Merge pull request #4055 from blakeblackshear/dev

0.12.0 Release

.devcontainer/devcontainer.json

@@ -1,16 +1,50 @@
 {
-  "name": "Frigate Dev",
+  "name": "Frigate Devcontainer",
   "dockerComposeFile": "../docker-compose.yml",
-  "service": "dev",
-  "workspaceFolder": "/lab/frigate",
+  "service": "devcontainer",
+  "workspaceFolder": "/workspace/frigate",
+  "initializeCommand": ".devcontainer/initialize.sh",
+  "postCreateCommand": ".devcontainer/post_create.sh",
+  "overrideCommand": false,
+  "remoteUser": "vscode",
+  "features": {
+    "ghcr.io/devcontainers/features/common-utils:1": {}
+  },
+  "forwardPorts": [5000, 5001, 5173, 1935, 8554, 8555],
+  "portsAttributes": {
+    "5000": {
+      "label": "NGINX",
+      "onAutoForward": "silent"
+    },
+    "5001": {
+      "label": "Frigate API",
+      "onAutoForward": "silent"
+    },
+    "5173": {
+      "label": "Vite Server",
+      "onAutoForward": "silent"
+    },
+    "1935": {
+      "label": "RTMP",
+      "onAutoForward": "silent"
+    },
+    "8554": {
+      "label": "gortc RTSP",
+      "onAutoForward": "silent"
+    },
+    "8555": {
+      "label": "go2rtc WebRTC",
+      "onAutoForward": "silent"
+    }
+  },
   "extensions": [
+    "ms-python.vscode-pylance",
     "ms-python.python",
     "visualstudioexptteam.vscodeintellicode",
     "mhutchie.git-graph",
     "ms-azuretools.vscode-docker",
     "streetsidesoftware.code-spell-checker",
     "esbenp.prettier-vscode",
-    "ms-python.vscode-pylance",
     "dbaeumer.vscode-eslint",
     "mikestead.dotenv",
     "csstools.postcss",
@@ -18,6 +52,7 @@
     "bradlc.vscode-tailwindcss"
   ],
   "settings": {
+    "remote.autoForwardPorts": false,
     "python.linting.pylintEnabled": true,
     "python.linting.enabled": true,
     "python.formatting.provider": "black",
@@ -25,6 +60,9 @@
     "editor.formatOnPaste": false,
     "editor.formatOnSave": true,
     "editor.formatOnType": true,
+    "python.testing.pytestEnabled": false,
+    "python.testing.unittestEnabled": true,
+    "python.testing.unittestArgs": ["-v", "-s", "./frigate/test"],
     "files.trimTrailingWhitespace": true,
     "eslint.workingDirectories": ["./web"],
     "[json][jsonc]": {

.devcontainer/initialize.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+set -euo pipefail
+
+# These folders needs to be created and owned by the host user
+mkdir -p debug web/dist
+
+if [[ -f "config/config.yml" ]]; then
+  echo "config/config.yml already exists, skipping initialization" >&2
+else
+  echo "initializing config/config.yml" >&2
+  cp -fv config/config.yml.example config/config.yml
+fi

.devcontainer/post_create.sh

@@ -0,0 +1,17 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+# Frigate normal container runs as root, so it have permission to create
+# the folders. But the devcontainer runs as the host user, so we need to
+# create the folders and give the host user permission to write to them.
+sudo mkdir -p /media/frigate
+sudo chown -R "$(id -u):$(id -g)" /media/frigate
+
+make version
+
+cd web
+
+npm install
+
+npm run build

.dockerignore

@@ -9,4 +9,8 @@ core
 *.mp4
 *.jpg
 *.db
-*.ts
+*.ts
+
+web/dist/
+web/node_modules/
+web/.npm

.github/ISSUE_TEMPLATE/detector_support_request.yml

@@ -1,6 +1,6 @@
-name: EdgeTpu Support Request
-description: Support for setting up EdgeTPU in Frigate
-title: "[EdgeTPU Support]: "
+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:

.github/dependabot.yml

@@ -0,0 +1,32 @@
+version: 2
+updates:
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
+  - package-ecosystem: "docker"
+    directory: "/docker"
+    schedule:
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
+  - package-ecosystem: "npm"
+    directory: "/web"
+    schedule:
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
+  - package-ecosystem: "npm"
+    directory: "/docs"
+    schedule:
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev

.github/workflows/ci.yml

@@ -0,0 +1,67 @@
+name: CI
+
+on:
+  push:
+    branches:
+      - dev
+      - master
+
+# only run the latest commit to avoid cache overwrites
+concurrency:
+  group: ${{ github.ref }}
+  cancel-in-progress: true
+
+env:
+  PYTHON_VERSION: 3.9
+
+jobs:
+  multi_arch_build:
+    runs-on: ubuntu-latest
+    name: Image Build
+    steps:
+      - name: Remove unnecessary files
+        run: |
+          sudo rm -rf /usr/share/dotnet
+          sudo rm -rf /usr/local/lib/android
+          sudo rm -rf /opt/ghc
+      - id: lowercaseRepo
+        uses: ASzc/change-string-case-action@v5
+        with:
+          string: ${{ github.repository }}
+      - name: Check out code
+        uses: actions/checkout@v3
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v2
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+      - name: Log in to the Container registry
+        uses: docker/login-action@f4ef78c080cd8ba55a85445d5b36e214a81df20a
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+      - name: Create version file
+        run: make version
+      - name: Create short sha
+        run: echo "SHORT_SHA=${GITHUB_SHA::7}" >> $GITHUB_ENV
+      - name: Build and push
+        uses: docker/build-push-action@v3
+        with:
+          context: .
+          push: true
+          platforms: linux/amd64,linux/arm64,linux/arm/v7
+          target: frigate
+          tags: |
+            ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+      - name: Build and push TensorRT
+        uses: docker/build-push-action@v3
+        with:
+          context: .
+          push: true
+          platforms: linux/amd64
+          target: frigate-tensorrt
+          tags: |
+            ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ github.ref_name }}-${{ env.SHORT_SHA }}-tensorrt
+          cache-from: type=gha

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

@@ -0,0 +1,22 @@
+name: dependabot-auto-merge
+on: pull_request
+
+permissions:
+  contents: write
+
+jobs:
+  dependabot-auto-merge:
+    runs-on: ubuntu-latest
+    if: github.actor == 'dependabot[bot]'
+    steps:
+      - name: Get Dependabot metadata
+        id: metadata
+        uses: dependabot/fetch-metadata@v1
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+      - name: Enable auto-merge for Dependabot PRs
+        if: steps.metadata.outputs.dependency-type == 'direct:development' && (steps.metadata.outputs.update-type == 'version-update:semver-minor' || steps.metadata.outputs.update-type == 'version-update:semver-patch')
+        run: gh pr merge --auto --squash "$PR_URL"
+        env:
+          PR_URL: ${{ github.event.pull_request.html_url }}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/pull_request.yml

@@ -6,11 +6,35 @@ env:
   DEFAULT_PYTHON: 3.9
 
 jobs:
+  build_devcontainer:
+    runs-on: ubuntu-latest
+    name: Build Devcontainer
+    # The Dockerfile contains features that requires buildkit, and since the
+    # devcontainer cli uses docker-compose to build the image, the only way to
+    # ensure docker-compose uses buildkit is to explicitly enable it.
+    env:
+      DOCKER_BUILDKIT: "1"
+    steps:
+      - uses: actions/checkout@v3
+      - uses: actions/setup-node@master
+        with:
+          node-version: 16.x
+      - name: Install devcontainer cli
+        run: npm install --global @devcontainers/cli
+      - name: Build devcontainer
+        run: devcontainer build --workspace-folder .
+      # It would be nice to also test the following commands, but for some
+      # reason they don't work even though in VS Code devcontainer works.
+      # - name: Start devcontainer
+      #   run: devcontainer up --workspace-folder .
+      # - name: Run devcontainer scripts
+      #   run: devcontainer run-user-commands --workspace-folder .
+
   web_lint:
     name: Web - Lint
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@master
+      - uses: actions/checkout@v3
       - uses: actions/setup-node@master
         with:
           node-version: 16.x
@@ -24,7 +48,7 @@ jobs:
     name: Web - Test
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@master
+      - uses: actions/checkout@v3
       - uses: actions/setup-node@master
         with:
           node-version: 16.x
@@ -36,12 +60,12 @@ jobs:
 
   python_checks:
     runs-on: ubuntu-latest
-    name: Python checks
+    name: Python Checks
     steps:
       - name: Check out the repository
-        uses: actions/checkout@v2.3.4
+        uses: actions/checkout@v3
       - name: Set up Python ${{ env.DEFAULT_PYTHON }}
-        uses: actions/setup-python@v2.2.2
+        uses: actions/setup-python@v4.5.0
         with:
           python-version: ${{ env.DEFAULT_PYTHON }}
       - name: Install requirements
@@ -57,7 +81,7 @@ jobs:
     name: Python Tests
     steps:
       - name: Check out code
-        uses: actions/checkout@v2
+        uses: actions/checkout@v3
       - uses: actions/setup-node@master
         with:
           node-version: 16.x
@@ -67,11 +91,9 @@ jobs:
         run: npm run build
         working-directory: ./web
       - name: Set up QEMU
-        uses: docker/setup-qemu-action@v1
+        uses: docker/setup-qemu-action@v2
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v1
-      - name: Create Version Module
-        run: make version
+        uses: docker/setup-buildx-action@v2
       - name: Build
         run: make
       - name: Run mypy

.github/workflows/stale.yml

@@ -6,7 +6,7 @@ name: "Stalebot"
 on:
   schedule:
     - cron: "0 0 * * *" # run stalebot once a day
-    
+
 jobs:
   stale:
     runs-on: ubuntu-latest
@@ -14,12 +14,13 @@ jobs:
       - uses: actions/stale@main
         id: stale
         with:
-          stale-issue-message: 'This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.'
-          close-issue-message: ''
+          stale-issue-message: "This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions."
+          close-issue-message: ""
           days-before-stale: 30
           days-before-close: 3
           exempt-draft-pr: true
-          exempt-issue-labels: 'pinned,security'
-          exempt-pr-labels: 'pinned,security'
+          exempt-issue-labels: "pinned,security"
+          exempt-pr-labels: "pinned,security,dependencies"
+          operations-per-run: 120
       - name: Print outputs
         run: echo ${{ join(steps.stale.outputs.*, ',') }}

.gitignore

@@ -2,7 +2,8 @@
 *.pyc
 *.swp
 debug
-.vscode
+.vscode/*
+!.vscode/launch.json
 config/config.yml
 models
 *.mp4

.vscode/launch.json

@@ -0,0 +1,12 @@
+{
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Python: Launch Frigate",
+      "type": "python",
+      "request": "launch",
+      "module": "frigate",
+      "justMyCode": true
+    }
+  ]
+}

Dockerfile

@@ -0,0 +1,272 @@
+# syntax=docker/dockerfile:1.2
+
+# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
+ARG DEBIAN_FRONTEND=noninteractive
+
+FROM debian:11 AS base
+
+FROM --platform=linux/amd64 debian:11 AS base_amd64
+
+FROM debian:11-slim AS slim-base
+
+FROM slim-base AS wget
+ARG DEBIAN_FRONTEND
+RUN apt-get update \
+    && apt-get install -y wget xz-utils \
+    && rm -rf /var/lib/apt/lists/*
+WORKDIR /rootfs
+
+FROM base AS nginx
+ARG DEBIAN_FRONTEND
+
+# bind /var/cache/apt to tmpfs to speed up nginx build
+RUN --mount=type=tmpfs,target=/tmp --mount=type=tmpfs,target=/var/cache/apt \
+    --mount=type=bind,source=docker/build_nginx.sh,target=/deps/build_nginx.sh \
+    /deps/build_nginx.sh
+
+FROM wget AS go2rtc
+ARG TARGETARCH
+WORKDIR /rootfs/usr/local/go2rtc/bin
+RUN wget -qO go2rtc "https://github.com/AlexxIT/go2rtc/releases/download/v1.2.0/go2rtc_linux_${TARGETARCH}" \
+    && chmod +x go2rtc
+
+
+####
+#
+# 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
+FROM base_amd64 AS ov-converter
+ARG DEBIAN_FRONTEND
+
+# Install OpenVino Runtime and Dev library
+COPY requirements-ov.txt /requirements-ov.txt
+RUN apt-get -qq update \
+    && apt-get -qq install -y wget python3 python3-distutils \
+    && 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
+
+# Build libUSB without udev.  Needed for Openvino NCS2 support
+WORKDIR /opt
+RUN apt-get update && apt-get install -y unzip build-essential automake libtool
+RUN wget -q https://github.com/libusb/libusb/archive/v1.0.25.zip -O v1.0.25.zip && \
+    unzip v1.0.25.zip && cd libusb-1.0.25 && \
+    ./bootstrap.sh && \
+    ./configure --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-1.0.25/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-1.0.25/ && \
+    /usr/bin/install -c -m 644 libusb-1.0.pc '/usr/local/lib/pkgconfig' && \
+    ldconfig
+
+FROM wget AS models
+
+# Get model and labels
+RUN wget -qO edgetpu_model.tflite https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess_edgetpu.tflite
+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
+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
+
+
+
+FROM wget AS s6-overlay
+ARG TARGETARCH
+RUN --mount=type=bind,source=docker/install_s6_overlay.sh,target=/deps/install_s6_overlay.sh \
+    /deps/install_s6_overlay.sh
+
+
+FROM base AS wheels
+ARG DEBIAN_FRONTEND
+ARG TARGETARCH
+
+# Use a separate container to build wheels to prevent build dependencies in final image
+RUN apt-get -qq update \
+    && apt-get -qq install -y \
+    apt-transport-https \
+    gnupg \
+    wget \
+    && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 9165938D90FDDD2E \
+    && echo "deb http://raspbian.raspberrypi.org/raspbian/ bullseye main contrib non-free rpi" | tee /etc/apt/sources.list.d/raspi.list \
+    && apt-get -qq update \
+    && apt-get -qq install -y \
+    python3 \
+    python3-dev \
+    wget \
+    # opencv dependencies
+    build-essential cmake git pkg-config libgtk-3-dev \
+    libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
+    libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev \
+    gfortran openexr libatlas-base-dev libssl-dev\
+    libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev \
+    libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev \
+    # scipy dependencies
+    gcc gfortran libopenblas-dev liblapack-dev && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
+    && python3 get-pip.py "pip"
+
+RUN if [ "${TARGETARCH}" = "arm" ]; \
+    then echo "[global]" > /etc/pip.conf \
+    && echo "extra-index-url=https://www.piwheels.org/simple" >> /etc/pip.conf; \
+    fi
+
+COPY requirements.txt /requirements.txt
+RUN pip3 install -r requirements.txt
+
+COPY requirements-wheels.txt /requirements-wheels.txt
+RUN pip3 wheel --wheel-dir=/wheels -r requirements-wheels.txt
+
+# Make this a separate target so it can be built/cached optionally
+FROM wheels as trt-wheels
+ARG DEBIAN_FRONTEND
+ARG TARGETARCH
+
+# Add TensorRT wheels to another folder
+COPY requirements-tensorrt.txt /requirements-tensorrt.txt
+RUN mkdir -p /trt-wheels && pip3 wheel --wheel-dir=/trt-wheels -r requirements-tensorrt.txt
+
+
+# Collect deps in a single layer
+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=s6-overlay /rootfs/ /
+COPY --from=models /rootfs/ /
+COPY docker/rootfs/ /
+
+
+# Frigate deps (ffmpeg, python, nginx, go2rtc, s6-overlay, etc)
+FROM slim-base AS deps
+ARG TARGETARCH
+
+ARG DEBIAN_FRONTEND
+# http://stackoverflow.com/questions/48162574/ddg#49462622
+ARG APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn
+
+# https://github.com/NVIDIA/nvidia-docker/wiki/Installation-(Native-GPU-Support)
+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}"
+
+# Install dependencies
+RUN --mount=type=bind,source=docker/install_deps.sh,target=/deps/install_deps.sh \
+    /deps/install_deps.sh
+
+RUN --mount=type=bind,from=wheels,source=/wheels,target=/deps/wheels \
+    pip3 install -U /deps/wheels/*.whl
+
+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"
+
+ENTRYPOINT ["/init"]
+CMD []
+
+# Frigate deps with Node.js and NPM for devcontainer
+FROM deps AS devcontainer
+
+# Do not start the actual Frigate service on devcontainer as it will be started by VSCode
+# But start a fake service for simulating the logs
+COPY docker/fake_frigate_run /etc/s6-overlay/s6-rc.d/frigate/run
+
+# Create symbolic link to the frigate source code, as go2rtc's create_config.sh uses it
+RUN mkdir -p /opt/frigate \
+    && ln -svf /workspace/frigate/frigate /opt/frigate/frigate
+
+# Install Node 16
+RUN apt-get update \
+    && apt-get install wget -y \
+    && wget -qO- https://deb.nodesource.com/setup_16.x | bash - \
+    && apt-get install -y nodejs \
+    && rm -rf /var/lib/apt/lists/* \
+    && npm install -g npm@9
+
+WORKDIR /workspace/frigate
+
+RUN apt-get update \
+    && apt-get install make -y \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN --mount=type=bind,source=./requirements-dev.txt,target=/workspace/frigate/requirements-dev.txt \
+    pip3 install -r requirements-dev.txt
+
+CMD ["sleep", "infinity"]
+
+
+# Frigate web build
+# force this to run on amd64 because QEMU is painfully slow
+FROM --platform=linux/amd64 node:16 AS web-build
+
+WORKDIR /work
+COPY web/package.json web/package-lock.json ./
+RUN npm install
+
+COPY web/ ./
+RUN npm run build \
+    && mv dist/BASE_PATH/monacoeditorwork/* dist/assets/ \
+    && rm -rf dist/BASE_PATH
+
+# Collect final files in a single layer
+FROM scratch AS rootfs
+
+WORKDIR /opt/frigate/
+COPY frigate frigate/
+COPY migrations migrations/
+COPY --from=web-build /work/dist/ web/
+
+# Frigate final container
+FROM deps AS frigate
+
+WORKDIR /opt/frigate/
+COPY --from=rootfs / /
+
+# Frigate w/ TensorRT Support as separate image
+FROM frigate AS frigate-tensorrt
+RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
+    pip3 install -U /deps/trt-wheels/*.whl && \
+    ln -s libnvrtc.so.11.2 /usr/local/lib/python3.9/dist-packages/nvidia/cuda_nvrtc/lib/libnvrtc.so && \
+    ldconfig
+
+# Dev Container w/ TRT
+FROM devcontainer AS devcontainer-trt
+
+RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels \
+    pip3 install -U /deps/trt-wheels/*.whl

Makefile

@@ -1,39 +1,42 @@
 default_target: local
 
 COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
-VERSION = 0.11.1
+VERSION = 0.12.0
+IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate
 CURRENT_UID := $(shell id -u)
 CURRENT_GID := $(shell id -g)
 
 version:
-	echo "VERSION=\"$(VERSION)-$(COMMIT_HASH)\"" > frigate/version.py
+	echo 'VERSION = "$(VERSION)-$(COMMIT_HASH)"' > frigate/version.py
 
-build_web:
-	docker run --volume ${PWD}/web:/web -w /web --volume /etc/passwd:/etc/passwd:ro --volume /etc/group:/etc/group:ro -u $(CURRENT_UID):$(CURRENT_GID) node:16 /bin/bash -c "npm install && npm run build"
+local: version
+	docker buildx build --target=frigate --tag frigate:latest --load .
 
