wanted to go from 24 hours to 30 minutes that would be going
# from 86400 seconds to 1800 seconds which would be 1800 / 86400 = 0.02.
# The -r (framerate) dictates how smooth the output video is.
# So the args would be -vf setpts=0.02*PTS -r 30 in that case.
timelapse_args: -vf setpts=0.04*PTS -r 30
# Optional: Recording Preview Settings
preview:
# Optional: Quality of recording preview (default: shown below).
# Options are: very_low, low, medium, high, very_high
quality: high
# Optional: Event recording settings
events:
# Optional: Number of seconds before the event to include (default: shown below)
pre_capture: 5
# Optional: Number of seconds after the event to include (default: shown below)
post_capture: 5
# Optional: Objects to save recordings for. (default: all tracked objects)
objects:
- person
# Optional: Retention settings for recordings of events
retain:
# Required: Default retention days (default: shown below)
default: 4 # <- number of days to keep event recordings -- mettre 0 pour purger
# Optional: Mode for retention. (default: shown below)
# all - save all recording segments for events regardless of activity
# motion - save all recordings segments for events with any detected motion
# active_objects - save all recording segments for event with active/moving objects
#
# NOTE: If the retain mode for the camera is more restrictive than the mode configured
# here, the segments will already be gone by the time this mode is applied.
# For example, if the camera retain mode is "motion", the segments without motion are
# never stored, so setting the mode to "all" here won't bring them back.
mode: motion
# Optional: Per object retention days
objects:
person: 4
cat: 4
# Optional: Review configuration
# NOTE: Can be overridden at the camera level
review:
# Optional: alerts configuration
alerts:
# Optional: labels that qualify as an alert (default: shown below)
labels:
- person
# Optional: required zones for an object to be marked as an alert (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones: []
# Optional: detections configuration
detections:
# Optional: labels that qualify as a detection (default: all labels that are tracked / listened to)
labels:
- cat
# Optional: required zones for an object to be marked as a detection (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones: []
# Optional: Motion configuration
# NOTE: Can be overridden at the camera level
motion:
# Optional: enables detection for the camera (default: True)
# NOTE: Motion detection is required for object detection,
# setting this to False and leaving detect enabled
# will result in an error on startup.
enabled: true
# 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 #30
# 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
# 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: Alpha value passed to cv2.accumulateWeighted when averaging frames to determine the background (default: shown below)
# Higher values mean the current frame impacts the average a lot, and a new object will be averaged into the background faster.
# Low values will cause things like moving shadows to be detected as motion for longer.
# https://www.geeksforgeeks.org/background-subtraction-in-an-image-using-concept-of-running-average/
frame_alpha: 0.01
# Optional: Height of the resized motion frame (default: 100)
# Higher values will result in more granular motion detection at the expense of higher CPU usage.
# Lower values result in less CPU, but small changes may not register as motion.
frame_height: 100
# Optional: motion mask
# NOTE: see docs for more detailed info on creating masks
# mask: 0.000,0.469,1.000,0.469,1.000,1.000,0.000,1.000
# Optional: improve contrast (default: shown below)
# Enables dynamic contrast improvement. This should help improve night detections at the cost of making motion detection more sensitive
