mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-26 19:06:11 +01:00
188 lines
6.6 KiB
YAML
188 lines
6.6 KiB
YAML
web_port: 5000
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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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# 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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# - rgb24
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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 person
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# max_area (optional): maximum width*height of the bounding box for the detected person
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# threshold (optional): The minimum decimal percentage (50% hit = 0.5) for the confidence from tensorflow
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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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- truck
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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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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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front_door:
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####################
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# For each camera, 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 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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driveway:
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front_door:
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coordinates: 545,1077,747,939,788,805
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yard:
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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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## Optional mask. Must be the same aspect ratio as your video feed. Value is either the
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## name of a file in the config directory or a base64 encoded bmp image prefixed with
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## 'base64,' eg. 'base64,asfasdfasdf....'.
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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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# 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. 30 seconds of video is added to the start of the clip. These are
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# optimized to capture "false_positive" examples for improving frigate.
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#
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# NOTE: 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. I do not expect this to work for mjpeg streams, and it may not work for many other
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# types of streams.
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#
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# WARNING: Videos in /cache are retained until there are no ongoing events. If you are tracking cars or
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# other objects for long periods of time, the cache will continue to grow indefinitely.
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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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# 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. This config is merged with the global config above.
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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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threshold: 0.8
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