-nginx_frigate:
-	docker buildx build --push --platform linux/arm/v7,linux/arm64/v8,linux/amd64 --tag blakeblackshear/frigate-nginx:1.0.2 --file docker/Dockerfile.nginx .
-
-local:
-	DOCKER_BUILDKIT=1 docker build -t frigate -f docker/Dockerfile .
+local-trt: version
+	docker buildx build --target=frigate-tensorrt --tag frigate:latest-tensorrt --load .
 
 amd64:
-	docker buildx build --platform linux/amd64 --tag blakeblackshear/frigate:$(VERSION)-$(COMMIT_HASH) --file docker/Dockerfile .
+	docker buildx build --platform linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
+	docker buildx build --platform linux/amd64 --target=frigate-tensorrt --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH)-tensorrt .
 
 arm64:
-	docker buildx build --platform linux/arm64 --tag blakeblackshear/frigate:$(VERSION)-$(COMMIT_HASH) --file docker/Dockerfile .
+	docker buildx build --platform linux/arm64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
 
 armv7:
-	docker buildx build --platform linux/arm/v7 --tag blakeblackshear/frigate:$(VERSION)-$(COMMIT_HASH) --file docker/Dockerfile .
+	docker buildx build --platform linux/arm/v7 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
 
 build: version amd64 arm64 armv7
-	docker buildx build --platform linux/arm/v7,linux/arm64/v8,linux/amd64 --tag blakeblackshear/frigate:$(VERSION)-$(COMMIT_HASH) --file docker/Dockerfile .
+	docker buildx build --platform linux/arm/v7,linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):$(VERSION)-$(COMMIT_HASH) .
 
 push: build
-	docker buildx build --push --platform linux/arm/v7,linux/arm64/v8,linux/amd64 --tag blakeblackshear/frigate:$(VERSION)-$(COMMIT_HASH) --file docker/Dockerfile .
+	docker buildx build --push --platform linux/arm/v7,linux/arm64/v8,linux/amd64 --target=frigate --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH) .
+	docker buildx build --push --platform linux/amd64 --target=frigate-tensorrt --tag $(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-tensorrt .
 
-run_tests: frigate
-	docker run --rm --entrypoint=python3 frigate:latest -u -m unittest
-	docker run --rm --entrypoint=python3 frigate:latest -u -m mypy --config-file frigate/mypy.ini frigate
+run: local
+	docker run --rm --publish=5000:5000 --volume=${PWD}/config/config.yml:/config/config.yml frigate:latest
+
+run_tests: local
+	docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest python3 -u -m unittest
+	docker run --rm --workdir=/opt/frigate --entrypoint= frigate:latest python3 -u -m mypy --config-file frigate/mypy.ini frigate
 
 .PHONY: run_tests

README.md

@@ -16,7 +16,8 @@ Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but
 - Communicates over MQTT for easy integration into other systems
 - Records video with retention settings based on detected objects
 - 24/7 recording
-- Re-streaming via RTMP to reduce the number of connections to your camera
+- Re-streaming via RTSP to reduce the number of connections to your camera
+- WebRTC & MSE support for low-latency live view
 
 ## Documentation
 

benchmark.py

@@ -3,10 +3,16 @@ from statistics import mean
 import multiprocessing as mp
 import numpy as np
 import datetime
-from frigate.edgetpu import LocalObjectDetector, EdgeTPUProcess, RemoteObjectDetector, load_labels
+from frigate.config import DetectorTypeEnum
+from frigate.object_detection import (
+    LocalObjectDetector,
+    ObjectDetectProcess,
+    RemoteObjectDetector,
+    load_labels,
+)
 
-my_frame = np.expand_dims(np.full((300,300,3), 1, np.uint8), axis=0)
-labels = load_labels('/labelmap.txt')
+my_frame = np.expand_dims(np.full((300, 300, 3), 1, np.uint8), axis=0)
+labels = load_labels("/labelmap.txt")
 
 ######
 # Minimal same process runner
@@ -39,20 +45,23 @@ labels = load_labels('/labelmap.txt')
 
 
 def start(id, num_detections, detection_queue, event):
-  object_detector = RemoteObjectDetector(str(id), '/labelmap.txt', detection_queue, event)
-  start = datetime.datetime.now().timestamp()
+    object_detector = RemoteObjectDetector(
+        str(id), "/labelmap.txt", detection_queue, event
+    )
+    start = datetime.datetime.now().timestamp()
 
-  frame_times = []
-  for x in range(0, num_detections):
-    start_frame = datetime.datetime.now().timestamp()
-    detections = object_detector.detect(my_frame)
-    frame_times.append(datetime.datetime.now().timestamp()-start_frame)
+    frame_times = []
+    for x in range(0, num_detections):
+        start_frame = datetime.datetime.now().timestamp()
+        detections = object_detector.detect(my_frame)
+        frame_times.append(datetime.datetime.now().timestamp() - start_frame)
+
+    duration = datetime.datetime.now().timestamp() - start
+    object_detector.cleanup()
+    print(f"{id} - Processed for {duration:.2f} seconds.")
+    print(f"{id} - FPS: {object_detector.fps.eps():.2f}")
+    print(f"{id} - Average frame processing time: {mean(frame_times)*1000:.2f}ms")
 
-  duration = datetime.datetime.now().timestamp()-start
-  object_detector.cleanup()
-  print(f"{id} - Processed for {duration:.2f} seconds.")
-  print(f"{id} - FPS: {object_detector.fps.eps():.2f}")
-  print(f"{id} - Average frame processing time: {mean(frame_times)*1000:.2f}ms")
 
 ######
 # Separate process runner
@@ -71,23 +80,29 @@ camera_processes = []
 
 events = {}
 for x in range(0, 10):
-  events[str(x)] = mp.Event()
+    events[str(x)] = mp.Event()
 detection_queue = mp.Queue()
-edgetpu_process_1 = EdgeTPUProcess(detection_queue, events, 'usb:0')
-edgetpu_process_2 = EdgeTPUProcess(detection_queue, events, 'usb:1')
+edgetpu_process_1 = ObjectDetectProcess(
+    detection_queue, events, DetectorTypeEnum.edgetpu, "usb:0"
+)
+edgetpu_process_2 = ObjectDetectProcess(
+    detection_queue, events, DetectorTypeEnum.edgetpu, "usb:1"
+)
 
 for x in range(0, 10):
-  camera_process = mp.Process(target=start, args=(x, 300, detection_queue, events[str(x)]))
-  camera_process.daemon = True
-  camera_processes.append(camera_process)
+    camera_process = mp.Process(
+        target=start, args=(x, 300, detection_queue, events[str(x)])
+    )
+    camera_process.daemon = True
+    camera_processes.append(camera_process)
 
 start_time = datetime.datetime.now().timestamp()
 
 for p in camera_processes:
-  p.start()
+    p.start()
 
 for p in camera_processes:
-  p.join()
+    p.join()
 
-duration = datetime.datetime.now().timestamp()-start_time
-print(f"Total - Processed for {duration:.2f} seconds.")
+duration = datetime.datetime.now().timestamp() - start_time
+print(f"Total - Processed for {duration:.2f} seconds.")

config/config.yml.example

@@ -0,0 +1,16 @@
+mqtt:
+  host: mqtt
+
+cameras:
+  test:
+    ffmpeg:
+      inputs:
+        - path: /media/frigate/car-stopping.mp4
+          input_args: -re -stream_loop -1 -fflags +genpts
+          roles:
+            - detect
+            - rtmp
+    detect:
+      height: 1080
+      width: 1920
+      fps: 5

docker-compose.yml

@@ -1,8 +1,7 @@
 version: "3"
 services:
-  dev:
-    container_name: frigate-dev
-    user: vscode
+  devcontainer:
+    container_name: frigate-devcontainer
     # add groups from host for render, plugdev, video
     group_add:
       - "109" # render
@@ -12,24 +11,27 @@ services:
     shm_size: "256mb"
     build:
       context: .
-      dockerfile: docker/Dockerfile.dev
+      # Use target devcontainer-trt for TensorRT dev
+      target: devcontainer
+    deploy:
+          resources:
+              reservations:
+                  devices:
+                      - driver: nvidia
+                        count: 1
+                        capabilities: [gpu]
     devices:
       - /dev/bus/usb:/dev/bus/usb
-      - /dev/dri:/dev/dri # for intel hwaccel, needs to be updated for your hardware
+      # - /dev/dri:/dev/dri # for intel hwaccel, needs to be updated for your hardware
     volumes:
+      - .:/workspace/frigate:cached
+      - ./web/dist:/opt/frigate/web:cached
       - /etc/localtime:/etc/localtime:ro
-      - .:/lab/frigate:cached
       - ./config/config.yml:/config/config.yml:ro
       - ./debug:/media/frigate
+      # Create the trt-models folder using the documented method of generating TRT models
+      # - ./debug/trt-models:/trt-models
       - /dev/bus/usb:/dev/bus/usb
-    ports:
-      - "1935:1935"
-      - "3000:3000"
-      - "5000:5000"
-      - "5001:5001"
-      - "8080:8080"
-    entrypoint: ["sudo", "/init"]
-    command: /bin/sh -c "while sleep 1000; do :; done"
   mqtt:
     container_name: mqtt
     image: eclipse-mosquitto:1.6

docker/Dockerfile

@@ -1,150 +0,0 @@
-FROM blakeblackshear/frigate-nginx:1.0.2 as nginx
-
-FROM debian:11 as wheels
-ARG TARGETARCH
-
-ENV DEBIAN_FRONTEND=noninteractive
-
-# Use a separate container to build wheels to prevent build dependencies in final image
-RUN apt-get -qq update \
-    && apt-get -qq install -y \
-    apt-transport-https \
-    gnupg \
-    wget \
-    && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 9165938D90FDDD2E \
-    && echo "deb http://raspbian.raspberrypi.org/raspbian/ bullseye main contrib non-free rpi" | tee /etc/apt/sources.list.d/raspi.list \
-    && apt-get -qq update \
-    && apt-get -qq install -y \
-    python3 \
-    python3-dev \
-    wget \
-    # opencv dependencies
-    build-essential cmake git pkg-config libgtk-3-dev \
-    libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
-    libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev \
-    gfortran openexr libatlas-base-dev libssl-dev\
-    libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev \
-    libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev \
-    # scipy dependencies
-    gcc gfortran libopenblas-dev liblapack-dev
-
-RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
-    && python3 get-pip.py "pip"
-
-RUN if [ "${TARGETARCH}" = "arm" ]; \
-    then echo "[global]" > /etc/pip.conf \
-    && echo "extra-index-url=https://www.piwheels.org/simple" >> /etc/pip.conf; \
-    fi
-
-COPY requirements.txt /requirements.txt
-RUN pip3 install -r requirements.txt
-
-COPY requirements-wheels.txt /requirements-wheels.txt
-RUN pip3 wheel --wheel-dir=/wheels -r requirements-wheels.txt
-
-# Frigate Container
-FROM debian:11-slim
-ARG TARGETARCH
-
-# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
-ARG DEBIAN_FRONTEND="noninteractive"
-# http://stackoverflow.com/questions/48162574/ddg#49462622
-ARG APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn
-# https://github.com/NVIDIA/nvidia-docker/wiki/Installation-(Native-GPU-Support)
-ENV NVIDIA_DRIVER_CAPABILITIES="compute,video,utility"
-
-ENV FLASK_ENV=development
-
-COPY --from=wheels /wheels /wheels
-
-# Install ffmpeg
-RUN apt-get -qq update \
-    && apt-get -qq install --no-install-recommends -y \
-    apt-transport-https \
-    gnupg \
-    wget \
-    unzip tzdata libxml2 xz-utils \
-    python3-pip \
-    # add raspberry pi repo
-    && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 9165938D90FDDD2E \
-    && echo "deb http://raspbian.raspberrypi.org/raspbian/ bullseye main contrib non-free rpi" | tee /etc/apt/sources.list.d/raspi.list \
-    # add coral repo
-    && apt-key adv --fetch-keys https://packages.cloud.google.com/apt/doc/apt-key.gpg \
-    && echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" > /etc/apt/sources.list.d/coral-edgetpu.list \
-    && echo "libedgetpu1-max libedgetpu/accepted-eula select true" | debconf-set-selections \
-    # enable non-free repo
-    && sed -i -e's/ main/ main contrib non-free/g' /etc/apt/sources.list \
-    && apt-get -qq update \
-    && apt-get -qq install --no-install-recommends --no-install-suggests -y \
-    # coral drivers
-    libedgetpu1-max python3-tflite-runtime python3-pycoral \
-    && pip3 install -U /wheels/*.whl \
-    # btbn-ffmpeg -> amd64 / arm64
-    && if [ "${TARGETARCH}" = "amd64" ] || [ "${TARGETARCH}" = "arm64" ]; then \
-    mkdir -p /usr/lib/btbn-ffmpeg \
-    && wget -O btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux$( [ "$TARGETARCH" = "amd64" ] && echo "64" || echo "arm64" )-gpl-5.1.tar.xz" \
-    && tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/btbn-ffmpeg --strip-components 1 \
-    && rm btbn-ffmpeg.tar.xz; \
-    fi \
-    # ffmpeg -> arm32
-    && if [ "${TARGETARCH}" = "arm" ]; then \
-    apt-get -qq install --no-install-recommends --no-install-suggests -y ffmpeg; \
-    fi \
-    # arch specific packages
-    && if [ "${TARGETARCH}" = "amd64" ]; then \
-    echo 'deb http://deb.debian.org/debian testing main non-free' >> /etc/apt/sources.list.d/deb.list \
-    && apt-get -qq update \
-    && apt-get -qq install --no-install-recommends --no-install-suggests -y \
-    mesa-va-drivers libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1; \
-    fi \
-    && if [ "${TARGETARCH}" = "arm64" ]; then \
-    apt-get -qq install --no-install-recommends --no-install-suggests -y \
-    libva-drm2 mesa-va-drivers; \
-    fi \
-    # not sure why 32bit arm requires all these
-    && if [ "${TARGETARCH}" = "arm" ]; then \
-    apt-get -qq install --no-install-recommends --no-install-suggests -y \
-    libgtk-3-dev \
-    libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
-    libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev \
-    gfortran openexr libatlas-base-dev libssl-dev\
-    libtbb2 libtbb-dev libdc1394-22-dev libopenexr-dev \
-    libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev; \
-    fi \
-    && rm -rf /wheels \
-    && apt-get remove gnupg apt-transport-https -y \
-    && apt-get clean autoclean -y \
-    && apt-get autoremove -y \
-    && rm -rf /var/lib/apt/lists/*
-
-ENV PATH=$PATH:/usr/lib/btbn-ffmpeg/bin
-
-COPY --from=nginx /usr/local/nginx/ /usr/local/nginx/
-
-# get model and labels
-COPY labelmap.txt /labelmap.txt
-RUN wget -q https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess_edgetpu.tflite -O /edgetpu_model.tflite
-RUN wget -q https://github.com/google-coral/test_data/raw/release-frogfish/ssdlite_mobiledet_coco_qat_postprocess.tflite -O /cpu_model.tflite
-
-WORKDIR /opt/frigate/
-ADD frigate frigate/
-ADD migrations migrations/
-
-COPY web/dist web/
-
-COPY docker/rootfs/ /
-
-# s6-overlay
-RUN S6_ARCH="${TARGETARCH}" \
-    && if [ "${TARGETARCH}" = "amd64" ]; then S6_ARCH="amd64"; fi \
-    && if [ "${TARGETARCH}" = "arm" ]; then S6_ARCH="armhf"; fi \
-    && if [ "${TARGETARCH}" = "arm64" ]; then S6_ARCH="aarch64"; fi \
-    && wget -O /tmp/s6-overlay-installer "https://github.com/just-containers/s6-overlay/releases/download/v2.2.0.3/s6-overlay-${S6_ARCH}-installer" \
-    && chmod +x /tmp/s6-overlay-installer && /tmp/s6-overlay-installer /
-
-EXPOSE 5000
-EXPOSE 1935
-
-ENTRYPOINT ["/init"]
-
-CMD ["python3", "-u", "-m", "frigate"]

docker/Dockerfile.dev

@@ -1,27 +0,0 @@
-FROM frigate:latest
-
-ARG USERNAME=vscode
-ARG USER_UID=1000
-ARG USER_GID=$USER_UID
-
-# Create the user
-RUN groupadd --gid $USER_GID $USERNAME \
-    && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME -s /bin/bash \
-    #
-    # [Optional] Add sudo support. Omit if you don't need to install software after connecting.
-    && apt-get update \
-    && apt-get install -y sudo \
-    && echo $USERNAME ALL=\(root\) NOPASSWD:ALL > /etc/sudoers.d/$USERNAME \
-    && chmod 0440 /etc/sudoers.d/$USERNAME
-
-RUN apt-get update \
-    && apt-get install -y git curl vim htop
-
-COPY requirements-dev.txt /opt/frigate/requirements-dev.txt
-RUN pip3 install -r requirements-dev.txt
-
-# Install Node 16
-RUN curl -sL https://deb.nodesource.com/setup_16.x | bash - \
-    && apt-get install -y nodejs
-
-RUN npm install -g npm@latest

docker/build_nginx.sh

@@ -0,0 +1,66 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+NGINX_VERSION="1.22.1"
+VOD_MODULE_VERSION="1.30"
+SECURE_TOKEN_MODULE_VERSION="1.4"
+RTMP_MODULE_VERSION="1.2.1"
+
+cp /etc/apt/sources.list /etc/apt/sources.list.d/sources-src.list
+sed -i 's|deb http|deb-src http|g' /etc/apt/sources.list.d/sources-src.list
+apt-get update
+
+apt-get -yqq build-dep nginx
+
+apt-get -yqq install --no-install-recommends ca-certificates wget
+update-ca-certificates -f
+mkdir /tmp/nginx
+wget -nv https://nginx.org/download/nginx-${NGINX_VERSION}.tar.gz
+tar -zxf nginx-${NGINX_VERSION}.tar.gz -C /tmp/nginx --strip-components=1
+rm nginx-${NGINX_VERSION}.tar.gz
+mkdir /tmp/nginx-vod-module
+wget -nv https://github.com/kaltura/nginx-vod-module/archive/refs/tags/${VOD_MODULE_VERSION}.tar.gz
+tar -zxf ${VOD_MODULE_VERSION}.tar.gz -C /tmp/nginx-vod-module --strip-components=1
+rm ${VOD_MODULE_VERSION}.tar.gz
+    # Patch MAX_CLIPS to allow more clips to be added than the default 128
+sed -i 's/MAX_CLIPS (128)/MAX_CLIPS (1080)/g' /tmp/nginx-vod-module/vod/media_set.h
+patch -d /tmp/nginx-vod-module/ -p1 << 'EOF'
+--- a/vod/avc_hevc_parser.c       2022-06-27 11:38:10.000000000 +0000
++++ b/vod/avc_hevc_parser.c       2023-01-16 11:25:10.900521298 +0000
+@@ -3,6 +3,9 @@
+ bool_t
+ avc_hevc_parser_rbsp_trailing_bits(bit_reader_state_t* reader)
+ {
++	// https://github.com/blakeblackshear/frigate/issues/4572
++	return TRUE;
++
+ 	uint32_t one_bit;
+
+ 	if (reader->stream.eof_reached)
+EOF
+
+
+mkdir /tmp/nginx-secure-token-module
+wget https://github.com/kaltura/nginx-secure-token-module/archive/refs/tags/${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
+
+cd /tmp/nginx
+
+./configure --prefix=/usr/local/nginx \
+    --with-file-aio \
+    --with-http_sub_module \
+    --with-http_ssl_module \
+    --with-threads \
+    --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 -j$(nproc) && make install
+rm -rf /usr/local/nginx/html /usr/local/nginx/conf/*.default

