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>

.cspell/frigate-dictionary.txt

@@ -0,0 +1,168 @@
+rtmp
+edgetpu
+labelmap
+rockchip
+jetson
+rocm
+vaapi
+CUDA
+hwaccel
+RTSP
+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
+ultrafast
+sleeptime
+radeontop
+vainfo
+tmpfs
+homography
+websockets
+LIBAVFORMAT
+NTSC
+onnxruntime
+fourcc
+radeonsi
+paho
+imagestream
+jsonify
+cgroups
+sysconf
+memlimit
+gpuload
+nvml
+setproctitle
+psutil
+Kalman
+frontdoor
+namedtuples
+zeep
+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

.devcontainer/devcontainer.json

@@ -10,10 +10,14 @@
   "features": {
     "ghcr.io/devcontainers/features/common-utils:1": {}
   },
-  "forwardPorts": [5000, 5001, 5173, 1935, 8554, 8555],
+  "forwardPorts": [8080, 5000, 5001, 5173, 8554, 8555],
   "portsAttributes": {
+    "8080": {
+      "label": "External NGINX",
+      "onAutoForward": "silent"
+    },
     "5000": {
-      "label": "NGINX",
+      "label": "Internal NGINX",
       "onAutoForward": "silent"
     },
     "5001": {
@@ -24,10 +28,6 @@
       "label": "Vite Server",
       "onAutoForward": "silent"
     },
-    "1935": {
-      "label": "RTMP",
-      "onAutoForward": "silent"
-    },
     "8554": {
       "label": "gortc RTSP",
       "onAutoForward": "silent"

.github/DISCUSSION_TEMPLATE/bug-report.yml

@@ -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

.github/DISCUSSION_TEMPLATE/camera-support.yml

@@ -1,8 +1,5 @@
-name: Camera Support Request
-description: Support for setting up cameras in Frigate
 title: "[Camera Support]: "
 labels: ["support", "triage"]
-assignees: []
 body:
   - type: textarea
     id: description
@@ -14,7 +11,7 @@ body:
     id: version
     attributes:
       label: Version
-      description: Visible on the Debug page in the Web UI
+      description: Visible on the System page in the Web UI
     validations:
       required: true
   - type: textarea
@@ -72,14 +69,14 @@ body:
     validations:
       required: true
   - type: dropdown
-    id: coral
+    id: object-detector
     attributes:
-      label: Coral version
+      label: Object Detector
       options:
-        - USB
-        - PCIe
-        - M.2
-        - Dev Board
+        - Coral
+        - OpenVino
+        - TensorRT
+        - RKNN
         - Other
         - CPU (no coral)
     validations:

.github/DISCUSSION_TEMPLATE/config-support.yml

@@ -1,8 +1,5 @@
-name: Config Support Request
-description: Support for Frigate configuration
 title: "[Config Support]: "
 labels: ["support", "triage"]
-assignees: []
 body:
   - type: textarea
     id: description
@@ -14,7 +11,7 @@ body:
     id: version
     attributes:
       label: Version
-      description: Visible on the Debug page in the Web UI
+      description: Visible on the System page in the Web UI
     validations:
       required: true
   - type: textarea
@@ -64,14 +61,14 @@ body:
     validations:
       required: true
   - type: dropdown
-    id: coral
+    id: object-detector
     attributes:
-      label: Coral version
+      label: Object Detector
       options:
-        - USB
-        - PCIe
-        - M.2
-        - Dev Board
+        - Coral
+        - OpenVino
+        - TensorRT
+        - RKNN
         - Other
         - CPU (no coral)
     validations:

.github/DISCUSSION_TEMPLATE/detector-support.yml

@@ -1,8 +1,5 @@
-name: Detector Support Request
-description: Support for setting up object detector in Frigate (Coral, OpenVINO, TensorRT, etc.)
 title: "[Detector Support]: "
 labels: ["support", "triage"]
-assignees: []
 body:
   - type: textarea
     id: description
@@ -14,7 +11,7 @@ body:
     id: version
     attributes:
       label: Version
-      description: Visible on the Debug page in the Web UI
+      description: Visible on the System page in the Web UI
     validations:
       required: true
   - type: textarea
@@ -66,14 +63,14 @@ body:
     validations:
       required: true
   - type: dropdown
-    id: coral
+    id: object-detector
     attributes:
-      label: Coral version
+      label: Object Detector
       options:
-        - USB
-        - PCIe
-        - M.2
-        - Dev Board
+        - Coral
+        - OpenVino
+        - TensorRT
+        - RKNN
         - Other
         - CPU (no coral)
     validations:

.github/DISCUSSION_TEMPLATE/general-support.yml

@@ -1,8 +1,5 @@
-name: General Support Request
-description: General support request for Frigate
 title: "[Support]: "
 labels: ["support", "triage"]
-assignees: []
 body:
   - type: textarea
     id: description
@@ -14,7 +11,7 @@ body:
     id: version
     attributes:
       label: Version
-      description: Visible on the Debug page in the Web UI
+      description: Visible on the System page in the Web UI
     validations:
       required: true
   - type: textarea
@@ -72,14 +69,14 @@ body:
     validations:
       required: true
   - type: dropdown
-    id: coral
+    id: object-detector
     attributes:
-      label: Coral version
+      label: Object Detector
       options:
-        - USB
-        - PCIe
-        - M.2
-        - Dev Board
+        - Coral
+        - OpenVino
+        - TensorRT
+        - RKNN
         - Other
         - CPU (no coral)
     validations:

.github/DISCUSSION_TEMPLATE/hardware-acceleration-support.yml

@@ -1,8 +1,5 @@
-name: Hardware Acceleration Support Request
-description: Support for setting up GPU hardware acceleration in Frigate
 title: "[HW Accel Support]: "
 labels: ["support", "triage"]
-assignees: []
 body:
   - type: textarea
     id: description
@@ -14,7 +11,7 @@ body:
     id: version
     attributes:
       label: Version
-      description: Visible on the Debug page in the Web UI
+      description: Visible on the System page in the Web UI
     validations:
       required: true
   - type: textarea

.github/DISCUSSION_TEMPLATE/question.yml

@@ -0,0 +1,9 @@
+title: "[Question]: "
+labels: ["question"]
+body:
+  - type: textarea
+    id: description
+    attributes:
+      label: "What is your question:"
+    validations:
+      required: true

.github/FUNDING.yml

@@ -1,3 +1,4 @@
 github:
   - blakeblackshear
   - NickM-27
+  - hawkeye217

.github/ISSUE_TEMPLATE/config.yml

@@ -1 +1,8 @@
 blank_issues_enabled: false
+contact_links:
+  - name: Frigate Support
+    url: https://github.com/blakeblackshear/frigate/discussions/new/choose
+    about: Get support for setting up or troubleshooting Frigate.
+  - name: Frigate Bug Report
+    url: https://github.com/blakeblackshear/frigate/discussions/new/choose
+    about: Report a specific UI or backend bug.

.github/dependabot.yml

@@ -34,5 +34,7 @@ updates:
     directory: "/docs"
     schedule:
       interval: daily
+    allow:
+      - dependency-name: "@docusaurus/*"
     open-pull-requests-limit: 10
     target-branch: dev

.github/workflows/ci.yml

@@ -37,16 +37,6 @@ jobs:
           target: frigate
           tags: ${{ steps.setup.outputs.image-name }}-amd64
           cache-from: type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64
-      - name: Build and push TensorRT (x86 GPU)
-        uses: docker/bake-action@v4
-        with:
-          push: true
-          targets: tensorrt
-          files: docker/tensorrt/trt.hcl
-          set: |
-            tensorrt.tags=${{ steps.setup.outputs.image-name }}-tensorrt
-            *.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64
-            *.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-amd64,mode=max
   arm64_build:
     runs-on: ubuntu-latest
     name: ARM Build
@@ -79,7 +69,7 @@ jobs:
             rpi.tags=${{ steps.setup.outputs.image-name }}-rpi
             *.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64
             *.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-arm64,mode=max
-      - name: Build and push RockChip build
+      - name: Build and push Rockchip build
         uses: docker/bake-action@v3
         with:
           push: true
@@ -140,6 +130,82 @@ jobs:
             tensorrt.tags=${{ steps.setup.outputs.image-name }}-tensorrt-jp5
             *.cache-from=type=registry,ref=${{ steps.setup.outputs.cache-name }}-jp5
             *.cache-to=type=registry,ref=${{ steps.setup.outputs.cache-name }}-jp5,mode=max
+  amd64_extra_builds:
+    runs-on: ubuntu-latest
+    name: AMD64 Extra Build
+    needs:
+      - amd64_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: ${{ secrets.GITHUB_TOKEN }}
+      - name: Build and push TensorRT (x86 GPU)
+        env:
+          COMPUTE_LEVEL: "50 60 70 80 90"
+        uses: docker/bake-action@v4
+        with:
+          push: true
+          targets: tensorrt
+          files: docker/tensorrt/trt.hcl
+          set: |
+            tensorrt.tags=${{ 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
+      #- 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:
@@ -154,16 +220,16 @@ jobs:
         with:
           string: ${{ github.repository }}
       - name: Log in to the Container registry
-        uses: docker/login-action@343f7c4344506bcbf9b4de18042ae17996df046d
+        uses: docker/login-action@0d4c9c5ea7693da7b068278f7b52bda2a190a446
         with:
           registry: ghcr.io
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
       - name: Create short sha
         run: echo "SHORT_SHA=${GITHUB_SHA::7}" >> $GITHUB_ENV
-      - uses: int128/docker-manifest-create-action@v1
+      - uses: int128/docker-manifest-create-action@v2
         with:
           tags: ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}
-          suffixes: |
-            -amd64
-            -rpi
+          sources: |
+            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

.github/workflows/dependabot-auto-merge.yaml

@@ -11,7 +11,7 @@ jobs:
     steps:
       - name: Get Dependabot metadata
         id: metadata
-        uses: dependabot/fetch-metadata@v1
+        uses: dependabot/fetch-metadata@v2
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
       - name: Enable auto-merge for Dependabot PRs

.github/workflows/pull_request.yml

@@ -51,12 +51,12 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-node@master
         with:
-          node-version: 16.x
+          node-version: 20.x
       - run: npm install
         working-directory: ./web
-      - name: Test
-        run: npm run test
-        working-directory: ./web
+      # - name: Test
+      #   run: npm run test
+      #   working-directory: ./web
 
   python_checks:
     runs-on: ubuntu-latest
@@ -65,7 +65,7 @@ jobs:
       - name: Check out the repository
         uses: actions/checkout@v4
       - name: Set up Python ${{ env.DEFAULT_PYTHON }}
-        uses: actions/setup-python@v5.0.0
+        uses: actions/setup-python@v5.1.0
         with:
           python-version: ${{ env.DEFAULT_PYTHON }}
       - name: Install requirements

.github/workflows/release.yml

@@ -16,7 +16,7 @@ jobs:
         with:
           string: ${{ github.repository }}
       - name: Log in to the Container registry
-        uses: docker/login-action@343f7c4344506bcbf9b4de18042ae17996df046d
+        uses: docker/login-action@0d4c9c5ea7693da7b068278f7b52bda2a190a446
         with:
           registry: ghcr.io
           username: ${{ github.actor }}
@@ -24,14 +24,24 @@ jobs:
       - name: Create tag variables
         run: |
           BRANCH=$([[ "${{ github.ref_name }}" =~ ^v[0-9]+\.[0-9]+\.[0-9]+$ ]] && echo "master" || echo "dev")
+          echo "BRANCH=${BRANCH}" >> $GITHUB_ENV
           echo "BASE=ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}" >> $GITHUB_ENV
           echo "BUILD_TAG=${BRANCH}-${GITHUB_SHA::7}" >> $GITHUB_ENV
           echo "CLEAN_VERSION=$(echo ${GITHUB_REF##*/} | tr '[:upper:]' '[:lower:]' | sed 's/^[v]//')" >> $GITHUB_ENV
       - name: Tag and push the main image
         run: |
           VERSION_TAG=${BASE}:${CLEAN_VERSION}
+          STABLE_TAG=${BASE}:stable
           PULL_TAG=${BASE}:${BUILD_TAG}
           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://${VERSION_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}-${variant} docker://${VERSION_TAG}-${variant}
           done
+
+          # stable tag
+          if [[ "${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}
+            done
+          fi

.github/workflows/stale.yml

@@ -24,3 +24,18 @@ jobs:
           operations-per-run: 120
       - 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
+

.gitignore

@@ -8,7 +8,6 @@ config/*
 !config/*.example
 models
 *.mp4
-*.ts
 *.db
 *.csv
 frigate/version.py
@@ -17,4 +16,5 @@ web/node_modules
 web/coverage
 core
 !/web/**/*.ts
-.idea/*
+.idea/*
+.ipynb_checkpoints

CODEOWNERS

@@ -2,5 +2,5 @@
 /docker/tensorrt/ @madsciencetist @NateMeyer
 /docker/tensorrt/*arm64* @madsciencetist
 /docker/tensorrt/*jetson* @madsciencetist
-
 /docker/rockchip/ @MarcA711
+/docker/rocm/ @harakas

Makefile

@@ -1,7 +1,7 @@
 default_target: local
 
 COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
-VERSION = 0.13.2
+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)

README.md

@@ -29,18 +29,22 @@ If you would like to make a donation to support development, please use [Github
 
 ## Screenshots
 
-Integration into Home Assistant
-
+### Live dashboard
 <div>
-<a href="docs/static/img/media_browser.png"><img src="docs/static/img/media_browser.png" height=400></a>
-<a href="docs/static/img/notification.png"><img src="docs/static/img/notification.png" height=400></a>
+<img width="800" alt="Live dashboard" src="https://github.com/blakeblackshear/frigate/assets/569905/5e713cb9-9db5-41dc-947a-6937c3bc376e">
 </div>
 
-Also comes with a builtin UI:
-
+### Streamlined review workflow
 <div>
-<a href="docs/static/img/home-ui.png"><img src="docs/static/img/home-ui.png" height=400></a>
-<a href="docs/static/img/camera-ui.png"><img src="docs/static/img/camera-ui.png" height=400></a>
+<img width="800" alt="Streamlined review workflow" src="https://github.com/blakeblackshear/frigate/assets/569905/6fed96e8-3b18-40e5-9ddc-31e6f3c9f2ff">
 </div>
 
-![Events](docs/static/img/events-ui.png)
+### Multi-camera scrubbing
+<div>
+<img width="800" alt="Multi-camera scrubbing" src="https://github.com/blakeblackshear/frigate/assets/569905/d6788a15-0eeb-4427-a8d4-80b93cae3d74">
+</div>
+
+### Built-in mask and zone editor
+<div>
+<img width="800" alt="Multi-camera scrubbing" src="https://github.com/blakeblackshear/frigate/assets/569905/d7885fc3-bfe6-452f-b7d0-d957cb3e31f5">
+</div>

cspell.json

@@ -0,0 +1,21 @@
+{
+  "version": "0.2",
+  "ignorePaths": [
+    "Dockerfile",
+    "Dockerfile.*",
+    "CMakeLists.txt",
+    "*.db",
+    "node_modules",
+    "__pycache__",
+    "dist"
+  ],
+  "language": "en",
+  "dictionaryDefinitions": [
+    {
+      "name": "frigate-dictionary",
+      "path": "./.cspell/frigate-dictionary.txt",
+      "addWords": true
+    }
+  ],
+  "dictionaries": ["frigate-dictionary"]
+}

docker/main/Dockerfile

@@ -33,15 +33,18 @@ RUN --mount=type=tmpfs,target=/tmp --mount=type=tmpfs,target=/var/cache/apt \
 FROM scratch AS go2rtc
 ARG TARGETARCH
 WORKDIR /rootfs/usr/local/go2rtc/bin
-ADD --link --chmod=755 "https://github.com/AlexxIT/go2rtc/releases/download/v1.8.4/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
+RUN --mount=type=bind,source=docker/main/install_tempio.sh,target=/deps/install_tempio.sh \
+    /deps/install_tempio.sh
 
 ####
 #
 # OpenVino Support
 #
 # 1. Download and convert a model from Intel's Public Open Model Zoo
-# 2. Build libUSB without udev to handle NCS2 enumeration
 #
 ####
 # Download and Convert OpenVino model
@@ -51,44 +54,17 @@ ARG DEBIAN_FRONTEND
 # Install OpenVino Runtime and Dev library
 COPY docker/main/requirements-ov.txt /requirements-ov.txt
 RUN apt-get -qq update \
-    && apt-get -qq install -y wget python3 python3-distutils \
+    && apt-get -qq install -y wget python3 python3-dev python3-distutils gcc pkg-config libhdf5-dev \
     && wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
     && python3 get-pip.py "pip" \
     && pip install -r /requirements-ov.txt
 
 # Get OpenVino Model
-RUN mkdir /models \
-    && cd /models && omz_downloader --name ssdlite_mobilenet_v2 \
-    && cd /models && omz_converter --name ssdlite_mobilenet_v2 --precision FP16
-
-
-# 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
+RUN --mount=type=bind,source=docker/main/build_ov_model.py,target=/build_ov_model.py \
+    mkdir /models && cd /models \
+    && wget http://download.tensorflow.org/models/object_detection/ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz \
+    && tar -xvf ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz \
+    && python3 /build_ov_model.py
 
 FROM wget AS models
 
@@ -97,7 +73,8 @@ RUN wget -qO edgetpu_model.tflite https://github.com/google-coral/test_data/raw/
 RUN wget -qO cpu_model.tflite https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess.tflite
 COPY labelmap.txt .
 # Copy OpenVino model
-COPY --from=ov-converter /models/public/ssdlite_mobilenet_v2/FP16 openvino-model
+COPY --from=ov-converter /models/ssdlite_mobilenet_v2.xml openvino-model/
+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
@@ -158,7 +135,7 @@ RUN pip3 wheel --wheel-dir=/wheels -r /requirements-wheels.txt
 FROM scratch AS deps-rootfs
 COPY --from=nginx /usr/local/nginx/ /usr/local/nginx/
 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/ /
 COPY docker/main/rootfs/ /
@@ -176,7 +153,7 @@ ARG APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn
 ENV NVIDIA_VISIBLE_DEVICES=all
 ENV NVIDIA_DRIVER_CAPABILITIES="compute,video,utility"
 
-ENV PATH="/usr/lib/btbn-ffmpeg/bin:/usr/local/go2rtc/bin:/usr/local/nginx/sbin:${PATH}"
+ENV PATH="/usr/lib/btbn-ffmpeg/bin:/usr/local/go2rtc/bin:/usr/local/tempio/bin:/usr/local/nginx/sbin:${PATH}"
 
 # Install dependencies
 RUN --mount=type=bind,source=docker/main/install_deps.sh,target=/deps/install_deps.sh \
@@ -188,15 +165,14 @@ RUN --mount=type=bind,from=wheels,source=/wheels,target=/deps/wheels \
 
 COPY --from=deps-rootfs / /
 
-RUN ldconfig
-
 EXPOSE 5000
-EXPOSE 1935
 EXPOSE 8554
 EXPOSE 8555/tcp 8555/udp
 
 # Configure logging to prepend timestamps, log to stdout, keep 0 archives and rotate on 10MB
 ENV S6_LOGGING_SCRIPT="T 1 n0 s10000000 T"
+# Do not fail on long-running download scripts
+ENV S6_CMD_WAIT_FOR_SERVICES_MAXTIME=0
 
 ENTRYPOINT ["/init"]
 CMD []
@@ -232,12 +208,14 @@ RUN apt-get update \
 RUN --mount=type=bind,source=./docker/main/requirements-dev.txt,target=/workspace/frigate/requirements-dev.txt \
     pip3 install -r requirements-dev.txt
 
+HEALTHCHECK NONE
+
 CMD ["sleep", "infinity"]
 
