update network requirements docs

.github/actions/setup/action.yml

@@ -17,14 +17,9 @@ runs:
       shell: bash
     # This creates a virtual volume at /var/lib/docker to maximize the size
     # As of 2/14/2024, this results in 97G for docker images
-    # Runners no longer have a separate /mnt disk, so the temp PV is also carved
-    # from root and temp-reserve-mb is what actually stays free on root. Keep 4G
-    # there for setup-qemu/buildx caches in ~/.docker and the tool cache
     - name: Maximize build space
       uses: easimon/maximize-build-space@master
       with:
-        root-reserve-mb: 8192
-        temp-reserve-mb: 4096
         remove-dotnet: 'true'
         remove-android: 'true'
         remove-haskell: 'true'
@@ -34,15 +29,15 @@ runs:
       run: sudo systemctl start docker
       shell: bash
     - id: lowercaseRepo
-      uses: ASzc/change-string-case-action@v8
+      uses: ASzc/change-string-case-action@v5
       with:
         string: ${{ github.repository }}
     - name: Set up QEMU
-      uses: docker/setup-qemu-action@v4
+      uses: docker/setup-qemu-action@v3
     - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v4
+      uses: docker/setup-buildx-action@v3
     - name: Log in to the Container registry
-      uses: docker/login-action@dbcb813823bdd20940b903addbd779551569679f
+      uses: docker/login-action@465a07811f14bebb1938fbed4728c6a1ff8901fc
       with:
         registry: ghcr.io
         username: ${{ github.actor }}

.github/dependabot.yml

@@ -1,157 +1,40 @@
 version: 2
 updates:
   - package-ecosystem: "github-actions"
-    # Local composite actions are only scanned when their directory is listed
-    directories:
-      - "/"
-      - "/.github/actions/setup"
+    directory: "/"
     schedule:
-      interval: weekly
-    cooldown:
-      default-days: 3
-    open-pull-requests-limit: 5
-    groups:
-      actions:
-        patterns: ["*"]
-      actions-security:
-        applies-to: security-updates
-        patterns: ["*"]
-
+      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: "/docker/main"
     schedule:
-      interval: weekly
-    cooldown:
-      default-days: 3
-    open-pull-requests-limit: 5
-    groups:
-      # Sets that fail pip resolution unless they move together
-      peewee:
-        patterns: ["peewee", "peewee-migrate"]
-      crypto:
-        patterns: ["cryptography", "joserfc", "pywebpush", "py-vapid"]
-      pydantic-genai:
-        patterns: ["pydantic", "google-genai"]
-      pip-main-minor-patch:
-        patterns: ["*"]
-        update-types: ["minor", "patch"]
-      pip-main-security:
-        applies-to: security-updates
-        patterns: ["*"]
-    ignore:
-      # numpy 2.5 needs Python 3.12; norfair, tflite_runtime and rknn-toolkit2
-      # cap numpy below 2
-      - dependency-name: "numpy"
-        versions: [">=2"]
-      # Every OpenCV wheel from 4.12 requires numpy 2
-      - dependency-name: "opencv-python-headless"
-        versions: [">=4.12"]
-      - dependency-name: "opencv-contrib-python"
-        versions: [">=4.12"]
-      # aarch64 only. Rockchip rknn-toolkit2 caps protobuf at 4.25.4 and
-      # TensorFlow 2.21 needs protobuf 6.31 or newer.
-      - dependency-name: "tensorflow"
-        versions: [">=2.20"]
-      # Needs Python 3.12 and numpy 2
-      - dependency-name: "librosa"
-        versions: [">=1.0"]
-      # Needs Python 3.12
-      - dependency-name: "scipy"
-        versions: [">=1.18"]
-      # Newer stubs report false errors against peewee 4
-      - dependency-name: "types-peewee"
-        versions: [">=4.1"]
-      # sdist only and imported by HailoRT; needs a Hailo device to test
-      - dependency-name: "netifaces"
-        versions: [">=0.11"]
-
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
   - package-ecosystem: "pip"
     directory: "/docker/tensorrt"
     schedule:
-      interval: weekly
-    # No pull request check builds these images, so version updates are off.
-    # Security updates still open.
-    open-pull-requests-limit: 0
-    groups:
-      pip-trt-security:
-        applies-to: security-updates
-        patterns: ["*"]
-    ignore:
-      # onnx 1.17 and newer write a newer IR and opset than TensorRT 8.6 on
-      # JetPack 6 is known to parse
-      - dependency-name: "onnx"
-        versions: [">=1.17"]
-      # 1.27 moved to CUDA 13, and the image ships the CUDA 12.8 wheel set
-      - dependency-name: "onnxruntime-gpu"
-        versions: [">=1.27"]
-      # Hand-matched CUDA 12.8 set (2c9a25e67); move as a block
-      - dependency-name: "nvidia-*"
-      # Must match the JetPack CUDA runtime
-      - dependency-name: "cuda-python"
-        versions: [">=12.9"]
-
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
   - package-ecosystem: "npm"
     directory: "/web"
     schedule:
-      interval: weekly
-    cooldown:
-      default-days: 3
-    open-pull-requests-limit: 5
-    groups:
-      radix:
-        patterns: ["@radix-ui/*"]
-      rjsf:
-        patterns: ["@rjsf/*"]
-      web-minor-patch:
-        patterns: ["*"]
-        update-types: ["minor", "patch"]
-      web-security:
-        applies-to: security-updates
-        patterns: ["*"]
-    ignore:
-      # typescript-eslint peers typescript below 6.1
-      - dependency-name: "typescript"
-        versions: [">=6.1"]
-      # Tailwind 4 is a config rewrite; scrollbar 4 and merge 3 depend on it
-      - dependency-name: "tailwindcss"
-        update-types: ["version-update:semver-major"]
-      - dependency-name: "tailwind-scrollbar"
-        update-types: ["version-update:semver-major"]
-      - dependency-name: "tailwind-merge"
-        update-types: ["version-update:semver-major"]
-      # Intermittent failure in the UI settings import spec, cause not found
-      - dependency-name: "zod"
-        update-types: ["version-update:semver-major"]
-      # Needs an on-device pinch test before moving
-      - dependency-name: "react-zoom-pan-pinch"
-        update-types: ["version-update:semver-major"]
-      # Build fails until monaco-worker-manager releases its PR 4
-      - dependency-name: "monaco-editor"
-        versions: [">=0.55.0"]
-      # Later versions need Node 22 and extract false keys
-      - dependency-name: "i18next-cli"
-        versions: [">1.5.11"]
-      # 6.11.0 refills the saved model in the GenAI settings form
-      - dependency-name: "@rjsf/*"
-        versions: ["6.11.0"]
-
+      interval: daily
+    open-pull-requests-limit: 10
+    target-branch: dev
   - package-ecosystem: "npm"
     directory: "/docs"
     schedule:
-      interval: weekly
-    cooldown:
-      default-days: 3
-    open-pull-requests-limit: 5
+      interval: daily
     allow:
       - dependency-name: "@docusaurus/*"
-    groups:
-      docusaurus:
-        patterns: ["@docusaurus/*"]
-      docs-security:
-        applies-to: security-updates
-        patterns: ["*"]
-    ignore:
-      # A Docusaurus major needs the openapi plugin and theme moved in the
-      # same commit
-      - dependency-name: "@docusaurus/*"
-        update-types: ["version-update:semver-major"]
+    open-pull-requests-limit: 10
+    target-branch: dev

.github/workflows/ci.yml

@@ -586,7 +586,7 @@ jobs:
       - arm64_build
     steps:
       - id: lowercaseRepo
-        uses: ASzc/change-string-case-action@v8
+        uses: ASzc/change-string-case-action@v6
         with:
           string: ${{ github.repository }}
       - name: Log in to the Container registry

.github/workflows/pull_request.yml

@@ -124,5 +124,7 @@ jobs:
         run: devcontainer exec --workspace-folder . bash -lc "python3 -u -m mypy --config-file frigate/mypy.ini frigate"
       - name: Check API spec is up to date
         run: devcontainer exec --workspace-folder . bash -lc "python3 generate_api_auth_spec.py --check"
+      - name: Check analytics schema is up to date
+        run: devcontainer exec --workspace-folder . bash -lc "python3 generate_analytics_schema.py --check"
       - name: Run unit tests in devcontainer
         run: devcontainer exec --workspace-folder . bash -lc "python3 -u -m unittest"