docker/fake_frigate_run

@@ -0,0 +1,13 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Start the fake Frigate service
+
+set -o errexit -o nounset -o pipefail
+
+# Tell S6-Overlay not to restart this service
+s6-svc -O .
+
+while true; do
+  echo "[INFO] The fake Frigate service is running..."
+  sleep 5s
+done

docker/install_deps.sh

@@ -0,0 +1,91 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+apt-get -qq update
+
+apt-get -qq install --no-install-recommends -y \
+    apt-transport-https \
+    gnupg \
+    wget \
+    procps vainfo \
+    unzip locales tzdata libxml2 xz-utils \
+    python3-pip \
+    curl \
+    jq
+
+mkdir -p -m 600 /root/.gnupg
+
+# add coral repo
+wget --quiet -O /usr/share/keyrings/google-edgetpu.gpg https://packages.cloud.google.com/apt/doc/apt-key.gpg
+echo "deb [signed-by=/usr/share/keyrings/google-edgetpu.gpg] https://packages.cloud.google.com/apt coral-edgetpu-stable main" | tee /etc/apt/sources.list.d/coral-edgetpu.list
+echo "libedgetpu1-max libedgetpu/accepted-eula select true" | debconf-set-selections
+
+# enable non-free repo
+sed -i -e's/ main/ main contrib non-free/g' /etc/apt/sources.list
+
+# coral drivers
+apt-get -qq update
+apt-get -qq install --no-install-recommends --no-install-suggests -y \
+    libedgetpu1-max python3-tflite-runtime python3-pycoral
+
+# btbn-ffmpeg -> amd64
+if [[ "${TARGETARCH}" == "amd64" ]]; then
+    mkdir -p /usr/lib/btbn-ffmpeg
+    wget -qO btbn-ffmpeg.tar.xz "https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2022-07-31-12-37/ffmpeg-n5.1-2-g915ef932a3-linux64-gpl-5.1.tar.xz"
+    tar -xf btbn-ffmpeg.tar.xz -C /usr/lib/btbn-ffmpeg --strip-components 1
+    rm -rf btbn-ffmpeg.tar.xz /usr/lib/btbn-ffmpeg/doc /usr/lib/btbn-ffmpeg/bin/ffplay
+fi
+
+# ffmpeg -> arm32
+if [[ "${TARGETARCH}" == "arm" ]]; then
+    # add raspberry pi repo
+    gpg --no-default-keyring --keyring /usr/share/keyrings/raspbian.gpg --keyserver keyserver.ubuntu.com --recv-keys 9165938D90FDDD2E
+    echo "deb [signed-by=/usr/share/keyrings/raspbian.gpg] http://raspbian.raspberrypi.org/raspbian/ bullseye main contrib non-free rpi" | tee /etc/apt/sources.list.d/raspi.list
+    apt-get -qq update
+    apt-get -qq install --no-install-recommends --no-install-suggests -y ffmpeg
+fi
+
+# ffmpeg -> arm64
+if [[ "${TARGETARCH}" == "arm64" ]]; then
+    # add raspberry pi repo
+    gpg --no-default-keyring --keyring /usr/share/keyrings/raspbian.gpg --keyserver keyserver.ubuntu.com --recv-keys 82B129927FA3303E
+    echo "deb [signed-by=/usr/share/keyrings/raspbian.gpg] https://archive.raspberrypi.org/debian/ bullseye main" | tee /etc/apt/sources.list.d/raspi.list
+    apt-get -qq update
+    apt-get -qq install --no-install-recommends --no-install-suggests -y ffmpeg
+fi
+
+# arch specific packages
+if [[ "${TARGETARCH}" == "amd64" ]]; then
+    # Use debian testing repo only for hwaccel packages
+    echo 'deb http://deb.debian.org/debian testing main non-free' >/etc/apt/sources.list.d/debian-testing.list
+    apt-get -qq update
+    # intel-opencl-icd specifically for GPU support in OpenVino
+    apt-get -qq install --no-install-recommends --no-install-suggests -y \
+        intel-opencl-icd \
+        mesa-va-drivers libva-drm2 intel-media-va-driver-non-free i965-va-driver libmfx1 radeontop intel-gpu-tools
+    # something about this dependency requires it to be installed in a separate call rather than in the line above
+    apt-get -qq install --no-install-recommends --no-install-suggests -y \
+        i965-va-driver-shaders
+    rm -f /etc/apt/sources.list.d/debian-testing.list
+fi
+
+if [[ "${TARGETARCH}" == "arm64" ]]; then
+    apt-get -qq install --no-install-recommends --no-install-suggests -y \
+        libva-drm2 mesa-va-drivers
+fi
+
+# not sure why 32bit arm requires all these
+if [[ "${TARGETARCH}" == "arm" ]]; then
+    apt-get -qq install --no-install-recommends --no-install-suggests -y \
+        libgtk-3-dev \
+        libavcodec-dev libavformat-dev libswscale-dev libv4l-dev \
+        libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev \
+        gfortran openexr libatlas-base-dev libtbb-dev libdc1394-22-dev libopenexr-dev \
+        libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev
+fi
+
+apt-get purge gnupg apt-transport-https wget xz-utils -y
+apt-get clean autoclean -y
+apt-get autoremove --purge -y
+rm -rf /var/lib/apt/lists/*

docker/install_s6_overlay.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+s6_version="3.1.4.1"
+
+if [[ "${TARGETARCH}" == "amd64" ]]; then
+    s6_arch="x86_64"
+elif [[ "${TARGETARCH}" == "arm" ]]; then
+    s6_arch="armhf"
+elif [[ "${TARGETARCH}" == "arm64" ]]; then
+    s6_arch="aarch64"
+fi
+
+mkdir -p /rootfs/
+
+wget -qO- "https://github.com/just-containers/s6-overlay/releases/download/v${s6_version}/s6-overlay-noarch.tar.xz" |
+    tar -C /rootfs/ -Jxpf -
+
+wget -qO- "https://github.com/just-containers/s6-overlay/releases/download/v${s6_version}/s6-overlay-${s6_arch}.tar.xz" |
+    tar -C /rootfs/ -Jxpf -

docker/rootfs/etc/ld.so.conf.d/cuda_tensorrt.conf

@@ -0,0 +1,5 @@
+/usr/local/lib/python3.9/dist-packages/nvidia/cudnn/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cuda_runtime/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cublas/lib
+/usr/local/lib/python3.9/dist-packages/nvidia/cuda_nvrtc/lib
+/usr/local/lib/python3.9/dist-packages/tensorrt

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

@@ -0,0 +1 @@
+frigate

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

@@ -0,0 +1 @@
+frigate-pipeline

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

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

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

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

docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/finish

@@ -0,0 +1,28 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Take down the S6 supervision tree when the service exits
+
+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="Frigate"
+
+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 $((128 + exit_code_signal)) >/run/s6-linux-init-container-results/exitcode
+  fi
+elif [[ "${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
+fi
+
+exec /run/s6/basedir/bin/halt

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

@@ -0,0 +1 @@
+frigate-log

docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/run

@@ -0,0 +1,18 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Start the Frigate service
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+# Tell S6-Overlay not to restart this service
+s6-svc -O .
+
+echo "[INFO] Starting Frigate..."
+
+cd /opt/frigate || echo "[ERROR] Failed to change working directory to /opt/frigate"
+
+# Replace the bash process with the Frigate process, redirecting stderr to stdout
+exec 2>&1
+exec python3 -u -m frigate

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

@@ -0,0 +1 @@
+120000

docker/rootfs/etc/s6-overlay/s6-rc.d/frigate/type

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

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/finish

@@ -0,0 +1,12 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+readonly exit_code_service="${1}"
+readonly exit_code_signal="${2}"
+readonly service="go2rtc-healthcheck"
+
+echo "[INFO] The ${service} service exited with code ${exit_code_service} (by signal ${exit_code_signal})"

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/producer-for

@@ -0,0 +1 @@
+go2rtc-log

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/run

@@ -0,0 +1,22 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Start the go2rtc-healthcheck service
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+# Give some additional time for go2rtc to start before start pinging
+sleep 10s
+echo "[INFO] Starting go2rtc healthcheck service..."
+
+while sleep 30s; do
+    # Check if the service is running
+    if ! curl --connect-timeout 10 --fail --silent --show-error --output /dev/null http://127.0.0.1:1984/api/streams 2>&1; then
+        echo "[ERROR] The go2rtc service is not responding to ping, restarting..."
+        # We can also use -r instead of -t to send kill signal rather than term
+        s6-svc -t /var/run/service/go2rtc 2>&1
+        # Give some additional time to go2rtc to restart before start pinging again
+        sleep 10s
+    fi
+done

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/timeout-kill

@@ -0,0 +1 @@
+5000

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-healthcheck/type

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

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/consumer-for

@@ -0,0 +1,2 @@
+go2rtc
+go2rtc-healthcheck

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/pipeline-name

@@ -0,0 +1 @@
+go2rtc-pipeline

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/run

@@ -0,0 +1,4 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+
+exec logutil-service /dev/shm/logs/go2rtc

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc-log/type

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

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/finish

@@ -0,0 +1,12 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+readonly exit_code_service="${1}"
+readonly exit_code_signal="${2}"
+readonly service="go2rtc"
+
+echo "[INFO] The ${service} service exited with code ${exit_code_service} (by signal ${exit_code_signal})"

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/producer-for

@@ -0,0 +1 @@
+go2rtc-log

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/run

@@ -0,0 +1,70 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Start the go2rtc service
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+function get_ip_and_port_from_supervisor() {
+    local ip_address
+    # Example: 192.168.1.10/24
+    local ip_regex='^([0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3})/[0-9]{1,2}$'
+    if ip_address=$(
+        curl -fsSL \
+            -H "Authorization: Bearer ${SUPERVISOR_TOKEN}" \
+            -H "Content-Type: application/json" \
+            http://supervisor/network/interface/default/info |
+            jq --exit-status --raw-output '.data.ipv4.address[0]'
+    ) && [[ "${ip_address}" =~ ${ip_regex} ]]; then
+        ip_address="${BASH_REMATCH[1]}"
+        echo "[INFO] Got IP address from supervisor: ${ip_address}"
+    else
+        echo "[WARN] Failed to get IP address from supervisor"
+        return 0
+    fi
+
+    local webrtc_port
+    local port_regex='^([0-9]{1,5})$'
+    if webrtc_port=$(
+        curl -fsSL \
+            -H "Authorization: Bearer ${SUPERVISOR_TOKEN}" \
+            -H "Content-Type: application/json" \
+            http://supervisor/addons/self/info |
+            jq --exit-status --raw-output '.data.network["8555/tcp"]'
+    ) && [[ "${webrtc_port}" =~ ${port_regex} ]]; then
+        webrtc_port="${BASH_REMATCH[1]}"
+        echo "[INFO] Got WebRTC port from supervisor: ${webrtc_port}"
+    else
+        echo "[WARN] Failed to get WebRTC port from supervisor"
+        return 0
+    fi
+
+    export FRIGATE_GO2RTC_WEBRTC_CANDIDATE_INTERNAL="${ip_address}:${webrtc_port}"
+}
+
+if [[ ! -f "/dev/shm/go2rtc.yaml" ]]; then
+    echo "[INFO] Preparing go2rtc config..."
+
+    if [[ -n "${SUPERVISOR_TOKEN:-}" ]]; then
+        # Running as a Home Assistant add-on, infer the IP address and port
+        get_ip_and_port_from_supervisor
+    fi
+
+    python3 /usr/local/go2rtc/create_config.py
+fi
+
+readonly config_path="/config"
+
+if [[ -x "${config_path}/go2rtc" ]]; then
+  readonly binary_path="${config_path}/go2rtc"
+  echo "[WARN] Using go2rtc binary from '${binary_path}' instead of the embedded one"
+else
+  readonly binary_path="/usr/local/go2rtc/bin/go2rtc"
+fi
+
+echo "[INFO] Starting go2rtc..."
+
+# Replace the bash process with the go2rtc process, redirecting stderr to stdout
+exec 2>&1
+exec "${binary_path}" -config=/dev/shm/go2rtc.yaml

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/timeout-kill

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

docker/rootfs/etc/s6-overlay/s6-rc.d/go2rtc/type

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

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

@@ -0,0 +1,11 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Prepare the logs folder for s6-log
+
+set -o errexit -o nounset -o pipefail
+
+dirs=(/dev/shm/logs/frigate /dev/shm/logs/go2rtc /dev/shm/logs/nginx)
+
+mkdir -p "${dirs[@]}"
+chown nobody:nogroup "${dirs[@]}"
+chmod 02755 "${dirs[@]}"

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

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

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

@@ -0,0 +1 @@
+/etc/s6-overlay/s6-rc.d/log-prepare/run

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

@@ -0,0 +1 @@
+nginx

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

@@ -0,0 +1 @@
+nginx-pipeline

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

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

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

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

docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/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="NGINX"
+
+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/rootfs/etc/s6-overlay/s6-rc.d/nginx/producer-for

@@ -0,0 +1 @@
+nginx-log

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

@@ -0,0 +1,13 @@
+#!/command/with-contenv bash
+# shellcheck shell=bash
+# Start the NGINX service
+
+set -o errexit -o nounset -o pipefail
+
+# Logs should be sent to stdout so that s6 can collect them
+
+echo "[INFO] Starting NGINX..."
+
+# Replace the bash process with the NGINX process, redirecting stderr to stdout
+exec 2>&1
+exec nginx

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

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

docker/rootfs/etc/s6-overlay/s6-rc.d/nginx/type

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

docker/rootfs/etc/services.d/nginx/finish

@@ -1,5 +0,0 @@
-#!/usr/bin/execlineb -S1
-if { s6-test ${1} -ne 0 }
-if { s6-test ${1} -ne 256 }
-
-s6-svscanctl -t /var/run/s6/services

docker/rootfs/etc/services.d/nginx/run

@@ -1,2 +0,0 @@
-#!/usr/bin/execlineb -P
-/usr/local/nginx/sbin/nginx

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

@@ -0,0 +1,106 @@
+"""Creates a go2rtc config file."""
+
+import json
+import os
+import sys
+import yaml
+
+sys.path.insert(0, "/opt/frigate")
+from frigate.const import BIRDSEYE_PIPE, BTBN_PATH
+from frigate.ffmpeg_presets import parse_preset_hardware_acceleration_encode
+
+sys.path.remove("/opt/frigate")
+
+
+FRIGATE_ENV_VARS = {k: v for k, v in os.environ.items() if k.startswith("FRIGATE_")}
+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
+
+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)
+
+go2rtc_config: dict[str, any] = config.get("go2rtc", {})
+
+# Need to enable CORS for go2rtc so the frigate integration / card work automatically
+if go2rtc_config.get("api") is None:
+    go2rtc_config["api"] = {"origin": "*"}
+elif go2rtc_config["api"].get("origin") is None:
+    go2rtc_config["api"]["origin"] = "*"
+
+# we want to ensure that logs are easy to read
+if go2rtc_config.get("log") is None:
+    go2rtc_config["log"] = {"format": "text"}
+elif go2rtc_config["log"].get("format") is None:
+    go2rtc_config["log"]["format"] = "text"
+
+if not go2rtc_config.get("webrtc", {}).get("candidates", []):
+    default_candidates = []
+    # use internal candidate if it was discovered when running through the add-on
+    internal_candidate = os.environ.get(
+        "FRIGATE_GO2RTC_WEBRTC_CANDIDATE_INTERNAL", None
+    )
+    if internal_candidate is not None:
+        default_candidates.append(internal_candidate)
+    # should set default stun server so webrtc can work
+    default_candidates.append("stun:8555")
+
+    go2rtc_config["webrtc"] = {"candidates": default_candidates}
+else:
+    print(
+        "[INFO] Not injecting WebRTC candidates into go2rtc config as it has been set manually",
+    )
+
+# sets default RTSP response to be equivalent to ?video=h264,h265&audio=aac
+# this means user does not need to specify audio codec when using restream
+# as source for frigate and the integration supports HLS playback
+if go2rtc_config.get("rtsp") is None:
+    go2rtc_config["rtsp"] = {"default_query": "mp4"}
+elif go2rtc_config["rtsp"].get("default_query") is None:
+    go2rtc_config["rtsp"]["default_query"] = "mp4"
+
+# need to replace ffmpeg command when using ffmpeg4
+if not os.path.exists(BTBN_PATH):
+    if go2rtc_config.get("ffmpeg") is None:
+        go2rtc_config["ffmpeg"] = {
+            "rtsp": "-fflags nobuffer -flags low_delay -stimeout 5000000 -user_agent go2rtc/ffmpeg -rtsp_transport tcp -i {input}"
+        }
+    elif go2rtc_config["ffmpeg"].get("rtsp") is None:
+        go2rtc_config["ffmpeg"][
+            "rtsp"
+        ] = "-fflags nobuffer -flags low_delay -stimeout 5000000 -user_agent go2rtc/ffmpeg -rtsp_transport tcp -i {input}"
+
+for name in go2rtc_config.get("streams", {}):
+    stream = go2rtc_config["streams"][name]
+
+    if isinstance(stream, str):
+        go2rtc_config["streams"][name] = go2rtc_config["streams"][name].format(
+            **FRIGATE_ENV_VARS
+        )
+    elif isinstance(stream, list):
+        for i, stream in enumerate(stream):
+            go2rtc_config["streams"][name][i] = stream.format(**FRIGATE_ENV_VARS)
+
+# add birdseye restream stream if enabled
+if config.get("birdseye", {}).get("restream", False):
+    birdseye: dict[str, any] = config.get("birdseye")
+
+    input = f"-f rawvideo -pix_fmt yuv420p -video_size {birdseye.get('width', 1280)}x{birdseye.get('height', 720)} -r 10 -i {BIRDSEYE_PIPE}"
+    ffmpeg_cmd = f"exec:{parse_preset_hardware_acceleration_encode(config.get('ffmpeg', {}).get('hwaccel_args'), input, '-rtsp_transport tcp -f rtsp {output}')}"
+
+    if go2rtc_config.get("streams"):
+        go2rtc_config["streams"]["birdseye"] = ffmpeg_cmd
+    else:
+        go2rtc_config["streams"] = {"birdseye": ffmpeg_cmd}
+
+# Write go2rtc_config to /dev/shm/go2rtc.yaml
+with open("/dev/shm/go2rtc.yaml", "w") as f:
+    yaml.dump(go2rtc_config, f)

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

@@ -1,27 +1,30 @@
 daemon off;
 user root;
-worker_processes  1;
+worker_processes auto;
 
-error_log  /usr/local/nginx/logs/error.log warn;
-pid        /var/run/nginx.pid;
+error_log /dev/stdout warn;
+pid /var/run/nginx.pid;
 
 events {
-    worker_connections  1024;
+    worker_connections 1024;
 }
 
 http {
-    include       mime.types;
-    default_type  application/octet-stream;
+    include mime.types;
+    default_type application/octet-stream;
 
-    log_format  main  '$remote_addr - $remote_user [$time_local] "$request" '
+    log_format main '$remote_addr - $remote_user [$time_local] "$request" '
                         '$status $body_bytes_sent "$http_referer" '
                         '"$http_user_agent" "$http_x_forwarded_for"';
 
-    access_log  /usr/local/nginx/logs/access.log  main;
+    access_log /dev/stdout main;
 
-    sendfile        on;
+    # send headers in one piece, it is better than sending them one by one
+    tcp_nopush on;
 
