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docker/compose.yml Normal file
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version: "3.9"
services:
frigate: #https://docs.frigate.video/frigate/installation
container_name: frigate
privileged: true # this may not be necessary for all setups
restart: always
image: ghcr.io/blakeblackshear/frigate:stable
shm_size: "128mb" # update for your cameras see installation link above
devices:
- /dev/apex_0:/dev/apex_0 # passes a PCIe Coral, follow driver instructions here https://coral.ai/docs/m2/get-started/#2a-on-linux
- /dev/dri/renderD128 # for intel hwaccel, needs to be updated for your hardware
volumes:
- /etc/localtime:/etc/localtime:ro
- /home/USER/.docker/nvr/config.yml:/config/config.yml
- /home/USER/.docker/nvr:/media/frigate
- /home/USER/.docker/nvr:/db
- type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
target: /tmp/cache
tmpfs:
size: 1000000000
ports:
- "5000:5000"
- "8554:8554" # RTSP feeds
- "8555:8555/tcp" # WebRTC over tcp
- "8555:8555/udp" # WebRTC over udp

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# https://docs.frigate.video/configuration/reference
# This config uses a PCIe based TPU, records a clip for a person and takes a snapshot for cats and dogs.
mqtt:
enabled: False
database:
path: /db/frigate.db
ffmpeg:
hwaccel_args: preset-vaapi #enables intel HW acceleration
# Using the Google Coral TPUs. Tested the Mini PCIe Accelerator and the M.2 Accelerator A+E key
# https://coral.ai/products/pcie-accelerator https://coral.ai/products/m2-accelerator-ae
detectors:
coral:
type: edgetpu
device: pci:0
detect:
enabled: True
width: 1280
height: 720
fps: 5
objects:
# Optional: list of objects to track from labelmap.txt (default: shown below)
track:
- person
- dog
- cat
# Optional: mask to prevent all object types from being detected in certain areas (default: no mask)
# Checks based on the bottom center of the bounding box of the object.
# NOTE: This mask is COMBINED with the object type specific mask below
mask: 0,0,1000,0,1000,200,0,200
# 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 width/height of the bounding box for the detected object (default: 0)
min_ratio: 0.5
# Optional: maximum width/height of the bounding box for the detected object (default: 24000000)
max_ratio: 2.0
# 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
# 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
# Optional: Motion configuration
# NOTE: Can be overridden 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 (default: 30)
# Increasing this value will prevent smaller areas of motion from being detected. Decreasing will
# make motion detection more sensitive to smaller moving objects.
# As a rule of thumb:
# - 15 - high sensitivity
# - 30 - medium sensitivity
# - 50 - low sensitivity
contour_area: 30
# 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: 50)
# 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: 50
# Optional: motion mask
# NOTE: see docs for more detailed info on creating masks
mask: 0,900,1080,900,1080,1920,0,1920
# Optional: improve contrast (default: shown below)
# Enables dynamic contrast improvement. This should help improve night detections at the cost of making motion detection more sensitive
# for daytime.
improve_contrast: False
# Optional: Delay when updating camera motion through MQTT from ON -> OFF (default: shown below).
mqtt_off_delay: 30
# Optional: Record configuration
# NOTE: Can be overridden at the camera level
record:
# Optional: Enable recording (default: shown below)
# WARNING: If recording is disabled in the config, turning it on via
# the UI or MQTT later will have no effect.
enabled: True
# Optional: Number of minutes to wait between cleanup runs (default: shown below)
# This can be used to reduce the frequency of deleting recording segments from disk if you want to minimize i/o
expire_interval: 60
# Optional: Retention settings for recording
retain:
# Optional: Number of days to retain recordings regardless of events (default: shown below)
# NOTE: This should be set to 0 and retention should be defined in events section below
# if you only want to retain recordings of events.
days: 0
# Optional: Mode for retention. Available options are: all, motion, and active_objects
# all - save all recording segments regardless of activity
# motion - save all recordings segments with any detected motion
# active_objects - save all recording segments with active/moving objects
# NOTE: this mode only applies when the days setting above is greater than 0
mode: motion
# Optional: Event recording settings
events:
# Optional: Number of seconds before the event to include (default: shown below)
pre_capture: 5
# Optional: Number of seconds after the event to include (default: shown below)
post_capture: 5
# Optional: Objects to save recordings for. (default: all tracked objects)
objects:
- person
# Optional: Restrict recordings to objects that entered any of the listed zones (default: no required zones)
required_zones: []
# Optional: Retention settings for recordings of events
retain:
# Required: Default retention days (default: shown below)
default: 10
# Optional: Mode for retention. (default: shown below)
# all - save all recording segments for events regardless of activity
# motion - save all recordings segments for events with any detected motion
# active_objects - save all recording segments for event with active/moving objects
#
# NOTE: If the retain mode for the camera is more restrictive than the mode configured
# here, the segments will already be gone by the time this mode is applied.
# For example, if the camera retain mode is "motion", the segments without motion are
# never stored, so setting the mode to "all" here won't bring them back.
mode: motion
# Optional: Per object retention days
objects:
person: 30
# Optional: Configuration for the jpg snapshots written to the clips directory for each event
# NOTE: Can be overridden at the camera level
snapshots:
# Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
enabled: True
# Optional: save a clean PNG copy of the snapshot image (default: shown below)
retain:
# Required: Default retention days (default: shown below)
default: 30
# Optional: Per object retention days
objects:
person: 30
## Cameras setup.
## Replace USER with your Cameras login user and CAMERA_PASSWORDS with the password for each login.
## Check IPs in the URLs.
## This is how my Riolink RLC-410-5MP need to be configured to have both streams available and accessible in Home Assistant
go2rtc:
streams:
username: USER
password: CAMERA_PASSWORDS
frontdoor:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X1:554/h264Preview_01_main
frontdoor_sub:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X1:554/h264Preview_01_sub
driveway:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X2:554/h264Preview_01_main
driveway_sub:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X2:554/h264Preview_01_sub
westgate:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X3:554/h264Preview_01_main
westgate_sub:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X3:554/h264Preview_01_sub
eastgate:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X4:554/h264Preview_01_main
eastgate_sub:
- rtsp://USER:CAMERA_PASSWORDS@192.168.1.X4:554/h264Preview_01_sub
cameras:
frontdoor:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/frontdoor
roles:
- record
- path: rtsp://127.0.0.1:8554/frontdoor_sub
roles:
- detect
driveway:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/driveway
roles:
- record
- path: rtsp://127.0.0.1:8554/driveway_sub
roles:
- detect
westgate:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/westgate
roles:
- record
- path: rtsp://127.0.0.1:8554/westgate_sub
roles:
- detect
eastgate:
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:8554/eastgate
roles:
- record
- path: rtsp://127.0.0.1:8554/eastgate_sub
roles:
- detect
# Birdseye creates a grid of the available cameras to see all at once.
birdseye:
enabled: True
mode: continuous
restream: False
width: 1920
height: 1080
quality: 4
rtmp:
enabled: false