.github/workflows/release.yml

@@ -14,7 +14,7 @@ jobs:
         with:
           persist-credentials: false
       - id: lowercaseRepo
-        uses: ASzc/change-string-case-action@v8
+        uses: ASzc/change-string-case-action@v6
         with:
           string: ${{ github.repository }}
       - name: Log in to the Container registry

docker/main/Dockerfile

@@ -217,8 +217,6 @@ COPY docker/main/rootfs/ /
 
 # Frigate deps (ffmpeg, python, nginx, go2rtc, s6-overlay, etc)
 FROM slim-base AS deps
-LABEL org.opencontainers.image.source="https://github.com/blakeblackshear/frigate"
-
 ARG TARGETARCH
 ARG BASE_IMAGE
 
@@ -383,6 +381,7 @@ FROM deps AS frigate
 
 WORKDIR /opt/frigate/
 COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=standard
 
 # Pre-compile bytecode so a read-only rootfs doesn't force re-parsing the
 # source tree on every boot (pip-installed packages are already compiled)

docker/main/requirements-dev.txt

@@ -1,4 +1,4 @@
-ruff == 0.17.0
+ruff == 0.15.20
 
 # types
 types-peewee == 4.0.*

docker/main/requirements-ov.txt

@@ -1,2 +1,2 @@
 numpy
-openvino >= 2026.4.1
+openvino >= 2026.2.0

docker/main/requirements-wheels.txt

@@ -1,66 +1,66 @@
 aiofiles == 25.1.*
 click == 8.5.*
 # FastAPI
-aiohttp == 3.14.*
-starlette == 1.7.*
+aiohttp == 3.12.*
+starlette == 0.47.*
 starlette-context == 0.5.*
-fastapi[standard-no-fastapi-cloud-cli] == 0.142.*
-uvicorn == 0.54.*
+fastapi[standard-no-fastapi-cloud-cli] == 0.116.*
+uvicorn == 0.52.*
 slowapi == 0.1.*
-joserfc == 1.7.*
-cryptography == 50.0.*
+joserfc == 1.6.*
+cryptography == 46.0.*
 pathvalidate == 3.3.*
 markupsafe == 3.0.*
-python-multipart == 0.0.32
+python-multipart == 0.0.31
 # Classification Model Training
 tensorflow == 2.19.* ; platform_machine == 'aarch64'
-tensorflow-cpu == 2.21.* ; platform_machine == 'x86_64'
+tensorflow-cpu == 2.19.* ; platform_machine == 'x86_64'
 # General
-mypy == 2.4.0
-onvif-zeep-async == 4.3.*
+mypy == 1.6.1
+onvif-zeep-async == 4.0.*
 paho-mqtt == 2.1.*
-pandas == 3.0.*
-peewee == 4.5.*
-peewee_migrate == 2.3.*
-psutil == 7.2.*
-pydantic == 2.14.*
+pandas == 2.2.*
+peewee == 3.17.*
+peewee_migrate == 1.14.*
+psutil == 7.1.*
+pydantic == 2.10.*
 git+https://github.com/fbcotter/py3nvml#egg=py3nvml
-tzdata == 2026.5
-pyzmq == 27.2.*
-ruamel.yaml == 0.19.*
-tzlocal == 5.4.4
-requests == 2.34.*
-types-requests == 2.33.*
+pytz == 2025.*
+pyzmq == 27.1.*
+ruamel.yaml == 0.18.*
+tzlocal == 5.2
+requests == 2.33.*
+types-requests == 2.32.*
 norfair == 2.3.*
 setproctitle == 1.3.*
-ws4py == 0.6.*
+ws4py == 0.5.*
 unidecode == 1.4.*
 titlecase == 2.4.*
 # Image Manipulation
 numpy == 1.26.*
 opencv-python-headless == 4.11.0.*
 opencv-contrib-python == 4.11.0.*
-scipy == 1.17.*
+scipy == 1.16.*
 # OpenVino & ONNX
-openvino == 2026.4.*
-onnxruntime == 1.30.*
+openvino == 2025.4.*
+onnxruntime == 1.22.*
 # Embeddings
-transformers == 5.19.*
+transformers == 4.45.*
 # Generative AI
-google-genai == 2.31.*
+google-genai == 1.58.*
 ollama == 0.6.*
-openai == 3.26.*
+openai == 1.65.*
 # push notifications
-py-vapid == 1.9.6
-pywebpush == 2.5.*
+py-vapid == 1.9.4
+pywebpush == 2.0.*
 # alpr
 pyclipper == 1.4.*
-shapely == 2.2.*
-rapidfuzz==3.14.*
+shapely == 2.0.*
+rapidfuzz==3.12.*
 # HailoRT
-argcomplete==3.7.*
-contextlib2==21.6.*
-future==1.0.*
+argcomplete==2.0.*
+contextlib2==0.6.*
+future==0.18.*
 netaddr==1.3.*
 netifaces==0.10.*
 prometheus-client == 0.26.*
@@ -71,6 +71,6 @@ tflite_runtime @ https://github.com/feranick/TFlite-builds/releases/download/v2.
 sherpa-onnx==1.13.*
 faster-whisper==1.2.*
 librosa==0.11.*
-soundfile==0.14.*
+soundfile==0.13.*
 # Memory profiling
 memray == 1.20.*

docker/main/requirements.txt

@@ -1 +1 @@
-scikit-build == 0.19.*
+scikit-build == 0.18.*

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

@@ -61,7 +61,7 @@ do
             ;;
     esac
 
-    liveprint=`openssl s_client -showcerts -connect 127.0.0.1:$listen_external_port </dev/null 2>&1 | openssl x509 -fingerprint 2>&1 | grep -i fingerprint  || echo 'failed'`
+    liveprint=`echo | openssl s_client -showcerts -connect 127.0.0.1:$listen_external_port 2>&1 | openssl x509 -fingerprint 2>&1 | grep -i fingerprint  || echo 'failed'`
 
     case "$liveprint" in
         *Fingerprint*)

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

@@ -8,14 +8,13 @@ from typing import Any
 from ruamel.yaml import YAML
 
 sys.path.insert(0, "/opt/frigate")
+from frigate.config.env import apply_config_env_vars, substitute_frigate_vars
 from frigate.const import (
     BIRDSEYE_PIPE,
     LIBAVFORMAT_VERSION_MAJOR,
 )
 from frigate.ffmpeg_presets import parse_preset_hardware_acceleration_encode
 from frigate.util.config import find_config_file, resolve_ffmpeg_path
-from frigate.util.env import apply_config_env_vars, substitute_frigate_vars
-from frigate.util.live_streams import raw_transcode_streams
 from frigate.util.services import (
     is_go2rtc_arbitrary_exec_allowed,
     is_restricted_go2rtc_source,
@@ -175,17 +174,6 @@ for name in list(go2rtc_config.get("streams", {})):
             del go2rtc_config["streams"][name]
             continue
 
-# add transcoded live streams; a user stream with the same name wins here and
-# fails Frigate's config validation
-transcoded_streams = raw_transcode_streams(config)
-
-if transcoded_streams:
-    if go2rtc_config.get("streams") is None:
-        go2rtc_config["streams"] = {}
-
-    for name, source in transcoded_streams.items():
-        go2rtc_config["streams"].setdefault(name, source)
-
 # add birdseye restream stream if enabled
 if config.get("birdseye", {}).get("restream", False):
     birdseye: dict[str, Any] = config.get("birdseye")

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

@@ -14,10 +14,7 @@ location /auth {
     proxy_pass_request_headers off;
     # Pass info about the request
     proxy_set_header X-Original-Method $request_method;
-    proxy_set_header X-Original-URL $request_uri;
-    # set by the go2rtc stream locations; client headers are not forwarded, so
-    # this cannot be spoofed
-    proxy_set_header X-Go2rtc-Stream-Proxy $go2rtc_stream_proxy;
+    proxy_set_header X-Original-URL $scheme://$http_host$request_uri;
     proxy_set_header X-Server-Port $server_port;
     proxy_set_header Content-Length "";
     # Pass along auth related info

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

@@ -219,8 +219,6 @@ http {
 
         # frigate lovelace card uses this path
         location /live/mse/api/ws {
-            # tells /auth to apply the go2rtc stream checks
-            set $go2rtc_stream_proxy 1;
             include auth_request.conf;
             limit_except GET {
                 deny  all;
@@ -230,8 +228,6 @@ http {
         }
 
         location /live/webrtc/api/ws {
-            # tells /auth to apply the go2rtc stream checks
-            set $go2rtc_stream_proxy 1;
             include auth_request.conf;
             limit_except GET {
                 deny  all;
@@ -252,8 +248,6 @@ http {
 
