Compare commits

..

1 Commits

Author SHA1 Message Date
dependabot[bot]
4558919ba7 Update scikit-build requirement in /docker/main
Updates the requirements on [scikit-build](https://github.com/scikit-build/scikit-build) to permit the latest version.
- [Release notes](https://github.com/scikit-build/scikit-build/releases)
- [Changelog](https://github.com/scikit-build/scikit-build/blob/main/CHANGES.rst)
- [Commits](https://github.com/scikit-build/scikit-build/compare/0.17.0...0.18.0)

---
updated-dependencies:
- dependency-name: scikit-build
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
2024-06-24 11:34:07 +00:00
405 changed files with 11624 additions and 38312 deletions

View File

@@ -1,304 +1,168 @@
aarch
absdiff
airockchip
Alloc
Amcrest
amdgpu
analyzeduration
Annke
apexcharts
arange
argmax
argmin
argpartition
ascontiguousarray
authelia
authentik
autodetected
automations
autotrack
autotracked
autotracker
autotracking
balena
Beelink
BGRA
BHWC
blackshear
blakeblackshear
bottombar
buildx
castable
cdist
Celeron
cgroups
chipset
chromadb
Chromecast
cmdline
codeowner
CODEOWNERS
codeproject
colormap
colorspace
comms
ctypeslib
CUDA
Cuvid
Dahua
datasheet
debconf
deci
deepstack
defragment
devcontainer
DEVICEMAP
discardcorrupt
dpkg
dsize
dtype
ECONNRESET
edgetpu
faststart
fflags
ffprobe
fillna
flac
foscam
fourcc
framebuffer
fregate
frégate
fromarray
frombuffer
frontdoor
fstype
fullchain
fullscreen
genai
generativeai
genpts
getpid
gpuload
HACS
Hailo
hass
hconcat
healthcheck
hideable
Hikvision
homeassistant
homekit
homography
hsize
hstack
httpx
hwaccel
hwdownload
hwmap
hwupload
iloc
imagestream
imdecode
imencode
imread
imutils
imwrite
interp
iostat
iotop
itemsize
Jellyfin
jetson
jetsons
joserfc
jsmpeg
jsonify
Kalman
keepalive
keepdims
labelmap
letsencrypt
levelname
LIBAVFORMAT
libedgetpu
libnvinfer
libva
libwebp
libx
libyolo
linalg
localzone
logpipe
Loryta
lstsq
lsusb
markupsafe
maxsplit
MEMHOSTALLOC
memlimit
meshgrid
metadatas
migraphx
minilm
mjpeg
mkfifo
mobiledet
mobilenet
modelpath
mosquitto
mountpoint
movflags
mpegts
mqtt
mse
msenc
namedtuples
nbytes
nchw
ndarray
ndimage
nethogs
newaxis
nhwc
NOBLOCK
nobuffer
nokey
NONBLOCK
noninteractive
noprint
Norfair
nptype
NTSC
numpy
nvenc
nvhost
nvml
nvmpi
ollama
onnx
onnxruntime
onvif
ONVIF
openai
opencv
openvino
OWASP
paho
passwordless
popleft
posthog
postprocess
poweroff
preexec
probesize
protobuf
psutil
pubkey
putenv
pycache
pydantic
pyobj
pysqlite
pytz
pywebpush
qnap
quantisation
Radeon
radeonsi
radeontop
rawvideo
rcond
RDONLY
rebranded
referer
reindex
Reolink
restream
restreamed
restreaming
rkmpp
rknn
rkrga
rockchip
rocm
rocminfo
rootfs
rtmp
edgetpu
labelmap
rockchip
jetson
rocm
vaapi
CUDA
hwaccel
RTSP
ruamel
scroller
setproctitle
setpts
shms
SIGUSR
skylake
sleeptime
SNDMORE
socs
sqliteq
ssdlite
statm
stimeout
stylelint
subclassing
substream
superfast
surveillance
svscan
Swipeable
sysconf
tailscale
Tapo
tensorrt
Hikvision
Dahua
Amcrest
Reolink
Loryta
Beelink
Celeron
vaapi
blakeblackshear
workdir
onvif
autotracking
openvino
tflite
deepstack
codeproject
udev
tailscale
restream
restreaming
webrtc
ssdlite
mobilenet
mosquitto
datasheet
Jellyfin
Radeon
libva
Ubiquiti
Unifi
Tapo
Annke
autotracker
autotracked
variations
ONVIF
traefik
devcontainer
rootfs
ffprobe
autotrack
logpipe
imread
imwrite
imencode
imutils
thresholded
timelapse
tmpfs
tobytes
toggleable
traefik
tzlocal
Ubiquiti
udev
udevadm
ultrafast
unichip
unidecode
Unifi
unixepoch
unraid
unreviewed
userdata
usermod
vaapi
sleeptime
radeontop
vainfo
variations
vconcat
vitb
vstream
vsync
wallclock
webp
webpush
webrtc
tmpfs
homography
websockets
webui
werkzeug
workdir
WRONLY
wsgirefserver
wsgiutils
wsize
xaddr
xmaxs
xmins
XPUB
XSUB
ymaxs
ymins
yolo
yolonas
yolox
LIBAVFORMAT
NTSC
onnxruntime
fourcc
radeonsi
paho
imagestream
jsonify
cgroups
sysconf
memlimit
gpuload
nvml
setproctitle
psutil
Kalman
frontdoor
namedtuples
zeep
zerolatency
fflags
probesize
wallclock
rknn
socs
pydantic
shms
imdecode
colormap
webui
mse
jsmpeg
unreviewed
Chromecast
Swipeable
flac
scroller
cmdline
toggleable
bottombar
opencv
apexcharts
buildx
mqtt
rawvideo
defragment
Norfair
subclassing
yolo
tensorrt
blackshear
stylelint
HACS
homeassistant
hass
castable
mobiledet
framebuffer
mjpeg
substream
codeowner
noninteractive
restreamed
mountpoint
fstype
OWASP
iotop
letsencrypt
fullchain
lsusb
iostat
usermod
balena
passwordless
debconf
dpkg
poweroff
surveillance
qnap
homekit
colorspace
quantisation
skylake
Cuvid
foscam
onnx
numpy
protobuf
aarch
amdgpu
chipset
referer
mpegts
webp
authelia
authentik
unichip
rebranded
udevadm
automations
unraid
hideable
healthcheck
keepalive

View File

@@ -10,9 +10,9 @@
"features": {
"ghcr.io/devcontainers/features/common-utils:1": {}
},
"forwardPorts": [8971, 5000, 5001, 5173, 8554, 8555],
"forwardPorts": [8080, 5000, 5001, 5173, 8554, 8555],
"portsAttributes": {
"8971": {
"8080": {
"label": "External NGINX",
"onAutoForward": "silent"
},
@@ -52,8 +52,7 @@
"csstools.postcss",
"blanu.vscode-styled-jsx",
"bradlc.vscode-tailwindcss",
"charliermarsh.ruff",
"eamodio.gitlens"
"charliermarsh.ruff"
],
"settings": {
"remote.autoForwardPorts": false,

View File

@@ -17,7 +17,7 @@ sudo chown -R "$(id -u):$(id -g)" /media/frigate
# When started as a service, LIBAVFORMAT_VERSION_MAJOR is defined in the
# s6 service file. For dev, where frigate is started from an interactive
# shell, we define it in .bashrc instead.
echo 'export LIBAVFORMAT_VERSION_MAJOR=$(/usr/lib/ffmpeg/7.0/bin/ffmpeg -version | grep -Po "libavformat\W+\K\d+")' >> $HOME/.bashrc
echo 'export LIBAVFORMAT_VERSION_MAJOR=$(ffmpeg -version | grep -Po "libavformat\W+\K\d+")' >> $HOME/.bashrc
make version

View File

@@ -0,0 +1,83 @@
title: "[Bug]: "
labels: ["bug", "triage"]
body:
- type: textarea
id: description
attributes:
label: Describe the problem you are having
validations:
required: true
- type: textarea
id: steps
attributes:
label: Steps to reproduce
validations:
required: true
- type: input
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI
validations:
required: true
- type: textarea
id: config
attributes:
label: Frigate config file
description: This will be automatically formatted into code, so no need for backticks.
render: yaml
validations:
required: true
- type: textarea
id: logs
attributes:
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating system
options:
- HassOS
- Debian
- Other Linux
- Proxmox
- UNRAID
- Windows
- Other
validations:
required: true
- type: dropdown
id: install-method
attributes:
label: Install method
options:
- HassOS Addon
- Docker Compose
- Docker CLI
validations:
required: true
- type: dropdown
id: network
attributes:
label: Network connection
options:
- Wired
- Wireless
- Mixed
validations:
required: true
- type: input
id: camera
attributes:
label: Camera make and model
description: Dahua, hikvision, amcrest, reolink, etc and model number
validations:
required: true
- type: textarea
id: other
attributes:
label: Any other information that may be helpful

View File

@@ -1,16 +1,6 @@
title: "[Camera Support]: "
labels: ["support", "triage"]
body:
- type: markdown
attributes:
value: |
Use this form for support or questions for an issue with your cameras.
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: textarea
id: description
attributes:
@@ -21,15 +11,9 @@ body:
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.14.0-ea36ds1)
description: Visible on the System page in the Web UI
validations:
required: true
- type: input
attributes:
label: What browser(s) are you using?
placeholder: Google Chrome 88.0.4324.150
description: >
Provide the full name and don't forget to add the version!
- type: textarea
id: config
attributes:
@@ -39,18 +23,10 @@ body:
validations:
required: true
- type: textarea
id: frigatelogs
id: logs
attributes:
label: Relevant Frigate log output
description: Please copy and paste any relevant Frigate log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: textarea
id: go2rtclogs
attributes:
label: Relevant go2rtc log output
description: Please copy and paste any relevant go2rtc log output. Include logs before and after your exact error when possible. Logs can be viewed via the Frigate UI, Docker, or the go2rtc dashboard. This will be automatically formatted into code, so no need for backticks.
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
@@ -58,7 +34,7 @@ body:
id: ffprobe
attributes:
label: FFprobe output from your camera
description: Run `ffprobe <camera_url>` from within the Frigate container if possible, and provide output below
description: Run `ffprobe <camera_url>` and provide output below
render: shell
validations:
required: true
@@ -90,9 +66,6 @@ body:
- HassOS Addon
- Docker Compose
- Docker CLI
- Proxmox via Docker
- Proxmox via TTeck Script
- Windows WSL2
validations:
required: true
- type: dropdown
@@ -125,13 +98,6 @@ body:
description: Dahua, hikvision, amcrest, reolink, etc and model number
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots of the Frigate UI's System metrics pages
description: Drag and drop for images is possible in this field. Please post screenshots of at least General and Cameras tabs.
validations:
required: true
- type: textarea
id: other
attributes:

View File

@@ -1,16 +1,6 @@
title: "[Config Support]: "
labels: ["support", "triage"]
body:
- type: markdown
attributes:
value: |
Use this form for support or questions related to Frigate's configuration and config file.
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: textarea
id: description
attributes:
@@ -21,7 +11,7 @@ body:
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.14.0-ea36ds1)
description: Visible on the System page in the Web UI
validations:
required: true
- type: textarea
@@ -33,18 +23,10 @@ body:
validations:
required: true
- type: textarea
id: frigatelogs
id: logs
attributes:
label: Relevant Frigate log output
description: Please copy and paste any relevant Frigate log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: textarea
id: go2rtclogs
attributes:
label: Relevant go2rtc log output
description: Please copy and paste any relevant go2rtc log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
@@ -76,17 +58,6 @@ body:
- HassOS Addon
- Docker Compose
- Docker CLI
- Proxmox via Docker
- Proxmox via TTeck Script
- Windows WSL2
validations:
required: true
- type: textarea
id: docker
attributes:
label: docker-compose file or Docker CLI command
description: This will be automatically formatted into code, so no need for backticks.
render: yaml
validations:
required: true
- type: dropdown
@@ -102,11 +73,6 @@ body:
- CPU (no coral)
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots of the Frigate UI's System metrics pages
description: Drag and drop or simple cut/paste is possible in this field
- type: textarea
id: other
attributes:

View File

@@ -1,16 +1,6 @@
title: "[Detector Support]: "
labels: ["support", "triage"]
body:
- type: markdown
attributes:
value: |
Use this form for support or questions related to Frigate's object detectors.
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: textarea
id: description
attributes:
@@ -21,7 +11,7 @@ body:
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.14.0-ea36ds1)
description: Visible on the System page in the Web UI
validations:
required: true
- type: textarea
@@ -41,13 +31,27 @@ body:
validations:
required: true
- type: textarea
id: frigatelogs
id: logs
attributes:
label: Relevant Frigate log output
description: Please copy and paste any relevant Frigate log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating system
options:
- HassOS
- Debian
- Other Linux
- Proxmox
- UNRAID
- Windows
- Other
validations:
required: true
- type: dropdown
id: install-method
attributes:
@@ -56,9 +60,6 @@ body:
- HassOS Addon
- Docker Compose
- Docker CLI
- Proxmox via Docker
- Proxmox via TTeck Script
- Windows WSL2
validations:
required: true
- type: dropdown
@@ -74,13 +75,6 @@ body:
- CPU (no coral)
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots of the Frigate UI's System metrics pages
description: Drag and drop for images is possible in this field. Please post screenshots of at least General and Cameras tabs.
validations:
required: true
- type: textarea
id: other
attributes:

View File

@@ -1,16 +1,6 @@
title: "[Support]: "
labels: ["support", "triage"]
body:
- type: markdown
attributes:
value: |
Use this form for support for issues that don't fall into any specific category.
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: textarea
id: description
attributes:
@@ -21,15 +11,9 @@ body:
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.14.0-ea36ds1)
description: Visible on the System page in the Web UI
validations:
required: true
- type: input
attributes:
label: What browser(s) are you using?
placeholder: Google Chrome 88.0.4324.150
description: >
Provide the full name and don't forget to add the version!
- type: textarea
id: config
attributes:
@@ -39,18 +23,10 @@ body:
validations:
required: true
- type: textarea
id: frigatelogs
id: logs
attributes:
label: Relevant Frigate log output
description: Please copy and paste any relevant Frigate log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: textarea
id: go2rtclogs
attributes:
label: Relevant go2rtc log output
description: Please copy and paste any relevant go2rtc log output. Include logs before and after your exact error when possible. Logs can be viewed via the Frigate UI, Docker, or the go2rtc dashboard. This will be automatically formatted into code, so no need for backticks.
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
@@ -58,7 +34,7 @@ body:
id: ffprobe
attributes:
label: FFprobe output from your camera
description: Run `ffprobe <camera_url>` from within the Frigate container if possible, and provide output below
description: Run `ffprobe <camera_url>` and provide output below
render: shell
validations:
required: true
@@ -68,6 +44,20 @@ body:
label: Frigate stats
description: Output from frigate's /api/stats endpoint
render: json
- type: dropdown
id: os
attributes:
label: Operating system
options:
- HassOS
- Debian
- Other Linux
- Proxmox
- UNRAID
- Windows
- Other
validations:
required: true
- type: dropdown
id: install-method
attributes:
@@ -76,17 +66,6 @@ body:
- HassOS Addon
- Docker Compose
- Docker CLI
- Proxmox via Docker
- Proxmox via TTeck Script
- Windows WSL2
validations:
required: true
- type: textarea
id: docker
attributes:
label: docker-compose file or Docker CLI command
description: This will be automatically formatted into code, so no need for backticks.
render: yaml
validations:
required: true
- type: dropdown
@@ -119,11 +98,6 @@ body:
description: Dahua, hikvision, amcrest, reolink, etc and model number
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots of the Frigate UI's System metrics pages
description: Drag and drop for images is possible in this field
- type: textarea
id: other
attributes:

View File

@@ -1,16 +1,6 @@
title: "[HW Accel Support]: "
labels: ["support", "triage"]
body:
- type: markdown
attributes:
value: |
Use this form to submit a support request for hardware acceleration issues.
Before submitting your support request, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: textarea
id: description
attributes:
@@ -21,7 +11,7 @@ body:
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.14.0-ea36ds1)
description: Visible on the System page in the Web UI
validations:
required: true
- type: textarea
@@ -41,18 +31,10 @@ body:
validations:
required: true
- type: textarea
id: frigatelogs
id: logs
attributes:
label: Relevant Frigate log output
description: Please copy and paste any relevant Frigate log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: textarea
id: go2rtclogs
attributes:
label: Relevant go2rtc log output
description: Please copy and paste any relevant go2rtc log output. Include logs before and after your exact error when possible. Logs can be viewed via the Frigate UI, Docker, or the go2rtc dashboard. This will be automatically formatted into code, so no need for backticks.
label: Relevant log output
description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
@@ -60,10 +42,24 @@ body:
id: ffprobe
attributes:
label: FFprobe output from your camera
description: Run `ffprobe <camera_url>` from within the Frigate container if possible, and provide output below
description: Run `ffprobe <camera_url>` and provide output below
render: shell
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating system
options:
- HassOS
- Debian
- Other Linux
- Proxmox
- UNRAID
- Windows
- Other
validations:
required: true
- type: dropdown
id: install-method
attributes:
@@ -72,22 +68,6 @@ body:
- HassOS Addon
- Docker Compose
- Docker CLI
- Proxmox via Docker
- Proxmox via TTeck Script
- Windows WSL2
validations:
required: true
- type: dropdown
id: object-detector
attributes:
label: Object Detector
options:
- Coral
- OpenVino
- TensorRT
- RKNN
- Other
- CPU (no coral)
validations:
required: true
- type: dropdown
@@ -107,13 +87,6 @@ body:
description: Dahua, hikvision, amcrest, reolink, etc and model number
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots of the Frigate UI's System metrics pages
description: Drag and drop for images is possible in this field. Please post screenshots of at least General and Cameras tabs.
validations:
required: true
- type: textarea
id: other
attributes:

View File

@@ -1,21 +1,9 @@
title: "[Question]: "
labels: ["question"]
body:
- type: markdown
attributes:
value: |
Use this form for questions you have about Frigate.
Before submitting your question, please [search the discussions][discussions], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your question has already been answered by the community.
**If you are looking for support, start a new discussion and use a support category.**
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: textarea
id: description
attributes:
label: "What is your question?"
label: "What is your question:"
validations:
required: true

View File

@@ -1,146 +0,0 @@
title: "[Bug]: "
labels: ["bug", "triage"]
body:
- type: markdown
attributes:
value: |
Use this form to submit a reproducible bug in Frigate or Frigate's UI.
Before submitting your bug report, please [search the discussions][discussions], look at recent open and closed [pull requests][prs], read the [official Frigate documentation][docs], and read the [Frigate FAQ][faq] pinned at the Discussion page to see if your bug has already been fixed by the developers or reported by the community.
**If you are unsure if your issue is actually a bug or not, please submit a support request first.**
[discussions]: https://www.github.com/blakeblackshear/frigate/discussions
[prs]: https://www.github.com/blakeblackshear/frigate/pulls
[docs]: https://docs.frigate.video
[faq]: https://github.com/blakeblackshear/frigate/discussions/12724
- type: checkboxes
attributes:
label: Checklist
description: Please verify that you've followed these steps
options:
- label: I have updated to the latest available Frigate version.
required: true
- label: I have cleared the cache of my browser.
required: true
- label: I have tried a different browser to see if it is related to my browser.
required: true
- label: I have tried reproducing the issue in [incognito mode](https://www.computerworld.com/article/1719851/how-to-go-incognito-in-chrome-firefox-safari-and-edge.html) to rule out problems with any third party extensions or plugins I have installed.
- type: textarea
id: description
attributes:
label: Describe the problem you are having
description: Provide a clear and concise description of what the bug is.
validations:
required: true
- type: textarea
id: steps
attributes:
label: Steps to reproduce
description: |
Please tell us exactly how to reproduce your issue.
Provide clear and concise step by step instructions and add code snippets if needed.
value: |
1.
2.
3.
...
validations:
required: true
- type: input
id: version
attributes:
label: Version
description: Visible on the System page in the Web UI. Please include the full version including the build identifier (eg. 0.14.0-ea36ds1)
validations:
required: true
- type: input
attributes:
label: In which browser(s) are you experiencing the issue with?
placeholder: Google Chrome 88.0.4324.150
description: >
Provide the full name and don't forget to add the version!
- type: textarea
id: config
attributes:
label: Frigate config file
description: This will be automatically formatted into code, so no need for backticks.
render: yaml
validations:
required: true
- type: textarea
id: docker
attributes:
label: docker-compose file or Docker CLI command
description: This will be automatically formatted into code, so no need for backticks.
render: yaml
validations:
required: true
- type: textarea
id: frigatelogs
attributes:
label: Relevant Frigate log output
description: Please copy and paste any relevant Frigate log output. Include logs before and after your exact error when possible. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: textarea
id: go2rtclogs
attributes:
label: Relevant go2rtc log output
description: Please copy and paste any relevant go2rtc log output. Include logs before and after your exact error when possible. Logs can be viewed via the Frigate UI, Docker, or the go2rtc dashboard. This will be automatically formatted into code, so no need for backticks.
render: shell
validations:
required: true
- type: dropdown
id: os
attributes:
label: Operating system
options:
- HassOS
- Debian
- Other Linux
- Proxmox
- UNRAID
- Windows
- Other
validations:
required: true
- type: dropdown
id: install-method
attributes:
label: Install method
options:
- HassOS Addon
- Docker Compose
- Docker CLI
validations:
required: true
- type: dropdown
id: network
attributes:
label: Network connection
options:
- Wired
- Wireless
- Mixed
validations:
required: true
- type: input
id: camera
attributes:
label: Camera make and model
description: Dahua, hikvision, amcrest, reolink, etc and model number
validations:
required: true
- type: textarea
id: screenshots
attributes:
label: Screenshots of the Frigate UI's System metrics pages
description: Drag and drop for images is possible in this field. Please post screenshots of all tabs.
validations:
required: true
- type: textarea
id: other
attributes:
label: Any other information that may be helpful

View File

@@ -5,7 +5,7 @@ inputs:
required: true
outputs:
image-name:
value: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ steps.create-short-sha.outputs.SHORT_SHA }}
value: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ steps.create-short-sha.outputs.SHORT_SHA }}
cache-name:
value: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:cache
runs:

View File

@@ -1,31 +0,0 @@
## Proposed change
<!--
Describe what this pull request does and how it will benefit users of Frigate.
Please describe in detail any considerations, breaking changes, etc. that are
made in this pull request.
-->
## Type of change
- [ ] Dependency upgrade
- [ ] Bugfix (non-breaking change which fixes an issue)
- [ ] New feature
- [ ] Breaking change (fix/feature causing existing functionality to break)
- [ ] Code quality improvements to existing code
## Additional information
- This PR fixes or closes issue: fixes #
- This PR is related to issue:
## Checklist
<!--
Put an `x` in the boxes that apply.
-->
- [ ] The code change is tested and works locally.
- [ ] Local tests pass. **Your PR cannot be merged unless tests pass**
- [ ] There is no commented out code in this PR.
- [ ] The code has been formatted using Ruff (`ruff format frigate`)

View File

@@ -155,64 +155,57 @@ jobs:
tensorrt.tags=${{ steps.setup.outputs.image-name }}-tensorrt
*.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64
*.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64,mode=max
arm64_extra_builds:
runs-on: ubuntu-latest
name: ARM Extra Build
needs:
- arm64_build
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push Rockchip build
uses: docker/bake-action@v3
with:
push: true
targets: rk
files: docker/rockchip/rk.hcl
set: |
rk.tags=${{ steps.setup.outputs.image-name }}-rk
*.cache-from=type=gha
combined_extra_builds:
runs-on: ubuntu-latest
name: Combined Extra Builds
needs:
- amd64_build
- arm64_build
steps:
- name: Check out code
uses: actions/checkout@v4
- name: Set up QEMU and Buildx
id: setup
uses: ./.github/actions/setup
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push Hailo-8l build
uses: docker/bake-action@v4
with:
push: true
targets: h8l
files: docker/hailo8l/h8l.hcl
set: |
h8l.tags=${{ steps.setup.outputs.image-name }}-h8l
*.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-h8l
*.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-h8l,mode=max
- name: AMD/ROCm general build
env:
AMDGPU: gfx
HSA_OVERRIDE: 0
uses: docker/bake-action@v3
with:
push: true
targets: rocm
files: docker/rocm/rocm.hcl
set: |
rocm.tags=${{ steps.setup.outputs.image-name }}-rocm
*.cache-from=type=gha
#- name: AMD/ROCm general build
# env:
# AMDGPU: gfx
# HSA_OVERRIDE: 0
# uses: docker/bake-action@v3
# with:
# push: true
# targets: rocm
# files: docker/rocm/rocm.hcl
# set: |
# rocm.tags=${{ steps.setup.outputs.image-name }}-rocm
# *.cache-from=type=gha
#- name: AMD/ROCm gfx900
# env:
# AMDGPU: gfx900
# HSA_OVERRIDE: 1
# HSA_OVERRIDE_GFX_VERSION: 9.0.0
# uses: docker/bake-action@v3
# with:
# push: true
# targets: rocm
# files: docker/rocm/rocm.hcl
# set: |
# rocm.tags=${{ steps.setup.outputs.image-name }}-rocm-gfx900
# *.cache-from=type=gha
#- name: AMD/ROCm gfx1030
# env:
# AMDGPU: gfx1030
# HSA_OVERRIDE: 1
# HSA_OVERRIDE_GFX_VERSION: 10.3.0
# uses: docker/bake-action@v3
# with:
# push: true
# targets: rocm
# files: docker/rocm/rocm.hcl
# set: |
# rocm.tags=${{ steps.setup.outputs.image-name }}-rocm-gfx1030
# *.cache-from=type=gha
#- name: AMD/ROCm gfx1100
# env:
# AMDGPU: gfx1100
# HSA_OVERRIDE: 1
# HSA_OVERRIDE_GFX_VERSION: 11.0.0
# uses: docker/bake-action@v3
# with:
# push: true
# targets: rocm
# files: docker/rocm/rocm.hcl
# set: |
# rocm.tags=${{ steps.setup.outputs.image-name }}-rocm-gfx1100
# *.cache-from=type=gha
# The majority of users running arm64 are rpi users, so the rpi
# build should be the primary arm64 image
assemble_default_build:
@@ -227,7 +220,7 @@ jobs:
with:
string: ${{ github.repository }}
- name: Log in to the Container registry
uses: docker/login-action@9780b0c442fbb1117ed29e0efdff1e18412f7567
uses: docker/login-action@0d4c9c5ea7693da7b068278f7b52bda2a190a446
with:
registry: ghcr.io
username: ${{ github.actor }}
@@ -236,7 +229,7 @@ jobs:
run: echo "SHORT_SHA=${GITHUB_SHA::7}" >> $GITHUB_ENV
- uses: int128/docker-manifest-create-action@v2
with:
tags: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ env.SHORT_SHA }}
tags: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}
sources: |
ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ env.SHORT_SHA }}-amd64
ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ env.SHORT_SHA }}-rpi
ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}-amd64
ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}-rpi