 
 # Frigate web build
 # This should be architecture agnostic, so speed up the build on multiarch by not using QEMU.
-FROM --platform=$BUILDPLATFORM node:16 AS web-build
+FROM --platform=$BUILDPLATFORM node:20 AS web-build
 
 WORKDIR /work
 COPY web/package.json web/package-lock.json ./

docker/main/build_nginx.sh

@@ -5,7 +5,8 @@ set -euxo pipefail
 NGINX_VERSION="1.25.3"
 VOD_MODULE_VERSION="1.31"
 SECURE_TOKEN_MODULE_VERSION="1.5"
-RTMP_MODULE_VERSION="1.2.2"
+SET_MISC_MODULE_VERSION="v0.33"
+NGX_DEVEL_KIT_VERSION="v0.3.3"
 
 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
@@ -49,10 +50,16 @@ mkdir /tmp/nginx-secure-token-module
 wget https://github.com/kaltura/nginx-secure-token-module/archive/refs/tags/${SECURE_TOKEN_MODULE_VERSION}.tar.gz
 tar -zxf ${SECURE_TOKEN_MODULE_VERSION}.tar.gz -C /tmp/nginx-secure-token-module --strip-components=1
 rm ${SECURE_TOKEN_MODULE_VERSION}.tar.gz
-mkdir /tmp/nginx-rtmp-module
-wget -nv https://github.com/arut/nginx-rtmp-module/archive/refs/tags/v${RTMP_MODULE_VERSION}.tar.gz
-tar -zxf v${RTMP_MODULE_VERSION}.tar.gz -C /tmp/nginx-rtmp-module --strip-components=1
-rm v${RTMP_MODULE_VERSION}.tar.gz
+
+mkdir /tmp/ngx_devel_kit
+wget https://github.com/vision5/ngx_devel_kit/archive/refs/tags/${NGX_DEVEL_KIT_VERSION}.tar.gz
+tar -zxf ${NGX_DEVEL_KIT_VERSION}.tar.gz -C /tmp/ngx_devel_kit --strip-components=1
+rm ${NGX_DEVEL_KIT_VERSION}.tar.gz
+
+mkdir /tmp/nginx-set-misc-module
+wget https://github.com/openresty/set-misc-nginx-module/archive/refs/tags/${SET_MISC_MODULE_VERSION}.tar.gz
+tar -zxf ${SET_MISC_MODULE_VERSION}.tar.gz -C /tmp/nginx-set-misc-module --strip-components=1
+rm ${SET_MISC_MODULE_VERSION}.tar.gz
 
 cd /tmp/nginx
 
@@ -60,10 +67,13 @@ cd /tmp/nginx
     --with-file-aio \
     --with-http_sub_module \
     --with-http_ssl_module \
+    --with-http_auth_request_module \
+    --with-http_realip_module \
     --with-threads \
+    --add-module=../ngx_devel_kit \
+    --add-module=../nginx-set-misc-module \
     --add-module=../nginx-vod-module \
     --add-module=../nginx-secure-token-module \
-    --add-module=../nginx-rtmp-module \
     --with-cc-opt="-O3 -Wno-error=implicit-fallthrough"
 
 make CC="ccache gcc" -j$(nproc) && make install

docker/main/build_ov_model.py

@@ -0,0 +1,11 @@
+import openvino as ov
+from openvino.tools import mo
+
+ov_model = mo.convert_model(
+    "/models/ssdlite_mobilenet_v2_coco_2018_05_09/frozen_inference_graph.pb",
+    compress_to_fp16=True,
+    transformations_config="/usr/local/lib/python3.9/dist-packages/openvino/tools/mo/front/tf/ssd_v2_support.json",
+    tensorflow_object_detection_api_pipeline_config="/models/ssdlite_mobilenet_v2_coco_2018_05_09/pipeline.config",
+    reverse_input_channels=True,
+)
+ov.save_model(ov_model, "/models/ssdlite_mobilenet_v2.xml")

docker/main/install_tempio.sh

@@ -0,0 +1,16 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+tempio_version="2021.09.0"
+
+if [[ "${TARGETARCH}" == "amd64" ]]; then
+    arch="amd64"
+elif [[ "${TARGETARCH}" == "arm64" ]]; then
+    arch="aarch64"
+fi
+
+mkdir -p /rootfs/usr/local/tempio/bin
+
+wget -q -O /rootfs/usr/local/tempio/bin/tempio "https://github.com/home-assistant/tempio/releases/download/${tempio_version}/tempio_${arch}"
+chmod 755 /rootfs/usr/local/tempio/bin/tempio

docker/main/requirements-ov.txt

@@ -1,5 +1,3 @@
 numpy
-# Openvino Library - Custom built with MYRIAD support
-openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-manylinux_2_31_x86_64.whl; platform_machine == 'x86_64'
-openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-linux_aarch64.whl; platform_machine == 'aarch64'
-openvino-dev[tensorflow2] @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino_dev-2022.3.1-1-py3-none-any.whl
+tensorflow
+openvino-dev>=2024.0.0

docker/main/requirements-wheels.txt

@@ -1,29 +1,33 @@
 click == 8.1.*
-Flask == 2.3.*
+Flask == 3.0.*
+Flask_Limiter == 3.7.*
 imutils == 0.5.*
-matplotlib == 3.7.*
+joserfc == 0.11.*
+markupsafe == 2.1.*
+matplotlib == 3.8.*
 mypy == 1.6.1
-numpy == 1.23.*
+numpy == 1.26.*
 onvif_zeep == 0.2.12
-opencv-python-headless == 4.7.0.*
-paho-mqtt == 1.6.*
+opencv-python-headless == 4.9.0.*
+paho-mqtt == 2.1.*
+pandas == 2.2.*
 peewee == 3.17.*
 peewee_migrate == 1.12.*
 psutil == 5.9.*
-pydantic == 1.10.*
+pydantic == 2.7.*
 git+https://github.com/fbcotter/py3nvml#egg=py3nvml
 PyYAML == 6.0.*
-pytz == 2023.3.post1
+pytz == 2024.1
+pyzmq == 26.0.*
 ruamel.yaml == 0.18.*
 tzlocal == 5.2
 types-PyYAML == 6.0.*
-requests == 2.31.*
-types-requests == 2.31.*
-scipy == 1.11.*
+requests == 2.32.*
+types-requests == 2.32.*
+scipy == 1.13.*
 norfair == 2.2.*
 setproctitle == 1.3.*
 ws4py == 0.5.*
 unidecode == 1.3.*
-# Openvino Library - Custom built with MYRIAD support
-openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-manylinux_2_31_x86_64.whl; platform_machine == 'x86_64'
-openvino @ https://github.com/NateMeyer/openvino-wheels/releases/download/multi-arch_2022.3.1/openvino-2022.3.1-1-cp39-cp39-linux_aarch64.whl; platform_machine == 'aarch64'
+onnxruntime == 1.18.*
+openvino == 2024.1.*

docker/main/requirements.txt

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

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync-log/consumer-for

@@ -0,0 +1 @@
+certsync

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync-log/pipeline-name

@@ -0,0 +1 @@
+certsync-pipeline

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync-log/run

@@ -0,0 +1,4 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+
+exec logutil-service /dev/shm/logs/certsync

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync-log/type

@@ -0,0 +1 @@
+longrun

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync/finish

@@ -0,0 +1,30 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Take down the S6 supervision tree when the service fails
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+declare exit_code_container
+exit_code_container=$(cat /run/s6-linux-init-container-results/exitcode)
+readonly exit_code_container
+readonly exit_code_service="${1}"
+readonly exit_code_signal="${2}"
+readonly service="CERTSYNC"
+
+echo "[INFO] Service ${service} exited with code ${exit_code_service} (by signal ${exit_code_signal})"
+
+if [[ "${exit_code_service}" -eq 256 ]]; then
+  if [[ "${exit_code_container}" -eq 0 ]]; then
+    echo $((128 + exit_code_signal)) >/run/s6-linux-init-container-results/exitcode
+  fi
+  if [[ "${exit_code_signal}" -eq 15 ]]; then
+    exec /run/s6/basedir/bin/halt
+  fi
+elif [[ "${exit_code_service}" -ne 0 ]]; then
+  if [[ "${exit_code_container}" -eq 0 ]]; then
+    echo "${exit_code_service}" >/run/s6-linux-init-container-results/exitcode
+  fi
+  exec /run/s6/basedir/bin/halt
+fi

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync/producer-for

@@ -0,0 +1 @@
+certsync-log

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync/run

@@ -0,0 +1,58 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Start the CERTSYNC service
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+echo "[INFO] Starting certsync..."
+
+lefile="/etc/letsencrypt/live/frigate/fullchain.pem"
+
+tls_enabled=`python3 /usr/local/nginx/get_tls_settings.py | jq -r .enabled`
+
+while true
+do
+    if [[ "$tls_enabled" == 'false' ]]; then
+        sleep 9999
+        continue
+    fi
+
+    if [ ! -e $lefile ]
+    then
+        echo "[ERROR] TLS certificate does not exist: $lefile"
+    fi
+
+    leprint=`openssl x509 -in $lefile -fingerprint -noout 2>&1 || echo 'failed'`
+
+    case "$leprint" in
+        *Fingerprint*)
+            ;;
+        *)
+            echo "[ERROR] Missing fingerprint from $lefile"
+            ;;
+    esac
+
+    liveprint=`echo | openssl s_client -showcerts -connect 127.0.0.1:8080 2>&1 | openssl x509 -fingerprint 2>&1 | grep -i fingerprint  || echo 'failed'`
+
+    case "$liveprint" in
+        *Fingerprint*)
+            ;;
+        *)
+            echo "[ERROR] Missing fingerprint from current nginx TLS cert"
+            ;;
+    esac
+
+    if [[ "$leprint" != "failed" && "$liveprint" != "failed" && "$leprint" != "$liveprint" ]]
+    then
+        echo "[INFO] Reloading nginx to refresh TLS certificate"
+        echo "$lefile: $leprint"
+        /usr/local/nginx/sbin/nginx -s reload
+    fi
+
+    sleep 60
+
+done
+
+exit 0

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync/timeout-kill

@@ -0,0 +1 @@
+30000

docker/main/rootfs/etc/s6-overlay/s6-rc.d/certsync/type

@@ -0,0 +1 @@
+longrun

docker/main/rootfs/etc/s6-overlay/s6-rc.d/log-prepare/run

@@ -4,7 +4,7 @@
 
 set -o errexit -o nounset -o pipefail
 
-dirs=(/dev/shm/logs/frigate /dev/shm/logs/go2rtc /dev/shm/logs/nginx)
+dirs=(/dev/shm/logs/frigate /dev/shm/logs/go2rtc /dev/shm/logs/nginx /dev/shm/logs/certsync)
 
 mkdir -p "${dirs[@]}"
 chown nobody:nogroup "${dirs[@]}"

docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/data/check

@@ -0,0 +1,5 @@
+#!/usr/bin/env bash
+set -e
+
+# Wait for PID file to exist.
+while ! test -f /run/nginx.pid; do sleep 1; done

docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/notification-fd

@@ -0,0 +1 @@
+3

docker/main/rootfs/etc/s6-overlay/s6-rc.d/nginx/run

@@ -8,6 +8,84 @@ set -o errexit -o nounset -o pipefail
 
 echo "[INFO] Starting NGINX..."
 
+# Taken from https://github.com/felipecrs/cgroup-scripts/commits/master/get_cpus.sh
+function get_cpus() {
+    local quota=""
+    local period=""
+
+    if [ -f /sys/fs/cgroup/cgroup.controllers ]; then
+        if [ -f /sys/fs/cgroup/cpu.max ]; then
+            read -r quota period </sys/fs/cgroup/cpu.max
+            if [ "$quota" = "max" ]; then
+                quota=""
+                period=""
+            fi
+        else
+            echo "[WARN] /sys/fs/cgroup/cpu.max not found. Falling back to /proc/cpuinfo." >&2
+        fi
+    else
+        if [ -f /sys/fs/cgroup/cpu/cpu.cfs_quota_us ] && [ -f /sys/fs/cgroup/cpu/cpu.cfs_period_us ]; then
+            quota=$(cat /sys/fs/cgroup/cpu/cpu.cfs_quota_us)
+            period=$(cat /sys/fs/cgroup/cpu/cpu.cfs_period_us)
+
+            if [ "$quota" = "-1" ]; then
+                quota=""
+                period=""
+            fi
+        else
+            echo "[WARN] /sys/fs/cgroup/cpu/cpu.cfs_quota_us or /sys/fs/cgroup/cpu/cpu.cfs_period_us not found. Falling back to /proc/cpuinfo." >&2
+        fi
+    fi
+
+    local cpus
+    if [ -n "${quota}" ] && [ -n "${period}" ]; then
+        cpus=$((quota / period))
+        if [ "$cpus" -eq 0 ]; then
+            cpus=1
+        fi
+    else
+        cpus=$(grep -c ^processor /proc/cpuinfo)
+    fi
+
+    printf '%s' "$cpus"
+}
+
+function set_worker_processes() {
+    # Capture number of assigned CPUs to calculate worker processes
+    local cpus
+
+    cpus=$(get_cpus)
+    if [[ "${cpus}" -gt 4 ]]; then
+        cpus=4
+    fi
+
+    # we need to catch any errors because sed will fail if user has bind mounted a custom nginx file
+    sed -i "s/worker_processes auto;/worker_processes ${cpus};/" /usr/local/nginx/conf/nginx.conf || true
+}
+
+set_worker_processes
+
+# ensure the directory for ACME challenges exists
+mkdir -p /etc/letsencrypt/www
+
+# Create self signed certs if needed
+letsencrypt_path=/etc/letsencrypt/live/frigate
+mkdir -p $letsencrypt_path
+
+if [ ! \( -f "$letsencrypt_path/privkey.pem" -a -f "$letsencrypt_path/fullchain.pem" \) ]; then
+    echo "[INFO] No TLS certificate found. Generating a self signed certificate..."
+    openssl req -new -newkey rsa:4096 -days 365 -nodes -x509 \
+        -subj "/O=FRIGATE DEFAULT CERT/CN=*" \
+        -keyout "$letsencrypt_path/privkey.pem" -out "$letsencrypt_path/fullchain.pem" 2>/dev/null
+fi
+
+# build templates for optional TLS support
+python3 /usr/local/nginx/get_tls_settings.py | \
+    tempio  -template /usr/local/nginx/templates/listen.gotmpl \
+            -out /usr/local/nginx/conf/listen.conf
+
 # Replace the bash process with the NGINX process, redirecting stderr to stdout
 exec 2>&1
-exec nginx
+exec \
+    s6-notifyoncheck -t 30000 -n 1 \
+    nginx

docker/main/rootfs/labelmap/coco-80.txt

@@ -0,0 +1,80 @@
+0  person
+1  bicycle
+2  car
+3  motorcycle
+4  airplane
+5  car
+6  train
+7  car
+8  boat
+9  traffic light
+10  fire hydrant
+11  stop sign
+12  parking meter
+13  bench
+14  bird
+15  cat
+16  dog
+17  horse
+18  sheep
+19  cow
+20  elephant
+21  bear
+22  zebra
+23  giraffe
+24  backpack
+25  umbrella
+26  handbag
+27  tie
+28  suitcase
+29  frisbee
+30  skis
+31  snowboard
+32  sports ball
+33  kite
+34  baseball bat
+35  baseball glove
+36  skateboard
+37  surfboard
+38  tennis racket
+39  bottle
+40  wine glass
+41  cup
+42  fork
+43  knife
+44  spoon
+45  bowl
+46  banana
+47  apple
+48  sandwich
+49  orange
+50  broccoli
+51  carrot
+52  hot dog
+53  pizza
+54  donut
+55  cake
+56  chair
+57  couch
+58  potted plant
+59  bed
+60  dining table
+61  toilet
+62  tv
+63  laptop
+64  mouse
+65  remote
+66  keyboard
+67  cell phone
+68  microwave
+69  oven
+70  toaster
+71  sink
+72  refrigerator
+73  book
+74  clock
+75  vase
+76  scissors
+77  teddy bear
+78  hair drier
+79  toothbrush

docker/main/rootfs/labelmap/coco.txt

@@ -0,0 +1,91 @@
+0  person
+1  bicycle
+2  car
+3  motorcycle
+4  airplane
+5  bus
+6  train
+7  car
+8  boat
+9  traffic light
+10  fire hydrant
+11  street sign
+12  stop sign
+13  parking meter
+14  bench
+15  bird
+16  cat
+17  dog
+18  horse
+19  sheep
+20  cow
+21  elephant
+22  bear
+23  zebra
+24  giraffe
+25  hat
+26  backpack
+27  umbrella
+28  shoe
+29  eye glasses
+30  handbag
+31  tie
+32  suitcase
+33  frisbee
+34  skis
+35  snowboard
+36  sports ball
+37  kite
+38  baseball bat
+39  baseball glove
+40  skateboard
+41  surfboard
+42  tennis racket
+43  bottle
+44  plate
+45  wine glass
+46  cup
+47  fork
+48  knife
+49  spoon
+50  bowl
+51  banana
+52  apple
+53  sandwich
+54  orange
+55  broccoli
+56  carrot
+57  hot dog
+58  pizza
+59  donut
+60  cake
+61  chair
+62  couch
+63  potted plant
+64  bed
+65  mirror
+66  dining table
+67  window
+68  desk
+69  toilet
+70  door
+71  tv
+72  laptop
+73  mouse
+74  remote
+75  keyboard
+76  cell phone
+77  microwave
+78  oven
+79  toaster
+80  sink
+81  refrigerator
+82  blender
+83  book
+84  clock
+85  vase
+86  scissors
+87  teddy bear
+88  hair drier
+89  toothbrush
+90  hair brush

docker/main/rootfs/usr/local/go2rtc/create_config.py

@@ -32,13 +32,16 @@ config_file_yaml = config_file.replace(".yml", ".yaml")
 if os.path.isfile(config_file_yaml):
     config_file = config_file_yaml
 
-with open(config_file) as f:
-    raw_config = f.read()
+try:
+    with open(config_file) as f:
+        raw_config = f.read()
 
-if config_file.endswith((".yaml", ".yml")):
-    config: dict[str, any] = yaml.safe_load(raw_config)
-elif config_file.endswith(".json"):
-    config: dict[str, any] = json.loads(raw_config)
+    if config_file.endswith((".yaml", ".yml")):
+        config: dict[str, any] = yaml.safe_load(raw_config)
+    elif config_file.endswith(".json"):
+        config: dict[str, any] = json.loads(raw_config)
+except FileNotFoundError:
+    config: dict[str, any] = {}
 
 go2rtc_config: dict[str, any] = config.get("go2rtc", {})
 
