mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-10-15 20:07:23 +02:00
93 lines
3.7 KiB
YAML
93 lines
3.7 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 -- Uncomment for use
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# password: password # Optional -- Uncomment for use
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cameras:
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back:
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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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ffmpeg_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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## Optional mask. Must be the same dimensions as your video feed.
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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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# 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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# Optional hardware acceleration parameters for ffmpeg. If your hardware supports it, it can
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# greatly reduce the CPU power used to decode the video stream. You will need to determine which
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# parameters work for your specific hardware. These may work for those with Intel hardware that
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# supports QuickSync.
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################
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# ffmpeg_hwaccel_args:
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# - -hwaccel
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# - vaapi
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# - -hwaccel_device
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# - /dev/dri/renderD128
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# - -hwaccel_output_format
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# - yuv420p
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################
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# FFmpeg log level. Default is "panic". https://ffmpeg.org/ffmpeg.html#Generic-options
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################
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# ffmpeg_log_level: panic
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################
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# Optional custom input args. Some cameras may need custom ffmpeg params to work reliably. Specifying
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# these will replace the default input params.
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################
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# ffmpeg_input_args: []
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################
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# Optional custom output args. Some cameras may need custom ffmpeg params to work reliably. Specifying
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# these will replace the default output params.
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################
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# ffmpeg_output_args: []
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################
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# size: size of the region in pixels
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# x_offset/y_offset: position of the upper left corner of your region (top left of image is 0,0)
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# min_person_area (optional): minimum width*height of the bounding box for the detected person
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# max_person_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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# Tips: All regions are resized to 300x300 before detection because the model is trained on that size.
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# Resizing regions takes CPU power. Ideally, all regions should be as close to 300x300 as possible.
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# Defining a region that goes outside the bounds of the image will result in errors.
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################
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regions:
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- size: 350
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x_offset: 0
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y_offset: 300
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min_person_area: 5000
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max_person_area: 100000
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threshold: 0.5
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- size: 400
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x_offset: 350
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y_offset: 250
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min_person_area: 2000
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max_person_area: 100000
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threshold: 0.5
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- size: 400
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x_offset: 750
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y_offset: 250
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min_person_area: 2000
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max_person_area: 100000
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threshold: 0.5
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