         # integration uses this to add webrtc candidate
         location /api/go2rtc/webrtc {
-            # tells /auth to apply the go2rtc stream checks
-            set $go2rtc_stream_proxy 1;
             include auth_request.conf;
             limit_except POST {
                 deny  all;

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

@@ -2,7 +2,7 @@
 proxy_set_header Host $host;
 proxy_set_header Upgrade $http_upgrade;
 proxy_set_header Connection "Upgrade";
-proxy_set_header X-Original-URL $request_uri;
+proxy_set_header X-Original-URL $scheme://$http_host$request_uri;
 proxy_set_header X-Forwarded-Proto $scheme;
 proxy_set_header X-Forwarded-Host $http_host;
 proxy_set_header X-Forwarded-URI $request_uri;

docker/rockchip/Dockerfile

@@ -25,6 +25,7 @@ RUN --mount=type=bind,from=rk-wheels,source=/rk-wheels,target=/deps/rk-wheels \
 
 WORKDIR /opt/frigate/
 COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=rk
 COPY docker/rockchip/COCO /COCO
 COPY docker/rockchip/conv2rknn.py /opt/conv2rknn.py
 

docker/rocm/Dockerfile

@@ -2,9 +2,32 @@
 
 # https://askubuntu.com/questions/972516/debian-frontend-environment-variable
 ARG DEBIAN_FRONTEND=noninteractive
+ARG ROCM=1
 ARG HSA_OVERRIDE_GFX_VERSION
 ARG HSA_OVERRIDE
 
+#######################################################################
+FROM wget AS rocm
+
+ARG ROCM
+
+RUN apt update -qq && \
+    apt install -y wget gpg && \
+    wget -O rocm.deb https://repo.radeon.com/amdgpu-install/7.2.3/ubuntu/jammy/amdgpu-install_7.2.3.70203-1_all.deb && \
+    apt install -y ./rocm.deb && \
+    apt update && \
+    apt install -qq -y rocm
+
+RUN mkdir -p /opt/rocm-dist/opt/rocm-$ROCM/lib
+RUN cd /opt/rocm-$ROCM/lib && \
+    cp -dpr libMIOpen*.so* libamd*.so* libhip*.so* libhsa*.so* libmigraphx*.so* librocm*.so* librocblas*.so* libroctracer*.so* librocsolver*.so* librocfft*.so* librocprofiler*.so* libroctx*.so*  librocroller.so* /opt/rocm-dist/opt/rocm-$ROCM/lib/ && \
+    mkdir -p /opt/rocm-dist/opt/rocm-$ROCM/lib/migraphx/lib && \
+    cp -dpr migraphx/lib/* /opt/rocm-dist/opt/rocm-$ROCM/lib/migraphx/lib
+RUN cd /opt/rocm-dist/opt/ && ln -s rocm-$ROCM rocm
+
+RUN mkdir -p /opt/rocm-dist/etc/ld.so.conf.d/
+RUN echo /opt/rocm/lib|tee /opt/rocm-dist/etc/ld.so.conf.d/rocm.conf
+
 #######################################################################
 FROM deps AS deps-prelim
 
@@ -19,35 +42,52 @@ RUN echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.
     rm -f /etc/apt/sources.list.d/trixie.list && \
     rm -rf /var/lib/apt/lists/*
 
+WORKDIR /opt/frigate
+COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=rocm
+
 RUN wget -q https://bootstrap.pypa.io/get-pip.py -O get-pip.py \
     && sed -i 's/args.append("setuptools")/args.append("setuptools==77.0.3")/' get-pip.py \
     && python3 get-pip.py "pip" --break-system-packages
 RUN python3 -m pip config set global.break-system-packages true
 
-# ROCm installs from AMD's wheels ahead of Frigate's code so code changes
-# reuse this layer, and is pruned in the same layer so the removed files never
-# reach the image. /opt/rocm links to the runtime for rocminfo and HIP headers.
 COPY docker/rocm/requirements-wheels-rocm.txt /requirements.txt
-RUN --mount=type=bind,source=docker/rocm/prune_rocm.sh,target=/deps/prune_rocm.sh \
-    pip3 uninstall -y onnxruntime \
-    && pip3 install --no-cache-dir -r /requirements.txt \
-    && ROCM_SDK_CORE="$(python3 -c 'import _rocm_sdk_core, os; print(os.path.dirname(_rocm_sdk_core.__file__))')" \
-    && /deps/prune_rocm.sh "$(dirname "${ROCM_SDK_CORE}")" \
-    && ln -s "${ROCM_SDK_CORE}" /opt/rocm
+RUN pip3 uninstall -y onnxruntime \
+    && pip3 install -r /requirements.txt
 
-WORKDIR /opt/frigate
-COPY --from=rootfs / /
+#######################################################################
+FROM scratch AS rocm-dist
+
+ARG ROCM
+
+# Copy HIP headers required for MIOpen JIT (BuildHip) / HIPRTC at runtime
+COPY --from=rocm /opt/rocm-${ROCM}/include/ /opt/rocm-${ROCM}/include/
+COPY --from=rocm /opt/rocm-$ROCM/bin/rocminfo /opt/rocm-$ROCM/bin/migraphx-driver /opt/rocm-$ROCM/bin/
+# Copy MIOpen database files for gfx10xx, gfx11xx, and gfx12xx only (RDNA2/RDNA3/RDNA4)
+COPY --from=rocm /opt/rocm-$ROCM/share/miopen/db/*gfx10* /opt/rocm-$ROCM/share/miopen/db/
+COPY --from=rocm /opt/rocm-$ROCM/share/miopen/db/*gfx11* /opt/rocm-$ROCM/share/miopen/db/
+COPY --from=rocm /opt/rocm-$ROCM/share/miopen/db/*gfx12* /opt/rocm-$ROCM/share/miopen/db/
+# Copy rocBLAS library files for gfx10xx, gfx11xx, and gfx12xx only
+COPY --from=rocm /opt/rocm-$ROCM/lib/rocblas/library/*gfx10* /opt/rocm-$ROCM/lib/rocblas/library/
+COPY --from=rocm /opt/rocm-$ROCM/lib/rocblas/library/*gfx11* /opt/rocm-$ROCM/lib/rocblas/library/
+COPY --from=rocm /opt/rocm-$ROCM/lib/rocblas/library/*gfx12* /opt/rocm-$ROCM/lib/rocblas/library/
+COPY --from=rocm /opt/rocm-dist/ /
 
 #######################################################################
 FROM deps-prelim AS rocm-prelim-hsa-override0
 ENV MIGRAPHX_DISABLE_MIOPEN_FUSION=1
 ENV MIGRAPHX_DISABLE_SCHEDULE_PASS=1
 ENV MIGRAPHX_DISABLE_REDUCE_FUSION=1
+ENV MIGRAPHX_ENABLE_HIPRTC_WORKAROUNDS=1
 ENV MIOPEN_CUSTOM_CACHE_DIR=/config/model_cache/migraphx
 ENV MIOPEN_USER_DB_PATH=/config/model_cache/migraphx
 ENV AMD_COMGR_CACHE=1
 ENV AMD_COMGR_CACHE_DIR=/config/model_cache/migraphx
 
+COPY --from=rocm-dist / /
+
+RUN ldconfig
+
 #######################################################################
 FROM rocm-prelim-hsa-override0 as rocm-prelim-hsa-override1
 

