Installation

Frigate is a Docker container that can be run on any Docker host including as a Home Assistant App. Note that the Home Assistant App is not the same thing as the integration. The integration is required to integrate Frigate into Home Assistant, whether you are running Frigate as a standalone Docker container or as a Home Assistant App.

tip

If you already have Frigate installed as a Home Assistant App, check out the getting started guide to configure Frigate.

Dependencies

MQTT broker (optional) - An MQTT broker is optional with Frigate, but is required for the Home Assistant integration. If using Home Assistant, Frigate and Home Assistant must be connected to the same MQTT broker.

Preparing your hardware

Operating System

Frigate runs best with Docker installed on bare metal Debian-based distributions. For ideal performance, Frigate needs low overhead access to underlying hardware for the Coral and GPU devices. Running Frigate in a VM on top of Proxmox, ESXi, Virtualbox, etc. is not recommended though some users have had success with Proxmox.

Windows is not officially supported, but some users have had success getting it to run under WSL or Virtualbox. Getting the GPU and/or Coral devices properly passed to Frigate may be difficult or impossible. Search previous discussions or issues for help.

Storage

Frigate uses the following locations for read/write operations in the container. Docker volume mappings can be used to map these to any location on your host machine.

/config: Used to store the Frigate config file and sqlite database. You will also see a few files alongside the database file while Frigate is running.
/media/frigate/clips: Used for snapshot storage. In the future, it will likely be renamed from clips to snapshots. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
/media/frigate/recordings: Internal system storage for recording segments. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
/media/frigate/exports: Storage for clips and timelapses that have been exported via the WebUI or API.
/tmp/cache: Cache location for recording segments. Initial recordings are written here before being checked and converted to mp4 and moved to the recordings folder. Segments generated via the clip.mp4 endpoints are also concatenated and processed here. It is recommended to use a tmpfs mount for this.
/dev/shm: Internal cache for raw decoded frames in shared memory. It is not recommended to modify this directory or map it with docker. The minimum size is impacted by the shm-size calculations below.

Ports

The following ports are used by Frigate and can be mapped via docker as required.

Port	Description
`8971`	Authenticated UI and API access without TLS. Reverse proxies should use this port.
`5000`	Internal unauthenticated UI and API access. Access to this port should be limited. Intended to be used within the docker network for services that integrate with Frigate.
`8554`	RTSP restreaming. By default, these streams are unauthenticated. Authentication can be configured in go2rtc section of config.
`8555`	WebRTC connections for cameras with two-way talk support.

Common Docker Compose storage configurations

Writing to a local disk or external USB drive:

services:
  frigate:
    ...
    volumes:
      - /path/to/your/config:/config
      - /path/to/your/storage:/media/frigate
      - type: tmpfs # 1GB In-memory filesystem for recording segment storage
        target: /tmp/cache
        tmpfs:
          size: 1000000000
    ...

warning

Users of the Snapcraft build of Docker cannot use storage locations outside your $HOME folder.

Calculating required shm-size

Frigate utilizes shared memory to store frames during processing. The default shm-size provided by Docker is 64MB.

The default shm size of 128MB is fine for setups with 2 cameras detecting at 720p. If Frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size, using --shm-size (or service.shm_size in Docker Compose).

The Frigate container also stores logs in shm, which can take up to 40MB, so make sure to take this into account in your math as well.

SHM Calculator

Calculate required shared memory (SHM) based on camera resolution and count

note

The resolution below is the detect stream resolution, not the record stream resolution. SHM size is determined by the detect resolution used for object detection. Learn more about choosing a detect resolution.

Width:

Height:

Camera Count:

Calculation Result

26.32MB

Single Camera: 26.32MB

Formula: (width × height × 1.5 × 20 + 270480) ÷ 1048576

With Logs: + 40mb

Common Presets

The shm size cannot be set per container for Home Assistant Apps. However, this is probably not required since by default Home Assistant Supervisor allocates /dev/shm with half the size of your total memory. If your machine has 8GB of memory, chances are that Frigate will have access to up to 4GB without any additional configuration.