@@ -109,23 +112,9 @@ if int(os.environ["LIBAVFORMAT_VERSION_MAJOR"]) < 59:
             "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}"
-
-# add hardware acceleration presets for rockchip devices
-# may be removed if frigate uses a go2rtc version that includes these presets
-if go2rtc_config.get("ffmpeg") is None:
-    go2rtc_config["ffmpeg"] = {
-        "h264/rk": "-c:v h264_rkmpp_encoder -g 50 -bf 0",
-        "h265/rk": "-c:v hevc_rkmpp_encoder -g 50 -bf 0",
-    }
-else:
-    if go2rtc_config["ffmpeg"].get("h264/rk") is None:
-        go2rtc_config["ffmpeg"]["h264/rk"] = "-c:v h264_rkmpp_encoder -g 50 -bf 0"
-
-    if go2rtc_config["ffmpeg"].get("h265/rk") is None:
-        go2rtc_config["ffmpeg"]["h265/rk"] = "-c:v hevc_rkmpp_encoder -g 50 -bf 0"
+        go2rtc_config["ffmpeg"]["rtsp"] = (
+            "-fflags nobuffer -flags low_delay -stimeout 5000000 -user_agent go2rtc/ffmpeg -rtsp_transport tcp -i {input}"
+        )
 
 for name in go2rtc_config.get("streams", {}):
     stream = go2rtc_config["streams"][name]

docker/main/rootfs/usr/local/nginx/conf/auth_location.conf

@@ -0,0 +1,43 @@
+set $upstream_auth http://127.0.0.1:5001/auth;
+
+## Virtual endpoint created by nginx to forward auth requests.
+location /auth {
+    ## Essential Proxy Configuration
+    internal;
+    proxy_pass $upstream_auth;
+
+    ## Headers
+
+    # First strip out all the request headers
+    # Note: This is important to ensure that upgrade requests for secure
+    #       websockets dont cause the backend to fail
+    proxy_pass_request_headers off;
+    # Pass info about the request
+    proxy_set_header X-Original-Method $request_method;
+    proxy_set_header X-Original-URL $scheme://$http_host$request_uri;
+    proxy_set_header X-Server-Port $server_port;
+    proxy_set_header Content-Length "";
+    # Pass along auth related info
+    proxy_set_header Authorization $http_authorization;
+    proxy_set_header Cookie $http_cookie;
+    proxy_set_header X-CSRF-TOKEN "1";
+
+    # include headers from common auth proxies
+    include proxy_trusted_headers.conf;
+
+    ## Basic Proxy Configuration
+    proxy_pass_request_body off;
+    proxy_next_upstream error timeout invalid_header http_500 http_502 http_503; # Timeout if the real server is dead
+    proxy_redirect http:// $scheme://;
+    proxy_http_version 1.1;
+    proxy_cache_bypass $cookie_session;
+    proxy_no_cache $cookie_session;
+    proxy_buffers 4 32k;
+    client_body_buffer_size 128k;
+
+    ## Advanced Proxy Configuration
+    send_timeout 5m;
+    proxy_read_timeout 240;
+    proxy_send_timeout 240;
+    proxy_connect_timeout 240;
+}

docker/main/rootfs/usr/local/nginx/conf/auth_request.conf

@@ -0,0 +1,22 @@
+## Send a subrequest to verify if the user is authenticated and has permission to access the resource.
+auth_request /auth;
+
+## Save the upstream metadata response headers from Authelia to variables.
+auth_request_set $user $upstream_http_remote_user;
+auth_request_set $groups $upstream_http_remote_groups;
+auth_request_set $name $upstream_http_remote_name;
+auth_request_set $email $upstream_http_remote_email;
+
+## Inject the metadata response headers from the variables into the request made to the backend.
+proxy_set_header Remote-User $user;
+proxy_set_header Remote-Groups $groups;
+proxy_set_header Remote-Email $email;
+proxy_set_header Remote-Name $name;
+
+## Refresh the cookie as needed
+auth_request_set $auth_cookie $upstream_http_set_cookie;
+add_header Set-Cookie $auth_cookie;
+
+## Pass the location header back up if it exists
+auth_request_set $redirection_url $upstream_http_location;
+add_header Location $redirection_url;

docker/main/rootfs/usr/local/nginx/conf/go2rtc_upstream.conf

@@ -0,0 +1,4 @@
+upstream go2rtc {
+    server 127.0.0.1:1984;
+    keepalive 1024;
+}

docker/main/rootfs/usr/local/nginx/conf/nginx.conf

@@ -56,13 +56,13 @@ http {
         keepalive 1024;
     }
 
-    upstream go2rtc {
-        server 127.0.0.1:1984;
-        keepalive 1024;
-    }
+    include go2rtc_upstream.conf;
 
     server {
-        listen 5000;
+        # intended for internal traffic, not protected by auth
+        listen [::]:5000 ipv6only=off;
+
+        include listen.conf;
 
         # vod settings
         vod_base_url '';
@@ -95,7 +95,10 @@ http {
         gzip on;
         gzip_types application/vnd.apple.mpegurl;
 
+        include auth_location.conf;
+
         location /vod/ {
+            include auth_request.conf;
             aio threads;
             vod hls;
 
@@ -107,6 +110,7 @@ http {
         }
 
         location /stream/ {
+            include auth_request.conf;
             add_header Cache-Control "no-store";
             expires off;
 
@@ -121,12 +125,14 @@ http {
         }
 
         location /clips/ {
-
+            include auth_request.conf;
             types {
                 video/mp4 mp4;
                 image/jpeg jpg;
             }
 
+            expires 7d;
+            add_header Cache-Control "public";
             autoindex on;
             root /media/frigate;
         }
@@ -137,6 +143,7 @@ http {
         }
 
         location /recordings/ {
+            include auth_request.conf;
             types {
                 video/mp4 mp4;
             }
@@ -147,6 +154,7 @@ http {
         }
 
         location /exports/ {
+            include auth_request.conf;
             types {
                 video/mp4 mp4;
             }
@@ -157,17 +165,20 @@ http {
         }
 
         location /ws {
+            include auth_request.conf;
             proxy_pass http://mqtt_ws/;
             include proxy.conf;
         }
 
         location /live/jsmpeg/ {
+            include auth_request.conf;
             proxy_pass http://jsmpeg/;
             include proxy.conf;
         }
 
         # frigate lovelace card uses this path
         location /live/mse/api/ws {
+            include auth_request.conf;
             limit_except GET {
                 deny  all;
             }
@@ -176,6 +187,7 @@ http {
         }
 
         location /live/webrtc/api/ws {
+            include auth_request.conf;
             limit_except GET {
                 deny  all;
             }
@@ -185,6 +197,7 @@ http {
 
         # pass through go2rtc player
         location /live/webrtc/webrtc.html {
+            include auth_request.conf;
             limit_except GET {
                 deny  all;
             }
@@ -194,6 +207,7 @@ http {
 
         # frontend uses this to fetch the version
         location /api/go2rtc/api {
+            include auth_request.conf;
             limit_except GET {
                 deny  all;
             }
@@ -203,6 +217,7 @@ http {
 
         # integration uses this to add webrtc candidate
         location /api/go2rtc/webrtc {
+            include auth_request.conf;
             limit_except POST {
                 deny  all;
             }
@@ -210,13 +225,15 @@ http {
             include proxy.conf;
         }
 
-        location ~* /api/.*\.(jpg|jpeg|png)$ {
+        location ~* /api/.*\.(jpg|jpeg|png|webp|gif)$ {
+            include auth_request.conf;
             rewrite ^/api/(.*)$ $1 break;
             proxy_pass http://frigate_api;
             include proxy.conf;
         }
 
         location /api/ {
+            include auth_request.conf;
             add_header Cache-Control "no-store";
             expires off;
             proxy_pass http://frigate_api/;
@@ -231,27 +248,38 @@ http {
             add_header X-Cache-Status $upstream_cache_status;
 
             location /api/vod/ {
+                include auth_request.conf;
                 proxy_pass http://frigate_api/vod/;
                 include proxy.conf;
                 proxy_cache off;
             }
 
+            location /api/login {
+                auth_request off;
+                rewrite ^/api(/.*)$ $1 break;
+                proxy_pass http://frigate_api;
+                include proxy.conf;
+            }
+
             location /api/stats {
+                include auth_request.conf;
                 access_log off;
-                rewrite ^/api/(.*)$ $1 break;
+                rewrite ^/api(/.*)$ $1 break;
                 proxy_pass http://frigate_api;
                 include proxy.conf;
             }
 
             location /api/version {
+                include auth_request.conf;
                 access_log off;
-                rewrite ^/api/(.*)$ $1 break;
+                rewrite ^/api(/.*)$ $1 break;
                 proxy_pass http://frigate_api;
                 include proxy.conf;
             }
         }
 
         location / {
+            # do not require auth for static assets
             add_header Cache-Control "no-store";
             expires off;
 
@@ -273,22 +301,7 @@ http {
             sub_filter_once off;
 
             root /opt/frigate/web;
-            try_files $uri $uri/ /index.html;
-        }
-    }
-}
-
-rtmp {
-    server {
-        listen 1935;
-        chunk_size 4096;
-        allow publish 127.0.0.1;
-        deny publish all;
-        allow play all;
-        application live {
-            live on;
-            record off;
-            meta copy;
+            try_files $uri $uri.html $uri/ /index.html;
         }
     }
 }

docker/main/rootfs/usr/local/nginx/conf/proxy.conf

@@ -1,4 +1,26 @@
-proxy_http_version 1.1;
+## Headers
+proxy_set_header Host $host;
 proxy_set_header Upgrade $http_upgrade;
 proxy_set_header Connection "Upgrade";
-proxy_set_header Host $host;
+proxy_set_header X-Original-URL $scheme://$http_host$request_uri;
+proxy_set_header X-Forwarded-Proto $scheme;
+proxy_set_header X-Forwarded-Host $http_host;
+proxy_set_header X-Forwarded-URI $request_uri;
+proxy_set_header X-Forwarded-Ssl on;
+proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+proxy_set_header X-Real-IP $remote_addr;
+
+## Basic Proxy Configuration
+client_body_buffer_size 128k;
+proxy_next_upstream error timeout invalid_header http_500 http_502 http_503; ## Timeout if the real server is dead.
+proxy_redirect  http://  $scheme://;
+proxy_http_version 1.1;
+proxy_cache_bypass $cookie_session;
+proxy_no_cache $cookie_session;
+proxy_buffers 64 256k;
+
+## Advanced Proxy Configuration
+send_timeout 5m;
+proxy_read_timeout 360;
+proxy_send_timeout 360;
+proxy_connect_timeout 360;

docker/main/rootfs/usr/local/nginx/conf/proxy_trusted_headers.conf

@@ -0,0 +1,25 @@
+# Header used to validate reverse proxy trust
+proxy_set_header X-Proxy-Secret $http_x_proxy_secret;
+
+# these headers will be copied to the /auth request and are available
+# to be mapped in the config to Frigate's remote-user header
+
+# List of headers sent by common authentication proxies:
+# - Authelia
+# - Traefik forward auth
+# - oauth2_proxy
+# - Authentik
+
+proxy_set_header Remote-User $http_remote_user;
+proxy_set_header Remote-Groups $http_remote_groups;
+proxy_set_header Remote-Email $http_remote_email;
+proxy_set_header Remote-Name $http_remote_name;
+proxy_set_header X-Forwarded-User $http_x_forwarded_user;
+proxy_set_header X-Forwarded-Groups $http_x_forwarded_groups;
+proxy_set_header X-Forwarded-Email $http_x_forwarded_email;
+proxy_set_header X-Forwarded-Preferred-Username $http_x_forwarded_preferred_username;
+proxy_set_header X-authentik-username $http_x_authentik_username;
+proxy_set_header X-authentik-groups $http_x_authentik_groups;
+proxy_set_header X-authentik-email $http_x_authentik_email;
+proxy_set_header X-authentik-name $http_x_authentik_name;
+proxy_set_header X-authentik-uid $http_x_authentik_uid;

docker/main/rootfs/usr/local/nginx/get_tls_settings.py

@@ -0,0 +1,28 @@
+"""Prints the tls config as json to stdout."""
+
+import json
+import os
+
+import yaml
+
+config_file = os.environ.get("CONFIG_FILE", "/config/config.yml")
+
+# Check if we can use .yaml instead of .yml
+config_file_yaml = config_file.replace(".yml", ".yaml")
+if os.path.isfile(config_file_yaml):
+    config_file = config_file_yaml
+
+try:
+    with open(config_file) as f:
+        raw_config = f.read()
+
+    if config_file.endswith((".yaml", ".yml")):
+        config: dict[str, any] = yaml.safe_load(raw_config)
+    elif config_file.endswith(".json"):
+        config: dict[str, any] = json.loads(raw_config)
+except FileNotFoundError:
+    config: dict[str, any] = {}
+
+tls_config: dict[str, any] = config.get("tls", {"enabled": True})
+
+print(json.dumps(tls_config))

docker/main/rootfs/usr/local/nginx/templates/listen.gotmpl

@@ -0,0 +1,30 @@
+{{ if not .enabled }}
+# intended for external traffic, protected by auth
+listen [::]:8080 ipv6only=off;
+{{ else }}
+# intended for external traffic, protected by auth
+listen [::]:8080 ipv6only=off ssl;
+
+ssl_certificate /etc/letsencrypt/live/frigate/fullchain.pem;
+ssl_certificate_key /etc/letsencrypt/live/frigate/privkey.pem;
+
+# generated 2024-06-01, Mozilla Guideline v5.7, nginx 1.25.3, OpenSSL 1.1.1w, modern configuration, no OCSP
+# https://ssl-config.mozilla.org/#server=nginx&version=1.25.3&config=modern&openssl=1.1.1w&ocsp=false&guideline=5.7
+ssl_session_timeout 1d;
+ssl_session_cache shared:MozSSL:10m;  # about 40000 sessions
+ssl_session_tickets off;
+
+# modern configuration
+ssl_protocols TLSv1.3;
+ssl_prefer_server_ciphers off;
+
+# HSTS (ngx_http_headers_module is required) (63072000 seconds)
+add_header Strict-Transport-Security "max-age=63072000" always;
+
+# ACME challenge location
+location /.well-known/acme-challenge/ {
+    default_type "text/plain";
+    root /etc/letsencrypt/www;
+}
+{{ end }}
+

docker/rockchip/Dockerfile

@@ -9,24 +9,18 @@ COPY docker/rockchip/requirements-wheels-rk.txt /requirements-wheels-rk.txt
 RUN sed -i "/https:\/\//d" /requirements-wheels.txt
 RUN pip3 wheel --wheel-dir=/rk-wheels -c /requirements-wheels.txt -r /requirements-wheels-rk.txt
 
-FROM deps AS rk-deps
+FROM deps AS rk-frigate
 ARG TARGETARCH
 
-RUN --mount=type=bind,from=rk-wheels,source=/rk-wheels,target=/deps/rk-wheels \ 
-    pip3 install -U /deps/rk-wheels/*.whl 
+RUN --mount=type=bind,from=rk-wheels,source=/rk-wheels,target=/deps/rk-wheels \
+    pip3 install -U /deps/rk-wheels/*.whl
 
 WORKDIR /opt/frigate/
 COPY --from=rootfs / /
 
-ADD https://github.com/MarcA711/rknpu2/releases/download/v1.5.2/librknnrt_rk356x.so /usr/lib/
-ADD https://github.com/MarcA711/rknpu2/releases/download/v1.5.2/librknnrt_rk3588.so /usr/lib/
-
-ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3562/yolov8n-320x320-rk3562.rknn /models/rknn/
-ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3566/yolov8n-320x320-rk3566.rknn /models/rknn/
-ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3568/yolov8n-320x320-rk3568.rknn /models/rknn/
-ADD https://github.com/MarcA711/rknn-models/releases/download/v1.5.2-rk3588/yolov8n-320x320-rk3588.rknn /models/rknn/
+ADD https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/librknnrt.so /usr/lib/
 
 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/6.0-1/ffmpeg /usr/lib/btbn-ffmpeg/bin/
-ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.0-1/ffprobe /usr/lib/btbn-ffmpeg/bin/
+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/

docker/rockchip/requirements-wheels-rk.txt

@@ -1,2 +1 @@
-hide-warnings == 0.17
-rknn-toolkit-lite2 @ https://github.com/MarcA711/rknn-toolkit2/releases/download/v1.5.2/rknn_toolkit_lite2-1.5.2-cp39-cp39-linux_aarch64.whl
+rknn-toolkit-lite2 @ https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/rknn_toolkit_lite2-2.0.0b0-cp39-cp39-linux_aarch64.whl

docker/rockchip/rk.hcl

@@ -1,9 +1,3 @@
-target wget {
-  dockerfile = "docker/main/Dockerfile"
-  platforms = ["linux/arm64"]
-  target = "wget"
-}
-
 target wheels {
   dockerfile = "docker/main/Dockerfile"
   platforms = ["linux/arm64"]
@@ -25,7 +19,6 @@ target rootfs {
 target rk {
   dockerfile = "docker/rockchip/Dockerfile"
   contexts = {
-    wget = "target:wget",
     wheels = "target:wheels",
     deps = "target:deps",
     rootfs = "target:rootfs"

docker/rocm/Dockerfile

@@ -0,0 +1,106 @@
+# syntax=docker/dockerfile:1.4
+
+# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
+ARG DEBIAN_FRONTEND=noninteractive
+ARG ROCM=5.7.3
+ARG AMDGPU=gfx900
+ARG HSA_OVERRIDE_GFX_VERSION
+ARG HSA_OVERRIDE
+
+#######################################################################
+FROM ubuntu:focal as rocm
+
+ARG ROCM
+
+RUN apt-get update && apt-get -y upgrade
+RUN apt-get -y install gnupg wget
+
+RUN mkdir --parents --mode=0755 /etc/apt/keyrings
+
+RUN wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | tee /etc/apt/keyrings/rocm.gpg > /dev/null
+COPY docker/rocm/rocm.list /etc/apt/sources.list.d/
+COPY docker/rocm/rocm-pin-600 /etc/apt/preferences.d/
+
+RUN apt-get update
+
+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* /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/
+RUN echo /opt/rocm/lib|tee /opt/rocm-dist/etc/ld.so.conf.d/rocm.conf
+
+#######################################################################
+FROM --platform=linux/amd64 debian:11 as debian-base
+
+RUN apt-get update && apt-get -y upgrade
+RUN apt-get -y install --no-install-recommends libelf1 libdrm2 libdrm-amdgpu1 libnuma1 kmod
+
+RUN apt-get -y install python3
+
+#######################################################################
+# ROCm does not come with migraphx wrappers for python 3.9, so we build it here
+FROM debian-base as debian-build
+
+ARG ROCM
+
+COPY --from=rocm /opt/rocm-$ROCM /opt/rocm-$ROCM
+RUN ln -s /opt/rocm-$ROCM /opt/rocm
+
+RUN apt-get -y install g++ cmake
+RUN apt-get -y install python3-pybind11 python3.9-distutils python3-dev
+
+WORKDIR /opt/build
+
+COPY docker/rocm/migraphx .
+
+RUN mkdir build && cd build && cmake .. && make install
+
+#######################################################################
+FROM deps AS deps-prelim
+
+# need this to install libnuma1
+RUN apt-get update
+# no ugprade?!?!
+RUN apt-get -y install libnuma1
+
+WORKDIR /opt/frigate/
+COPY --from=rootfs / /
+COPY docker/rocm/rootfs/ /
+
+#######################################################################
+FROM scratch AS rocm-dist
+
+ARG ROCM
+ARG AMDGPU
+
+COPY --from=rocm /opt/rocm-$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/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-$ROCM/lib/
+
+#######################################################################
+FROM deps-prelim AS rocm-prelim-hsa-override0
+
+ENV HSA_ENABLE_SDMA=0
+
+COPY --from=rocm-dist / /
+
+RUN ldconfig
+
+#######################################################################
+FROM rocm-prelim-hsa-override0 as rocm-prelim-hsa-override1
+
+ARG HSA_OVERRIDE_GFX_VERSION
+ENV HSA_OVERRIDE_GFX_VERSION=$HSA_OVERRIDE_GFX_VERSION
+
+#######################################################################
+FROM rocm-prelim-hsa-override$HSA_OVERRIDE as rocm-deps
+
+# Request yolov8 download at startup
+ENV DOWNLOAD_YOLOV8=1
+

docker/rocm/migraphx/CMakeLists.txt

@@ -0,0 +1,26 @@
+
+cmake_minimum_required(VERSION 3.1)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
+set(CMAKE_CXX_EXTENSIONS OFF)
+
+if(NOT CMAKE_BUILD_TYPE)
+  set(CMAKE_BUILD_TYPE Release)
+endif()
+
+SET(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE)
+
+project(migraphx_py)
+
+include_directories(/opt/rocm/include)
+
+find_package(pybind11 REQUIRED)
+pybind11_add_module(migraphx migraphx_py.cpp)
+
+target_link_libraries(migraphx PRIVATE /opt/rocm/lib/libmigraphx.so /opt/rocm/lib/libmigraphx_tf.so /opt/rocm/lib/libmigraphx_onnx.so)
+
+install(TARGETS migraphx
+  COMPONENT python
+  LIBRARY DESTINATION /opt/rocm/lib
+)