-    keepalive_timeout  65;
+    sendfile on;
+
+    keepalive_timeout 65;
 
     gzip on;
     gzip_comp_level 6;
@@ -30,18 +33,23 @@ http {
     gzip_vary on;
 
     upstream frigate_api {
-      server 127.0.0.1:5001;
-      keepalive 1024;
+        server 127.0.0.1:5001;
+        keepalive 1024;
     }
 
     upstream mqtt_ws {
-      server 127.0.0.1:5002;
-      keepalive 1024;
+        server 127.0.0.1:5002;
+        keepalive 1024;
     }
 
     upstream jsmpeg {
-      server 127.0.0.1:8082;
-      keepalive 1024;
+        server 127.0.0.1:8082;
+        keepalive 1024;
+    }
+
+    upstream go2rtc {
+        server 127.0.0.1:1984;
+        keepalive 1024;
     }
 
     server {
@@ -56,6 +64,19 @@ http {
         vod_align_segments_to_key_frames on;
         vod_manifest_segment_durations_mode accurate;
         vod_ignore_edit_list on;
+        vod_segment_duration 10000;
+        vod_hls_mpegts_align_frames off;
+        vod_hls_mpegts_interleave_frames on;
+
+        # file handle caching / aio
+        open_file_cache max=1000 inactive=5m;
+        open_file_cache_valid 2m;
+        open_file_cache_min_uses 1;
+        open_file_cache_errors on;
+        aio on;
+
+        # https://github.com/kaltura/nginx-vod-module#vod_open_file_thread_pool
+        vod_open_file_thread_pool default;
 
         # vod caches
         vod_metadata_cache metadata_cache 512m;
@@ -65,18 +86,12 @@ http {
         gzip on;
         gzip_types application/vnd.apple.mpegurl;
 
-        # file handle caching / aio
-        open_file_cache          max=1000 inactive=5m;
-        open_file_cache_valid    2m;
-        open_file_cache_min_uses 1;
-        open_file_cache_errors   on;
-        aio on;
-
         location /vod/ {
+            aio threads;
             vod hls;
 
             secure_token $args;
-			secure_token_types application/vnd.apple.mpegurl;
+            secure_token_types application/vnd.apple.mpegurl;
 
             add_header Access-Control-Allow-Headers '*';
             add_header Access-Control-Expose-Headers 'Server,range,Content-Length,Content-Range';
@@ -132,8 +147,8 @@ http {
         }
 
         location /cache/ {
-                internal; # This tells nginx it's not accessible from the outside
-                alias /tmp/cache/;
+            internal; # This tells nginx it's not accessible from the outside
+            alias /tmp/cache/;
         }
 
         location /recordings/ {
@@ -165,7 +180,7 @@ http {
             proxy_set_header Host $host;
         }
 
-        location /live/ {
+        location /live/jsmpeg/ {
             proxy_pass http://jsmpeg/;
             proxy_http_version 1.1;
             proxy_set_header Upgrade $http_upgrade;
@@ -173,6 +188,22 @@ http {
             proxy_set_header Host $host;
         }
 
+        location /live/mse/ {
+            proxy_pass http://go2rtc/;
+            proxy_http_version 1.1;
+            proxy_set_header Upgrade $http_upgrade;
+            proxy_set_header Connection "Upgrade";
+            proxy_set_header Host $host;
+        }
+
+        location /live/webrtc/ {
+            proxy_pass http://go2rtc/;
+            proxy_http_version 1.1;
+            proxy_set_header Upgrade $http_upgrade;
+            proxy_set_header Connection "Upgrade";
+            proxy_set_header Host $host;
+        }
+
         location ~* /api/.*\.(jpg|jpeg|png)$ {
             add_header 'Access-Control-Allow-Origin' '*';
             add_header 'Access-Control-Allow-Methods' 'GET, POST, PUT, DELETE, OPTIONS';
@@ -212,7 +243,8 @@ http {
             sub_filter '"/BASE_PATH/dist/' '"$http_x_ingress_path/dist/';
             sub_filter '"/BASE_PATH/js/' '"$http_x_ingress_path/js/';
             sub_filter '"/BASE_PATH/assets/' '"$http_x_ingress_path/assets/';
-            sub_filter '="/BASE_PATH/"' '=window.baseUrl';
+            sub_filter '"/BASE_PATH/monacoeditorwork/' '"$http_x_ingress_path/assets/';
+            sub_filter 'return"/BASE_PATH/"' 'return window.baseUrl';
             sub_filter '<body>' '<body><script>window.baseUrl="$http_x_ingress_path/";</script>';
             sub_filter_types text/css application/javascript;
             sub_filter_once off;
@@ -236,4 +268,4 @@ rtmp {
             meta copy;
         }
     }
-}
+}

docker/tensorrt_models.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+CUDA_HOME=/usr/local/cuda
+LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
+OUTPUT_FOLDER=/tensorrt_models
+echo "Generating the following TRT Models: ${YOLO_MODELS:="yolov4-tiny-288,yolov4-tiny-416,yolov7-tiny-416"}"
+
+# Create output folder
+mkdir -p ${OUTPUT_FOLDER}
+
+# Install packages
+pip install --upgrade pip && pip install onnx==1.9.0 protobuf==3.20.3
+
+# Clone tensorrt_demos repo
+git clone --depth 1 https://github.com/yeahme49/tensorrt_demos.git /tensorrt_demos
+
+# Build libyolo
+cd /tensorrt_demos/plugins && make all
+cp libyolo_layer.so ${OUTPUT_FOLDER}/libyolo_layer.so
+
+# Download yolo weights
+cd /tensorrt_demos/yolo && ./download_yolo.sh
+
+# Build trt engine
+cd /tensorrt_demos/yolo
+
+for model in ${YOLO_MODELS//,/ }
+do
+    python3 yolo_to_onnx.py -m ${model}
+    python3 onnx_to_tensorrt.py -m ${model}
+    cp /tensorrt_demos/yolo/${model}.trt ${OUTPUT_FOLDER}/${model}.trt;
+done

docs/docs/configuration/advanced.md

@@ -23,7 +23,7 @@ Examples of available modules are:
 
 - `frigate.app`
 - `frigate.mqtt`
-- `frigate.edgetpu`
+- `frigate.object_detection`
 - `frigate.zeroconf`
 - `detector.<detector_name>`
 - `watchdog.<camera_name>`
@@ -33,6 +33,13 @@ Examples of available modules are:
 
 This section can be used to set environment variables for those unable to modify the environment of the container (ie. within HassOS)
 
+Example:
+
+```yaml
+environment_vars:
+  VARIABLE_NAME: variable_value
+```
+
 ### `database`
 
 Event and recording information is managed in a sqlite database at `/media/frigate/frigate.db`. If that database is deleted, recordings will be orphaned and will need to be cleaned up manually. They also won't show up in the Media Browser within Home Assistant.
@@ -50,6 +57,30 @@ database:
 
 If using a custom model, the width and height will need to be specified.
 
+Custom models may also require different input tensor formats. The colorspace conversion supports RGB, BGR, or YUV frames to be sent to the object detector. The input tensor shape parameter is an enumeration to match what specified by the model.
+
+| Tensor Dimension | Description    |
+| :--------------: | -------------- |
+|        N         | Batch Size     |
+|        H         | Model Height   |
+|        W         | Model Width    |
+|        C         | Color Channels |
+
+| Available Input Tensor Shapes |
+| :---------------------------: |
+|            "nhwc"             |
+|            "nchw"             |
+
+```yaml
+# Optional: model config
+model:
+  path: /path/to/model
+  width: 320
+  height: 320
+  input_tensor: "nhwc"
+  input_pixel_format: "bgr"
+```
+
 The labelmap can be customized to your needs. A common reason to do this is to combine multiple object types that are easily confused when you don't need to be as granular such as car/truck. By default, truck is renamed to car because they are often confused. You cannot add new object types, but you can change the names of existing objects in the model.
 
 ```yaml
@@ -71,8 +102,9 @@ Note that if you rename objects in the labelmap, you will also need to update yo
 Included with Frigate is a build of ffmpeg that works for the vast majority of users. However, there exists some hardware setups which have incompatibilities with the included build. In this case, a docker volume mapping can be used to overwrite the included ffmpeg build with an ffmpeg build that works for your specific hardware setup.
 
 To do this:
+
 1. Download your ffmpeg build and uncompress to a folder on the host (let's use `/home/appdata/frigate/custom-ffmpeg` for this example).
 2. Update your docker-compose or docker CLI to include `'/home/appdata/frigate/custom-ffmpeg':'/usr/lib/btbn-ffmpeg':'ro'` in the volume mappings.
-3. Restart frigate and the custom version will be used if the mapping was done correctly.
+3. Restart Frigate and the custom version will be used if the mapping was done correctly.
 
 NOTE: The folder that is mapped from the host needs to be the folder that contains `/bin`. So if the full structure is `/home/appdata/frigate/custom-ffmpeg/bin/ffmpeg` then `/home/appdata/frigate/custom-ffmpeg` needs to be mapped to `/usr/lib/btbn-ffmpeg`.

docs/docs/configuration/camera_specific.md

@@ -3,20 +3,30 @@ id: camera_specific
 title: Camera Specific Configurations
 ---
 
+:::note
+
+This page makes use of presets of FFmpeg args. For more information on presets, see the [FFmpeg Presets](/configuration/ffmpeg_presets) page.
+
+:::
+
 ## MJPEG Cameras
 
-The input and output parameters need to be adjusted for MJPEG cameras
+Note that mjpeg cameras require encoding the video into h264 for recording, and restream roles. This will use significantly more CPU than if the cameras supported h264 feeds directly. It is recommended to use the restream role to create an h264 restream and then use that as the source for ffmpeg.
 
 ```yaml
-input_args: -avoid_negative_ts make_zero -fflags nobuffer -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -use_wallclock_as_timestamps 1 -c:v mjpeg
-```
+go2rtc:
+  streams:
+    mjpeg_cam: "ffmpeg:{your_mjpeg_stream_url}#video=h264#hardware" # <- use hardware acceleration to create an h264 stream usable for other components.
 
-Note that mjpeg cameras require encoding the video into h264 for recording, and rtmp roles. This will use significantly more CPU than if the cameras supported h264 feeds directly.
-
-```yaml
-output_args:
-  record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v libx264 -an
-  rtmp: -c:v libx264 -an -f flv
+cameras:
+  ...
+  mjpeg_cam:
+    ffmpeg:
+      inputs:
+        - path: rtsp://127.0.0.1:8554/mjpeg_cam
+          roles:
+            - detect
+            - record
 ```
 
 ## JPEG Stream Cameras
@@ -24,25 +34,7 @@ output_args:
 Cameras using a live changing jpeg image will need input parameters as below
 
 ```yaml
-input_args:
-- -r
-- 5 # << enter FPS here
-- -stream_loop
-- -1
-- -f
-- image2
-- -avoid_negative_ts
-- make_zero
-- -fflags
-- nobuffer
-- -flags
-- low_delay
-- -strict
-- experimental
-- -fflags
-- +genpts+discardcorrupt
-- -use_wallclock_as_timestamps
-- 1
+input_args: preset-http-jpeg-generic
 ```
 
 Outputting the stream will have the same args and caveats as per [MJPEG Cameras](#mjpeg-cameras)
@@ -53,7 +45,7 @@ The input parameters need to be adjusted for RTMP cameras
 
 ```yaml
 ffmpeg:
-  input_args: -avoid_negative_ts make_zero -fflags nobuffer -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -rw_timeout 5000000 -use_wallclock_as_timestamps 1 -f live_flv
+  input_args: preset-rtmp-generic
 ```
 
 ## UDP Only Cameras
@@ -62,12 +54,13 @@ If your cameras do not support TCP connections for RTSP, you can use UDP.
 
 ```yaml
 ffmpeg:
-  input_args: -avoid_negative_ts make_zero -fflags +genpts+discardcorrupt -rtsp_transport udp -timeout 5000000 -use_wallclock_as_timestamps 1
+  input_args: preset-rtsp-udp
 ```
 
 ## Model/vendor specific setup
 
 ### Annke C800
+
 This camera is H.265 only. To be able to play clips on some devices (like MacOs or iPhone) the H.265 stream has to be repackaged and the audio stream has to be converted to aac. Unfortunately direct playback of in the browser is not working (yet), but the downloaded clip can be played locally.
 
 ```yaml
@@ -77,7 +70,7 @@ cameras:
       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:
@@ -87,10 +80,8 @@ cameras:
     rtmp:
       enabled: False # <-- RTMP should be disabled if your stream is not H264
     detect:
-      width:  # <---- update for your camera's resolution
-      height:  # <---- update for your camera's resolution
-
-
+      width: # <---- update for your camera's resolution
+      height: # <---- update for your camera's resolution
 ```
 
 ### Blue Iris RTSP Cameras
@@ -99,60 +90,64 @@ You will need to remove `nobuffer` flag for Blue Iris RTSP cameras
 
 ```yaml
 ffmpeg:
-  input_args: -avoid_negative_ts make_zero -flags low_delay -strict experimental -fflags +genpts+discardcorrupt -rtsp_transport tcp -timeout 5000000 -use_wallclock_as_timestamps 1
+  input_args: preset-rtsp-blue-iris
 ```
 
 ### Reolink Cameras
 
-Reolink has older cameras (ex: 410 & 520) as well as newer camera (ex: 520a & 511wa) which support different subsets of options. In both cases using the http stream is recommended. 
+Reolink has older cameras (ex: 410 & 520) as well as newer camera (ex: 520a & 511wa) which support different subsets of options. In both cases using the http stream is recommended.
 Frigate works much better with newer reolink cameras that are setup with the below options:
 
 If available, recommended settings are:
+
 - `On, fluency first` this sets the camera to CBR (constant bit rate)
 - `Interframe Space 1x` this sets the iframe interval to the same as the frame rate
 
 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.
 
 ```yaml
+go2rtc:
+  streams:
+    reolink: 
+      - http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password
+      - "ffmpeg:reolink#audio=opus"
+    reolink_sub: 
+      - http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password
+
 cameras:
   reolink:
     ffmpeg:
-      input_args:
-        - -avoid_negative_ts
-        - make_zero
-        - -fflags
-        - +genpts+discardcorrupt
-        - -flags
-        - low_delay
-        - -strict
-        - experimental
-        - -analyzeduration
-        - 1000M
-        - -probesize
-        - 1000M
-        - -rw_timeout
-        - "5000000"
       inputs:
-        - path: http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=username&password=password
+        - path: rtsp://127.0.0.1:8554/reolink?video=copy&audio=aac
+          input_args: preset-rtsp-restream
           roles:
             - record
-            - rtmp
-        - path: http://reolink_ip/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=username&password=password
+        - path: rtsp://127.0.0.1:8554/reolink_sub?video=copy
+          input_args: preset-rtsp-restream
           roles:
             - detect
-    detect:
-      width: 896
-      height: 672
-      fps: 7
 ```
 
 ### Unifi Protect Cameras
 
-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.
+Unifi protect cameras require the rtspx stream to be used with go2rtc.
+To utilize a Unifi protect camera, modify the rtsps link to begin with rtspx.
+Additionally, remove the "?enableSrtp" from the end of the Unifi link.
+
+```yaml
+go2rtc:
+  streams:
+    front:
+      - rtspx://192.168.1.1:7441/abcdefghijk
+```
+
+[See the go2rtc docs for more information](https://github.com/AlexxIT/go2rtc/tree/v1.2.0#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.
 
 ```yaml
 ffmpeg:
   output_args:
-    record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c:v copy -ar 44100 -c:a aac
-    rtmp: -c:v copy -f flv -ar 44100 -c:a aac
+    record: preset-record-ubiquiti
+    rtmp: preset-rtmp-ubiquiti # recommend using go2rtc instead
 ```

docs/docs/configuration/cameras.md

@@ -7,25 +7,28 @@ title: Cameras
 
 Several inputs can be configured for each camera and the role of each input can be mixed and matched based on your needs. This allows you to use a lower resolution stream for object detection, but create recordings from a higher resolution stream, or vice versa.
 
+A camera is enabled by default but can be temporarily disabled by using `enabled: False`. Existing events and recordings can still be accessed. Live streams, recording and detecting are not working. Camera specific configurations will be used.
+
 Each role can only be assigned to one input per camera. The options for roles are as follows:
 
-| Role     | Description                                                                          |
-| -------- | ------------------------------------------------------------------------------------ |
-| `detect` | Main feed for object detection                                                       |
-| `record` | Saves segments of the video feed based on configuration settings. [docs](record.md) |
-| `rtmp`   | Broadcast as an RTMP feed for other services to consume. [docs](rtmp.md)            |
+| Role       | Description                                                                              |
+| ---------- | ---------------------------------------------------------------------------------------- |
+| `detect`   | Main feed for object detection                                                           |
+| `record`   | Saves segments of the video feed based on configuration settings. [docs](record.md)      |
+| `rtmp`     | Deprecated: Broadcast as an RTMP feed for other services to consume. [docs](restream.md) |
 
 ```yaml
 mqtt:
   host: mqtt.server.com
 cameras:
   back:
+    enabled: True
     ffmpeg:
       inputs:
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
           roles:
             - detect
-            - rtmp
+            - rtmp # <- deprecated, recommend using restream instead
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/live
           roles:
             - record

docs/docs/configuration/detectors.md

@@ -3,11 +3,37 @@ id: detectors
 title: Detectors
 ---
 
-By default, Frigate will use a single CPU detector. If you have a Coral, you will need to configure your detector devices in the config file. When using multiple detectors, they run in dedicated processes, but pull from a common queue of requested detections across all cameras.
+Frigate provides the following builtin detector types: `cpu`, `edgetpu`, `openvino`, and `tensorrt`. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
 
-Frigate supports `edgetpu` and `cpu` as detector types. The device value should be specified according to the [Documentation for the TensorFlow Lite Python API](https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api).
+## CPU Detector (not recommended)
 
-**Note**: There is no support for Nvidia GPUs to perform object detection with tensorflow. It can be used for ffmpeg decoding, but not object detection.
+The CPU detector type runs a TensorFlow Lite model utilizing the CPU without hardware acceleration. It is recommended to use a hardware accelerated detector type instead for better performance. To configure a CPU based detector, set the `"type"` attribute to `"cpu"`.
+
+The number of threads used by the interpreter can be specified using the `"num_threads"` attribute, and defaults to `3.`
+
+A TensorFlow Lite model is provided in the container at `/cpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with `model.path`.
+
+```yaml
+detectors:
+  cpu1:
+    type: cpu
+    num_threads: 3
+    model:
+      path: "/custom_model.tflite"
+  cpu2:
+    type: cpu
+    num_threads: 3
+```
+
+When using CPU detectors, you can add one CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.
+
+## Edge-TPU Detector
+
+The EdgeTPU detector type runs a TensorFlow Lite model utilizing the Google Coral delegate for hardware acceleration. To configure an EdgeTPU detector, set the `"type"` attribute to `"edgetpu"`.
+
+The EdgeTPU device can be specified using the `"device"` attribute according to the [Documentation for the TensorFlow Lite Python API](https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api). If not set, the delegate will use the first device it finds.
+
+A TensorFlow Lite model is provided in the container at `/edgetpu_model.tflite` and is used by this detector type by default. To provide your own model, bind mount the file into the container and provide the path with `model.path`.
 
