Advanced Options
logger
Change the default log level for troubleshooting purposes.
logger:
# Optional: default log level (default: shown below)
default: info
# Optional: module by module log level configuration
logs:
frigate.mqtt: error
Available log levels are: debug
, info
, warning
, error
, critical
Examples of available modules are:
frigate.app
frigate.mqtt
frigate.object_detection
detector.<detector_name>
watchdog.<camera_name>
ffmpeg.<camera_name>.<sorted_roles>
NOTE: All FFmpeg logs are sent aserror
level.
environment_vars
This section can be used to set environment variables for those unable to modify the environment of the container (ie. within HassOS)
Example:
environment_vars:
VARIABLE_NAME: variable_value
database
Tracked object and recording information is managed in a sqlite database at /config/frigate.db
. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant.
If you are storing your database on a network share (SMB, NFS, etc), you may get a database is locked
error message on startup. You can customize the location of the database in the config if necessary.
This may need to be in a custom location if network storage is used for the media folder.
database:
path: /path/to/frigate.db
model
If using a custom model, the width and height will need to be specified.
Custom models may also require different input tensor formats. The colorspace conversion supports RGB, BGR, or YUV frames to be sent to the object detector. The input tensor shape parameter is an enumeration to match what specified by the model.
Tensor Dimension | Description |
---|---|
N | Batch Size |
H | Model Height |
W | Model Width |
C | Color Channels |
Available Input Tensor Shapes |
---|
"nhwc" |
"nchw" |
# Optional: model config
model:
path: /path/to/model
width: 320
height: 320
input_tensor: "nhwc"
input_pixel_format: "bgr"
labelmap
If the labelmap is customized then the labels used for alerts will need to be adjusted as well. See alert labels for more info.
The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. By default, truck is renamed to car because they are often confused. You cannot add new object types, but you can change the names of existing objects in the model.
model:
labelmap:
2: vehicle
3: vehicle
5: vehicle
7: vehicle
15: animal
16: animal
17: animal
Note that if you rename objects in the labelmap, you will also need to update your objects -> track
list as well.
Some labels have special handling and modifications can disable functionality.
person
objects are associated with face
and amazon
car
objects are associated with license_plate
, ups
, fedex
, amazon