diff --git a/404.html b/404.html index 584f29366..2fe2efcb9 100644 --- a/404.html +++ b/404.html @@ -8,7 +8,7 @@ Page Not Found | Frigate - + @@ -20,7 +20,7 @@

Page Not Found

We could not find what you were looking for.

Please contact the owner of the site that linked you to the original URL and let them know their link is broken.

- + diff --git a/configuration/advanced/index.html b/configuration/advanced/index.html index 9a84d5000..9ff8271f1 100644 --- a/configuration/advanced/index.html +++ b/configuration/advanced/index.html @@ -8,7 +8,7 @@ Advanced | Frigate - + @@ -22,7 +22,7 @@

Advanced

Advanced configuration#

motion#

Global motion detection config. These may also be defined at the camera level.

motion:
# Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below)
# Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive.
# The value should be between 1 and 255.
threshold: 25
# Optional: Minimum size in pixels in the resized motion image that counts as motion
# Increasing this value will prevent smaller areas of motion from being detected. Decreasing will make motion detection more sensitive to smaller
# moving objects.
contour_area: 100
# Optional: Alpha value passed to cv2.accumulateWeighted when averaging the motion delta across multiple frames (default: shown below)
# Higher values mean the current frame impacts the delta a lot, and a single raindrop may register as motion.
# Too low and a fast moving person wont be detected as motion.
delta_alpha: 0.2
# Optional: Alpha value passed to cv2.accumulateWeighted when averaging frames to determine the background (default: shown below)
# Higher values mean the current frame impacts the average a lot, and a new object will be averaged into the background faster.
# Low values will cause things like moving shadows to be detected as motion for longer.
# https://www.geeksforgeeks.org/background-subtraction-in-an-image-using-concept-of-running-average/
frame_alpha: 0.2
# Optional: Height of the resized motion frame (default: 1/6th of the original frame height)
# This operates as an efficient blur alternative. Higher values will result in more granular motion detection at the expense of higher CPU usage.
# Lower values result in less CPU, but small changes may not register as motion.
frame_height: 180

detect#

Global object detection settings. These may also be defined at the camera level.

detect:
# Optional: Number of frames without a detection before frigate considers an object to be gone. (default: double the frame rate)
max_disappeared: 10

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.edgetpu
  • frigate.zeroconf
  • detector.<detector_name>
  • watchdog.<camera_name>
  • ffmpeg.<camera_name>.<sorted_roles> NOTE: All FFmpeg logs are sent as error level.

environment_vars#

This section can be used to set environment variables for those unable to modify the environment of the container (ie. within Hass.io)

environment_vars:
EXAMPLE_VAR: value

database#

Event and clip information is managed in a sqlite database at /media/frigate/clips/frigate.db. If that database is deleted, clips will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within HomeAssistant.

If you are storing your clips 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 clips.

database:
path: /media/frigate/clips/frigate.db

detectors#

detectors:
# Required: name of the detector
coral:
# Required: type of the detector
# Valid values are 'edgetpu' (requires device property below) and 'cpu'. type: edgetpu
# Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
device: usb
# Optional: num_threads value passed to the tflite.Interpreter (default: shown below)
# This value is only used for CPU types
num_threads: 3

model#

model:
# Required: height of the trained model
height: 320
# Required: width of the trained model
width: 320

Custom Models#

Models for both CPU and EdgeTPU (Coral) are bundled in the image. You can use your own models with volume mounts:

  • CPU Model: /cpu_model.tflite
  • EdgeTPU Model: /edgetpu_model.tflite
  • Labels: /labelmap.txt

You also need to update the model width/height in the config if they differ from the defaults.

Customizing the Labelmap#

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. You must retain the same number of labels, but you can change the names. To change:

  • Download the COCO labelmap
  • Modify the label names as desired. For example, change 7 truck to 7 car
  • Mount the new file at /labelmap.txt in the container with an additional volume
    -v ./config/labelmap.txt:/labelmap.txt
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- + diff --git a/configuration/cameras/index.html b/configuration/cameras/index.html index 04a75207b..415875498 100644 --- a/configuration/cameras/index.html +++ b/configuration/cameras/index.html @@ -8,7 +8,7 @@ Cameras | Frigate - + @@ -34,7 +34,7 @@
# Optional: Configuration for the jpg snapshots published via MQTT
mqtt:
# Optional: Enable publishing snapshot via mqtt for camera (default: shown below)
# NOTE: Only applies to publishing image data to MQTT via 'frigate/<camera_name>/<object_name>/snapshot'.
# All other messages will still be published.
enabled: True
# Optional: print a timestamp on the snapshots (default: shown below)
timestamp: True
# Optional: draw bounding box on the snapshots (default: shown below)
bounding_box: True
# Optional: crop the snapshot (default: shown below)
crop: True
# Optional: height to resize the snapshot to (default: shown below)
height: 270
# Optional: Camera level object filters config.
objects:
track:
- person
- car
filters:
person:
min_area: 5000
max_area: 100000
min_score: 0.5
threshold: 0.7
# Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object
mask: 0,0,1000,0,1000,200,0,200