View File

@@ -16,17 +16,17 @@ jobs:
with:
string: ${{ github.repository }}
- name: Log in to the Container registry
uses: docker/login-action@9780b0c442fbb1117ed29e0efdff1e18412f7567
uses: docker/login-action@0d4c9c5ea7693da7b068278f7b52bda2a190a446
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create tag variables
run: |
BUILD_TYPE=$([[ "${{ github.ref_name }}" =~ ^v[0-9]+\.[0-9]+\.[0-9]+$ ]] && echo "stable" || echo "beta")
echo "BUILD_TYPE=${BUILD_TYPE}" >> $GITHUB_ENV
BRANCH=$([[ "${{ github.ref_name }}" =~ ^v[0-9]+\.[0-9]+\.[0-9]+$ ]] && echo "master" || echo "dev")
echo "BRANCH=${BRANCH}" >> $GITHUB_ENV
echo "BASE=ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}" >> $GITHUB_ENV
echo "BUILD_TAG=${GITHUB_SHA::7}" >> $GITHUB_ENV
echo "BUILD_TAG=${BRANCH}-${GITHUB_SHA::7}" >> $GITHUB_ENV
echo "CLEAN_VERSION=$(echo ${GITHUB_REF##*/} | tr '[:upper:]' '[:lower:]' | sed 's/^[v]//')" >> $GITHUB_ENV
- name: Tag and push the main image
run: |
@@ -39,7 +39,7 @@ jobs:
done
# stable tag
if [[ "${BUILD_TYPE}" == "stable" ]]; then
if [[ "${BRANCH}" == "master" ]]; then
docker run --rm -v $HOME/.docker/config.json:/config.json quay.io/skopeo/stable:latest copy --authfile /config.json --multi-arch all docker://${PULL_TAG} docker://${STABLE_TAG}
for variant in standard-arm64 tensorrt tensorrt-jp4 tensorrt-jp5 rk; do
docker run --rm -v $HOME/.docker/config.json:/config.json quay.io/skopeo/stable:latest copy --authfile /config.json --multi-arch all docker://${PULL_TAG}-${variant} docker://${STABLE_TAG}-${variant}

View File

@@ -25,17 +25,17 @@ jobs:
- name: Print outputs
run: echo ${{ join(steps.stale.outputs.*, ',') }}
# clean_ghcr:
# name: Delete outdated dev container images
# runs-on: ubuntu-latest
# steps:
# - name: Delete old images
# uses: snok/container-retention-policy@v2
# with:
# image-names: dev-*
# cut-off: 60 days ago UTC
# keep-at-least: 5
# account-type: personal
# token: ${{ secrets.GITHUB_TOKEN }}
# token-type: github-token
clean_ghcr:
name: Delete outdated dev container images
runs-on: ubuntu-latest
steps:
- name: Delete old images
uses: snok/container-retention-policy@v2
with:
image-names: dev-*
cut-off: 60 days ago UTC
keep-at-least: 5
account-type: personal
token: ${{ secrets.GITHUB_TOKEN }}
token-type: github-token

3
.gitignore vendored
View File

@@ -1,6 +1,5 @@
.DS_Store
__pycache__
.mypy_cache
*.pyc
*.swp
debug
.vscode/*

5
.vscode/launch.json vendored
View File

@@ -3,9 +3,10 @@
"configurations": [
{
"name": "Python: Launch Frigate",
"type": "debugpy",
"type": "python",
"request": "launch",
"module": "frigate"
"module": "frigate",
"justMyCode": true
}
]
}

View File

@@ -4,4 +4,3 @@
/docker/tensorrt/*jetson* @madsciencetist
/docker/rockchip/ @MarcA711
/docker/rocm/ @harakas
/docker/hailo8l/ @spanner3003

View File

@@ -1,9 +1,11 @@
default_target: local
COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
VERSION = 0.15.0
VERSION = 0.14.0
IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate
GITHUB_REF_NAME ?= $(shell git rev-parse --abbrev-ref HEAD)
CURRENT_UID := $(shell id -u)
CURRENT_GID := $(shell id -g)
BOARDS= #Initialized empty
include docker/*/*.mk
@@ -16,38 +18,25 @@ version:
echo 'VERSION = "$(VERSION)-$(COMMIT_HASH)"' > frigate/version.py
local: version
docker buildx build --target=frigate --file docker/main/Dockerfile . \
--tag frigate:latest \
--load
docker buildx build --target=frigate --tag frigate:latest --load --file docker/main/Dockerfile .
amd64:
docker buildx build --target=frigate --file docker/main/Dockerfile . \
--tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) \
--platform linux/amd64
docker buildx build --platform linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile .
arm64:
docker buildx build --target=frigate --file docker/main/Dockerfile . \
--tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) \
--platform linux/arm64
docker buildx build --platform linux/arm64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile .
build: version amd64 arm64
docker buildx build --target=frigate --file docker/main/Dockerfile . \
--tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) \
--platform linux/arm64/v8,linux/amd64
docker buildx build --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) --file docker/main/Dockerfile .
push: push-boards
docker buildx build --target=frigate --file docker/main/Dockerfile . \
--tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH) \
--platform linux/arm64/v8,linux/amd64 \
--push
docker buildx build --push --platform linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH) --file docker/main/Dockerfile .
run: local
docker run --rm --publish=5000:5000 --volume=${PWD}/config:/config frigate:latest
run_tests: local
docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest \
python3 -u -m unittest
docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest \
python3 -u -m mypy --config-file frigate/mypy.ini frigate
docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest python3 -u -m unittest
docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest python3 -u -m mypy --config-file frigate/mypy.ini frigate
.PHONY: run_tests

View File

@@ -4,7 +4,6 @@ from statistics import mean
import numpy as np
import frigate.util as util
from frigate.config import DetectorTypeEnum
from frigate.object_detection import (
ObjectDetectProcess,
@@ -91,7 +90,7 @@ edgetpu_process_2 = ObjectDetectProcess(
)
for x in range(0, 10):
camera_process = util.Process(
camera_process = mp.Process(
target=start, args=(x, 300, detection_queue, events[str(x)])
)
camera_process.daemon = True

View File

@@ -7,8 +7,7 @@
"*.db",
"node_modules",
"__pycache__",
"dist",
"/audio-labelmap.txt"
"dist"
],
"language": "en",
"dictionaryDefinitions": [

View File

@@ -1,104 +0,0 @@
# syntax=docker/dockerfile:1.6
ARG DEBIAN_FRONTEND=noninteractive
# Build Python wheels
FROM wheels AS h8l-wheels
COPY docker/main/requirements-wheels.txt /requirements-wheels.txt
COPY docker/hailo8l/requirements-wheels-h8l.txt /requirements-wheels-h8l.txt
RUN sed -i "/https:\/\//d" /requirements-wheels.txt
# Create a directory to store the built wheels
RUN mkdir /h8l-wheels
# Build the wheels
RUN pip3 wheel --wheel-dir=/h8l-wheels -c /requirements-wheels.txt -r /requirements-wheels-h8l.txt
# Build HailoRT and create wheel
FROM wheels AS build-hailort
ARG TARGETARCH
SHELL ["/bin/bash", "-c"]
# Install necessary APT packages
RUN apt-get -qq update \
&& apt-get -qq install -y \
apt-transport-https \
gnupg \
wget \
# the key fingerprint can be obtained from https://ftp-master.debian.org/keys.html
&& wget -qO- "https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xA4285295FC7B1A81600062A9605C66F00D6C9793" | \
gpg --dearmor > /usr/share/keyrings/debian-archive-bullseye-stable.gpg \
&& echo "deb [signed-by=/usr/share/keyrings/debian-archive-bullseye-stable.gpg] http://deb.debian.org/debian bullseye main contrib non-free" | \
tee /etc/apt/sources.list.d/debian-bullseye-nonfree.list \
&& apt-get -qq update \
&& apt-get -qq install -y \
python3.9 \
python3.9-dev \
build-essential cmake git \
&& rm -rf /var/lib/apt/lists/*
# Extract Python version and set environment variables
RUN PYTHON_VERSION=$(python3 --version 2>&1 | awk '{print $2}' | cut -d. -f1,2) && \
PYTHON_VERSION_NO_DOT=$(echo $PYTHON_VERSION | sed 's/\.//') && \
echo "PYTHON_VERSION=$PYTHON_VERSION" > /etc/environment && \
echo "PYTHON_VERSION_NO_DOT=$PYTHON_VERSION_NO_DOT" >> /etc/environment
# Clone and build HailoRT
RUN . /etc/environment && \
git clone https://github.com/hailo-ai/hailort.git /opt/hailort && \
cd /opt/hailort && \
git checkout v4.18.0 && \
cmake -H. -Bbuild -DCMAKE_BUILD_TYPE=Release -DHAILO_BUILD_PYBIND=1 -DPYBIND11_PYTHON_VERSION=${PYTHON_VERSION} && \
cmake --build build --config release --target libhailort && \
cmake --build build --config release --target _pyhailort && \
cp build/hailort/libhailort/bindings/python/src/_pyhailort.cpython-${PYTHON_VERSION_NO_DOT}-$(if [ $TARGETARCH == "amd64" ]; then echo 'x86_64'; else echo 'aarch64'; fi )-linux-gnu.so hailort/libhailort/bindings/python/platform/hailo_platform/pyhailort/ && \
cp build/hailort/libhailort/src/libhailort.so hailort/libhailort/bindings/python/platform/hailo_platform/pyhailort/
RUN ls -ahl /opt/hailort/build/hailort/libhailort/src/
RUN ls -ahl /opt/hailort/hailort/libhailort/bindings/python/platform/hailo_platform/pyhailort/
# Remove the existing setup.py if it exists in the target directory
RUN rm -f /opt/hailort/hailort/libhailort/bindings/python/platform/setup.py
# Copy generate_wheel_conf.py and setup.py
COPY docker/hailo8l/pyhailort_build_scripts/generate_wheel_conf.py /opt/hailort/hailort/libhailort/bindings/python/platform/generate_wheel_conf.py
COPY docker/hailo8l/pyhailort_build_scripts/setup.py /opt/hailort/hailort/libhailort/bindings/python/platform/setup.py
# Run the generate_wheel_conf.py script
RUN python3 /opt/hailort/hailort/libhailort/bindings/python/platform/generate_wheel_conf.py
# Create a wheel file using pip3 wheel
RUN cd /opt/hailort/hailort/libhailort/bindings/python/platform && \
python3 setup.py bdist_wheel --dist-dir /hailo-wheels
# Use deps as the base image
FROM deps AS h8l-frigate
# Copy the wheels from the wheels stage
COPY --from=h8l-wheels /h8l-wheels /deps/h8l-wheels
COPY --from=build-hailort /hailo-wheels /deps/hailo-wheels
COPY --from=build-hailort /etc/environment /etc/environment
RUN CC=$(python3 -c "import sysconfig; import shlex; cc = sysconfig.get_config_var('CC'); cc_cmd = shlex.split(cc)[0]; print(cc_cmd[:-4] if cc_cmd.endswith('-gcc') else cc_cmd)") && \
echo "CC=$CC" >> /etc/environment
# Install the wheels
RUN pip3 install -U /deps/h8l-wheels/*.whl
RUN pip3 install -U /deps/hailo-wheels/*.whl
RUN . /etc/environment && \
mv /usr/local/lib/python${PYTHON_VERSION}/dist-packages/hailo_platform/pyhailort/libhailort.so /usr/lib/${CC} && \
cd /usr/lib/${CC}/ && \
ln -s libhailort.so libhailort.so.4.18.0
# Copy base files from the rootfs stage
COPY --from=rootfs / /
# Set environment variables for Hailo SDK
ENV PATH="/opt/hailort/bin:${PATH}"
ENV LD_LIBRARY_PATH="/usr/lib/$(if [ $TARGETARCH == "amd64" ]; then echo 'x86_64'; else echo 'aarch64'; fi )-linux-gnu:${LD_LIBRARY_PATH}"
# Set workdir
WORKDIR /opt/frigate/

View File

@@ -1,27 +0,0 @@
target wheels {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64","linux/amd64"]
target = "wheels"
}
target deps {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64","linux/amd64"]
target = "deps"
}
target rootfs {
dockerfile = "docker/main/Dockerfile"
platforms = ["linux/arm64","linux/amd64"]
target = "rootfs"
}
target h8l {
dockerfile = "docker/hailo8l/Dockerfile"
contexts = {
wheels = "target:wheels"
deps = "target:deps"
rootfs = "target:rootfs"
}
platforms = ["linux/arm64","linux/amd64"]
}

View File

@@ -1,15 +0,0 @@
BOARDS += h8l
local-h8l: version
docker buildx bake --file=docker/hailo8l/h8l.hcl h8l \
--set h8l.tags=frigate:latest-h8l \
--load
build-h8l: version
docker buildx bake --file=docker/hailo8l/h8l.hcl h8l \
--set h8l.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-h8l
push-h8l: build-h8l
docker buildx bake --file=docker/hailo8l/h8l.hcl h8l \
--set h8l.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-h8l \
--push

View File

@@ -1,67 +0,0 @@
import json
import os
import platform
import sys
import sysconfig
def extract_toolchain_info(compiler):
# Remove the "-gcc" or "-g++" suffix if present
if compiler.endswith("-gcc") or compiler.endswith("-g++"):
compiler = compiler.rsplit("-", 1)[0]
# Extract the toolchain and ABI part (e.g., "gnu")
toolchain_parts = compiler.split("-")
abi_conventions = next(
(part for part in toolchain_parts if part in ["gnu", "musl", "eabi", "uclibc"]),
"",
)
return abi_conventions
def generate_wheel_conf():
conf_file_path = os.path.join(
os.path.abspath(os.path.dirname(__file__)), "wheel_conf.json"
)
# Extract current system and Python version information
py_version = f"cp{sys.version_info.major}{sys.version_info.minor}"
arch = platform.machine()
system = platform.system().lower()
libc_version = platform.libc_ver()[1]
# Get the compiler information
compiler = sysconfig.get_config_var("CC")
abi_conventions = extract_toolchain_info(compiler)
# Create the new configuration data
new_conf_data = {
"py_version": py_version,
"arch": arch,
"system": system,
"libc_version": libc_version,
"abi": abi_conventions,
"extension": {
"posix": "so",
"nt": "pyd", # Windows
}[os.name],
}
# If the file exists, load the existing data
if os.path.isfile(conf_file_path):
with open(conf_file_path, "r") as conf_file:
conf_data = json.load(conf_file)
# Update the existing data with the new data
conf_data.update(new_conf_data)
else:
# If the file does not exist, use the new data
conf_data = new_conf_data
# Write the updated data to the file
with open(conf_file_path, "w") as conf_file:
json.dump(conf_data, conf_file, indent=4)
if __name__ == "__main__":
generate_wheel_conf()

View File

@@ -1,111 +0,0 @@
import json
import os
from setuptools import find_packages, setup
from wheel.bdist_wheel import bdist_wheel as orig_bdist_wheel
class NonPurePythonBDistWheel(orig_bdist_wheel):
"""Makes the wheel platform-dependent so it can be based on the _pyhailort architecture"""
def finalize_options(self):
orig_bdist_wheel.finalize_options(self)
self.root_is_pure = False
def _get_hailort_lib_path():
lib_filename = "libhailort.so"
lib_path = os.path.join(
os.path.abspath(os.path.dirname(__file__)),
f"hailo_platform/pyhailort/{lib_filename}",
)
if os.path.exists(lib_path):
print(f"Found libhailort shared library at: {lib_path}")
else:
print(f"Error: libhailort shared library not found at: {lib_path}")
raise FileNotFoundError(f"libhailort shared library not found at: {lib_path}")
return lib_path
def _get_pyhailort_lib_path():
conf_file_path = os.path.join(
os.path.abspath(os.path.dirname(__file__)), "wheel_conf.json"
)
if not os.path.isfile(conf_file_path):
raise FileNotFoundError(f"Configuration file not found: {conf_file_path}")
with open(conf_file_path, "r") as conf_file:
content = json.load(conf_file)
py_version = content["py_version"]
arch = content["arch"]
system = content["system"]
extension = content["extension"]
abi = content["abi"]
# Construct the filename directly
lib_filename = f"_pyhailort.cpython-{py_version.split('cp')[1]}-{arch}-{system}-{abi}.{extension}"
lib_path = os.path.join(
os.path.abspath(os.path.dirname(__file__)),
f"hailo_platform/pyhailort/{lib_filename}",
)
if os.path.exists(lib_path):
print(f"Found _pyhailort shared library at: {lib_path}")
else:
print(f"Error: _pyhailort shared library not found at: {lib_path}")
raise FileNotFoundError(
f"_pyhailort shared library not found at: {lib_path}"
)
return lib_path
def _get_package_paths():
packages = []
pyhailort_lib = _get_pyhailort_lib_path()
hailort_lib = _get_hailort_lib_path()
if pyhailort_lib:
packages.append(pyhailort_lib)
if hailort_lib:
packages.append(hailort_lib)
packages.append(os.path.abspath("hailo_tutorials/notebooks/*"))
packages.append(os.path.abspath("hailo_tutorials/hefs/*"))
return packages
if __name__ == "__main__":
setup(
author="Hailo team",
author_email="contact@hailo.ai",
cmdclass={
"bdist_wheel": NonPurePythonBDistWheel,
},
description="HailoRT",
entry_points={
"console_scripts": [
"hailo=hailo_platform.tools.hailocli.main:main",
]
},
install_requires=[
"argcomplete",
"contextlib2",
"future",
"netaddr",
"netifaces",
"verboselogs",
"numpy==1.23.3",
],
name="hailort",
package_data={
"hailo_platform": _get_package_paths(),
},
packages=find_packages(),
platforms=[
"linux_x86_64",
"linux_aarch64",
"win_amd64",
],
url="https://hailo.ai/",
version="4.17.0",
zip_safe=False,
)

View File

@@ -1,12 +0,0 @@
appdirs==1.4.4
argcomplete==2.0.0
contextlib2==0.6.0.post1
distlib==0.3.6
filelock==3.8.0
future==0.18.2
importlib-metadata==5.1.0
importlib-resources==5.1.2
netaddr==0.8.0
netifaces==0.10.9
verboselogs==1.7
virtualenv==20.17.0

View File

@@ -1,48 +0,0 @@
#!/bin/bash
# Update package list and install dependencies
sudo apt-get update
sudo apt-get install -y build-essential cmake git wget
arch=$(uname -m)
if [[ $arch == "x86_64" ]]; then
sudo apt install -y linux-headers-$(uname -r);
else
sudo apt install -y linux-modules-extra-$(uname -r);
fi
# Clone the HailoRT driver repository
git clone --depth 1 --branch v4.18.0 https://github.com/hailo-ai/hailort-drivers.git
# Build and install the HailoRT driver
cd hailort-drivers/linux/pcie
sudo make all
sudo make install
# Load the Hailo PCI driver
sudo modprobe hailo_pci
if [ $? -ne 0 ]; then
echo "Unable to load hailo_pci module, common reasons for this are:"
echo "- Key was rejected by service: Secure Boot is enabling disallowing install."
echo "- Permissions are not setup correctly."
exit 1
fi
# Download and install the firmware
cd ../../
./download_firmware.sh
# verify the firmware folder is present
if [ ! -d /lib/firmware/hailo ]; then
sudo mkdir /lib/firmware/hailo
fi
sudo mv hailo8_fw.4.17.0.bin /lib/firmware/hailo/hailo8_fw.bin
# Install udev rules
sudo cp ./linux/pcie/51-hailo-udev.rules /etc/udev/rules.d/
sudo udevadm control --reload-rules && sudo udevadm trigger
echo "HailoRT driver installation complete."
echo "reboot your system to load the firmware!"

View File

@@ -30,20 +30,10 @@ RUN --mount=type=tmpfs,target=/tmp --mount=type=tmpfs,target=/var/cache/apt \
--mount=type=cache,target=/root/.ccache \
/deps/build_nginx.sh
FROM wget AS sqlite-vec
ARG DEBIAN_FRONTEND
# Build sqlite_vec from source
COPY docker/main/build_sqlite_vec.sh /deps/build_sqlite_vec.sh
RUN --mount=type=tmpfs,target=/tmp --mount=type=tmpfs,target=/var/cache/apt \
--mount=type=bind,source=docker/main/build_sqlite_vec.sh,target=/deps/build_sqlite_vec.sh \
--mount=type=cache,target=/root/.ccache \
/deps/build_sqlite_vec.sh
FROM scratch AS go2rtc
ARG TARGETARCH
WORKDIR /rootfs/usr/local/go2rtc/bin
ADD --link --chmod=755 "https://github.com/AlexxIT/go2rtc/releases/download/v1.9.2/go2rtc_linux_${TARGETARCH}" go2rtc
ADD --link --chmod=755 "https://github.com/AlexxIT/go2rtc/releases/download/v1.9.4/go2rtc_linux_${TARGETARCH}" go2rtc
FROM wget AS tempio
ARG TARGETARCH
@@ -76,40 +66,6 @@ RUN --mount=type=bind,source=docker/main/build_ov_model.py,target=/build_ov_mode
&& tar -xvf ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz \
&& python3 /build_ov_model.py
####
#
# Coral Compatibility
#
# Builds libusb without udev. Needed for synology and other devices with USB coral
####
# libUSB - No Udev
FROM wget as libusb-build
ARG TARGETARCH
ARG DEBIAN_FRONTEND
ENV CCACHE_DIR /root/.ccache
ENV CCACHE_MAXSIZE 2G
# Build libUSB without udev. Needed for Openvino NCS2 support
WORKDIR /opt
RUN apt-get update && apt-get install -y unzip build-essential automake libtool ccache pkg-config
RUN --mount=type=cache,target=/root/.ccache wget -q https://github.com/libusb/libusb/archive/v1.0.26.zip -O v1.0.26.zip && \
unzip v1.0.26.zip && cd libusb-1.0.26 && \
./bootstrap.sh && \
./configure CC='ccache gcc' CCX='ccache g++' --disable-udev --enable-shared && \
make -j $(nproc --all)
RUN apt-get update && \
apt-get install -y --no-install-recommends libusb-1.0-0-dev && \
rm -rf /var/lib/apt/lists/*
WORKDIR /opt/libusb-1.0.26/libusb
RUN /bin/mkdir -p '/usr/local/lib' && \
/bin/bash ../libtool --mode=install /usr/bin/install -c libusb-1.0.la '/usr/local/lib' && \
/bin/mkdir -p '/usr/local/include/libusb-1.0' && \
/usr/bin/install -c -m 644 libusb.h '/usr/local/include/libusb-1.0' && \
/bin/mkdir -p '/usr/local/lib/pkgconfig' && \
cd /opt/libusb-1.0.26/ && \
/usr/bin/install -c -m 644 libusb-1.0.pc '/usr/local/lib/pkgconfig' && \
ldconfig
FROM wget AS models
# Get model and labels
@@ -122,7 +78,7 @@ COPY --from=ov-converter /models/ssdlite_mobilenet_v2.bin openvino-model/
RUN wget -q https://github.com/openvinotoolkit/open_model_zoo/raw/master/data/dataset_classes/coco_91cl_bkgr.txt -O openvino-model/coco_91cl_bkgr.txt && \
sed -i 's/truck/car/g' openvino-model/coco_91cl_bkgr.txt
# Get Audio Model and labels
RUN wget -qO - https://www.kaggle.com/api/v1/models/google/yamnet/tfLite/classification-tflite/1/download | tar xvz && mv 1.tflite cpu_audio_model.tflite
RUN wget -qO cpu_audio_model.tflite https://tfhub.dev/google/lite-model/yamnet/classification/tflite/1?lite-format=tflite
COPY audio-labelmap.txt .
@@ -158,8 +114,6 @@ RUN apt-get -qq update \
gfortran openexr libatlas-base-dev libssl-dev\
libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev \
libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev \
# sqlite3 dependencies
tclsh \
# scipy dependencies
gcc gfortran libopenblas-dev liblapack-dev && \
rm -rf /var/lib/apt/lists/*
@@ -173,10 +127,6 @@ RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
COPY docker/main/requirements.txt /requirements.txt
RUN pip3 install -r /requirements.txt
# Build pysqlite3 from source
COPY docker/main/build_pysqlite3.sh /build_pysqlite3.sh
RUN /build_pysqlite3.sh
COPY docker/main/requirements-wheels.txt /requirements-wheels.txt
RUN pip3 wheel --wheel-dir=/wheels -r /requirements-wheels.txt
@@ -184,9 +134,7 @@ RUN pip3 wheel --wheel-dir=/wheels -r /requirements-wheels.txt
# Collect deps in a single layer
FROM scratch AS deps-rootfs
COPY --from=nginx /usr/local/nginx/ /usr/local/nginx/
COPY --from=sqlite-vec /usr/local/lib/ /usr/local/lib/
COPY --from=go2rtc /rootfs/ /
COPY --from=libusb-build /usr/local/lib /usr/local/lib
COPY --from=tempio /rootfs/ /
COPY --from=s6-overlay /rootfs/ /
COPY --from=models /rootfs/ /
@@ -205,14 +153,7 @@ ARG APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn
ENV NVIDIA_VISIBLE_DEVICES=all
ENV NVIDIA_DRIVER_CAPABILITIES="compute,video,utility"
# Disable tokenizer parallelism warning
# https://stackoverflow.com/questions/62691279/how-to-disable-tokenizers-parallelism-true-false-warning/72926996#72926996
ENV TOKENIZERS_PARALLELISM=true
# https://github.com/huggingface/transformers/issues/27214
ENV TRANSFORMERS_NO_ADVISORY_WARNINGS=1
ENV PATH="/usr/local/go2rtc/bin:/usr/local/tempio/bin:/usr/local/nginx/sbin:${PATH}"
ENV LIBAVFORMAT_VERSION_MAJOR=60
ENV PATH="/usr/lib/btbn-ffmpeg/bin:/usr/local/go2rtc/bin:/usr/local/tempio/bin:/usr/local/nginx/sbin:${PATH}"
# Install dependencies
RUN --mount=type=bind,source=docker/main/install_deps.sh,target=/deps/install_deps.sh \
@@ -224,8 +165,6 @@ RUN --mount=type=bind,from=wheels,source=/wheels,target=/deps/wheels \
COPY --from=deps-rootfs / /
RUN ldconfig
EXPOSE 5000
EXPOSE 8554
EXPOSE 8555/tcp 8555/udp
@@ -238,7 +177,7 @@ ENV S6_CMD_WAIT_FOR_SERVICES_MAXTIME=0
ENTRYPOINT ["/init"]
CMD []
HEALTHCHECK --start-period=300s --start-interval=5s --interval=15s --timeout=5s --retries=3 \
HEALTHCHECK --start-period=120s --start-interval=5s --interval=15s --timeout=5s --retries=3 \
CMD curl --fail --silent --show-error http://127.0.0.1:5000/api/version || exit 1
# Frigate deps with Node.js and NPM for devcontainer

View File

@@ -1,35 +0,0 @@
#!/bin/bash
set -euxo pipefail
SQLITE3_VERSION="96c92aba00c8375bc32fafcdf12429c58bd8aabfcadab6683e35bbb9cdebf19e" # 3.46.0
PYSQLITE3_VERSION="0.5.3"
# Fetch the source code for the latest release of Sqlite.
if [[ ! -d "sqlite" ]]; then
wget https://www.sqlite.org/src/tarball/sqlite.tar.gz?r=${SQLITE3_VERSION} -O sqlite.tar.gz
tar xzf sqlite.tar.gz
cd sqlite/
LIBS="-lm" ./configure --disable-tcl --enable-tempstore=always
make sqlite3.c
cd ../
rm sqlite.tar.gz
fi
# Grab the pysqlite3 source code.
if [[ ! -d "./pysqlite3" ]]; then
git clone https://github.com/coleifer/pysqlite3.git
fi
cd pysqlite3/
git checkout ${PYSQLITE3_VERSION}
# Copy the sqlite3 source amalgamation into the pysqlite3 directory so we can
# create a self-contained extension module.
cp "../sqlite/sqlite3.c" ./
cp "../sqlite/sqlite3.h" ./
# Create the wheel and put it in the /wheels dir.
sed -i "s|name='pysqlite3-binary'|name=PACKAGE_NAME|g" setup.py
python3 setup.py build_static
pip3 wheel . -w /wheels