docker/rocm/prune_rocm.sh

@@ -1,63 +0,0 @@
-#!/bin/bash
-
-# Remove the parts of AMD's ROCm wheels that MIGraphX inference never loads:
-# compilers, debuggers, profilers, management tools, and the math libraries
-# (sparse, solver, FFT, random, RCCL, image processing) outside MIGraphX's
-# dependencies. Runs in the same layer as the install so the files never
-# reach the image.
-
-set -euo pipefail
-
-site_packages="$1"
-core="${site_packages}/_rocm_sdk_core"
-libraries="${site_packages}/_rocm_sdk_libraries"
-
-# rocminfo stays for checking that the GPU is visible in the container
-find "${core}/bin" -mindepth 1 -maxdepth 1 \
-    ! -name rocminfo ! -name rocm_agent_enumerator -exec rm -rf {} +
-
-# hiprtc compiles MIGraphX's kernels through comgr, which needs libLLVM,
-# libclang-cpp, the clang resource headers, and the amdgcn device libraries
-rm -rf "${core}/lib/llvm/bin" "${core}/lib/llvm/include"
-find "${core}/lib/llvm/lib" -mindepth 1 -maxdepth 1 \
-    ! -name 'libLLVM.so*' ! -name 'libclang-cpp.so*' ! -name clang \
-    -exec rm -rf {} +
-rm -rf "${core}"/lib/llvm/lib/clang/*/lib
-
-rm -rf \
-    "${core}/lib/host-math" \
-    "${core}"/lib/python3* \
-    "${core}/lib/rocprofiler-sdk" \
-    "${core}"/lib/librocprofiler-sdk*.so* \
-    "${core}"/lib/librocprof-trace-decoder.so* \
-    "${core}"/lib/librocm-dbgapi.so* \
-    "${core}"/lib/librocm-debug-agent.so* \
-    "${core}"/lib/libamd_smi*.so* \
-    "${core}"/lib/libgoamdsmi_shim64.so* \
-    "${core}"/lib/librocdecode.so* \
-    "${core}"/lib/librocjpeg.so* \
-    "${core}"/lib/librocdxg.so* \
-    "${core}"/lib/librocjitsu_*.so* \
-    "${core}"/lib/libhsa_hotswap_rocjitsu.so* \
-    "${core}"/lib/*.a
-
-rm -rf \
-    "${libraries}"/lib/librpp.so* \
-    "${libraries}"/lib/librocsparse.so* \
-    "${libraries}"/lib/libhipsparse.so* \
-    "${libraries}"/lib/libhipsparselt.so* \
-    "${libraries}/lib/rocsparse" \
-    "${libraries}"/lib/librocsolver.so* \
-    "${libraries}"/lib/libhipsolver.so* \
-    "${libraries}"/lib/libhipblas.so* \
-    "${libraries}"/lib/librocrand.so* \
-    "${libraries}"/lib/libhiprand.so* \
-    "${libraries}"/lib/librocfft.so* \
-    "${libraries}"/lib/libhipfft.so* \
-    "${libraries}"/lib/libhipfftw.so* \
-    "${libraries}"/lib/librccl.so* \
-    "${libraries}"/.kpack/sparse_lib_*.kpack \
-    "${libraries}"/.kpack/solver_lib_*.kpack \
-    "${libraries}"/.kpack/rand_lib_*.kpack \
-    "${libraries}"/.kpack/fft_lib_*.kpack \
-    "${libraries}"/.kpack/rccl_lib_*.kpack

docker/rocm/requirements-wheels-rocm.txt

@@ -1,19 +1 @@
-# ROCm 10.1.0, MIGraphX, and its ONNX Runtime plugin provider from AMD's wheels.
-onnxruntime == 1.29.*
-onnxruntime-ep-migraphx @ https://stable.repo.amd.com/rocm/onnxruntime/whl-next/onnxruntime-ep-migraphx/onnxruntime_ep_migraphx-1.0.0%2Brocm10.1.0-cp311-cp311-manylinux_2_28_x86_64.whl
-migraphx-libs @ https://stable.repo.amd.com/rocm/migraphx/whl-next/migraphx-libs/migraphx_libs-2.18.0%2Brocm10.1.0-py3-none-manylinux_2_28_x86_64.whl
-rocm-sdk-core @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-core/rocm_sdk_core-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-libraries @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-libraries/rocm_sdk_libraries-10.1.0-py3-none-linux_x86_64.whl
-# Kernels for each supported GPU target. MIGraphX has no gfx1031-gfx1036 kernels,
-# so those GPUs run as gfx1030 with HSA_OVERRIDE_GFX_VERSION=10.3.0
-rocm-sdk-device-gfx1030 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1030/rocm_sdk_device_gfx1030-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1100 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1100/rocm_sdk_device_gfx1100-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1101 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1101/rocm_sdk_device_gfx1101-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1102 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1102/rocm_sdk_device_gfx1102-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1103 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1103/rocm_sdk_device_gfx1103-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1150 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1150/rocm_sdk_device_gfx1150-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1151 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1151/rocm_sdk_device_gfx1151-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1152 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1152/rocm_sdk_device_gfx1152-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1153 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1153/rocm_sdk_device_gfx1153-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1200 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1200/rocm_sdk_device_gfx1200-10.1.0-py3-none-linux_x86_64.whl
-rocm-sdk-device-gfx1201 @ https://stable.repo.amd.com/rocm/whl-next/rocm-sdk-device-gfx1201/rocm_sdk_device_gfx1201-10.1.0-py3-none-linux_x86_64.whl
+onnxruntime-migraphx @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v7.2.3-1/onnxruntime_migraphx-1.24.4-cp311-cp311-linux_x86_64.whl

docker/rocm/rocm.hcl

@@ -1,3 +1,6 @@
+variable "ROCM" {
+  default = "7.2.3"
+}
 variable "HSA_OVERRIDE_GFX_VERSION" {
   default = ""
 }
@@ -5,6 +8,12 @@ variable "HSA_OVERRIDE" {
   default = "1"
 }
 
+target wget {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64"]
+  target = "wget"
+}
+
 target deps {
   dockerfile = "docker/main/Dockerfile"
   platforms = ["linux/amd64"]
@@ -21,10 +30,12 @@ target rocm {
   dockerfile = "docker/rocm/Dockerfile"
   contexts = {
     deps = "target:deps",
+    wget = "target:wget",
     rootfs = "target:rootfs"
   }
   platforms = ["linux/amd64"]
   args = {
+    ROCM = ROCM,
     HSA_OVERRIDE_GFX_VERSION = HSA_OVERRIDE_GFX_VERSION,
     HSA_OVERRIDE = HSA_OVERRIDE
   }

docker/rpi/Dockerfile

@@ -15,3 +15,4 @@ ENV INCLUDED_FFMPEG_VERSIONS="${DEFAULT_FFMPEG_VERSION}:${INCLUDED_FFMPEG_VERSIO
 
 WORKDIR /opt/frigate/
 COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=rpi

docker/synaptics/Dockerfile

@@ -22,6 +22,7 @@ pip3 install --no-deps -U /deps/synap-wheels/*.whl
 
 WORKDIR /opt/frigate/
 COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=synaptics
 
 COPY --from=synap1680-wheels /rootfs/usr/local/lib/*.so /usr/lib
 

docker/tensorrt/Dockerfile.amd64

@@ -25,6 +25,7 @@ RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels
     && pip3 install -U /deps/trt-wheels/*.whl
 
 COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=tensorrt
 COPY docker/tensorrt/detector/rootfs/etc/ld.so.conf.d /etc/ld.so.conf.d
 RUN ldconfig
 

docker/tensorrt/Dockerfile.arm64

@@ -151,6 +151,7 @@ RUN --mount=type=bind,from=trt-wheels,source=/trt-wheels,target=/deps/trt-wheels
 
 WORKDIR /opt/frigate/
 COPY --from=rootfs / /
+ENV FRIGATE_IMAGE_VARIANT=tensorrt-jp6
 
 # Fixes "Error importing detector runtime: /usr/lib/aarch64-linux-gnu/libstdc++.so.6: cannot allocate memory in static TLS block"
 ENV LD_PRELOAD /usr/lib/aarch64-linux-gnu/libstdc++.so.6

docker/tensorrt/requirements-amd64.txt

@@ -14,4 +14,4 @@ nvidia-nccl-cu12==2.26.2.post1; platform_machine == 'x86_64'
 nvidia-nvjitlink-cu12==12.8.93; platform_machine == 'x86_64'
 onnx==1.16.*; platform_machine == 'x86_64'
 onnxruntime-gpu==1.24.*; platform_machine == 'x86_64'
-protobuf==7.36.*; platform_machine == 'x86_64'
+protobuf==3.20.3; platform_machine == 'x86_64'