 ### Single USB Coral
 
@@ -16,6 +42,8 @@ detectors:
   coral:
     type: edgetpu
     device: usb
+    model:
+      path: "/custom_model.tflite"
 ```
 
 ### Multiple USB Corals
@@ -31,6 +59,7 @@ detectors:
 ```
 
 ### Native Coral (Dev Board)
+
 _warning: may have [compatibility issues](https://github.com/blakeblackshear/frigate/issues/1706) after `v0.9.x`_
 
 ```yaml
@@ -64,16 +93,166 @@ detectors:
     device: pci
 ```
 
-### CPU Detectors (not recommended)
+## OpenVINO Detector
+
+The OpenVINO detector type runs an OpenVINO IR model on Intel CPU, GPU and 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.
+
+OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. 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)
+
+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.
 
 ```yaml
 detectors:
-  cpu1:
-    type: cpu
-    num_threads: 3
-  cpu2:
-    type: cpu
-    num_threads: 3
+  ov:
+    type: openvino
+    device: AUTO
+    model:
+      path: /openvino-model/ssdlite_mobilenet_v2.xml
+
+model:
+  width: 300
+  height: 300
+  input_tensor: nhwc
+  input_pixel_format: bgr
+  labelmap_path: /openvino-model/coco_91cl_bkgr.txt
 ```
 
-When using CPU detectors, you can add a CPU detector per camera. Adding more detectors than the number of cameras should not improve performance.
+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/index.md#full-configuration-reference) 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
+
+model:
+  width: 416
+  height: 416
+  input_tensor: nchw
+  input_pixel_format: bgr
+  model_type: yolox
+  labelmap_path: /path/to/coco_80cl.txt
+```
+
+### Intel NCS2 VPU and Myriad X Setup
+
+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.
+
+```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
+```
+
+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
+```
+
+## NVidia TensorRT Detector
+
+NVidia GPUs may be used for object detection using the TensorRT libraries. Due to the size of the additional libraries, this detector is only provided in images with the `-tensorrt` tag suffix. This detector is designed to work with Yolo models for object detection.
+
+### Minimum Hardware Support
+
+The TensorRT detector uses the 11.x series of CUDA libraries which have minor version compatibility. The minimum driver version on the host system must be `>=450.80.02`. Also the GPU must support a Compute Capability of `5.0` or greater. This generally correlates to a Maxwell-era GPU or newer, check the NVIDIA GPU Compute Capability table linked below.
+
+> **TODO:** NVidia claims support on compute 3.5 and 3.7, but marks it as deprecated. This would have some, but not all, Kepler GPUs as possibly working. This needs testing before making any claims of support.
+
+To use the TensorRT detector, make sure your host system has the [nvidia-container-runtime](https://docs.docker.com/config/containers/resource_constraints/#access-an-nvidia-gpu) installed to pass through the GPU to the container and the host system has a compatible driver installed for your GPU.
+
+There are improved capabilities in newer GPU architectures that TensorRT can benefit from, such as INT8 operations and Tensor cores. The features compatible with your hardware will be optimized when the model is converted to a trt file. Currently the script provided for generating the model provides a switch to enable/disable FP16 operations. If you wish to use newer features such as INT8 optimization, more work is required.
+
+#### Compatibility References:
+
+[NVIDIA TensorRT Support Matrix](https://docs.nvidia.com/deeplearning/tensorrt/archives/tensorrt-841/support-matrix/index.html)
+
+[NVIDIA CUDA Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html)
+
+[NVIDIA GPU Compute Capability](https://developer.nvidia.com/cuda-gpus)
+
+### Generate Models
+
+The model used for TensorRT must be preprocessed on the same hardware platform that they will run on. This means that each user must run additional setup to generate a model file for the TensorRT library. A script is provided that will build several common models.
+
+To generate model files, create a new folder to save the models, download the script, and launch a docker container that will run the script.
+
+```bash
+mkdir trt-models
+wget https://raw.githubusercontent.com/blakeblackshear/frigate/docker/tensorrt_models.sh
+chmod +x tensorrt_models.sh
+docker run --gpus=all --rm -it -v `pwd`/trt-models:/tensorrt_models -v `pwd`/tensorrt_models.sh:/tensorrt_models.sh nvcr.io/nvidia/tensorrt:22.07-py3 /tensorrt_models.sh
+```
+
+The `trt-models` folder can then be mapped into your Frigate container as `trt-models` and the models referenced from the config.
+
+If your GPU does not support FP16 operations, you can pass the environment variable `-e USE_FP16=False` to the `docker run` command to disable it.
+
+Specific models can be selected by passing an environment variable to the `docker run` command. Use the form `-e YOLO_MODELS=yolov4-416,yolov4-tiny-416` to select one or more model names. The models available are shown below.
+
+```
+yolov3-288
+yolov3-416
+yolov3-608
+yolov3-spp-288
+yolov3-spp-416
+yolov3-spp-608
+yolov3-tiny-288
+yolov3-tiny-416
+yolov4-288
+yolov4-416
+yolov4-608
+yolov4-csp-256
+yolov4-csp-512
+yolov4-p5-448
+yolov4-p5-896
+yolov4-tiny-288
+yolov4-tiny-416
+yolov4x-mish-320
+yolov4x-mish-640
+yolov7-tiny-288
+yolov7-tiny-416
+yolov7-640
+yolov7-320
+yolov7x-640
+yolov7x-320
+```
+
+### 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 uses `.trt` model files that are located in `/trt-models/` by default. These model file path and dimensions used will depend on which model you have generated.
+
+```yaml
+detectors:
+  tensorrt:
+    type: tensorrt
+    device: 0 #This is the default, select the first GPU
+
+model:
+  path: /trt-models/yolov7-tiny-416.trt
+  input_tensor: nchw
+  input_pixel_format: rgb
+  width: 416
+  height: 416
+```

docs/docs/configuration/ffmpeg_presets.md

@@ -0,0 +1,79 @@
+---
+id: ffmpeg_presets
+title: FFmpeg presets
+---
+
+Some presets of FFmpeg args are provided by default to make the configuration easier. All presets can be seen in [this file](https://github.com/blakeblackshear/frigate/blob/master/frigate/ffmpeg_presets.py).
+
+### Hwaccel Presets
+
+It is highly recommended to use hwaccel presets in the config. These presets not only replace the longer args, but they also give Frigate hints of what hardware is available and allows Frigate to make other optimizations using the GPU such as when encoding the birdseye restream or when scaling a stream that has a size different than the native stream size.
+
+See [the hwaccel docs](/configuration/hardware_acceleration.md) for more info on how to setup hwaccel for your GPU / iGPU.
+
+| Preset                | Usage                        | Other Notes                                           |
+| --------------------- | ---------------------------- | ----------------------------------------------------- |
+| preset-rpi-32-h264    | 32 bit Rpi with h264 stream  |                                                       |
+| preset-rpi-64-h264    | 64 bit Rpi with h264 stream  |                                                       |
+| 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     |
+
+### Input Args Presets
+
+Input args presets help make the config more readable and handle use cases for different types of streams to ensure maximum compatibility.
+
+See [the camera specific docs](/configuration/camera_specific.md) for more info on non-standard cameras and recommendations for using them in Frigate.
+
+| Preset                           | Usage                     | Other Notes                                                                                      |
+| -------------------------------- | ------------------------- | ------------------------------------------------------------------------------------------------ |
+| preset-http-jpeg-generic         | HTTP Live Jpeg            | Recommend restreaming live jpeg instead                                                          |
+| preset-http-mjpeg-generic        | HTTP Mjpeg Stream         | Recommend restreaming mjpeg stream instead                                                       |
+| preset-http-reolink              | Reolink HTTP-FLV Stream   | Only for reolink http, not when restreaming as rtsp                                              |
+| preset-rtmp-generic              | RTMP Stream               |                                                                                                  |
+| preset-rtsp-generic              | RTSP Stream               | This is the default when nothing is specified                                                    |
+| preset-rtsp-restream             | RTSP Stream from restream | Use for rtsp restream as source for frigate                                                      |
+| preset-rtsp-restream-low-latency | RTSP Stream from restream | Use for rtsp restream as source for frigate to lower latency, may cause issues with some cameras |
+| 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
+
+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.
+
+:::
+
+```yaml
+go2rtc:
+  streams:
+    reolink_cam: http://192.168.0.139/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password=password
+
+cameras:
+  reolink_cam:
+    ffmpeg:
+      inputs:
+        - path: http://192.168.0.139/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=admin&password=password
+          input_args: preset-http-reolink
+          roles:
+            - detect
+        - path: rtsp://127.0.0.1:8554/reolink_cam
+          input_args: preset-rtsp-generic
+          roles:
+            - record
+```
+
+### Output Args Presets
+
+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-aac  | Record WITH aac audio             | Use this to enable audio in recordings        |
+| preset-record-generic-audio-copy | Record WITH original audio        | Use this to enable audio in recordings        |
+| 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

@@ -7,57 +7,73 @@ It is recommended to update your configuration to enable hardware accelerated de
 
 ### Raspberry Pi 3/4
 
-:::caution
-
-There is currently a bug in ffmpeg that causes hwaccel to not work for the RPi kernel 5.15.61 and above. For more information see https://github.com/blakeblackshear/frigate/issues/3780
-
-:::
-
 Ensure you increase the allocated RAM for your GPU to at least 128 (raspi-config > Performance Options > GPU Memory).
 **NOTICE**: If you are using the addon, you may need to turn off `Protection mode` for hardware acceleration.
 
 ```yaml
 ffmpeg:
-  hwaccel_args: -c:v h264_v4l2m2m
+  hwaccel_args: preset-rpi-64-h264
 ```
 
-### Intel-based CPUs (<10th Generation) via Quicksync
+### Intel-based CPUs (<10th Generation) 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.
 
 ```yaml
 ffmpeg:
-  hwaccel_args: -hwaccel vaapi -hwaccel_device /dev/dri/renderD128 -hwaccel_output_format yuv420p
+  hwaccel_args: preset-vaapi
 ```
-**NOTICE**: With some of the processors, like the J4125, the default driver `iHD` doesn't seem to work correctly for hardware acceleration. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the frigate.yml for HA OS users](advanced.md#environment_vars).   
+
+**NOTICE**: With some of the processors, like the J4125, the default driver `iHD` doesn't seem to work correctly for hardware acceleration. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the frigate.yml for HA OS users](advanced.md#environment_vars).
 
 ### Intel-based CPUs (>=10th Generation) via Quicksync
 
+QSV must be set specifically based on the video encoding of the stream.
+
+#### H.264 streams
+
 ```yaml
 ffmpeg:
-  hwaccel_args: -c:v h264_qsv
+  hwaccel_args: preset-intel-qsv-h264
+```
+
+#### H.265 streams
+
+```yaml
+ffmpeg:
+  hwaccel_args: preset-intel-qsv-h265
 ```
 
 ### AMD/ATI GPUs (Radeon HD 2000 and newer GPUs) via libva-mesa-driver
 
+VAAPI supports automatic profile selection so it will work automatically with both H.264 and H.265 streams.
+
 **Note:** You also need to set `LIBVA_DRIVER_NAME=radeonsi` as an environment variable on the container.
 
 ```yaml
 ffmpeg:
-  hwaccel_args: -hwaccel vaapi -hwaccel_device /dev/dri/renderD128 -hwaccel_output_format yuv420p
+  hwaccel_args: preset-vaapi
 ```
 
-### NVIDIA GPU
+### NVIDIA GPUs
 
-[Supported Nvidia GPUs for Decoding](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new)
+While older GPUs may work, it is recommended to use modern, supported GPUs. NVIDIA provides a [matrix of supported GPUs and features](https://developer.nvidia.com/video-encode-and-decode-gpu-support-matrix-new). If your card is on the list and supports CUVID/NVDEC, it will most likely work with Frigate for decoding. However, you must also use [a driver version that will work with FFmpeg](https://github.com/FFmpeg/nv-codec-headers/blob/master/README). Older driver versions may be missing symbols and fail to work, and older cards are not supported by newer driver versions. The only way around this is to [provide your own FFmpeg](/configuration/advanced#custom-ffmpeg-build) that will work with your driver version, but this is unsupported and may not work well if at all.
 
-These instructions are based on the [jellyfin documentation](https://jellyfin.org/docs/general/administration/hardware-acceleration.html#nvidia-hardware-acceleration-on-docker-linux)
+A more complete list of cards and ther compatible drivers is available in the [driver release readme](https://download.nvidia.com/XFree86/Linux-x86_64/525.85.05/README/supportedchips.html).
+
+If your distribution does not offer NVIDIA driver packages, you can [download them here](https://www.nvidia.com/en-us/drivers/unix/).
+
+#### Docker Configuration
+
+Additional configuration is needed for the Docker container to be able to access the NVIDIA GPU. The supported method for this is to install the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker) and specify the GPU to Docker. How you do this depends on how Docker is being run:
+
+##### Docker Compose
 
-Add `--gpus all` to your docker run command or update your compose file.
-If you have multiple Nvidia graphic card, you can add them with their ids obtained via `nvidia-smi` command
 ```yaml
 services:
   frigate:
     ...
-    image: blakeblackshear/frigate:stable
+    image: ghcr.io/blakeblackshear/frigate:stable
     deploy:    # <------------- Add this section
       resources:
         reservations:
@@ -68,11 +84,23 @@ services:
               capabilities: [gpu]
 ```
 
+##### Docker Run CLI
+
+```bash
+docker run -d \
+  --name frigate \
+  ...
+  --gpus=all \
+  ghcr.io/blakeblackshear/frigate:stable
+```
+
+#### Setup Decoder
+
 The decoder you need to pass in the `hwaccel_args` will depend on the input video.
 
-A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the container to get a list)
+A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the container to get the ones your card supports)
 
-```shell
+```
  V..... h263_cuvid           Nvidia CUVID H263 decoder (codec h263)
  V..... h264_cuvid           Nvidia CUVID H264 decoder (codec h264)
  V..... hevc_cuvid           Nvidia CUVID HEVC decoder (codec hevc)
@@ -85,17 +113,23 @@ A list of supported codecs (you can use `ffmpeg -decoders | grep cuvid` in the c
  V..... vp9_cuvid            Nvidia CUVID VP9 decoder (codec vp9)
 ```
 
-For example, for H264 video, you'll select `h264_cuvid`.
+For example, for H264 video, you'll select `preset-nvidia-h264`.
 
 ```yaml
 ffmpeg:
-  hwaccel_args: -c:v h264_cuvid
+  hwaccel_args: preset-nvidia-h264
 ```
 
 If everything is working correctly, you should see a significant improvement in performance.
-Verify that hardware decoding is working by running `docker exec -it frigate nvidia-smi`, which should show the ffmpeg
+Verify that hardware decoding is working by running `nvidia-smi`, which should show `ffmpeg`
 processes:
 
+:::note
+
+`nvidia-smi` may not show `ffmpeg` processes when run inside the container [due to docker limitations](https://github.com/NVIDIA/nvidia-docker/issues/179#issuecomment-645579458).
+
+:::
+
 ```
 +-----------------------------------------------------------------------------+
 | NVIDIA-SMI 455.38       Driver Version: 455.38       CUDA Version: 11.1     |
@@ -123,3 +157,7 @@ processes:
 |    0   N/A  N/A     12827      C   ffmpeg                            417MiB |
 +-----------------------------------------------------------------------------+
 ```
+
+If you do not see these processes, check the `docker logs` for the container and look for decoding errors.
+
+These instructions were originally based on the [Jellyfin documentation](https://jellyfin.org/docs/general/administration/hardware-acceleration.html#nvidia-hardware-acceleration-on-docker-linux).

docs/docs/configuration/index.md

@@ -3,7 +3,7 @@ id: index
 title: Configuration File
 ---
 
-For Home Assistant Addon installations, the config file needs to be in the root of your Home Assistant config directory (same location as `configuration.yaml`) and named `frigate.yml`.
+For Home Assistant Addon installations, the config file needs to be in the root of your Home Assistant config directory (same location as `configuration.yaml`). It can be named `frigate.yml` or `frigate.yaml`, but if both files exist `frigate.yaml` will be preferred and `frigate.yml` will be ignored.
 
 For all other installation types, the config file should be mapped to `/config/config.yml` inside the container.
 
@@ -19,7 +19,6 @@ cameras:
         - path: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
           roles:
             - detect
-            - rtmp
     detect:
       width: 1280
       height: 720
@@ -27,7 +26,7 @@ cameras:
 
 ### VSCode Configuration Schema
 
-VSCode (and VSCode addon) supports the JSON schemas which will automatically validate the config. This can be added by adding `# yaml-language-server: $schema=http://frigate_host:5000/api/config/schema` to the top of the config file. `frigate_host` being the IP address of frigate or `ccab4aaf-frigate` if running in the addon.
+VSCode (and VSCode addon) supports the JSON schemas which will automatically validate the config. This can be added by adding `# yaml-language-server: $schema=http://frigate_host:5000/api/config/schema.json` to the top of the config file. `frigate_host` being the IP address of Frigate or `ccab4aaf-frigate` if running in the addon.
 
 ### Full configuration reference:
 
@@ -37,8 +36,29 @@ It is not recommended to copy this full configuration file. Only specify values
 
 :::
 
+**Note:** The following values will be replaced at runtime by using environment variables
+
+- `{FRIGATE_MQTT_USER}`
+- `{FRIGATE_MQTT_PASSWORD}`
+- `{FRIGATE_RTSP_USER}`
+- `{FRIGATE_RTSP_PASSWORD}`
+
+for example:
+
 ```yaml
 mqtt:
+  user: "{FRIGATE_MQTT_USER}"
+  password: "{FRIGATE_MQTT_PASSWORD}"
+```
+
+```yaml
+- path: rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:8554/unicast
+```
+
+```yaml
+mqtt:
+  # Optional: Enable mqtt server (default: shown below)
+  enabled: True
   # Required: host name
   host: mqtt.server.com
   # Optional: port (default: shown below)
@@ -50,6 +70,8 @@ mqtt:
   # NOTE: must be unique if you are running multiple instances
   client_id: frigate
   # Optional: user
+  # NOTE: MQTT user can be specified with an environment variables that must begin with 'FRIGATE_'.
+  #       e.g. user: '{FRIGATE_MQTT_USER}'
   user: mqtt_user
   # Optional: password
   # NOTE: MQTT password can be specified with an environment variables that must begin with 'FRIGATE_'.
@@ -72,15 +94,13 @@ mqtt:
 # Optional: Detectors configuration. Defaults to a single CPU detector
 detectors:
   # Required: name of the detector
-  coral:
+  detector_name:
     # Required: type of the detector
-    # Valid values are 'edgetpu' (requires device property below) and 'cpu'.
-    type: edgetpu
-    # Optional: device name as defined here: https://coral.ai/docs/edgetpu/multiple-edgetpu/#using-the-tensorflow-lite-python-api
-    device: usb
-    # Optional: num_threads value passed to the tflite.Interpreter (default: shown below)
-    # This value is only used for CPU types
-    num_threads: 3
+    # Frigate provided types include 'cpu', 'edgetpu', and 'openvino' (default: shown below)
+    # Additional detector types can also be plugged in.
+    # Detectors may require additional configuration.
+    # Refer to the Detectors configuration page for more information.
+    type: cpu
 
 # Optional: Database configuration
 database:
@@ -97,6 +117,15 @@ model:
   width: 320
   # Required: Object detection model input height (default: shown below)
   height: 320
+  # Optional: Object detection model input colorspace
+  # Valid values are rgb, bgr, or yuv. (default: shown below)
+  input_pixel_format: rgb
+  # Optional: Object detection model input tensor format
+  # 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)
+  model_type: ssd
   # Optional: Label name modifications. These are merged into the standard labelmap.
   labelmap:
     2: vehicle
@@ -118,6 +147,9 @@ environment_vars:
 birdseye:
   # Optional: Enable birdseye view (default: shown below)
   enabled: True
+  # Optional: Restream birdseye via RTSP (default: shown below)
+  # NOTE: Enabling this will set birdseye to run 24/7 which may increase CPU usage somewhat.
+  restream: False
   # Optional: Width of the output resolution (default: shown below)
   width: 1280
   # Optional: Height of the output resolution (default: shown below)
@@ -132,22 +164,23 @@ birdseye:
   mode: objects
 