View File

@@ -1,31 +0,0 @@
#!/bin/bash
set -euxo pipefail
SQLITE_VEC_VERSION="0.1.3"
cp /etc/apt/sources.list /etc/apt/sources.list.d/sources-src.list
sed -i 's|deb http|deb-src http|g' /etc/apt/sources.list.d/sources-src.list
apt-get update
apt-get -yqq build-dep sqlite3 gettext git
mkdir /tmp/sqlite_vec
# Grab the sqlite_vec source code.
wget -nv https://github.com/asg017/sqlite-vec/archive/refs/tags/v${SQLITE_VEC_VERSION}.tar.gz
tar -zxf v${SQLITE_VEC_VERSION}.tar.gz -C /tmp/sqlite_vec
cd /tmp/sqlite_vec/sqlite-vec-${SQLITE_VEC_VERSION}
mkdir -p vendor
wget -O sqlite-amalgamation.zip https://www.sqlite.org/2024/sqlite-amalgamation-3450300.zip
unzip sqlite-amalgamation.zip
mv sqlite-amalgamation-3450300/* vendor/
rmdir sqlite-amalgamation-3450300
rm sqlite-amalgamation.zip
# build loadable module
make loadable
# install it
cp dist/vec0.* /usr/local/lib

View File

@@ -8,13 +8,11 @@ apt-get -qq install --no-install-recommends -y \
apt-transport-https \
gnupg \
wget \
lbzip2 \
procps vainfo \
unzip locales tzdata libxml2 xz-utils \
python3.9 \
python3-pip \
curl \
lsof \
jq \
nethogs
@@ -41,68 +39,39 @@ apt-get -qq install --no-install-recommends --no-install-suggests -y \
# btbn-ffmpeg -> amd64
if [[ "${TARGETARCH}" == "amd64" ]]; then
mkdir -p /usr/lib/ffmpeg/5.0
mkdir -p /usr/lib/ffmpeg/7.0
wget -qO btbn-ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux64-gpl-5.1.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/5.0 --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/5.0/doc /usr/lib/ffmpeg/5.0/bin/ffplay
wget -qO btbn-ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linux64-gpl-7.0.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/7.0 --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/7.0/doc /usr/lib/ffmpeg/7.0/bin/ffplay
mkdir -p /usr/lib/btbn-ffmpeg
wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux64-gpl-5.1.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/btbn-ffmpeg --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/btbn-ffmpeg/doc /usr/lib/btbn-ffmpeg/bin/ffplay
fi
# ffmpeg -> arm64
if [[ "${TARGETARCH}" == "arm64" ]]; then
mkdir -p /usr/lib/ffmpeg/5.0
mkdir -p /usr/lib/ffmpeg/7.0
wget -qO btbn-ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linuxarm64-gpl-5.1.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/5.0 --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/5.0/doc /usr/lib/ffmpeg/5.0/bin/ffplay
wget -qO btbn-ffmpeg.tar.xz "https://github.com/NickM-27/FFmpeg-Builds/releases/download/autobuild-2024-09-19-12-51/ffmpeg-n7.0.2-18-g3e6cec1286-linuxarm64-gpl-7.0.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/ffmpeg/7.0 --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/ffmpeg/7.0/doc /usr/lib/ffmpeg/7.0/bin/ffplay
mkdir -p /usr/lib/btbn-ffmpeg
wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linuxarm64-gpl-5.1.tar.xz"
tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/btbn-ffmpeg --strip-components 1
rm -rf btbn-ffmpeg.tar.xz /usr/lib/btbn-ffmpeg/doc /usr/lib/btbn-ffmpeg/bin/ffplay
fi
# arch specific packages
if [[ "${TARGETARCH}" == "amd64" ]]; then
# use debian bookworm for amd / intel-i965 driver packages
# use debian bookworm for hwaccel packages
echo 'deb https://deb.debian.org/debian bookworm main contrib non-free' >/etc/apt/sources.list.d/debian-bookworm.list
apt-get -qq update
apt-get -qq install --no-install-recommends --no-install-suggests -y \
i965-va-driver intel-gpu-tools onevpl-tools \
libva-drm2 \
mesa-va-drivers radeontop
intel-opencl-icd \
mesa-va-drivers radeontop libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 intel-gpu-tools
# something about this dependency requires it to be installed in a separate call rather than in the line above
apt-get -qq install --no-install-recommends --no-install-suggests -y \
i965-va-driver-shaders
# intel packages use zst compression so we need to update dpkg
apt-get install -y dpkg
rm -f /etc/apt/sources.list.d/debian-bookworm.list
# use intel apt intel packages
wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | tee /etc/apt/sources.list.d/intel-gpu-jammy.list
apt-get -qq update
apt-get -qq install --no-install-recommends --no-install-suggests -y \
intel-opencl-icd intel-level-zero-gpu intel-media-va-driver-non-free \
libmfx1 libmfxgen1 libvpl2
rm -f /usr/share/keyrings/intel-graphics.gpg
rm -f /etc/apt/sources.list.d/intel-gpu-jammy.list
fi
if [[ "${TARGETARCH}" == "arm64" ]]; then
apt-get -qq install --no-install-recommends --no-install-suggests -y \
libva-drm2 mesa-va-drivers radeontop
libva-drm2 mesa-va-drivers
fi
# install vulkan
apt-get -qq install --no-install-recommends --no-install-suggests -y \
libvulkan1 mesa-vulkan-drivers
apt-get purge gnupg apt-transport-https xz-utils -y
apt-get clean autoclean -y
apt-get autoremove --purge -y

View File

@@ -1,13 +1,10 @@
click == 8.1.*
# FastAPI
starlette-context == 0.3.6
fastapi == 0.115.0
uvicorn == 0.30.*
slowapi == 0.1.9
Flask == 3.0.*
Flask_Limiter == 3.7.*
imutils == 0.5.*
joserfc == 1.0.*
pathvalidate == 3.2.*
joserfc == 0.11.*
markupsafe == 2.1.*
matplotlib == 3.8.*
mypy == 1.6.1
numpy == 1.26.*
onvif_zeep == 0.2.12
@@ -15,14 +12,16 @@ opencv-python-headless == 4.9.0.*
paho-mqtt == 2.1.*
pandas == 2.2.*
peewee == 3.17.*
peewee_migrate == 1.13.*
peewee_migrate == 1.12.*
psutil == 5.9.*
pydantic == 2.8.*
pydantic == 2.7.*
git+https://github.com/fbcotter/py3nvml#egg=py3nvml
PyYAML == 6.0.*
pytz == 2024.1
pyzmq == 26.2.*
pyzmq == 26.0.*
ruamel.yaml == 0.18.*
tzlocal == 5.2
types-PyYAML == 6.0.*
requests == 2.32.*
types-requests == 2.32.*
scipy == 1.13.*
@@ -30,16 +29,5 @@ norfair == 2.2.*
setproctitle == 1.3.*
ws4py == 0.5.*
unidecode == 1.3.*
# OpenVino & ONNX
openvino == 2024.3.*
onnxruntime-openvino == 1.19.* ; platform_machine == 'x86_64'
onnxruntime == 1.19.* ; platform_machine == 'aarch64'
# Embeddings
transformers == 4.45.*
# Generative AI
google-generativeai == 0.8.*
ollama == 0.3.*
openai == 1.51.*
# push notifications
py-vapid == 1.9.*
pywebpush == 2.0.*
onnxruntime == 1.18.*
openvino == 2024.1.*

View File

@@ -1,2 +1,2 @@
scikit-build == 0.17.*
scikit-build == 0.18.*
nvidia-pyindex

View File

@@ -34,7 +34,7 @@ do
;;
esac
liveprint=`echo | openssl s_client -showcerts -connect 127.0.0.1:8971 2>&1 | openssl x509 -fingerprint 2>&1 | grep -i fingerprint || echo 'failed'`
liveprint=`echo | openssl s_client -showcerts -connect 127.0.0.1:8080 2>&1 | openssl x509 -fingerprint 2>&1 | grep -i fingerprint || echo 'failed'`
case "$liveprint" in
*Fingerprint*)

View File

@@ -16,8 +16,8 @@ function migrate_db_path() {
if [[ -f "${config_file_yaml}" ]]; then
config_file="${config_file_yaml}"
elif [[ ! -f "${config_file}" ]]; then
# Frigate will create the config file on startup
return 0
echo "[ERROR] Frigate config file not found"
return 1
fi
unset config_file_yaml
@@ -44,6 +44,8 @@ function migrate_db_path() {
echo "[INFO] Preparing Frigate..."
migrate_db_path
export LIBAVFORMAT_VERSION_MAJOR=$(ffmpeg -version | grep -Po 'libavformat\W+\K\d+')
echo "[INFO] Starting Frigate..."
cd /opt/frigate || echo "[ERROR] Failed to change working directory to /opt/frigate"

View File

@@ -43,6 +43,8 @@ function get_ip_and_port_from_supervisor() {
export FRIGATE_GO2RTC_WEBRTC_CANDIDATE_INTERNAL="${ip_address}:${webrtc_port}"
}
export LIBAVFORMAT_VERSION_MAJOR=$(ffmpeg -version | grep -Po 'libavformat\W+\K\d+')
if [[ -f "/dev/shm/go2rtc.yaml" ]]; then
echo "[INFO] Removing stale config from last run..."
rm /dev/shm/go2rtc.yaml

View File

@@ -38,7 +38,7 @@ function get_cpus() {
fi
local cpus
if [ "${period}" != "0" ] && [ -n "${quota}" ] && [ -n "${period}" ]; then
if [ -n "${quota}" ] && [ -n "${period}" ]; then
cpus=$((quota / period))
if [ "$cpus" -eq 0 ]; then
cpus=1

View File

@@ -2,32 +2,28 @@
import json
import os
import shutil
import sys
from pathlib import Path
from ruamel.yaml import YAML
import yaml
sys.path.insert(0, "/opt/frigate")
from frigate.const import (
BIRDSEYE_PIPE,
DEFAULT_FFMPEG_VERSION,
INCLUDED_FFMPEG_VERSIONS,
from frigate.const import BIRDSEYE_PIPE # noqa: E402
from frigate.ffmpeg_presets import ( # noqa: E402
parse_preset_hardware_acceleration_encode,
)
from frigate.ffmpeg_presets import parse_preset_hardware_acceleration_encode
sys.path.remove("/opt/frigate")
yaml = YAML()
FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
# read docker secret files as env vars too
if os.path.isdir("/run/secrets"):
for secret_file in os.listdir("/run/secrets"):
if secret_file.startswith("FRIGATE_"):
FRIGATE_ENV_VARS[secret_file] = (
Path(os.path.join("/run/secrets", secret_file)).read_text().strip()
)
FRIGATE_ENV_VARS[secret_file] = Path(
os.path.join("/run/secrets", secret_file)
).read_text()
config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
@@ -41,7 +37,7 @@ try:
raw_config = f.read()
if config_file.endswith((".yaml", ".yml")):
config: dict[str, any] = yaml.load(raw_config)
config: dict[str, any] = yaml.safe_load(raw_config)
elif config_file.endswith(".json"):
config: dict[str, any] = json.loads(raw_config)
except FileNotFoundError:
@@ -109,32 +105,16 @@ else:
**FRIGATE_ENV_VARS
)
# ensure ffmpeg path is set correctly
path = config.get("ffmpeg", {}).get("path", "default")
if path == "default":
if shutil.which("ffmpeg") is None:
ffmpeg_path = f"/usr/lib/ffmpeg/{DEFAULT_FFMPEG_VERSION}/bin/ffmpeg"
else:
ffmpeg_path = "ffmpeg"
elif path in INCLUDED_FFMPEG_VERSIONS:
ffmpeg_path = f"/usr/lib/ffmpeg/{path}/bin/ffmpeg"
else:
ffmpeg_path = f"{path}/bin/ffmpeg"
if go2rtc_config.get("ffmpeg") is None:
go2rtc_config["ffmpeg"] = {"bin": ffmpeg_path}
elif go2rtc_config["ffmpeg"].get("bin") is None:
go2rtc_config["ffmpeg"]["bin"] = ffmpeg_path
# need to replace ffmpeg command when using ffmpeg4
if int(os.environ.get("LIBAVFORMAT_VERSION_MAJOR", "59") or "59") < 59:
if go2rtc_config["ffmpeg"].get("rtsp") is None:
if int(os.environ["LIBAVFORMAT_VERSION_MAJOR"]) < 59:
if go2rtc_config.get("ffmpeg") is None:
go2rtc_config["ffmpeg"] = {
"rtsp": "-fflags nobuffer -flags low_delay -stimeout 5000000 -user_agent go2rtc/ffmpeg -rtsp_transport tcp -i {input}"
}
elif go2rtc_config["ffmpeg"].get("rtsp") is None:
go2rtc_config["ffmpeg"]["rtsp"] = (
"-fflags nobuffer -flags low_delay -stimeout 5000000 -user_agent go2rtc/ffmpeg -rtsp_transport tcp -i {input}"
)
else:
if go2rtc_config.get("ffmpeg") is None:
go2rtc_config["ffmpeg"] = {"path": ""}
for name in go2rtc_config.get("streams", {}):
stream = go2rtc_config["streams"][name]
@@ -165,7 +145,7 @@ if config.get("birdseye", {}).get("restream", False):
birdseye: dict[str, any] = config.get("birdseye")
input = f"-f rawvideo -pix_fmt yuv420p -video_size {birdseye.get('width', 1280)}x{birdseye.get('height', 720)} -r 10 -i {BIRDSEYE_PIPE}"
ffmpeg_cmd = f"exec:{parse_preset_hardware_acceleration_encode(ffmpeg_path, config.get('ffmpeg', {}).get('hwaccel_args'), input, '-rtsp_transport tcp -f rtsp {output}')}"
ffmpeg_cmd = f"exec:{parse_preset_hardware_acceleration_encode(config.get('ffmpeg', {}).get('hwaccel_args'), input, '-rtsp_transport tcp -f rtsp {output}')}"
if go2rtc_config.get("streams"):
go2rtc_config["streams"]["birdseye"] = ffmpeg_cmd

View File

@@ -59,6 +59,9 @@ http {
include go2rtc_upstream.conf;
server {
# intended for internal traffic, not protected by auth
listen [::]:5000 ipv6only=off;
include listen.conf;
# vod settings
@@ -104,8 +107,6 @@ http {
add_header Cache-Control "no-store";
expires off;
keepalive_disable safari;
}
location /stream/ {
@@ -226,7 +227,7 @@ http {
location ~* /api/.*\.(jpg|jpeg|png|webp|gif)$ {
include auth_request.conf;
rewrite ^/api/(.*)$ /$1 break;
rewrite ^/api/(.*)$ $1 break;
proxy_pass http://frigate_api;
include proxy.conf;
}

View File

@@ -3,9 +3,7 @@
import json
import os
from ruamel.yaml import YAML
yaml = YAML()
import yaml
config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
@@ -19,7 +17,7 @@ try:
raw_config = f.read()
if config_file.endswith((".yaml", ".yml")):
config: dict[str, any] = yaml.load(raw_config)
config: dict[str, any] = yaml.safe_load(raw_config)
elif config_file.endswith(".json"):
config: dict[str, any] = json.loads(raw_config)
except FileNotFoundError:

View File

@@ -1,12 +1,9 @@
# intended for internal traffic, not protected by auth
listen 5000;
{{ if not .enabled }}
# intended for external traffic, protected by auth
listen 8971;
listen [::]:8080 ipv6only=off;
{{ else }}
# intended for external traffic, protected by auth
listen 8971 ssl;
listen [::]:8080 ipv6only=off ssl;
ssl_certificate /etc/letsencrypt/live/frigate/fullchain.pem;
ssl_certificate_key /etc/letsencrypt/live/frigate/privkey.pem;

View File

@@ -22,6 +22,5 @@ ADD https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/librknnrt
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffmpeg
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffprobe
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffmpeg /usr/lib/ffmpeg/6.0/bin/
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffprobe /usr/lib/ffmpeg/6.0/bin/
ENV PATH="/usr/lib/ffmpeg/6.0/bin/:${PATH}"
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffmpeg /usr/lib/btbn-ffmpeg/bin/
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-5/ffprobe /usr/lib/btbn-ffmpeg/bin/

View File

@@ -1,15 +1,10 @@
BOARDS += rk
local-rk: version
docker buildx bake --file=docker/rockchip/rk.hcl rk \
--set rk.tags=frigate:latest-rk \
--load
docker buildx bake --load --file=docker/rockchip/rk.hcl --set rk.tags=frigate:latest-rk rk
build-rk: version
docker buildx bake --file=docker/rockchip/rk.hcl rk \
--set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk
docker buildx bake --file=docker/rockchip/rk.hcl --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk rk
push-rk: build-rk
docker buildx bake --file=docker/rockchip/rk.hcl rk \
--set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk \
--push
docker buildx bake --push --file=docker/rockchip/rk.hcl --set rk.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rk rk

View File

@@ -23,11 +23,11 @@ COPY docker/rocm/rocm-pin-600 /etc/apt/preferences.d/
RUN apt-get update
RUN apt-get -y install --no-install-recommends migraphx hipfft roctracer
RUN apt-get -y install --no-install-recommends migraphx
RUN apt-get -y install --no-install-recommends migraphx-dev
RUN mkdir -p /opt/rocm-dist/opt/rocm-$ROCM/lib
RUN cd /opt/rocm-$ROCM/lib && cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* libroctracer*.so* librocfft*.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/
RUN cd /opt/rocm-$ROCM/lib && cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/
RUN cd /opt/rocm-dist/opt/ && ln -s rocm-$ROCM rocm
RUN mkdir -p /opt/rocm-dist/etc/ld.so.conf.d/
@@ -69,11 +69,7 @@ RUN apt-get -y install libnuma1
WORKDIR /opt/frigate/
COPY --from=rootfs / /
COPY docker/rocm/requirements-wheels-rocm.txt /requirements.txt
RUN python3 -m pip install --upgrade pip \
&& pip3 uninstall -y onnxruntime-openvino \
&& pip3 install -r /requirements.txt
COPY docker/rocm/rootfs/ /
#######################################################################
FROM scratch AS rocm-dist
@@ -83,7 +79,6 @@ ARG AMDGPU
COPY --from=rocm /opt/rocm-$ROCM/bin/rocminfo /opt/rocm-$ROCM/bin/migraphx-driver /opt/rocm-$ROCM/bin/
COPY --from=rocm /opt/rocm-$ROCM/share/miopen/db/*$AMDGPU* /opt/rocm-$ROCM/share/miopen/db/
COPY --from=rocm /opt/rocm-$ROCM/share/miopen/db/*gfx908* /opt/rocm-$ROCM/share/miopen/db/
COPY --from=rocm /opt/rocm-$ROCM/lib/rocblas/library/*$AMDGPU* /opt/rocm-$ROCM/lib/rocblas/library/
COPY --from=rocm /opt/rocm-dist/ /
COPY --from=debian-build /opt/rocm/lib/migraphx.cpython-39-x86_64-linux-gnu.so /opt/rocm-$ROCM/lib/
@@ -106,3 +101,6 @@ ENV HSA_OVERRIDE_GFX_VERSION=$HSA_OVERRIDE_GFX_VERSION
#######################################################################
FROM rocm-prelim-hsa-override$HSA_OVERRIDE as rocm-deps
# Request yolov8 download at startup
ENV DOWNLOAD_YOLOV8=1

View File

@@ -1 +0,0 @@
onnxruntime-rocm @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v1.0.0/onnxruntime_rocm-1.17.3-cp39-cp39-linux_x86_64.whl

View File

@@ -4,50 +4,14 @@ BOARDS += rocm
ROCM_CHIPSETS:=gfx900:9.0.0 gfx1030:10.3.0 gfx1100:11.0.0
local-rocm: version
$(foreach chipset,$(ROCM_CHIPSETS), \
AMDGPU=$(word 1,$(subst :, ,$(chipset))) \
HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) \
HSA_OVERRIDE=1 \
docker buildx bake --file=docker/rocm/rocm.hcl rocm \
--set rocm.tags=frigate:latest-rocm-$(word 1,$(subst :, ,$(chipset))) \
--load \
&&) true
unset HSA_OVERRIDE_GFX_VERSION && \
HSA_OVERRIDE=0 \
AMDGPU=gfx \
docker buildx bake --file=docker/rocm/rocm.hcl rocm \
--set rocm.tags=frigate:latest-rocm \
--load
$(foreach chipset,$(ROCM_CHIPSETS),AMDGPU=$(word 1,$(subst :, ,$(chipset))) HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) HSA_OVERRIDE=1 docker buildx bake --load --file=docker/rocm/rocm.hcl --set rocm.tags=frigate:latest-rocm-$(word 1,$(subst :, ,$(chipset))) rocm;)
unset HSA_OVERRIDE_GFX_VERSION && HSA_OVERRIDE=0 AMDGPU=gfx docker buildx bake --load --file=docker/rocm/rocm.hcl --set rocm.tags=frigate:latest-rocm rocm
build-rocm: version
$(foreach chipset,$(ROCM_CHIPSETS), \
AMDGPU=$(word 1,$(subst :, ,$(chipset))) \
HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) \
HSA_OVERRIDE=1 \
docker buildx bake --file=docker/rocm/rocm.hcl rocm \
--set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) \
&&) true
unset HSA_OVERRIDE_GFX_VERSION && \
HSA_OVERRIDE=0 \
AMDGPU=gfx \
docker buildx bake --file=docker/rocm/rocm.hcl rocm \
--set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm
$(foreach chipset,$(ROCM_CHIPSETS),AMDGPU=$(word 1,$(subst :, ,$(chipset))) HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) HSA_OVERRIDE=1 docker buildx bake --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) rocm;)
unset HSA_OVERRIDE_GFX_VERSION && HSA_OVERRIDE=0 AMDGPU=gfx docker buildx bake --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm rocm
push-rocm: build-rocm
$(foreach chipset,$(ROCM_CHIPSETS), \
AMDGPU=$(word 1,$(subst :, ,$(chipset))) \
HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) \
HSA_OVERRIDE=1 \
docker buildx bake --file=docker/rocm/rocm.hcl rocm \
--set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) \
--push \
&&) true
$(foreach chipset,$(ROCM_CHIPSETS),AMDGPU=$(word 1,$(subst :, ,$(chipset))) HSA_OVERRIDE_GFX_VERSION=$(word 2,$(subst :, ,$(chipset))) HSA_OVERRIDE=1 docker buildx bake --push --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm-$(chipset) rocm;)
unset HSA_OVERRIDE_GFX_VERSION && HSA_OVERRIDE=0 AMDGPU=gfx docker buildx bake --push --file=docker/rocm/rocm.hcl --set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm rocm
unset HSA_OVERRIDE_GFX_VERSION && \
HSA_OVERRIDE=0 \
AMDGPU=gfx \
docker buildx bake --file=docker/rocm/rocm.hcl rocm \
--set rocm.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rocm \
--push

View File

@@ -0,0 +1,20 @@
#!/command/with-contenv bash
# shellcheck shell=bash
# Compile YoloV8 ONNX files into ROCm MIGraphX files
OVERRIDE=$(cd /opt/frigate && python3 -c 'import frigate.detectors.plugins.rocm as rocm; print(rocm.auto_override_gfx_version())')
if ! test -z "$OVERRIDE"; then
echo "Using HSA_OVERRIDE_GFX_VERSION=${OVERRIDE}"
export HSA_OVERRIDE_GFX_VERSION=$OVERRIDE
fi
for onnx in /config/model_cache/yolov8/*.onnx
do
mxr="${onnx%.onnx}.mxr"
if ! test -f $mxr; then
echo "processing $onnx into $mxr"
/opt/rocm/bin/migraphx-driver compile $onnx --optimize --gpu --enable-offload-copy --binary -o $mxr
fi
done

View File

@@ -0,0 +1 @@
oneshot

View File

@@ -0,0 +1 @@
/etc/s6-overlay/s6-rc.d/compile-rocm-models/run

View File

@@ -12,7 +12,5 @@ RUN rm -rf /usr/lib/btbn-ffmpeg/
RUN --mount=type=bind,source=docker/rpi/install_deps.sh,target=/deps/install_deps.sh \
/deps/install_deps.sh
ENV LIBAVFORMAT_VERSION_MAJOR=58
WORKDIR /opt/frigate/
COPY --from=rootfs / /

View File

@@ -1,15 +1,10 @@
BOARDS += rpi
local-rpi: version
docker buildx bake --file=docker/rpi/rpi.hcl rpi \
--set rpi.tags=frigate:latest-rpi \
--load
docker buildx bake --load --file=docker/rpi/rpi.hcl --set rpi.tags=frigate:latest-rpi rpi
build-rpi: version
docker buildx bake --file=docker/rpi/rpi.hcl rpi \
--set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi
docker buildx bake --file=docker/rpi/rpi.hcl --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi rpi
push-rpi: build-rpi
docker buildx bake --file=docker/rpi/rpi.hcl rpi \
--set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi \
--push
docker buildx bake --push --file=docker/rpi/rpi.hcl --set rpi.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-rpi rpi

View File

@@ -12,28 +12,12 @@ ARG TARGETARCH
COPY docker/tensorrt/requirements-amd64.txt /requirements-tensorrt.txt
RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r /requirements-tensorrt.txt
# Build CuDNN
FROM wget AS cudnn-deps
ARG COMPUTE_LEVEL
RUN apt-get update \
&& apt-get install -y git build-essential
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/cuda-keyring_1.1-1_all.deb \
&& dpkg -i cuda-keyring_1.1-1_all.deb \
&& apt-get update \
&& apt-get -y install cuda-toolkit \
&& rm -rf /var/lib/apt/lists/*
FROM tensorrt-base AS frigate-tensorrt
ENV TRT_VER=8.5.3
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
pip3 install -U /deps/trt-wheels/*.whl && \
ldconfig
COPY --from=cudnn-deps /usr/local/cuda-12.6 /usr/local/cuda
ENV LD_LIBRARY_PATH=/usr/local/lib/python3.9/dist-packages/tensorrt:/usr/local/cuda/lib64:/usr/local/lib/python3.9/dist-packages/nvidia/cufft/lib
WORKDIR /opt/frigate/
COPY --from=rootfs / /
@@ -42,7 +26,6 @@ FROM devcontainer AS devcontainer-trt
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
COPY --from=trt-deps /usr/local/src/tensorrt_demos /usr/local/src/tensorrt_demos
COPY --from=cudnn-deps /usr/local/cuda-12.6 /usr/local/cuda
COPY docker/tensorrt/detector/rootfs/ /
COPY --from=trt-deps /usr/local/lib/libyolo_layer.so /usr/local/lib/libyolo_layer.so
RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \

View File

@@ -8,7 +8,5 @@ nvidia-cuda-runtime-cu12 == 12.1.*; platform_machine == 'x86_64'
nvidia-cuda-runtime-cu11 == 11.8.*; platform_machine == 'x86_64'
nvidia-cublas-cu11 == 11.11.3.6; platform_machine == 'x86_64'
nvidia-cudnn-cu11 == 8.6.0.*; platform_machine == 'x86_64'
nvidia-cufft-cu11==10.*; platform_machine == 'x86_64'
onnx==1.14.0; platform_machine == 'x86_64'
onnxruntime-gpu==1.17.*; platform_machine == 'x86_64'
protobuf==3.20.3; platform_machine == 'x86_64'

View File

@@ -7,35 +7,20 @@ JETPACK4_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK4_BASE) SLIM_BASE=$(JETPACK4_BAS
JETPACK5_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK5_BASE) SLIM_BASE=$(JETPACK5_BASE) TRT_BASE=$(JETPACK5_BASE)
local-trt: version
$(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=frigate:latest-tensorrt \
--load
$(X86_DGPU_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt tensorrt
local-trt-jp4: version
$(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=frigate:latest-tensorrt-jp4 \
--load
$(JETPACK4_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt-jp4 tensorrt
local-trt-jp5: version
$(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=frigate:latest-tensorrt-jp5 \
--load
$(JETPACK5_ARGS) docker buildx bake --load --file=docker/tensorrt/trt.hcl --set tensorrt.tags=frigate:latest-tensorrt-jp5 tensorrt
build-trt:
$(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt
$(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4
$(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5
$(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt tensorrt
$(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 tensorrt
$(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 tensorrt
push-trt: build-trt
$(X86_DGPU_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt \
--push
$(JETPACK4_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 \
--push
$(JETPACK5_ARGS) docker buildx bake --file=docker/tensorrt/trt.hcl tensorrt \
--set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 \
--push
$(X86_DGPU_ARGS) docker buildx bake --push --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt tensorrt
$(JETPACK4_ARGS) docker buildx bake --push --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp4 tensorrt
$(JETPACK5_ARGS) docker buildx bake --push --file=docker/tensorrt/trt.hcl --set tensorrt.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt-jp5 tensorrt

View File

@@ -1,10 +1,5 @@
# Website
This website is built using [Docusaurus 3.5](https://docusaurus.io/docs), a modern static website generator.
This website is built using [Docusaurus 2](https://v2.docusaurus.io/), a modern static website generator.
For installation and contributing instructions, please follow the [Contributing Docs](https://docs.frigate.video/development/contributing).
# Development
1. Run `npm i` to install dependencies
2. Run `npm run start` to start the website

View File

@@ -41,7 +41,7 @@ environment_vars:
### `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.
Event 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.
@@ -80,14 +80,6 @@ model:
input_pixel_format: "bgr"
```
#### `labelmap`
:::warning
If the labelmap is customized then the labels used for alerts will need to be adjusted as well. See [alert labels](../configuration/review.md#restricting-alerts-to-specific-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.
```yaml
@@ -114,65 +106,19 @@ Some labels have special handling and modifications can disable functionality.
:::
## Network Configuration
## Custom ffmpeg build
Changes to Frigate's internal network configuration can be made by bind mounting nginx.conf into the container. For example:
```yaml
services:
frigate:
container_name: frigate
...
volumes:
...
- /path/to/your/nginx.conf:/usr/local/nginx/conf/nginx.conf
```
### Enabling IPv6
IPv6 is disabled by default, to enable IPv6 listen.gotmpl needs to be bind mounted with IPv6 enabled. For example:
```
{{ if not .enabled }}
# intended for external traffic, protected by auth
listen 8971;
{{ else }}
# intended for external traffic, protected by auth
listen 8971 ssl;
# intended for internal traffic, not protected by auth
listen 5000;
```
becomes
```
{{ if not .enabled }}
# intended for external traffic, protected by auth
listen [::]:8971 ipv6only=off;
{{ else }}
# intended for external traffic, protected by auth
listen [::]:8971 ipv6only=off ssl;
# intended for internal traffic, not protected by auth
listen [::]:5000 ipv6only=off;
```
## Custom Dependencies
### Custom ffmpeg build
Included with Frigate is a build of ffmpeg that works for the vast majority of users. However, there exists some hardware setups which have incompatibilities with the included build. In this case, statically built ffmpeg binary can be downloaded to /config and used.
Included with Frigate is a build of ffmpeg that works for the vast majority of users. However, there exists some hardware setups which have incompatibilities with the included build. In this case, a docker volume mapping can be used to overwrite the included ffmpeg build with an ffmpeg build that works for your specific hardware setup.
To do this:
1. Download your ffmpeg build and uncompress to the Frigate config folder.
1. Download your ffmpeg build and uncompress to a folder on the host (let's use `/home/appdata/frigate/custom-ffmpeg` for this example).
2. Update your docker-compose or docker CLI to include `'/home/appdata/frigate/custom-ffmpeg':'/usr/lib/btbn-ffmpeg':'ro'` in the volume mappings.
3. Restart Frigate and the custom version will be used if the mapping was done correctly.
NOTE: The folder that is set for the config needs to be the folder that contains `/bin`. So if the full structure is `/home/appdata/frigate/custom-ffmpeg/bin/ffmpeg` then the `ffmpeg -> path` field should be `/config/custom-ffmpeg/bin`.
NOTE: The folder that is mapped from the host needs to be the folder that contains `/bin`. So if the full structure is `/home/appdata/frigate/custom-ffmpeg/bin/ffmpeg` then `/home/appdata/frigate/custom-ffmpeg` needs to be mapped to `/usr/lib/btbn-ffmpeg`.
### Custom go2rtc version
## Custom go2rtc version
Frigate currently includes go2rtc v1.9.4, there may be certain cases where you want to run a different version of go2rtc.
@@ -183,7 +129,7 @@ To do this:
3. Give `go2rtc` execute permission.
4. Restart Frigate and the custom version will be used, you can verify by checking go2rtc logs.
## Validating your config.yml file updates
## Validating your config.yaml file updates
When frigate starts up, it checks whether your config file is valid, and if it is not, the process exits. To minimize interruptions when updating your config, you have three options -- you can edit the config via the WebUI which has built in validation, use the config API, or you can validate on the command line using the frigate docker container.
@@ -211,5 +157,5 @@ docker run \
--entrypoint python3 \
ghcr.io/blakeblackshear/frigate:stable \
-u -m frigate \
--validate-config
--validate_config
```

View File

@@ -13,7 +13,7 @@ The following ports are available to access the Frigate web UI.
| Port | Description |
| ------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `8971` | Authenticated UI and API. Reverse proxies should use this port. |
| `8080` | Authenticated UI and API. 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 and do not support authentication. |
## Onboarding
@@ -26,7 +26,7 @@ In the event that you are locked out of your instance, you can tell Frigate to r
## Login failure rate limiting
In order to limit the risk of brute force attacks, rate limiting is available for login failures. This is implemented with SlowApi, and the string notation for valid values is available in [the documentation](https://limits.readthedocs.io/en/stable/quickstart.html#examples).
In order to limit the risk of brute force attacks, rate limiting is available for login failures. This is implemented with Flask-Limiter, and the string notation for valid values is available in [the documentation](https://flask-limiter.readthedocs.io/en/stable/configuration.html#rate-limit-string-notation).
For example, `1/second;5/minute;20/hour` will rate limit the login endpoint when failures occur more than:

View File

@@ -9,12 +9,6 @@ This page makes use of presets of FFmpeg args. For more information on presets,
:::
:::note
Many cameras support encoding options which greatly affect the live view experience, see the [Live view](/configuration/live) page for more info.
:::
## MJPEG Cameras
Note that mjpeg cameras require encoding the video into h264 for recording, and restream roles. This will use significantly more CPU than if the cameras supported h264 feeds directly. It is recommended to use the restream role to create an h264 restream and then use that as the source for ffmpeg.
@@ -193,4 +187,4 @@ ffmpeg:
### TP-Link VIGI Cameras
TP-Link VIGI cameras need some adjustments to the main stream settings on the camera itself to avoid issues. The stream needs to be configured as `H264` with `Smart Coding` set to `off`. Without these settings you may have problems when trying to watch recorded footage. For example Firefox will stop playback after a few seconds and show the following error message: `The media playback was aborted due to a corruption problem or because the media used features your browser did not support.`.
TP-Link VIGI cameras need some adjustments to the main stream settings on the camera itself to avoid issues. The stream needs to be configured as `H264` with `Smart Coding` set to `off`. Without these settings you may have problems when trying to watch recorded events. For example Firefox will stop playback after a few seconds and show the following error message: `The media playback was aborted due to a corruption problem or because the media used features your browser did not support.`.

View File

@@ -7,7 +7,7 @@ title: Camera Configuration
Several inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create recordings from a higher resolution stream, or vice versa.
A camera is enabled by default but can be temporarily disabled by using `enabled: False`. Existing tracked objects and recordings can still be accessed. Live streams, recording and detecting are not working. Camera specific configurations will be used.
A camera is enabled by default but can be temporarily disabled by using `enabled: False`. Existing events and recordings can still be accessed. Live streams, recording and detecting are not working. Camera specific configurations will be used.
Each role can only be assigned to one input per camera. The options for roles are as follows:
@@ -46,14 +46,6 @@ cameras:
side: ...
```
:::note
If you only define one stream in your `inputs` and do not assign a `detect` role to it, Frigate will automatically assign it the `detect` role. Frigate will always decode a stream to support motion detection, Birdseye, the API image endpoints, and other features, even if you have disabled object detection with `enabled: False` in your config's `detect` section.
If you plan to use Frigate for recording only, it is still recommended to define a `detect` role for a low resolution stream to minimize resource usage from the required stream decoding.
:::
For camera model specific settings check the [camera specific](camera_specific.md) infos.
## Setting up camera PTZ controls
@@ -79,12 +71,6 @@ cameras:
If the ONVIF connection is successful, PTZ controls will be available in the camera's WebUI.
:::tip
If your ONVIF camera does not require authentication credentials, you may still need to specify an empty string for `user` and `password`, eg: `user: ""` and `password: ""`.
:::
An ONVIF-capable camera that supports relative movement within the field of view (FOV) can also be configured to automatically track moving objects and keep them in the center of the frame. For autotracking setup, see the [autotracking](autotracking.md) docs.
## ONVIF PTZ camera recommendations
@@ -92,27 +78,21 @@ An ONVIF-capable camera that supports relative movement within the field of view
This list of working and non-working PTZ cameras is based on user feedback.
| Brand or specific camera | PTZ Controls | Autotracking | Notes |
| ---------------------------- | :----------: | :----------: | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| ------------------------ | :----------: | :----------: | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| Amcrest | ✅ | ✅ | ⛔️ Generally, Amcrest should work, but some older models (like the common IP2M-841) don't support autotracking |
| Amcrest ASH21 | | ❌ | ONVIF service port: 80 |
| Amcrest IP4M-S2112EW-AI | ✅ | ❌ | FOV relative movement not supported. |
| Amcrest IP5M-1190EW | ✅ | ❌ | ONVIF Port: 80. FOV relative movement not supported. |
| Amcrest ASH21 | | ❌ | No ONVIF support |
| Ctronics PTZ | ✅ | ❌ | |
| Dahua | ✅ | ✅ | |
| Dahua DH-SD2A500HB | ✅ | ❌ | |
| Foscam R5 | ✅ | ❌ | |
| Hanwha XNP-6550RH | ✅ | ❌ | |
| Hikvision | ✅ | ❌ | Incomplete ONVIF support (MoveStatus won't update even on latest firmware) - reported with HWP-N4215IH-DE and DS-2DE3304W-DE, but likely others |
| Hikvision DS-2DE3A404IWG-E/W | ✅ | ✅ | |
| Reolink 511WA | ✅ | ❌ | Zoom only |
| Reolink E1 Pro | ✅ | ❌ | |
| Reolink E1 Zoom | ✅ | ❌ | |
| Reolink RLC-823A 16x | ✅ | ❌ | |
| Speco O8P32X | ✅ | ❌ | |
| Sunba 405-D20X | ✅ | ❌ | |
| Tapo | ✅ | ❌ | Many models supported, ONVIF Service Port: 2020 |
| Uniview IPC672LR-AX4DUPK | ✅ | ❌ | Firmware says FOV relative movement is supported, but camera doesn't actually move when sending ONVIF commands |
| Uniview IPC6612SR-X33-VG | ✅ | ✅ | Leave `calibrate_on_startup` as `False`. A user has reported that zooming with `absolute` is working. |
| Vikylin PTZ-2804X-I2 | ❌ | ❌ | Incomplete ONVIF support |
## Setting up camera groups
@@ -131,6 +111,6 @@ camera_groups:
cameras:
- driveway_cam
- garage_cam
icon: LuCar
icon: car
order: 0
```

View File

@@ -1,189 +0,0 @@
---
id: genai
title: Generative AI
---
Generative AI can be used to automatically generate descriptive text based on the thumbnails of your tracked objects. This helps with [Semantic Search](/configuration/semantic_search) in Frigate to provide more context about your tracked objects.
Semantic Search must be enabled to use Generative AI. Descriptions are accessed via the _Explore_ view in the Frigate UI by clicking on a tracked object's thumbnail.
## Configuration
Generative AI can be enabled for all cameras or only for specific cameras. There are currently 3 providers available to integrate with Frigate.
If the provider you choose requires an API key, you may either directly paste it in your configuration, or store it in an environment variable prefixed with `FRIGATE_`.
```yaml
genai:
enabled: True
provider: gemini
api_key: "{FRIGATE_GEMINI_API_KEY}"
model: gemini-1.5-flash
cameras:
front_camera: ...
indoor_camera:
genai: # <- disable GenAI for your indoor camera
enabled: False
```
## Ollama
[Ollama](https://ollama.com/) allows you to self-host large language models and keep everything running locally. It provides a nice API over [llama.cpp](https://github.com/ggerganov/llama.cpp). It is highly recommended to host this server on a machine with an Nvidia graphics card, or on a Apple silicon Mac for best performance. CPU inference is not recommended.
Most of the 7b parameter 4-bit vision models will fit inside 8GB of VRAM. There is also a [docker container](https://hub.docker.com/r/ollama/ollama) available.
Parallel requests also come with some caveats. See the [Ollama documentation](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-does-ollama-handle-concurrent-requests).
### Supported Models
You must use a vision capable model with Frigate. Current model variants can be found [in their model library](https://ollama.com/library). At the time of writing, this includes `llava`, `llava-llama3`, `llava-phi3`, and `moondream`. Note that Frigate will not automatically download the model you specify in your config, you must download the model to your local instance of Ollama first.
:::note
You should have at least 8 GB of RAM available (or VRAM if running on GPU) to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
:::
### Configuration
```yaml
genai:
enabled: True
provider: ollama
base_url: http://localhost:11434
model: llava
```
## Google Gemini
Google Gemini has a free tier allowing [15 queries per minute](https://ai.google.dev/pricing) to the API, which is more than sufficient for standard Frigate usage.
### Supported Models
You must use a vision capable model with Frigate. Current model variants can be found [in their documentation](https://ai.google.dev/gemini-api/docs/models/gemini). At the time of writing, this includes `gemini-1.5-pro` and `gemini-1.5-flash`.
### Get API Key
To start using Gemini, you must first get an API key from [Google AI Studio](https://aistudio.google.com).
1. Accept the Terms of Service
2. Click "Get API Key" from the right hand navigation
3. Click "Create API key in new project"
4. Copy the API key for use in your config
### Configuration
```yaml
genai:
enabled: True
provider: gemini
api_key: "{FRIGATE_GEMINI_API_KEY}"
model: gemini-1.5-flash
```
## OpenAI
OpenAI does not have a free tier for their API. With the release of gpt-4o, pricing has been reduced and each generation should cost fractions of a cent if you choose to go this route.
### Supported Models
You must use a vision capable model with Frigate. Current model variants can be found [in their documentation](https://platform.openai.com/docs/models). At the time of writing, this includes `gpt-4o` and `gpt-4-turbo`.
### Get API Key
To start using OpenAI, you must first [create an API key](https://platform.openai.com/api-keys) and [configure billing](https://platform.openai.com/settings/organization/billing/overview).
### Configuration
```yaml
genai:
enabled: True
provider: openai
api_key: "{FRIGATE_OPENAI_API_KEY}"
model: gpt-4o
```
## Azure OpenAI
Microsoft offers several vision models through Azure OpenAI. A subscription is required.
### Supported Models
You must use a vision capable model with Frigate. Current model variants can be found [in their documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models). At the time of writing, this includes `gpt-4o` and `gpt-4-turbo`.
### Create Resource and Get API Key
To start using Azure OpenAI, you must first [create a resource](https://learn.microsoft.com/azure/cognitive-services/openai/how-to/create-resource?pivots=web-portal#create-a-resource). You'll need your API key and resource URL, which must include the `api-version` parameter (see the example below). The model field is not required in your configuration as the model is part of the deployment name you chose when deploying the resource.
### Configuration
```yaml
genai:
enabled: True
provider: azure_openai
base_url: https://example-endpoint.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2023-03-15-preview
api_key: "{FRIGATE_OPENAI_API_KEY}"
```
## Usage and Best Practices
Frigate's thumbnail search excels at identifying specific details about tracked objects for example, using an "image caption" approach to find a "person wearing a yellow vest," "a white dog running across the lawn," or "a red car on a residential street." To enhance this further, Frigates default prompts are designed to ask your AI provider about the intent behind the object's actions, rather than just describing its appearance.
While generating simple descriptions of detected objects is useful, understanding intent provides a deeper layer of insight. Instead of just recognizing "what" is in a scene, Frigates default prompts aim to infer "why" it might be there or "what" it could do next. Descriptions tell you whats happening, but intent gives context. For instance, a person walking toward a door might seem like a visitor, but if theyre moving quickly after hours, you can infer a potential break-in attempt. Detecting a person loitering near a door at night can trigger an alert sooner than simply noting "a person standing by the door," helping you respond based on the situations context.
## Custom Prompts
Frigate sends multiple frames from the tracked object along with a prompt to your Generative AI provider asking it to generate a description. The default prompt is as follows:
```
Analyze the sequence of images containing the {label}. Focus on the likely intent or behavior of the {label} based on its actions and movement, rather than describing its appearance or the surroundings. Consider what the {label} is doing, why, and what it might do next.
```
:::tip
Prompts can use variable replacements like `{label}`, `{sub_label}`, and `{camera}` to substitute information from the tracked object as part of the prompt.
:::
You are also able to define custom prompts in your configuration.
```yaml
genai:
enabled: True
provider: ollama
base_url: http://localhost:11434
model: llava
prompt: "Analyze the {label} in these images from the {camera} security camera. Focus on the actions, behavior, and potential intent of the {label}, rather than just describing its appearance."
object_prompts:
person: "Examine the main person in these images. What are they doing and what might their actions suggest about their intent (e.g., approaching a door, leaving an area, standing still)? Do not describe the surroundings or static details."
car: "Observe the primary vehicle in these images. Focus on its movement, direction, or purpose (e.g., parking, approaching, circling). If it's a delivery vehicle, mention the company."
```
Prompts can also be overriden at the camera level to provide a more detailed prompt to the model about your specific camera, if you desire. By default, descriptions will be generated for all tracked objects and all zones. But you can also optionally specify `objects` and `required_zones` to only generate descriptions for certain tracked objects or zones.
Optionally, you can generate the description using a snapshot (if enabled) by setting `use_snapshot` to `True`. By default, this is set to `False`, which sends the thumbnails collected over the object's lifetime to the model. Using a snapshot provides the AI with a higher-resolution image (typically downscaled by the AI itself), but the trade-off is that only a single image is used, which might limit the model's ability to determine object movement or direction.
```yaml
cameras:
front_door:
genai:
use_snapshot: True
prompt: "Analyze the {label} in these images from the {camera} security camera at the front door. Focus on the actions and potential intent of the {label}."
object_prompts:
person: "Examine the person in these images. What are they doing, and how might their actions suggest their purpose (e.g., delivering something, approaching, leaving)? If they are carrying or interacting with a package, include details about its source or destination."
cat: "Observe the cat in these images. Focus on its movement and intent (e.g., wandering, hunting, interacting with objects). If the cat is near the flower pots or engaging in any specific actions, mention it."
objects:
- person
- cat
required_zones:
- steps
```
### Experiment with prompts
Many providers also have a public facing chat interface for their models. Download a couple of different thumbnails or snapshots from Frigate and try new things in the playground to get descriptions to your liking before updating the prompt in Frigate.
- OpenAI - [ChatGPT](https://chatgpt.com)
- Gemini - [Google AI Studio](https://aistudio.google.com)
- Ollama - [Open WebUI](https://docs.openwebui.com/)

View File

@@ -65,37 +65,24 @@ Or map in all the `/dev/video*` devices.
## Intel-based CPUs
:::info
**Recommended hwaccel Preset**
| CPU Generation | Intel Driver | Recommended Preset | Notes |
| -------------- | ------------ | ------------------ | ----------------------------------- |
| gen1 - gen7 | i965 | preset-vaapi | qsv is not supported |
| gen8 - gen12 | iHD | preset-vaapi | preset-intel-qsv-* can also be used |
| gen13+ | iHD / Xe | preset-intel-qsv-* | |
| Intel Arc GPU | iHD / Xe | preset-intel-qsv-* | |
:::
:::note
The default driver is `iHD`. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `frigate.yaml` for HA OS users](advanced.md#environment_vars).
See [The Intel Docs](https://www.intel.com/content/www/us/en/support/articles/000005505/processors.html) to figure out what generation your CPU is.
:::
### Via VAAPI
VAAPI supports automatic profile selection so it will work automatically with both H.264 and H.265 streams.
VAAPI supports automatic profile selection so it will work automatically with both H.264 and H.265 streams. VAAPI is recommended for all generations of Intel-based CPUs.
```yaml
ffmpeg:
hwaccel_args: preset-vaapi
```
### Via Quicksync
:::note
With some of the processors, like the J4125, the default driver `iHD` doesn't seem to work correctly for hardware acceleration. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `frigate.yaml` for HA OS users](advanced.md#environment_vars).
:::
### Via Quicksync (>=10th Generation only)
If VAAPI does not work for you, you can try QSV if your processor supports it. QSV must be set specifically based on the video encoding of the stream.
#### H.264 streams
@@ -383,7 +370,7 @@ Make sure to follow the [Rockchip specific installation instructions](/frigate/i
### Configuration
Add one of the following FFmpeg presets to your `config.yml` to enable hardware video processing:
Add one of the following FFmpeg presets to your `config.yaml` to enable hardware video processing:
```yaml
# if you try to decode a h264 encoded stream

View File

@@ -56,11 +56,6 @@ go2rtc:
password: "{FRIGATE_GO2RTC_RTSP_PASSWORD}"
```
```yaml
genai:
api_key: "{FRIGATE_GENAI_API_KEY}"
```
## Common configuration examples
Here are some common starter configuration examples. Refer to the [reference config](./reference.md) for detailed information about all the config values.
@@ -72,7 +67,7 @@ Here are some common starter configuration examples. Refer to the [reference con
- Hardware acceleration for decoding video
- USB Coral detector
- Save all video with any detectable motion for 7 days regardless of whether any objects were detected or not
- Continue to keep all video if it qualified as an alert or detection for 30 days
- Continue to keep all video if it was during any event for 30 days
- Save snapshots for 30 days
- Motion mask for the camera timestamp
@@ -95,12 +90,10 @@ record:
retain:
days: 7
mode: motion
alerts:
events:
retain:
days: 30
detections:
retain:
days: 30
default: 30
mode: motion
snapshots:
enabled: True
@@ -130,7 +123,7 @@ cameras:
- VAAPI hardware acceleration for decoding video
- USB Coral detector
- Save all video with any detectable motion for 7 days regardless of whether any objects were detected or not
- Continue to keep all video if it qualified as an alert or detection for 30 days
- Continue to keep all video if it was during any event for 30 days
- Save snapshots for 30 days
- Motion mask for the camera timestamp
@@ -151,12 +144,10 @@ record:
retain:
days: 7
mode: motion
alerts:
events:
retain:
days: 30
detections:
retain:
days: 30
default: 30
mode: motion
snapshots:
enabled: True
@@ -186,7 +177,7 @@ cameras:
- VAAPI hardware acceleration for decoding video
- OpenVino detector
- Save all video with any detectable motion for 7 days regardless of whether any objects were detected or not
- Continue to keep all video if it qualified as an alert or detection for 30 days
- Continue to keep all video if it was during any event for 30 days
- Save snapshots for 30 days
- Motion mask for the camera timestamp
@@ -218,12 +209,10 @@ record:
retain:
days: 7
mode: motion
alerts:
events:
retain:
days: 30
detections:
retain:
days: 30
default: 30
mode: motion
snapshots:
enabled: True

View File

@@ -7,25 +7,13 @@ Frigate intelligently displays your camera streams on the Live view dashboard. Y
## Live View technologies
Frigate intelligently uses three different streaming technologies to display your camera streams on the dashboard and the single camera view, switching between available modes based on network bandwidth, player errors, or required features like two-way talk. The highest quality and fluency of the Live view requires the bundled `go2rtc` to be configured as shown in the [step by step guide](/guides/configuring_go2rtc).
Frigate intelligently uses three different streaming technologies to display your camera streams. The highest quality and fluency of the Live view requires the bundled `go2rtc` to be configured as shown in the [step by step guide](/guides/configuring_go2rtc).
The jsmpeg live view will use more browser and client GPU resources. Using go2rtc is highly recommended and will provide a superior experience.
| Source | Frame Rate | Resolution | Audio | Requires go2rtc | Notes |
| ------ | ------------------------------------- | ---------- | ---------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| jsmpeg | same as `detect -> fps`, capped at 10 | 720p | no | no | Resolution is configurable, but go2rtc is recommended if you want higher resolutions and better frame rates. jsmpeg is Frigate's default without go2rtc configured. |
| mse | native | native | yes (depends on audio codec) | yes | iPhone requires iOS 17.1+, Firefox is h.264 only. This is Frigate's default when go2rtc is configured. |
| webrtc | native | native | yes (depends on audio codec) | yes | Requires extra configuration, doesn't support h.265. Frigate attempts to use WebRTC when MSE fails or when using a camera's two-way talk feature. |
### Camera Settings Recommendations
If you are using go2rtc, you should adjust the following settings in your camera's firmware for the best experience with Live view:
- Video codec: **H.264** - provides the most compatible video codec with all Live view technologies and browsers. Avoid any kind of "smart codec" or "+" codec like _H.264+_ or _H.265+_. as these non-standard codecs remove keyframes (see below).
- Audio codec: **AAC** - provides the most compatible audio codec with all Live view technologies and browsers that support audio.
- I-frame interval (sometimes called the keyframe interval, the interframe space, or the GOP length): match your camera's frame rate, or choose "1x" (for interframe space on Reolink cameras). For example, if your stream outputs 20fps, your i-frame interval should be 20 (or 1x on Reolink). Values higher than the frame rate will cause the stream to take longer to begin playback. See [this page](https://gardinal.net/understanding-the-keyframe-interval/) for more on keyframes.
The default video and audio codec on your camera may not always be compatible with your browser, which is why setting them to H.264 and AAC is recommended. See the [go2rtc docs](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#codecs-madness) for codec support information.
| Source | Latency | Frame Rate | Resolution | Audio | Requires go2rtc | Other Limitations |
| ------ | ------- | ------------------------------------- | -------------- | ---------------------------- | --------------- | ------------------------------------------------ |
| jsmpeg | low | same as `detect -> fps`, capped at 10 | same as detect | no | no | none |
| mse | low | native | native | yes (depends on audio codec) | yes | iPhone requires iOS 17.1+, Firefox is h.264 only |
| webrtc | lowest | native | native | yes (depends on audio codec) | yes | requires extra config, doesn't support h.265 |
### Audio Support
@@ -42,15 +30,6 @@ go2rtc:
- "ffmpeg:http_cam#audio=opus" # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
```
If your camera does not have audio and you are having problems with Live view, you should have go2rtc send video only:
```yaml
go2rtc:
streams:
no_audio_camera:
- ffmpeg:rtsp://192.168.1.5:554/live0#video=copy
```
### Setting Stream For Live UI
There may be some cameras that you would prefer to use the sub stream for live view, but the main stream for recording. This can be done via `live -> stream_name`.