docs/data/object_detectors_models.yaml

@@ -824,38 +824,6 @@ cpu:
         models:
           - devices:
               - cpu:3
-xdna2:
-  title: AMD XDNA2
-  models:
-    - key: yolov9
-      label: YOLOv9
-      recommended: true
-      download: |-
-        Prepare the model using the frigate-xdna setup instructions linked above. For local YOLO models, Frigate must have access to the same ONNX file bytes as the sidecar. The example below uses YOLOv9-C at 320x320. Frigate+ models may instead use the same `plus://MODEL_ID` in Frigate and the sidecar.
-      ui: |-
-        Navigate to **Settings > System > Detection models** and add a model. The ZMQ endpoint is not reported by the hardware probe, so set `devices` to `zmq:tcp://xdna:5555` in YAML. Then, on the same model, open the **Custom Model** tab and configure:
-
-        | Field                                    | Value                                      |
-        | ---------------------------------------- | ------------------------------------------ |
-        | **Custom object detector model path**    | `/config/models/yolov9-c-320.onnx`       |
-        | **Label map for custom object detector** | `/labelmap/coco-80.txt`                   |
-        | **Object detection model input width**   | `320`                                    |
-        | **Object detection model input height**  | `320`                                    |
-        | **Model Input Pixel Color Format**       | `rgb` (Frigate's default value)          |
-        | **Model Input Tensor Shape**             | `nchw`                                   |
-        | **Model Input D Type**                   | `float`                                  |
-        | **Object Detection Model Type**          | `yolo-generic`                           |
-      yaml: |-
-        models:
-          - devices:
-              - zmq:tcp://xdna:5555
-            model_type: yolo-generic
-            width: 320
-            height: 320
-            input_tensor: nchw
-            input_dtype: float
-            path: /config/models/yolov9-c-320.onnx
-            labelmap_path: /labelmap/coco-80.txt
 memryx:
   title: MemryX
   models:

docs/docs/configuration/advanced/analytics.md

@@ -0,0 +1,41 @@
+---
+id: analytics
+title: Anonymous Analytics
+---
+
+import AnalyticsFields from "@site/src/components/AnalyticsFields";
+import NavPath from "@site/src/components/NavPath";
+
+Frigate can send one anonymous usage report a day. The reports show the maintainers which hardware to support, which features people use, and how releases perform. Sharing is off until you turn it on.
+
+## Turning it on
+
+Enable **Share anonymous analytics** at <NavPath path="Settings > System > Telemetry" />, or set it in your config:
+
+```yaml
+telemetry:
+  analytics: true
+```
+
+The same page has a **Preview the report** button that shows exactly what the next report contains.
+
+## How it's sent
+
+- Once a day, as a JSON POST to `https://analytics.frigate.video/report`
+- The server looks up your country and region from your IP address and never stores the address
+- Raw reports are kept for 60 days; only aggregate totals are published
+- A random install ID, stored in `/config/.analytics.json`, keeps your install from being counted twice. Turning sharing off deletes it
+
+## What's never sent
+
+- Camera, zone, group, profile, or user names
+- Object labels, face names, or license plate text
+- IP addresses, hostnames, URLs, or stream paths
+- Credentials or API keys
+- Events, recordings, or anything from them
+
+## Every field
+
+Fields marked public appear in the published totals. The machine-readable schema is [frigate-analytics-schema.json](pathname:///frigate-analytics-schema.json).
+
+<AnalyticsFields />

docs/docs/configuration/advanced/reference.md

@@ -152,10 +152,9 @@ auth:
 models:
     # Optional: the camera environment this model is for (default: shown below)
     # Cameras select a model by setting detect -> scene to a matching value, and
-    # the model with a scene of default is used by any camera that does not set one.
-    # Any name made up of letters, numbers, _ and - is valid, such as thermal.
-    # Models that use the same model file are combined into one model.
-  - scene: default
+    # a model with a scene of all is used by any camera that does not set one.
+    # Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
+  - scene: all
     # Required: hardware this model runs on, as <detector> or <detector>:<device>
     # See https://docs.frigate.video/configuration/object_detectors for the
     # detectors available and the devices each one accepts. All of a model's
@@ -294,9 +293,9 @@ ffmpeg:
     # Optional: output args for detect streams (default: shown below)
     detect: -threads 2 -f rawvideo -pix_fmt yuv420p
     # Optional: output args for record streams (default: shown below)
-    record: preset-record-generic-audio-aac
+    record: preset-record-generic
     # Optional: output args for sub stream record streams (default: the record output args above)
-    # record_sub: preset-record-generic-audio-aac
+    # record_sub: preset-record-generic
   # Optional: Time in seconds to wait before ffmpeg retries connecting to the camera. (default: shown below)
   # If set too low, frigate will retry a connection to the camera's stream too frequently, using up the limited streams some cameras can allow at once
   # If set too high, then if a ffmpeg crash or camera stream timeout occurs, you could potentially lose up to a maximum of retry_interval second(s) of footage
@@ -317,9 +316,9 @@ detect:
   # Optional: height of the frame for the input with the detect role (default: use native stream resolution)
   height: 720
   # Optional: the environment this camera looks at, which picks the model it runs on
-  # (default: the model with a scene of default)
-  # Must match the scene of a configured model
-  scene: thermal
+  # (default: the model with a scene of all)
+  # Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
+  scene: outdoor
   # Optional: desired fps for your camera for the input with the detect role (default: shown below)
   # NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
   fps: 5
@@ -556,7 +555,7 @@ motion:
       # Optional: Whether this mask is active (default: true)
       enabled: true
       # Required: Coordinates polygon for the mask
-      coordinates: "0.000,0.469,1.0,0.469,1.0,1.0,0.000,1.0"
+      coordinates: "0.000,0.469,1.000,0.469,1.000,1.000,0.000,1.000"
   # Optional: improve contrast (default: shown below)
   # Enables dynamic contrast improvement. This should help improve night detections at the cost of making motion detection more sensitive
   # for daytime.
@@ -571,8 +570,6 @@ notifications:
   enabled: False
   # Optional: Email for push service to reach out to
   # NOTE: This is required to use notifications
-  # NOTE: Email can be specified with an environment variable or docker secrets that must begin with 'FRIGATE_'.
-  #       e.g. email: '{FRIGATE_NOTIFICATION_EMAIL}'
   email: "admin@example.com"
   # Optional: Cooldown time for notifications in seconds (default: shown below)
   cooldown: 0
@@ -903,21 +900,6 @@ live:
   streams:
     main_stream: main_stream_name
     sub_stream: sub_stream_name
-  # Optional: Lower-quality live streams transcoded by go2rtc while someone is watching.
-  # NOTE: Set at the camera level only.
-  transcode:
-    # Optional: Enable transcoded streams (default: shown below)
-    enabled: False
-    # Optional: go2rtc stream to transcode (default: the first live stream)
-    source: main_stream_name
-    # Optional: One transcoded stream per quality (default: shown below)
-    qualities:
-      - height: 720
-        bitrate: 1200
-      - height: 480
-        bitrate: 500
-      - height: 360
-        bitrate: 250
   # 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 jsmpeg stream. Width is computed to match known aspect ratio.
@@ -1212,6 +1194,9 @@ ui:
 
 # Optional: Telemetry configuration
 telemetry:
+  # Optional: Share one anonymous usage report a day (default: shown below)
+  # NOTE: See https://docs.frigate.video/configuration/advanced/analytics for what is sent
+  analytics: False
   # Optional: Enabled network interfaces for bandwidth stats monitoring (default: empty list, let nethogs search all)
   network_interfaces:
     - eth

docs/docs/configuration/audio_detectors.md

@@ -289,7 +289,7 @@ The only field that is valid at the camera level is `enabled`. In particular `mo
 
 #### GenAI Provider
 
-Frigate can send audio to a GenAI provider for transcription when that provider has the `transcribe` role. This is useful if you already run a GenAI provider, or if you do not have the CPU/GPU headroom for a local whisper model. See [Provider support](/configuration/genai/genai_config#provider-support) for which providers can serve this role. The model must accept audio: either a dedicated ASR model such as Qwen3-ASR, or a general multimodal model that accepts audio.
+Frigate can send audio to a GenAI provider for transcription when that provider has the `transcribe` role. This is useful if you already run a GenAI provider, or if you do not have the CPU/GPU headroom for a local whisper model. Supported providers are **OpenAI**, **Azure OpenAI**, **Gemini**, and **llama.cpp** with an audio-capable model (a dedicated ASR model such as Qwen3-ASR, or a general multimodal model that accepts audio). Ollama is not supported as it has no audio input.
 
 To use a GenAI provider for audio transcription:
 

docs/docs/configuration/camera_specific.md

@@ -169,10 +169,10 @@ The [Add Camera Wizard](cameras.md#adding-a-camera-with-the-add-camera-wizard) i
 
 1. Click **Add Camera** in <NavPath path="Settings > Global configuration > Camera management" />.
 2. Choose **Manual selection** as the stream detection method and select **Reolink** as the camera brand.
-3. The wizard queries the camera and automatically uses an http-flv stream for cameras 5MP and lower. For higher resolution cameras, it tries the http-flv stream first and falls back to RTSP when the camera does not support it.
-4. The wizard turns on **Use stream compatibility mode** for the http-flv stream it selects. Enable it for any other http-flv stream you add, such as the sub stream.
+3. The wizard queries the camera and automatically uses an http-flv stream for cameras 5MP and lower, or an RTSP stream for higher resolution cameras.
+4. In the validation step, enable **Use stream compatibility mode** for http-flv streams when the wizard recommends it.
 
