TrueChartsCatalogClone/incubator/frigate/2.0.2/ix_values.yaml

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image:
repository: blakeblackshear/frigate
pullPolicy: IfNotPresent
tag: 0.10.0-beta6-amd64nvidia
securityContext:
readOnlyRootFilesystem: false
runAsNonRoot: false
configmap:
config:
enabled: true
data:
config.yml: |
mqtt:
# Required: host name
host: {{ .Values.frigate.mqtt.host }}
# Optional: port (default: shown below)
port: {{ .Values.frigate.mqtt.port }}
# Optional: topic prefix (default: shown below)
# NOTE: must be unique if you are running multiple instances
topic_prefix: frigate
# Optional: client id (default: shown below)
# NOTE: must be unique if you are running multiple instances
client_id: frigate
{{- if .Values.frigate.mqtt.authenticated }}
user: {{ .Values.frigate.mqtt.username }}
password: {{ .Values.frigate.mqtt.password }}
# Optional: user
# user: mqtt_user
# Optional: password
# NOTE: MQTT password can be specified with an environment variables that must begin with 'FRIGATE_'.
# e.g. password: '{FRIGATE_MQTT_PASSWORD}'
# password: password
{{- end }}
# Optional: tls_ca_certs for enabling TLS using self-signed certs (default: None)
# tls_ca_certs: /path/to/ca.crt
# Optional: tls_client_cert and tls_client key in order to use self-signed client
# certificates (default: None)
# NOTE: certificate must not be password-protected
# do not set user and password when using a client certificate
# tls_client_cert: /path/to/client.crt
# tls_client_key: /path/to/client.key
# Optional: tls_insecure (true/false) for enabling TLS verification of
# the server hostname in the server certificate (default: None)
# tls_insecure: false
# Optional: interval in seconds for publishing stats (default: shown below)
stats_interval: 60
# Optional: Detectors configuration. Defaults to a single CPU detector
detectors:
# Required: name of the detector
{{- if .Values.persistence.coral }}
{{- if .Values.persistence.coral.enabled }}
coral:
# Required: type of the detector
# Valid values are 'edgetpu' (requires device property below) and 'cpu'.
type: edgetpu
# Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
device: usb
{{- else }}
cpu1:
type: cpu
# Optional: num_threads value passed to the tflite.Interpreter (default: shown below)
# This value is only used for CPU types
num_threads: 2
{{- end }}
{{- end }}
# Optional: Database configuration
# database:
# The path to store the SQLite DB (default: shown below)
# path: /media/frigate/frigate.db
# Optional: model modifications
# model:
# Optional: path to the model (default: automatic based on detector)
# path: /edgetpu_model.tflite
# Optional: path to the labelmap (default: shown below)
# labelmap_path: /labelmap.txt
# Required: Object detection model input width (default: shown below)
# width: 320
# Required: Object detection model input height (default: shown below)
# height: 240
# Optional: Label name modifications. These are merged into the standard labelmap.
# labelmap:
# 2: vehicle
# Optional: logger verbosity settings
logger:
# Optional: Default log verbosity (default: shown below)
default: info
# Optional: Component specific logger overrides
# logs:
# frigate.event: info
# Optional: set environment variables
# environment_vars:
# EXAMPLE_VAR: value
# Optional: birdseye configuration
birdseye:
# Optional: Enable birdseye view (default: shown below)
enabled: {{ .Values.frigate.birdseye.enabled }}
# Optional: Width of the output resolution (default: shown below)
width: 1280
# Optional: Height of the output resolution (default: shown below)
height: 720
# Optional: Encoding quality of the mpeg1 feed (default: shown below)
# 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources.
quality: 8
# Optional: Mode of the view. Available options are: objects, motion, and continuous
# objects - cameras are included if they have had a tracked object within the last 30 seconds
# motion - cameras are included if motion was detected in the last 30 seconds
# continuous - all cameras are included always
mode: {{ .Values.frigate.birdseye.mode }}
# Optional: ffmpeg configuration
ffmpeg:
# Optional: global ffmpeg args (default: shown below) warning instead of debug
global_args: -hide_banner -loglevel debug
# Optional: global hwaccel args (default: shown below)
# NOTE: See hardware acceleration docs for your specific device
# hwaccel_args: []
# Optional: global input args (default: shown below)
# input_args: -avoid_negative_ts make_zero -fflags +genpts+discardcorrupt -rtsp_transport tcp -stimeout 5000000 -use_wallclock_as_timestamps 1
# Optional: global output args
# output_args:
# Optional: output args for detect streams (default: shown below)
# detect: -f rawvideo -pix_fmt yuv420p
# Optional: output args for record streams (default: shown below)
# record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
# Optional: output args for rtmp streams (default: shown below)
# rtmp: -c copy -f flv
# Optional: Detect configuration
# NOTE: Can be overridden at the camera level
detect:
# Optional: width of the frame for the input with the detect role (default: shown below)
width: 1280
# Optional: height of the frame for the input with the detect role (default: shown below)
height: 720
# Optional: desired fps for your camera for the input with the detect role (default: shown below)
# NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
fps: 5
# Optional: enables detection for the camera (default: True)
# This value can be set via MQTT and will be updated in startup based on retained value
enabled: True
# Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate)
# max_disappeared: 25
# Optional: Frequency for running detection on stationary objects (default: 10x the frame rate)
# stationary_interval: 50
# 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
- car
- motorcyle
- cat
- dog
# 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 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 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
# mask: 0,0,1000,0,1000,200,0,200
# Optional: Motion configuration
# NOTE: Can be overridden at the camera level
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: 25
# Optional: Minimum size in pixels in the resized motion image that counts as motion (default: 30)
# 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:
# - 15 - high sensitivity
# - 30 - medium sensitivity
# - 50 - low sensitivity
contour_area: 30
# Optional: Alpha value passed to cv2.accumulateWeighted when averaging the motion delta across multiple frames (default: shown below)
# Higher values mean the current frame impacts the delta a lot, and a single raindrop may register as motion.
# Too low and a fast moving person wont be detected as motion.
# delta_alpha: 0.2
# 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: 0.2
# Optional: Height of the resized motion frame (default: 50)
# This operates as an efficient blur alternative. 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: 50
# Optional: motion mask
# NOTE: see docs for more detailed info on creating masks
# mask: 0,900,1080,900,1080,1920,0,1920
# Optional: Record configuration
# NOTE: Can be overridden at the camera level
record:
# Optional: Enable recording (default: shown below)
enabled: 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: 7
# 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: motion
# Optional: Event recording settings
events:
# Optional: Maximum length of time to retain video during long events. (default: shown below)
# NOTE: If an object is being tracked for longer than this amount of time, the retained recordings
# will be the last x seconds of the event unless retain->days under record is > 0.
max_seconds: 300
# 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: Restrict recordings to objects that entered any of the listed zones (default: no required zones)
# required_zones: []
# Optional: Retention settings for recordings of events
retain:
# Required: Default retention days (default: shown below)
default: 14
# 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: active_objects
# Optional: Per object retention days
# objects:
# person: 15
# Optional: Configuration for the jpg snapshots written to the clips directory for each event
# NOTE: Can be overridden at the camera level
snapshots:
# Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
# This value can be set via MQTT and will be updated in startup based on retained value
enabled: 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: False
# Optional: crop the snapshot (default: shown below)
# crop: False
# Optional: height to resize the snapshot to (default: original size)
# height: 175
# 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: 10
# Optional: Per object retention days
objects:
person: 15
# Optional: RTMP configuration
# NOTE: Can be overridden at the camera level
rtmp:
# Optional: Enable the RTMP stream (default: True)
enabled: True
# Optional: Live stream configuration for WebUI
# NOTE: Can be overridden at the camera level
live:
# Optional: Set the height of the live stream. (default: 720)
# This must be less than or equal to the height of the detect stream. Lower resolutions
# reduce bandwidth required for viewing the live stream. Width is computed to match known aspect ratio.
# height: 720
# Optional: Set the encode quality of the live stream (default: shown below)
# 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources.
quality: 8
# Optional: in-feed timestamp style configuration
# NOTE: Can be overridden at the camera level
# timestamp_style:
# Optional: Position of the timestamp (default: shown below)
# "tl" (top left), "tr" (top right), "bl" (bottom left), "br" (bottom right)
# position: "tl"
# Optional: Format specifier conform to the Python package "datetime" (default: shown below)
# Additional Examples:
# german: "%d.%m.%Y %H:%M:%S"
# format: "%m/%d/%Y %H:%M:%S"
# Optional: Color of font
# color:
# All Required when color is specified (default: shown below)
# red: 255
# green: 255
# blue: 255
# Optional: Line thickness of font (default: shown below)
# thickness: 2
# Optional: Effect of lettering (default: shown below)
# None (No effect),
# "solid" (solid background in inverse color of font)
# "shadow" (shadow for font)
effect: solid
# Required
cameras:
{{- range .Values.frigate.cameras }}
# Required: name of the camera
{{ .name }}:
objects:
# Optional: list of objects to track from labelmap.txt (default: shown below)
track:
{{- range .objects.track }}
- {{ . }}
{{- end }}
detect:
width: {{ .detect.width }}
height: {{ .detect.height }}
# Required: ffmpeg settings for the camera
ffmpeg:
# Required: A list of input streams for the camera. See documentation for more information.
inputs:
{{- range .inputs }}
- path: {{ .path }}
roles:
{{- range .roles }}
- {{ . }}
{{- end }}
{{- end }}
record:
enabled: {{ .record.enabled }}
# Optional: timeout for highest scoring image before allowing it
# to be replaced by a newer image. (default: shown below)
best_image_timeout: 60
snapshots:
enabled: {{ .snapshots.enabled }}
# Optional: zones for this camera
# zones:
# Required: name of the zone
# NOTE: This must be different than any camera names, but can match with another zone on another
# camera.
# front_steps:
# Required: List of x,y coordinates to define the polygon of the zone.
# NOTE: Coordinates can be generated at https://www.image-map.net/
# coordinates: 545,1077,747,939,788,805
# Optional: List of objects that can trigger this zone (default: all tracked objects)
# objects:
# - person
# Optional: Zone level object filters.
# NOTE: The global and camera filters are applied upstream.
# filters:
# person:
# min_area: 5000
# max_area: 100000
# threshold: 0.7
# Optional: Configuration for the jpg snapshots published via MQTT
# mqtt:
# Optional: Enable publishing snapshot via mqtt for camera (default: shown below)
# NOTE: Only applies to publishing image data to MQTT via 'frigate/<camera_name>/<object_name>/snapshot'.
# All other messages will still be published.
# enabled: true
# Optional: print a timestamp on the snapshots (default: shown below)
# timestamp: True
# Optional: draw bounding box on the snapshots (default: shown below)
# bounding_box: True
# Optional: crop the snapshot (default: shown below)
# crop: True
# Optional: height to resize the snapshot to (default: shown below)
# height: 270
# Optional: jpeg encode quality (default: shown below)
# quality: 70
# Optional: Restrict mqtt messages to objects that entered any of the listed zones (default: no required zones)
# required_zones: []
{{- end }}
podSecurityContext:
runAsUser: 0
runAsGroup: 0
portal:
enabled: true
service:
main:
ports:
main:
targetPort: 5000
port: 5000
rtmp:
enabled: true
ports:
rtmp:
protocol: TCP
enabled: true
port: 1935
targetPort: 1935
ingress:
rtmp:
autoLink: true
frigate:
mqtt:
host: mosquitto.ix-mosquitto.svc.cluster.local
port: 1883
authentitcated: false
username: mqtt_user
password: password
birdseye:
enabled: true
mode: motion
cameras:
- name: camera1
objects:
# Optional: list of objects to track from labelmap.txt (default: shown below)
track:
- person
- car
- motorcyle
- cat
- dog
detect:
height: 720
width: 1280
inputs:
# Required: the path to the stream
# NOTE: path may include environment variables, which must begin with 'FRIGATE_' and be referenced in {}
- path: rtsp://username:password@highres.url
# Required: list of roles for this stream. valid values are: detect,record,rtmp
# NOTICE: In addition to assigning the record, and rtmp roles,
# they must also be enabled in the camera config.
roles:
- record
- path: rtsp://username:password@lowres.url
roles:
- detect
- rtmp
record:
enabled: True
# Optional: timeout for highest scoring image before allowing it
# to be replaced by a newer image. (default: shown below)
best_image_timeout: 60
snapshots:
enabled: true
persistence:
cache:
enabled: true
mountPath: "/tmp/cache"
type: "emptyDir"
shm:
enabled: true
mountPath: "/dev/shm"
type: "emptyDir"
medium: "Memory"
media:
enabled: true
mountPath: "/media"
frigate-config:
enabled: true
mountPath: "/config/config.yml"
subPath: "config.yml"
type: "custom"
volumeSpec:
configMap:
name: '{{ template "tc.common.names.fullname" . }}-config'