Extra Steps for Specific Hardware

The following sections contain additional setup steps that are only required if you are using specific hardware. If you are not using any of these hardware types, you can skip to the Docker installation section.

Raspberry Pi 3/4

By default, the Raspberry Pi limits the amount of memory available to the GPU. In order to use ffmpeg hardware acceleration, you must increase the available memory by setting gpu_mem to the maximum recommended value in config.txt as described in the official docs.

Additionally, the USB Coral draws a considerable amount of power. If using any other USB devices such as an SSD, you will experience instability due to the Pi not providing enough power to USB devices. You will need to purchase an external USB hub with it's own power supply. Some have reported success with this (affiliate link).

Hailo-8

The Hailo-8 and Hailo-8L AI accelerators are available in both M.2 and HAT form factors for the Raspberry Pi. The M.2 version typically connects to a carrier board for PCIe, which then interfaces with the Raspberry Pi 5 as part of the AI Kit. The HAT version can be mounted directly onto compatible Raspberry Pi models. Both form factors have been successfully tested on x86 platforms as well, making them versatile options for various computing environments.

Installation

warning

On Raspberry Pi OS Bookworm, the kernel includes an older version of the Hailo driver that is incompatible with Frigate. You must follow the installation steps below to install the correct driver version, and you must disable the built-in kernel driver as described in step 1.

On Raspberry Pi OS Trixie, the Hailo driver is no longer shipped with the kernel. It is installed via DKMS, and the conflict described below does not apply. You can simply run the installation script.

Disable the built-in Hailo driver (Raspberry Pi Bookworm OS only):

note
If you are not using a Raspberry Pi with Bookworm OS, skip this step and proceed directly to step 2.
If you are using Raspberry Pi with Trixie OS, also skip this step and proceed directly to step 2.

First, check if the driver is currently loaded:
```
lsmod | grep hailo
```
If it shows hailo_pci, unload it:
```
sudo modprobe -r hailo_pci
```
Then locate the built-in kernel driver and rename it so it cannot be loaded. Renaming allows the original driver to be restored later if needed. First, locate the currently installed kernel module:
```
modinfo -n hailo_pci
```
Example output:
```
/lib/modules/6.6.31+rpt-rpi-2712/kernel/drivers/media/pci/hailo/hailo_pci.ko.xz
```
Save the module path to a variable:
```
BUILTIN=$(modinfo -n hailo_pci)
```
And rename the module by appending .bak:
```
sudo mv "$BUILTIN" "${BUILTIN}.bak"
```
Now refresh the kernel module map so the system recognizes the change:
```
sudo depmod -a
```
Reboot your Raspberry Pi:
```
sudo reboot
```
After rebooting, verify the built-in driver is not loaded:
```
lsmod | grep hailo
```
This command should return no results.
Run the installation script:

Download the installation script:
```
wget https://raw.githubusercontent.com/blakeblackshear/frigate/dev/docker/hailo8l/user_installation.sh
```
Make it executable:
```
sudo chmod +x user_installation.sh
```
Run the script:
```
./user_installation.sh
```
The script will:
- Install necessary build dependencies
- Clone and build the Hailo driver from the official repository
- Install the driver
- Download and install the required firmware
- Set up udev rules
Reboot your system:

After the script completes successfully, reboot to load the firmware:
```
sudo reboot
```
Verify the installation:

After rebooting, verify that the Hailo device is available:
```
ls -l /dev/hailo0
```
You should see the device listed. You can also verify the driver is loaded:
```
lsmod | grep hailo_pci
```
Verify the driver version:
```
cat /sys/module/hailo_pci/version
```
Verify that the firmware was installed correctly:
```
ls -l /lib/firmware/hailo/hailo8_fw.bin
```
Optional: Fix PCIe descriptor page size error