# for daytime.
improve_contrast: true
# Optional: Delay when updating camera motion through MQTT from ON -> OFF (default: shown below).
mqtt_off_delay: 30
# 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
- cat
# Optional: filters to reduce false positives for specific object types
filters:
person:
# Optional: minimum width*height 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: 0.4 #0.6
# Optional: maximum width/height of the bounding box for the detected object (default: 24000000)
max_ratio: 1 #2.0
# Optional: minimum score for the object to initiate tracking (default: shown below)
min_score: 0.7 #0.5
# Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
threshold: 0.7 #0.7
cat: # Voir ici : https://community.home-assistant.io/t/frigate-detecting-small-objects-birds-cats-etc/565386/10?u=milesteg
min_area: 2000 # Adjust depending on the size and distance of the object in view
max_area: 10000 # Limit larger object detections
min_score: 0.6 # Confidence score for detection
threshold: 0.7 # Higher threshold to avoid false positives
min_ratio: 0.4 # Cat's body tends to be longer than it is tall
max_ratio: 2.0 # Allow for a longer body, so the width can be up to twice the height
go2rtc:
webrtc:
candidates:
- 192.168.2.64:8555
- stun:8555
streams:
Camera_Salon_RLC_510A:
- rtsp://{FRIGATE_RTSP_REOLINK_USER}:{FRIGATE_RTSP_REOLINK_PASSWORD}@192.168.2.163:554/Preview_01_main
- ffmpeg:Camera_Salon_RLC_510A#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
Camera_Salon_RLC_510A_sub:
- rtsp://{FRIGATE_RTSP_REOLINK_USER}:{FRIGATE_RTSP_REOLINK_PASSWORD}@192.168.2.163:554/Preview_01_sub
- ffmpeg:Camera_Salon_RLC_510A_sub#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
Camera_Annke_C800_Test_1:
- rtsp://{FRIGATE_RTSP_ANNKE_USER}:{FRIGATE_RTSP_ANNKE_PASSWORD}@192.168.2.164:554/H264/ch1/main/av_stream
- ffmpeg:Camera_Annke_C800_Test_1#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
Camera_Annke_C800_Test_1_sub:
- rtsp://{FRIGATE_RTSP_ANNKE_USER}:{FRIGATE_RTSP_ANNKE_PASSWORD}@192.168.2.164:554/H264/ch1/sub/av_stream
- ffmpeg:Camera_Annke_C800_Test_1_sub#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
Camera_Annke_C800_Test_2:
- rtsp://{FRIGATE_RTSP_ANNKE_USER}:{FRIGATE_RTSP_ANNKE_PASSWORD}@192.168.2.165:554/H264/ch1/main/av_stream
- ffmpeg:Camera_Annke_C800_Test_2#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
Camera_Annke_C800_Test_2_sub:
- rtsp://{FRIGATE_RTSP_ANNKE_USER}:{FRIGATE_RTSP_ANNKE_PASSWORD}@192.168.2.165:554/H264/ch1/sub/av_stream
- ffmpeg:Camera_Annke_C800_Test_2_sub#audio=aac # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
cameras:
Camera_Salon_RLC_510A:
enabled: true
ffmpeg:
hwaccel_args: preset-vaapi
# hwaccel_args: preset-intel-qsv-h265
inputs:
- path: rtsp://127.0.0.1:8554/Camera_Salon_RLC_510A # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles:
- record
- detect
- path: rtsp://127.0.0.1:8554/Camera_Salon_RLC_510A_sub # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles: []
detect:
enabled: true # <---- disable detection until you have a working camera feed
fps: 10
width: 1280 # 640 <---- update for your camera's resolution
height: 720 # 480 <---- update for your camera's resolution
record: # <----- Enable recording
enabled: true
snapshots:
enabled: true
motion:
mask:
- 0.037,0.5,0.044,0.678,0.21,0.663,0.211,0.504
- 0,0.296,0,0,1,0,1,0.289,0.886,0.283,0.818,0.288,0.88,0.363,0.765,0.36,0.657,0.377,0.486,0.38
threshold: 30
contour_area: 10
improve_contrast: true
zones:
Salon:
coordinates:
0,0.304,0,0.619,0,1,1,1,1,0.282,0.952,0.28,0.897,0.284,0.824,0.289,0.884,0.366,0.859,0.367,0.845,0.801,0.663,0.758,0.662,0.723,0.623,0.705,0.623,0.641,0.545,0.618,0.55,0.381,0.498,0.384,0.248,0.342,0.023,0.301
