image: repository: tccr.io/truecharts/frigate-nvidia pullPolicy: IfNotPresent tag: latest@sha256:9facc1383ebbf148873bcc2fba501868b0e09417cffff7f6c06fb31b9c9b95ec 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///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'