Camera specific configuration#

RTMP Cameras#

The input parameters need to be adjusted for RTMP cameras

ffmpeg:
input_args:
- -avoid_negative_ts
- make_zero
- -fflags
- nobuffer
- -flags
- low_delay
- -strict
- experimental
- -fflags
- +genpts+discardcorrupt
- -use_wallclock_as_timestamps
- '1'

Blue Iris RTSP Cameras#

You will need to remove nobuffer flag for Blue Iris RTSP cameras

ffmpeg:
input_args:
- -avoid_negative_ts
- make_zero
- -flags
- low_delay
- -strict
- experimental
- -fflags
- +genpts+discardcorrupt
- -rtsp_transport
- tcp
- -stimeout
- '5000000'
- -use_wallclock_as_timestamps
- '1'
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- + diff --git a/configuration/detectors/index.html b/configuration/detectors/index.html index 010232041..84db486fd 100644 --- a/configuration/detectors/index.html +++ b/configuration/detectors/index.html @@ -8,7 +8,7 @@ Detectors | Frigate - + @@ -22,7 +22,7 @@

Detectors

The default config will look for a USB Coral device. If you do not have a Coral, you will need to configure a CPU detector. If you have PCI or multiple Coral devices, you need to configure your detector devices in the config file. When using multiple detectors, they run in dedicated processes, but pull from a common queue of requested detections across all cameras.

Frigate supports edgetpu and cpu as detector types. The device value should be specified according to the Documentation for the TensorFlow Lite Python API.

Note: There is no support for Nvidia GPUs to perform object detection with tensorflow. It can be used for ffmpeg decoding, but not object detection.

Single USB Coral:

detectors:
coral:
type: edgetpu
device: usb

Multiple USB Corals:

detectors:
coral1:
type: edgetpu
device: usb:0
coral2:
type: edgetpu
device: usb:1

Mixing Corals:

detectors:
coral_usb:
type: edgetpu
device: usb
coral_pci:
type: edgetpu
device: pci

CPU Detectors (not recommended):

detectors:
cpu1:
type: cpu
cpu2:
type: cpu
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- + diff --git a/configuration/false_positives/index.html b/configuration/false_positives/index.html index 835efa4c0..cdb17c2f8 100644 --- a/configuration/false_positives/index.html +++ b/configuration/false_positives/index.html @@ -8,7 +8,7 @@ Reducing false positives | Frigate - + @@ -22,7 +22,7 @@

Reducing false positives

Tune your object filters to adjust false positives: min_area, max_area, min_score, threshold.

For object filters in your configuration, any single detection below min_score will be ignored as a false positive. threshold is based on the median of the history of scores (padded to 3 values) for a tracked object. Consider the following frames when min_score is set to 0.6 and threshold is set to 0.85:

FrameCurrent ScoreScore HistoryComputed ScoreDetected Object
10.70.0, 0, 0.70.0No
20.550.0, 0.7, 0.00.0No
30.850.7, 0.0, 0.850.7No
40.900.7, 0.85, 0.95, 0.900.875Yes
50.880.7, 0.85, 0.95, 0.90, 0.880.88Yes
60.950.7, 0.85, 0.95, 0.90, 0.88, 0.950.89Yes

In frame 2, the score is below the min_score value, so frigate ignores it and it becomes a 0.0. The computed score is the median of the score history (padding to at least 3 values), and only when that computed score crosses the threshold is the object marked as a true positive. That happens in frame 4 in the example.

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- + diff --git a/configuration/index/index.html b/configuration/index/index.html index 4f93d855a..5c7793d1e 100644 --- a/configuration/index/index.html +++ b/configuration/index/index.html @@ -8,7 +8,7 @@ Configuration | Frigate - + @@ -16,13 +16,13 @@ - +

Configuration

HassOS users can manage their configuration directly in the addon Configuration tab. For other installations, the default location for the config file is /config/config.yml. This can be overridden with the CONFIG_FILE environment variable. Camera specific ffmpeg parameters are documented here.