inertia: 3
loitering_time: 0
Entrée:
coordinates:
0.551,0.383,0.547,0.617,0.625,0.639,0.623,0.701,0.665,0.721,0.675,0.369,0.645,0.381,0.601,0.385
loitering_time: 0
inertia: 3
Cuisine:
coordinates: 0.678,0.375,0.664,0.752,0.841,0.797,0.857,0.362,0.815,0.356,0.78,0.358
loitering_time: 0
inertia: 3
objects:
mask: 0.037,0.499,0.045,0.673,0.21,0.659,0.208,0.505
Camera_Annke_C800_Test_1:
enabled: true
ffmpeg:
hwaccel_args: preset-vaapi
# hwaccel_args: preset-intel-qsv-h265
inputs:
- path: rtsp://127.0.0.1:8554/Camera_Annke_C800_Test_1 # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles:
- record
- path: rtsp://127.0.0.1:8554/Camera_Annke_C800_Test_1_sub # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles:
- detect
#output_args:
# record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v copy -tag:v hvc1 -bsf:v hevc_mp4toannexb -c:a aac
detect:
enabled: true # <---- disable detection until you have a working camera feed
fps: 10
width: 1280 # 640 <---- update for your camera's resolution
height: 720 # 480 <---- update for your camera's resolution
record: # <----- Enable recording
enabled: true
snapshots:
enabled: true
motion:
mask:
- 0.037,0.628,0.045,0.842,0.209,0.843,0.2,0.642
- 0,0.35,0,0,1,0,1,0.279,0.893,0.289,0.889,0.343,0.923,0.398,0.765,0.415,0.714,0.421,0.716,0.438,0.58,0.456,0.493,0.408
threshold: 30
contour_area: 10
improve_contrast: true
zones:
Salon:
coordinates:
0,0.352,0,0.619,0,1,1,1,1,0.275,0.893,0.286,0.888,0.342,0.926,0.4,0.902,0.415,0.892,0.948,0.707,0.936,0.708,0.888,0.666,0.824,0.582,0.816,0.579,0.457,0.497,0.41,0.328,0.394,0.033,0.353
inertia: 3
loitering_time: 0
Entrée:
coordinates:
0.579,0.454,0.58,0.621,0.582,0.813,0.668,0.82,0.708,0.882,0.718,0.434,0.688,0.446,0.644,0.45
loitering_time: 0
inertia: 3
Cuisine:
coordinates: 0.718,0.42,0.709,0.932,0.889,0.947,0.903,0.402,0.859,0.404,0.79,0.41
loitering_time: 0
inertia: 3
objects:
mask: 0.038,0.635,0.046,0.839,0.204,0.839,0.2,0.641
Camera_Annke_C800_Test_2:
enabled: true
ffmpeg:
hwaccel_args: preset-vaapi
# hwaccel_args: preset-intel-qsv-h265
inputs:
- path: rtsp://127.0.0.1:8554/Camera_Annke_C800_Test_2 # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles:
- record
- path: rtsp://127.0.0.1:8554/Camera_Annke_C800_Test_2_sub # <--- the name here must match the name of the camera in restream
input_args: preset-rtsp-restream
roles:
- detect
#output_args:
# record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v copy -tag:v hvc1 -bsf:v hevc_mp4toannexb -c:a aac
detect:
enabled: true # <---- disable detection until you have a working camera feed
fps: 10
width: 1280 # 640 <---- update for your camera's resolution
height: 720 # 480 <---- update for your camera's resolution
record: # Voir détails des entrée dans la partie commune
enabled: true
retain:
days: 2 # <- number of days to keep continuous recordings -- mettre 0 pour purger
mode: all
events:
retain:
default: 2 # <- number of days to keep event recordings -- mettre 0 pour purger
mode: motion
objects:
person: 2
cat: 2
snapshots: # Voir détails des entrée dans la partie commune
enabled: true
retain:
# Required: Default retention days (default: shown below)
default: 2
# Optional: Per object retention days
objects:
person: 2
# Optional: quality of the encoded jpeg, 0-100 (default: shown below)
quality: 100
# Optional
zones:
Fenêtre_bureau:
coordinates: 1,1,0.796,0.774,0.807,0.425,0.779,0,1,0,1,0.327,1,0.662
loitering_time: 0
inertia: 3
Arbre_à_chat:
coordinates: 0.479,0.723,0.724,0.74,0.739,0.344,0.717,0.011,0.476,0.017,0.515,0.327
loitering_time: 0
Étagère_bureau:
coordinates: 0,0.592,0.413,0.642,0.414,0.383,0,0.377
loitering_time: 0
Bureau:
coordinates: 0,1,1,1,1,0,0,0
loitering_time: 0
ui:
# Optional: Set a timezone to use in the UI (default: use browser local time)
# timezone: America/Denver
# Optional: Set the time format used.
# Options are browser, 12hour, or 24hour (default: browser)
time_format: 24hour
# Optional: Set the date style for a specified length.
# Options are: full, long, medium, short
# Examples:
# short: 2/11/23
# medium: Feb 11, 2023
# full: Saturday, February 11, 2023
# (default: short).
date_style: short
# Optional: Set the time style for a specified length.
# Options are: full, long, medium, short
# Examples:
# short: 8:14 PM
# medium: 8:15:22 PM
# full: 8:15:22 PM Mountain Standard Time
# (default: medium).
time_style: medium
# Optional: Ability to manually override the date / time styling to use strftime format
# https://www.gnu.org/software/libc/manual/html_node/Formatting-Calendar-Time.html
# possible values are shown above (default: not set)
strftime_fmt: '%d/%m/%Y/ %H:%M:%S'
# Optional: Telemetry configuration
telemetry:
# Optional: Enabled network interfaces for bandwidth stats monitoring (default: empty list, let nethogs search all)
network_interfaces: []
# Optional: Configure system stats
stats:
# Enable AMD GPU stats (default: shown below)
amd_gpu_stats: false
# Enable Intel GPU stats (default: shown below)
intel_gpu_stats: true
# Enable network bandwidth stats monitoring for camera ffmpeg processes, go2rtc, and object detectors. (default: shown below)
# NOTE: The container must either be privileged or have cap_net_admin, cap_net_raw capabilities enabled.
network_bandwidth: false
# Optional: Enable the latest version outbound check (default: shown below)
# NOTE: If you use the HomeAssistant integration, disabling this will prevent it from reporting new versions
version_check: true
version: 0.14
Et une image de la caméra :
Voilà voilà
Merci d’avance, et bonne soirée.
Bonjour @MilesTEG1,
À moins de dépasser du cadre de la caméra, la détection devrait se faire normalement. Tu peux t’en assurer en regardant la vue « Debug » avec les cadres de détection pour voir comment cela se comporte.
Oui tu peux paramétrer la détection spécifiquement par caméra, ça prendra le pas sur le paramétrage général (que tu peux laisser).
Exemple pour une de mes caméras :
cameras:
Salon:
ffmpeg:
inputs:
- path: rtsp://user:password@192.168.0.43:554/stream1
input_args: preset-rtsp-restream
roles:
- record
- path: rtsp://user:password@192.168.0.43:554/stream2
input_args: preset-rtsp-restream
roles:
- detect
detect:
enabled: false
width: 1280
height: 720
fps: 5
objects:
track:
- person
filters:
person:
min_score: 0.6
threshold: 0.75
Salut @Integra
Disons que quand je passe devant cette caméra, on ne voit que mon buste et ma tête ^^
Oui j’ai pu voir ça en faisant des essais cette après-midi ^^
J’ai essayé ces réglages :
objects:
# Optional: list of objects to track from labelmap.txt (default: shown below)
track:
- person
- cat
# Optional: filters to reduce false positives for specific object types
filters:
person:
# Optional: minimum width*height of the bounding box for the detected object (default: 0)
min_area: 100000
# Optional: maximum width*height of the bounding box for the detected object (default: 24000000)
max_area: 2000000
# Optional: minimum width/height of the bounding box for the detected object (default: 0)
min_ratio: 0.4 #0.6
# Optional: maximum width/height of the bounding box for the detected object (default: 24000000)
max_ratio: 1 #2.0
# Optional: minimum score for the object to initiate tracking (default: shown below)
min_score: 0.7 #0.5
# Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
threshold: 0.7 #0.7
cat: # Voir ici : https://community.home-assistant.io/t/frigate-detecting-small-objects-birds-cats-etc/565386/10?u=milesteg
min_area: 10000 # Adjust depending on the size and distance of the object in view
max_area: 200000 # Limit larger object detections
min_score: 0.6 # Confidence score for detection
threshold: 0.7 # Higher threshold to avoid false positives
min_ratio: 0.4 # Cat's body tends to be longer than it is tall
max_ratio: 2.0 # Allow for a longer body, so the width can be up to twice the height
Et ça semble fonctionner à peu près. Faut que je voie sur le long terme si je n’ai pas de faux positifs, mais du coup, ça m’apprend que ces réglages vont être dépendant de l’emplacement de la caméra ^^
En tout cas, merci pour ton aide ^^
PS : mettre les fps à 5 pour la détection, c’est pas un peu trop faible ?