View File

@@ -78,7 +78,7 @@ It is, but the definition of "unnecessary" varies. I want to ignore areas of mot
> For me, giving my masks ANY padding results in a lot of people detection I'm not interested in. I live in the city and catch a lot of the sidewalk on my camera. People walk by my front door all the time and the margin between the sidewalk and actually walking onto my stoop is very thin, so I basically have everything but the exact contours of my stoop masked out. This results in very tidy detections but this info keeps throwing me off. Am I just overthinking it?
This is what `required_zones` are for. You should define a zone (remember this is evaluated based on the bottom center of the bounding box) and make it required to save snapshots and clips (previously events in 0.9.0 to 0.13.0 and review items in 0.14.0 and later). You can also use this in your conditions for a notification.
This is what `required_zones` are for. You should define a zone (remember this is evaluated based on the bottom center of the bounding box) and make it required to save snapshots and clips (now events in 0.9.0). You can also use this in your conditions for a notification.
> Maybe my specific situation just warrants this. I've just been having a hard time understanding the relevance of this information - it seems to be that it's exactly what would be expected when "masking out" an area of ANY image.

View File

@@ -13,11 +13,11 @@ Once motion is detected, it tries to group up nearby areas of motion together in
The default motion settings should work well for the majority of cameras, however there are cases where tuning motion detection can lead to better and more optimal results. Each camera has its own environment with different variables that affect motion, this means that the same motion settings will not fit all of your cameras.
Before tuning motion it is important to understand the goal. In an optimal configuration, motion from people and cars would be detected, but not grass moving, lighting changes, timestamps, etc. If your motion detection is too sensitive, you will experience higher CPU loads and greater false positives from the increased rate of object detection. If it is not sensitive enough, you will miss objects that you want to track.
Before tuning motion it is important to understand the goal. In an optimal configuration, motion from people and cars would be detected, but not grass moving, lighting changes, timestamps, etc. If your motion detection is too sensitive, you will experience higher CPU loads and greater false positives from the increased rate of object detection. If it is not sensitive enough, you will miss events.
## Create Motion Masks
First, mask areas with regular motion not caused by the objects you want to detect. The best way to find candidates for motion masks is by watching the debug stream with motion boxes enabled. Good use cases for motion masks are timestamps or tree limbs and large bushes that regularly move due to wind. When possible, avoid creating motion masks that would block motion detection for objects you want to track **even if they are in locations where you don't want alerts or detections**. Motion masks should not be used to avoid detecting objects in specific areas. More details can be found [in the masks docs.](/configuration/masks.md).
First, mask areas with regular motion not caused by the objects you want to detect. The best way to find candidates for motion masks is by watching the debug stream with motion boxes enabled. Good use cases for motion masks are timestamps or tree limbs and large bushes that regularly move due to wind. When possible, avoid creating motion masks that would block motion detection for objects you want to track **even if they are in locations where you don't want events**. Motion masks should not be used to avoid detecting objects in specific areas. More details can be found [in the masks docs.](/configuration/masks.md).
## Prepare For Testing
@@ -29,7 +29,7 @@ Now that things are set up, find a time to tune that represents normal circumsta
:::note
Remember that motion detection is just used to determine when object detection should be used. You should aim to have motion detection sensitive enough that you won't miss objects you want to detect with object detection. The goal is to prevent object detection from running constantly for every small pixel change in the image. Windy days are still going to result in lots of motion being detected.
Remember that motion detection is just used to determine when object detection should be used. You should aim to have motion detection sensitive enough that you won't miss events from objects you want to detect with object detection. The goal is to prevent object detection from running constantly for every small pixel change in the image. Windy days are still going to result in lots of motion being detected.
:::
@@ -94,7 +94,7 @@ motion:
:::tip
Some cameras like doorbell cameras may have missed detections when someone walks directly in front of the camera and the lightning_threshold causes motion detection to be re-calibrated. In this case, it may be desirable to increase the `lightning_threshold` to ensure these objects are not missed.
Some cameras like doorbell cameras may have missed detections when someone walks directly in front of the camera and the lightning_threshold causes motion detection to be re-calibrated. In this case, it may be desirable to increase the `lightning_threshold` to ensure these events are not missed.
:::

View File

@@ -1,42 +0,0 @@
---
id: notifications
title: Notifications
---
# Notifications
Frigate offers native notifications using the [WebPush Protocol](https://web.dev/articles/push-notifications-web-push-protocol) which uses the [VAPID spec](https://tools.ietf.org/html/draft-thomson-webpush-vapid) to deliver notifications to web apps using encryption.
## Setting up Notifications
In order to use notifications the following requirements must be met:
- Frigate must be accessed via a secure https connection
- A supported browser must be used. Currently Chrome, Firefox, and Safari are known to be supported.
- In order for notifications to be usable externally, Frigate must be accessible externally
### Configuration
To configure notifications, go to the Frigate WebUI -> Settings -> Notifications and enable, then fill out the fields and save.
### Registration
Once notifications are enabled, press the `Register for Notifications` button on all devices that you would like to receive notifications on. This will register the background worker. After this Frigate must be restarted and then notifications will begin to be sent.
## Supported Notifications
Currently notifications are only supported for review alerts. More notifications will be supported in the future.
:::note
Currently, only Chrome supports images in notifications. Safari and Firefox will only show a title and message in the notification.
:::
## Reduce Notification Latency
Different platforms handle notifications differently, some settings changes may be required to get optimal notification delivery.
### Android
Most Android phones have battery optimization settings. To get reliable Notification delivery the browser (Chrome, Firefox) should have battery optimizations disabled. If Frigate is running as a PWA then the Frigate app should have battery optimizations disabled as well.

View File

@@ -3,39 +3,37 @@ id: object_detectors
title: Object Detectors
---
# Supported Hardware
# Officially Supported Detectors
:::info
Frigate provides the following builtin detector types: `cpu`, `edgetpu`, `openvino`, `tensorrt`, and `rknn`. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
Frigate supports multiple different detectors that work on different types of hardware:
## CPU Detector (not recommended)
**Most Hardware**
- [Coral EdgeTPU](#edge-tpu-detector): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices.
- [Hailo](#hailo-8l): The Hailo8 AI Acceleration module is available in m.2 format with a HAT for RPi devices, offering a wide range of compatibility with devices.
The CPU detector type runs a TensorFlow Lite model utilizing the CPU without hardware acceleration. It is recommended to use a hardware accelerated detector type instead for better performance. To configure a CPU based detector, set the `"type"` attribute to `"cpu"`.
**AMD**
- [ROCm](#amdrocm-gpu-detector): ROCm can run on AMD Discrete GPUs to provide efficient object detection.
- [ONNX](#onnx): ROCm will automatically be detected and used as a detector in the `-rocm` Frigate image when a supported ONNX model is configured.
:::tip
**Intel**
- [OpenVino](#openvino-detector): OpenVino can run on Intel Arc GPUs, Intel integrated GPUs, and Intel CPUs to provide efficient object detection.
- [ONNX](#onnx): OpenVINO will automatically be detected and used as a detector in the default Frigate image when a supported ONNX model is configured.
**Nvidia**
- [TensortRT](#nvidia-tensorrt-detector): TensorRT can run on Nvidia GPUs, using one of many default models.
- [ONNX](#onnx): TensorRT will automatically be detected and used as a detector in the `-tensorrt` Frigate image when a supported ONNX model is configured.
**Rockchip**
- [RKNN](#rockchip-platform): RKNN models can run on Rockchip devices with included NPUs.
**For Testing**
- [CPU Detector (not recommended for actual use](#cpu-detector-not-recommended): Use a CPU to run tflite model, this is not recommended and in most cases OpenVINO can be used in CPU mode with better results.
If you do not have GPU or Edge TPU hardware, using the [OpenVINO Detector](#openvino-detector) is often more efficient than using the CPU detector.
:::
# Officially Supported Detectors
The number of threads used by the interpreter can be specified using the `"num_threads"` attribute, and defaults to `3.`
Frigate provides the following builtin detector types: `cpu`, `edgetpu`, `hailo8l`, `onnx`, `openvino`, `rknn`, `rocm`, and `tensorrt`. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
A TensorFlow Lite model is provided in the container at `/cpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with `model.path`.
```yaml
detectors:
cpu1:
type: cpu
num_threads: 3
model:
path: "/custom_model.tflite"
cpu2:
type: cpu
num_threads: 3
```
When using CPU detectors, you can add one CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.
## Edge TPU Detector
@@ -83,15 +81,6 @@ detectors:
device: ""
```
### Single PCIE/M.2 Coral
```yaml
detectors:
coral:
type: edgetpu
device: pci
```
### Multiple PCIE/M.2 Corals
```yaml
@@ -124,22 +113,6 @@ The OpenVINO device to be used is specified using the `"device"` attribute accor
OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will also run on AMD CPUs despite having no official support for it. A supported Intel platform is required to use the `GPU` device with OpenVINO. For detailed system requirements, see [OpenVINO System Requirements](https://docs.openvino.ai/2024/about-openvino/release-notes-openvino/system-requirements.html)
:::tip
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
```yaml
detectors:
ov_0:
type: openvino
device: GPU
ov_1:
type: openvino
device: GPU
```
:::
### Supported Models
#### SSDLite MobileNet v2
@@ -163,11 +136,27 @@ model:
#### YOLOX
This detector also supports YOLOX. Frigate does not come with any YOLOX models preloaded, so you will need to supply your own models.
This detector also supports YOLOX. Frigate does not come with any YOLOX models preloaded, so you will need to supply your own models. This detector has been verified to work with the [yolox_tiny](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/yolox-tiny) model from Intel's Open Model Zoo. You can follow [these instructions](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/yolox-tiny#download-a-model-and-convert-it-into-openvino-ir-format) to retrieve the OpenVINO-compatible `yolox_tiny` model. Make sure that the model input dimensions match the `width` and `height` parameters, and `model_type` is set accordingly. See [Full Configuration Reference](/configuration/reference.md) for a list of possible `model_type` options. Below is an example of how `yolox_tiny` can be used in Frigate:
```yaml
detectors:
ov:
type: openvino
device: GPU
model:
width: 416
height: 416
input_tensor: nchw
input_pixel_format: bgr
model_type: yolox
path: /path/to/yolox_tiny.xml
labelmap_path: /path/to/coco_80cl.txt
```
#### YOLO-NAS
[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) models are supported, but not included by default. You can build and download a compatible model with pre-trained weights using [this notebook](https://github.com/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb).
[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) models are supported, but not included by default. You can build and download a compatible model with pre-trained weights using [this notebook](https://github.com/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb).
:::warning
@@ -296,201 +285,6 @@ model:
height: 320
```
## AMD/ROCm GPU detector
### Setup
The `rocm` detector supports running YOLO-NAS models on AMD GPUs. Use a frigate docker image with `-rocm` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-rocm`.
### Docker settings for GPU access
ROCm needs access to the `/dev/kfd` and `/dev/dri` devices. When docker or frigate is not run under root then also `video` (and possibly `render` and `ssl/_ssl`) groups should be added.
When running docker directly the following flags should be added for device access:
```bash
$ docker run --device=/dev/kfd --device=/dev/dri \
...
```
When using docker compose:
```yaml
services:
frigate:
---
devices:
- /dev/dri
- /dev/kfd
```
For reference on recommended settings see [running ROCm/pytorch in Docker](https://rocm.docs.amd.com/projects/install-on-linux/en/develop/how-to/3rd-party/pytorch-install.html#using-docker-with-pytorch-pre-installed).
### Docker settings for overriding the GPU chipset
Your GPU might work just fine without any special configuration but in many cases they need manual settings. AMD/ROCm software stack comes with a limited set of GPU drivers and for newer or missing models you will have to override the chipset version to an older/generic version to get things working.
Also AMD/ROCm does not "officially" support integrated GPUs. It still does work with most of them just fine but requires special settings. One has to configure the `HSA_OVERRIDE_GFX_VERSION` environment variable. See the [ROCm bug report](https://github.com/ROCm/ROCm/issues/1743) for context and examples.
For the rocm frigate build there is some automatic detection:
- gfx90c -> 9.0.0
- gfx1031 -> 10.3.0
- gfx1103 -> 11.0.0
If you have something else you might need to override the `HSA_OVERRIDE_GFX_VERSION` at Docker launch. Suppose the version you want is `9.0.0`, then you should configure it from command line as:
```bash
$ docker run -e HSA_OVERRIDE_GFX_VERSION=9.0.0 \
...
```
When using docker compose:
```yaml
services:
frigate:
...
environment:
HSA_OVERRIDE_GFX_VERSION: "9.0.0"
```
Figuring out what version you need can be complicated as you can't tell the chipset name and driver from the AMD brand name.
- first make sure that rocm environment is running properly by running `/opt/rocm/bin/rocminfo` in the frigate container -- it should list both the CPU and the GPU with their properties
- find the chipset version you have (gfxNNN) from the output of the `rocminfo` (see below)
- use a search engine to query what `HSA_OVERRIDE_GFX_VERSION` you need for the given gfx name ("gfxNNN ROCm HSA_OVERRIDE_GFX_VERSION")
- override the `HSA_OVERRIDE_GFX_VERSION` with relevant value
- if things are not working check the frigate docker logs
#### Figuring out if AMD/ROCm is working and found your GPU
```bash
$ docker exec -it frigate /opt/rocm/bin/rocminfo
```
#### Figuring out your AMD GPU chipset version:
We unset the `HSA_OVERRIDE_GFX_VERSION` to prevent an existing override from messing up the result:
```bash
$ docker exec -it frigate /bin/bash -c '(unset HSA_OVERRIDE_GFX_VERSION && /opt/rocm/bin/rocminfo |grep gfx)'
```
### Supported Models
There is no default model provided, the following formats are supported:
#### YOLO-NAS
[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) models are supported, but not included by default. You can build and download a compatible model with pre-trained weights using [this notebook](https://github.com/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb).
:::warning
The pre-trained YOLO-NAS weights from DeciAI are subject to their license and can't be used commercially. For more information, see: https://docs.deci.ai/super-gradients/latest/LICENSE.YOLONAS.html
:::
The input image size in this notebook is set to 320x320. This results in lower CPU usage and faster inference times without impacting performance in most cases due to the way Frigate crops video frames to areas of interest before running detection. The notebook and config can be updated to 640x640 if desired.
After placing the downloaded onnx model in your config folder, you can use the following configuration:
```yaml
detectors:
rocm:
type: rocm
model:
model_type: yolonas
width: 320 # <--- should match whatever was set in notebook
height: 320 # <--- should match whatever was set in notebook
input_pixel_format: bgr
path: /config/yolo_nas_s.onnx
labelmap_path: /labelmap/coco-80.txt
```
Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.
## ONNX
ONNX is an open format for building machine learning models, Frigate supports running ONNX models on CPU, OpenVINO, and TensorRT. On startup Frigate will automatically try to use a GPU if one is available.
:::tip
When using many cameras one detector may not be enough to keep up. Multiple detectors can be defined assuming GPU resources are available. An example configuration would be:
```yaml
detectors:
onnx_0:
type: onnx
onnx_1:
type: onnx
```
:::
### Supported Models
There is no default model provided, the following formats are supported:
#### YOLO-NAS
[YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) models are supported, but not included by default. You can build and download a compatible model with pre-trained weights using [this notebook](https://github.com/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/blakeblackshear/frigate/blob/dev/notebooks/YOLO_NAS_Pretrained_Export.ipynb).
:::warning
The pre-trained YOLO-NAS weights from DeciAI are subject to their license and can't be used commercially. For more information, see: https://docs.deci.ai/super-gradients/latest/LICENSE.YOLONAS.html
:::
The input image size in this notebook is set to 320x320. This results in lower CPU usage and faster inference times without impacting performance in most cases due to the way Frigate crops video frames to areas of interest before running detection. The notebook and config can be updated to 640x640 if desired.
After placing the downloaded onnx model in your config folder, you can use the following configuration:
```yaml
detectors:
onnx:
type: onnx
model:
model_type: yolonas
width: 320 # <--- should match whatever was set in notebook
height: 320 # <--- should match whatever was set in notebook
input_pixel_format: bgr
path: /config/yolo_nas_s.onnx
labelmap_path: /labelmap/coco-80.txt
```
Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.
## CPU Detector (not recommended)
The CPU detector type runs a TensorFlow Lite model utilizing the CPU without hardware acceleration. It is recommended to use a hardware accelerated detector type instead for better performance. To configure a CPU based detector, set the `"type"` attribute to `"cpu"`.
:::danger
The CPU detector is not recommended for general use. If you do not have GPU or Edge TPU hardware, using the [OpenVINO Detector](#openvino-detector) in CPU mode is often more efficient than using the CPU detector.
:::
The number of threads used by the interpreter can be specified using the `"num_threads"` attribute, and defaults to `3.`
A TensorFlow Lite model is provided in the container at `/cpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with `model.path`.
```yaml
detectors:
cpu1:
type: cpu
num_threads: 3
model:
path: "/custom_model.tflite"
cpu2:
type: cpu
num_threads: 3
```
When using CPU detectors, you can add one CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.
## Deepstack / CodeProject.AI Server Detector
The Deepstack / CodeProject.AI Server detector for Frigate allows you to integrate Deepstack and CodeProject.AI object detection capabilities into Frigate. CodeProject.AI and DeepStack are open-source AI platforms that can be run on various devices such as the Raspberry Pi, Nvidia Jetson, and other compatible hardware. It is important to note that the integration is performed over the network, so the inference times may not be as fast as native Frigate detectors, but it still provides an efficient and reliable solution for object detection and tracking.
@@ -599,27 +393,3 @@ $ cat /sys/kernel/debug/rknpu/load
- All models are automatically downloaded and stored in the folder `config/model_cache/rknn_cache`. After upgrading Frigate, you should remove older models to free up space.
- You can also provide your own `.rknn` model. You should not save your own models in the `rknn_cache` folder, store them directly in the `model_cache` folder or another subfolder. To convert a model to `.rknn` format see the `rknn-toolkit2` (requires a x86 machine). Note, that there is only post-processing for the supported models.
## Hailo-8l
This detector is available for use with Hailo-8 AI Acceleration Module.
See the [installation docs](../frigate/installation.md#hailo-8l) for information on configuring the hailo8.
### Configuration
```yaml
detectors:
hailo8l:
type: hailo8l
device: PCIe
model:
path: /config/model_cache/h8l_cache/ssd_mobilenet_v1.hef
model:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
model_type: ssd
```

View File

@@ -20,13 +20,15 @@ For object filters in your configuration, any single detection below `min_score`
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.
show image of snapshot vs event with differing scores
### Minimum Score
Any detection below `min_score` will be immediately thrown out and never tracked because it is considered a false positive. If `min_score` is too low then false positives may be detected and tracked which can confuse the object tracker and may lead to wasted resources. If `min_score` is too high then lower scoring true positives like objects that are further away or partially occluded may be thrown out which can also confuse the tracker and cause valid tracked objects to be lost or disjointed.
Any detection below `min_score` will be immediately thrown out and never tracked because it is considered a false positive. If `min_score` is too low then false positives may be detected and tracked which can confuse the object tracker and may lead to wasted resources. If `min_score` is too high then lower scoring true positives like objects that are further away or partially occluded may be thrown out which can also confuse the tracker and cause valid events to be lost or disjointed.
### Threshold
`threshold` is used to determine that the object is a true positive. Once an object is detected with a score >= `threshold` object is considered a true positive. If `threshold` is too low then some higher scoring false positives may create an tracked object. If `threshold` is too high then true positive tracked objects may be missed due to the object never scoring high enough.
`threshold` is used to determine that the object is a true positive. Once an object is detected with a score >= `threshold` object is considered a true positive. If `threshold` is too low then some higher scoring false positives may create an event. If `threshold` is too high then true positive events may be missed due to the object never scoring high enough.
## Object Shape
@@ -50,7 +52,7 @@ Conceptually, a ratio of 1 is a square, 0.5 is a "tall skinny" box, and 2 is a "
### Zones
[Required zones](/configuration/zones.md) can be a great tool to reduce false positives that may be detected in the sky or other areas that are not of interest. The required zones will only create tracked objects for objects that enter the zone.
[Required zones](/configuration/zones.md) can be a great tool to reduce false positives that may be detected in the sky or other areas that are not of interest. The required zones will only create events for objects that enter the zone.
### Object Masks

View File

@@ -1,24 +0,0 @@
---
id: pwa
title: Installing Frigate App
---
Frigate supports being installed as a [Progressive Web App](https://web.dev/explore/progressive-web-apps) on Desktop, Android, and iOS.
This adds features including the ability to deep link directly into the app.
## Requirements
In order to install Frigate as a PWA, the following requirements must be met:
- Frigate must be accessed via a secure context (localhost, secure https, etc.)
- On Android, Firefox, Chrome, Edge, Opera, and Samsung Internet Browser all support installing PWAs.
- On iOS 16.4 and later, PWAs can be installed from the Share menu in Safari, Chrome, Edge, Firefox, and Orion.
## Installation
Installation varies slightly based on the device that is being used:
- Desktop: Use the install button typically found in right edge of the address bar
- Android: Use the `Install as App` button in the more options menu
- iOS: Use the `Add to Homescreen` button in the share menu

View File

@@ -3,7 +3,7 @@ id: record
title: Recording
---
Recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM-DD/HH/<camera_name>/MM.SS.mp4` in **UTC time**. These recordings are written directly from your camera stream without re-encoding. Each camera supports a configurable retention policy in the config. Frigate chooses the largest matching retention value between the recording retention and the tracked object retention when determining if a recording should be removed.
Recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM-DD/HH/<camera_name>/MM.SS.mp4` in **UTC time**. These recordings are written directly from your camera stream without re-encoding. Each camera supports a configurable retention policy in the config. Frigate chooses the largest matching retention value between the recording retention and the event retention when determining if a recording should be removed.
New recording segments are written from the camera stream to cache, they are only moved to disk if they match the setup recording retention policy.
@@ -13,7 +13,7 @@ H265 recordings can be viewed in Chrome 108+, Edge and Safari only. All other br
### Most conservative: Ensure all video is saved
For users deploying Frigate in environments where it is important to have contiguous video stored even if there was no detectable motion, the following config will store all video for 3 days. After 3 days, only video containing motion and overlapping with alerts or detections will be retained until 30 days have passed.
For users deploying Frigate in environments where it is important to have contiguous video stored even if there was no detectable motion, the following config will store all video for 3 days. After 3 days, only video containing motion and overlapping with events will be retained until 30 days have passed.
```yaml
record:
@@ -21,13 +21,9 @@ record:
retain:
days: 3
mode: all
alerts:
events:
retain:
days: 30
mode: motion
detections:
retain:
days: 30
default: 30
mode: motion
```
@@ -41,28 +37,25 @@ record:
retain:
days: 3
mode: motion
alerts:
events:
retain:
days: 30
mode: motion
detections:
retain:
days: 30
default: 30
mode: motion
```
### Minimum: Alerts only
### Minimum: Events only
If you only want to retain video that occurs during a tracked object, this config will discard video unless an alert is ongoing.
If you only want to retain video that occurs during an event, this config will discard video unless an event is ongoing.
```yaml
record:
enabled: True
retain:
days: 0
alerts:
mode: all
events:
retain:
days: 30
default: 30
mode: motion
```
@@ -72,7 +65,7 @@ As of Frigate 0.12 if there is less than an hour left of storage, the oldest 2 h
## Configuring Recording Retention
Frigate supports both continuous and tracked object based recordings with separate retention modes and retention periods.
Frigate supports both continuous and event based recordings with separate retention modes and retention periods.
:::tip
@@ -93,28 +86,25 @@ record:
Continuous recording supports different retention modes [which are described below](#what-do-the-different-retain-modes-mean)
### Object Recording
### Event Recording
The number of days to record review items can be specified for review items classified as alerts as well as tracked objects.
If you only used clips in previous versions with recordings disabled, you can use the following config to get the same behavior. This is also the default behavior when recordings are enabled.
```yaml
record:
enabled: True
alerts:
events:
retain:
days: 10 # <- number of days to keep alert recordings
detections:
retain:
days: 10 # <- number of days to keep detections recordings
default: 10 # <- number of days to keep event recordings
```
This configuration will retain recording segments that overlap with alerts and detections for 10 days. Because multiple tracked objects can reference the same recording segments, this avoids storing duplicate footage for overlapping tracked objects and reduces overall storage needs.
This configuration will retain recording segments that overlap with events and have active tracked objects for 10 days. Because multiple events can reference the same recording segments, this avoids storing duplicate footage for overlapping events and reduces overall storage needs.
**WARNING**: Recordings still must be enabled in the config. If a camera has recordings disabled in the config, enabling via the methods listed above will have no effect.
## What do the different retain modes mean?
Frigate saves from the stream with the `record` role in 10 second segments. These options determine which recording segments are kept for continuous recording (but can also affect tracked objects).
Frigate saves from the stream with the `record` role in 10 second segments. These options determine which recording segments are kept for continuous recording (but can also affect events).
Let's say you have Frigate configured so that your doorbell camera would retain the last **2** days of continuous recording.
@@ -122,7 +112,11 @@ Let's say you have Frigate configured so that your doorbell camera would retain
- With the `motion` option the only parts of those 48 hours would be segments that Frigate detected motion. This is the middle ground option that won't keep all 48 hours, but will likely keep all segments of interest along with the potential for some extra segments.
- With the `active_objects` option the only segments that would be kept are those where there was a true positive object that was not considered stationary.
The same options are available with alerts and detections, except it will only save the recordings when it overlaps with a review item of that type.
The same options are available with events. Let's consider a scenario where you drive up and park in your driveway, go inside, then come back out 4 hours later.
- With the `all` option all segments for the duration of the event would be saved for the event. This event would have 4 hours of footage.
- With the `motion` option all segments for the duration of the event with motion would be saved. This means any segment where a car drove by in the street, person walked by, lighting changed, etc. would be saved.
- With the `active_objects` it would only keep segments where the object was active. In this case the only segments that would be saved would be the ones where the car was driving up, you going inside, you coming outside, and the car driving away. Essentially reducing the 4 hours to a minute or two of event footage.
A configuration example of the above retain modes where all `motion` segments are stored for 7 days and `active objects` are stored for 14 days would be as follows:
@@ -132,32 +126,44 @@ record:
retain:
days: 7
mode: motion
alerts:
events:
retain:
days: 14
mode: active_objects
detections:
retain:
days: 14
default: 14
mode: active_objects
```
The above configuration example can be added globally or on a per camera basis.
### Object Specific Retention
You can also set specific retention length for an object type. The below configuration example builds on from above but also specifies that recordings of dogs only need to be kept for 2 days and recordings of cars should be kept for 7 days.
```yaml
record:
enabled: True
retain:
days: 7
mode: motion
events:
retain:
default: 14
mode: active_objects
objects:
dog: 2
car: 7
```
## Can I have "continuous" recordings, but only at certain times?
Using Frigate UI, HomeAssistant, or MQTT, cameras can be automated to only record in certain situations or at certain times.
## How do I export recordings?
Footage can be exported from Frigate by right-clicking (desktop) or long pressing (mobile) on a review item in the Review pane or by clicking the Export button in the History view. Exported footage is then organized and searchable through the Export view, accessible from the main navigation bar.
The export page in the Frigate WebUI allows for exporting real time clips with a designated start and stop time as well as exporting a time-lapse for a designated start and stop time. These exports can take a while so it is important to leave the file until it is no longer in progress.
### Time-lapse export
Time lapse exporting is available only via the [HTTP API](../integrations/api/export-recording-export-camera-name-start-start-time-end-end-time-post.api.mdx).
When exporting a time-lapse the default speed-up is 25x with 30 FPS. This means that every 25 seconds of (real-time) recording is condensed into 1 second of time-lapse video (always without audio) with a smoothness of 30 FPS.
To configure the speed-up factor, the frame rate and further custom settings, the configuration parameter `timelapse_args` can be used. The below configuration example would change the time-lapse speed to 60x (for fitting 1 hour of recording into 1 minute of time-lapse) with 25 FPS:
```yaml