It is recommended to start with a minimal configuration and add to it:

mqtt:
host: mqtt.server.com
cameras:
back:
ffmpeg:
inputs:
- path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
roles:
- detect
- rtmp
width: 1280
height: 720
fps: 5

Required#

mqtt#

mqtt:
# Required: host name
host: mqtt.server.com
# Optional: port (default: shown below)
port: 1883
# Optional: topic prefix (default: shown below)
# WARNING: must be unique if you are running multiple instances
topic_prefix: frigate
# Optional: client id (default: shown below)
# WARNING: must be unique if you are running multiple instances
client_id: frigate
# Optional: user
user: mqtt_user
# Optional: password
# NOTE: Environment variables that begin with 'FRIGATE_' may be referenced in {}.
# eg. password: '{FRIGATE_MQTT_PASSWORD}'
password: password
# Optional: interval in seconds for publishing stats (default: shown below)
stats_interval: 60

cameras#

Each of your cameras must be configured. The following is the minimum required to register a camera in Frigate. Check the camera configuration page for a complete list of options.

cameras:
# Name of your camera
front_door:
ffmpeg:
inputs:
- path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
roles:
- detect
- rtmp
width: 1280
height: 720
fps: 5

Optional#

clips#

clips:
# Optional: Maximum length of time to retain video during long events. (default: shown below)
# NOTE: If an object is being tracked for longer than this amount of time, the cache
# will begin to expire and the resulting clip will be the last x seconds of the event.
max_seconds: 300
# Optional: size of tmpfs mount to create for cache files (default: not set)
# mount -t tmpfs -o size={tmpfs_cache_size} tmpfs /tmp/cache
# Notice: If you have mounted a tmpfs volume through docker, this value should not be set in your config
tmpfs_cache_size: 256m
# Optional: Retention settings for clips (default: shown below)
retain:
# Required: Default retention days (default: shown below)
default: 10
# Optional: Per object retention days
objects:
person: 15

ffmpeg#

ffmpeg:
# Optional: global ffmpeg args (default: shown below)
global_args: -hide_banner -loglevel fatal
# Optional: global hwaccel args (default: shown below)
# NOTE: See hardware acceleration docs for your specific device
hwaccel_args: []
# Optional: global input args (default: shown below)
input_args: -avoid_negative_ts make_zero -fflags +genpts+discardcorrupt -rtsp_transport tcp -stimeout 5000000 -use_wallclock_as_timestamps 1
# Optional: global output args
output_args:
# Optional: output args for detect streams (default: shown below)
detect: -f rawvideo -pix_fmt yuv420p
# Optional: output args for record streams (default: shown below)
record: -f segment -segment_time 60 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
# Optional: output args for clips streams (default: shown below)
clips: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
# Optional: output args for rtmp streams (default: shown below)
rtmp: -c copy -f flv

objects#

Can be overridden at the camera level

objects:
# Optional: list of objects to track from labelmap.txt (default: shown below)
track:
- person
# Optional: filters to reduce false positives for specific object types
filters:
person:
# Optional: minimum width*height of the bounding box for the detected object (default: 0)
min_area: 5000
# Optional: maximum width*height of the bounding box for the detected object (default: 24000000)
max_area: 100000
# Optional: minimum score for the object to initiate tracking (default: shown below)
min_score: 0.5
# Optional: minimum decimal percentage for tracked object's computed score to be considered a true positive (default: shown below)
threshold: 0.7
Edit this page
- + @@ -30,6 +30,6 @@ - + \ No newline at end of file diff --git a/configuration/nvdec/index.html b/configuration/nvdec/index.html index befcf0609..bce5fc24a 100644 --- a/configuration/nvdec/index.html +++ b/configuration/nvdec/index.html @@ -8,7 +8,7 @@ nVidia hardware decoder | Frigate - + @@ -35,7 +35,7 @@ processes:

using the fps filter:

output_args:
- -filter:v
- fps=fps=5

This setting, for example, allows Frigate to consume my 10-15fps camera streams on my relatively low powered Haswell machine with relatively low cpu usage.