J’avais fait des tests sur ma caméra et quand je me rapprochais elle ne voyait que mon buste et mon visage comme pour toi, et Frigate détectait bien un humain .
De ce que je vois, tu as paramétré les cadres de détections (min_area, max_area, min_ratio et max_ratio) et si ces paramètres font bien ce que je pense, à savoir définir la taille minimum et maximum du cadre de détection, alors c’est peut-être ça qui pose problème.
Si les cadres sont trop petits et que tu es proche de la caméra forcément tu déborderas .
De mon côté, je n’ai rien de tout ça (donc ça prend les valeurs par défaut), j’ai simplement le min_score et threshold.
C’est ce qui est conseillé dans la doc de mémoire. Et dans la mesure ou Frigate lance la détection sur des images et non sur un flux vidéo, 5 images pas secondes suffisent, en tout cas pour moi.
Les détections restent fiables et ça soulage d’autant le CPU.
salut @Integra
Ho je n’avais pas vu ça…
Je vais modifier alors, ça fera ça de moins en charge CPU/iGPU/Coral
Faudra que je vois correctement ça quand elles seront placées au bon endroit ^^
Mais je prend note Peut-être que je ne devrais pas mettre de borne maximale pour celle que j’ai mise dans mon bureau ^^
Par contre, la vache, ça prend de la place sur le disque ! J’ai dû réduire la durée de conservation à 2 jours, sinon mon disque était plein … bon sur ce 2To j’ai aussi 3 caméras Reolink en 5MP qui sont enregistrées dessus par Synology Surveillance Station.
Va me falloir investir dans un disque de 4To un de ces 4 
Ah oui ça prend vite de la place quand on enregistre en continu avec de hautes résolutions … .
Dans mon cas je n’enregistre pas en continu mais seulement quand un objet est détecté donc ça limite grandement l’occupation en stockage et l’utilisation du CPU (encore lui ) mais forcément c’est moins complet.
Bonjour, ma question n’est pas totalement lié à votre sujet mais je possède 2 Reolink 510A je voyait les lives avec RTSPtoWebrtc avant la mise à jour de novembre et j’ai du supprimer puisque got2rtc est passé en natif. Depuis je n’ai plus de lecture de flux en RTC et plus de lecture à distance. J’ai cru voir sur plusieurs forum que les flux réolink étaient capricieux je ne sais pas si vous avez une solution pour que je puisse lire les flux vidéos de mes caméras ? Pour l’extérieur je passe pas NGINX reverse proxy. Merci par avance de votre aide.
Salut,
@Pierre_H Il est installé comment Frigate ?
Chez moi c’est dans un conteneur Docker hors de la VM HAOS.
J’ai mis le proxy Frigate dans HA, et j’accède au flux Go2RTC de Frigate.
Tu utilises quoi comme carte pour afficher la caméra ?
Oups j’ai oublié de préciser je n’utilise pas frigate c’est pour ça que j’ai dit que c’était pas tout a fait en rapport avec le sujet 
.
J’ai les flux de mes caméras dans l’intégration Reolink et j’ai essayé de mettre Onvif et caméra générique sans succès non plus. J’utilise sois la carte frigate ou la carte picture glance mais je n’ai pas de flux rtc uniquement mse ou vga hls…
Je sèche un peu comment récupérer les flux qui fonctionnaient bien avec le module web2rtc avant.
Ha ! Et bien je ne te serais pas d’un grand secours…
Sache que les caméras Reolink ont un nombre très limité de flux vidéo.
Sur les 510A, c’est 2 flux vidéo HD. Et plus (je ne sais plus combien) en basse définition.
Tu as autre chose qui utilisent les flux de la caméra ?
J’ai que les flux sur l’appli réolink et sur HA uniquement.