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# Edit this configuration file to define what should be installed on
# your system. Help is available in the configuration.nix(5) man page
# and in the NixOS manual (accessible by running ‘nixos-help’).
{ config, lib, pkgs, ... }:
{
# To get the Coral stuff to build get:
# https://github.com/colino17/nixdots/blob/6291ecdccc3670c8e823b8e5f1fd5c0bb1a2993c/services/coral.nix
# https://github.com/colino17/nixdots/blob/main/packages/gasket.nix
# https://github.com/colino17/nixdots/blob/main/packages/libedgetpu.nix
# Put coral.nix in /etc/nixos/ put gasket.nix and libedgetpu.nix in /etc/nixos/packages
# Import ./coral.nix
imports =
[ # Include the results of the hardware scan.
./hardware-configuration.nix
./coral.nix
];
# Bootloader.
boot.loader.systemd-boot.enable = true;
boot.kernelParams = ["intel_iommu=on"];
boot.loader.efi.canTouchEfiVariables = true;
# HostName
networking.hostName = "frigate"; # Define your hostname.
# networking.wireless.enable = true; # Enables wireless support via wpa_supplicant.
# Enable networking
networking.networkmanager.enable = true;
# Set your time zone.
time.timeZone = "America/Los_Angeles";
# Select internationalisation properties.
i18n.defaultLocale = "en_US.UTF-8";
i18n.extraLocaleSettings = {
LC_ADDRESS = "en_US.UTF-8";
LC_IDENTIFICATION = "en_US.UTF-8";
LC_MEASUREMENT = "en_US.UTF-8";
LC_MONETARY = "en_US.UTF-8";
LC_NAME = "en_US.UTF-8";
LC_NUMERIC = "en_US.UTF-8";
LC_PAPER = "en_US.UTF-8";
LC_TELEPHONE = "en_US.UTF-8";
LC_TIME = "en_US.UTF-8";
};
# Define a user account. Don't forget to set a password with ‘passwd’.
users.users.USER = {
isNormalUser = true;
description = "USER";
extraGroups = [ "networkmanager" "wheel" "docker" "apex" ]; # apex is needed for the TPU.
packages = with pkgs; [
tree
nano
htop
tailscale
zfs
btop
pciutils
usbutils
tmux
ncdu
];
};
# Enable Docker
virtualisation.docker = {
enable = true;
};
# Fish Shell
programs.fish.enable = true;
# Enables the tailscale service
services.tailscale.enable = true;
# Allow unfree packages
nixpkgs.config.allowUnfree = true;
# List packages installed in system profile. To search, run:
# $ nix search wget
environment.systemPackages = with pkgs; [
# vim # Do not forget to add an editor to edit configuration.nix! The Nano editor is also installed by default.
curl
nano
git
wget
python3
];
# List services that you want to enable:
# Enable the OpenSSH daemon.
services.openssh.enable = true;
# Open ports in the firewall.
# networking.firewall.allowedTCPPorts = [ ... ];
# networking.firewall.allowedUDPPorts = [ ... ];
# Or disable the firewall altogether.
networking.firewall.enable = false;
# This value determines the NixOS release from which the default
# settings for stateful data, like file locations and database versions
# on your system were taken. It‘s perfectly fine and recommended to leave
# this value at the release version of the first install of this system.
# Before changing this value read the documentation for this option
# (e.g. man configuration.nix or on https://nixos.org/nixos/options.html).
system.stateVersion = "23.11"; # Did you read the comment?
}