If you encounter the following error:
```
[HailoRT] [error] CHECK failed - max_desc_page_size given 16384 is bigger than hw max desc page size 4096
```
Create a configuration file to force the correct descriptor page size:
```
echo 'options hailo_pci force_desc_page_size=4096' | sudo tee /etc/modprobe.d/hailo_pci.conf
```
and reboot:
```
sudo reboot
```

Setup

To set up Frigate, follow the default installation instructions, for example: ghcr.io/blakeblackshear/frigate:stable

Next, grant Docker permissions to access your hardware by adding the following lines to your docker-compose.yml file:

devices:
  - /dev/hailo0

If you are using docker run, add this option to your command --device /dev/hailo0

Configuration

Finally, configure hardware object detection to complete the setup.

MemryX MX3

The MemryX MX3 Accelerator is available in the M.2 2280 form factor (like an NVMe SSD), and supports a variety of configurations:

x86 (Intel/AMD) PCs
Raspberry Pi 5
Orange Pi 5 Plus/Max
Multi-M.2 PCIe carrier cards

Configuration

Installation

To get started with MX3 hardware setup for your system, refer to the Hardware Setup Guide.

Then follow these steps for installing the correct driver/runtime configuration:

Copy or download this script.
Ensure it has execution permissions with sudo chmod +x user_installation.sh
Run the script with ./user_installation.sh
Restart your computer to complete driver installation.

Setup

To set up Frigate, follow the default installation instructions, for example: ghcr.io/blakeblackshear/frigate:stable

Next, grant Docker permissions to access your hardware by adding the following lines to your docker-compose.yml file:

devices:
  - /dev/memx0

During configuration, you must run Docker in privileged mode and ensure the container can access the max-manager.

In your docker-compose.yml, also add:

privileged: true

volumes:
  - /run/mxa_manager:/run/mxa_manager

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

  docker run -d \
    --name frigate-memx \
    --restart=unless-stopped \
    --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 \
    --shm-size=256m \
    -v /path/to/your/storage:/media/frigate \
    -v /path/to/your/config:/config \
    -v /etc/localtime:/etc/localtime:ro \
    -v /run/mxa_manager:/run/mxa_manager \
    -e FRIGATE_RTSP_PASSWORD='password' \
    --privileged=true \
    -p 8971:8971 \
    -p 8554:8554 \
    -p 5000:5000 \
    -p 8555:8555/tcp \
    -p 8555:8555/udp \
    --device /dev/memx0 \
    ghcr.io/blakeblackshear/frigate:stable

Configuration

Finally, configure hardware object detection to complete the setup.

Rockchip platform

Make sure that you use a linux distribution that comes with the rockchip BSP kernel 5.10 or 6.1 and necessary drivers (especially rkvdec2 and rknpu). To check, enter the following commands:

$ uname -r
5.10.xxx-rockchip # or 6.1.xxx; the -rockchip suffix is important
$ ls /dev/dri
by-path  card0  card1  renderD128  renderD129 # should list renderD128 (VPU) and renderD129 (NPU)
$ sudo cat /sys/kernel/debug/rknpu/version
RKNPU driver: v0.9.2 # or later version

I recommend Armbian, if your board is supported.

Setup

Follow Frigate's default installation instructions, but use a docker image with -rk suffix for example ghcr.io/blakeblackshear/frigate:stable-rk.

Next, you need to grant docker permissions to access your hardware:

During the configuration process, you should run docker in privileged mode to avoid any errors due to insufficient permissions. To do so, add privileged: true to your docker-compose.yml file or the --privileged flag to your docker run command.
After everything works, you should only grant necessary permissions to increase security. Disable the privileged mode and add the lines below to your docker-compose.yml file:

security_opt:
  - apparmor=unconfined
  - systempaths=unconfined
devices:
  - /dev/dri
  - /dev/dma_heap
  - /dev/rga
  - /dev/mpp_service
volumes:
  - /sys/:/sys/:ro

or add these options to your docker run command:

--security-opt systempaths=unconfined \
--security-opt apparmor=unconfined \
--device /dev/dri \
--device /dev/dma_heap \
--device /dev/rga \
--device /dev/mpp_service \
--volume /sys/:/sys/:ro

Configuration

Next, you should configure hardware object detection and hardware video processing.