docker/rocm/migraphx/migraphx_py.cpp

@@ -0,0 +1,582 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+#include <pybind11/numpy.h>
+#include <migraphx/program.hpp>
+#include <migraphx/instruction_ref.hpp>
+#include <migraphx/operation.hpp>
+#include <migraphx/quantization.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/ref/target.hpp>
+#include <migraphx/stringutils.hpp>
+#include <migraphx/tf.hpp>
+#include <migraphx/onnx.hpp>
+#include <migraphx/load_save.hpp>
+#include <migraphx/register_target.hpp>
+#include <migraphx/json.hpp>
+#include <migraphx/make_op.hpp>
+#include <migraphx/op/common.hpp>
+
+#ifdef HAVE_GPU
+#include <migraphx/gpu/hip.hpp>
+#endif
+
+using half   = half_float::half;
+namespace py = pybind11;
+
+#ifdef __clang__
+#define MIGRAPHX_PUSH_UNUSED_WARNING \
+    _Pragma("clang diagnostic push") \
+        _Pragma("clang diagnostic ignored \"-Wused-but-marked-unused\"")
+#define MIGRAPHX_POP_WARNING _Pragma("clang diagnostic pop")
+#else
+#define MIGRAPHX_PUSH_UNUSED_WARNING
+#define MIGRAPHX_POP_WARNING
+#endif
+#define MIGRAPHX_PYBIND11_MODULE(...) \
+    MIGRAPHX_PUSH_UNUSED_WARNING      \
+    PYBIND11_MODULE(__VA_ARGS__)      \
+    MIGRAPHX_POP_WARNING
+
+#define MIGRAPHX_PYTHON_GENERATE_SHAPE_ENUM(x, t) .value(#x, migraphx::shape::type_t::x)
+namespace migraphx {
+
+migraphx::value to_value(py::kwargs kwargs);
+migraphx::value to_value(py::list lst);
+
+template <class T, class F>
+void visit_py(T x, F f)
+{
+    if(py::isinstance<py::kwargs>(x))
+    {
+        f(to_value(x.template cast<py::kwargs>()));
+    }
+    else if(py::isinstance<py::list>(x))
+    {
+        f(to_value(x.template cast<py::list>()));
+    }
+    else if(py::isinstance<py::bool_>(x))
+    {
+        f(x.template cast<bool>());
+    }
+    else if(py::isinstance<py::int_>(x) or py::hasattr(x, "__index__"))
+    {
+        f(x.template cast<int>());
+    }
+    else if(py::isinstance<py::float_>(x))
+    {
+        f(x.template cast<float>());
+    }
+    else if(py::isinstance<py::str>(x))
+    {
+        f(x.template cast<std::string>());
+    }
+    else if(py::isinstance<migraphx::shape::dynamic_dimension>(x))
+    {
+        f(migraphx::to_value(x.template cast<migraphx::shape::dynamic_dimension>()));
+    }
+    else
+    {
+        MIGRAPHX_THROW("VISIT_PY: Unsupported data type!");
+    }
+}
+
+migraphx::value to_value(py::list lst)
+{
+    migraphx::value v = migraphx::value::array{};
+    for(auto val : lst)
+    {
+        visit_py(val, [&](auto py_val) { v.push_back(py_val); });
+    }
+
+    return v;
+}
+
+migraphx::value to_value(py::kwargs kwargs)
+{
+    migraphx::value v = migraphx::value::object{};
+
+    for(auto arg : kwargs)
+    {
+        auto&& key = py::str(arg.first);
+        auto&& val = arg.second;
+        visit_py(val, [&](auto py_val) { v[key] = py_val; });
+    }
+    return v;
+}
+} // namespace migraphx
+
+namespace pybind11 {
+namespace detail {
+
+template <>
+struct npy_format_descriptor<half>
+{
+    static std::string format()
+    {
+        // following: https://docs.python.org/3/library/struct.html#format-characters
+        return "e";
+    }
+    static constexpr auto name() { return _("half"); }
+};
+
+} // namespace detail
+} // namespace pybind11
+
+template <class F>
+void visit_type(const migraphx::shape& s, F f)
+{
+    s.visit_type(f);
+}
+
+template <class T, class F>
+void visit(const migraphx::raw_data<T>& x, F f)
+{
+    x.visit(f);
+}
+
+template <class F>
+void visit_types(F f)
+{
+    migraphx::shape::visit_types(f);
+}
+
+template <class T>
+py::buffer_info to_buffer_info(T& x)
+{
+    migraphx::shape s = x.get_shape();
+    assert(s.type() != migraphx::shape::tuple_type);
+    if(s.dynamic())
+        MIGRAPHX_THROW("MIGRAPHX PYTHON: dynamic shape argument passed to to_buffer_info");
+    auto strides = s.strides();
+    std::transform(
+        strides.begin(), strides.end(), strides.begin(), [&](auto i) { return i * s.type_size(); });
+    py::buffer_info b;
+    visit_type(s, [&](auto as) {
+        // migraphx use int8_t data to store bool type, we need to
+        // explicitly specify the data type as bool for python
+        if(s.type() == migraphx::shape::bool_type)
+        {
+            b = py::buffer_info(x.data(),
+                                as.size(),
+                                py::format_descriptor<bool>::format(),
+                                s.ndim(),
+                                s.lens(),
+                                strides);
+        }
+        else
+        {
+            b = py::buffer_info(x.data(),
+                                as.size(),
+                                py::format_descriptor<decltype(as())>::format(),
+                                s.ndim(),
+                                s.lens(),
+                                strides);
+        }
+    });
+    return b;
+}
+
+migraphx::shape to_shape(const py::buffer_info& info)
+{
+    migraphx::shape::type_t t;
+    std::size_t n = 0;
+    visit_types([&](auto as) {
+        if(info.format == py::format_descriptor<decltype(as())>::format() or
+           (info.format == "l" and py::format_descriptor<decltype(as())>::format() == "q") or
+           (info.format == "L" and py::format_descriptor<decltype(as())>::format() == "Q"))
+        {
+            t = as.type_enum();
+            n = sizeof(as());
+        }
+        else if(info.format == "?" and py::format_descriptor<decltype(as())>::format() == "b")
+        {
+            t = migraphx::shape::bool_type;
+            n = sizeof(bool);
+        }
+    });
+
+    if(n == 0)
+    {
+        MIGRAPHX_THROW("MIGRAPHX PYTHON: Unsupported data type " + info.format);
+    }
+
+    auto strides = info.strides;
+    std::transform(strides.begin(), strides.end(), strides.begin(), [&](auto i) -> std::size_t {
+        return n > 0 ? i / n : 0;
+    });
+
+    // scalar support
+    if(info.shape.empty())
+    {
+        return migraphx::shape{t};
+    }
+    else
+    {
+        return migraphx::shape{t, info.shape, strides};
+    }
+}
+
+MIGRAPHX_PYBIND11_MODULE(migraphx, m)
+{
+    py::class_<migraphx::shape> shape_cls(m, "shape");
+    shape_cls
+        .def(py::init([](py::kwargs kwargs) {
+            auto v = migraphx::to_value(kwargs);
+            auto t = migraphx::shape::parse_type(v.get("type", "float"));
+            if(v.contains("dyn_dims"))
+            {
+                auto dyn_dims =
+                    migraphx::from_value<std::vector<migraphx::shape::dynamic_dimension>>(
+                        v.at("dyn_dims"));
+                return migraphx::shape(t, dyn_dims);
+            }
+            auto lens = v.get<std::size_t>("lens", {1});
+            if(v.contains("strides"))
+                return migraphx::shape(t, lens, v.at("strides").to_vector<std::size_t>());
+            else
+                return migraphx::shape(t, lens);
+        }))
+        .def("type", &migraphx::shape::type)
+        .def("lens", &migraphx::shape::lens)
+        .def("strides", &migraphx::shape::strides)
+        .def("ndim", &migraphx::shape::ndim)
+        .def("elements", &migraphx::shape::elements)
+        .def("bytes", &migraphx::shape::bytes)
+        .def("type_string", &migraphx::shape::type_string)
+        .def("type_size", &migraphx::shape::type_size)
+        .def("dyn_dims", &migraphx::shape::dyn_dims)
+        .def("packed", &migraphx::shape::packed)
+        .def("transposed", &migraphx::shape::transposed)
+        .def("broadcasted", &migraphx::shape::broadcasted)
+        .def("standard", &migraphx::shape::standard)
+        .def("scalar", &migraphx::shape::scalar)
+        .def("dynamic", &migraphx::shape::dynamic)
+        .def("__eq__", std::equal_to<migraphx::shape>{})
+        .def("__ne__", std::not_equal_to<migraphx::shape>{})
+        .def("__repr__", [](const migraphx::shape& s) { return migraphx::to_string(s); });
+
+    py::enum_<migraphx::shape::type_t>(shape_cls, "type_t")
+        MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_PYTHON_GENERATE_SHAPE_ENUM);
+
+    py::class_<migraphx::shape::dynamic_dimension>(shape_cls, "dynamic_dimension")
+        .def(py::init<>())
+        .def(py::init<std::size_t, std::size_t>())
+        .def(py::init<std::size_t, std::size_t, std::set<std::size_t>>())
+        .def_readwrite("min", &migraphx::shape::dynamic_dimension::min)
+        .def_readwrite("max", &migraphx::shape::dynamic_dimension::max)
+        .def_readwrite("optimals", &migraphx::shape::dynamic_dimension::optimals)
+        .def("is_fixed", &migraphx::shape::dynamic_dimension::is_fixed);
+
+    py::class_<migraphx::argument>(m, "argument", py::buffer_protocol())
+        .def_buffer([](migraphx::argument& x) -> py::buffer_info { return to_buffer_info(x); })
+        .def(py::init([](py::buffer b) {
+            py::buffer_info info = b.request();
+            return migraphx::argument(to_shape(info), info.ptr);
+        }))
+        .def("get_shape", &migraphx::argument::get_shape)
+        .def("data_ptr",
+             [](migraphx::argument& x) { return reinterpret_cast<std::uintptr_t>(x.data()); })
+        .def("tolist",
+             [](migraphx::argument& x) {
+                 py::list l{x.get_shape().elements()};
+                 visit(x, [&](auto data) { l = py::cast(data.to_vector()); });
+                 return l;
+             })
+        .def("__eq__", std::equal_to<migraphx::argument>{})
+        .def("__ne__", std::not_equal_to<migraphx::argument>{})
+        .def("__repr__", [](const migraphx::argument& x) { return migraphx::to_string(x); });
+
+    py::class_<migraphx::target>(m, "target");
+
+    py::class_<migraphx::instruction_ref>(m, "instruction_ref")
+        .def("shape", [](migraphx::instruction_ref i) { return i->get_shape(); })
+        .def("op", [](migraphx::instruction_ref i) { return i->get_operator(); });
+
+    py::class_<migraphx::module, std::unique_ptr<migraphx::module, py::nodelete>>(m, "module")
+        .def("print", [](const migraphx::module& mm) { std::cout << mm << std::endl; })
+        .def(
+            "add_instruction",
+            [](migraphx::module& mm,
+               const migraphx::operation& op,
+               std::vector<migraphx::instruction_ref>& args,
+               std::vector<migraphx::module*>& mod_args) {
+                return mm.add_instruction(op, args, mod_args);
+            },
+            py::arg("op"),
+            py::arg("args"),
+            py::arg("mod_args") = std::vector<migraphx::module*>{})
+        .def(
+            "add_literal",
+            [](migraphx::module& mm, py::buffer data) {
+                py::buffer_info info = data.request();
+                auto literal_shape   = to_shape(info);
+                return mm.add_literal(literal_shape, reinterpret_cast<char*>(info.ptr));
+            },
+            py::arg("data"))
+        .def(
+            "add_parameter",
+            [](migraphx::module& mm, const std::string& name, const migraphx::shape shape) {
+                return mm.add_parameter(name, shape);
+            },
+            py::arg("name"),
+            py::arg("shape"))
+        .def(
+            "add_return",
+            [](migraphx::module& mm, std::vector<migraphx::instruction_ref>& args) {
+                return mm.add_return(args);
+            },
+            py::arg("args"))
+        .def("__repr__", [](const migraphx::module& mm) { return migraphx::to_string(mm); });
+
+    py::class_<migraphx::program>(m, "program")
+        .def(py::init([]() { return migraphx::program(); }))
+        .def("get_parameter_names", &migraphx::program::get_parameter_names)
+        .def("get_parameter_shapes", &migraphx::program::get_parameter_shapes)
+        .def("get_output_shapes", &migraphx::program::get_output_shapes)
+        .def("is_compiled", &migraphx::program::is_compiled)
+        .def(
+            "compile",
+            [](migraphx::program& p,
+               const migraphx::target& t,
+               bool offload_copy,
+               bool fast_math,
+               bool exhaustive_tune) {
+                migraphx::compile_options options;
+                options.offload_copy    = offload_copy;
+                options.fast_math       = fast_math;
+                options.exhaustive_tune = exhaustive_tune;
+                p.compile(t, options);
+            },
+            py::arg("t"),
+            py::arg("offload_copy")    = true,
+            py::arg("fast_math")       = true,
+            py::arg("exhaustive_tune") = false)
+        .def("get_main_module", [](const migraphx::program& p) { return p.get_main_module(); })
+        .def(
+            "create_module",
+            [](migraphx::program& p, const std::string& name) { return p.create_module(name); },
+            py::arg("name"))
+        .def("run",
+             [](migraphx::program& p, py::dict params) {
+                 migraphx::parameter_map pm;
+                 for(auto x : params)
+                 {
+                     std::string key      = x.first.cast<std::string>();
+                     py::buffer b         = x.second.cast<py::buffer>();
+                     py::buffer_info info = b.request();
+                     pm[key]              = migraphx::argument(to_shape(info), info.ptr);
+                 }
+                 return p.eval(pm);
+             })
+        .def("run_async",
+             [](migraphx::program& p,
+                py::dict params,
+                std::uintptr_t stream,
+                std::string stream_name) {
+                 migraphx::parameter_map pm;
+                 for(auto x : params)
+                 {
+                     std::string key      = x.first.cast<std::string>();
+                     py::buffer b         = x.second.cast<py::buffer>();
+                     py::buffer_info info = b.request();
+                     pm[key]              = migraphx::argument(to_shape(info), info.ptr);
+                 }
+                 migraphx::execution_environment exec_env{
+                     migraphx::any_ptr(reinterpret_cast<void*>(stream), stream_name), true};
+                 return p.eval(pm, exec_env);
+             })
+        .def("sort", &migraphx::program::sort)
+        .def("print", [](const migraphx::program& p) { std::cout << p << std::endl; })
+        .def("__eq__", std::equal_to<migraphx::program>{})
+        .def("__ne__", std::not_equal_to<migraphx::program>{})
+        .def("__repr__", [](const migraphx::program& p) { return migraphx::to_string(p); });
+
+    py::class_<migraphx::operation> op(m, "op");
+    op.def(py::init([](const std::string& name, py::kwargs kwargs) {
+          migraphx::value v = migraphx::value::object{};
+          if(kwargs)
+          {
+              v = migraphx::to_value(kwargs);
+          }
+          return migraphx::make_op(name, v);
+      }))
+        .def("name", &migraphx::operation::name);
+
+    py::enum_<migraphx::op::pooling_mode>(op, "pooling_mode")
+        .value("average", migraphx::op::pooling_mode::average)
+        .value("max", migraphx::op::pooling_mode::max)
+        .value("lpnorm", migraphx::op::pooling_mode::lpnorm);
+
+    py::enum_<migraphx::op::rnn_direction>(op, "rnn_direction")
+        .value("forward", migraphx::op::rnn_direction::forward)
+        .value("reverse", migraphx::op::rnn_direction::reverse)
+        .value("bidirectional", migraphx::op::rnn_direction::bidirectional);
+
+    m.def(
+        "argument_from_pointer",
+        [](const migraphx::shape shape, const int64_t address) {
+            return migraphx::argument(shape, reinterpret_cast<void*>(address));
+        },
+        py::arg("shape"),
+        py::arg("address"));
+
+    m.def(
+        "parse_tf",
+        [](const std::string& filename,
+           bool is_nhwc,
+           unsigned int batch_size,
+           std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims,
+           std::vector<std::string> output_names) {
+            return migraphx::parse_tf(
+                filename, migraphx::tf_options{is_nhwc, batch_size, map_input_dims, output_names});
+        },
+        "Parse tf protobuf (default format is nhwc)",
+        py::arg("filename"),
+        py::arg("is_nhwc")        = true,
+        py::arg("batch_size")     = 1,
+        py::arg("map_input_dims") = std::unordered_map<std::string, std::vector<std::size_t>>(),
+        py::arg("output_names")   = std::vector<std::string>());
+
+    m.def(
+        "parse_onnx",
+        [](const std::string& filename,
+           unsigned int default_dim_value,
+           migraphx::shape::dynamic_dimension default_dyn_dim_value,
+           std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims,
+           std::unordered_map<std::string, std::vector<migraphx::shape::dynamic_dimension>>
+               map_dyn_input_dims,
+           bool skip_unknown_operators,
+           bool print_program_on_error,
+           int64_t max_loop_iterations) {
+            migraphx::onnx_options options;
+            options.default_dim_value      = default_dim_value;
+            options.default_dyn_dim_value  = default_dyn_dim_value;
+            options.map_input_dims         = map_input_dims;
+            options.map_dyn_input_dims     = map_dyn_input_dims;
+            options.skip_unknown_operators = skip_unknown_operators;
+            options.print_program_on_error = print_program_on_error;
+            options.max_loop_iterations    = max_loop_iterations;
+            return migraphx::parse_onnx(filename, options);
+        },
+        "Parse onnx file",
+        py::arg("filename"),
+        py::arg("default_dim_value")     = 0,
+        py::arg("default_dyn_dim_value") = migraphx::shape::dynamic_dimension{1, 1},
+        py::arg("map_input_dims") = std::unordered_map<std::string, std::vector<std::size_t>>(),
+        py::arg("map_dyn_input_dims") =
+            std::unordered_map<std::string, std::vector<migraphx::shape::dynamic_dimension>>(),
+        py::arg("skip_unknown_operators") = false,
+        py::arg("print_program_on_error") = false,
+        py::arg("max_loop_iterations")    = 10);
+
+    m.def(
+        "parse_onnx_buffer",
+        [](const std::string& onnx_buffer,
+           unsigned int default_dim_value,
+           migraphx::shape::dynamic_dimension default_dyn_dim_value,
+           std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims,
+           std::unordered_map<std::string, std::vector<migraphx::shape::dynamic_dimension>>
+               map_dyn_input_dims,
+           bool skip_unknown_operators,
+           bool print_program_on_error) {
+            migraphx::onnx_options options;
+            options.default_dim_value      = default_dim_value;
+            options.default_dyn_dim_value  = default_dyn_dim_value;
+            options.map_input_dims         = map_input_dims;
+            options.map_dyn_input_dims     = map_dyn_input_dims;
+            options.skip_unknown_operators = skip_unknown_operators;
+            options.print_program_on_error = print_program_on_error;
+            return migraphx::parse_onnx_buffer(onnx_buffer, options);
+        },
+        "Parse onnx file",
+        py::arg("filename"),
+        py::arg("default_dim_value")     = 0,
+        py::arg("default_dyn_dim_value") = migraphx::shape::dynamic_dimension{1, 1},
+        py::arg("map_input_dims") = std::unordered_map<std::string, std::vector<std::size_t>>(),
+        py::arg("map_dyn_input_dims") =
+            std::unordered_map<std::string, std::vector<migraphx::shape::dynamic_dimension>>(),
+        py::arg("skip_unknown_operators") = false,
+        py::arg("print_program_on_error") = false);
+
+    m.def(
+        "load",
+        [](const std::string& name, const std::string& format) {
+            migraphx::file_options options;
+            options.format = format;
+            return migraphx::load(name, options);
+        },
+        "Load MIGraphX program",
+        py::arg("filename"),
+        py::arg("format") = "msgpack");
+
+    m.def(
+        "save",
+        [](const migraphx::program& p, const std::string& name, const std::string& format) {
+            migraphx::file_options options;
+            options.format = format;
+            return migraphx::save(p, name, options);
+        },
+        "Save MIGraphX program",
+        py::arg("p"),
+        py::arg("filename"),
+        py::arg("format") = "msgpack");
+
+    m.def("get_target", &migraphx::make_target);
+    m.def("create_argument", [](const migraphx::shape& s, const std::vector<double>& values) {
+        if(values.size() != s.elements())
+            MIGRAPHX_THROW("Values and shape elements do not match");
+        migraphx::argument a{s};
+        a.fill(values.begin(), values.end());
+        return a;
+    });
+    m.def("generate_argument", &migraphx::generate_argument, py::arg("s"), py::arg("seed") = 0);
+    m.def("fill_argument", &migraphx::fill_argument, py::arg("s"), py::arg("value"));
+    m.def("quantize_fp16",
+          &migraphx::quantize_fp16,
+          py::arg("prog"),
+          py::arg("ins_names") = std::vector<std::string>{"all"});
+    m.def("quantize_int8",
+          &migraphx::quantize_int8,
+          py::arg("prog"),
+          py::arg("t"),
+          py::arg("calibration") = std::vector<migraphx::parameter_map>{},
+          py::arg("ins_names")   = std::vector<std::string>{"dot", "convolution"});
+
+#ifdef HAVE_GPU
+    m.def("allocate_gpu", &migraphx::gpu::allocate_gpu, py::arg("s"), py::arg("host") = false);
+    m.def("to_gpu", &migraphx::gpu::to_gpu, py::arg("arg"), py::arg("host") = false);
+    m.def("from_gpu", &migraphx::gpu::from_gpu);
+    m.def("gpu_sync", [] { migraphx::gpu::gpu_sync(); });
+#endif
+
+#ifdef VERSION_INFO
+    m.attr("__version__") = VERSION_INFO;
+#else
+    m.attr("__version__") = "dev";
+#endif
+}