View File

@@ -65,7 +65,7 @@ database:
# Optional: TLS configuration
tls:
# Optional: Enable TLS for port 8971 (default: shown below)
# Optional: Enable TLS for port 8080 (default: shown below)
enabled: True
# Optional: Proxy configuration
@@ -138,16 +138,6 @@ model:
# Optional: Label name modifications. These are merged into the standard labelmap.
labelmap:
2: vehicle
# Optional: Map of object labels to their attribute labels (default: depends on model)
attributes_map:
person:
- amazon
- face
car:
- amazon
- fedex
- license_plate
- ups
# Optional: Audio Events Configuration
# NOTE: Can be overridden at the camera level
@@ -212,7 +202,7 @@ birdseye:
inactivity_threshold: 30
# Optional: Configure the birdseye layout
layout:
# Optional: Scaling factor for the layout calculator, range 1.0-5.0 (default: shown below)
# Optional: Scaling factor for the layout calculator (default: shown below)
scaling_factor: 2.0
# Optional: Maximum number of cameras to show at one time, showing the most recent (default: show all cameras)
max_cameras: 1
@@ -220,10 +210,6 @@ birdseye:
# Optional: ffmpeg configuration
# More information about presets at https://docs.frigate.video/configuration/ffmpeg_presets
ffmpeg:
# Optional: ffmpeg binry path (default: shown below)
# can also be set to `7.0` or `5.0` to specify one of the included versions
# or can be set to any path that holds `bin/ffmpeg` & `bin/ffprobe`
path: "default"
# Optional: global ffmpeg args (default: shown below)
global_args: -hide_banner -loglevel warning -threads 2
# Optional: global hwaccel args (default: auto detect)
@@ -285,13 +271,13 @@ detect:
# especially when using separate streams for detect and record.
# Use this setting to make the timeline bounding boxes more closely align
# with the recording. The value can be positive or negative.
# TIP: Imagine there is an tracked object clip with a person walking from left to right.
# If the tracked object lifecycle bounding box is consistently to the left of the person
# TIP: Imagine there is an event clip with a person walking from left to right.
# If the event timeline bounding box is consistently to the left of the person
# then the value should be decreased. Similarly, if a person is walking from
# left to right and the bounding box is consistently ahead of the person
# then the value should be increased.
# TIP: This offset is dynamic so you can change the value and it will update existing
# tracked objects, this makes it easy to tune.
# events, this makes it easy to tune.
# WARNING: Fast moving objects will likely not have the bounding box align.
annotation_offset: 0
@@ -334,9 +320,6 @@ review:
- car
- person
# Optional: required zones for an object to be marked as an alert (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones:
- driveway
# Optional: detections configuration
@@ -346,20 +329,12 @@ review:
- car
- person
# Optional: required zones for an object to be marked as a detection (default: none)
# NOTE: when settings required zones globally, this zone must exist on all cameras
# or the config will be considered invalid. In that case the required_zones
# should be configured at the camera level.
required_zones:
- driveway
# Optional: Motion configuration
# NOTE: Can be overridden at the camera level
motion:
# Optional: enables detection for the camera (default: True)
# NOTE: Motion detection is required for object detection,
# setting this to False and leaving detect enabled
# will result in an error on startup.
enabled: False
# 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.
@@ -397,14 +372,6 @@ motion:
# Optional: Delay when updating camera motion through MQTT from ON -> OFF (default: shown below).
mqtt_off_delay: 30
# Optional: Notification Configuration
notifications:
# Optional: Enable notification service (default: shown below)
enabled: False
# Optional: Email for push service to reach out to
# NOTE: This is required to use notifications
email: "admin@example.com"
# Optional: Record configuration
# NOTE: Can be overridden at the camera level
record:
@@ -419,9 +386,9 @@ record:
sync_recordings: False
# Optional: Retention settings for recording
retain:
# Optional: Number of days to retain recordings regardless of tracked objects (default: shown below)
# NOTE: This should be set to 0 and retention should be defined in alerts and detections section below
# if you only want to retain recordings of alerts and detections.
# 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
@@ -444,48 +411,34 @@ record:
# Optional: Quality of recording preview (default: shown below).
# Options are: very_low, low, medium, high, very_high
quality: medium
# Optional: alert recording settings
alerts:
# Optional: Number of seconds before the alert to include (default: shown below)
# 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 alert to include (default: shown below)
# Optional: Number of seconds after the event to include (default: shown below)
post_capture: 5
# Optional: Retention settings for recordings of alerts
# Optional: Objects to save recordings for. (default: all tracked objects)
objects:
- person
# Optional: Retention settings for recordings of events
retain:
# Required: Retention days (default: shown below)
days: 14
# Required: Default retention days (default: shown below)
default: 10
# Optional: Mode for retention. (default: shown below)
# all - save all recording segments for alerts regardless of activity
# motion - save all recordings segments for alerts with any detected motion
# active_objects - save all recording segments for alerts 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: detection recording settings
detections:
# Optional: Number of seconds before the detection to include (default: shown below)
pre_capture: 5
# Optional: Number of seconds after the detection to include (default: shown below)
post_capture: 5
# Optional: Retention settings for recordings of detections
retain:
# Required: Retention days (default: shown below)
days: 14
# Optional: Mode for retention. (default: shown below)
# all - save all recording segments for detections regardless of activity
# motion - save all recordings segments for detections with any detected motion
# active_objects - save all recording segments for detections with active/moving objects
# 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: 15
# Optional: Configuration for the jpg snapshots written to the clips directory for each tracked object
# 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)
@@ -512,40 +465,8 @@ snapshots:
# Optional: quality of the encoded jpeg, 0-100 (default: shown below)
quality: 70
# Optional: Configuration for semantic search capability
semantic_search:
# Optional: Enable semantic search (default: shown below)
enabled: False
# Optional: Re-index embeddings database from historical tracked objects (default: shown below)
reindex: False
# Optional: Set the model size used for embeddings. (default: shown below)
# NOTE: small model runs on CPU and large model runs on GPU
model_size: "small"
# Optional: Configuration for AI generated tracked object descriptions
# NOTE: Semantic Search must be enabled for this to do anything.
# WARNING: Depending on the provider, this will send thumbnails over the internet
# to Google or OpenAI's LLMs to generate descriptions. It can be overridden at
# the camera level (enabled: False) to enhance privacy for indoor cameras.
genai:
# Optional: Enable AI description generation (default: shown below)
enabled: False
# Required if enabled: Provider must be one of ollama, gemini, or openai
provider: ollama
# Required if provider is ollama. May also be used for an OpenAI API compatible backend with the openai provider.
base_url: http://localhost::11434
# Required if gemini or openai
api_key: "{FRIGATE_GENAI_API_KEY}"
# Optional: The default prompt for generating descriptions. Can use replacement
# variables like "label", "sub_label", "camera" to make more dynamic. (default: shown below)
prompt: "Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background."
# Optional: Object specific prompts to customize description results
# Format: {label}: {prompt}
object_prompts:
person: "My special person prompt."
# Optional: Restream configuration
# Uses https://github.com/AlexxIT/go2rtc (v1.9.2)
# Uses https://github.com/AlexxIT/go2rtc (v1.8.3)
go2rtc:
# Optional: jsmpeg stream configuration for WebUI
@@ -692,9 +613,6 @@ cameras:
user: admin
# Optional: password for login.
password: admin
# Optional: Ignores time synchronization mismatches between the camera and the server during authentication.
# Using NTP on both ends is recommended and this should only be set to True in a "safe" environment due to the security risk it represents.
ignore_time_mismatch: False
# Optional: PTZ camera object autotracking. Keeps a moving object in
# the center of the frame by automatically moving the PTZ camera.
autotracking:
@@ -736,26 +654,6 @@ cameras:
# By default the cameras are sorted alphabetically.
order: 0
# Optional: Configuration for AI generated tracked object descriptions
genai:
# Optional: Enable AI description generation (default: shown below)
enabled: False
# Optional: Use the object snapshot instead of thumbnails for description generation (default: shown below)
use_snapshot: False
# Optional: The default prompt for generating descriptions. Can use replacement
# variables like "label", "sub_label", "camera" to make more dynamic. (default: shown below)
prompt: "Describe the {label} in the sequence of images with as much detail as possible. Do not describe the background."
# Optional: Object specific prompts to customize description results
# Format: {label}: {prompt}
object_prompts:
person: "My special person prompt."
# Optional: objects to generate descriptions for (default: all objects that are tracked)
objects:
- person
- cat
# Optional: Restrict generation to objects that entered any of the listed zones (default: none, all zones qualify)
required_zones: []
# Optional
ui:
# Optional: Set a timezone to use in the UI (default: use browser local time)
@@ -818,7 +716,7 @@ camera_groups:
- side_cam
- front_doorbell_cam
# Required: icon used for group
icon: LuCar
icon: car
# Required: index of this group
order: 0
```

View File

@@ -21,7 +21,7 @@ Birdseye RTSP restream can be accessed at `rtsp://<frigate_host>:8554/birdseye`.
```yaml
birdseye:
restream: True
restream: true
```
### Securing Restream With Authentication

View File

@@ -7,16 +7,6 @@ The Review page of the Frigate UI is for quickly reviewing historical footage of
Review items are filterable by date, object type, and camera.
### Review items vs. tracked objects (formerly "events")
In Frigate 0.13 and earlier versions, the UI presented "events". An event was synonymous with a tracked or detected object. In Frigate 0.14 and later, a review item is a time period where any number of tracked objects were active.
For example, consider a situation where two people walked past your house. One was walking a dog. At the same time, a car drove by on the street behind them.
In this scenario, Frigate 0.13 and earlier would show 4 "events" in the UI - one for each person, another for the dog, and yet another for the car. You would have had 4 separate videos to watch even though they would have all overlapped.
In 0.14 and later, all of that is bundled into a single review item which starts and ends to capture all of that activity. Reviews for a single camera cannot overlap. Once you have watched that time period on that camera, it is marked as reviewed.
## Alerts and Detections
Not every segment of video captured by Frigate may be of the same level of interest to you. Video of people who enter your property may be a different priority than those walking by on the sidewalk. For this reason, Frigate 0.14 categorizes review items as _alerts_ and _detections_. By default, all person and car objects are considered alerts. You can refine categorization of your review items by configuring required zones for them.
@@ -41,6 +31,8 @@ review:
By default all detections that do not qualify as an alert qualify as a detection. However, detections can further be filtered to only include certain labels or certain zones.
By default a review item will only be marked as an alert if a person or car is detected. This can be configured to include any object or audio label using the following config:
```yaml
# can be overridden at the camera level
review:
@@ -70,6 +62,6 @@ By default a review item will be created if any `review -> alerts -> labels` and
:::info
Because zones don't apply to audio, audio labels will always be marked as a detection by default.
Because zones don't apply to audio, audio labels will always be marked as an alert.
:::

View File

@@ -1,68 +0,0 @@
---
id: semantic_search
title: Using Semantic Search
---
Semantic Search in Frigate allows you to find tracked objects within your review items using either the image itself, a user-defined text description, or an automatically generated one. This feature works by creating _embeddings_ — numerical vector representations — for both the images and text descriptions of your tracked objects. By comparing these embeddings, Frigate assesses their similarities to deliver relevant search results.
Frigate has support for [Jina AI's CLIP model](https://huggingface.co/jinaai/jina-clip-v1) to create embeddings, which runs locally. Embeddings are then saved to Frigate's database.
Semantic Search is accessed via the _Explore_ view in the Frigate UI.
## Minimum System Requirements
Semantic Search works by running a large AI model locally on your system. Small or underpowered systems like a Raspberry Pi will not run Semantic Search reliably or at all.
A minimum of 8GB of RAM is required to use Semantic Search. A GPU is not strictly required but will provide a significant performance increase over CPU-only systems.
For best performance, 16GB or more of RAM and a dedicated GPU are recommended.
## Configuration
Semantic search is disabled by default, and must be enabled in your config file before it can be used. Semantic Search is a global configuration setting.
```yaml
semantic_search:
enabled: True
reindex: False
```
:::tip
The embeddings database can be re-indexed from the existing tracked objects in your database by adding `reindex: True` to your `semantic_search` configuration. Depending on the number of tracked objects you have, it can take a long while to complete and may max out your CPU while indexing. Make sure to set the config back to `False` before restarting Frigate again.
If you are enabling the Search feature for the first time, be advised that Frigate does not automatically index older tracked objects. You will need to enable the `reindex` feature in order to do that.
:::
### Jina AI CLIP
The vision model is able to embed both images and text into the same vector space, which allows `image -> image` and `text -> image` similarity searches. Frigate uses this model on tracked objects to encode the thumbnail image and store it in the database. When searching for tracked objects via text in the search box, Frigate will perform a `text -> image` similarity search against this embedding. When clicking "Find Similar" in the tracked object detail pane, Frigate will perform an `image -> image` similarity search to retrieve the closest matching thumbnails.
The text model is used to embed tracked object descriptions and perform searches against them. Descriptions can be created, viewed, and modified on the Search page when clicking on the gray tracked object chip at the top left of each review item. See [the Generative AI docs](/configuration/genai.md) for more information on how to automatically generate tracked object descriptions.
Differently weighted CLIP models are available and can be selected by setting the `model_size` config option:
:::tip
The CLIP models are downloaded in ONNX format, which means they will be accelerated using GPU hardware when available. This depends on the Docker build that is used. See [the object detector docs](../configuration/object_detectors.md) for more information.
:::
```yaml
semantic_search:
enabled: True
model_size: small
```
- Configuring the `large` model employs the full Jina model and will automatically run on the GPU if applicable.
- Configuring the `small` model employs a quantized version of the model that uses much less RAM and runs faster on CPU with a very negligible difference in embedding quality.
## Usage and Best Practices
1. Semantic search is used in conjunction with the other filters available on the Search page. Use a combination of traditional filtering and semantic search for the best results.
2. Use the thumbnail search type when searching for particular objects in the scene. Use the description search type when attempting to discern the intent of your object.
3. Because of how the AI models Frigate uses have been trained, the comparison between text and image embedding distances generally means that with multi-modal (`thumbnail` and `description`) searches, results matching `description` will appear first, even if a `thumbnail` embedding may be a better match. Play with the "Search Type" setting to help find what you are looking for. Note that if you are generating descriptions for specific objects or zones only, this may cause search results to prioritize the objects with descriptions even if the the ones without them are more relevant.
4. Make your search language and tone closely match exactly what you're looking for. If you are using thumbnail search, **phrase your query as an image caption**. Searching for "red car" may not work as well as "red sedan driving down a residential street on a sunny day".
5. Semantic search on thumbnails tends to return better results when matching large subjects that take up most of the frame. Small things like "cat" tend to not work well.
6. Experiment! Find a tracked object you want to test and start typing keywords and phrases to see what works for you.

View File

@@ -3,7 +3,7 @@ id: snapshots
title: Snapshots
---
Frigate can save a snapshot image to `/media/frigate/clips` for each object that is detected named as `<camera>-<id>.jpg`. They are also accessible [via the api](../integrations/api/event-snapshot-events-event-id-snapshot-jpg-get.api.mdx)
Frigate can save a snapshot image to `/media/frigate/clips` for each object that is detected named as `<camera>-<id>.jpg`. They are also accessible [via the api](../integrations/api.md#get-apieventsidsnapshotjpg)
For users with Frigate+ enabled, snapshots are accessible in the UI in the Frigate+ pane to allow for quick submission to the Frigate+ service.

View File

@@ -5,7 +5,7 @@ title: TLS
# TLS
Frigate's integrated NGINX server supports TLS certificates. By default Frigate will generate a self signed certificate that will be used for port 8971. Frigate is designed to make it easy to use whatever tool you prefer to manage certificates.
Frigate's integrated NGINX server supports TLS certificates. By default Frigate will generate a self signed certificate that will be used for port 8080. Frigate is designed to make it easy to use whatever tool you prefer to manage certificates.
Frigate is often running behind a reverse proxy that manages TLS certificates for multiple services. You will likely need to set your reverse proxy to allow self signed certificates or you can disable TLS in Frigate's config. However, if you are running on a dedicated device that's separate from your proxy or if you expose Frigate directly to the internet, you may want to configure TLS with valid certificates.
@@ -24,33 +24,21 @@ TLS certificates can be mounted at `/etc/letsencrypt/live/frigate` using a bind
frigate:
...
volumes:
- /path/to/your/certificate_folder:/etc/letsencrypt/live/frigate:ro
- /path/to/your/certificate_folder:/etc/letsencrypt/live/frigate
...
```
Within the folder, the private key is expected to be named `privkey.pem` and the certificate is expected to be named `fullchain.pem`.
Note that certbot uses symlinks, and those can't be followed by the container unless it has access to the targets as well, so if using certbot you'll also have to mount the `archive` folder for your domain, e.g.:
```yaml
frigate:
...
volumes:
- /etc/letsencrypt/live/frigate:/etc/letsencrypt/live/frigate:ro
- /etc/letsencrypt/archive/frigate:/etc/letsencrypt/archive/frigate:ro
...
```
Frigate automatically compares the fingerprint of the certificate at `/etc/letsencrypt/live/frigate/fullchain.pem` against the fingerprint of the TLS cert in NGINX every minute. If these differ, the NGINX config is reloaded to pick up the updated certificate.
If you issue Frigate valid certificates you will likely want to configure it to run on port 443 so you can access it without a port number like `https://your-frigate-domain.com` by mapping 8971 to 443.
If you issue Frigate valid certificates you will likely want to configure it to run on port 443 so you can access it without a port number like `https://your-frigate-domain.com` by mapping 8080 to 443.
```yaml
frigate:
...
ports:
- "443:8971"
- "443:8080"
...
```

View File

@@ -64,7 +64,7 @@ cameras:
### Restricting zones to specific objects
Sometimes you want to limit a zone to specific object types to have more granular control of when alerts, detections, and snapshots are saved. The following example will limit one zone to person objects and the other to cars.
Sometimes you want to limit a zone to specific object types to have more granular control of when events/snapshots are saved. The following example will limit one zone to person objects and the other to cars.
```yaml
cameras:
@@ -80,7 +80,7 @@ cameras:
- car
```
Only car objects can trigger the `front_yard_street` zone and only person can trigger the `entire_yard`. Objects will be tracked for any `person` that enter anywhere in the yard, and for cars only if they enter the street.
Only car objects can trigger the `front_yard_street` zone and only person can trigger the `entire_yard`. You will get events for person objects that enter anywhere in the yard, and events for cars only if they enter the street.
### Zone Loitering

View File

@@ -193,7 +193,7 @@ npm run test
#### 1. Installation
```console
cd docs && npm install
npm install
```
#### 2. Local Development

View File

@@ -9,12 +9,9 @@ The glossary explains terms commonly used in Frigate's documentation.
A box returned from the object detection model that outlines an object in the frame. These have multiple colors depending on object type in the debug live view.
### Bounding Box Colors
## Event
- At startup different colors will be assigned to each object label
- A dark blue thin line indicates that object is not detected at this current point in time
- A gray thin line indicates that object is detected as being stationary
- A thick line indicates that object is the subject of autotracking (when enabled).
The time period starting when a tracked object entered the frame and ending when it left the frame, including any time that the object remained still. Events are saved when it is considered a [true positive](#threshold) and meets the requirements for a snapshot or recording to be saved.
## False Positive
@@ -44,10 +41,6 @@ When pixels in the current camera frame are different than previous frames. When
A portion of the camera frame that is sent to object detection, regions can be sent due to motion, active objects, or occasionally for stationary objects. These are represented by green boxes in the debug live view.
## Review Item
A review item is a time period where any number of events/tracked objects were active. [See the review docs for more info](/configuration/review)
## Snapshot Score
The score shown in a snapshot is the score of that object at that specific moment in time.
@@ -60,10 +53,6 @@ The threshold is the median score that an object must reach in order to be consi
The top score for an object is the highest median score for an object.
## Tracked Object ("event" in previous versions)
The time period starting when a tracked object entered the frame and ending when it left the frame, including any time that the object remained still. Tracked objects are saved when it is considered a [true positive](#threshold) and meets the requirements for a snapshot or recording to be saved.
## Zone
Zones are areas of interest, zones can be used for notifications and for limiting the areas where Frigate will create an [event](#event). [See the zone docs for more info](/configuration/zones)

View File

@@ -69,7 +69,6 @@ Inference speeds vary greatly depending on the CPU, GPU, or VPU used, some known
| Intel i5 7500 | ~ 15 ms | Inference speeds on CPU were ~ 260 ms |
| Intel i5 1135G7 | 10 - 15 ms | |
| Intel i5 12600K | ~ 15 ms | Inference speeds on CPU were ~ 35 ms |
| Intel Arc A750 | ~ 4 ms | |
### TensorRT - Nvidia GPU
@@ -88,10 +87,6 @@ Inference speeds will vary greatly depending on the GPU and the model used.
| Quadro P400 2GB | 20 - 25 ms |
| Quadro P2000 | ~ 12 ms |
#### AMD GPUs
With the [rocm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many AMD GPUs.
### Community Supported:
#### Nvidia Jetson
@@ -112,12 +107,6 @@ Frigate supports hardware video processing on all Rockchip boards. However, hard
The inference time of a rk3588 with all 3 cores enabled is typically 25-30 ms for yolo-nas s.
#### Hailo-8l PCIe
Frigate supports the Hailo-8l M.2 card on any hardware but currently it is only tested on the Raspberry Pi5 PCIe hat from the AI kit.
The inference time for the Hailo-8L chip at time of writing is around 17-21 ms for the SSD MobileNet Version 1 model.
## What does Frigate use the CPU for and what does it use a detector for? (ELI5 Version)
This is taken from a [user question on reddit](https://www.reddit.com/r/homeassistant/comments/q8mgau/comment/hgqbxh5/?utm_source=share&utm_medium=web2x&context=3). Modified slightly for clarity.

View File

@@ -5,12 +5,6 @@ title: Installation
Frigate is a Docker container that can be run on any Docker host including as a [HassOS Addon](https://www.home-assistant.io/addons/). Note that a Home Assistant Addon is **not** the same thing as the integration. The [integration](/integrations/home-assistant) is required to integrate Frigate into Home Assistant.
:::tip
If you already have Frigate installed as a Home Assistant addon, check out the [getting started guide](../guides/getting_started#configuring-frigate) 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.
@@ -40,7 +34,7 @@ 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. |
| `8080` | 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 low latency live views. |
@@ -73,23 +67,23 @@ Users of the Snapcraft build of Docker cannot use storage locations outside your
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`](https://docs.docker.com/engine/reference/run/#runtime-constraints-on-resources) (or [`service.shm_size`](https://docs.docker.com/compose/compose-file/compose-file-v2/#shm_size) in docker-compose).
The default shm size of **64MB** 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`](https://docs.docker.com/engine/reference/run/#runtime-constraints-on-resources) (or [`service.shm_size`](https://docs.docker.com/compose/compose-file/compose-file-v2/#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.
The Frigate container also stores logs in shm, which can take up to **30MB**, so make sure to take this into account in your math as well.
You can calculate the **minimum** shm size for each camera with the following formula using the resolution specified for detect:
You can calculate the necessary shm size for each camera with the following formula using the resolution specified for detect:
```console
# Replace <width> and <height>
$ python -c 'print("{:.2f}MB".format((<width> * <height> * 1.5 * 10 + 270480) / 1048576))'
$ python -c 'print("{:.2f}MB".format((<width> * <height> * 1.5 * 9 + 270480) / 1048576))'
# Example for 1280x720
$ python -c 'print("{:.2f}MB".format((1280 * 720 * 1.5 * 10 + 270480) / 1048576))'
13.44MB
$ python -c 'print("{:.2f}MB".format((1280 * 720 * 1.5 * 9 + 270480) / 1048576))'
12.12MB
# Example for eight cameras detecting at 1280x720, including logs
$ python -c 'print("{:.2f}MB".format(((1280 * 720 * 1.5 * 10 + 270480) / 1048576) * 8 + 40))'
136.99MB
$ python -c 'print("{:.2f}MB".format(((1280 * 720 * 1.5 * 9 + 270480) / 1048576) * 8 + 30))'
126.99MB
```
The shm size cannot be set per container for Home Assistant add-ons. 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.
@@ -100,38 +94,6 @@ By default, the Raspberry Pi limits the amount of memory available to the GPU. I
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 <a href="https://amzn.to/3a2mH0P" target="_blank" rel="nofollow noopener sponsored">this</a> (affiliate link).
### Hailo-8L
The Hailo-8L is an M.2 card typically connected to a carrier board for PCIe, which then connects to the Raspberry Pi 5 as part of the AI Kit. However, it can also be used on other boards equipped with an M.2 M key edge connector.
#### Installation
For Raspberry Pi 5 users with the AI Kit, installation is straightforward. Simply follow this [guide](https://www.raspberrypi.com/documentation/accessories/ai-kit.html#ai-kit-installation) to install the driver and software.
For other installations, follow these steps for installation:
1. Install the driver from the [Hailo GitHub repository](https://github.com/hailo-ai/hailort-drivers). A convenient script for Linux is available to clone the repository, build the driver, and install it.
2. Copy or download [this script](https://github.com/blakeblackshear/frigate/blob/41c9b13d2fffce508b32dfc971fa529b49295fbd/docker/hailo8l/user_installation.sh).
3. Ensure it has execution permissions with `sudo chmod +x user_installation.sh`
4. Run the script with `./user_installation.sh`
#### Setup
To set up Frigate, follow the default installation instructions, but use a Docker image with the `-h8l` suffix, for example: `ghcr.io/blakeblackshear/frigate:stable-h8l`
Next, grant Docker permissions to access your hardware by adding the following lines to your `docker-compose.yml` file:
```yaml
devices:
- /dev/hailo0
```
If you are using `docker run`, add this option to your command `--device /dev/hailo0`
#### Configuration
Finally, configure [hardware object detection](/configuration/object_detectors#hailo-8l) 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:
@@ -209,7 +171,7 @@ services:
tmpfs:
size: 1000000000
ports:
- "8971:8971"
- "8080:8080"
# - "5000:5000" # Internal unauthenticated access. Expose carefully.
- "8554:8554" # RTSP feeds
- "8555:8555/tcp" # WebRTC over tcp
@@ -232,7 +194,7 @@ docker run -d \
-v /path/to/your/config:/config \
-v /etc/localtime:/etc/localtime:ro \
-e FRIGATE_RTSP_PASSWORD='password' \
-p 8971:8971 \
-p 8080:8080 \
-p 8554:8554 \
-p 8555:8555/tcp \
-p 8555:8555/udp \
@@ -250,8 +212,10 @@ The community supported docker image tags for the current stable version are:
- `stable-tensorrt-jp5` - Frigate build optimized for nvidia Jetson devices running Jetpack 5
- `stable-tensorrt-jp4` - Frigate build optimized for nvidia Jetson devices running Jetpack 4.6
- `stable-rk` - Frigate build for SBCs with Rockchip SoC
- `stable-rocm` - Frigate build for [AMD GPUs](../configuration/object_detectors.md#amdrocm-gpu-detector)
- `stable-h8l` - Frigate build for the Hailo-8L M.2 PICe Raspberry Pi 5 hat
- `stable-rocm` - Frigate build for [AMD GPUs and iGPUs](../configuration/object_detectors.md#amdrocm-gpu-detector), all drivers
- `stable-rocm-gfx900` - AMD gfx900 driver only
- `stable-rocm-gfx1030` - AMD gfx1030 driver only
- `stable-rocm-gfx1100` - AMD gfx1100 driver only
## Home Assistant Addon
@@ -406,7 +370,7 @@ docker run \
--network=bridge \
--privileged \
--workdir=/opt/frigate \
-p 8971:8971 \
-p 8080:8080 \
-p 8554:8554 \
-p 8555:8555 \
-p 8555:8555/udp \

View File

@@ -13,7 +13,7 @@ Use of the bundled go2rtc is optional. You can still configure FFmpeg to connect
# Setup a go2rtc stream
First, you will want to configure go2rtc to connect to your camera stream by adding the stream you want to use for live view in your Frigate config file. For the best experience, you should set the stream name under go2rtc to match the name of your camera so that Frigate will automatically map it and be able to use better live view options for the camera. Avoid changing any other parts of your config at this step. Note that go2rtc supports [many different stream types](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#module-streams), not just rtsp.
First, you will want to configure go2rtc to connect to your camera stream by adding the stream you want to use for live view in your Frigate config file. If you set the stream name under go2rtc to match the name of your camera, it will automatically be mapped and you will get additional live view options for the camera. Avoid changing any other parts of your config at this step. Note that go2rtc supports [many different stream types](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#module-streams), not just rtsp.
```yaml
go2rtc:
@@ -22,35 +22,22 @@ go2rtc:
- rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
```
After adding this to the config, restart Frigate and try to watch the live stream for a single camera by clicking on it from the dashboard. It should look much clearer and more fluent than the original jsmpeg stream.
The easiest live view to get working is MSE. After adding this to the config, restart Frigate and try to watch the live stream by selecting MSE in the dropdown after clicking on the camera.
### What if my video doesn't play?
- Check Logs:
- Access the go2rtc logs in the Frigate UI under Logs in the sidebar.
- If go2rtc is having difficulty connecting to your camera, you should see some error messages in the log.
If you are unable to see your video feed, first check the go2rtc logs in the Frigate UI under Logs in the sidebar. If go2rtc is having difficulty connecting to your camera, you should see some error messages in the log. If you do not see any errors, then the video codec of the stream may not be supported in your browser. If your camera stream is set to H265, try switching to H264. You can see more information about [video codec compatibility](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#codecs-madness) in the go2rtc documentation. If you are not able to switch your camera settings from H265 to H264 or your stream is a different format such as MJPEG, you can use go2rtc to re-encode the video using the [FFmpeg parameters](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#source-ffmpeg). It supports rotating and resizing video feeds and hardware acceleration. Keep in mind that transcoding video from one format to another is a resource intensive task and you may be better off using the built-in jsmpeg view. Here is an example of a config that will re-encode the stream to H264 without hardware acceleration:
- Check go2rtc Web Interface: if you don't see any errors in the logs, try viewing the camera through go2rtc's web interface.
- Navigate to port 1984 in your browser to access go2rtc's web interface.
- If using Frigate through Home Assistant, enable the web interface at port 1984.
- If using Docker, forward port 1984 before accessing the web interface.
- Click `stream` for the specific camera to see if the camera's stream is being received.
- Check Video Codec:
- If the camera stream works in go2rtc but not in your browser, the video codec might be unsupported.
- If using H265, switch to H264. Refer to [video codec compatibility](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#codecs-madness) in go2rtc documentation.
- If unable to switch from H265 to H264, or if the stream format is different (e.g., MJPEG), re-encode the video using [FFmpeg parameters](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#source-ffmpeg). It supports rotating and resizing video feeds and hardware acceleration. Keep in mind that transcoding video from one format to another is a resource intensive task and you may be better off using the built-in jsmpeg view.
```yaml
go2rtc:
streams:
back:
- rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
- "ffmpeg:back#video=h264#hardware"
- "ffmpeg:back#video=h264"
```
- Switch to FFmpeg if needed:
- Some camera streams may need to use the ffmpeg module in go2rtc. This has the downside of slower startup times, but has compatibility with more stream types.
Some camera streams may need to use the ffmpeg module in go2rtc. This has the downside of slower startup times, but has compatibility with more stream types.
```yaml
go2rtc:
streams:
@@ -58,9 +45,8 @@ After adding this to the config, restart Frigate and try to watch the live strea
- ffmpeg:rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
```
- If you can see the video but do not have audio, this is most likely because your camera's audio stream codec is not AAC.
- If possible, update your camera's audio settings to AAC in your camera's firmware.
- If your cameras do not support AAC audio, you will need to tell go2rtc to re-encode the audio to AAC on demand if you want audio. This will use additional CPU and add some latency. To add AAC audio on demand, you can update your go2rtc config as follows:
If you can see the video but do not have audio, this is most likely because your camera's audio stream is not AAC. If possible, update your camera's audio settings to AAC. If your cameras do not support AAC audio, you will need to tell go2rtc to re-encode the audio to AAC on demand if you want audio. This will use additional CPU and add some latency. To add AAC audio on demand, you can update your go2rtc config as follows:
```yaml
go2rtc:
streams:
@@ -76,7 +62,7 @@ After adding this to the config, restart Frigate and try to watch the live strea
streams:
back:
- rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
- "ffmpeg:back#video=h264#audio=aac#hardware"
- "ffmpeg:back#video=h264#audio=aac"
```
When using the ffmpeg module, you would add AAC audio like this:
@@ -85,20 +71,16 @@ After adding this to the config, restart Frigate and try to watch the live strea
go2rtc:
streams:
back:
- "ffmpeg:rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2#video=copy#audio=copy#audio=aac#hardware"
- "ffmpeg:rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2#video=copy#audio=copy#audio=aac"
```
:::warning
To access the go2rtc stream externally when utilizing the Frigate Add-On (for
instance through VLC), you must first enable the RTSP Restream port.
You can do this by visiting the Frigate Add-On configuration page within Home
Assistant and revealing the hidden options under the "Show disabled ports"
section.
To access the go2rtc stream externally when utilizing the Frigate Add-On (for instance through VLC), you must first enable the RTSP Restream port. You can do this by visiting the Frigate Add-On configuration page within Home Assistant and revealing the hidden options under the "Show disabled ports" section.
:::
## Next steps
1. If the stream you added to go2rtc is also used by Frigate for the `record` or `detect` role, you can migrate your config to pull from the RTSP restream to reduce the number of connections to your camera as shown [here](/configuration/restream#reduce-connections-to-camera).
2. You may also prefer to [setup WebRTC](/configuration/live#webrtc-extra-configuration) for slightly lower latency than MSE. Note that WebRTC only supports h264 and specific audio formats and may require opening ports on your router.
1. You may also prefer to [setup WebRTC](/configuration/live#webrtc-extra-configuration) for slightly lower latency than MSE. Note that WebRTC only supports h264 and specific audio formats.