 # Optional: ffmpeg configuration
+# More information about presets at https://docs.frigate.video/configuration/ffmpeg_presets
 ffmpeg:
   # Optional: global ffmpeg args (default: shown below)
-  global_args: -hide_banner -loglevel warning
+  global_args: -hide_banner -loglevel warning -threads 2
   # Optional: global hwaccel args (default: shown below)
   # NOTE: See hardware acceleration docs for your specific device
   hwaccel_args: []
   # Optional: global input args (default: shown below)
-  input_args: -avoid_negative_ts make_zero -fflags +genpts+discardcorrupt -rtsp_transport tcp -timeout 5000000 -use_wallclock_as_timestamps 1
+  input_args: preset-rtsp-generic
   # Optional: global output args
   output_args:
     # Optional: output args for detect streams (default: shown below)
-    detect: -f rawvideo -pix_fmt yuv420p
+    detect: -threads 2 -f rawvideo -pix_fmt yuv420p
     # Optional: output args for record streams (default: shown below)
-    record: -f segment -segment_time 10 -segment_format mp4 -reset_timestamps 1 -strftime 1 -c copy -an
+    record: preset-record-generic
     # Optional: output args for rtmp streams (default: shown below)
-    rtmp: -c copy -f flv
+    rtmp: preset-rtmp-generic
 
 # Optional: Detect configuration
 # NOTE: Can be overridden at the camera level
@@ -160,9 +193,8 @@ detect:
   # NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
   fps: 5
   # Optional: enables detection for the camera (default: True)
-  # This value can be set via MQTT and will be updated in startup based on retained value
   enabled: True
-  # Optional: Number of frames without a detection before frigate considers an object to be gone. (default: 5x the frame rate)
+  # Optional: Number of frames without a detection before Frigate considers an object to be gone. (default: 5x the frame rate)
   max_disappeared: 25
   # Optional: Configuration for stationary object tracking
   stationary:
@@ -259,11 +291,6 @@ record:
   # Optional: Enable recording (default: shown below)
   # WARNING: If recording is disabled in the config, turning it on via
   #          the UI or MQTT later will have no effect.
-  # WARNING: Frigate does not currently support limiting recordings based
-  #          on available disk space automatically. If using recordings,
-  #          you must specify retention settings for a number of days that
-  #          will fit within the available disk space of your drive or Frigate
-  #          will crash.
   enabled: False
   # Optional: Number of minutes to wait between cleanup runs (default: shown below)
   # This can be used to reduce the frequency of deleting recording segments from disk if you want to minimize i/o
@@ -313,7 +340,6 @@ record:
 # NOTE: Can be overridden at the camera level
 snapshots:
   # Optional: Enable writing jpg snapshot to /media/frigate/clips (default: shown below)
-  # This value can be set via MQTT and will be updated in startup based on retained value
   enabled: False
   # Optional: save a clean PNG copy of the snapshot image (default: shown below)
   clean_copy: True
@@ -336,19 +362,26 @@ snapshots:
       person: 15
 
 # 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: True)
-  enabled: True
+  # Optional: Enable the RTMP stream (default: False)
+  enabled: False
 
-# Optional: Live stream configuration for WebUI
-# NOTE: Can be overridden at the camera level
+# Optional: Restream configuration
+# Uses https://github.com/AlexxIT/go2rtc (v1.2.0)
+go2rtc:
+
+# Optional: jsmpeg stream configuration for WebUI
 live:
-  # Optional: Set the height of the live stream. (default: 720)
+  # Optional: Set the name of the stream that should be used for live view
+  # in frigate WebUI. (default: name of camera)
+  stream_name: camera_name
+  # Optional: Set the height of the jsmpeg stream. (default: 720)
   # This must be less than or equal to the height of the detect stream. Lower resolutions
-  # reduce bandwidth required for viewing the live stream. Width is computed to match known aspect ratio.
+  # reduce bandwidth required for viewing the jsmpeg stream. Width is computed to match known aspect ratio.
   height: 720
-  # Optional: Set the encode quality of the live stream (default: shown below)
+  # Optional: Set the encode quality of the jsmpeg stream (default: shown below)
   # 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources.
   quality: 8
 
@@ -380,6 +413,10 @@ timestamp_style:
 cameras:
   # Required: name of the camera
   back:
+    # Optional: Enable/Disable the camera (default: shown below).
+    # If disabled: config is used but no live stream and no capture etc.
+    # Events/Recordings are still viewable.
+    enabled: True
     # Required: ffmpeg settings for the camera
     ffmpeg:
       # Required: A list of input streams for the camera. See documentation for more information.
@@ -388,10 +425,11 @@ cameras:
         # NOTE: path may include environment variables, 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: detect,record,rtmp
-          # NOTICE: In addition to assigning the record, and rtmp roles,
+          # NOTICE: In addition to assigning the record and rtmp roles,
           # they must also be enabled in the camera config.
           roles:
             - detect
+            - record
             - rtmp
           # Optional: stream specific global args (default: inherit)
           # global_args:
@@ -458,4 +496,42 @@ cameras:
       order: 0
       # Optional: Whether or not to show the camera in the Frigate UI (default: shown below)
       dashboard: True
+
+# 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
+  # Optional: Set the date style for a specified length.
+  # Options are: full, long, medium, short
+  # Examples:
+  #    short: 2/11/23
+  #    medium: Feb 11, 2023
+  #    full: Saturday, February 11, 2023
+  # (default: shown below).
+  date_style: short
+  # Optional: Set the time style for a specified length.
+  # Options are: full, long, medium, short
+  # Examples:
+  #    short: 8:14 PM
+  #    medium: 8:15:22 PM
+  #    full: 8:15:22 PM Mountain Standard Time
+  # (default: shown below).
+  time_style: medium
+  # Optional: Ability to manually override the date / time styling to use strftime format
+  # https://www.gnu.org/software/libc/manual/html_node/Formatting-Calendar-Time.html
+  # possible values are shown above (default: not set)
+  strftime_fmt: "%Y/%m/%d %H:%M"
+
+# Optional: Telemetry configuration
+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
 ```

docs/docs/configuration/live.md

@@ -0,0 +1,104 @@
+---
+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).
+
+## Live View Options
+
+Live view options can be selected while viewing the live stream. The options are:
+
+| Source | Latency | Frame Rate                            | Resolution     | Audio                        | Requires go2rtc | Other Limitations                            |
+| ------ | ------- | ------------------------------------- | -------------- | ---------------------------- | --------------- | -------------------------------------------- |
+| jsmpeg | low     | same as `detect -> fps`, capped at 10 | same as detect | no                           | no              | none                                         |
+| mse    | low     | native                                | native         | yes (depends on audio codec) | yes             | not supported on iOS, Firefox is h.264 only  |
+| webrtc | lowest  | native                                | native         | yes (depends on audio codec) | yes             | requires extra config, doesn't support h.265 |
+
+### Audio Support
+
+MSE Requires AAC audio, WebRTC requires PCMU/PCMA, or opus audio. If you want to support both MSE and WebRTC then your restream config needs to make sure both are enabled.
+
+```yaml
+go2rtc:
+  streams:
+    rtsp_cam: # <- for RTSP streams
+      - rtsp://192.168.1.5:554/live0 # <- stream which supports video & aac audio
+      - "ffmpeg:rtsp_cam#audio=opus" # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
+    http_cam: # <- for http streams
+      - http://192.168.50.155/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=user&password=password # <- stream which supports video & aac audio
+      - "ffmpeg:http_cam#audio=opus" # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
+```
+
+### Setting Stream For Live UI
+
+There may be some cameras that you would prefer to use the sub stream for live view, but the main stream for recording. This can be done via `live -> stream_name`.
+
+```yaml
+go2rtc:
+  streams:
+    rtsp_cam:
+      - rtsp://192.168.1.5:554/live0 # <- stream which supports video & aac audio.
+      - "ffmpeg:rtsp_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
+    rtsp_cam_sub:
+      - rtsp://192.168.1.5:554/substream # <- stream which supports video & aac audio.
+      - "ffmpeg:rtsp_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
+
+cameras:
+  test_cam:
+    ffmpeg:
+      output_args:
+        record: preset-record-generic-audio-copy
+      inputs:
+        - path: rtsp://127.0.0.1:8554/test_cam # <--- the name here must match the name of the camera in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - record
+        - path: rtsp://127.0.0.1:8554/test_cam_sub # <--- the name here must match the name of the camera_sub in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - detect
+    live:
+      stream_name: rtsp_cam_sub
+```
+
+### WebRTC extra configuration:
+
+WebRTC works by creating a TCP or UDP connection on port `8555`. However, it requires additional configuration:
+
+- For external access, over the internet, setup your router to forward port `8555` to port `8555` on the Frigate device, for both TCP and UDP.
+- For internal/local access, unless you are running through the add-on, you will also need to set the WebRTC candidates list in the go2rtc config. For example, if `192.168.1.10` is the local IP of the device running Frigate:
+
+  ```yaml title="/config/frigate.yaml"
+  go2rtc:
+    streams:
+      test_cam: ...
+    webrtc:
+      candidates:
+        - 192.168.1.10:8555
+        - stun:8555
+  ```
+
+:::tip
+
+This extra configuration may not be required if Frigate has been installed as a Home Assistant add-on, as Frigate uses the Supervisor's API to generate a WebRTC candidate.
+
+However, it is recommended if issues occur to define the candidates manually. You should do this if the Frigate add-on fails to generate a valid candidate. If an error occurs you will see some warnings like the below in the add-on logs page during the initialization:
+
+```log
+[WARN] Failed to get IP address from supervisor
+[WARN] Failed to get WebRTC port from supervisor
+```
+
+:::
+
+:::note
+
+If you are having difficulties getting WebRTC to work and you are running Frigate with docker, you may want to try changing the container network mode:
+
+- `network: host`, in this mode you don't need to forward any ports. The services inside of the Frigate container will have full access to the network interfaces of your host machine as if they were running natively and not in a container. Any port conflicts will need to be resolved. This network mode is recommended by go2rtc, but we recommend you only use it if necessary.
+- `network: bridge` creates a virtual network interface for the container, and the container will have full access to it. You also don't need to forward any ports, however, the IP for accessing Frigate locally will differ from the IP of the host machine. Your router will see Frigate as if it was a new device connected in the network.
+
+:::
+
+See [go2rtc WebRTC docs](https://github.com/AlexxIT/go2rtc/tree/v1.2.0#module-webrtc) for more information about this.

docs/docs/configuration/masks.md

@@ -7,7 +7,7 @@ There are two types of masks available:
 
 **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.
 
-**Object filter masks**: Object filter masks are used to filter out false positives for a given object type based on location. These should be used to filter any areas where it is not possible for an object of that type to be. The bottom center of the detected object's bounding box is evaluated against the mask. If it is in a masked area, it is assumed to be a false positive. For example, you may want to mask out rooftops, walls, the sky, treetops for people. For cars, masking locations other than the street or your driveway will tell frigate that anything in your yard is a false positive.
+**Object filter masks**: Object filter masks are used to filter out false positives for a given object type based on location. These should be used to filter any areas where it is not possible for an object of that type to be. The bottom center of the detected object's bounding box is evaluated against the mask. If it is in a masked area, it is assumed to be a false positive. For example, you may want to mask out rooftops, walls, the sky, treetops for people. For cars, masking locations other than the street or your driveway will tell Frigate that anything in your yard is a false positive.
 
 To create a poly mask:
 

docs/docs/configuration/record.md

@@ -3,9 +3,15 @@ id: record
 title: Recording
 ---
 
-Recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM/DD/HH/<camera_name>/MM.SS.mp4`. These recordings are written directly from your camera stream without re-encoding. Each camera supports a configurable retention policy in the config. Frigate chooses the largest matching retention value between the recording retention and the event retention when determining if a recording should be removed.
+Recordings can be enabled and are stored at `/media/frigate/recordings`. The folder structure for the recordings is `YYYY-MM-DD/HH/<camera_name>/MM.SS.mp4`. These recordings are written directly from your camera stream without re-encoding. Each camera supports a configurable retention policy in the config. Frigate chooses the largest matching retention value between the recording retention and the event retention when determining if a recording should be removed.
 
-H265 recordings can be viewed in Edge and Safari only. All other browsers require recordings to be encoded with H264.
+New recording segments are written from the camera stream to cache, they are only moved to disk if they match the setup recording retention policy.
+
+H265 recordings can be viewed in Chrome 108+, Edge and Safari only. All other browsers require recordings to be encoded with H264.
+
+## Will Frigate delete old recordings if my storage runs out?
+
+As of Frigate 0.12 if there is less than an hour left of storage, the oldest 2 hours of recordings will be deleted.
 
 ## What if I don't want 24/7 recordings?
 
@@ -25,23 +31,23 @@ When `retain -> days` is set to `0`, segments will be deleted from the cache if
 
 ## Can I have "24/7" recordings, but only at certain times?
 
-Using Frigate UI, HomeAssistant, or MQTT, cameras can be automated to only record in certain situations or at certain times. 
+Using Frigate UI, HomeAssistant, or MQTT, cameras can be automated to only record in certain situations or at certain times.
 
 **WARNING**: Recordings still must be enabled in the config. If a camera has recordings disabled in the config, enabling via the methods listed above will have no effect.
 
 ## What do the different retain modes mean?
 
-Frigate saves from the stream with the `record` role in 10 second segments. These options determine which recording segments are kept for 24/7 recording (but can also affect events). 
+Frigate saves from the stream with the `record` role in 10 second segments. These options determine which recording segments are kept for 24/7 recording (but can also affect events).
 
-Let's say you have frigate configured so that your doorbell camera would retain the last **2** days of 24/7 recording. 
-- With the `all` option all 48 hours of those two days would be kept and viewable. 
-- With the `motion` option the only parts of those 48 hours would be segments that frigate detected motion. This is the middle ground option that won't keep all 48 hours, but will likely keep all segments of interest along with the potential for some extra segments.
+Let's say you have Frigate configured so that your doorbell camera would retain the last **2** days of 24/7 recording.
+- With the `all` option all 48 hours of those two days would be kept and viewable.
+- With the `motion` option the only parts of those 48 hours would be segments that Frigate detected motion. This is the middle ground option that won't keep all 48 hours, but will likely keep all segments of interest along with the potential for some extra segments.
 - With the `active_objects` option the only segments that would be kept are those where there was a true positive object that was not considered stationary.
 
 The same options are available with events. Let's consider a scenario where you drive up and park in your driveway, go inside, then come back out 4 hours later.
 - With the `all` option all segments for the duration of the event would be saved for the event. This event would have 4 hours of footage.
-- With the `motion` option all segments for the duration of the event with motion would be saved. This means any segment where a car drove by in the street, person walked by, lighting changed, etc. would be saved. 
-- With the `active_objects` it would only keep segments where the object was active. In this case the only segments that would be saved would be the ones where the car was driving up, you going inside, you coming outside, and the car driving away. Essentially reducing the 4 hours to a minute or two of event footage. 
+- With the `motion` option all segments for the duration of the event with motion would be saved. This means any segment where a car drove by in the street, person walked by, lighting changed, etc. would be saved.
+- With the `active_objects` it would only keep segments where the object was active. In this case the only segments that would be saved would be the ones where the car was driving up, you going inside, you coming outside, and the car driving away. Essentially reducing the 4 hours to a minute or two of event footage.
 
 A configuration example of the above retain modes where all `motion` segments are stored for 7 days and `active objects` are stored for 14 days would be as follows:
 ```yaml

docs/docs/configuration/restream.md

@@ -0,0 +1,141 @@
+---
+id: restream
+title: Restream
+---
+
+## RTSP
+
+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/v1.2.0) 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/v1.2.0#configuration) for more advanced configurations and features.
+
+:::note
+
+You can access the go2rtc webUI at `http://frigate_ip:5000/live/webrtc` which can be helpful to debug as well as provide useful information about your camera streams.
+
+:::
+
+### Birdseye Restream
+
+Birdseye RTSP restream can be enabled at `birdseye -> restream` and accessed at `rtsp://<frigate_host>:8554/birdseye`. Enabling the restream will cause birdseye to run 24/7 which may increase CPU usage somewhat.
+
+### Securing Restream With Authentication
+
+The go2rtc restream can be secured with RTSP based username / password authentication. Ex:
+
+```yaml
+go2rtc:
+  rtsp:
+    username: "admin"
+    password: "pass"
+  streams:
+    ...
+```
+
+**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 to move to the new restream role.
+
+## 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.
+
+### With Single Stream
+
+One connection is made to the camera. One for the restream, `detect` and `record` connect to the restream.
+
+```yaml
+go2rtc:
+  streams:
+    rtsp_cam: # <- for RTSP streams
+      - rtsp://192.168.1.5:554/live0 # <- stream which supports video & aac audio
+      - "ffmpeg:rtsp_cam#audio=opus" # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
+    http_cam: # <- for other streams
+      - http://192.168.50.155/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=user&password=password # <- stream which supports video & aac audio
+      - "ffmpeg:http_cam#audio=opus" # <- copy of the stream which transcodes audio to the missing codec (usually will be opus)
+
+cameras:
+  rtsp_cam:
+    ffmpeg:
+      output_args:
+        record: preset-record-generic-audio-copy
+      inputs:
+        - path: rtsp://127.0.0.1:8554/rtsp_cam # <--- the name here must match the name of the camera in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - record
+            - detect
+  http_cam:
+    ffmpeg:
+      output_args:
+        record: preset-record-generic-audio-copy
+      inputs:
+        - path: rtsp://127.0.0.1:8554/http_cam # <--- the name here must match the name of the camera in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - record
+            - detect
+```
+
+### With Sub Stream
+
+Two connections are made to the camera. One for the sub stream, one for the restream, `record` connects to the restream.
+
+```yaml
+go2rtc:
+  streams:
+    rtsp_cam: 
+      - rtsp://192.168.1.5:554/live0 # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
+      - "ffmpeg:rtsp_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
+    rtsp_cam_sub:
+      - rtsp://192.168.1.5:554/substream # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
+      - "ffmpeg:rtsp_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
+    http_cam:
+      - http://192.168.50.155/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=user&password=password # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
+      - "ffmpeg:http_cam#audio=opus" # <- copy of the stream which transcodes audio to opus
+    http_cam_sub:
+      - http://192.168.50.155/flv?port=1935&app=bcs&stream=channel0_ext.bcs&user=user&password=password # <- stream which supports video & aac audio. This is only supported for rtsp streams, http must use ffmpeg
+      - "ffmpeg:http_cam_sub#audio=opus" # <- copy of the stream which transcodes audio to opus
+
+cameras:
+  rtsp_cam:
+    ffmpeg:
+      output_args:
+        record: preset-record-generic-audio-copy
+      inputs:
+        - path: rtsp://127.0.0.1:8554/rtsp_cam # <--- the name here must match the name of the camera in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - record
+        - path: rtsp://127.0.0.1:8554/rtsp_cam_sub # <--- the name here must match the name of the camera_sub in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - detect
+  http_cam:
+    ffmpeg:
+      output_args:
+        record: preset-record-generic-audio-copy
+      inputs:
+        - path: rtsp://127.0.0.1:8554/http_cam # <--- the name here must match the name of the camera in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - record
+        - path: rtsp://127.0.0.1:8554/http_cam_sub # <--- the name here must match the name of the camera_sub in restream
+          input_args: preset-rtsp-restream
+          roles:
+            - detect
+```
+
+## Advanced Restream Configurations
+
+The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.2.0#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}}`
+
+```yaml
+go2rtc:
+  streams:
+    stream1: exec:ffmpeg -hide_banner -re -stream_loop -1 -i /media/BigBuckBunny.mp4 -c copy -rtsp_transport tcp -f rtsp {{output}}
+```

docs/docs/configuration/rtmp.md

@@ -1,8 +0,0 @@
----
-id: rtmp
-title: RTMP
----
-
-Frigate can re-stream your video feed as a RTMP feed for other applications such as Home Assistant to utilize it at `rtmp://<frigate_host>/live/<camera_name>`. Port 1935 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. The video feed is copied from the original video feed directly to avoid re-encoding. This feed does not include any annotation by Frigate.
-
-Some video feeds are not compatible with RTMP. If you are experiencing issues, check to make sure your camera feed is h264 with AAC audio. If your camera doesn't support a compatible format for RTMP, you can use the ffmpeg args to re-encode it on the fly at the expense of increased CPU utilization. Some more information about it can be found [here](../troubleshooting/faqs.md#audio-in-recordings). 

docs/docs/configuration/zones.md

@@ -11,6 +11,24 @@ During testing, enable the Zones option for the debug feed so you can adjust as
 
 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
+
+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:
+
+```yaml
+camera:
+  record:
+    events:
+      required_zones:
+        - entire_yard
+  snapshots:
+    required_zones:
+      - entire_yard
+  zones:
+    entire_yard:
+      coordinates: ...
+```
+
 ### Restricting zones to specific objects
 
 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.

docs/docs/development/contributing.md

@@ -40,9 +40,11 @@ Fork [blakeblackshear/frigate-hass-integration](https://github.com/blakeblackshe
 
 ### Setup
 
-#### 1. Build the version information and docker container locally by running `make`
+#### 1. Open the repo with Visual Studio Code
 
-#### 2. Create a local config file for testing
+Upon opening, you should be prompted to open the project in a remote container. This will build a container on top of the base Frigate container with all the development dependencies installed. This ensures everyone uses a consistent development environment without the need to install any dependencies on your host machine.
+
+#### 2. Modify your local config file for testing
 
 Place the file at `config/config.yml` in the root of the repo.
 