Edit this page
- + diff --git a/configuration/optimizing/index.html b/configuration/optimizing/index.html index 024d2c958..7794b602d 100644 --- a/configuration/optimizing/index.html +++ b/configuration/optimizing/index.html @@ -8,7 +8,7 @@ Optimizing performance | Frigate - + @@ -25,7 +25,7 @@ NOTICE: If you are using the addon, ensure you turn off Protection mode for hardware acceleration.

ffmpeg:
hwaccel_args:
- -c:v
- h264_v4l2m2m

Intel-based CPUs (<10th Generation) via Quicksync (https://trac.ffmpeg.org/wiki/Hardware/QuickSync)

ffmpeg:
hwaccel_args:
- -hwaccel
- vaapi
- -hwaccel_device
- /dev/dri/renderD128
- -hwaccel_output_format
- yuv420p

Intel-based CPUs (>=10th Generation) via Quicksync (https://trac.ffmpeg.org/wiki/Hardware/QuickSync)

ffmpeg:
hwaccel_args:
- -hwaccel
- qsv
- -qsv_device
- /dev/dri/renderD128

AMD/ATI GPUs (Radeon HD 2000 and newer GPUs) via libva-mesa-driver (https://trac.ffmpeg.org/wiki/Hardware/QuickSync) Note: You also need to set LIBVA_DRIVER_NAME=radeonsi as an environment variable on the container.

ffmpeg:
hwaccel_args:
- -hwaccel
- vaapi
- -hwaccel_device
- /dev/dri/renderD128

Nvidia GPU based decoding via NVDEC is supported, but requires special configuration. See the nvidia NVDEC documentation for more details.

Edit this page
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Recommended hardware

Cameras#

Cameras that output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and HomeAssistant. It is also helpful if your camera supports multiple substreams to allow different resolutions to be used for detection, streaming, clips, and recordings without re-encoding.

Computer#

NameInference SpeedNotes
Atomic Pi16msGood option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding.
Intel NUC NUC7i3BNK8-10msGreat performance. Can handle many cameras at 5fps depending on typical amounts of motion.
BMAX B2 Plus10-12msGood balance of performance and cost. Also capable of running many other services at the same time as frigate.
Minisforum GK419-10msGreat alternative to a NUC with dual Gigabit NICs. Easily handles several 1080p cameras.
Raspberry Pi 3B (32bit)60msCan handle a small number of cameras, but the detection speeds are slow due to USB 2.0.
Raspberry Pi 4 (32bit)15-20msCan handle a small number of cameras. The 2GB version runs fine.
Raspberry Pi 4 (64bit)10-15msCan handle a small number of cameras. The 2GB version runs fine.
Edit this page
- + diff --git a/how-it-works/index.html b/how-it-works/index.html index 3c4b4802c..23aae6fb7 100644 --- a/how-it-works/index.html +++ b/how-it-works/index.html @@ -8,7 +8,7 @@ How Frigate Works | Frigate - + @@ -22,7 +22,7 @@

How Frigate Works

Frigate is designed to minimize resource and maximize performance by only looking for objects when and where it is necessary

Diagram

  1. Look for Motion
  2. Calculate Detection Regions
  3. Run Object Detection
Edit this page
- + diff --git a/index.html b/index.html index bbd29b2ce..bff26bd9a 100644 --- a/index.html +++ b/index.html @@ -8,7 +8,7 @@ Frigate | Frigate - + @@ -22,7 +22,7 @@

Your Docusaurus site did not load properly.

A very common reason is a wrong site baseUrl configuration.

Current configured baseUrl = /frigate/

We suggest trying baseUrl =

Frigate

A complete and local NVR designed for HomeAssistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.

Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.

  • Tight integration with HomeAssistant via a custom component
  • Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
  • Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
  • Uses a very low overhead motion detection to determine where to run object detection
  • Object detection with TensorFlow runs in separate processes for maximum FPS
  • Communicates over MQTT for easy integration into other systems
  • 24/7 recording
  • Re-streaming via RTMP to reduce the number of connections to your camera

Screenshots#

Media Browser

Notification

Edit this page
- + diff --git a/installation/index.html b/installation/index.html index 3b1681f63..a4aebdda7 100644 --- a/installation/index.html +++ b/installation/index.html @@ -8,7 +8,7 @@ Installation | Frigate - + @@ -22,7 +22,7 @@

Installation

Frigate is a Docker container that can be run on any Docker host including as a HassOS Addon. See instructions below for installing the HassOS addon.

For HomeAssistant users, there is also a custom component (aka integration). This custom component adds tighter integration with HomeAssistant by automatically setting up camera entities, sensors, media browser for clips and recordings, and a public API to simplify notifications.

Note that HassOS Addons and custom components are different things. If you are already running Frigate with Docker directly, you do not need the Addon since the Addon would run another instance of Frigate.

HassOS Addon#

HassOS users can install via the addon repository. Frigate requires an MQTT server.

