| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196 | web_port: 5000################## Tell frigate to look for a specific EdgeTPU device. Useful if you want to run multiple instances of frigate## on the same machine with multiple EdgeTPUs. https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api################tensorflow_device: usbmqtt:  host: mqtt.server.com  topic_prefix: frigate  # client_id: frigate # Optional -- set to override default client id of 'frigate' if running multiple instances  # user: username # Optional  #################  ## Environment variables that begin with 'FRIGATE_' may be referenced in {}.  ##   password: '{FRIGATE_MQTT_PASSWORD}'  #################  # password: password # Optional################## Default ffmpeg args. Optional and can be overwritten per camera.# Should work with most RTSP cameras that send h264 video# Built from the properties below with:# "ffmpeg" + global_args + input_args + "-i" + input + output_args################## ffmpeg:#   global_args:#     - -hide_banner#     - -loglevel#     - panic#   hwaccel_args: []#   input_args:#     - -avoid_negative_ts#     - make_zero#     - -fflags#     - nobuffer#     - -flags#     - low_delay#     - -strict#     - experimental#     - -fflags#     - +genpts+discardcorrupt#     - -vsync#     - drop#     - -rtsp_transport#     - tcp#     - -stimeout#     - '5000000'#     - -use_wallclock_as_timestamps#     - '1'#   output_args:#     - -f#     - rawvideo#     - -pix_fmt#     - rgb24##################### Global object configuration. Applies to all cameras# unless overridden at the camera levels.# Keys must be valid labels. By default, the model uses coco (https://dl.google.com/coral/canned_models/coco_labels.txt).# All labels from the model are reported over MQTT. These values are used to filter out false positives.# min_area (optional): minimum width*height of the bounding box for the detected object# max_area (optional): maximum width*height of the bounding box for the detected object# min_score (optional): minimum score for the object# threshold (optional): The minimum decimal percentage for tracked object's computed score to considered a true positive####################objects:  track:    - person    - car    - truck  filters:    person:      min_area: 5000      max_area: 100000      min_score: 0.5      threshold: 0.85zones:  #################  # Name of the zone  ################  front_steps:    front_door:      ####################      # For each camera, a list of x,y coordinates to define the polygon of the zone. The top       # left corner is 0,0. Can also be a comma separated string of all x,y coordinates combined.      # The same zone can exist across multiple cameras if they have overlapping FOVs.      # An object is determined to be in the zone based on whether or not the bottom center      # of it's bounding box is within the polygon. The polygon must have at least 3 points.      # Coordinates can be generated at https://www.image-map.net/      ####################      coordinates:        - 545,1077        - 747,939        - 788,805      ################      # Zone level object filters. These are applied in addition to the global and camera filters      # and should be more restrictive than the global and camera filters. The global and camera      # filters are applied upstream.      ################      filters:        person:          min_area: 5000          max_area: 100000          threshold: 0.8  driveway:    front_door:      coordinates: 545,1077,747,939,788,805  yard:cameras:  back:    ffmpeg:      ################      # Source passed to ffmpeg after the -i parameter. Supports anything compatible with OpenCV and FFmpeg.      # Environment variables that begin with 'FRIGATE_' may be referenced in {}      ################      input: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2      #################      # These values will override default values for just this camera      #################      # global_args: []      # hwaccel_args: []      # input_args: []      # output_args: []        ################    ## Optionally specify the resolution of the video feed. Frigate will try to auto detect if not specified    ################    # height: 1280    # width: 720    ################    ## Optional mask. Must be the same aspect ratio as your video feed. Value is either the    ## name of a file in the config directory or a base64 encoded bmp image prefixed with    ## 'base64,' eg. 'base64,asfasdfasdf....'.    ##     ## The mask works by looking at the bottom center of the bounding box for the detected    ## person in the image. If that pixel in the mask is a black pixel, it ignores it as a    ## false positive. In my mask, the grass and driveway visible from my backdoor camera     ## are white. The garage doors, sky, and trees (anywhere it would be impossible for a     ## person to stand) are black.    ##     ## Masked areas are also ignored for motion detection.    ################    # mask: back-mask.bmp    ################    # Allows you to limit the framerate within frigate for cameras that do not support    # custom framerates. A value of 1 tells frigate to look at every frame, 2 every 2nd frame,     # 3 every 3rd frame, etc.    ################    take_frame: 1    ################    # This will save a clip for each tracked object by frigate along with a json file that contains    # data related to the tracked object. This works by telling ffmpeg to write video segments to /cache    # from the video stream without re-encoding. Clips are then created by using ffmpeg to merge segments    # without re-encoding. The segments saved are unaltered from what frigate receives to avoid re-encoding.    # They do not contain bounding boxes. 30 seconds of video is added to the start of the clip. These are    # optimized to capture "false_positive" examples for improving frigate.    #    # NOTE: This will only work for camera feeds that can be copied into the mp4 container format without    # encoding such as h264. I do not expect this to work for mjpeg streams, and it may not work for many other    # types of streams.    #    # WARNING: Videos in /cache are retained until there are no ongoing events. If you are tracking cars or    # other objects for long periods of time, the cache will continue to grow indefinitely.    ################    save_clips:      enabled: False      #########      # Number of seconds before the event to include in the clips      #########      pre_capture: 30    ################    # Configuration for the snapshots in the debug view and mqtt    ################    snapshots:      show_timestamp: True      draw_zones: False    ################    # Camera level object config. This config is merged with the global config above.    ################    objects:      track:        - person      filters:        person:          min_area: 5000          max_area: 100000          min_score: 0.5          threshold: 0.85
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