-If you use the **Probe camera** method instead, the discovered stream URLs will be RTSP. For Reolink cameras 5MP and lower, where http-flv is recommended, the wizard will show a warning in the validation step.
+If you use the **Probe camera** method instead, the discovered stream URLs will be RTSP. For Reolink cameras where http-flv is recommended, the wizard will show a warning in the validation step.
 
 The wizard covers standard single-camera setups. For two way talk, cameras connected through a Reolink NVR, or audio transcoding for WebRTC live view, configure the camera manually as shown below.
 

docs/docs/configuration/cameras.md

@@ -235,7 +235,7 @@ The FeatureList on the [ONVIF Conformant Products Database](https://www.onvif.or
 | Amcrest ASH21                |      ✅      |      ❌      | ONVIF service port: 80                                                                                                                                                                                                                                            |
 | Amcrest IP4M-S2112EW-AI      |      ✅      |      ❌      | FOV relative movement not supported.                                                                                                                                                                                                                              |
 | Amcrest IP5M-1190EW          |      ✅      |      ❌      | ONVIF Port: 80. FOV relative movement not supported.                                                                                                                                                                                                              |
-| Annke CZ504                  |      ✅      |      ❌      |                                                                                                                                                                                                                                                                   |
+| Annke CZ504                  |      ✅      |      ✅      | Annke support provide specific firmware ([V5.7.1 build 250227](https://github.com/pierrepinon/annke_cz504/raw/refs/heads/main/digicap_V5-7-1_build_250227.dav)) to fix issue with ONVIF "TranslationSpaceFov"                                                     |
 | Axis Q-6155E                 |      ✅      |      ❌      | ONVIF service port: 80; Camera does not support MoveStatus.                                                                                                                                                                                                       |
 | Ctronics PTZ                 |      ✅      |      ❌      |                                                                                                                                                                                                                                                                   |
 | Dahua                        |      ✅      |      ✅      | Some low-end Dahuas (lite series, picoo series (commonly), among others) have been reported to not support autotracking. These models usually don't have a four digit model number with chassis prefix and options postfix (e.g. DH-P5AE-PV vs DH-SD49825GB-HNR). |

docs/docs/configuration/custom_classification/state_classification.md

@@ -85,14 +85,6 @@ An optional config, `save_attempts`, can be set as a key under the model name. T
 </TabItem>
 </ConfigTabs>
 
-## Review items
-
-When a model's state changes while its camera has an active review item, the change is recorded on that review item. This includes changes in the few seconds before the item starts, such as a garage door opening just before the car is detected. State changes never create or extend review items on their own, and the first state reported after Frigate starts is not recorded as a change.
-
-Recorded changes appear in the review item's data as `classification_state_changes` (see the [`frigate/reviews`](/integrations/mqtt#frigatereviews) MQTT topic) and are passed to [GenAI review summaries](/configuration/genai/genai_review) as facts, so a description can note that a gate was opened during the activity.
-
-Change times are most accurate with `motion: true`. A model that only runs on an `interval` notices a change at its next run, so the change may be recorded late or attached to a later review item.
-
 ## Training the model
 
 Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of three steps:

docs/docs/configuration/ffmpeg_presets.md

@@ -17,19 +17,17 @@ Hardware acceleration arguments tell FFmpeg to decode your camera's video stream
 
 See [the hardware acceleration docs](/configuration/hardware_acceleration_video.md) for details on setting up hardware acceleration for your GPU / iGPU, then select the preset that matches your hardware.
 
-| Preset (YAML config)      | UI Label                | Usage                                         | Notes                                                           |
-| ------------------------- | ----------------------- | --------------------------------------------- | --------------------------------------------------------------- |
-| preset-rpi-64-h264        | Raspberry Pi (H.264)    | 64-bit Raspberry Pi, H.264 stream             |                                                                 |
-| preset-rpi-64-h265        | Raspberry Pi (H.265)    | 64-bit Raspberry Pi, H.265 stream             |                                                                 |
-| preset-apple-silicon-h264 | Apple Silicon (H.264)   | Apple Silicon Mac under lighter, H.264 stream | Needs the `lighter.sh/video` device                             |
-| preset-apple-silicon-h265 | Apple Silicon (H.265)   | Apple Silicon Mac under lighter, H.265 stream | Needs the `lighter.sh/video` device                             |
-| preset-vaapi              | VAAPI (Intel/AMD GPU)   | Intel or AMD GPU via VAAPI                    | Check the hwaccel docs to ensure the correct driver is selected |
-| preset-intel-qsv-h264     | Intel QuickSync (H.264) | Intel QuickSync, H.264 stream                 | If you have issues, use the VAAPI preset instead                |
-| preset-intel-qsv-h265     | Intel QuickSync (H.265) | Intel QuickSync, H.265 stream                 | If you have issues, use the VAAPI preset instead                |
-| preset-nvidia             | NVIDIA GPU              | NVIDIA GPU                                    |                                                                 |
-| preset-jetson-h264        | NVIDIA Jetson (H.264)   | NVIDIA Jetson, H.264 stream                   |                                                                 |
-| preset-jetson-h265        | NVIDIA Jetson (H.265)   | NVIDIA Jetson, H.265 stream                   |                                                                 |
-| preset-rkmpp              | Rockchip RKMPP          | Rockchip MPP                                  | Use an image with the `-rk` suffix and run in privileged mode   |
+| Preset (YAML config)  | UI Label                | Usage                             | Notes                                                           |
+| --------------------- | ----------------------- | --------------------------------- | --------------------------------------------------------------- |
+| preset-rpi-64-h264    | Raspberry Pi (H.264)    | 64-bit Raspberry Pi, H.264 stream |                                                                 |
+| preset-rpi-64-h265    | Raspberry Pi (H.265)    | 64-bit Raspberry Pi, H.265 stream |                                                                 |
+| preset-vaapi          | VAAPI (Intel/AMD GPU)   | Intel or AMD GPU via VAAPI        | Check the hwaccel docs to ensure the correct driver is selected |
+| preset-intel-qsv-h264 | Intel QuickSync (H.264) | Intel QuickSync, H.264 stream     | If you have issues, use the VAAPI preset instead                |
+| preset-intel-qsv-h265 | Intel QuickSync (H.265) | Intel QuickSync, H.265 stream     | If you have issues, use the VAAPI preset instead                |
+| preset-nvidia         | NVIDIA GPU              | NVIDIA GPU                        |                                                                 |
+| preset-jetson-h264    | NVIDIA Jetson (H.264)   | NVIDIA Jetson, H.264 stream       |                                                                 |
+| preset-jetson-h265    | NVIDIA Jetson (H.265)   | NVIDIA Jetson, H.265 stream       |                                                                 |
+| preset-rkmpp          | Rockchip RKMPP          | Rockchip MPP                      | Use an image with the `-rk` suffix and run in privileged mode   |
 
 <ConfigTabs>
 <TabItem value="ui">

docs/docs/configuration/genai/config.md

@@ -43,19 +43,7 @@ genai:
 
 The examples on this page all use `my_provider`, but the name is arbitrary and is only used to reference the provider elsewhere in the config (for example, `semantic_search.model`).
 
-Each provider handles one or more **roles**: `chat`, `descriptions`, `embeddings`, and `transcribe`. A provider handles the first three by default; `transcribe` must always be listed explicitly. Each role may be assigned to exactly one provider. Define a single provider if you want it to do everything, or split the roles across several providers using the `roles` option. Not every provider supports every role; see [Provider support](#provider-support).
-
-### Provider support
-
-| Provider                      | Descriptions | Chat | Embeddings | Transcription |
-| ----------------------------- | :----------: | :--: | :--------: | :-----------: |
-| llama.cpp (`llamacpp`)        |      ✅      |  ✅  |     ✅     |      ✅       |
-| Ollama (`ollama`)             |      ✅      |  ✅  |     ✅     |      ❌       |
-| OpenAI (`openai`)             |      ✅      |  ✅  |     ❌     |      ✅       |
-| Azure OpenAI (`azure_openai`) |      ✅      |  ✅  |     ❌     |      ✅       |
-| Google Gemini (`gemini`)      |      ✅      |  ✅  |     ❌     |      ✅       |
-
-A ✅ means Frigate can use the provider for that feature. The configured model must also support it: a vision model for descriptions and chat, a multimodal embedding model for embeddings (see [Embedding models](#embedding-models)), and an audio-capable model for transcription. Some features also need extra provider setup, covered in each provider's section below. OpenAI-compatible servers use the `openai` provider, so they follow the OpenAI row.
+Each provider handles one or more **roles**: `chat`, `descriptions`, `embeddings`, and `transcribe`. A provider handles the first three by default; `transcribe` must always be listed explicitly, and is not available on Ollama, which has no audio input. Each role may be assigned to exactly one provider. Define a single provider if you want it to do everything, or split the roles across several providers using the `roles` option.
 