docker/rocm/rocm-pin-600

@@ -0,0 +1,3 @@
+Package: *
+Pin: release o=repo.radeon.com
+Pin-Priority: 600

docker/rocm/rocm.hcl

@@ -0,0 +1,38 @@
+variable "AMDGPU" {
+  default = "gfx900"
+}
+variable "ROCM" {
+  default = "5.7.3"
+}
+variable "HSA_OVERRIDE_GFX_VERSION" {
+  default = ""
+}
+variable "HSA_OVERRIDE" {
+  default = "1"
+}
+target deps {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "deps"
+}
+
+target rootfs {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "rootfs"
+}
+
+target rocm {
+  dockerfile = "docker/rocm/Dockerfile"
+  contexts = {
+    deps = "target:deps",
+    rootfs = "target:rootfs"
+  }
+  platforms = ["linux/amd64"]
+  args = {
+    AMDGPU = AMDGPU,
+    ROCM = ROCM,
+    HSA_OVERRIDE_GFX_VERSION = HSA_OVERRIDE_GFX_VERSION,
+    HSA_OVERRIDE = HSA_OVERRIDE
+  }
+}

docker/rocm/rocm.list

@@ -0,0 +1 @@
+deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/5.7.3 focal main

docker/rocm/rocm.mk

@@ -0,0 +1,17 @@
+BOARDS += rocm
+
+# AMD/ROCm is chunky so we build couple of smaller images for specific chipsets
+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 --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 --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 --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
+

docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/run

@@ -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
+

docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/type

@@ -0,0 +1 @@
+oneshot

docker/rocm/rootfs/etc/s6-overlay/s6-rc.d/compile-rocm-models/up

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

docker/tensorrt/Dockerfile.base

@@ -8,6 +8,8 @@ ARG TRT_BASE=nvcr.io/nvidia/tensorrt:23.03-py3
 # Build TensorRT-specific library
 FROM ${TRT_BASE} AS trt-deps
 
+ARG COMPUTE_LEVEL
+
 RUN apt-get update \
     && apt-get install -y git build-essential cuda-nvcc-* cuda-nvtx-* libnvinfer-dev libnvinfer-plugin-dev libnvparsers-dev libnvonnxparsers-dev \
     && rm -rf /var/lib/apt/lists/*

docker/tensorrt/detector/tensorrt_libyolo.sh

@@ -11,7 +11,7 @@ git clone --depth 1 https://github.com/NateMeyer/tensorrt_demos.git -b condition
 if [ ! -e /usr/local/cuda ]; then
     ln -s /usr/local/cuda-* /usr/local/cuda
 fi
-cd ./tensorrt_demos/plugins && make all -j$(nproc)
+cd ./tensorrt_demos/plugins && make all -j$(nproc) computes="${COMPUTE_LEVEL:-}"
 cp libyolo_layer.so /usr/local/lib/libyolo_layer.so
 
 # Store yolo scripts for later conversion

docker/tensorrt/trt.hcl

@@ -10,12 +10,16 @@ variable "SLIM_BASE" {
 variable "TRT_BASE" {
   default = null
 }
+variable "COMPUTE_LEVEL" {
+  default = ""
+}
 
 target "_build_args" {
   args = {
     BASE_IMAGE = BASE_IMAGE,
     SLIM_BASE = SLIM_BASE,
-    TRT_BASE = TRT_BASE
+    TRT_BASE = TRT_BASE,
+    COMPUTE_LEVEL = COMPUTE_LEVEL
   }
   platforms = ["linux/${ARCH}"]
 }

docker/tensorrt/trt.mk

@@ -2,7 +2,7 @@ BOARDS += trt
 
 JETPACK4_BASE ?= timongentzsch/l4t-ubuntu20-opencv:latest	# L4T 32.7.1 JetPack 4.6.1
 JETPACK5_BASE ?= nvcr.io/nvidia/l4t-tensorrt:r8.5.2-runtime	# L4T 35.3.1 JetPack 5.1.1
-X86_DGPU_ARGS := ARCH=amd64
+X86_DGPU_ARGS := ARCH=amd64 COMPUTE_LEVEL="50 60 70 80 90"
 JETPACK4_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK4_BASE) SLIM_BASE=$(JETPACK4_BASE) TRT_BASE=$(JETPACK4_BASE)
 JETPACK5_ARGS := ARCH=arm64 BASE_IMAGE=$(JETPACK5_BASE) SLIM_BASE=$(JETPACK5_BASE) TRT_BASE=$(JETPACK5_BASE)
 

docs/docs/configuration/advanced.md

@@ -96,7 +96,7 @@ model:
 
 Note that if you rename objects in the labelmap, you will also need to update your `objects -> track` list as well.
 
-:::caution
+:::warning
 
 Some labels have special handling and modifications can disable functionality.
 
@@ -120,7 +120,7 @@ NOTE: The folder that is mapped from the host needs to be the folder that contai
 
 ## Custom go2rtc version
 
-Frigate currently includes go2rtc v1.8.4, there may be certain cases where you want to run a different version of go2rtc.
+Frigate currently includes go2rtc v1.9.4, there may be certain cases where you want to run a different version of go2rtc.
 
 To do this:
 

docs/docs/configuration/authentication.md

@@ -0,0 +1,132 @@
+---
+id: authentication
+title: Authentication
+---
+
+# Authentication
+
+Frigate stores user information in its database. Password hashes are generated using industry standard PBKDF2-SHA256 with 600,000 iterations. Upon successful login, a JWT token is issued with an expiration date and set as a cookie. The cookie is refreshed as needed automatically. This JWT token can also be passed in the Authorization header as a bearer token.
+
+Users are managed in the UI under Settings > Users.
+
+The following ports are available to access the Frigate web UI.
+
+| Port   | Description                                                                                                                                                                                                  |
+| ------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| `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
+
+On startup, an admin user and password are generated and printed in the logs. It is recommended to set a new password for the admin account after logging in for the first time under Settings > Users.
+
+## Resetting admin password
+
+In the event that you are locked out of your instance, you can tell Frigate to reset the admin password and print it in the logs on next startup using the `reset_admin_password` setting in your config file.
+
+## 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 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:
+
+- 1 time per second
+- 5 times per minute
+- 20 times per hour
+
+Restarting Frigate will reset the rate limits.
+
+If you are running Frigate behind a proxy, you will want to set `trusted_proxies` or these rate limits will apply to the upstream proxy IP address. This means that a brute force attack will rate limit login attempts from other devices and could temporarily lock you out of your instance. In order to ensure rate limits only apply to the actual IP address where the requests are coming from, you will need to list the upstream networks that you want to trust. These trusted proxies are checked against the `X-Forwarded-For` header when looking for the IP address where the request originated.
+
+If you are running a reverse proxy in the same docker compose file as Frigate, here is an example of how your auth config might look:
+
+```yaml
+auth:
+  failed_login_rate_limit: "1/second;5/minute;20/hour"
+  trusted_proxies:
+    - 172.18.0.0/16 # <---- this is the subnet for the internal docker compose network
+```
+
+## JWT Token Secret
+
+The JWT token secret needs to be kept secure. Anyone with this secret can generate valid JWT tokens to authenticate with Frigate. This should be a cryptographically random string of at least 64 characters.
+
+You can generate a token using the Python secret library with the following command:
+
+```shell
+python3 -c 'import secrets; print(secrets.token_hex(64))'
+```
+
+Frigate looks for a JWT token secret in the following order:
+
+1. An environment variable named `FRIGATE_JWT_SECRET`
+2. A docker secret named `FRIGATE_JWT_SECRET` in `/run/secrets/`
+3. A `jwt_secret` option from the Home Assistant Addon options
+4. A `.jwt_secret` file in the config directory
+
+If no secret is found on startup, Frigate generates one and stores it in a `.jwt_secret` file in the config directory.
+
+Changing the secret will invalidate current tokens.
+
+## Proxy configuration
+
+Frigate can be configured to leverage features of common upstream authentication proxies such as Authelia, Authentik, oauth2_proxy, or traefik-forward-auth.
+
+If you are leveraging the authentication of an upstream proxy, you likely want to disable Frigate's authentication. Optionally, if communication between the reverse proxy and Frigate is over an untrusted network, you should set an `auth_secret` in the `proxy` config and configure the proxy to send the secret value as a header named `X-Proxy-Secret`. Assuming this is an untrusted network, you will also want to [configure a real TLS certificate](tls.md) to ensure the traffic can't simply be sniffed to steal the secret.
+
+Here is an example of how to disable Frigate's authentication and also ensure the requests come only from your known proxy.
+
+```yaml
+auth:
+  enabled: False
+
+proxy:
+  auth_secret: <some random long string>
+```
+
+You can use the following code to generate a random secret.
+
+```shell
+python3 -c 'import secrets; print(secrets.token_hex(64))'
+```
+
+### Header mapping
+
+If you have disabled Frigate's authentication and your proxy supports passing a header with the authenticated username, you can use the `header_map` config to specify the header name so it is passed to Frigate. For example, the following will map the `X-Forwarded-User` value. Header names are not case sensitive.
+
+```yaml
+proxy:
+  ...
+  header_map:
+    user: x-forwarded-user
+```
+
+Note that only the following list of headers are permitted by default:
+
+```
+Remote-User
+Remote-Groups
+Remote-Email
+Remote-Name
+X-Forwarded-User
+X-Forwarded-Groups
+X-Forwarded-Email
+X-Forwarded-Preferred-Username
+X-authentik-username
+X-authentik-groups
+X-authentik-email
+X-authentik-name
+X-authentik-uid
+```
+
+If you would like to add more options, you can overwrite the default file with a docker bind mount at `/usr/local/nginx/conf/proxy_trusted_headers.conf`. Reference the source code for the default file formatting.
+
+Future versions of Frigate may leverage group and role headers for authorization in Frigate as well.
+
+### Login page redirection
+
+Frigate gracefully performs login page redirection that should work with most authentication proxies. If your reverse proxy returns a `Location` header on `401`, `302`, or `307` unauthorized responses, Frigate's frontend will automatically detect it and redirect to that URL.
+
+### Custom logout url
+
+If your reverse proxy has a dedicated logout url, you can specify using the `logout_url` config option. This will update the link for the `Logout` link in the UI.

docs/docs/configuration/autotracking.md

@@ -159,7 +159,7 @@ This is often caused by the same reason as above - the `MoveStatus` ONVIF parame
 
 ### I'm seeing this error in the logs: "Autotracker: motion estimator couldn't get transformations". What does this mean?
 
-To maintain object tracking during PTZ moves, Frigate tracks the motion of your camera based on the details of the frame. If you are seeing this message, it could mean that your `zoom_factor` may be set too high, the scene around your detected object does not have enough details (like hard edges or color variatons), or your camera's shutter speed is too slow and motion blur is occurring. Try reducing `zoom_factor`, finding a way to alter the scene around your object, or changing your camera's shutter speed.
+To maintain object tracking during PTZ moves, Frigate tracks the motion of your camera based on the details of the frame. If you are seeing this message, it could mean that your `zoom_factor` may be set too high, the scene around your detected object does not have enough details (like hard edges or color variations), or your camera's shutter speed is too slow and motion blur is occurring. Try reducing `zoom_factor`, finding a way to alter the scene around your object, or changing your camera's shutter speed.
 
 ### Calibration seems to have completed, but the camera is not actually moving to track my object. Why?
 

docs/docs/configuration/birdseye.md

@@ -1,15 +1,20 @@
 # Birdseye
 
-Birdseye allows a heads-up view of your cameras to see what is going on around your property / space without having to watch all cameras that may have nothing happening. Birdseye allows specific modes that intelligently show and disappear based on what you care about.
+In addition to Frigate's Live camera dashboard, Birdseye allows a portable heads-up view of your cameras to see what is going on around your property / space without having to watch all cameras that may have nothing happening. Birdseye allows specific modes that intelligently show and disappear based on what you care about.
+
+Birdseye can be viewed by adding the "Birdseye" camera to a Camera Group in the Web UI. Add a Camera Group by pressing the "+" icon on the Live page, and choose "Birdseye" as one of the cameras.
+
+Birdseye can also be used in HomeAssistant dashboards, cast to media devices, etc.
 
 ## Birdseye Behavior
 
 ### Birdseye Modes
 
 Birdseye offers different modes to customize which cameras show under which circumstances.
- - **continuous:** All cameras are always included
- - **motion:** Cameras that have detected motion within the last 30 seconds are included
- - **objects:** Cameras that have tracked an active object within the last 30 seconds are included
+
+- **continuous:** All cameras are always included
+- **motion:** Cameras that have detected motion within the last 30 seconds are included
+- **objects:** Cameras that have tracked an active object within the last 30 seconds are included
 
 ### Custom Birdseye Icon
 
@@ -79,7 +84,7 @@ cameras:
       order: 2
 ```
 
-*Note*: Cameras are sorted by default using their name to ensure a constant view inside Birdseye.
+_Note_: Cameras are sorted by default using their name to ensure a constant view inside Birdseye.
 
 ### Birdseye Cameras
 

docs/docs/configuration/camera_specific.md

@@ -69,16 +69,12 @@ cameras:
     ffmpeg:
       output_args:
         record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v copy -tag:v hvc1 -bsf:v hevc_mp4toannexb -c:a aac
-        rtmp: -c:v copy -c:a aac -f flv
 
       inputs:
         - path: rtsp://user:password@camera-ip:554/H264/ch1/main/av_stream # <----- Update for your camera
           roles:
             - detect
             - record
-            - rtmp
-    rtmp:
-      enabled: False # <-- RTMP should be disabled if your stream is not H264
     detect:
       width: # <- optional, by default Frigate tries to automatically detect resolution
       height: # <- optional, by default Frigate tries to automatically detect resolution
@@ -105,10 +101,10 @@ If available, recommended settings are:
 
 According to [this discussion](https://github.com/blakeblackshear/frigate/issues/3235#issuecomment-1135876973), the http video streams seem to be the most reliable for Reolink.
 
-Cameras connected via a Reolink NVR can be connected with the http stream, use `channel[0..15]` in the stream url for the additional channels. 
+Cameras connected via a Reolink NVR can be connected with the http stream, use `channel[0..15]` in the stream url for the additional channels.
 The setup of main stream can be also done via RTSP, but isn't always reliable on all hardware versions. The example configuration is working with the oldest HW version RLN16-410 device with multiple types of cameras.
 
-:::caution
+:::warning
 
 The below configuration only works for reolink cameras with stream resolution of 5MP or lower, 8MP+ cameras need to use RTSP as http-flv is not supported in this case.
 
@@ -149,7 +145,7 @@ cameras:
         - path: rtsp://127.0.0.1:8554/your_reolink_camera_via_nvr_sub?video=copy
           input_args: preset-rtsp-restream
           roles:
-            - detect   
+            - detect
 ```
 
 #### Reolink Doorbell
@@ -179,15 +175,14 @@ go2rtc:
       - rtspx://192.168.1.1:7441/abcdefghijk
 ```
 
-[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.8.4#source-rtsp)
+[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#source-rtsp)
 
-In the Unifi 2.0 update Unifi Protect Cameras had a change in audio sample rate which causes issues for ffmpeg. The input rate needs to be set for record and rtmp if used directly with unifi protect.
+In the Unifi 2.0 update Unifi Protect Cameras had a change in audio sample rate which causes issues for ffmpeg. The input rate needs to be set for record if used directly with unifi protect.
 
 ```yaml
 ffmpeg:
   output_args:
     record: preset-record-ubiquiti
-    rtmp: preset-rtmp-ubiquiti # recommend using go2rtc instead
 ```
 
 ### TP-Link VIGI Cameras

docs/docs/configuration/cameras.md

@@ -11,12 +11,11 @@ A camera is enabled by default but can be temporarily disabled by using `enabled
 
 Each role can only be assigned to one input per camera. The options for roles are as follows:
 
-| Role     | Description                                                                              |
-| -------- | ---------------------------------------------------------------------------------------- |
-| `detect` | Main feed for object detection. [docs](object_detectors.md)                              |
-| `record` | Saves segments of the video feed based on configuration settings. [docs](record.md)      |
-| `audio`  | Feed for audio based detection. [docs](audio_detectors.md)                               |
-| `rtmp`   | Deprecated: Broadcast as an RTMP feed for other services to consume. [docs](restream.md) |
+| Role     | Description                                                                         |
+| -------- | ----------------------------------------------------------------------------------- |
+| `detect` | Main feed for object detection. [docs](object_detectors.md)                         |
+| `record` | Saves segments of the video feed based on configuration settings. [docs](record.md) |
+| `audio`  | Feed for audio based detection. [docs](audio_detectors.md)                          |
 
 ```yaml
 mqtt:
@@ -29,7 +28,6 @@ cameras:
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
           roles:
             - detect
-            - rtmp # <- deprecated, recommend using restream instead
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/live
           roles:
             - record
@@ -52,7 +50,7 @@ For camera model specific settings check the [camera specific](camera_specific.m
 
 ## Setting up camera PTZ controls
 
-:::caution
+:::warning
 
 Not every PTZ supports ONVIF, which is the standard protocol Frigate uses to communicate with your camera. Check the [official list of ONVIF conformant products](https://www.onvif.org/conformant-products/), your camera documentation, or camera manufacturer's website to ensure your PTZ supports ONVIF. Also, ensure your camera is running the latest firmware.
 