  1. Navigate to Supervisor > Add-on Store > Repositories
  2. Add https://github.com/blakeblackshear/frigate-hass-addons
  3. Setup your configuration in the Configuration tab
  4. Start the addon container

Docker#

Make sure you choose the right image for your architecture:

ArchImage Name
amd64blakeblackshear/frigate:stable-amd64
amd64nvidiablakeblackshear/frigate:stable-amd64nvidia
armv7blakeblackshear/frigate:stable-armv7
aarch64blakeblackshear/frigate:stable-aarch64

It is recommended to run with docker-compose:

version: '3.6'
services:
frigate:
container_name: frigate
restart: unless-stopped
privileged: true
image: blakeblackshear/frigate:0.8.0-beta2-amd64
volumes:
- /dev/bus/usb:/dev/bus/usb
- /etc/localtime:/etc/localtime:ro
- <path_to_config>:/config
- <path_to_directory_for_clips>:/media/frigate/clips
- <path_to_directory_for_recordings>:/media/frigate/recordings
- type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
target: /tmp/cache
tmpfs:
size: 1000000000
ports:
- '5000:5000'
- '1935:1935' # RTMP feeds
environment:
FRIGATE_RTSP_PASSWORD: 'password'

If you can't use docker compose, you can run the container with something similar to this:

docker run --rm \
--name frigate \
--privileged \
--mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 \
-v /dev/bus/usb:/dev/bus/usb \
-v <path_to_directory_for_clips>:/media/frigate/clips \
-v <path_to_directory_for_recordings>:/media/frigate/recordings \
-v <path_to_config>:/config:ro \
-v /etc/localtime:/etc/localtime:ro \
-e FRIGATE_RTSP_PASSWORD='password' \
-p 5000:5000 \
-p 1935:1935 \
blakeblackshear/frigate:0.8.0-beta2-amd64

Kubernetes#

Use the helm chart.

Virtualization#

For ideal performance, Frigate needs access to underlying hardware for the Coral and GPU devices for ffmpeg decoding. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended. The virtualization layer typically introduces a sizable amount of overhead for communication with Coral devices.

Proxmox#

Some people have had success running Frigate in LXC directly with the following config:

arch: amd64
cores: 2
features: nesting=1
hostname: FrigateLXC
memory: 4096
net0: name=eth0,bridge=vmbr0,firewall=1,hwaddr=2E:76:AE:5A:58:48,ip=dhcp,ip6=auto,type=veth
ostype: debian
rootfs: local-lvm:vm-115-disk-0,size=12G
swap: 512
lxc.cgroup.devices.allow: c 189:385 rwm
lxc.mount.entry: /dev/dri/renderD128 dev/dri/renderD128 none bind,optional,create=file
lxc.mount.entry: /dev/bus/usb/004/002 dev/bus/usb/004/002 none bind,optional,create=file
lxc.apparmor.profile: unconfined
lxc.cgroup.devices.allow: a
lxc.cap.drop:

Calculating shm-size#

The default shm-size of 64m is fine for setups with 3 or less 1080p cameras. If frigate is exiting with "Bus error" messages, it could be because you have too many high resolution cameras and you need to specify a higher shm size.

You can calculate the necessary shm-size for each camera with the following formula:

(width * height * 1.5 * 7 + 270480)/1048576 = <shm size in mb>
Edit this page
- + diff --git a/mdx/index.html b/mdx/index.html index 12c01d768..8a557b9e2 100644 --- a/mdx/index.html +++ b/mdx/index.html @@ -8,7 +8,7 @@ Powered by MDX | Frigate - + @@ -22,7 +22,7 @@

Powered by MDX

You can write JSX and use React components within your Markdown thanks to MDX.

Docusaurus green and Facebook blue are my favorite colors.

I can write Markdown alongside my JSX!

Edit this page
- + diff --git a/runtime~main.29630785.js b/runtime~main.2d335baa.js similarity index 98% rename from runtime~main.29630785.js rename to runtime~main.2d335baa.js index 536e890de..67999a658 100644 --- a/runtime~main.29630785.js +++ b/runtime~main.2d335baa.js @@ -1 +1 @@ -!function(e){function r(r){for(var n,f,c=r[0],u=r[1],d=r[2],i=0,p=[];i Search the documentation | Frigate - + @@ -18,7 +18,7 @@

Search the documentation

- + diff --git a/troubleshooting/index.html b/troubleshooting/index.html index afba817fa..1c1fc24d4 100644 --- a/troubleshooting/index.html +++ b/troubleshooting/index.html @@ -8,7 +8,7 @@ Troubleshooting | Frigate - + @@ -22,7 +22,7 @@

Troubleshooting

My mjpeg stream or snapshots look green and crazy#

This almost always means that the width/height defined for your camera are not correct. Double check the resolution with vlc or another player. Also make sure you don't have the width and height values backwards.

mismatched-resolution

"[mov,mp4,m4a,3gp,3g2,mj2 @ 0x5639eeb6e140] moov atom not found"#

These messages in the logs are expected in certain situations. Frigate checks the integrity of the video cache before assembling clips. Occasionally these cached files will be invalid and cleaned up automatically.