 If the provider you choose requires an API key, you may either directly paste it in your configuration, or store it in an environment variable prefixed with `FRIGATE_`.
 
@@ -85,10 +73,9 @@ You must use a vision-capable model with Frigate. The following models are recom
 
 The `embeddings` role needs a different kind of model. Text queries are matched against the stored image embeddings, so the model must be trained to place images and text into the same vector space. A chat or description model will still return vectors when asked, but those vectors are not trained for retrieval and text searches will return poor matches with no error to indicate why.
 
-| Model                | Notes                                                                                                                                                                  |
-| -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `embeddinggemma-2`   | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Strong semantic search accuracy with efficient inference on a small model. |
-| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Good performance, large model that requires strong hardware for inference. |
+| Model                | Notes                                                                                                                                                               |
+| -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Must be served by llama.cpp started with `--embeddings` and `--mmproj`. |
 
 #### Transcription models
 
@@ -165,10 +152,6 @@ genai:
 
 Frigate queries the llama.cpp server for the model's context size at startup and logs it along with the other detected capabilities. If `context_size` is set in `provider_options`, that value is always used instead, even when the server reports its own.
 
-#### Embeddings
-
-To serve the `embeddings` role for [Semantic Search](/configuration/semantic_search#genai-provider), start the llama.cpp server with `--embeddings`, plus `--mmproj` for image support. See the [llama.cpp server documentation](https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md) for details.
-
 ### Ollama
 
 [Ollama](https://ollama.com/) allows you to self-host large language models and keep everything running locally. It is highly recommended to host this server on a machine with an Nvidia graphics card, or on a Apple silicon Mac for best performance.
@@ -214,10 +197,6 @@ genai:
 </TabItem>
 </ConfigTabs>
 
-#### Embeddings
-
-Ollama can serve the `embeddings` role for [Semantic Search](/configuration/semantic_search#genai-provider). Embedding images requires Ollama 0.40.1 or newer and an embedding model with a vision encoder, such as `embeddinggemma-2:440m`. For a saved provider, the UI hides the role unless Ollama reports its model as an embedding model. Use a separate provider entry for the embedding model rather than adding the role to a vision chat model.
-
 ### OpenAI-Compatible
 
 Frigate supports any provider that implements the OpenAI API standard. This includes self-hosted solutions like [vLLM](https://docs.vllm.ai/), [LocalAI](https://localai.io/), and other OpenAI-compatible servers.

docs/docs/configuration/genai/review_summaries.md

@@ -201,8 +201,6 @@ Review items are sent to the model as a sequence of still frames. Some models fo
 
 The notes come from tracking data rather than from the images, so they describe activity the model may not have picked up on its own. In testing with a person carrying three waste bins to the curb one at a time, `gemma4` described a single trip on every attempt with `frames`, and consistently described multiple trips with `annotated_frames`. Models that already handle these sequences well, such as the `qwen3-vl` family, gain little and should stay on `frames`.
 
-Changes reported by [state classification](/configuration/custom_classification/state_classification#review-items) models during the review item are listed in the prompt in both modes. `annotated_frames` also notes each change before the frame where it happened.
-
 Annotated mode also caps the number of frames, since the notes already establish the order of events and extra near-duplicate frames tend to crowd out the middle of a clip. Longer review items are sampled more sparsely as a result, and typically use fewer tokens than `frames` mode for the same item.
 
 :::note

docs/docs/configuration/hardware_acceleration_video.md

@@ -43,10 +43,6 @@ Frigate supports presets for optimal hardware accelerated video decoding:
 
 - [RKNN](#rockchip-platform): Frigate can utilize the media engine in RockChip SOCs to accelerate video decoding.
 
-**Apple Silicon Mac** <CommunityBadge />
-
-- [lighter](#apple-silicon-mac-lighter): Frigate can utilize the media engine in Apple Silicon Macs to accelerate video decoding, when running under the lighter container runtime.
-
 **Other Hardware**
 
 Depending on your system, these presets may not be compatible, and you may need to use manual hwaccel args to take advantage of your hardware. More information on hardware accelerated decoding for ffmpeg can be found here: https://trac.ffmpeg.org/wiki/HWAccelIntro
@@ -136,8 +132,7 @@ ffmpeg:
 
 Frigate reads Intel GPU utilization directly from the kernel's per-client DRM usage counters exposed at `/proc/<pid>/fdinfo/<fd>`. This requires:
 
-- An Intel GPU from Broadwell (5th gen) or newer. Older GPUs do not expose these counters on any kernel.
-- Linux kernel **5.19 or newer** for the `i915` driver (**6.5 or newer** on 12th gen and newer), or any release of the `xe` driver.
+- Linux kernel **5.19 or newer** for the `i915` driver, or any release of the `xe` driver.
 - Frigate running with permission to read other processes' fdinfo. Running as root inside the container (the default) satisfies this; non-root setups may need `CAP_SYS_PTRACE`.
 
 No `intel_gpu_top` binary, `CAP_PERFMON`, privileged mode, or `perf_event_paranoid` tuning is required.
@@ -538,35 +533,3 @@ output_args:
 Make sure that your SoC supports hardware acceleration for your input stream and your input stream is h264 encoding. For example, if your camera streams with h264 encoding, your SoC must be able to de- and encode with it. If you are unsure whether your SoC meets the requirements, take a look at the datasheet.
 
 :::
-
-## Apple Silicon Mac (lighter)
-
-[lighter](https://github.com/fieldwork-ai/lighter) is an open-source container runtime for macOS. It gives a container the Mac's media engine as a standard V4L2 decoder, backed by VideoToolbox, so Frigate decodes H.264 and H.265 streams in hardware with the ffmpeg it already ships. It works on M1 and newer Macs with lighter 0.9.2 or newer.
-
-Give the container the video device. With Docker Compose:
-
-```yaml {4-5}
-services:
-  frigate:
-    ...
-    devices:
-      - lighter.sh/video=all
-```
-
-Or with `docker run`, add `--device lighter.sh/video=all`.
-
-Then set the preset for the codec your cameras stream. The decoder is specific to the codec, so if your cameras mix H.264 and H.265, set the preset for the most common codec globally and override it on the other cameras:
-
-```yaml
-ffmpeg:
-  hwaccel_args: preset-apple-silicon-h264
-
-cameras:
-  garage: # an H.265 camera
-    ffmpeg:
-      hwaccel_args: preset-apple-silicon-h265
-```
-
-The presets decode on the media engine and encode the Birdseye restream and timelapses there too. Scaling to the detect resolution runs on the CPU, as ffmpeg's V4L2 decoders cannot scale.
-
-lighter can also run object detection on the Mac's Neural Engine; see [Apple Neural Engine (lighter)](object_detectors.md#apple-neural-engine-lighter).

docs/docs/configuration/license_plate_recognition.md

@@ -378,10 +378,10 @@ Navigate to <NavPath path="Settings > Camera configuration > Object detection" /
 
 Navigate to <NavPath path="Settings > Camera configuration > Objects" />.
 