@@ -86,13 +84,33 @@ This list of working and non-working PTZ cameras is based on user feedback.
 | Ctronics PTZ             |      ✅      |      ❌      |                                                                                                                                                 |
 | Dahua                    |      ✅      |      ✅      |                                                                                                                                                 |
 | 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 |
 | Reolink 511WA            |      ✅      |      ❌      | Zoom only                                                                                                                                       |
 | Reolink E1 Pro           |      ✅      |      ❌      |                                                                                                                                                 |
 | Reolink E1 Zoom          |      ✅      |      ❌      |                                                                                                                                                 |
 | Reolink RLC-823A 16x     |      ✅      |      ❌      |                                                                                                                                                 |
 | Sunba 405-D20X           |      ✅      |      ❌      |                                                                                                                                                 |
-| Tapo C200                |      ✅      |      ❌      | Incomplete ONVIF support                                                                                                                        |
-| Tapo C210                |      ❌      |      ❌      | Incomplete ONVIF support                                                                                                                        |
+| 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                                  |
 | Vikylin PTZ-2804X-I2     |      ❌      |      ❌      | Incomplete ONVIF support                                                                                                                        |
+
+## Setting up camera groups
+
+:::tip
+
+It is recommended to set up camera groups using the UI.
+
+:::
+
+Cameras can be grouped together and assigned a name and icon, this allows them to be reviewed and filtered together. There will always be the default group for all cameras.
+
+```yaml
+camera_groups:
+  front:
+    cameras:
+      - driveway_cam
+      - garage_cam
+    icon: car
+    order: 0
+```

docs/docs/configuration/ffmpeg_presets.md

@@ -18,13 +18,11 @@ See [the hwaccel docs](/configuration/hardware_acceleration.md) for more info on
 | preset-vaapi          | Intel & AMD VAAPI              | Check hwaccel docs to ensure correct driver is chosen |
 | preset-intel-qsv-h264 | Intel QSV with h264 stream     | If issues occur recommend using vaapi preset instead  |
 | preset-intel-qsv-h265 | Intel QSV with h265 stream     | If issues occur recommend using vaapi preset instead  |
-| preset-nvidia-h264    | Nvidia GPU with h264 stream    |                                                       |
-| preset-nvidia-h265    | Nvidia GPU with h265 stream    |                                                       |
-| preset-nvidia-mjpeg   | Nvidia GPU with mjpeg stream   | Recommend restreaming mjpeg and using nvidia-h264     |
+| preset-nvidia         | Nvidia GPU                     |                                                       |
 | preset-jetson-h264    | Nvidia Jetson with h264 stream |                                                       |
 | preset-jetson-h265    | Nvidia Jetson with h265 stream |                                                       |
-| preset-rk-h264        | Rockchip MPP with h264 stream  | Use image with *-rk suffix and privileged mode        |
-| preset-rk-h265        | Rockchip MPP with h265 stream  | Use image with *-rk suffix and privileged mode        |
+| preset-rk-h264        | Rockchip MPP with h264 stream  | Use image with \*-rk suffix and privileged mode       |
+| preset-rk-h265        | Rockchip MPP with h265 stream  | Use image with \*-rk suffix and privileged mode       |
 
 ### Input Args Presets
 
@@ -44,7 +42,7 @@ See [the camera specific docs](/configuration/camera_specific.md) for more info
 | preset-rtsp-udp                  | RTSP Stream via UDP       | Use when camera is UDP only                                                                      |
 | preset-rtsp-blue-iris            | Blue Iris RTSP Stream     | Use when consuming a stream from Blue Iris                                                       |
 
-:::caution
+:::warning
 
 It is important to be mindful of input args when using restream because you can have a mix of protocols. `http` and `rtmp` presets cannot be used with `rtsp` streams. For example, when using a reolink cam with the rtsp restream as a source for record the preset-http-reolink will cause a crash. In this case presets will need to be set at the stream level. See the example below.
 
@@ -73,11 +71,11 @@ cameras:
 
 Output args presets help make the config more readable and handle use cases for different types of streams to ensure consistent recordings.
 
-| Preset                           | Usage                             | Other Notes                                   |
-| -------------------------------- | --------------------------------- | --------------------------------------------- |
-| preset-record-generic            | Record WITHOUT audio              | This is the default when nothing is specified |
-| preset-record-generic-audio-copy | Record WITH original audio        | Use this to enable audio in recordings        |
+| Preset                           | Usage                             | Other Notes                                                                                                                          |
+| -------------------------------- | --------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ |
+| preset-record-generic            | Record WITHOUT audio              | This is the default when nothing is specified                                                                                        |
+| preset-record-generic-audio-copy | Record WITH original audio        | Use this to enable audio in recordings                                                                                               |
 | preset-record-generic-audio-aac  | Record WITH transcoded aac audio  | Use this to transcode to aac audio. If your source is already aac, use preset-record-generic-audio-copy instead to avoid re-encoding |
-| preset-record-mjpeg              | Record an mjpeg stream            | Recommend restreaming mjpeg stream instead    |
-| preset-record-jpeg               | Record live jpeg                  | Recommend restreaming live jpeg instead       |
-| preset-record-ubiquiti           | Record ubiquiti stream with audio | Recordings with ubiquiti non-standard audio   |
+| preset-record-mjpeg              | Record an mjpeg stream            | Recommend restreaming mjpeg stream instead                                                                                           |
+| preset-record-jpeg               | Record live jpeg                  | Recommend restreaming live jpeg instead                                                                                              |
+| preset-record-ubiquiti           | Record ubiquiti stream with audio | Recordings with ubiquiti non-standard audio                                                                                          |

docs/docs/configuration/hardware_acceleration.md

@@ -5,13 +5,15 @@ title: Hardware Acceleration
 
 # Hardware Acceleration
 
-It is recommended to update your configuration to enable hardware accelerated decoding in ffmpeg. Depending on your system, these parameters may not be compatible. More information on hardware accelerated decoding for ffmpeg can be found here: https://trac.ffmpeg.org/wiki/HWAccelIntro
+It is highly recommended to use a GPU for hardware acceleration in Frigate. Some types of hardware acceleration are detected and used automatically, but you may need to update your configuration to enable hardware accelerated decoding in ffmpeg.
+
+Depending on your system, these parameters may not be compatible. More information on hardware accelerated decoding for ffmpeg can be found here: https://trac.ffmpeg.org/wiki/HWAccelIntro
 
 # Officially Supported
 
 ## Raspberry Pi 3/4
 
-Ensure you increase the allocated RAM for your GPU to at least 128 (`raspi-config` > Performance Options > GPU Memory).  
+Ensure you increase the allocated RAM for your GPU to at least 128 (`raspi-config` > Performance Options > GPU Memory).
 If you are using the HA addon, you may need to use the full access variant and turn off `Protection mode` for hardware acceleration.
 
 ```yaml
@@ -65,7 +67,7 @@ Or map in all the `/dev/video*` devices.
 
 ### Via VAAPI
 
-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 if QSV does not work.
+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:
@@ -80,7 +82,7 @@ With some of the processors, like the J4125, the default driver `iHD` doesn't se
 
 ### Via Quicksync (>=10th Generation only)
 
-QSV must be set specifically based on the video encoding of the stream.
+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
 
@@ -286,10 +288,10 @@ These instructions were originally based on the [Jellyfin documentation](https:/
 
 ## NVIDIA Jetson (Orin AGX, Orin NX, Orin Nano\*, Xavier AGX, Xavier NX, TX2, TX1, Nano)
 
-A separate set of docker images is available that is based on Jetpack/L4T. They comes with an `ffmpeg` build
+A separate set of docker images is available that is based on Jetpack/L4T. They come with an `ffmpeg` build
 with codecs that use the Jetson's dedicated media engine. If your Jetson host is running Jetpack 4.6, use the
-`frigate-tensorrt-jp4` image, or if your Jetson host is running Jetpack 5.0+, use the `frigate-tensorrt-jp5`
-image. Note that the Orin Nano has no video encoder, so frigate will use software encoding on this platform,
+`stable-tensorrt-jp4` tagged image, or if your Jetson host is running Jetpack 5.0+, use the `stable-tensorrt-jp5`
+tagged image. Note that the Orin Nano has no video encoder, so frigate will use software encoding on this platform,
 but the image will still allow hardware decoding and tensorrt object detection.
 
 You will need to use the image with the nvidia container runtime:
@@ -300,7 +302,7 @@ You will need to use the image with the nvidia container runtime:
 docker run -d \
   ...
   --runtime nvidia
-  ghcr.io/blakeblackshear/frigate-tensorrt-jp5
+  ghcr.io/blakeblackshear/frigate:stable-tensorrt-jp5
 ```
 
 ### Docker Compose - Jetson
@@ -310,7 +312,7 @@ version: '2.4'
 services:
   frigate:
     ...
-    image: ghcr.io/blakeblackshear/frigate-tensorrt-jp5
+    image: ghcr.io/blakeblackshear/frigate:stable-tensorrt-jp5
     runtime: nvidia   # Add this
 ```
 
@@ -360,15 +362,15 @@ that NVDEC/NVDEC1 are in use.
 
 ## Rockchip platform
 
-Hardware accelerated video de-/encoding is supported on all Rockchip SoCs.
+Hardware accelerated video de-/encoding is supported on all Rockchip SoCs using [Nyanmisaka's FFmpeg 6.1 Fork](https://github.com/nyanmisaka/ffmpeg-rockchip) based on [Rockchip's mpp library](https://github.com/rockchip-linux/mpp).
 
-### Setup
+### Prerequisites
 
-Use a frigate docker image with `-rk` suffix and enable privileged mode by adding the `--privileged` flag to your docker run command or `privileged: true` to your `docker-compose.yml` file.
+Make sure to follow the [Rockchip specific installation instructions](/frigate/installation#rockchip-platform).
 
 ### Configuration
 
-Add one of the following ffmpeg presets to your `config.yaml` to enable hardware acceleration:
+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
@@ -385,29 +387,3 @@ ffmpeg:
 Make sure that your SoC supports hardware acceleration for your input stream. For example, if your camera streams with h265 encoding and a 4k resolution, your SoC must be able to de- and encode h265 with a 4k resolution or higher. If you are unsure whether your SoC meets the requirements, take a look at the datasheet.
 
 :::
-
-### go2rtc presets for hardware accelerated transcoding
-
-If your input stream is to be transcoded using hardware acceleration, there are these presets for go2rtc: `h264/rk` and `h265/rk`. You can use them this way:
-
-```
-go2rtc:
-  streams:
-    Cam_h264: ffmpeg:rtsp://username:password@192.168.1.123/av_stream/ch0#video=h264/rk
-    Cam_h265: ffmpeg:rtsp://username:password@192.168.1.123/av_stream/ch0#video=h265/rk
-```
-
-:::warning
-
-The go2rtc docs may suggest the following configuration:
-
-```
-go2rtc:
-  streams:
-    Cam_h264: ffmpeg:rtsp://username:password@192.168.1.123/av_stream/ch0#video=h264#hardware=rk
-    Cam_h265: ffmpeg:rtsp://username:password@192.168.1.123/av_stream/ch0#video=h265#hardware=rk
-```
-
-However, this does not currently work.
-
-:::

docs/docs/configuration/index.md

@@ -25,7 +25,7 @@ cameras:
 
 ## VSCode Configuration Schema
 
-VSCode supports JSON schemas for automatically validating configuration files. You can enable this feature by adding `# yaml-language-server: $schema=http://frigate_host:5000/api/config/schema.json` to the beginning of the configuration file. Replace `frigate_host` with the IP address or hostname of your Frigate server. If you're using both VSCode and Frigate as an add-on, you should use `ccab4aaf-frigate` instead. Make sure to expose port `5000` for the Web Interface when accessing the config from VSCode on another machine.
+VSCode supports JSON schemas for automatically validating configuration files. You can enable this feature by adding `# yaml-language-server: $schema=http://frigate_host:5000/api/config/schema.json` to the beginning of the configuration file. Replace `frigate_host` with the IP address or hostname of your Frigate server. If you're using both VSCode and Frigate as an add-on, you should use `ccab4aaf-frigate` instead. Make sure to expose the internal unauthenticated port `5000` when accessing the config from VSCode on another machine.
 
 ## Environment Variable Substitution
 
@@ -113,7 +113,7 @@ cameras:
             - detect
     motion:
       mask:
-        - 0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432
+        - 0.000,0.427,0.002,0.000,0.999,0.000,0.999,0.781,0.885,0.456,0.700,0.424,0.701,0.311,0.507,0.294,0.453,0.347,0.451,0.400
 ```
 
 ### Standalone Intel Mini PC with USB Coral
@@ -167,7 +167,7 @@ cameras:
             - detect
     motion:
       mask:
-        - 0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432
+        - 0.000,0.427,0.002,0.000,0.999,0.000,0.999,0.781,0.885,0.456,0.700,0.424,0.701,0.311,0.507,0.294,0.453,0.347,0.451,0.400
 ```
 
 ### Home Assistant integrated Intel Mini PC with OpenVino
@@ -232,5 +232,5 @@ cameras:
             - detect
     motion:
       mask:
-        - 0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432
+        - 0.000,0.427,0.002,0.000,0.999,0.000,0.999,0.781,0.885,0.456,0.700,0.424,0.701,0.311,0.507,0.294,0.453,0.347,0.451,0.400
 ```

docs/docs/configuration/live.md

@@ -3,11 +3,11 @@ id: live
 title: Live View
 ---
 
-Frigate has different live view options, some of which require the bundled `go2rtc` to be configured as shown in the [step by step guide](/guides/configuring_go2rtc).
+Frigate intelligently displays your camera streams on the Live view dashboard. Your camera images update once per minute when no detectable activity is occurring to conserve bandwidth and resources. As soon as any motion is detected, cameras seamlessly switch to a live stream.
 
-## Live View Options
+## Live View technologies
 
-Live view options can be selected while viewing the live stream. The options are:
+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).
 
 | Source | Latency | Frame Rate                            | Resolution     | Audio                        | Requires go2rtc | Other Limitations                                |
 | ------ | ------- | ------------------------------------- | -------------- | ---------------------------- | --------------- | ------------------------------------------------ |
@@ -79,7 +79,7 @@ WebRTC works by creating a TCP or UDP connection on port `8555`. However, it req
         - stun:8555
   ```
 
-- For access through Tailscale, the Frigate system's Tailscale IP must be added as a WebRTC candidate. Tailscale IPs all start with `100.`, and are reserved within the `100.0.0.0/8` CIDR block.
+- For access through Tailscale, the Frigate system's Tailscale IP must be added as a WebRTC candidate. Tailscale IPs all start with `100.`, and are reserved within the `100.64.0.0/10` CIDR block.
 
 :::tip
 

docs/docs/configuration/masks.md

@@ -5,7 +5,9 @@ title: Masks
 
 ## Motion masks
 
-Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the debug feed with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. Over masking will make it more difficult for objects to be tracked. To see this effect, create a mask, and then watch the video feed with `Motion Boxes` enabled again.
+Motion masks are used to prevent unwanted types of motion from triggering detection. Try watching the Debug feed (Settings --> Debug) with `Motion Boxes` enabled to see what may be regularly detected as motion. For example, you want to mask out your timestamp, the sky, rooftops, etc. Keep in mind that this mask only prevents motion from being detected and does not prevent objects from being detected if object detection was started due to motion in unmasked areas. Motion is also used during object tracking to refine the object detection area in the next frame. _Over-masking will make it more difficult for objects to be tracked._
+
+See [further clarification](#further-clarification) below on why you may not want to use a motion mask.
 
 ## Object filter masks
 
@@ -20,32 +22,30 @@ Object filter masks can be used to filter out stubborn false positives in fixed
 To create a poly mask:
 
 1. Visit the Web UI
-1. Click the camera you wish to create a mask for
-1. Select "Debug" at the top
-1. Expand the "Options" below the video feed
-1. Click "Mask & Zone creator"
-1. Click "Add" on the type of mask or zone you would like to create
-1. Click on the camera's latest image to create a masked area. The yaml representation will be updated in real-time
-1. When you've finished creating your mask, click "Copy" and paste the contents into your config file and restart Frigate
+2. Click/tap the gear icon and open "Settings"
+3. Select "Mask / zone editor"
+4. At the top right, select the camera you wish to create a mask or zone for
+5. Click the plus icon under the type of mask or zone you would like to create
+6. Click on the camera's latest image to create the points for a masked area. Click the first point again to close the polygon.
+7. When you've finished creating your mask, press Save.
+8. Restart Frigate to apply your changes.
 
-Example of a finished row corresponding to the below example image:
+Your config file will be updated with the relative coordinates of the mask/zone:
 
 ```yaml
 motion:
-  mask: "0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432"
+  mask: "0.000,0.427,0.002,0.000,0.999,0.000,0.999,0.781,0.885,0.456,0.700,0.424,0.701,0.311,0.507,0.294,0.453,0.347,0.451,0.400"
 ```
 
-Multiple masks can be listed.
+Multiple masks can be listed in your config.
 
 ```yaml
 motion:
   mask:
-    - 458,1346,336,973,317,869,375,866,432
-    - 0,461,3,0,1919,0,1919,843,1699,492,1344
+    - 0.239,1.246,0.175,0.901,0.165,0.805,0.195,0.802
+    - 0.000,0.427,0.002,0.000,0.999,0.000,0.999,0.781,0.885,0.456
 ```
 
-![poly](/img/example-mask-poly-min.png)
-
 ### Further Clarification
 
 This is a response to a [question posed on reddit](https://www.reddit.com/r/homeautomation/comments/ppxdve/replacing_my_doorbell_with_a_security_camera_a_6/hd876w4?utm_source=share&utm_medium=web2x&context=3):

docs/docs/configuration/motion_detection.md

@@ -17,13 +17,11 @@ Before tuning motion it is important to understand the goal. In an optimal confi
 
 ## 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 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). 
+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
 
-The easiest way to tune motion detection is to do it live, have one window / screen open with the frigate debug view and motion boxes enabled with another window / screen open allowing for configuring the motion settings. It is recommended to use Home Assistant or MQTT as they offer live configuration of some motion settings meaning that Frigate does not need to be restarted when values are changed.
-
-In Home Assistant the `Improve Contrast`, `Contour Area`, and `Threshold` configuration entities are disabled by default but can easily be enabled and used to tune live, otherwise MQTT can be used.
+The easiest way to tune motion detection is to use the Frigate UI under Settings > Motion Tuner. This screen allows the changing of motion detection values live to easily see the immediate effect on what is detected as motion.
 
 ## Tuning Motion Detection During The Day
 
@@ -37,7 +35,7 @@ Remember that motion detection is just used to determine when object detection s
 
 ### Threshold
 
-The threshold value dictates how much of a change in a pixels luminance is required to be considered motion. 
+The threshold value dictates how much of a change in a pixels luminance is required to be considered motion.
 
 ```yaml
 # default threshold value
@@ -69,7 +67,7 @@ motion:
 
 Once the threshold calculation is run, the pixels that have changed are grouped together. The contour area value is used to decide which groups of changed pixels qualify as motion. Smaller values are more sensitive meaning people that are far away, small animals, etc. are more likely to be detected as motion, but it also means that small changes in shadows, leaves, etc. are detected as motion. Higher values are less sensitive meaning these things won't be detected as motion but with the risk that desired motion won't be detected until closer to the camera.
 
-Watching the motion boxes in the debug view, adjust the contour area until there are no motion boxes smaller than the smallest you'd expect frigate to detect something moving. 
+Watching the motion boxes in the debug view, adjust the contour area until there are no motion boxes smaller than the smallest you'd expect frigate to detect something moving.
 