@@ -60,7 +62,6 @@ cameras:
           input_args: -re -stream_loop -1 -fflags +genpts
           roles:
             - detect
-            - rtmp
     detect:
       height: 1080
       width: 1920
@@ -73,18 +74,14 @@ These input args tell ffmpeg to read the mp4 file in an infinite loop. You can u
 
 Create and place these files in a `debug` folder in the root of the repo. This is also where recordings will be created if you enable them in your test config. Update your config from step 2 above to point at the right file. You can check the `docker-compose.yml` file in the repo to see how the volumes are mapped.
 
-#### 4. Open the repo with Visual Studio Code
-
-Upon opening, you should be prompted to open the project in a remote container. This will build a container on top of the base frigate container with all the development dependencies installed. This ensures everyone uses a consistent development environment without the need to install any dependencies on your host machine.
-
-#### 5. Run frigate from the command line
+#### 4. Run Frigate from the command line
 
 VSCode will start the docker compose file for you and open a terminal window connected to `frigate-dev`.
 
 - Run `python3 -m frigate` to start the backend.
 - In a separate terminal window inside VS Code, change into the `web` directory and run `npm install && npm start` to start the frontend.
 
-#### 6. Teardown
+#### 5. Teardown
 
 After closing VSCode, you may still have containers running. To close everything down, just run `docker-compose down -v` to cleanup all containers.
 
@@ -126,7 +123,7 @@ ffmpeg -c:v h264_qsv -re -stream_loop -1 -i https://streams.videolan.org/ffmpeg/
 
 - [Frigate source code](#frigate-core-web-and-docs)
 - All [core](#core) prerequisites _or_ another running Frigate instance locally available
-- Node.js 14
+- Node.js 16
 
 ### Making changes
 
@@ -169,6 +166,7 @@ npm run lint
 ```
 
 - Add to unit tests and ensure they pass. As much as possible, you should strive to _increase_ test coverage whenever making changes. This will help ensure features do not accidentally become broken in the future.
+- If you run into error messages like "TypeError: Cannot read properties of undefined (reading 'context')" when running tests, this may be due to these issues (https://github.com/vitest-dev/vitest/issues/1910, https://github.com/vitest-dev/vitest/issues/1652) in vitest, but I haven't been able to resolve them.
 
 ```console
 npm run test
@@ -181,7 +179,7 @@ npm run test
 ### Prerequisites
 
 - [Frigate source code](#frigate-core-web-and-docs)
-- Node.js 14
+- Node.js 16
 
 ### Making changes
 
@@ -218,6 +216,5 @@ docker buildx stop builder && docker buildx rm builder # <---- if existing
 docker run --privileged --rm tonistiigi/binfmt --install all
 docker buildx create --name builder --driver docker-container --driver-opt network=host --use
 docker buildx inspect builder --bootstrap
-make build_web
 make push
 ```

docs/docs/frigate/camera_setup.md

@@ -3,7 +3,7 @@ id: camera_setup
 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 far less compatibility. Safari and Edge are the only browsers able to play H.265. 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.
+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.
 
@@ -23,22 +23,14 @@ Larger resolutions **do** improve performance if the objects are very small in t
 
 For the Dahua/Loryta 5442 camera, I use the following settings:
 
-**Main Stream (Recording)**
+**Main Stream (Recording & RTSP)**
 
 - Encode Mode: H.264
 - Resolution: 2688\*1520
 - Frame Rate(FPS): 15
 - I Frame Interval: 30
 
-**Sub Stream 1 (RTMP)**
-
-- Enable: Sub Stream 1
-- Encode Mode: H.264
-- Resolution: 720\*576
-- Frame Rate: 10
-- I Frame Interval: 10
-
-**Sub Stream 2 (Detection)**
+**Sub Stream (Detection)**
 
 - Enable: Sub Stream 2
 - Encode Mode: H.264

docs/docs/frigate/hardware.md

@@ -23,19 +23,19 @@ I may earn a small commission for my endorsement, recommendation, testimonial, o
 
 My current favorite is the Minisforum GK41 because of the dual NICs that allow you to setup a dedicated private network for your cameras where they can be blocked from accessing the internet. There are many used workstation options on eBay that work very well. Anything with an Intel CPU and capable of running Debian should work fine. As a bonus, you may want to look for devices with a M.2 or PCIe express slot that is compatible with the Google Coral. I may earn a small commission for my endorsement, recommendation, testimonial, or link to any products or services from this website.
 
-| Name                                                                                                                                                                                                                                                                                                              | Inference Speed | Coral Compatibility | Notes                                                                                                                                   |
-| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------- | ------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
-| Odyssey X86 Blue J4125 (<a href="https://amzn.to/3oH4BKi" target="_blank" rel="nofollow noopener sponsored">Amazon</a>) (<a href="https://www.seeedstudio.com/Frigate-NVR-with-Odyssey-Blue-and-Coral-USB-Accelerator.html?utm_source=Frigate" target="_blank" rel="nofollow noopener sponsored">SeeedStudio</a>) | 9-10ms          | M.2 B+M, USB        | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
-| Minisforum GK41 (<a href="https://amzn.to/3ptnb8D" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                  | 9-10ms          | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
-| Beelink GK55 (<a href="https://amzn.to/35E79BC" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                     | 9-10ms          | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
-| Intel NUC (<a href="https://amzn.to/3psFlHi" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                        | 8-10ms          | USB                 | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion. Requires extra parts. |
-| BMAX B2 Plus (<a href="https://amzn.to/3a6TBh8" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                     | 10-12ms         | USB                 | Good balance of performance and cost. Also capable of running many other services at the same time as frigate.                          |
-| Atomic Pi (<a href="https://amzn.to/2YjpY9m" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                        | 16ms            | USB                 | Good option for a dedicated low power board with a small number of cameras. Can leverage Intel QuickSync for stream decoding.           |
-| Raspberry Pi 4 (64bit) (<a href="https://amzn.to/2YhSGHH" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                           | 10-15ms         | USB                 | Can handle a small number of cameras.                                                                                                   |
+| Name                                                                                                                                                                                                                                                                                                              | Coral Inference Speed | Coral Compatibility | Notes                                                                                                                                   |
+| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------- | ------------------- | --------------------------------------------------------------------------------------------------------------------------------------- |
+| Odyssey X86 Blue J4125 (<a href="https://amzn.to/3oH4BKi" target="_blank" rel="nofollow noopener sponsored">Amazon</a>) (<a href="https://www.seeedstudio.com/Frigate-NVR-with-Odyssey-Blue-and-Coral-USB-Accelerator.html?utm_source=Frigate" target="_blank" rel="nofollow noopener sponsored">SeeedStudio</a>) | 9-10ms                | M.2 B+M, USB        | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
+| Minisforum GK41 (<a href="https://amzn.to/3ptnb8D" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                  | 9-10ms                | USB                 | Dual gigabit NICs for easy isolated camera network. Easily handles several 1080p cameras.                                               |
+| Intel NUC (<a href="https://amzn.to/3psFlHi" target="_blank" rel="nofollow noopener sponsored">Amazon</a>)                                                                                                                                                                                                        | 8-10ms                | USB                 | Overkill for most, but great performance. Can handle many cameras at 5fps depending on typical amounts of motion. Requires extra parts. |
 
-## Google Coral TPU
+## Detectors
 
-It is strongly recommended to use a Google Coral. Frigate is designed around the expectation that a Coral is used to achieve very low inference speeds. Offloading TensorFlow to the Google Coral is an order of magnitude faster and will reduce your CPU load dramatically. A $60 device will outperform $2000 CPU. Frigate should work with any supported Coral device from https://coral.ai
+A detector is a device which is optimized for running inferences efficiently to detect objects. Using a recommended detector means there will be less latency between detections and more detections can be run per second. Frigate is designed around the epectation that a detector is used to achieve very low inference speeds. Offloading TensorFlow to a detector is an order of magnitude faster and will reduce your CPU load dramatically. As of 0.12, Frigate supports a handful of different detector types with varying inference speeds and performance.
+
+### Google Coral TPU
+
+It is strongly recommended to use a Google Coral. A $60 device will outperform $2000 CPU. Frigate should work with any supported Coral device from https://coral.ai
 
 The USB version is compatible with the widest variety of hardware and does not require a driver on the host machine. However, it does lack the automatic throttling features of the other versions.
 
@@ -43,7 +43,51 @@ The PCIe and M.2 versions require installation of a driver on the host. Follow t
 
 A single Coral can handle many cameras and will be sufficient for the majority of users. You can calculate the maximum performance of your Coral based on the inference speed reported by Frigate. With an inference speed of 10, your Coral will top out at `1000/10=100`, or 100 frames per second. If your detection fps is regularly getting close to that, you should first consider tuning motion masks. If those are already properly configured, a second Coral may be needed.
 
-### What does Frigate use the CPU for and what does it use the Coral for? (ELI5 Version)
+### OpenVino
+
+The OpenVINO detector type is able to run on:
+
+- 6th Gen Intel Platforms and newer that have an iGPU
+- x86 & Arm32/64 hosts with VPU Hardware (ex: Intel NCS2)
+
+More information is available [in the detector docs](/configuration/detectors#openvino-detector)
+
+Inference speeds vary greatly depending on the CPU, GPU, or VPU used, some known examples are below:
+
+| Name                 | Inference Speed | Notes                                                                 |
+| -------------------- | --------------- | --------------------------------------------------------------------- |
+| Intel NCS2 VPU       | 60 - 65 ms      | May vary based on host device                                         |
+| Intel Celeron J4105  | ~ 25 ms         | Inference speeds on CPU were 150 - 200 ms                             |
+| Intel Celeron N3060  | 130 - 150 ms    | Inference speeds on CPU were ~ 550 ms                                 |
+| Intel Celeron N3205U | ~ 120 ms        | Inference speeds on CPU were ~ 380 ms                                 |
+| Intel Celeron N4020  | 50 - 200 ms     | Inference speeds on CPU were ~ 800 ms, greatly depends on other loads |
+| Intel i3 6100T       | 15 - 35 ms      | Inference speeds on CPU were 60 - 120 ms                              |
+| Intel i3 8100        | ~ 15 ms         | Inference speeds on CPU were ~ 65 ms                                  |
+| Intel i5 4590        | ~ 20 ms         | Inference speeds on CPU were ~ 230 ms                                 |
+| Intel i5 6500        | ~ 15 ms         | Inference speeds on CPU were ~ 150 ms                                 |
+| Intel i5 7200u       | 15 - 25 ms      | Inference speeds on CPU were ~ 150 ms                                 |
+| Intel i5 7500        | ~ 15 ms         | Inference speeds on CPU were ~ 260 ms                                 |
+| Intel i5 1135G7      | 10 - 15 ms      |                                                                       |
+| Intel i5 12600K      | ~ 15 ms         | Inference speeds on CPU were ~ 35 ms                                  |
+
+### TensorRT
+
+The TensortRT detector is able to run on x86 hosts that have an Nvidia GPU which supports the 11.x series of CUDA libraries. The minimum driver version on the host system must be `>=450.80.02`. Also the GPU must support a Compute Capability of `5.0` or greater. This generally correlates to a Maxwell-era GPU or newer, check the [TensorRT docs for more info](/configuration/detectors#nvidia-tensorrt-detector).
+
+Inference speeds will vary greatly depending on the GPU and the model used.
+`tiny` variants are faster than the equivalent non-tiny model, some known examples are below:
+
+| Name            | Inference Speed |
+| --------------- | --------------- |
+| GTX 1060 6GB    | ~ 7 ms          |
+| GTX 1070        | ~ 6 ms          |
+| GTX 1660 SUPER  | ~ 4 ms          |
+| RTX 3050        | 5 - 7 ms        |
+| RTX 3070 Mobile | ~ 5 ms          |
+| Quadro P400 2GB | 20 - 25 ms      |
+| Quadro P2000    | ~ 12 ms         |
+
+## What does Frigate use the CPU for and what does it use a detector for? (ELI5 Version)
 
 This is taken from a [user question on reddit](https://www.reddit.com/r/homeassistant/comments/q8mgau/comment/hgqbxh5/?utm_source=share&utm_medium=web2x&context=3). Modified slightly for clarity.
 
@@ -59,7 +103,7 @@ However we realize that there is a problem. There is still booby poop all over t
 
 Basically - When you increase the resolution and/or the frame rate of the stream there is now significantly more data for the CPU to parse. That takes additional computing power. The Google Coral is really good at doing object detection, but it doesn't have time to look everywhere all the time (especially when there are many windows to check). To balance it, Frigate uses the CPU to look for movement, then sends those frames to the Coral to do object detection. This allows the Coral to be available to a large number of cameras and not overload it.
 
-### Do hwaccel args help if I am using a Coral?
+## Do hwaccel args help if I am using a Coral?
 
 YES! The Coral does not help with decoding video streams.
 

docs/docs/frigate/index.md

@@ -15,7 +15,7 @@ Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but
 - Object detection with TensorFlow runs in separate processes for maximum FPS
 - Communicates over MQTT for easy integration into other systems
 - Recording with retention based on detected objects
-- Re-streaming via RTMP to reduce the number of connections to your camera
+- Re-streaming via RTSP to reduce the number of connections to your camera
 - A dynamic combined camera view of all tracked cameras.
 
 ## Screenshots

docs/docs/frigate/installation.md

@@ -3,11 +3,11 @@ id: installation
 title: Installation
 ---
 
-Frigate is a Docker container that can be run on any Docker host including as a [HassOS Addon](https://www.home-assistant.io/addons/). Note that a Home Assistant Addon is **not** the same thing as the integration. The [integration](integrations/home-assistant) is required to integrate Frigate into Home Assistant.
+Frigate is a Docker container that can be run on any Docker host including as a [HassOS Addon](https://www.home-assistant.io/addons/). Note that a Home Assistant Addon is **not** the same thing as the integration. The [integration](/integrations/home-assistant) is required to integrate Frigate into Home Assistant.
 
 ## Dependencies
 
-**MQTT broker** - Frigate requires an MQTT broker. If using Home Assistant, Frigate and Home Assistant must be connected to the same MQTT broker.
+**MQTT broker (optional)** - An MQTT broker is optional with Frigate, but is required for the Home Assistant integration. If using Home Assistant, Frigate and Home Assistant must be connected to the same MQTT broker.
 
 ## Preparing your hardware
 
@@ -21,15 +21,9 @@ Windows is not officially supported, but some users have had success getting it
 
 Frigate uses the following locations for read/write operations in the container. Docker volume mappings can be used to map these to any location on your host machine.
 
-:::caution
-
-Note that Frigate does not currently support limiting recordings based on available disk space automatically. If using recordings, you must specify retention settings for a number of days that will fit within the available disk space of your drive or Frigate will crash.
-
-:::
-
 - `/media/frigate/clips`: Used for snapshot storage. In the future, it will likely be renamed from `clips` to `snapshots`. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
 - `/media/frigate/recordings`: Internal system storage for recording segments. The file structure here cannot be modified and isn't intended to be browsed or managed manually.
-- `/media/frigate/frigate.db`: Default location for the sqlite database. You will also see several files alongside this file while frigate is running. If moving the database location (often needed when using a network drive at `/media/frigate`), it is recommended to mount a volume with docker at `/db` and change the storage location of the database to `/db/frigate.db` in the config file.
+- `/media/frigate/frigate.db`: Default location for the sqlite database. You will also see several files alongside this file while Frigate is running. If moving the database location (often needed when using a network drive at `/media/frigate`), it is recommended to mount a volume with docker at `/db` and change the storage location of the database to `/db/frigate.db` in the config file.
 - `/tmp/cache`: Cache location for recording segments. Initial recordings are written here before being checked and converted to mp4 and moved to the recordings folder.
 - `/dev/shm`: It is not recommended to modify this directory or map it with docker. This is the location for raw decoded frames in shared memory and it's size is impacted by the `shm-size` calculations below.
 - `/config/config.yml`: Default location of the config file.
@@ -44,7 +38,7 @@ services:
   frigate:
     ...
     volumes:
-      - /path/to/your/config.yml:/config/config.yml:ro
+      - /path/to/your/config.yml:/config/config.yml
       - /path/to/your/storage:/media/frigate
       - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
         target: /tmp/cache
@@ -61,7 +55,7 @@ services:
   frigate:
     ...
     volumes:
-      - /path/to/your/config.yml:/config/config.yml:ro
+      - /path/to/your/config.yml:/config/config.yml
       - /path/to/network/storage:/media/frigate
       - /path/to/local/disk:/db
       - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
@@ -80,17 +74,29 @@ database:
 
 ### Calculating required shm-size
 
-Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is 64m.
+Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is **64MB**.
 
-The default shm-size of 64m is fine for setups with 2 or less 1080p cameras. If frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size.
+The default shm size of **64MB** is fine for setups with **2 cameras** detecting at **720p**. If Frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size.
 
-You can calculate the necessary shm-size for each camera with the following formula using the resolution specified for detect:
+The Frigate container also stores logs in shm, which can take up to **30MB**, so make sure to take this into account in your math as well.
 
-```
-(width * height * 1.5 * 9 + 270480)/1048576 = <shm size in mb>
+You can calculate the necessary shm size for each camera with the following formula using the resolution specified for detect:
+
+```console
+# Replace <width> and <height>
+$ python -c 'print("{:.2f}MB".format((<width> * <height> * 1.5 * 9 + 270480) / 1048576))'
+
+# Example for 1280x720
+$ python -c 'print("{:.2f}MB".format((1280 * 720 * 1.5 * 9 + 270480) / 1048576))'
+12.12MB
+
+# Example for eight cameras detecting at 1280x720, including logs
+$ python -c 'print("{:.2f}MB".format(((1280 * 720 * 1.5 * 9 + 270480) / 1048576) * 8 + 30))'
+126.99MB
 ```
 
-The shm size cannot be set per container for Home Assistant Addons. You must set `default-shm-size` in `/etc/docker/daemon.json` to increase the default shm size. This will increase the shm size for all of your docker containers. This may or may not cause issues with your setup. https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file
+The shm size cannot be set per container for Home Assistant add-ons. However, this is probably not required since by default Home Assistant Supervisor allocates `/dev/shm` with half the size of your total memory. If your machine has 8GB of memory, chances are that Frigate will have access to up to 4GB without any additional configuration.
+
 
 ### Raspberry Pi 3/4
 
@@ -109,7 +115,7 @@ services:
     container_name: frigate
     privileged: true # this may not be necessary for all setups
     restart: unless-stopped
-    image: blakeblackshear/frigate:stable
+    image: ghcr.io/blakeblackshear/frigate:stable
     shm_size: "64mb" # update for your cameras based on calculation above
     devices:
       - /dev/bus/usb:/dev/bus/usb # passes the USB Coral, needs to be modified for other versions
@@ -117,7 +123,7 @@ services:
       - /dev/dri/renderD128 # for intel hwaccel, needs to be updated for your hardware
     volumes:
       - /etc/localtime:/etc/localtime:ro
-      - /path/to/your/config.yml:/config/config.yml:ro
+      - /path/to/your/config.yml:/config/config.yml
       - /path/to/your/storage:/media/frigate
       - type: tmpfs # Optional: 1GB of memory, reduces SSD/SD Card wear
         target: /tmp/cache
@@ -125,7 +131,9 @@ services:
           size: 1000000000
     ports:
       - "5000:5000"
-      - "1935:1935" # RTMP feeds
+      - "8554:8554" # RTSP feeds
+      - "8555:8555/tcp" # WebRTC over tcp
+      - "8555:8555/udp" # WebRTC over udp
     environment:
       FRIGATE_RTSP_PASSWORD: "password"
 ```
@@ -141,19 +149,24 @@ docker run -d \
   --device /dev/dri/renderD128 \
   --shm-size=64m \
   -v /path/to/your/storage:/media/frigate \
-  -v /path/to/your/config.yml:/config/config.yml:ro \
+  -v /path/to/your/config.yml:/config/config.yml \
   -v /etc/localtime:/etc/localtime:ro \
   -e FRIGATE_RTSP_PASSWORD='password' \
   -p 5000:5000 \
-  -p 1935:1935 \
-  blakeblackshear/frigate:stable
+  -p 8554:8554 \
+  -p 8555:8555/tcp \
+  -p 8555:8555/udp \
+  ghcr.io/blakeblackshear/frigate:stable
 ```
 
 ## Home Assistant Operating System (HassOS)
 
 :::caution
 
-Due to limitations in Home Assistant Operating System, utilizing external storage for recordings or snapshots requires [modifying udev rules manually](https://community.home-assistant.io/t/solved-mount-usb-drive-in-hassio-to-be-used-on-the-media-folder-with-udev-customization/258406/46).
+There are important limitations in Home Assistant Operating System to be aware of:
+- Utilizing external storage for recordings or snapshots requires [modifying udev rules manually](https://community.home-assistant.io/t/solved-mount-usb-drive-in-hassio-to-be-used-on-the-media-folder-with-udev-customization/258406/46).
+- AMD GPUs are not supported because HA OS does not include the mesa driver.
+- Nvidia GPUs are not supported because addons do not support the nvidia runtime.
 