"ffmpeg didnt return a frame. something is wrong"#

Turn on logging for the ffmpeg process by overriding the global_args and setting the log level to info (the default is fatal). Note that all ffmpeg logs show up in the Frigate logs as ERROR level. This does not mean they are actually errors.

ffmpeg:
global_args: -hide_banner -loglevel info

"On connect called"#

If you see repeated "On connect called" messages in your config, check for another instance of frigate. This happens when multiple frigate containers are trying to connect to mqtt with the same client_id.

Edit this page
- + diff --git a/usage/api/index.html b/usage/api/index.html index 4cd6b5672..eb794cf97 100644 --- a/usage/api/index.html +++ b/usage/api/index.html @@ -8,7 +8,7 @@ HTTP API | Frigate - + @@ -22,7 +22,7 @@

HTTP API

A web server is available on port 5000 with the following endpoints.

/api/<camera_name>#

An mjpeg stream for debugging. Keep in mind the mjpeg endpoint is for debugging only and will put additional load on the system when in use.

Accepts the following query string parameters:

paramTypeDescription
fpsintFrame rate
hintHeight in pixels
bboxintShow bounding boxes for detected objects (0 or 1)
timestampintPrint the timestamp in the upper left (0 or 1)
zonesintDraw the zones on the image (0 or 1)
maskintOverlay the mask on the image (0 or 1)
motionintDraw blue boxes for areas with detected motion (0 or 1)
regionsintDraw green boxes for areas where object detection was run (0 or 1)

You can access a higher resolution mjpeg stream by appending h=height-in-pixels to the endpoint. For example http://localhost:5000/back?h=1080. You can also increase the FPS by appending fps=frame-rate to the URL such as http://localhost:5000/back?fps=10 or both with ?fps=10&h=1000.

/api/<camera_name>/<object_name>/best.jpg[?h=300&crop=1]#

The best snapshot for any object type. It is a full resolution image by default.

Example parameters:

  • h=300: resizes the image to 300 pixes tall
  • crop=1: crops the image to the region of the detection rather than returning the entire image

/api/<camera_name>/latest.jpg[?h=300]#

The most recent frame that frigate has finished processing. It is a full resolution image by default.

Accepts the following query string parameters:

paramTypeDescription
hintHeight in pixels
bboxintShow bounding boxes for detected objects (0 or 1)
timestampintPrint the timestamp in the upper left (0 or 1)
zonesintDraw the zones on the image (0 or 1)
maskintOverlay the mask on the image (0 or 1)
motionintDraw blue boxes for areas with detected motion (0 or 1)
regionsintDraw green boxes for areas where object detection was run (0 or 1)

Example parameters:

  • h=300: resizes the image to 300 pixes tall

/api/stats#

Contains some granular debug info that can be used for sensors in HomeAssistant.

Sample response:

{
/* Per Camera Stats */
"back": {
/***************
* Frames per second being consumed from your camera. If this is higher
* than it is supposed to be, you should set -r FPS in your input_args.
* camera_fps = process_fps + skipped_fps
***************/
"camera_fps": 5.0,
/***************
* Number of times detection is run per second. This can be higher than
* your camera FPS because frigate often looks at the same frame multiple times
* or in multiple locations
***************/
"detection_fps": 1.5,
/***************
* PID for the ffmpeg process that consumes this camera
***************/
"capture_pid": 27,
/***************
* PID for the process that runs detection for this camera
***************/
"pid": 34,
/***************
* Frames per second being processed by frigate.
***************/
"process_fps": 5.1,
/***************
* Frames per second skip for processing by frigate.
***************/
"skipped_fps": 0.0
},
/***************
* Sum of detection_fps across all cameras and detectors.
* This should be the sum of all detection_fps values from cameras.
***************/
"detection_fps": 5.0,
/* Detectors Stats */
"detectors": {
"coral": {
/***************
* Timestamp when object detection started. If this value stays non-zero and constant
* for a long time, that means the detection process is stuck.
***************/
"detection_start": 0.0,
/***************
* Time spent running object detection in milliseconds.
***************/
"inference_speed": 10.48,
/***************
* PID for the shared process that runs object detection on the Coral.
***************/
"pid": 25321
}
},
"service": {
/* Uptime in seconds */
"uptime": 10,
"version": "0.8.0-8883709"
}
}