View File

@@ -5,17 +5,9 @@ title: Getting started
# Getting Started
:::tip
If you already have an environment with Linux and Docker installed, you can continue to [Installing Frigate](#installing-frigate) below.
If you already have Frigate installed in Docker or as a Home Assistant addon, you can continue to [Configuring Frigate](#configuring-frigate) below.
:::
## Setting up hardware
This section guides you through setting up a server with Debian Bookworm and Docker.
This section guides you through setting up a server with Debian Bookworm and Docker. If you already have an environment with Linux and Docker installed, you can continue to [Installing Frigate](#installing-frigate) below.
### Install Debian 12 (Bookworm)
@@ -85,19 +77,20 @@ This section shows how to create a minimal directory structure for a Docker inst
### Setup directories
Frigate will create a config file if one does not exist on the initial startup. The following directory structure is the bare minimum to get started. Once Frigate is running, you can use the built-in config editor which supports config validation.
Frigate requires a valid config file to start. The following directory structure is the bare minimum to get started. Once Frigate is running, you can use the built-in config editor which supports config validation.
```
.
├── docker-compose.yml
├── config/
│ └── config.yml
└── storage/
```
This will create the above structure:
```bash
mkdir storage config && touch docker-compose.yml
mkdir storage config && touch docker-compose.yml config/config.yml
```
If you are setting up Frigate on a Linux device via SSH, you can use [nano](https://itsfoss.com/nano-editor-guide/) to edit the following files. If you prefer to edit remote files with a full editor instead of a terminal, I recommend using [Visual Studio Code](https://code.visualstudio.com/) with the [Remote SSH extension](https://code.visualstudio.com/docs/remote/ssh-tutorial).
@@ -124,11 +117,27 @@ services:
tmpfs:
size: 1000000000
ports:
- "8971:8971"
- "8080:8080"
- "8554:8554" # RTSP feeds
```
Now you should be able to start Frigate by running `docker compose up -d` from within the folder containing `docker-compose.yml`. On startup, an admin user and password will be created and outputted in the logs. You can see this by running `docker logs frigate`. Frigate should now be accessible at `https://server_ip:8971` where you can login with the `admin` user and finish the configuration using the built-in configuration editor.
`config.yml`
```yaml
mqtt:
enabled: False
cameras:
dummy_camera: # <--- this will be changed to your actual camera later
enabled: False
ffmpeg:
inputs:
- path: rtsp://127.0.0.1:554/rtsp
roles:
- detect
```
Now you should be able to start Frigate by running `docker compose up -d` from within the folder containing `docker-compose.yml`. On startup, an admin user and password will be created and outputted in the logs. You can see this by running `docker logs frigate`. Frigate should now be accessible at `https://server_ip:8080` where you can login with the `admin` user and finish the configuration using the built-in configuration editor.
## Configuring Frigate
@@ -238,7 +247,7 @@ Now that you know where you need to mask, use the "Mask & Zone creator" in the o
:::warning
Note that motion masks should not be used to mark out areas where you do not want objects to be detected or to reduce false positives. They do not alter the image sent to object detection, so you can still get tracked objects, alerts, and detections in areas with motion masks. These only prevent motion in these areas from initiating object detection.
Note that motion masks should not be used to mark out areas where you do not want objects to be detected or to reduce false positives. They do not alter the image sent to object detection, so you can still get events and detections in areas with motion masks. These only prevent motion in these areas from initiating object detection.
:::
@@ -265,11 +274,13 @@ cameras:
- 0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432
```
### Step 6: Enable recordings
### Step 6: Enable recording and/or snapshots
In order to review activity in the Frigate UI, recordings need to be enabled.
In order to see Events in the Frigate UI, either snapshots or record will need to be enabled.
To enable recording video, add the `record` role to a stream and enable it in the config. If record is disabled in the config, it won't be possible to enable it in the UI.
#### Record
To enable recording video, add the `record` role to a stream and enable it in the config. If record is disabled in the config, turning it on via the UI will not have any effect.
```yaml
mqtt: ...
@@ -294,15 +305,27 @@ cameras:
If you don't have separate streams for detect and record, you would just add the record role to the list on the first input.
:::note
By default, Frigate will retain video of all events for 10 days. The full set of options for recording can be found [here](../configuration/reference.md).
If you only define one stream in your `inputs` and do not assign a `detect` role to it, Frigate will automatically assign it the `detect` role. Frigate will always decode a stream to support motion detection, Birdseye, the API image endpoints, and other features, even if you have disabled object detection with `enabled: False` in your config's `detect` section.
#### Snapshots
If you only plan to use Frigate for recording, it is still recommended to define a `detect` role for a low resolution stream to minimize resource usage from the required stream decoding.
To enable snapshots of your events, just enable it in the config. Snapshots are taken from the detect stream because it is the only stream decoded.
:::
```yaml
mqtt: ...
By default, Frigate will retain video of all tracked objects for 10 days. The full set of options for recording can be found [here](../configuration/reference.md).
detectors: ...
cameras:
name_of_your_camera: ...
detect: ...
record: ...
snapshots: # <----- Enable snapshots
enabled: True
motion: ...
```
By default, Frigate will retain snapshots of all events for 10 days. The full set of options for snapshots can be found [here](../configuration/reference.md).
### Step 7: Complete config
@@ -313,7 +336,6 @@ At this point you have a complete config with basic functionality. You can see t
Now that you have a working install, you can use the following documentation for additional features:
1. [Configuring go2rtc](configuring_go2rtc.md) - Additional live view options and RTSP relay
2. [Zones](../configuration/zones.md)
3. [Review](../configuration/review.md)
4. [Masks](../configuration/masks.md)
5. [Home Assistant Integration](../integrations/home-assistant.md) - Integrate with Home Assistant
2. [Home Assistant Integration](../integrations/home-assistant.md) - Integrate with Home Assistant
3. [Masks](../configuration/masks.md)
4. [Zones](../configuration/zones.md)

View File

@@ -5,19 +5,19 @@ title: Home Assistant notifications
The best way to get started with notifications for Frigate is to use the [Blueprint](https://community.home-assistant.io/t/frigate-mobile-app-notifications-2-0/559732). You can use the yaml generated from the Blueprint as a starting point and customize from there.
It is generally recommended to trigger notifications based on the `frigate/reviews` mqtt topic. This provides the event_id(s) needed to fetch [thumbnails/snapshots/clips](../integrations/home-assistant.md#notification-api) and other useful information to customize when and where you want to receive alerts. The data is published in the form of a change feed, which means you can reference the "previous state" of the object in the `before` section and the "current state" of the object in the `after` section. You can see an example [here](../integrations/mqtt.md#frigateevents).
It is generally recommended to trigger notifications based on the `frigate/events` mqtt topic. This provides the event_id needed to fetch [thumbnails/snapshots/clips](../integrations/home-assistant.md#notification-api) and other useful information to customize when and where you want to receive alerts. The data is published in the form of a change feed, which means you can reference the "previous state" of the object in the `before` section and the "current state" of the object in the `after` section. You can see an example [here](../integrations/mqtt.md#frigateevents).
Here is a simple example of a notification automation of tracked objects 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.
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.
```yaml
automation:
- alias: Notify of tracked object
- alias: Notify of events
trigger:
platform: mqtt
topic: frigate/events
action:
- service: notify.mobile_app_pixel_3
data:
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'
@@ -33,18 +33,48 @@ automation:
description: ""
trigger:
- platform: mqtt
topic: frigate/reviews
payload: alert
value_template: "{{ value_json['after']['severity'] }}"
topic: frigate/events
payload: new
value_template: "{{ value_json.type }}"
action:
- service: notify.mobile_app_iphone
data:
message: 'A {{trigger.payload_json["after"]["data"]["objects"] | sort | join(", ") | title}} was detected.'
message: 'A {{trigger.payload_json["after"]["label"]}} was detected.'
data:
image: >-
https://your.public.hass.address.com/api/frigate/notifications/{{trigger.payload_json["after"]["data"]["detections"][0]}}/thumbnail.jpg
https://your.public.hass.address.com/api/frigate/notifications/{{trigger.payload_json["after"]["id"]}}/thumbnail.jpg
tag: '{{trigger.payload_json["after"]["id"]}}'
when: '{{trigger.payload_json["after"]["start_time"]|int}}'
entity_id: camera.{{trigger.payload_json["after"]["camera"] | replace("-","_") | lower}}
mode: single
```
## Conditions
Conditions with the `before` and `after` values allow a high degree of customization for automations.
When a person enters a zone named yard
```yaml
condition:
- "{{ trigger.payload_json['after']['label'] == 'person' }}"
- "{{ 'yard' in trigger.payload_json['after']['entered_zones'] }}"
```
When a person leaves a zone named yard
```yaml
condition:
- "{{ trigger.payload_json['after']['label'] == 'person' }}"
- "{{ 'yard' in trigger.payload_json['before']['current_zones'] }}"
- "{{ not 'yard' in trigger.payload_json['after']['current_zones'] }}"
```
Notify for dogs in the front with a high top score
```yaml
condition:
- "{{ trigger.payload_json['after']['label'] == 'dog' }}"
- "{{ trigger.payload_json['after']['camera'] == 'front' }}"
- "{{ trigger.payload_json['after']['top_score'] > 0.98 }}"
```

View File

@@ -3,38 +3,25 @@ id: reverse_proxy
title: Setting up a reverse proxy
---
This guide outlines the basic configuration steps needed to set up a reverse proxy in front of your Frigate instance.
This guide outlines the basic configuration steps needed to expose your Frigate UI to the internet.
A common way of accomplishing this is to use a reverse proxy webserver between your router and your Frigate instance.
A reverse proxy accepts HTTP requests from the public internet and redirects them transparently to internal webserver(s) on your network.
A reverse proxy is typically needed if you want to set up Frigate on a custom URL, on a subdomain, or on a host serving multiple sites. It could also be used to set up your own authentication provider or for more advanced HTTP routing.
The suggested steps are:
Before setting up a reverse proxy, check if any of the built-in functionality in Frigate suits your needs:
|Topic|Docs|
|-|-|
|TLS|Please see the `tls` [configuration option](../configuration/tls.md)|
|Authentication|Please see the [authentication](../configuration/authentication.md) documentation|
|IPv6|[Enabling IPv6](../configuration/advanced.md#enabling-ipv6)
**Note about TLS**
When using a reverse proxy, the TLS session is usually terminated at the proxy, sending the internal request over plain HTTP. If this is the desired behavior, TLS must first be disabled in Frigate, or you will encounter an HTTP 400 error: "The plain HTTP request was sent to HTTPS port."
To disable TLS, set the following in your Frigate configuration:
```yml
tls:
enabled: false
```
- **Configure** a 'proxy' HTTP webserver (such as [Apache2](https://httpd.apache.org/docs/current/) or [NPM](https://github.com/NginxProxyManager/nginx-proxy-manager)) and only expose ports 80/443 from this webserver to the internet
- **Encrypt** content from the proxy webserver by installing SSL (such as with [Let's Encrypt](https://letsencrypt.org/)). Note that SSL is then not required on your Frigate webserver as the proxy encrypts all requests for you
- **Restrict** access to your Frigate instance at the proxy using, for example, password authentication
:::warning
A reverse proxy can be used to secure access to an internal web server, but the user will be entirely reliant on the steps they have taken. You must ensure you are following security best practices.
A reverse proxy can be used to secure access to an internal webserver but the user will be entirely reliant
on the steps they have taken. You must ensure you are following security best practices.
This page does not attempt to outline the specific steps needed to secure your internal website.
Please use your own knowledge to assess and vet the reverse proxy software before you install anything on your system.
:::
## Proxies
There are many solutions available to implement reverse proxies and the community is invited to help out documenting others through a contribution to this page.
* [Apache2](#apache2-reverse-proxy)
* [Nginx](#nginx-reverse-proxy)
* [Traefik](#traefik-reverse-proxy)
There are several technologies available to implement reverse proxies. This document currently suggests one, using Apache2,
and the community is invited to document others through a contribution to this page.
## Apache2 Reverse Proxy
@@ -51,20 +38,20 @@ Here we access Frigate via https://cctv.mydomain.co.uk
ServerName cctv.mydomain.co.uk
ProxyPreserveHost On
ProxyPass "/" "http://frigatepi.local:8971/"
ProxyPassReverse "/" "http://frigatepi.local:8971/"
ProxyPass "/" "http://frigatepi.local:8080/"
ProxyPassReverse "/" "http://frigatepi.local:8080/"
ProxyPass /ws ws://frigatepi.local:8971/ws
ProxyPassReverse /ws ws://frigatepi.local:8971/ws
ProxyPass /ws ws://frigatepi.local:8080/ws
ProxyPassReverse /ws ws://frigatepi.local:8080/ws
ProxyPass /live/ ws://frigatepi.local:8971/live/
ProxyPassReverse /live/ ws://frigatepi.local:8971/live/
ProxyPass /live/ ws://frigatepi.local:8080/live/
ProxyPassReverse /live/ ws://frigatepi.local:8080/live/
RewriteEngine on
RewriteCond %{HTTP:Upgrade} =websocket [NC]
RewriteRule /(.*) ws://frigatepi.local:8971/$1 [P,L]
RewriteRule /(.*) ws://frigatepi.local:8080/$1 [P,L]
RewriteCond %{HTTP:Upgrade} !=websocket [NC]
RewriteRule /(.*) http://frigatepi.local:8971/$1 [P,L]
RewriteRule /(.*) http://frigatepi.local:8080/$1 [P,L]
</VirtualHost>
```
@@ -114,7 +101,7 @@ This is set in `$server` and `$port` this should match your ports you have expos
server {
set $forward_scheme http;
set $server "192.168.100.2"; # FRIGATE SERVER LOCATION
set $port 8971;
set $port 8080;
listen 80;
listen 443 ssl http2;
@@ -154,26 +141,3 @@ The settings below enabled connection upgrade, sets up logging (optional) and pr
}
```
## Traefik Reverse Proxy
This example shows how to add a `label` to the Frigate Docker compose file, enabling Traefik to automatically discover your Frigate instance.
Before using the example below, you must first set up Traefik with the [Docker provider](https://doc.traefik.io/traefik/providers/docker/)
```yml
services:
frigate:
container_name: frigate
image: ghcr.io/blakeblackshear/frigate:stable
...
...
labels:
- "traefik.enable=true"
- "traefik.http.services.frigate.loadbalancer.server.port=8971"
- "traefik.http.routers.frigate.rule=Host(`traefik.example.com`)"
```
The above configuration will create a "service" in Traefik, automatically adding your container's IP on port 8971 as a backend.
It will also add a router, routing requests to "traefik.example.com" to your local container.
Note that with this approach, you don't need to expose any ports for the Frigate instance since all traffic will be routed over the internal Docker network.

View File

@@ -0,0 +1,526 @@
---
id: api
title: HTTP API
---
A web server is available on port 5000 with the following endpoints.
## Management & Information
### `GET /api/config`
A json representation of your configuration
### `POST /api/restart`
Restarts Frigate process.
### `GET /api/stats`
Contains some granular debug info that can be used for sensors in Home Assistant.
Sample response:
```json
{
/* Per Camera Stats */
"cameras": {
"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": "0.10.1-8883709",
"latest_version": "0.10.1",
/* Storage data in MB for important locations */
"storage": {
"/media/frigate/clips": {
"total": 1000,
"used": 700,
"free": 300,
"mnt_type": "ext4"
},
"/media/frigate/recordings": {
"total": 1000,
"used": 700,
"free": 300,
"mnt_type": "ext4"
},
"/tmp/cache": {
"total": 256,
"used": 100,
"free": 156,
"mnt_type": "tmpfs"
},
"/dev/shm": {
"total": 256,
"used": 100,
"free": 156,
"mnt_type": "tmpfs"
}
}
},
"cpu_usages": {
"pid": {
"cmdline": "ffmpeg...",
"cpu": "5.0",
"cpu_average": "3.0",
"mem": "0.5"
}
},
"gpu_usages": {
"gpu-type": {
"gpu": "17%",
"mem": "18%"
}
}
}
```
### `GET /api/version`
Version info
### `GET /api/ffprobe`
Get ffprobe output for camera feed paths.
| param | Type | Description |
| ------- | ------ | ---------------------------------- |
| `paths` | string | `,` separated list of camera paths |
### `GET /api/<camera_name>/ptz/info`
Get PTZ info for the camera.
## Camera Media
### `GET /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:
| param | Type | Description |
| ----------- | ---- | ------------------------------------------------------------------ |
| `fps` | int | Frame rate |
| `h` | int | Height in pixels |
| `bbox` | int | Show bounding boxes for detected objects (0 or 1) |
| `timestamp` | int | Print the timestamp in the upper left (0 or 1) |
| `zones` | int | Draw the zones on the image (0 or 1) |
| `mask` | int | Overlay the mask on the image (0 or 1) |
| `motion` | int | Draw blue boxes for areas with detected motion (0 or 1) |
| `regions` | int | Draw 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 `/api/back?h=1080`. You can also increase the FPS by appending `fps=frame-rate` to the URL such as `/api/back?fps=10` or both with `?fps=10&h=1000`.
### `GET /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:
| param | Type | Description |
| ----------- | ---- | ------------------------------------------------------------------ |
| `h` | int | Height in pixels |
| `bbox` | int | Show bounding boxes for detected objects (0 or 1) |
| `timestamp` | int | Print the timestamp in the upper left (0 or 1) |
| `zones` | int | Draw the zones on the image (0 or 1) |
| `mask` | int | Overlay the mask on the image (0 or 1) |
| `motion` | int | Draw blue boxes for areas with detected motion (0 or 1) |
| `regions` | int | Draw green boxes for areas where object detection was run (0 or 1) |
| `quality` | int | Jpeg encoding quality (0-100). Defaults to 70. |
Example parameters:
- `h=300`: resizes the image to 300 pixels tall
### `GET /api/<camera_name>/<label>/thumbnail.jpg`
Returns the thumbnail from the latest event for the given camera and label combo. Using `any` as the label will return the latest thumbnail regardless of type.
### `GET /api/<camera_name>/<label>/clip.mp4`
Returns the clip from the latest event for the given camera and label combo. Using `any` as the label will return the latest clip regardless of type.
### `GET /api/<camera_name>/<label>/snapshot.jpg`
Returns the snapshot image from the latest event for the given camera and label combo. Using `any` as the label will return the latest thumbnail regardless of type.
### `GET /api/<camera_name>/grid.jpg`
Returns the latest camera image with the regions grid overlaid.
| param | Type | Description |
| ------------ | ----- | ------------------------------------------------------------------------------------------ |
| `color` | str | The color of the grid (red,green,blue,black,white). Defaults to "green". |
| `font_scale` | float | Font scale. Can be used to increase font size on high resolution cameras. Defaults to 0.5. |
### `GET /clips/<camera>-<id>.jpg`
JPG snapshot for the given camera and event id.
## Events
### `GET /api/events`
Events from the database. Accepts the following query string parameters:
| param | Type | Description |
| -------------------- | ----- | ----------------------------------------------------- |
| `before` | int | Epoch time |
| `after` | int | Epoch time |
| `cameras` | str | , separated list of cameras |
| `labels` | str | , separated list of labels |
| `zones` | str | , separated list of zones |
| `limit` | int | Limit the number of events returned |
| `has_snapshot` | int | Filter to events that have snapshots (0 or 1) |
| `has_clip` | int | Filter to events that have clips (0 or 1) |
| `include_thumbnails` | int | Include thumbnails in the response (0 or 1) |
| `in_progress` | int | Limit to events in progress (0 or 1) |
| `time_range` | str | Time range in format after,before (00:00,24:00) |
| `timezone` | str | Timezone to use for time range |
| `min_score` | float | Minimum score of the event |
| `max_score` | float | Maximum score of the event |
| `is_submitted` | int | Filter events that are submitted to Frigate+ (0 or 1) |
| `min_length` | float | Minimum length of the event |
| `max_length` | float | Maximum length of the event |
### `GET /api/events/summary`
Returns summary data for events in the database. Used by the Home Assistant integration.
### `GET /api/events/<id>`
Returns data for a single event.
### `DELETE /api/events/<id>`
Permanently deletes the event along with any clips/snapshots.
### `POST /api/events/<id>/retain`
Sets retain to true for the event id.
### `POST /api/events/<id>/plus`
Submits the snapshot of the event to Frigate+ for labeling.
| param | Type | Description |
| -------------------- | ---- | ---------------------------------- |
| `include_annotation` | int | Submit annotation to Frigate+ too. |
### `PUT /api/events/<id>/false_positive`
Submits the snapshot of the event to Frigate+ for labeling and adds the detection as a false positive.
### `DELETE /api/events/<id>/retain`
Sets retain to false for the event id (event may be deleted quickly after removing).
### `POST /api/events/<id>/sub_label`
Set a sub label for an event. For example to update `person` -> `person's name` if they were recognized with facial recognition.
Sub labels must be 100 characters or shorter.
```json
{
"subLabel": "some_string",
"subLabelScore": 0.79
}
```
### `GET /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.
### `GET /api/events/<id>/clip.mp4`
Returns the clip for the event id. Works after the event has ended.
### `GET /api/events/<id>/snapshot-clean.png`
Returns the clean snapshot image for the event id. Only works if `snapshots` and `clean_copy` are enabled in the config.
| param | Type | Description |
| ---------- | ---- | ------------------ |
| `download` | bool | Download the image |
### `GET /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:
| param | Type | Description |
| ----------- | ---- | ------------------------------------------------- |
| `h` | int | Height in pixels |
| `bbox` | int | Show bounding boxes for detected objects (0 or 1) |
| `timestamp` | int | Print the timestamp in the upper left (0 or 1) |
| `crop` | int | Crop the snapshot to the (0 or 1) |
| `quality` | int | Jpeg encoding quality (0-100). Defaults to 70. |
| `download` | bool | Download the image |
### `POST /api/events/<camera_name>/<label>/create`
Create a manual event with a given `label` (ex: doorbell press) to capture a specific event besides an object being detected.
:::warning
Recording retention config still applies to manual events, if frigate is configured with `mode: motion` then the manual event will only keep recording segments when motion occurred.
:::
**Optional Body:**
```json
{
"sub_label": "some_string", // add sub label to event
"duration": 30, // predetermined length of event (default: 30 seconds) or can be to null for indeterminate length event
"include_recording": true, // whether the event should save recordings along with the snapshot that is taken
"draw": {
// optional annotations that will be drawn on the snapshot
"boxes": [
{
"box": [0.5, 0.5, 0.25, 0.25], // box consists of x, y, width, height which are on a scale between 0 - 1
"color": [255, 0, 0], // color of the box, default is red
"score": 100 // optional score associated with the box
}
]
}
}
```
**Success Response:**
```json
{
"event_id": "1682970645.13116-1ug7ns",
"message": "Successfully created event.",
"success": true
}
```
### `PUT /api/events/<event_id>/end`
End a specific manual event without a predetermined length.
### `GET /api/events/<id>/preview.gif`
Gif covering the first 20 seconds of a specific event.
## Previews
Previews are low res / fps videos that are quickly scrubbable and can be used for notifications or time-lapses.
### `GET /api/preview/<camera>/start/<start-timestamp>/end/<end-timestamp>`
Metadata about previews for this time range.
### `GET /api/preview/<year>-<month>/<day>/<hour>/<camera>/<timezone>`
Metadata about previews for this hour
### `GET /api/preview/<camera>/start/<start-timestamp>/end/<end-timestamp>`
List of frames in the preview cache for the time range. Previews are only kept in the cache until they are combined into an mp4 at the end of the hour.
### `GET /api/preview/<file_name>/thumbnail.jpg`
Specific preview frame from preview cache.
### `GET /<camera>/start/<start-timestamp>/end/<end-timestamp>/preview.gif`
Gif made from preview video / frames during this time range
## Recordings
### `GET /vod/<year>-<month>/<day>/<hour>/<camera>/master.m3u8`
HTTP Live Streaming Video on Demand URL for the specified hour and camera. Can be viewed in an application like VLC.
### `GET /vod/event/<event-id>/index.m3u8`
HTTP Live Streaming Video on Demand URL for the specified event. Can be viewed in an application like VLC.
### `GET /vod/<camera>/start/<start-timestamp>/end/<end-timestamp>/index.m3u8`
HTTP Live Streaming Video on Demand URL for the camera with the specified time range. Can be viewed in an application like VLC.
### `POST /api/export/<camera>/start/<start-timestamp>/end/<end-timestamp>`
Export recordings from `start-timestamp` to `end-timestamp` for `camera` as a single mp4 file. These recordings will be exported to the `/media/frigate/exports` folder.
It is also possible to export this recording as a time-lapse.
**Optional Body:**
```json
{
"playback": "realtime" // playback factor: realtime or timelapse_25x
}
```
### `DELETE /api/export/<export_name>`
Delete an export from disk.
### `PATCH /api/export/<export_name_current>/<export_name_new>`
Renames an export.
### `GET /api/<camera_name>/recordings/summary`
Hourly summary of recordings data for a camera.
### `GET /api/<camera_name>/recordings`
Get recording segment details for the given timestamp range.
| param | Type | Description |
| -------- | ---- | ------------------------------------- |
| `after` | int | Unix timestamp for beginning of range |
| `before` | int | Unix timestamp for end of range |
### `GET /api/<camera_name>/recordings/<frame_time>/snapshot.png`
Returns the snapshot image from the specific point in that cameras recordings.
## Reviews
### `GET /api/review`
Reviews from the database. Accepts the following query string parameters:
| param | Type | Description |
| ---------- | ---- | -------------------------------------------------------------- |
| `before` | int | Epoch time |
| `after` | int | Epoch time |
| `cameras` | str | , separated list of cameras |
| `labels` | str | , separated list of labels |
| `zones` | str | , separated list of zones |
| `reviewed` | int | Include items that have been reviewed (0 or 1) |
| `limit` | int | Limit the number of events returned |
| `severity` | str | Limit items to severity (alert, detection, significant_motion) |
### `GET /api/review/summary`
Summary of reviews for the last 30 days. Accepts the following query string parameters:
| param | Type | Description |
| ---------- | ---- | --------------------------- |
| `cameras` | str | , separated list of cameras |
| `labels` | str | , separated list of labels |
| `timezone` | str | Timezone name |
### `POST /api/reviews/viewed`
Mark item(s) as reviewed.
**Required Body:**
```json
{
"ids": ["123", "456"] // , separated list of review IDs
}
```
### `DELETE /api/review/<id>/viewed`
Mark an item as not reviewed.
### `POST /api/reviews/delete`
Delete review items.
**Required Body:**
```json
{
"ids": ["123", "456"] // , separated list of review IDs
}
```
### `GET /review/activity/motion`
Get the motion activity for camera(s) during a specified time period.
| param | Type | Description |
| --------- | ---- | --------------------------- |
| `before` | int | Epoch time |
| `after` | int | Epoch time |
| `cameras` | str | , separated list of cameras |
### `GET /review/activity/audio`
Get the audio activity for camera(s) during a specified time period.
| param | Type | Description |
| --------- | ---- | --------------------------- |
| `before` | int | Epoch time |
| `after` | int | Epoch time |
| `cameras` | str | , separated list of cameras |
## Timeline
### `GET /api/timeline`
Timeline of key moments of an event(s) from the database. Accepts the following query string parameters:
| param | Type | Description |
| ----------- | ---- | ----------------------------------- |
| `camera` | str | Name of camera |
| `source_id` | str | ID of tracked object |
| `limit` | int | Limit the number of events returned |

View File

@@ -25,7 +25,7 @@ Available via HACS as a default repository. To install:
- Use [HACS](https://hacs.xyz/) to install the integration:
```
Home Assistant > HACS > Click in the Search bar and type "Frigate" > Frigate
Home Assistant > HACS > Integrations > "Explore & Add Integrations" > Frigate
```
- Restart Home Assistant.
@@ -149,7 +149,7 @@ Home Assistant > Configuration > Integrations > Frigate > Options
## Entities Provided
| Platform | Description |
| --------------- | ------------------------------------------------------------------------------- |
| --------------- | --------------------------------------------------------------------------------- |
| `camera` | Live camera stream (requires RTSP). |
| `image` | Image of the latest detected object for each camera. |
| `sensor` | States to monitor Frigate performance, object counts for all zones and cameras. |
@@ -160,7 +160,7 @@ Home Assistant > Configuration > Integrations > Frigate > Options
The integration provides:
- Browsing tracked object recordings with thumbnails
- Browsing event recordings with thumbnails
- Browsing snapshots
- Browsing recordings by month, day, camera, time
@@ -183,19 +183,19 @@ For clips to be castable to media devices, audio is required and may need to be
Many people do not want to expose Frigate to the web, so the integration creates some public API endpoints that can be used for notifications.
To load a thumbnail for a tracked object:
To load a thumbnail for an event:
```
https://HA_URL/api/frigate/notifications/<event-id>/thumbnail.jpg
```
To load a snapshot for a tracked object:
To load a snapshot for an event:
```
https://HA_URL/api/frigate/notifications/<event-id>/snapshot.jpg
```
To load a video clip of a tracked object:
To load a video clip of an event:
```
https://HA_URL/api/frigate/notifications/<event-id>/clip.mp4
@@ -215,7 +215,7 @@ For advanced usecases, this behavior can be changed with the [RTSP URL
template](#options) option. When set, this string will override the default stream
address that is derived from the default behavior described above. This option supports
[jinja2 templates](https://jinja.palletsprojects.com/) and has the `camera` dict
variables from [Frigate API](../integrations/api)
variables from [Frigate API](api.md)
available for the template. Note that no Home Assistant state is available to the
template, only the camera dict from Frigate.