Synaptics

SL1680

Setup

Follow Frigate's default installation instructions, but use a docker image with -synaptics suffix for example ghcr.io/blakeblackshear/frigate:stable-synaptics.

Next, you need to grant docker permissions to access your hardware:

During the configuration process, you should run docker in privileged mode to avoid any errors due to insufficient permissions. To do so, add privileged: true to your docker-compose.yml file or the --privileged flag to your docker run command.

devices:
  - /dev/synap
  - /dev/video0
  - /dev/video1

or add these options to your docker run command:

--device /dev/synap \
--device /dev/video0 \
--device /dev/video1

Configuration

Next, you should configure hardware object detection and hardware video processing.

AXERA

AXERA accelerators are available in an M.2 form factor, compatible with both Raspberry Pi and Orange Pi. This form factor has also been successfully tested on x86 platforms, making it a versatile choice for various computing environments.

Installation

Using AXERA accelerators requires the installation of the AXCL driver. We provide a convenient Linux script to complete this installation.

Follow these steps for installation:

Copy or download this script.
Ensure it has execution permissions with sudo chmod +x user_installation.sh
Run the script with ./user_installation.sh

Setup

To set up Frigate, follow the default installation instructions, for example: ghcr.io/blakeblackshear/frigate:stable

Next, grant Docker permissions to access your hardware by adding the following lines to your docker-compose.yml file:

devices:
  - /dev/axcl_host
  - /dev/ax_mmb_dev
  - /dev/msg_userdev
volumes:
  - /usr/bin/axcl:/usr/bin/axcl
  - /usr/lib/axcl:/usr/lib/axcl

If you are using docker run, add this option to your command --device /dev/axcl_host --device /dev/ax_mmb_dev --device /dev/msg_userdev

Configuration

Finally, configure hardware object detection to complete the setup.

Docker

Running through Docker with Docker Compose is the recommended install method.

services:
  frigate:
    container_name: frigate
    privileged: true # this may not be necessary for all setups
    restart: unless-stopped
    stop_grace_period: 30s # allow enough time to shut down the various services
    image: ghcr.io/blakeblackshear/frigate:stable
    shm_size: "512mb" # update for your cameras based on calculation above
    devices:
      - /dev/bus/usb:/dev/bus/usb # Passes the USB Coral, needs to be modified for other versions
      - /dev/apex_0:/dev/apex_0 # Passes a PCIe Coral, follow driver instructions here https://github.com/jnicolson/gasket-builder
      - /dev/video11:/dev/video11 # For Raspberry Pi 4B
      - /dev/dri/renderD128:/dev/dri/renderD128 # AMD / Intel GPU, needs to be updated for your hardware
      - /dev/kfd:/dev/kfd # AMD Kernel Fusion Driver for ROCm
      - /dev/accel:/dev/accel # AMD / Intel NPU
    volumes:
      - /etc/localtime:/etc/localtime:ro
      - /path/to/your/config:/config
      - /path/to/your/storage:/media/frigate
      - type: tmpfs # 1GB In-memory filesystem for recording segment storage
        target: /tmp/cache
        tmpfs:
          size: 1000000000
    ports:
      - "8971:8971"
      # - "5000:5000" # Internal unauthenticated access. Expose carefully.
      - "8554:8554" # RTSP feeds
      - "8555:8555/tcp" # WebRTC over tcp
      - "8555:8555/udp" # WebRTC over udp
    environment:
      FRIGATE_RTSP_PASSWORD: "password"

