frigate/config/config.example.yml

web_port: 5000

mqtt:
  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 person
# max_area (optional): maximum width*height of the bounding box for the detected person
# threshold (optional): The minimum decimal percentage (50% hit = 0.5) for the confidence from tensorflow
####################
objects:
  track:
    - person
    - car
    - truck
  filters:
    person:
      min_area: 5000
      max_area: 100000
      threshold: 0.5

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.
    ##
    ## 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

    ################
    # Camera level object config. This config is merged with the global config above.
    ################
    objects:
      track:
        - person
      filters:
        person:
          min_area: 5000
          max_area: 100000
          threshold: 0.5

    ################
    ## Tracker configuration
    ##
    ## If you have problems with keeping track of objects try changing these constants.
    ## See SORT project for details:
    ##  https://github.com/abewley/sort/blob/master/sort.py
    ##
    ## min_hits: Minimum number of hits to start tracking an object.
    ## max_age: Number of missed frames before discarding track.
    ## iou_threshold: Intersection over union threshold.
    ################
    tracker:
      min_hits: 1
      max_age: 5
      iou_threshold: 0.2