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{ config, pkgs, ... }:
let
libedgetpu = config.boot.kernelPackages.callPackage /etc/nixos/packages/libedgetpu.nix {};
gasket = config.boot.kernelPackages.callPackage /etc/nixos/packages/gasket.nix {};
in
{
services.udev.packages = [ libedgetpu ];
users.groups.plugdev = {};
boot.extraModulePackages = [ gasket ];
}

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{ stdenv, lib, fetchFromGitHub, kernel }:
stdenv.mkDerivation rec {
pname = "gasket";
version = "1.0-18";
src = fetchFromGitHub {
owner = "google";
repo = "gasket-driver";
rev = "97aeba584efd18983850c36dcf7384b0185284b3";
sha256 = "pJwrrI7jVKFts4+bl2xmPIAD01VKFta2SRuElerQnTo=";
};
makeFlags = [
"-C"
"${kernel.dev}/lib/modules/${kernel.modDirVersion}/build"
"M=$(PWD)"
];
buildFlags = [ "modules" ];
installFlags = [ "INSTALL_MOD_PATH=${placeholder "out"}" ];
installTargets = [ "modules_install" ];
sourceRoot = "source/src";
hardeningDisable = [ "pic" "format" ];
nativeBuildInputs = kernel.moduleBuildDependencies;
meta = with lib; {
description = "The Coral Gasket Driver allows usage of the Coral EdgeTPU on Linux systems.";
homepage = "https://github.com/google/gasket-driver";
license = licenses.gpl2;
maintainers = [ lib.maintainers.kylehendricks ];
platforms = platforms.linux;
};
}

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{ stdenv
, lib
, fetchFromGitHub
, libusb1
, abseil-cpp
, flatbuffers
, xxd
}:
let
flatbuffers_1_12 = flatbuffers.overrideAttrs (oldAttrs: rec {
version = "1.12.0";
NIX_CFLAGS_COMPILE = "-Wno-error=class-memaccess -Wno-error=maybe-uninitialized";
cmakeFlags = (oldAttrs.cmakeFlags or []) ++ ["-DFLATBUFFERS_BUILD_SHAREDLIB=ON"];
NIX_CXXSTDLIB_COMPILE = "-std=c++17";
configureFlags = (oldAttrs.configureFlags or []) ++ ["--enable-shared"];
src = fetchFromGitHub {
owner = "google";
repo = "flatbuffers";
rev = "v${version}";
sha256 = "sha256-L1B5Y/c897Jg9fGwT2J3+vaXsZ+lfXnskp8Gto1p/Tg=";
};
});
in stdenv.mkDerivation rec {
pname = "libedgetpu";
version = "grouper";
src = fetchFromGitHub {
owner = "google-coral";
repo = pname;
rev = "release-${version}";
sha256 = "sha256-73hwItimf88Iqnb40lk4ul/PzmCNIfdt6Afi+xjNiBE=";
};
makeFlags = ["-f" "makefile_build/Makefile" "libedgetpu" ];
buildInputs = [
libusb1
abseil-cpp
flatbuffers_1_12
];
nativeBuildInputs = [
xxd
];
NIX_CXXSTDLIB_COMPILE = "-std=c++17";
TFROOT = "${fetchFromGitHub {
owner = "tensorflow";
repo = "tensorflow";
rev = "v2.7.4";
sha256 = "sha256-liDbUAdaVllB0b74aBeqNxkYNu/zPy7k3CevzRF5dk0=";
}}";
enableParallelBuilding = false;
installPhase = ''
mkdir -p $out/lib
cp out/direct/k8/libedgetpu.so.1.0 $out/lib
ln -s $out/lib/libedgetpu.so.1.0 $out/lib/libedgetpu.so.1
mkdir -p $out/lib/udev/rules.d
cp debian/edgetpu-accelerator.rules $out/lib/udev/rules.d/99-edgetpu-accelerator.rules
'';
}