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

docker run -d \
  --name frigate \
  --restart=unless-stopped \
  --stop-timeout 30 \
  --mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 \
  --device /dev/bus/usb:/dev/bus/usb \
  --device /dev/dri/renderD128 \
  --shm-size=64m \
  -v /path/to/your/storage:/media/frigate \
  -v /path/to/your/config:/config \
  -v /etc/localtime:/etc/localtime:ro \
  -e FRIGATE_RTSP_PASSWORD='password' \
  -p 8971:8971 \
  -p 8554:8554 \
  -p 8555:8555/tcp \
  -p 8555:8555/udp \
  ghcr.io/blakeblackshear/frigate:stable

The official docker image tags for the current stable version are:

stable - Standard Frigate build for amd64 & RPi Optimized Frigate build for arm64. This build includes support for Hailo devices as well.
stable-standard-arm64 - Standard Frigate build for arm64
stable-tensorrt - Frigate build specific for amd64 devices running an Nvidia GPU
stable-rocm - Frigate build for AMD GPUs

The community supported docker image tags for the current stable version are:

stable-tensorrt-jp6 - Frigate build optimized for Nvidia Jetson devices running Jetpack 6
stable-rk - Frigate build for SBCs with Rockchip SoC

Home Assistant App

warning

As of Home Assistant Operating System 10.2 and Home Assistant 2023.6 defining separate network storage for media is supported.

There are important limitations in HA OS to be aware of:

Separate local storage for media is not yet supported by Home Assistant
AMD GPUs are not supported because HA OS does not include the mesa driver.
Intel NPUs are not supported because HA OS does not include the NPU firmware.
Nvidia GPUs are not supported because HA Apps do not support the Nvidia runtime.

tip

See the network storage guide for instructions to setup network storage for frigate.

Home Assistant OS users can install via the App repository.

In Home Assistant, navigate to Settings > Apps > App Store > Repositories
Add https://github.com/blakeblackshear/frigate-hass-addons
Install the desired variant of the Frigate App (see below)
Setup your network configuration in the Configuration tab
Start the App
Use the Open Web UI button to access the Frigate UI, then click in the cog icon > Configuration editor and configure Frigate to your liking

There are several variants of the App available:

App Variant	Description
Frigate	Current release with protection mode on
Frigate (Full Access)	Current release with the option to disable protection mode
Frigate Beta	Beta release with protection mode on
Frigate Beta (Full Access)	Beta release with the option to disable protection mode

If you are using hardware acceleration for ffmpeg, you may need to use the Full Access variant of the App. This is because the Frigate App runs in a container with limited access to the host system. The Full Access variant allows you to disable Protection mode and give Frigate full access to the host system.

You can also edit the Frigate configuration file through the VS Code App or similar. In that case, the configuration file will be at /addon_configs/<addon_directory>/config.yml, where <addon_directory> is specific to the variant of the Frigate App you are running. See the list of directories here.

Kubernetes

Use the helm chart.

Unraid

Many people have powerful enough NAS devices or home servers to also run docker. There is a Unraid Community App. To install make sure you have the community app plugin here. Then search for "Frigate" in the apps section within Unraid - you can see the online store here

Proxmox

According to Proxmox documentation it is recommended that you run application containers like Frigate inside a Proxmox QEMU VM. This will give you all the advantages of application containerization, while also providing the benefits that VMs offer, such as strong isolation from the host and the ability to live-migrate, which otherwise isn’t possible with containers. Ensure that ballooning is disabled, especially if you are passing through a GPU to the VM.

warning

If you choose to run Frigate via LXC in Proxmox the setup can be complex so be prepared to read the Proxmox and LXC documentation, Frigate does not officially support running inside of an LXC.