/api/config#

A json representation of your configuration

/api/version#

Version info

/api/events#

Events from the database. Accepts the following query string parameters:

paramTypeDescription
beforeintEpoch time
afterintEpoch time
camerastrCamera name
labelstrLabel name
zonestrZone name
limitintLimit the number of events returned
has_snapshotintFilter to events that have snapshots (0 or 1)
has_clipintFilter to events that have clips (0 or 1)

/api/events/summary#

Returns summary data for events in the database. Used by the HomeAssistant integration.

/api/events/<id>#

Returns data for a single event.

/api/events/<id>/thumbnail.jpg#

Returns a thumbnail for the event id optimized for notifications. Works while the event is in progress and after completion. Passing ?format=android will convert the thumbnail to 2:1 aspect ratio.

/api/events/<id>/snapshot.jpg#

Returns the snapshot image for the event id. Works while the event is in progress and after completion.

Accepts the following query string parameters, but they are only applied when an event is in progress. After the event is completed, the saved snapshot is returned from disk without modification:

paramTypeDescription
hintHeight in pixels
bboxintShow bounding boxes for detected objects (0 or 1)
timestampintPrint the timestamp in the upper left (0 or 1)
cropintCrop the snapshot to the (0 or 1)

/clips/<camera>-<id>.mp4#

Video clip for the given camera and event id.

/clips/<camera>-<id>.jpg#

JPG snapshot for the given camera and event id.

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- + diff --git a/usage/home-assistant/index.html b/usage/home-assistant/index.html index dd40599a4..ddf8da8bc 100644 --- a/usage/home-assistant/index.html +++ b/usage/home-assistant/index.html @@ -8,7 +8,7 @@ Integration with Home Assistant | Frigate - + @@ -22,7 +22,7 @@

Integration with Home Assistant

The best way to integrate with HomeAssistant is to use the official integration. When configuring the integration, you will be asked for the Host of your frigate instance. This value should be the url you use to access Frigate in the browser and will look like http://<host>:5000/. If you are using HassOS with the addon, the host should be http://ccab4aaf-frigate:5000 (or http://ccab4aaf-frigate-beta:5000 if your are using the beta version of the addon). HomeAssistant needs access to port 5000 (api) and 1935 (rtmp) for all features. The integration will setup the following entities within HomeAssistant:

Sensors:#

  • Stats to monitor frigate performance
  • Object counts for all zones and cameras

Cameras:#

  • Cameras for image of the last detected object for each camera
  • Camera entities with stream support (requires RTMP)

Media Browser:#

  • Rich UI with thumbnails for browsing event clips
  • Rich UI for browsing 24/7 recordings by month, day, camera, time

API:#

  • Notification API with public facing endpoints for images in notifications

Notifications#

Frigate publishes event information in the form of a change feed via MQTT. This allows lots of customization for notifications to meet your needs. Event changes are published with before and after information as shown here.

Here is a simple example of a notification automation of events which will update the existing notification for each change. This means the image you see in the notification will update as frigate finds a "better" image.

automation:
- alias: Notify of events
trigger:
platform: mqtt
topic: frigate/events
action:
- service: notify.mobile_app_pixel_3
data_template:
message: 'A {{trigger.payload_json["after"]["label"]}} was detected.'
data:
image: 'https://your.public.hass.address.com/api/frigate/notifications/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg?format=android'
tag: '{{trigger.payload_json["after"]["id"]}}'
automation:
- alias: When a person enters a zone named yard
trigger:
platform: mqtt
topic: frigate/events
conditions:
- "{{ trigger.payload_json['after']['label'] == 'person' }}"
- "{{ 'yard' in trigger.payload_json['after']['entered_zones'] }}"
action:
- service: notify.mobile_app_pixel_3
data_template:
message: "A {{trigger.payload_json['after']['label']}} has entered the yard."
data:
image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg"
tag: "{{trigger.payload_json['after']['id']}}"
- alias: When a person leaves a zone named yard
trigger:
platform: mqtt
topic: frigate/events
conditions:
- "{{ trigger.payload_json['after']['label'] == 'person' }}"
- "{{ 'yard' in trigger.payload_json['before']['current_zones'] }}"
- "{{ not 'yard' in trigger.payload_json['after']['current_zones'] }}"
action:
- service: notify.mobile_app_pixel_3
data_template:
message: "A {{trigger.payload_json['after']['label']}} has left the yard."
data:
image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg"
tag: "{{trigger.payload_json['after']['id']}}"
- alias: Notify for dogs in the front with a high top score
trigger:
platform: mqtt
topic: frigate/events
conditions:
- "{{ trigger.payload_json['after']['label'] == 'dog' }}"
- "{{ trigger.payload_json['after']['camera'] == 'front' }}"
- "{{ trigger.payload_json['after']['top_score'] > 0.98 }}"
action:
- service: notify.mobile_app_pixel_3
data_template:
message: 'High confidence dog detection.'
data:
image: "https://url.com/api/frigate/notifications/{{trigger.payload_json['after']['id']}}/thumbnail.jpg"
tag: "{{trigger.payload_json['after']['id']}}"