 :::
 
@@ -184,6 +197,13 @@ There are several versions of the addon available:
 
 ## Home Assistant Supervised
 
+:::caution
+
+There are important limitations in Home Assistant Supervised to be aware of:
+- Nvidia GPUs are not supported because addons do not support the nvidia runtime.
+
+:::
+
 :::tip
 
 If possible, it is recommended to run Frigate standalone in Docker and use [Frigate's Proxy Addon](https://github.com/blakeblackshear/frigate-hass-addons/blob/main/frigate_proxy/README.md).

docs/docs/guides/configuring_go2rtc.md

@@ -0,0 +1,77 @@
+---
+id: configuring_go2rtc
+title: Configuring go2rtc
+---
+
+Use of the bundled go2rtc is optional. You can still configure FFmpeg to connect directly to your cameras. However, adding go2rtc to your configuration is required for the following features:
+
+- WebRTC or MSE for live viewing with higher resolutions and frame rates than the jsmpeg stream which is limited to the detect stream
+- RTSP (instead of RTMP) relay for use with Home Assistant or other consumers to reduce the number of connections to your camera streams
+
+# Setup a go2rtc stream
+
+First, you will want to configure go2rtc to connect to your camera stream by adding the stream you want to use for live view in your Frigate config file. If you set the stream name under go2rtc to match the name of your camera, it will automatically be mapped and you will get additional live view options for the camera. Avoid changing any other parts of your config at this step. Note that go2rtc supports [many different stream types](https://github.com/AlexxIT/go2rtc/tree/v1.2.0#module-streams), not just rtsp.
+
+```yaml
+go2rtc:
+  streams:
+    back:
+      - rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
+```
+
+The easiest live view to get working is MSE. After adding this to the config, restart Frigate and try to watch the live stream by selecting MSE in the dropdown after clicking on the camera.
+
+### What if my video doesn't play?
+
+If you are unable to see your video feed, first check the go2rtc logs in the Frigate UI under Logs in the sidebar. If go2rtc is having difficulty connecting to your camera, you should see some error messages in the log. If you do not see any errors, then the video codec of the stream may not be supported in your browser. If your camera stream is set to H265, try switching to H264. You can see more information about [video codec compatibility](https://github.com/AlexxIT/go2rtc/tree/v1.2.0#codecs-madness) in the go2rtc documentation. If you are not able to switch your camera settings from H265 to H264 or your stream is a different format such as MJPEG, you can use go2rtc to re-encode the video using the [FFmpeg parameters](https://github.com/AlexxIT/go2rtc/tree/v1.2.0#source-ffmpeg). It supports rotating and resizing video feeds and hardware acceleration. Keep in mind that transcoding video from one format to another is a resource intensive task and you may be better off using the built-in jsmpeg view. Here is an example of a config that will re-encode the stream to H264 without hardware acceleration:
+
+```yaml
+go2rtc:
+  streams:
+    back:
+      - rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
+      - "ffmpeg:back#video=h264"
+```
+
+Some camera streams may need to use the ffmpeg module in go2rtc. This has the downside of slower startup times, but has compatibility with more stream types.
+
+```yaml
+go2rtc:
+  streams:
+    back:
+      - ffmpeg:rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
+```
+
+If you can see the video but do not have audio, this is most likely because your camera's audio stream is not AAC. If possible, update your camera's audio settings to AAC. If your cameras do not support AAC audio, you will need to tell go2rtc to re-encode the audio to AAC on demand if you want audio. This will use additional CPU and add some latency. To add AAC audio on demand, you can update your go2rtc config as follows:
+
+```yaml
+go2rtc:
+  streams:
+    back:
+      - rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
+      - "ffmpeg:back#audio=aac"
+```
+
+If you need to convert **both** the audio and video streams, you can use the following:
+
+```yaml
+go2rtc:
+  streams:
+    back:
+      - rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
+      - "ffmpeg:back#video=h264#audio=aac"
+```
+
+When using the ffmpeg module, you would add AAC audio like this:
+
+```yaml
+go2rtc:
+  streams:
+    back:
+      - "ffmpeg:rtsp://user:password@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2#video=copy#audio=copy#audio=aac"
+```
+
+## Next steps
+
+1. If the stream you added to go2rtc is also used by Frigate for the `record` or `detect` role, you can migrate your config to pull from the RTSP restream to reduce the number of connections to your camera as shown [here](/configuration/restream#reduce-connections-to-camera).
+1. You may also prefer to [setup WebRTC](/configuration/live#webrtc-extra-configuration) for slightly lower latency than MSE. Note that WebRTC only supports h264 and specific audio formats.

docs/docs/guides/events_setup.md

@@ -1,10 +0,0 @@
----
-id: events_setup
-title: Setting Up Events
----
-
-[Snapshots](../configuration/snapshots.md) and/or [Recordings](../configuration/record.md) must be enabled for events to be created for detected objects.
-
-## Limiting Events to Areas of Interest
-
-The best way to limit events to areas of interest is to use [zones](../configuration/zones.md) along with `required_zones` for events and snapshots to only have events created in areas of interest.

docs/docs/guides/false_positives.md

@@ -20,4 +20,4 @@ For object filters in your configuration, any single detection below `min_score`
 | 5     | 0.88          | 0.7, 0.85, 0.95, 0.90, 0.88       | 0.88           | Yes             |
 | 6     | 0.95          | 0.7, 0.85, 0.95, 0.90, 0.88, 0.95 | 0.89           | Yes             |
 
-In frame 2, the score is below the `min_score` value, so frigate ignores it and it becomes a 0.0. The computed score is the median of the score history (padding to at least 3 values), and only when that computed score crosses the `threshold` is the object marked as a true positive. That happens in frame 4 in the example.
+In frame 2, the score is below the `min_score` value, so Frigate ignores it and it becomes a 0.0. The computed score is the median of the score history (padding to at least 3 values), and only when that computed score crosses the `threshold` is the object marked as a true positive. That happens in frame 4 in the example.

docs/docs/guides/getting_started.md

@@ -1,123 +1,81 @@
 ---
 id: getting_started
-title: Creating a config file
+title: Getting started
 ---
 
-This guide walks through the steps to build a configuration file for Frigate. It assumes that you already have an environment setup as described in [Installation](../frigate/installation.md). You should also configure your cameras according to the [camera setup guide](/guides/camera_setup)
+This guide walks through the steps to build a configuration file for Frigate. It assumes that you already have an environment setup as described in [Installation](../frigate/installation.md). You should also configure your cameras according to the [camera setup guide](/frigate/camera_setup). Pay particular attention to the section on choosing a detect resolution.
 
-### Step 1: Configure the MQTT server
+### Step 1: Add a detect stream
 
-Frigate requires a functioning MQTT server. Start by adding the mqtt section at the top level in your config:
+First we will add the detect stream for the camera:
 
 ```yaml
 mqtt:
-  host: <ip of your mqtt server>
-```
-
-If using the Mosquitto Addon in Home Assistant, a username and password is required. For example:
-
-```yaml
-mqtt:
-  host: <ip of your mqtt server>
-  user: <username>
-  password: <password>
-```
-
-Frigate supports many configuration options for mqtt. See the [configuration reference](../configuration/index.md#full-configuration-reference) for more info.
-
-### Step 2: Configure detectors
-
-By default, Frigate will use a single CPU detector. If you have a USB Coral, you will need to add a detectors section to your config.
-
-```yaml
-mqtt:
-  host: <ip of your mqtt server>
-
-detectors:
-  coral:
-    type: edgetpu
-    device: usb
-```
-
-More details on available detectors can be found [here](../configuration/detectors.md).
-
-### Step 3: Add a minimal camera configuration
-
-Now let's add the first camera:
-
-:::caution
-
-Note that passwords that contain special characters often cause issues with ffmpeg connecting to the camera. If receiving `end-of-file` or `unauthorized` errors with a verified correct password, try changing the password to something simple to rule out the possibility that the password is the issue.
-
-:::
-
-```yaml
-mqtt:
-  host: <ip of your mqtt server>
-
-detectors:
-  coral:
-    type: edgetpu
-    device: usb
+  enabled: False
 
 cameras:
   camera_1: # <------ Name the camera
     ffmpeg:
       inputs:
-        - path: rtsp://10.0.10.10:554/rtsp # <----- Update for your camera
+        - path: rtsp://10.0.10.10:554/rtsp # <----- The stream you want to use for detection
           roles:
             - detect
-            - rtmp
-    rtmp:
-      enabled: False # <-- RTMP should be disabled if your stream is not H264
     detect:
+      enabled: False # <---- disable detection until you have a working camera feed
       width: 1280 # <---- update for your camera's resolution
       height: 720 # <---- update for your camera's resolution
 ```
 
-### Step 4: Start Frigate
+### Step 2: Start Frigate
 
 At this point you should be able to start Frigate and see the the video feed in the UI.
 
-If you get a green image from the camera, this means ffmpeg was not able to get the video feed from your camera. Check the logs for error messages from ffmpeg. The default ffmpeg arguments are designed to work with H264 RTSP cameras that support TCP connections. If you do not have H264 cameras, make sure you have disabled RTMP. It is possible to enable it, but you must tell ffmpeg to re-encode the video with customized output args.
+If you get an error image from the camera, this means ffmpeg was not able to get the video feed from your camera. Check the logs for error messages from ffmpeg. The default ffmpeg arguments are designed to work with H264 RTSP cameras that support TCP connections.
 
 FFmpeg arguments for other types of cameras can be found [here](../configuration/camera_specific.md).
 
-### Step 5: Configure hardware acceleration (optional)
+### Step 3: Configure hardware acceleration (recommended)
 
 Now that you have a working camera configuration, you want to setup hardware acceleration to minimize the CPU required to decode your video streams. See the [hardware acceleration](../configuration/hardware_acceleration.md) config reference for examples applicable to your hardware.
 
-In order to best evaluate the performance impact of hardware acceleration, it is recommended to temporarily disable detection.
+Here is an example configuration with hardware acceleration configured for Intel processors with an integrated GPU using the [preset](../configuration/ffmpeg_presets.md):
 
 ```yaml
 mqtt: ...
 
-detectors: ...
-
-cameras:
-  camera_1:
-    ffmpeg: ...
-    detect:
-      enabled: False
-      ...
-```
-
-Here is an example configuration with hardware acceleration configured:
-
-```yaml
-mqtt: ...
-
-detectors: ...
-
 cameras:
   camera_1:
     ffmpeg:
       inputs: ...
-      hwaccel_args: -c:v h264_v4l2m2m
+      hwaccel_args: preset-vaapi
     detect: ...
 ```
 
-### Step 6: Setup motion masks
+### Step 4: Configure detectors
+
+By default, Frigate will use a single CPU detector. If you have a USB Coral, you will need to add a detectors section to your config.
+
+```yaml
+mqtt: ...
+
+detectors: # <---- add detectors
+  coral:
+    type: edgetpu
+    device: usb
+
+cameras:
+  camera_1:
+    ffmpeg: ...
+    detect:
+      enabled: True # <---- turn on detection
+      ...
+```
+
+More details on available detectors can be found [here](../configuration/detectors.md).
+
+Restart Frigate and you should start seeing detections for `person`. If you want to track other objects, they will need to be added according to the [configuration file reference](../configuration/index.md#full-configuration-reference).
+
+### Step 5: Setup motion masks
 
 Now that you have optimized your configuration for decoding the video stream, you will want to check to see where to implement motion masks. To do this, navigate to the camera in the UI, select "Debug" at the top, and enable "Motion boxes" in the options below the video feed. Watch for areas that continuously trigger unwanted motion to be detected. Common areas to mask include camera timestamps and trees that frequently blow in the wind. The goal is to avoid wasting object detection cycles looking at these areas.
 
@@ -133,7 +91,7 @@ Your configuration should look similar to this now.
 
 ```yaml
 mqtt:
-  host: mqtt.local
+  enabled: False
 
 detectors:
   coral:
@@ -147,7 +105,6 @@ cameras:
         - path: rtsp://10.0.10.10:554/rtsp
           roles:
             - detect
-            - rtmp
     detect:
       width: 1280
       height: 720
@@ -156,9 +113,13 @@ cameras:
         - 0,461,3,0,1919,0,1919,843,1699,492,1344,458,1346,336,973,317,869,375,866,432
 ```
 
-### Step 7: Enable recording (optional)
+### Step 6: Enable recording and/or snapshots
 
-To enable recording video, add the `record` role to a stream and enable it in the config.
+In order to see Events in the Frigate UI, either snapshots or record will need to be enabled.
+
+#### Record
+
+To enable recording video, add the `record` role to a stream and enable it in the config. If record is disabled in the config, turning it on via the UI will not have any effect.
 
 ```yaml
 mqtt: ...
@@ -172,8 +133,7 @@ cameras:
         - path: rtsp://10.0.10.10:554/rtsp
           roles:
             - detect
-            - rtmp
-        - path: rtsp://10.0.10.10:554/high_res_stream # <----- Add high res stream
+        - path: rtsp://10.0.10.10:554/high_res_stream # <----- Add stream you want to record from
           roles:
             - record
     detect: ...
@@ -186,9 +146,9 @@ If you don't have separate streams for detect and record, you would just add the
 
 By default, Frigate will retain video of all events for 10 days. The full set of options for recording can be found [here](../configuration/index.md#full-configuration-reference).
 
-### Step 8: Enable snapshots (optional)
+#### Snapshots
 
-To enable snapshots of your events, just enable it in the config.
+To enable snapshots of your events, just enable it in the config. Snapshots are taken from the detect stream because it is the only stream decoded.
 
 ```yaml
 mqtt: ...
@@ -205,3 +165,10 @@ cameras:
 ```
 
 By default, Frigate will retain snapshots of all events for 10 days. The full set of options for snapshots can be found [here](../configuration/index.md#full-configuration-reference).
+
+### Step 7: Follow up guides
+
+Now that you have a working install, you can use the following guides for additional features:
+
+1. [Configuring go2rtc](configuring_go2rtc) - Additional live view options and RTSP relay
+2. [Home Assistant Integration](../integrations/home-assistant.md) - Integrate with Home Assistant

docs/docs/guides/ha_notifications.md

@@ -7,7 +7,7 @@ The best way to get started with notifications for Frigate is to use the [Bluepr
 
 It is generally recommended to trigger notifications based on the `frigate/events` mqtt topic. This provides the event_id needed to fetch [thumbnails/snapshots/clips](../integrations/home-assistant.md#notification-api) and other useful information to customize when and where you want to receive alerts. The data is published in the form of a change feed, which means you can reference the "previous state" of the object in the `before` section and the "current state" of the object in the `after` section. You can see an example [here](../integrations/mqtt.md#frigateevents).
 
-Here is a simple example of a notification automation of events which will update the existing notification for each change. This means the image you see in the notification will update as frigate finds a "better" image.
+Here is a simple example of a notification automation of events which will update the existing notification for each change. This means the image you see in the notification will update as Frigate finds a "better" image.
 
 ```yaml
 automation:

docs/docs/guides/reverse_proxy.md

@@ -1,6 +1,6 @@
 ---
 id: reverse_proxy
-title: Setting up a Reverse Proxy
+title: Setting up a reverse proxy
 ---
 
 This guide outlines the basic configuration steps needed to expose your Frigate UI to the internet.
@@ -8,6 +8,7 @@ A common way of accomplishing this is to use a reverse proxy webserver between y
 A reverse proxy accepts HTTP requests from the public internet and redirects them transparently to internal webserver(s) on your network.
 
 The suggested steps are:
+
 - **Configure** a 'proxy' HTTP webserver (such as [Apache2](https://httpd.apache.org/docs/current/) or [NPM](https://github.com/NginxProxyManager/nginx-proxy-manager)) and only expose ports 80/443 from this webserver to the internet
 - **Encrypt** content from the proxy webserver by installing SSL (such as with [Let's Encrypt](https://letsencrypt.org/)). Note that SSL is then not required on your Frigate webserver as the proxy encrypts all requests for you
 - **Restrict** access to your Frigate instance at the proxy using, for example, password authentication
@@ -31,6 +32,7 @@ On Debian Apache2 the configuration file will be named along the lines of `/etc/
 
 Make life easier for yourself by presenting your Frigate interface as a DNS sub-domain rather than as a sub-folder of your main domain.
 Here we access Frigate via https://cctv.mydomain.co.uk
+
 ```xml
 <VirtualHost *:443>
     ServerName cctv.mydomain.co.uk
@@ -38,7 +40,7 @@ Here we access Frigate via https://cctv.mydomain.co.uk
     ProxyPreserveHost On
     ProxyPass "/"  "http://frigatepi.local:5000/"
     ProxyPassReverse "/"  "http://frigatepi.local:5000/"
-    
+
     ProxyPass /ws ws://frigatepi.local:5000/ws
     ProxyPassReverse /ws ws://frigatepi.local:5000/ws