mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
232 lines
8.1 KiB
YAML
232 lines
8.1 KiB
YAML
web_port: 5000
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################
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## List of detectors.
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## Currently supported types: cpu, edgetpu
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## EdgeTPU requires device as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
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################
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detectors:
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coral:
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type: edgetpu
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device: usb
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mqtt:
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host: mqtt.server.com
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topic_prefix: frigate
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# client_id: frigate # Optional -- set to override default client id of 'frigate' if running multiple instances
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# user: username # Optional
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#################
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## Environment variables that begin with 'FRIGATE_' may be referenced in {}.
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## password: '{FRIGATE_MQTT_PASSWORD}'
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#################
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# password: password # Optional
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################
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# Global configuration for saving clips
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################
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save_clips:
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###########
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# Maximum length of time to retain video during long events.
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# If an object is being tracked for longer than this amount of time, the cache
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# will begin to expire and the resulting clip will be the last x seconds of the event.
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###########
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max_seconds: 300
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#################
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# Default ffmpeg args. Optional and can be overwritten per camera.
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# Should work with most RTSP cameras that send h264 video
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# Built from the properties below with:
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# "ffmpeg" + global_args + input_args + "-i" + input + output_args
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#################
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# ffmpeg:
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# global_args:
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# - -hide_banner
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# - -loglevel
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# - panic
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# hwaccel_args: []
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# input_args:
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# - -avoid_negative_ts
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# - make_zero
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# - -fflags
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# - nobuffer
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# - -flags
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# - low_delay
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# - -strict
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# - experimental
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# - -fflags
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# - +genpts+discardcorrupt
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# - -vsync
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# - drop
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# - -rtsp_transport
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# - tcp
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# - -stimeout
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# - '5000000'
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# - -use_wallclock_as_timestamps
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# - '1'
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# output_args:
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# - -f
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# - rawvideo
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# - -pix_fmt
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# - yuv420p
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####################
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# Global object configuration. Applies to all cameras
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# unless overridden at the camera levels.
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# Keys must be valid labels. By default, the model uses coco (https://dl.google.com/coral/canned_models/coco_labels.txt).
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# All labels from the model are reported over MQTT. These values are used to filter out false positives.
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# min_area (optional): minimum width*height of the bounding box for the detected object
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# max_area (optional): maximum width*height of the bounding box for the detected object
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# min_score (optional): minimum score for the object to initiate tracking
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# threshold (optional): The minimum decimal percentage for tracked object's computed score to considered a true positive
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####################
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objects:
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track:
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- person
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filters:
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person:
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min_area: 5000
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max_area: 100000
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min_score: 0.5
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threshold: 0.85
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cameras:
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back:
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ffmpeg:
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################
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# Source passed to ffmpeg after the -i parameter. Supports anything compatible with OpenCV and FFmpeg.
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# Environment variables that begin with 'FRIGATE_' may be referenced in {}
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################
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input: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
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#################
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# These values will override default values for just this camera
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#################
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# global_args: []
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# hwaccel_args: []
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# input_args: []
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# output_args: []
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################
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## Optionally specify the resolution of the video feed. Frigate will try to auto detect if not specified
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################
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# height: 1280
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# width: 720
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################
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## Specify the framerate of your camera
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##
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## NOTE: This should only be set in the event ffmpeg is unable to determine your camera's framerate
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## on its own and the reported framerate for your camera in frigate is well over what is expected.
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################
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# fps: 5
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################
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## Optional mask. Must be the same aspect ratio as your video feed. Value is any of the following:
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## - name of a file in the config directory
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## - base64 encoded image prefixed with 'base64,' eg. 'base64,asfasdfasdf....'
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## - polygon of x,y coordinates prefixed with 'poly,' eg. 'poly,0,900,1080,900,1080,1920,0,1920'
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##
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## The mask works by looking at the bottom center of the bounding box for the detected
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## person in the image. If that pixel in the mask is a black pixel, it ignores it as a
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## false positive. In my mask, the grass and driveway visible from my backdoor camera
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## are white. The garage doors, sky, and trees (anywhere it would be impossible for a
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## person to stand) are black.
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##
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## Masked areas are also ignored for motion detection.
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################
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# mask: back-mask.bmp
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################
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# Allows you to limit the framerate within frigate for cameras that do not support
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# custom framerates. A value of 1 tells frigate to look at every frame, 2 every 2nd frame,
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# 3 every 3rd frame, etc.
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################
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take_frame: 1
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################
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# The number of seconds to retain the highest scoring image for the best.jpg endpoint before allowing it
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# to be replaced by a newer image. Defaults to 60 seconds.
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################
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best_image_timeout: 60
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################
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# MQTT settings
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################
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# mqtt:
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# crop_to_region: True
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# snapshot_height: 300
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################
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# Zones
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################
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zones:
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#################
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# Name of the zone
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################
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front_steps:
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####################
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# A list of x,y coordinates to define the polygon of the zone. The top
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# left corner is 0,0. Can also be a comma separated string of all x,y coordinates combined.
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# The same zone name can exist across multiple cameras if they have overlapping FOVs.
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# An object is determined to be in the zone based on whether or not the bottom center
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# of it's bounding box is within the polygon. The polygon must have at least 3 points.
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# Coordinates can be generated at https://www.image-map.net/
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####################
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coordinates:
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- 545,1077
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- 747,939
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- 788,805
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################
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# Zone level object filters. These are applied in addition to the global and camera filters
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# and should be more restrictive than the global and camera filters. The global and camera
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# filters are applied upstream.
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################
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filters:
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person:
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min_area: 5000
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max_area: 100000
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threshold: 0.8
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################
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# This will save a clip for each tracked object by frigate along with a json file that contains
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# data related to the tracked object. This works by telling ffmpeg to write video segments to /cache
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# from the video stream without re-encoding. Clips are then created by using ffmpeg to merge segments
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# without re-encoding. The segments saved are unaltered from what frigate receives to avoid re-encoding.
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# They do not contain bounding boxes. These are optimized to capture "false_positive" examples for improving frigate.
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#
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# NOTE: This feature does not work if you have "-vsync drop" configured in your input params.
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# This will only work for camera feeds that can be copied into the mp4 container format without
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# encoding such as h264. It may not work for some types of streams.
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################
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save_clips:
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enabled: False
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#########
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# Number of seconds before the event to include in the clips
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#########
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pre_capture: 30
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#########
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# Objects to save clips for. Defaults to all tracked object types.
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#########
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# objects:
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# - person
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################
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# Configuration for the snapshots in the debug view and mqtt
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################
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snapshots:
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show_timestamp: True
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draw_zones: False
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################
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# Camera level object config. If defined, this is used instead of the global config.
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################
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objects:
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track:
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- person
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- car
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filters:
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person:
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min_area: 5000
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max_area: 100000
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min_score: 0.5
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threshold: 0.85
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