If you are using telegram, you can fetch the image directly from Frigate:

automation:
- alias: Notify of events
trigger:
platform: mqtt
topic: frigate/events
action:
- service: notify.telegram_full
data_template:
message: 'A {{trigger.payload_json["after"]["label"]}} was detected.'
data:
photo:
# this url should work for addon users
- url: 'http://ccab4aaf-frigate:5000/api/events/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg'
caption: 'A {{trigger.payload_json["after"]["label"]}} was detected on {{ trigger.payload_json["after"]["camera"] }} camera'
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- + diff --git a/usage/mqtt/index.html b/usage/mqtt/index.html index 6ec14bb1d..a6854498e 100644 --- a/usage/mqtt/index.html +++ b/usage/mqtt/index.html @@ -8,7 +8,7 @@ MQTT | Frigate - + @@ -25,7 +25,7 @@ "offline": published right before frigate stops

frigate/<camera_name>/<object_name>#

Publishes the count of objects for the camera for use as a sensor in HomeAssistant.

frigate/<zone_name>/<object_name>#

Publishes the count of objects for the zone for use as a sensor in HomeAssistant.

frigate/<camera_name>/<object_name>/snapshot#

Publishes a jpeg encoded frame of the detected object type. When the object is no longer detected, the highest confidence image is published or the original image is published again.

The height and crop of snapshots can be configured in the config.

frigate/events#

Message published for each changed event. The first message is published when the tracked object is no longer marked as a false_positive. When frigate finds a better snapshot of the tracked object or when a zone change occurs, it will publish a message with the same id. When the event ends, a final message is published with end_time set.

{
"type": "update", // new, update, or end
"before": {
"id": "1607123955.475377-mxklsc",
"camera": "front_door",
"frame_time": 1607123961.837752,
"label": "person",
"top_score": 0.958984375,
"false_positive": false,
"start_time": 1607123955.475377,
"end_time": null,
"score": 0.7890625,
"box": [424, 500, 536, 712],
"area": 23744,
"region": [264, 450, 667, 853],
"current_zones": ["driveway"],
"entered_zones": ["yard", "driveway"],
"thumbnail": null
},
"after": {
"id": "1607123955.475377-mxklsc",
"camera": "front_door",
"frame_time": 1607123962.082975,
"label": "person",
"top_score": 0.958984375,
"false_positive": false,
"start_time": 1607123955.475377,
"end_time": null,
"score": 0.87890625,
"box": [432, 496, 544, 854],
"area": 40096,
"region": [218, 440, 693, 915],
"current_zones": ["yard", "driveway"],
"entered_zones": ["yard", "driveway"],
"thumbnail": null
}
}

frigate/stats#

Same data available at /api/stats published at a configurable interval.

frigate/<camera_name>/detect/set#

Topic to turn detection for a camera on and off. Expected values are ON and OFF.

frigate/<camera_name>/detect/state#

Topic with current state of detection for a camera. Published values are ON and OFF.

frigate/<camera_name>/clips/set#

Topic to turn clips for a camera on and off. Expected values are ON and OFF.

frigate/<camera_name>/clips/state#

Topic with current state of clips for a camera. Published values are ON and OFF.

frigate/<camera_name>/snapshots/set#

Topic to turn snapshots for a camera on and off. Expected values are ON and OFF.

frigate/<camera_name>/snapshots/state#

Topic with current state of snapshots for a camera. Published values are ON and OFF.

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- + diff --git a/usage/web/index.html b/usage/web/index.html index 6a92446c8..57723c507 100644 --- a/usage/web/index.html +++ b/usage/web/index.html @@ -8,7 +8,7 @@ Web Interface | Frigate - + @@ -22,7 +22,7 @@

Web Interface

Frigate comes bundled with a simple web ui that supports the following:

  • Show cameras
  • Browse events
  • Mask helper
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