Suggestions include:

For Intel-based hardware acceleration, to allow access to the /dev/dri/renderD128 device with major number 226 and minor number 128, add the following lines to the /etc/pve/lxc/<id>.conf LXC configuration:
- lxc.cgroup2.devices.allow: c 226:128 rwm
- lxc.mount.entry: /dev/dri/renderD128 dev/dri/renderD128 none bind,optional,create=file
The LXC configuration will likely also need features: fuse=1,nesting=1. This allows running a Docker container in an LXC container (nesting) and prevents duplicated files and wasted storage (fuse).
Successfully passing hardware devices through multiple levels of containerization (LXC then Docker) can be difficult. Many people make devices like /dev/dri/renderD128 world-readable in the host or run Frigate in a privileged LXC container.
The virtualization layer often introduces a sizable amount of overhead for communication with Coral devices, but not in all circumstances.

See the Proxmox LXC discussion for more general information.

ESXi

For details on running Frigate using ESXi, please see the instructions here.

If you're running Frigate on a rack mounted server and want to passthrough the Google Coral, read this.

Synology NAS on DSM 7

These settings were tested on DSM 7.1.1-42962 Update 4

General:

The Execute container using high privilege option needs to be enabled in order to give the frigate container the elevated privileges it may need.

The Enable auto-restart option can be enabled if you want the container to automatically restart whenever it improperly shuts down due to an error.

Advanced Settings:

If you want to use the password template feature, you should add the "FRIGATE_RTSP_PASSWORD" environment variable and set it to your preferred password under advanced settings. The rest of the environment variables should be left as default for now.

Port Settings:

The network mode should be set to bridge. You need to map the default frigate container ports to your local Synology NAS ports that you want to use to access Frigate.

There may be other services running on your NAS that are using the same ports that frigate uses. In that instance you can set the ports to auto or a specific port.

Volume Settings:

You need to configure 2 paths:

The location of your config directory which will be different depending on your NAS folder structure e.g. /docker/frigate/config will mount to /config within the container.
The location on your NAS where the recordings will be saved this needs to be a folder e.g. /docker/volumes/frigate-0-media

QNAP NAS

These instructions were tested on a QNAP with an Intel J3455 CPU and 16G RAM, running QTS 4.5.4.2117.

QNAP has a graphic tool named Container Station to install and manage docker containers. However, there are two limitations with Container Station that make it unsuitable to install Frigate:

Container Station does not incorporate GitHub Container Registry (ghcr), which hosts Frigate docker image version 0.12.0 and above.
Container Station uses default 64 Mb shared memory size (shm-size), and does not have a mechanism to adjust it. Frigate requires a larger shm-size to be able to work properly with more than two high resolution cameras.

Because of above limitations, the installation has to be done from command line. Here are the steps:

Preparation

Install Container Station from QNAP App Center if it is not installed.
Enable ssh on your QNAP (please do an Internet search on how to do this).
Prepare Frigate config file, name it config.yml.
Calculate shared memory size according to documentation.
Find your time zone value from https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
ssh to QNAP.

Installation

Run the following commands to install Frigate (using stable version as example):

# Download Frigate image
docker pull ghcr.io/blakeblackshear/frigate:stable
# Create directory to host Frigate config file on QNAP file system.
# E.g., you can choose to create it under /share/Container.
mkdir -p /share/Container/frigate/config
# Copy the config file prepared in step 2 into the newly created config directory.
cp path/to/your/config/file /share/Container/frigate/config
# Create directory to host Frigate media files on QNAP file system.
# (if you have a surveillance disk, create media directory on the surveillance disk.
# Example command assumes share_vol2 is the surveillance drive
mkdir -p /share/share_vol2/frigate/media
# Create Frigate docker container.  Replace shm-size value with the value from preparation step 3.
# Also replace the time zone value for 'TZ' in the sample command.
# Example command will create a docker container that uses at most 2 CPUs and 4G RAM.
# You may need to add "--env=LIBVA_DRIVER_NAME=i965 \" to the following docker run command if you
# have certain CPU (e.g., J4125). See https://docs.frigate.video/configuration/hardware_acceleration_video.
docker run \
  --name=frigate \
  --shm-size=256m \
  --restart=unless-stopped \
  --env=TZ=America/New_York \
  --volume=/share/Container/frigate/config:/config:rw \
  --volume=/share/share_vol2/frigate/media:/media/frigate:rw \
  --network=bridge \
  --privileged \
  --workdir=/opt/frigate \
  -p 8971:8971 \
  -p 8554:8554 \
  -p 8555:8555 \
  -p 8555:8555/udp \
  --label='com.qnap.qcs.network.mode=nat' \
  --label='com.qnap.qcs.gpu=False' \
  --memory="4g" \
  --cpus="2" \
  --detach=true \
  -t \
  ghcr.io/blakeblackshear/frigate:stable