View File

@@ -11,7 +11,7 @@ These are the MQTT messages generated by Frigate. The default topic_prefix is `f
Designed to be used as an availability topic with Home Assistant. Possible message are:
"online": published when Frigate is running (on startup)
"offline": published after Frigate has stopped
"offline": published right before Frigate stops
### `frigate/restart`
@@ -19,7 +19,7 @@ Causes Frigate to exit. Docker should be configured to automatically restart the
### `frigate/events`
Message published for each changed tracked object. 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 tracked object ends, a final message is published with `end_time` set.
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.
```json
{
@@ -45,7 +45,6 @@ Message published for each changed tracked object. The first message is publishe
"thumbnail": null,
"has_snapshot": false,
"has_clip": false,
"active": true, // convenience attribute, this is strictly opposite of "stationary"
"stationary": false, // whether or not the object is considered stationary
"motionless_count": 0, // number of frames the object has been motionless
"position_changes": 2, // number of times the object has moved from a stationary position
@@ -75,7 +74,6 @@ Message published for each changed tracked object. The first message is publishe
"thumbnail": null,
"has_snapshot": false,
"has_clip": false,
"active": true, // convenience attribute, this is strictly opposite of "stationary"
"stationary": false, // whether or not the object is considered stationary
"motionless_count": 0, // number of frames the object has been motionless
"position_changes": 2, // number of times the object has changed position
@@ -109,13 +107,15 @@ Message published for each changed review item. The first message is published w
"severity": "detection",
"thumb_path": "/media/frigate/clips/review/thumb-front_cam-1718987129.308396-fqk5ka.webp",
"data": {
"detections": [
// list of event IDs
"detections": [ // list of event IDs
"1718987128.947436-g92ztx",
"1718987148.879516-d7oq7r",
"1718987126.934663-q5ywpt"
],
"objects": ["person", "car"],
"objects": [
"person",
"car"
],
"sub_labels": [],
"zones": [],
"audio": []
@@ -134,31 +134,23 @@ Message published for each changed review item. The first message is published w
"1718987148.879516-d7oq7r",
"1718987126.934663-q5ywpt"
],
"objects": ["person", "car"],
"sub_labels": ["Bob"],
"zones": ["front_yard"],
"objects": [
"person",
"car"
],
"sub_labels": [],
"zones": [
"front_yard"
],
"audio": []
}
}
}
```
### `frigate/stats`
Same data available at `/api/stats` published at a configurable interval.
### `frigate/camera_activity`
Returns data about each camera, its current features, and if it is detecting motion, objects, etc. Can be triggered by publising to `frigate/onConnect`
### `frigate/notifications/set`
Topic to turn notifications on and off. Expected values are `ON` and `OFF`.
### `frigate/notifications/state`
Topic with current state of notifications. Published values are `ON` and `OFF`.
## Frigate Camera Topics
### `frigate/<camera_name>/<object_name>`
@@ -166,23 +158,11 @@ Topic with current state of notifications. Published values are `ON` and `OFF`.
Publishes the count of objects for the camera for use as a sensor in Home Assistant.
`all` can be used as the object_name for the count of all objects for the camera.
### `frigate/<camera_name>/<object_name>/active`
Publishes the count of active objects for the camera for use as a sensor in Home
Assistant. `all` can be used as the object_name for the count of all active objects
for the camera.
### `frigate/<zone_name>/<object_name>`
Publishes the count of objects for the zone for use as a sensor in Home Assistant.
`all` can be used as the object_name for the count of all objects for the zone.
### `frigate/<zone_name>/<object_name>/active`
Publishes the count of active objects for the zone for use as a sensor in Home
Assistant. `all` can be used as the object_name for the count of all objects for the
zone.
### `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

View File

@@ -19,17 +19,17 @@ Once logged in, you can generate an API key for Frigate in Settings.
### Set your API key
In Frigate, you can use an environment variable or a docker secret named `PLUS_API_KEY` to enable the `Frigate+` buttons on the Explore page. Home Assistant Addon users can set it under Settings > Addons > Frigate NVR > Configuration > Options (be sure to toggle the "Show unused optional configuration options" switch).
In Frigate, you can use an environment variable or a docker secret named `PLUS_API_KEY` to enable the `SEND TO FRIGATE+` buttons on the events page. Home Assistant Addon users can set it under Settings > Addons > Frigate NVR > Configuration > Options (be sure to toggle the "Show unused optional configuration options" switch).
:::warning
You cannot use the `environment_vars` section of your Frigate configuration file to set this environment variable. It must be defined as an environment variable in the docker config or HA addon config.
You cannot use the `environment_vars` section of your configuration file to set this environment variable.
:::
## Submit examples
Once your API key is configured, you can submit examples directly from the Explore page in Frigate using the `Frigate+` button.
Once your API key is configured, you can submit examples directly from the events page in Frigate using the `SEND TO FRIGATE+` button.
:::note

View File

@@ -18,7 +18,3 @@ Please use your own knowledge to assess and vet them before you install anything
[Double Take](https://github.com/skrashevich/double-take) provides an unified UI and API for processing and training images for facial recognition.
It supports automatically setting the sub labels in Frigate for person objects that are detected and recognized.
This is a fork (with fixed errors and new features) of [original Double Take](https://github.com/jakowenko/double-take) project which, unfortunately, isn't being maintained by author.
## [Frigate telegram](https://github.com/OldTyT/frigate-telegram)
[Frigate telegram](https://github.com/OldTyT/frigate-telegram) makes it possible to send events from Frigate to Telegram. Events are sent as a message with a text description, video, and thumbnail.

View File

@@ -3,7 +3,7 @@ id: index
title: Models
---
<a href="https://frigate.video/plus" target="_blank" rel="nofollow">Frigate+</a> offers models trained on images submitted by Frigate+ users from their security cameras and is specifically designed for the way Frigate NVR analyzes video footage. These models offer higher accuracy with less resources. The images you upload are used to fine tune a baseline model trained from images uploaded by all Frigate+ users. This fine tuning process results in a model that is optimized for accuracy in your specific conditions.
<a href="https://plus.frigate.video" target="_blank" rel="nofollow">Frigate+</a> offers models trained on images submitted by Frigate+ users from their security cameras and is specifically designed for the way Frigate NVR analyzes video footage. These models offer higher accuracy with less resources. The images you upload are used to fine tune a baseline model trained from images uploaded by all Frigate+ users. This fine tuning process results in a model that is optimized for accuracy in your specific conditions.
:::info
@@ -33,7 +33,7 @@ Frigate+ models support a more relevant set of objects for security cameras. Cur
### Label attributes
Frigate has special handling for some labels when using Frigate+ models. `face`, `license_plate`, `amazon`, `ups`, and `fedex` are considered attribute labels which are not tracked like regular objects and do not generate review items directly. In addition, the `threshold` filter will have no effect on these labels. You should adjust the `min_score` and other filter values as needed.
Frigate has special handling for some labels when using Frigate+ models. `face`, `license_plate`, `amazon`, `ups`, and `fedex` are considered attribute labels which are not tracked like regular objects and do not generate events. In addition, the `threshold` filter will have no effect on these labels. You should adjust the `min_score` and other filter values as needed.
In order to have Frigate start using these attribute labels, you will need to add them to the list of objects to track:

View File

@@ -28,18 +28,6 @@ The USB coral has different IDs when it is uninitialized and initialized.
- When running Frigate in a VM, Proxmox lxc, etc. you must ensure both device IDs are mapped.
- When running HA OS you may need to run the Full Access version of the Frigate addon with the `Protected Mode` switch disabled so that the coral can be accessed.
### Synology 716+II running DSM 7.2.1-69057 Update 5
Some users have reported that this older device runs an older kernel causing issues with the coral not being detected. The following steps allowed it to be detected correctly:
1. Plug in the coral TPU in any of the USB ports on the NAS
2. Open the control panel - info screen. The coral TPU would be shown as a generic device.
3. Start the docker container with Coral TPU enabled in the config
4. The TPU would be detected but a few moments later it would disconnect.
5. While leaving the TPU device plugged in, restart the NAS using the reboot command in the UI. Do NOT unplug the NAS/power it off etc.
6. Open the control panel - info scree. The coral TPU will now be recognised as a USB Device - google inc
7. Start the frigate container. Everything should work now!
## USB Coral Detection Appears to be Stuck
The USB Coral can become stuck and need to be restarted, this can happen for a number of reasons depending on hardware and software setup. Some common reasons are:

View File

@@ -17,7 +17,7 @@ ffmpeg:
record: preset-record-generic-audio-aac
```
### I can't view recordings in the Web UI.
### I can't view events or recordings in the Web UI.
Ensure your cameras send h264 encoded video, or [transcode them](/configuration/restream.md).
@@ -28,7 +28,6 @@ You can open `chrome://media-internals/` in another tab and then try to playback
Frigate generally [recommends cameras with configurable sub streams](/frigate/hardware.md). However, if your camera does not have a sub stream that a suitable resolution, the main stream can be resized.
To do this efficiently the following setup is required:
1. A GPU or iGPU must be available to do the scaling.
2. [ffmpeg presets for hwaccel](/configuration/hardware_acceleration.md) must be used
3. Set the desired detection resolution for `detect -> width` and `detect -> height`.
@@ -57,44 +56,4 @@ SQLite does not work well on a network share, if the `/media` folder is mapped t
If MQTT isn't working in docker try using the IP of the device hosting the MQTT server instead of `localhost`, `127.0.0.1`, or `mosquitto.ix-mosquitto.svc.cluster.local`.
This is because Frigate does not run in host mode so localhost points to the Frigate container and not the host device's network.
### How do I know if my camera is offline
A camera being offline can be detected via MQTT or /api/stats, the camera_fps for any offline camera will be 0.
Also, Home Assistant will mark any offline camera as being unavailable when the camera is offline.
### How can I view the Frigate log files without using the Web UI?
Frigate manages logs internally as well as outputs directly to Docker via standard output. To view these logs using the CLI, follow these steps:
- Open a terminal or command prompt on the host running your Frigate container.
- Type the following command and press Enter:
```
docker logs -f frigate
```
This command tells Docker to show you the logs from the Frigate container.
Note: If you've given your Frigate container a different name, replace "frigate" in the command with your container's actual name. The "-f" option means the logs will continue to update in real-time as new entries are added. To stop viewing the logs, press `Ctrl+C`. If you'd like to learn more about using Docker logs, including additional options and features, you can explore Docker's [official documentation](https://docs.docker.com/engine/reference/commandline/logs/).
Alternatively, when you create the Frigate Docker container, you can bind a directory on the host to the mountpoint `/dev/shm/logs` to not only be able to persist the logs to disk, but also to be able to query them directly from the host using your favorite log parsing/query utility.
```
docker run -d \
--name frigate \
--restart=unless-stopped \
--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 \
-v /path/to/local/log/dir:/dev/shm/logs \
-e FRIGATE_RTSP_PASSWORD='password' \
-p 5000:5000 \
-p 8554:8554 \
-p 8555:8555/tcp \
-p 8555:8555/udp \
ghcr.io/blakeblackshear/frigate:stable
```
This is because, by default, Frigate does not run in host mode so localhost points to the Frigate container and not the host device's network.

102
docs/docusaurus.config.js Normal file
View File

@@ -0,0 +1,102 @@
const path = require("path");
module.exports = {
title: "Frigate",
tagline: "NVR With Realtime Object Detection for IP Cameras",
url: "https://docs.frigate.video",
baseUrl: "/",
onBrokenLinks: "throw",
onBrokenMarkdownLinks: "warn",
favicon: "img/favicon.ico",
organizationName: "blakeblackshear",
projectName: "frigate",
themes: ["@docusaurus/theme-mermaid"],
markdown: {
mermaid: true,
},
themeConfig: {
algolia: {
appId: "WIURGBNBPY",
apiKey: "d02cc0a6a61178b25da550212925226b",
indexName: "frigate",
},
docs: {
sidebar: {
hideable: true,
},
},
prism: {
additionalLanguages: ["bash", "json"],
},
navbar: {
title: "Frigate",
logo: {
alt: "Frigate",
src: "img/logo.svg",
srcDark: "img/logo-dark.svg",
},
items: [
{
to: "/",
activeBasePath: "docs",
label: "Docs",
position: "left",
},
{
href: "https://frigate.video",
label: "Website",
position: "right",
},
{
href: "http://demo.frigate.video",
label: "Demo",
position: "right",
},
{
href: "https://github.com/blakeblackshear/frigate",
label: "GitHub",
position: "right",
},
],
},
footer: {
style: "dark",
links: [
{
title: "Community",
items: [
{
label: "GitHub",
href: "https://github.com/blakeblackshear/frigate",
},
{
label: "Discussions",
href: "https://github.com/blakeblackshear/frigate/discussions",
},
],
},
],
copyright: `Copyright © ${new Date().getFullYear()} Blake Blackshear`,
},
},
plugins: [path.resolve(__dirname, "plugins", "raw-loader")],
presets: [
[
"@docusaurus/preset-classic",
{
docs: {
routeBasePath: "/",
sidebarPath: require.resolve("./sidebars.js"),
// Please change this to your repo.
editUrl:
"https://github.com/blakeblackshear/frigate/edit/master/docs/",
sidebarCollapsible: false,
},
theme: {
customCss: require.resolve("./src/css/custom.css"),
},
},
],
],
};

View File

@@ -1,158 +0,0 @@
import type * as Preset from '@docusaurus/preset-classic';
import * as path from 'node:path';
import type { Config, PluginConfig } from '@docusaurus/types';
import type * as OpenApiPlugin from 'docusaurus-plugin-openapi-docs';
const config: Config = {
title: 'Frigate',
tagline: 'NVR With Realtime Object Detection for IP Cameras',
url: 'https://docs.frigate.video',
baseUrl: '/',
onBrokenLinks: 'throw',
onBrokenMarkdownLinks: 'warn',
favicon: 'img/favicon.ico',
organizationName: 'blakeblackshear',
projectName: 'frigate',
themes: ['@docusaurus/theme-mermaid', 'docusaurus-theme-openapi-docs'],
markdown: {
mermaid: true,
},
themeConfig: {
algolia: {
appId: 'WIURGBNBPY',
apiKey: 'd02cc0a6a61178b25da550212925226b',
indexName: 'frigate',
},
docs: {
sidebar: {
hideable: true,
},
},
prism: {
additionalLanguages: ['bash', 'json'],
},
languageTabs: [
{
highlight: 'python',
language: 'python',
logoClass: 'python',
},
{
highlight: 'javascript',
language: 'nodejs',
logoClass: 'nodejs',
},
{
highlight: 'javascript',
language: 'javascript',
logoClass: 'javascript',
},
{
highlight: 'bash',
language: 'curl',
logoClass: 'curl',
},
{
highlight: "rust",
language: "rust",
logoClass: "rust",
},
],
navbar: {
title: 'Frigate',
logo: {
alt: 'Frigate',
src: 'img/logo.svg',
srcDark: 'img/logo-dark.svg',
},
items: [
{
to: '/',
activeBasePath: 'docs',
label: 'Docs',
position: 'left',
},
{
href: 'https://frigate.video',
label: 'Website',
position: 'right',
},
{
href: 'http://demo.frigate.video',
label: 'Demo',
position: 'right',
},
{
href: 'https://github.com/blakeblackshear/frigate',
label: 'GitHub',
position: 'right',
},
],
},
footer: {
style: 'dark',
links: [
{
title: 'Community',
items: [
{
label: 'GitHub',
href: 'https://github.com/blakeblackshear/frigate',
},
{
label: 'Discussions',
href: 'https://github.com/blakeblackshear/frigate/discussions',
},
],
},
],
copyright: `Copyright © ${new Date().getFullYear()} Blake Blackshear`,
},
},
plugins: [
path.resolve(__dirname, 'plugins', 'raw-loader'),
[
'docusaurus-plugin-openapi-docs',
{
id: 'openapi',
docsPluginId: 'classic', // configured for preset-classic
config: {
frigateApi: {
specPath: 'static/frigate-api.yaml',
outputDir: 'docs/integrations/api',
sidebarOptions: {
groupPathsBy: 'tag',
categoryLinkSource: 'tag',
sidebarCollapsible: true,
sidebarCollapsed: true,
},
showSchemas: true,
} satisfies OpenApiPlugin.Options,
},
},
]
] as PluginConfig[],
presets: [
[
'classic',
{
docs: {
routeBasePath: '/',
sidebarPath: './sidebars.ts',
// Please change this to your repo.
editUrl: 'https://github.com/blakeblackshear/frigate/edit/master/docs/',
sidebarCollapsible: false,
docItemComponent: '@theme/ApiItem', // Derived from docusaurus-theme-openapi
},
theme: {
customCss: './src/css/custom.css',
},
} satisfies Preset.Options,
],
],
};
export default async function createConfig() {
return config;
}

Some files were not shown because too many files have changed in this diff Show More