blakeblackshear.frigate/config/config.example.yml
2019-12-14 15:18:21 -06:00

129 lines
4.2 KiB
YAML

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 -- Uncomment for use
# password: password # Optional -- Uncomment for use
#################
# 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:
# - -vf
# - mpdecimate
# - -f
# - rawvideo
# - -pix_fmt
# - rgb24
####################
# Global object configuration. Applies to all cameras and regions
# unless overridden at the camera/region 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.
####################
objects:
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: []
################
## Optional mask. Must be the same dimensions 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.
################
# 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
objects:
person:
min_area: 5000
max_area: 100000
threshold: 0.5
################
# size: size of the region in pixels
# x_offset/y_offset: position of the upper left corner of your region (top left of image is 0,0)
# min_person_area (optional): minimum width*height of the bounding box for the detected person
# max_person_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
# Tips: All regions are resized to 300x300 before detection because the model is trained on that size.
# Resizing regions takes CPU power. Ideally, all regions should be as close to 300x300 as possible.
# Defining a region that goes outside the bounds of the image will result in errors.
################
regions:
- size: 350
x_offset: 0
y_offset: 300
objects:
car:
threshold: 0.2
- size: 400
x_offset: 350
y_offset: 250
objects:
person:
min_area: 2000
- size: 400
x_offset: 750
y_offset: 250
objects:
person:
min_area: 2000