Log into QNAP, open Container Station. Frigate docker container should be listed under 'Overview' and running. Visit Frigate Web UI by clicking Frigate docker, and then clicking the URL shown at the top of the detail page.

macOS - Apple Silicon

warning

macOS uses port 5000 for its Airplay Receiver service. If you want to expose port 5000 in Frigate for local app and API access the port will need to be mapped to another port on the host e.g. 5001

Failure to remap port 5000 on the host will result in the WebUI and all API endpoints on port 5000 being unreachable, even if port 5000 is exposed correctly in Docker.

Docker containers on macOS can be orchestrated by either Docker Desktop or OrbStack (native swift app). The difference in inference speeds is negligable, however CPU, power consumption and container start times will be lower on OrbStack because it is a native Swift application.

To allow Frigate to use the Apple Silicon Neural Engine / Processing Unit (NPU) the host must be running Apple Silicon Detector on the host (outside Docker)

Docker Compose example

services:
  frigate:
    container_name: frigate
    image: ghcr.io/blakeblackshear/frigate:stable-standard-arm64
    restart: unless-stopped
    shm_size: "512mb" # update for your cameras based on calculation above
    volumes:
      - /etc/localtime:/etc/localtime:ro
      - /path/to/your/config:/config
      - /path/to/your/recordings:/recordings
    ports:
      - "8971:8971"
      # If exposing on macOS map to a diffent host port like 5001 or any orher port with no conflicts
      # - "5001:5000" # Internal unauthenticated access. Expose carefully.
      - "8554:8554" # RTSP feeds
    extra_hosts:
      # This is very important
      # It allows frigate access to the NPU on Apple Silicon via Apple Silicon Detector
      - "host.docker.internal:host-gateway" # Required to talk to the NPU detector
    environment:
      - FRIGATE_RTSP_PASSWORD: "password"

Dependencies​

Preparing your hardware​

Operating System​

Storage​

Ports​

Common Docker Compose storage configurations​

Calculating required shm-size​

SHM Calculator

Calculation Result

Common Presets

Extra Steps for Specific Hardware​

Raspberry Pi 3/4​

Hailo-8​

Installation​

Setup​

Configuration​

MemryX MX3​

Configuration​

Installation​

Setup​

Configuration​

Rockchip platform​

Setup​

Configuration​

Synaptics​

Setup​

Configuration​

AXERA​

Installation​

Setup​

Configuration​

Docker​

Home Assistant App​

Kubernetes​

Unraid​

Proxmox​

ESXi​

Synology NAS on DSM 7​

QNAP NAS​

macOS - Apple Silicon​

Docker Compose example​

Dependencies

Preparing your hardware

Operating System

Storage

Ports

Common Docker Compose storage configurations

Calculating required shm-size

Extra Steps for Specific Hardware

Raspberry Pi 3/4

Hailo-8

Installation

Setup

Configuration

MemryX MX3

Configuration

Installation

Setup

Configuration

Rockchip platform

Setup

Configuration

Synaptics

Setup

Configuration

AXERA

Installation

Setup

Configuration

Docker

Home Assistant App

Kubernetes

Unraid

Proxmox

ESXi

Synology NAS on DSM 7

QNAP NAS

macOS - Apple Silicon

Docker Compose example