 ### Improve Contrast
 
@@ -77,7 +75,7 @@ At this point if motion is working as desired there is no reason to continue wit
 
 ## Tuning Motion Detection During The Night
 
-Once daytime motion detection is tuned, there is a chance that the settings will work well for motion detection during the night as well. If this is the case then the preferred settings can be written to the config file and left alone. 
+Once daytime motion detection is tuned, there is a chance that the settings will work well for motion detection during the night as well. If this is the case then the preferred settings can be written to the config file and left alone.
 
 However, if the preferred day settings do not work well at night it is recommended to use HomeAssistant or some other solution to automate changing the settings. That way completely separate sets of motion settings can be used for optimal day and night motion detection.
 

docs/docs/configuration/object_detectors.md

@@ -13,7 +13,7 @@ The CPU detector type runs a TensorFlow Lite model utilizing the CPU without har
 
 :::tip
 
-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. 
+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.
 
 :::
 
@@ -109,9 +109,13 @@ detectors:
 
 The OpenVINO detector type runs an OpenVINO IR model on AMD and Intel CPUs, Intel GPUs and Intel VPU hardware. To configure an OpenVINO detector, set the `"type"` attribute to `"openvino"`.
 
-The OpenVINO device to be used is specified using the `"device"` attribute according to the naming conventions in the [Device Documentation](https://docs.openvino.ai/latest/openvino_docs_OV_UG_Working_with_devices.html). Other supported devices could be `AUTO`, `CPU`, `GPU`, `MYRIAD`, etc. If not specified, the default OpenVINO device will be selected by the `AUTO` plugin.
+The OpenVINO device to be used is specified using the `"device"` attribute according to the naming conventions in the [Device Documentation](https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes.html). The most common devices are `CPU` and `GPU`. Currently, there is a known issue with using `AUTO`. For backwards compatibility, Frigate will attempt to use `GPU` if `AUTO` is set in your configuration.
 
-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. The `MYRIAD` device may be run on any platform, including Arm devices. For detailed system requirements, see [OpenVINO System Requirements](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/system-requirements.html)
+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)
+
+### Supported Models
+
+#### SSDLite MobileNet v2
 
 An OpenVINO model is provided in the container at `/openvino-model/ssdlite_mobilenet_v2.xml` and is used by this detector type by default. The model comes from Intel's Open Model Zoo [SSDLite MobileNet V2](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/ssdlite_mobilenet_v2) and is converted to an FP16 precision IR model. Use the model configuration shown below when using the OpenVINO detector with the default model.
 
@@ -119,27 +123,26 @@ An OpenVINO model is provided in the container at `/openvino-model/ssdlite_mobil
 detectors:
   ov:
     type: openvino
-    device: AUTO
-    model:
-      path: /openvino-model/ssdlite_mobilenet_v2.xml
+    device: GPU
 
 model:
   width: 300
   height: 300
   input_tensor: nhwc
   input_pixel_format: bgr
+  path: /openvino-model/ssdlite_mobilenet_v2.xml
   labelmap_path: /openvino-model/coco_91cl_bkgr.txt
 ```
 
-This detector also supports some YOLO variants: YOLOX, YOLOv5, and YOLOv8 specifically. Other YOLO variants are not officially supported/tested. Frigate does not come with any yolo 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:
+#### 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 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: AUTO
-    model:
-      path: /path/to/yolox_tiny.xml
+    device: GPU
 
 model:
   width: 416
@@ -147,38 +150,41 @@ model:
   input_tensor: nchw
   input_pixel_format: bgr
   model_type: yolox
+  path: /path/to/yolox_tiny.xml
   labelmap_path: /path/to/coco_80cl.txt
 ```
 
-### Intel NCS2 VPU and Myriad X Setup
+#### YOLO-NAS
 
-Intel produces a neural net inference accelleration chip called Myriad X. This chip was sold in their Neural Compute Stick 2 (NCS2) which has been discontinued. If intending to use the MYRIAD device for accelleration, additional setup is required to pass through the USB device. The host needs a udev rule installed to handle the NCS2 device.
+[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).
 
-```bash
-sudo usermod -a -G users "$(whoami)"
-cat <<EOF > 97-myriad-usbboot.rules
-SUBSYSTEM=="usb", ATTRS{idProduct}=="2485", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1"
-SUBSYSTEM=="usb", ATTRS{idProduct}=="f63b", ATTRS{idVendor}=="03e7", GROUP="users", MODE="0666", ENV{ID_MM_DEVICE_IGNORE}="1"
-EOF
-sudo cp 97-myriad-usbboot.rules /etc/udev/rules.d/
-sudo udevadm control --reload-rules
-sudo udevadm trigger
+:::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:
+  ov:
+    type: openvino
+    device: GPU
+
+model:
+  model_type: yolonas
+  width: 320 # <--- should match whatever was set in notebook
+  height: 320 # <--- should match whatever was set in notebook
+  input_tensor: nchw
+  input_pixel_format: bgr
+  path: /config/yolo_nas_s.onnx
+  labelmap_path: /labelmap/coco-80.txt
 ```
 
-Additionally, the Frigate docker container needs to run with the following configuration:
-
-```bash
---device-cgroup-rule='c 189:\* rmw' -v /dev/bus/usb:/dev/bus/usb
-```
-
-or in your compose file:
-
-```yml
-device_cgroup_rules:
-  - "c 189:* rmw"
-volumes:
-  - /dev/bus/usb:/dev/bus/usb
-```
+Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.
 
 ## NVidia TensorRT Detector
 
@@ -261,7 +267,7 @@ frigate:
 
 ### Configuration Parameters
 
-The TensorRT detector can be selected by specifying `tensorrt` as the model type. The GPU will need to be passed through to the docker container using the same methods described in the [Hardware Acceleration](hardware_acceleration.md#nvidia-gpu) section. If you pass through multiple GPUs, you can select which GPU is used for a detector with the `device` configuration parameter. The `device` parameter is an integer value of the GPU index, as shown by `nvidia-smi` within the container.
+The TensorRT detector can be selected by specifying `tensorrt` as the model type. The GPU will need to be passed through to the docker container using the same methods described in the [Hardware Acceleration](hardware_acceleration.md#nvidia-gpus) section. If you pass through multiple GPUs, you can select which GPU is used for a detector with the `device` configuration parameter. The `device` parameter is an integer value of the GPU index, as shown by `nvidia-smi` within the container.
 
 The TensorRT detector uses `.trt` model files that are located in `/config/model_cache/tensorrt` by default. These model path and dimensions used will depend on which model you have generated.
 
@@ -303,71 +309,76 @@ To verify that the integration is working correctly, start Frigate and observe t
 
 # Community Supported Detectors
 
-## Rockchip RKNN-Toolkit-Lite2
+## Rockchip platform
 
-This detector is only available if one of the following Rockchip SoCs is used:
+Hardware accelerated object detection is supported on the following SoCs:
 
-- RK3588/RK3588S
-- RK3568
-- RK3566
 - RK3562
+- RK3566
+- RK3568
+- RK3576
+- RK3588
 
-These SoCs come with a NPU that will highly speed up detection.
+This implementation uses the [Rockchip's RKNN-Toolkit2](https://github.com/airockchip/rknn-toolkit2/), version v2.0.0.beta0. Currently, only [Yolo-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) is supported as object detection model.
 
-### Setup
+### Prerequisites
 
-Use a frigate docker image with `-rk` suffix and enable privileged mode by adding the `--privileged` flag to your docker run command or `privileged: true` to your `docker-compose.yml` file.
+Make sure to follow the [Rockchip specific installation instrucitions](/frigate/installation#rockchip-platform).
 
 ### Configuration
 
-This `config.yml` shows all relevant options to configure the detector and explains them. All values shown are the default values (except for one). Lines that are required at least to use the detector are labeled as required, all other lines are optional.
+This `config.yml` shows all relevant options to configure the detector and explains them. All values shown are the default values (except for two). Lines that are required at least to use the detector are labeled as required, all other lines are optional.
 
 ```yaml
 detectors: # required
   rknn: # required
     type: rknn # required
-    # core mask for npu
-    core_mask: 0
+    # number of NPU cores to use
+    # 0 means choose automatically
+    # increase for better performance if you have a multicore NPU e.g. set to 3 on rk3588
+    num_cores: 0
 
 model: # required
-  # name of yolov8 model or path to your own .rknn model file
+  # name of model (will be automatically downloaded) or path to your own .rknn model file
   # possible values are:
-  # - default-yolov8n
-  # - default-yolov8s
-  # - default-yolov8m
-  # - default-yolov8l
-  # - default-yolov8x
-  # - /config/model_cache/rknn/your_custom_model.rknn
-  path: default-yolov8n
+  # - deci-fp16-yolonas_s
+  # - deci-fp16-yolonas_m
+  # - deci-fp16-yolonas_l
+  # - /config/model_cache/your_custom_model.rknn
+  path: deci-fp16-yolonas_s
   # width and height of detection frames
   width: 320
   height: 320
   # pixel format of detection frame
-  # default value is rgb but yolov models usually use bgr format
+  # default value is rgb but yolo models usually use bgr format
   input_pixel_format: bgr # required
   # shape of detection frame
   input_tensor: nhwc
+  # needs to be adjusted to model, see below
+  labelmap_path: /labelmap.txt # required
 ```
 
-Explanation for rknn specific options:
+The correct labelmap must be loaded for each model. If you use a custom model (see notes below), you must make sure to provide the correct labelmap. The table below lists the correct paths for the bundled models:
 
-- **core mask** controls which cores of your NPU should be used. This option applies only to SoCs with a multicore NPU (at the time of writing this in only the RK3588/S). The easiest way is to pass the value as a binary number. To do so, use the prefix `0b` and write a `0` to disable a core and a `1` to enable a core, whereas the last digit coresponds to core0, the second last to core1, etc. You also have to use the cores in ascending order (so you can't use core0 and core2; but you can use core0 and core1). Enabling more cores can reduce the inference speed, especially when using bigger models (see section below). Examples:
-  - `core_mask: 0b000` or just `core_mask: 0` let the NPU decide which cores should be used. Default and recommended value.
-  - `core_mask: 0b001` use only core0.
-  - `core_mask: 0b011` use core0 and core1.
-  - `core_mask: 0b110` use core1 and core2. **This does not** work, since core0 is disabled.
+| `path`                | `labelmap_path`       |
+| --------------------- | --------------------- |
+| deci-fp16-yolonas\_\* | /labelmap/coco-80.txt |
 
 ### Choosing a model
 
-There are 5 default yolov8 models that differ in size and therefore load the NPU more or less. In ascending order, with the top one being the smallest and least computationally intensive model:
+:::warning
 
-| Model   | Size in mb |
-| ------- | ---------- |
-| yolov8n | 9          |
-| yolov8s | 25         |
-| yolov8m | 54         |
-| yolov8l | 90         |
-| yolov8x | 136        |
+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 inference time was determined on a rk3588 with 3 NPU cores.
+
+| Model               | Size in mb | Inference time in ms |
+| ------------------- | ---------- | -------------------- |
+| deci-fp16-yolonas_s | 24         | 25                   |
+| deci-fp16-yolonas_m | 62         | 35                   |
+| deci-fp16-yolonas_l | 81         | 45                   |
 
 :::tip
 
@@ -380,26 +391,5 @@ $ cat /sys/kernel/debug/rknpu/load
 
 :::
 
-- By default the rknn detector uses the yolov8n model (`model: path: default-yolov8n`). This model comes with the image, so no further steps than those mentioned above are necessary.
-- If you want to use a more precise model, you can pass `default-yolov8s`, `default-yolov8m`, `default-yolov8l` or `default-yolov8x` as `model: path:` option.
-  - If the model does not exist, it will be automatically downloaded to `/config/model_cache/rknn`.
-  - If your server has no internet connection, you can download the model from [this Github repository](https://github.com/MarcA711/rknn-models/releases) using another device and place it in the `config/model_cache/rknn` on your system.
-- Finally, you can also provide your own model. Note that only yolov8 models are currently supported. Moreover, you will need to convert your model to the rknn format using `rknn-toolkit2` on a x86 machine. Afterwards, you can place your `.rknn` model file in the `config/model_cache/rknn` directory on your system. Then you need to pass the path to your model using the `path` option of your `model` block like this:
-
-```yaml
-model:
-  path: /config/model_cache/rknn/my-rknn-model.rknn
-```
-
-:::tip
-
-When you have a multicore NPU, you can enable all cores to reduce inference times. You should consider activating all cores if you use a larger model like yolov8l. If your NPU has 3 cores (like rk3588/S SoCs), you can enable all 3 cores using:
-
-```yaml
-detectors:
-  rknn:
-    type: rknn
-    core_mask: 0b111
-```
-
-:::
+- 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.

docs/docs/configuration/object_filters.md

@@ -36,7 +36,7 @@ False positives can also be reduced by filtering a detection based on its shape.
 
 ### Object Area
 
-`min_area` and `max_area` filter on the area of an objects bounding box in pixels and can be used to reduce false positives that are outside the range of expected sizes. For example when a leaf is detected as a dog or when a large tree is detected as a person, these can be reduced by adding a `min_area` / `max_area` filter. The recordings timeline can be used to determine the area of the bounding box in that frame by selecting a timeline item then mousing over or tapping the red box.
+`min_area` and `max_area` filter on the area of an objects bounding box in pixels and can be used to reduce false positives that are outside the range of expected sizes. For example when a leaf is detected as a dog or when a large tree is detected as a person, these can be reduced by adding a `min_area` / `max_area` filter.
 
 ### Object Proportions
 

docs/docs/configuration/reference.md

@@ -5,7 +5,7 @@ title: Full Reference Config
 
 ### Full configuration reference:
 
-:::caution
+:::warning
 
 It is not recommended to copy this full configuration file. Only specify values that are different from the defaults. Configuration options and default values may change in future versions.
 
@@ -63,6 +63,59 @@ database:
   # The path to store the SQLite DB (default: shown below)
   path: /config/frigate.db
 
+# Optional: TLS configuration
+tls:
+  # Optional: Enable TLS for port 8080 (default: shown below)
+  enabled: True
+
+# Optional: Proxy configuration
+proxy:
+  # Optional: Mapping for headers from upstream proxies. Only used if Frigate's auth
+  # is disabled.
+  # NOTE: Many authentication proxies pass a header downstream with the authenticated
+  #       user name. Not all values are supported. It must be a whitelisted header.
+  #       See the docs for more info.
+  header_map:
+    user: x-forwarded-user
+  # Optional: Url for logging out a user. This sets the location of the logout url in
+  # the UI.
+  logout_url: /api/logout
+  # Optional: Auth secret that is checked against the X-Proxy-Secret header sent from
+  # the proxy. If not set, all requests are trusted regardless of origin.
+  auth_secret: None
+
+# Optional: Authentication configuration
+auth:
+  # Optional: Enable authentication
+  enabled: True
+  # Optional: Reset the admin user password on startup (default: shown below)
+  # New password is printed in the logs
+  reset_admin_password: False
+  # Optional: Cookie to store the JWT token for native auth (default: shown below)
+  cookie_name: frigate_token
+  # Optional: Set secure flag on cookie. (default: shown below)
+  # NOTE: This should be set to True if you are using TLS
+  cookie_secure: False
+  # Optional: Session length in seconds (default: shown below)
+  session_length: 86400 # 24 hours
+  # Optional: Refresh time in seconds (default: shown below)
+  # When the session is going to expire in less time than this setting,
+  # it will be refreshed back to the session_length.
+  refresh_time: 43200 # 12 hours
+  # Optional: Rate limiting for login failures to help prevent brute force
+  # login attacks (default: shown below)
+  # See the docs for more information on valid values
+  failed_login_rate_limit: None
+  # Optional: Trusted proxies for determining IP address to rate limit
+  # NOTE: This is only used for rate limiting login attempts and does not bypass
+  # authentication. See the authentication docs for more details.
+  trusted_proxies: []
+  # Optional: Number of hashing iterations for user passwords
+  # As of Feb 2023, OWASP recommends 600000 iterations for PBKDF2-SHA256
+  # NOTE: changing this value will not automatically update password hashes, you
+  #       will need to change each user password for it to apply
+  hash_iterations: 600000
+
 # Optional: model modifications
 model:
   # Optional: path to the model (default: automatic based on detector)
@@ -80,7 +133,7 @@ model:
   # Valid values are nhwc or nchw (default: shown below)
   input_tensor: nhwc
   # Optional: Object detection model type, currently only used with the OpenVINO detector
-  # Valid values are ssd, yolox, yolov5, or yolov8 (default: shown below)
+  # Valid values are ssd, yolox, yolonas (default: shown below)
   model_type: ssd
   # Optional: Label name modifications. These are merged into the standard labelmap.
   labelmap:
@@ -159,9 +212,9 @@ birdseye:
 ffmpeg:
   # Optional: global ffmpeg args (default: shown below)
   global_args: -hide_banner -loglevel warning -threads 2
-  # Optional: global hwaccel args (default: shown below)
+  # Optional: global hwaccel args (default: auto detect)
   # NOTE: See hardware acceleration docs for your specific device
-  hwaccel_args: []
+  hwaccel_args: "auto"
   # Optional: global input args (default: shown below)
   input_args: preset-rtsp-generic
   # Optional: global output args
@@ -170,8 +223,6 @@ ffmpeg:
     detect: -threads 2 -f rawvideo -pix_fmt yuv420p
     # Optional: output args for record streams (default: shown below)
     record: preset-record-generic
-    # Optional: output args for rtmp streams (default: shown below)
-    rtmp: preset-rtmp-generic
   # Optional: Time in seconds to wait before ffmpeg retries connecting to the camera. (default: shown below)
   # If set too low, frigate will retry a connection to the camera's stream too frequently, using up the limited streams some cameras can allow at once
   # If set too high, then if a ffmpeg crash or camera stream timeout occurs, you could potentially lose up to a maximum of retry_interval second(s) of footage
@@ -239,7 +290,7 @@ objects:
   # Optional: mask to prevent all object types from being detected in certain areas (default: no mask)
   # Checks based on the bottom center of the bounding box of the object.
   # NOTE: This mask is COMBINED with the object type specific mask below
-  mask: 0,0,1000,0,1000,200,0,200
+  mask: 0.000,0.000,0.781,0.000,0.781,0.278,0.000,0.278
   # Optional: filters to reduce false positives for specific object types
   filters:
     person:
@@ -257,7 +308,29 @@ objects:
       threshold: 0.7
       # Optional: mask to prevent this object type from being detected in certain areas (default: no mask)
       # Checks based on the bottom center of the bounding box of the object
-      mask: 0,0,1000,0,1000,200,0,200
+      mask: 0.000,0.000,0.781,0.000,0.781,0.278,0.000,0.278
+
+# Optional: Review configuration
+# NOTE: Can be overridden at the camera level
+review:
+  # Optional: alerts configuration
+  alerts:
+    # Optional: labels that qualify as an alert (default: shown below)
+    labels:
+      - car
+      - person
+    # Optional: required zones for an object to be marked as an alert (default: none)
+    required_zones:
+      - driveway
+  # Optional: detections configuration
+  detections:
+    # Optional: labels that qualify as a detection (default: all labels that are tracked / listened to)
+    labels:
+      - car
+      - person
+    # Optional: required zones for an object to be marked as a detection (default: none)
+    required_zones:
+      - driveway
 
 # Optional: Motion configuration
 # NOTE: Can be overridden at the camera level
@@ -291,7 +364,7 @@ motion:
   frame_height: 100
   # Optional: motion mask
   # NOTE: see docs for more detailed info on creating masks
-  mask: 0,900,1080,900,1080,1920,0,1920
+  mask: 0.000,0.469,1.000,0.469,1.000,1.000,0.000,1.000
   # Optional: improve contrast (default: shown below)
   # Enables dynamic contrast improvement. This should help improve night detections at the cost of making motion detection more sensitive
   # for daytime.
@@ -333,6 +406,11 @@ record:
     # The -r (framerate) dictates how smooth the output video is.
     # So the args would be -vf setpts=0.02*PTS -r 30 in that case.
     timelapse_args: "-vf setpts=0.04*PTS -r 30"
+  # Optional: Recording Preview Settings
+  preview:
+    # Optional: Quality of recording preview (default: shown below).
+    # Options are: very_low, low, medium, high, very_high
+    quality: medium
   # Optional: Event recording settings
   events:
     # Optional: Number of seconds before the event to include (default: shown below)
@@ -342,8 +420,6 @@ record:
     # Optional: Objects to save recordings for. (default: all tracked objects)
     objects:
       - person
-    # Optional: Restrict recordings to objects that entered any of the listed zones (default: no required zones)
-    required_zones: []
     # Optional: Retention settings for recordings of events
     retain:
       # Required: Default retention days (default: shown below)
@@ -389,13 +465,6 @@ snapshots:
   # Optional: quality of the encoded jpeg, 0-100 (default: shown below)
   quality: 70
 
-# Optional: RTMP configuration
-# NOTE: RTMP is deprecated in favor of restream
-# NOTE: Can be overridden at the camera level
-rtmp:
-  # Optional: Enable the RTMP stream (default: False)
-  enabled: False
-
 # Optional: Restream configuration
 # Uses https://github.com/AlexxIT/go2rtc (v1.8.3)
 go2rtc:
@@ -452,14 +521,13 @@ cameras:
         # Required: the path to the stream
         # NOTE: path may include environment variables or docker secrets, which must begin with 'FRIGATE_' and be referenced in {}
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
-          # Required: list of roles for this stream. valid values are: audio,detect,record,rtmp
-          # NOTICE: In addition to assigning the audio, record, and rtmp roles,
+          # Required: list of roles for this stream. valid values are: audio,detect,record
+          # NOTICE: In addition to assigning the audio, detect, and record roles
           # they must also be enabled in the camera config.
           roles:
             - audio
             - detect
             - record
-            - rtmp
           # Optional: stream specific global args (default: inherit)
           # global_args:
           # Optional: stream specific hwaccel args (default: inherit)
@@ -490,9 +558,11 @@ cameras:
       front_steps:
         # Required: List of x,y coordinates to define the polygon of the zone.
         # NOTE: Presence in a zone is evaluated only based on the bottom center of the objects bounding box.
-        coordinates: 545,1077,747,939,788,805
+        coordinates: 0.284,0.997,0.389,0.869,0.410,0.745
         # Optional: Number of consecutive frames required for object to be considered present in the zone (default: shown below).
         inertia: 3
+        # Optional: Number of seconds that an object must loiter to be considered in the zone (default: shown below)
+        loitering_time: 0
         # Optional: List of objects that can trigger this zone (default: all tracked objects)
         objects:
           - person
@@ -586,12 +656,8 @@ cameras:
 
 # Optional
 ui:
-  # Optional: Set the default live mode for cameras in the UI (default: shown below)
-  live_mode: mse
   # Optional: Set a timezone to use in the UI (default: use browser local time)
   # timezone: America/Denver
-  # Optional: Use an experimental recordings / camera view UI (default: shown below)
-  use_experimental: False
   # Optional: Set the time format used.
   # Options are browser, 12hour, or 24hour (default: shown below)
   time_format: browser
@@ -638,4 +704,19 @@ telemetry:
   # Optional: Enable the latest version outbound check (default: shown below)
   # NOTE: If you use the HomeAssistant integration, disabling this will prevent it from reporting new versions
   version_check: True
+
+# Optional: Camera groups (default: no groups are setup)
+# NOTE: It is recommended to use the UI to setup camera groups
+camera_groups:
+  # Required: Name of camera group
+  front:
+    # Required: list of cameras in the group
+    cameras:
+      - front_cam
+      - side_cam
+      - front_doorbell_cam
+    # Required: icon used for group
+    icon: car
+    # Required: index of this group
+    order: 0
 ```

docs/docs/configuration/restream.md

@@ -7,11 +7,11 @@ title: Restream
 
 Frigate can restream your video feed as an RTSP feed for other applications such as Home Assistant to utilize it at `rtsp://<frigate_host>:8554/<camera_name>`. Port 8554 must be open. [This allows you to use a video feed for detection in Frigate and Home Assistant live view at the same time without having to make two separate connections to the camera](#reduce-connections-to-camera). The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate.
 
-Frigate uses [go2rtc](https://github.com/AlexxIT/go2rtc/tree/v1.8.4) to provide its restream and MSE/WebRTC capabilities. The go2rtc config is hosted at the `go2rtc` in the config, see [go2rtc docs](https://github.com/AlexxIT/go2rtc/tree/v1.8.4#configuration) for more advanced configurations and features.
+Frigate uses [go2rtc](https://github.com/AlexxIT/go2rtc/tree/v1.9.4) to provide its restream and MSE/WebRTC capabilities. The go2rtc config is hosted at the `go2rtc` in the config, see [go2rtc docs](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#configuration) for more advanced configurations and features.
 
 :::note
 
-You can access the go2rtc stream info at `http://frigate_ip:5000/api/go2rtc/streams` which can be helpful to debug as well as provide useful information about your camera streams.
+You can access the go2rtc stream info at `/api/go2rtc/streams` which can be helpful to debug as well as provide useful information about your camera streams.
 
 :::
 
@@ -38,10 +38,6 @@ go2rtc:
 
 **NOTE:** This does not apply to localhost requests, there is no need to provide credentials when using the restream as a source for frigate cameras.
 
-## RTMP (Deprecated)
-
-In previous Frigate versions RTMP was used for re-streaming. RTMP has disadvantages however including being incompatible with H.265, high bitrates, and certain audio codecs. RTMP is deprecated and it is recommended use the built in go2rtc config for restreaming.
-
 ## Reduce Connections To Camera
 
 Some cameras only support one active connection or you may just want to have a single connection open to the camera. The RTSP restream allows this to be possible.
@@ -138,7 +134,7 @@ cameras:
 
 ## Advanced Restream Configurations
 
-The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.8.4#source-exec) source in go2rtc can be used for custom ffmpeg commands. An example is below:
+The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.4#source-exec) source in go2rtc can be used for custom ffmpeg commands. An example is below:
 
 NOTE: The output will need to be passed with two curly braces `{{output}}`
 

docs/docs/configuration/review.md

@@ -0,0 +1,67 @@
+---
+id: review
+title: Review
+---
+
+The Review page of the Frigate UI is for quickly reviewing historical footage of interest from your cameras. _Review items_ are indicated on a vertical timeline and displayed as a grid of previews - bandwidth-optimized, low frame rate, low resolution videos. Hovering over or swiping a preview plays the video and marks it as reviewed. If more in-depth analysis is required, the preview can be clicked/tapped and the full frame rate, full resolution recording is displayed.
+
+Review items are filterable by date, object type, and camera.
+
+## 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.
+
+## Restricting alerts to specific labels
+
+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:
+  alerts:
+    labels:
+      - car
+      - cat
+      - dog
+      - person
+      - speech
+```
+
+## Restricting detections to specific labels
+
+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:
+  detections:
+    labels:
+      - bark
+      - dog
+```
+
+## Excluding a camera from alerts or detections
+
+To exclude a specific camera from alerts or detections, simply provide an empty list to the alerts or detections field _at the camera level_.
+
+For example, to exclude objects on the camera _gatecamera_ from any detections, include this in your config:
+
+```yaml
+cameras:
+  gatecamera:
+    review:
+      detections:
+        labels: []
+```
+
+## Restricting review items to specific zones
+
+By default a review item will be created if any `review -> alerts -> labels` and `review -> detections -> labels` are detected anywhere in the camera frame. You will likely want to configure review items to only be created when the object enters an area of interest, [see the zone docs for more information](./zones.md#restricting-alerts-and-detections-to-specific-zones)
+
+:::info
+
+Because zones don't apply to audio, audio labels will always be marked as an alert.
+
+:::

docs/docs/configuration/snapshots.md

@@ -3,6 +3,10 @@ id: snapshots
 title: Snapshots
 ---
 
-Frigate can save a snapshot image to `/media/frigate/clips` for each event named as `<camera>-<id>.jpg`.
+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)
 
-Snapshots sent via MQTT are configured in the [config file](https://docs.frigate.video/configuration/) under  `cameras -> your_camera -> mqtt`
+For users with Frigate+ enabled, snapshots are accessible in the UI in the Frigate+ pane to allow for quick submission to the Frigate+ service.
+
+To only save snapshots for objects that enter a specific zone, [see the zone docs](./zones.md#restricting-snapshots-to-specific-zones)
+
+Snapshots sent via MQTT are configured in the [config file](https://docs.frigate.video/configuration/) under `cameras -> your_camera -> mqtt`

docs/docs/configuration/stationary_objects.md

@@ -23,10 +23,6 @@ NOTE: There is no way to disable stationary object tracking with this value.
 
 `threshold` is the number of frames an object needs to remain relatively still before it is considered stationary.
 
-## Handling stationary objects
-
-In some cases, like a driveway, you may prefer to only have an event when a car is coming & going vs a constant event of it stationary in the driveway. You can reference [this guide](../guides/parked_cars.md) for recommended approaches.
-
 ## Why does Frigate track stationary objects?
 
 Frigate didn't always track stationary objects. In fact, it didn't even track objects at all initially.

docs/docs/configuration/tls.md

@@ -0,0 +1,47 @@
+---
+id: tls
+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 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.
+
+In many deployments, TLS will be unnecessary. It can be disabled in the config with the following yaml:
+
+```yaml
+tls:
+  enabled: False
+```
+
+## Certificates
+
+TLS certificates can be mounted at `/etc/letsencrypt/live/frigate` using a bind mount or docker volume.
+
+```yaml
+frigate:
+  ...
+  volumes:
+    - /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`.
+
+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 8080 to 443.
+
+```yaml
+frigate:
+  ...
+  ports:
+    - "443:8080"
+  ...
+```
+
+## ACME Challenge
+
+Frigate also supports hosting the acme challenge files for the HTTP challenge method if needed. The challenge files should be mounted at `/etc/letsencrypt/www`.

docs/docs/configuration/user_interface.md

@@ -1,15 +0,0 @@
----
-id: user_interface
-title: User Interface Configurations
----
-
-### Experimental UI
-
-While developing and testing new components, users may decide to opt-in to test potential new features on the front-end.
-
-```yaml
-ui:
-  use_experimental: true
-```
-
-Note that experimental changes may contain bugs or may be removed at any time in future releases of the software. Use of these features are presented as-is and with no functional guarantee.

docs/docs/configuration/zones.md

@@ -10,26 +10,56 @@ For example, the cat in this image is currently in Zone 1, but **not** Zone 2.
 
 Zones cannot have the same name as a camera. If desired, a single zone can include multiple cameras if you have multiple cameras covering the same area by configuring zones with the same name for each camera.
 
-During testing, enable the Zones option for the debug feed so you can adjust as needed. The zone line will increase in thickness when any object enters the zone.
+During testing, enable the Zones option for the Debug view of your camera (Settings --> Debug) so you can adjust as needed. The zone line will increase in thickness when any object enters the zone.
 
 To create a zone, follow [the steps for a "Motion mask"](masks.md), but use the section of the web UI for creating a zone instead.
 
-### Restricting events to specific zones
+### Restricting alerts and detections to specific zones
 
-Often you will only want events to be created when an object enters areas of interest. This is done using zones along with setting required_zones. Let's say you only want to be notified when an object enters your entire_yard zone, the config would be:
+Often you will only want alerts to be created when an object enters areas of interest. This is done using zones along with setting required_zones. Let's say you only want to have an alert created when an object enters your entire_yard zone, the config would be:
 
 ```yaml
-camera:
-  record:
-    events:
+cameras:
+  name_of_your_camera:
+    review:
+      alerts:
+        required_zones:
+          - entire_yard
+    zones:
+      entire_yard:
+        coordinates: ...
+```
+
+You may also want to filter detections to only be created when an object enters a secondary area of interest. This is done using zones along with setting required_zones. Let's say you want alerts when an object enters the inner area of the yard but detections when an object enters the edge of the yard, the config would be
+
+```yaml
+cameras:
+  name_of_your_camera:
+    review:
+      alerts:
+        required_zones:
+          - inner_yard
+      detections:
+        required_zones:
+          - edge_yard
+    zones:
+      edge_yard:
+        coordinates: ...
+      inner_yard:
+        coordinates: ...
+```
+
+### Restricting snapshots to specific zones
+
+```yaml
+cameras:
+  name_of_your_camera:
+    snapshots:
       required_zones:
         - entire_yard
-  snapshots:
-    required_zones:
-      - entire_yard
-  zones:
-    entire_yard:
-      coordinates: ...
+    zones:
+      entire_yard:
+        coordinates: ...
 ```
 
 ### Restricting zones to specific objects
@@ -37,49 +67,71 @@ camera:
 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
-camera:
-  record:
-    events:
-      required_zones:
-        - entire_yard
-        - front_yard_street
-  snapshots:
-    required_zones:
-      - entire_yard
-      - front_yard_street
-  zones:
-    entire_yard:
-      coordinates: ... (everywhere you want a person)
-      objects:
-        - person
-    front_yard_street:
-      coordinates: ... (just the street)
-      objects:
-        - car
+cameras:
+  name_of_your_camera:
+    zones:
+      entire_yard:
+        coordinates: ... (everywhere you want a person)
+        objects:
+          - person
+      front_yard_street:
+        coordinates: ... (just the street)
+        objects:
+          - car
 ```
 
 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
+
+Sometimes objects are expected to be passing through a zone, but an object loitering in an area is unexpected. Zones can be configured to have a minimum loitering time before the object will be considered in the zone.
+
+```yaml
+cameras:
+  name_of_your_camera:
+    zones:
+      sidewalk:
+        loitering_time: 4 # unit is in seconds
+        objects:
+          - person
+```
+
 ### Zone Inertia
 
 Sometimes an objects bounding box may be slightly incorrect and the bottom center of the bounding box is inside the zone while the object is not actually in the zone. Zone inertia helps guard against this by requiring an object's bounding box to be within the zone for multiple consecutive frames. This value can be configured:
 
 ```yaml
-camera:
-  zones:
-    front_yard:
-      inertia: 3
-      objects:
-        - person
+cameras:
+  name_of_your_camera:
+    zones:
+      front_yard:
+        inertia: 3
+        objects:
+          - person
 ```
 
 There may also be cases where you expect an object to quickly enter and exit a zone, like when a car is pulling into the driveway, and you may want to have the object be considered present in the zone immediately:
 
 ```yaml
-camera:
-  zones:
-    driveway_entrance:
-      inertia: 1
-      objects:
-        - car
+cameras:
+  name_of_your_camera:
+    zones:
+      driveway_entrance:
+        inertia: 1
+        objects:
+          - car
+```
+
+### Loitering Time
+
+Zones support a `loitering_time` configuration which can be used to only consider an object as part of a zone if they loiter in the zone for the specified number of seconds. This can be used, for example, to create alerts for cars that stop on the street but not cars that just drive past your camera.
+
+```yaml
+cameras:
+  name_of_your_camera:
+    zones:
+      front_yard:
+        loitering_time: 5 # unit is in seconds
+        objects:
+          - person
 ```

docs/docs/development/contributing.md

@@ -33,7 +33,6 @@ Fork [blakeblackshear/frigate-hass-integration](https://github.com/blakeblackshe
 
 ### Prerequisites
 
-- [Frigate source code](#frigate-core-web-and-docs)
 - GNU make
 - Docker
 - An extra detector (Coral, OpenVINO, etc.) is optional but recommended to simulate real world performance.
@@ -129,7 +128,6 @@ ffmpeg -c:v h264_qsv -re -stream_loop -1 -i https://streams.videolan.org/ffmpeg/
 
 ### Prerequisites
 
-- [Frigate source code](#frigate-core-web-and-docs)
 - All [core](#core) prerequisites _or_ another running Frigate instance locally available
 - Node.js 20
 
@@ -155,6 +153,12 @@ cd web && npm install
 cd web && npm run dev
 ```
 
+##### 3a. Run the development server against a non-local instance
+
+To run the development server against a non-local instance, you will need to
+replace the `localhost` values in `vite.config.ts` with the IP address of the
+non-local backend server.
+
 #### 4. Making changes
 
 The Web UI is built using [Vite](https://vitejs.dev/), [Preact](https://preactjs.com), and [Tailwind CSS](https://tailwindcss.com).
@@ -182,7 +186,6 @@ npm run test
 
 ### Prerequisites
 
-- [Frigate source code](#frigate-core-web-and-docs)
 - Node.js 20
 
 ### Making changes
@@ -222,3 +225,13 @@ docker buildx create --name builder --driver docker-container --driver-opt netwo
 docker buildx inspect builder --bootstrap
 make push
 ```
+
+## Other
+
+### Nginx
+
+When testing nginx config changes from within the dev container, the following command can be used to copy and reload the config for testing without rebuilding the container:
+
+```console
+sudo cp docker/main/rootfs/usr/local/nginx/conf/* /usr/local/nginx/conf/ && sudo /usr/local/nginx/sbin/nginx -s reload
+```

docs/docs/frigate/camera_setup.md

@@ -5,9 +5,9 @@ title: Camera setup
 
 Cameras configured to output H.264 video and AAC audio will offer the most compatibility with all features of Frigate and Home Assistant. H.265 has better compression, but less compatibility. Chrome 108+, Safari and Edge are the only browsers able to play H.265 and only support a limited number of H.265 profiles. Ideally, cameras should be configured directly for the desired resolutions and frame rates you want to use in Frigate. Reducing frame rates within Frigate will waste CPU resources decoding extra frames that are discarded. There are three different goals that you want to tune your stream configurations around.
 
-- **Detection**: This is the only stream that Frigate will decode for processing. Also, this is the stream where snapshots will be generated from. The resolution for detection should be tuned for the size of the objects you want to detect. See [Choosing a detect resolution](#choosing-a-detect-resolution) for more details. The recommended frame rate is 5fps, but may need to be higher for very fast moving objects. Higher resolutions and frame rates will drive higher CPU usage on your server.
+- **Detection**: This is the only stream that Frigate will decode for processing. Also, this is the stream where snapshots will be generated from. The resolution for detection should be tuned for the size of the objects you want to detect. See [Choosing a detect resolution](#choosing-a-detect-resolution) for more details. The recommended frame rate is 5fps, but may need to be higher (10fps is the recommended maximum for most users) for very fast moving objects. Higher resolutions and frame rates will drive higher CPU usage on your server.
 
-- **Recording**: This stream should be the resolution you wish to store for reference. Typically, this will be the highest resolution your camera supports. I recommend setting this feed to 15 fps.
+- **Recording**: This stream should be the resolution you wish to store for reference. Typically, this will be the highest resolution your camera supports. I recommend setting this feed in your camera's firmware to 15 fps.
 
 - **Stream Viewing**: This stream will be rebroadcast as is to Home Assistant for viewing with the stream component. Setting this resolution too high will use significant bandwidth when viewing streams in Home Assistant, and they may not load reliably over slower connections.
 

docs/docs/frigate/glossary.md

@@ -27,7 +27,7 @@ Motion masks prevent detection of [motion](#motion) in masked areas from trigger
 
 ### Object Mask
 
-Object filter masks drop any bounding boxes where the bottom center (overlap doesn't matter) is in the masked area. It forces them to be considered a [false positive](#false_positive) so that they are ignored.
+Object filter masks drop any bounding boxes where the bottom center (overlap doesn't matter) is in the masked area. It forces them to be considered a [false positive](#false-positive) so that they are ignored.
 
 ## Min Score
 
@@ -55,4 +55,4 @@ The top score for an object is the highest median score for an object.
 
 ## 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)
+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)