-| Field                                                     | Description         |
-| --------------------------------------------------------- | ------------------- |
-| **Objects to track**                                      | Add `license_plate` |
-| **Object filters > License Plate > Confidence threshold** | Set to `0.7`        |
+| Field                                          | Description         |
+| ---------------------------------------------- | ------------------- |
+| **Objects to track**                           | Add `license_plate` |
+| **Object filters > License Plate > Threshold** | Set to `0.7`        |
 
 Navigate to <NavPath path="Settings > Camera configuration > Motion detection" />.
 

docs/docs/configuration/live.md

@@ -38,7 +38,7 @@ Frigate [defaults to MSE](#why-does-frigate-prefer-mse-over-webrtc-for-live-view
 
 - The choices are saved **per device, per camera** in your browser's local storage.
 - **WebRTC is only selectable when it can actually work for that stream.** When it can't, the option is shown disabled with the reason inline, and a more detailed reason (the failing codecs, or why the connectivity check failed) is logged to your browser's console. Common reasons:
-  - **Not configured**: no `candidates` or `ice_servers` are set under `go2rtc.webrtc`, and the connectivity check failed with go2rtc's default candidates (see [WebRTC extra configuration](#webrtc-extra-configuration)). This is a setup note rather than an error, since live view works without WebRTC.
+  - **Not configured**: no `candidates` or `ice_servers` are set under `go2rtc.webrtc` (see [WebRTC extra configuration](#webrtc-extra-configuration)).
   - **Could not connect**: e.g. port `8555` isn't reachable, or a STUN/TURN server is misconfigured. Frigate runs a one-time WebRTC connectivity check when the Live view opens; the option may briefly show as "checking" while it runs.
   - **Unsupported video codec**: the stream's video codec can't be played over WebRTC in your browser, most commonly H.265/HEVC in Firefox or Edge.
   - **Unsupported audio codec**: WebRTC needs opus or G.711 audio, so a stream whose playback audio is only AAC (without an added opus/G.711 track) can't carry audio over WebRTC. See [Audio Support](#audio-support) for how to add one.
@@ -92,7 +92,7 @@ go2rtc:
 
 ### Setting Streams For Live UI
 
-You can configure Frigate to allow manual selection of the stream you want to view in the Live UI. For example, you may want to view your camera's substream on mobile devices, but the full resolution stream on desktop devices. Setting the streams list will populate a dropdown in the UI's Live view that allows you to choose between the streams. This stream setting is _per device_ and is saved in your browser's local storage. When a camera has more than one stream, the dropdown also offers **Auto**, which is used until you pick a specific stream. Auto starts on the first stream, steps down the list when your connection can't keep up, and steps back up when it recovers. To retry the top stream right away, select **Try highest quality** under the stream picker. List streams from highest to lowest quality, and avoid names that are plain numbers (such as `720`), which the browser sorts ahead of the others. In the UI, drag streams to reorder them, or use **Auto order** to sort them by measured bitrate.
+You can configure Frigate to allow manual selection of the stream you want to view in the Live UI. For example, you may want to view your camera's substream on mobile devices, but the full resolution stream on desktop devices. Setting the streams list will populate a dropdown in the UI's Live view that allows you to choose between the streams. This stream setting is _per device_ and is saved in your browser's local storage.
 
 Additionally, when creating and editing camera groups in the UI, you can choose the stream you want to use for your camera group's Live dashboard.
 
@@ -158,26 +158,6 @@ cameras:
 </TabItem>
 </ConfigTabs>
 
-### Transcoded streams
-
-When a camera has no suitable sub stream, Frigate can add lower-quality streams that go2rtc transcodes to H.264 while someone is watching. They appear in the stream list like any other stream, so Auto mode can step down to them. Enable them under <NavPath path="Settings > Camera configuration > Live playback" />, or in YAML:
-
-```yaml
-cameras:
-  test_cam:
-    live:
-      transcode:
-        enabled: true
-        source: test_cam # optional, defaults to the first live stream
-        qualities:
-          - height: 720
-            bitrate: 1200 # kbps
-          - height: 480
-            bitrate: 500
-```
-
-Each quality becomes a go2rtc stream named `<camera>_transcode_<height>p`. go2rtc picks a hardware encoder automatically and falls back to the CPU, which costs CPU for each transcode while it is being watched. Check go2rtc's `api/ffmpeg/hardware` page to see which encoder it found. Using a sub stream as the `source` lowers the cost.
-
 ### WebRTC extra configuration:
 
 WebRTC works by creating a TCP or UDP connection on port `8555`. However, it requires additional configuration:
@@ -383,13 +363,6 @@ When your browser runs into problems playing back your camera streams, it will l
     - `Safari reported InvalidStateError.`
     - `Safari reported decoding errors.`
 
-- **mse-codec**
-  - What it means: go2rtc has no codec for this stream that the browser can play.
-  - What to try: Pick a stream with a codec the browser supports (H.264 is the most compatible), or use a browser that supports the stream's codec. In Auto, Frigate skips this stream for the rest of the session.
-
-  - Possible console messages from the player code:
-    - `mse: streams: codecs not matched: ...`
-
 - **stalled**
   - What it means: Playback has stalled because the player has fallen too far behind live (extended buffering or no data arriving).
   - What to try: This is usually indicative of the browser struggling to decode too many high-resolution streams at once. Try selecting a lower-bandwidth stream (substream), reduce the number of live streams open, improve the network connection, or lower the camera resolution. Also check your camera's keyframe (I-frame) interval: shorter intervals make playback start and recover faster. You can also try increasing the timeout value in <NavPath path="Settings > UI" /> .

docs/docs/configuration/masks.md

@@ -82,13 +82,13 @@ objects:
         person_filter1:
           friendly_name: "Roof area"
           enabled: true
-          coordinates: "0.000,0.000,1.0,0.000,1.0,0.400,0.000,0.400"
+          coordinates: "0.000,0.000,1.000,0.000,1.000,0.400,0.000,0.400"
     car:
       mask:
         car_filter1:
           friendly_name: "Sidewalk area"
           enabled: true
-          coordinates: "0.000,0.700,1.0,0.700,1.0,1.0,0.000,1.0"
+          coordinates: "0.000,0.700,1.000,0.700,1.000,1.000,0.000,1.000"
 ```
 
 </TabItem>

docs/docs/configuration/object_detectors.md

@@ -30,12 +30,10 @@ Frigate supports multiple different detectors that work on different types of ha
 
 - [ROCm](#amdrocm-gpu-detector): ROCm can run on AMD Discrete GPUs to provide efficient object detection.
 - [ONNX](#onnx): ROCm will automatically be detected and used as a detector in the `-rocm` Frigate image when a supported ONNX model is configured.
-- <CommunityBadge /> [XDNA2](#amd-xdna2): AMD Ryzen AI / XDNA2 NPUs can run object detection through the community-maintained `frigate-xdna` ZMQ sidecar.
 
 **Apple Silicon**
 
 - [Apple Silicon](#apple-silicon-detector): Apple Silicon can run on M1 and newer Apple Silicon devices.
-- <CommunityBadge /> [ONNX](#apple-neural-engine-lighter): the ONNX detector runs on the Neural Engine of M1 and newer Macs when Frigate runs under the lighter container runtime.
 
 **Intel**
 
@@ -104,36 +102,32 @@ Coral EdgeTPU and MemryX accelerators can only be opened by one process, so thos
 
 ### Running more than one model
 
-Cameras can be split across models by scene, which is useful when some cameras benefit from a differently trained model, such as thermal cameras. Each model declares the `scene` it is for, and each camera picks one with `detect -> scene`:
+Cameras can be split across models by scene, which is useful when indoor and outdoor cameras benefit from differently trained models. Each model declares the `scene` it is for, and each camera picks one with `detect -> scene`:
 
 ```yaml
 models:
-  - scene: default
-    path: plus://your-model
+  - scene: outdoor
+    path: plus://your-outdoor-model
     devices:
       - edgetpu:pci:0
-  - scene: thermal
-    path: /config/model_cache/thermal.onnx
+  - scene: indoor
+    path: /config/model_cache/indoor.onnx
     model_type: yolo-generic
     devices:
       - openvino:GPU
 
 cameras:
   driveway:
-    ...
-  backyard_thermal:
     detect:
-      scene: thermal
+      scene: outdoor
+    ...
+  hallway:
+    detect:
+      scene: indoor
     ...
 ```
 
-A scene is any name made up of letters, numbers, `_`, and `-`. The model with a scene of `default` is used by every camera that does not set one (or sets a scene that no model is configured for), and `default` is used when a model does not declare a scene. Changing a camera's scene requires a restart.
-
-:::warning
-
-Scenes are for running **different** models. Do not configure the same model under several scenes to dedicate a detector to specific cameras: every detector of a model already serves every camera using it, and splitting them only leaves some detectors idle while others fall behind. Frigate detects models that use the same model file, even under a different path or file name, combines them into one model with all of their hardware, and logs a warning.
-
-:::
+Available scenes are `all`, `indoor`, `outdoor`, `indoor_thermal`, and `outdoor_thermal`. A model with a scene of `all` is used by every camera that does not set one, and `all` is the default when a model does not declare a scene. Changing a camera's scene requires a restart.
 
 ### Choosing a model size
 
@@ -394,22 +388,6 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl
 
 Support for AMD GPUs is provided using the [ONNX detector](#onnx). In order to utilize the AMD GPU for object detection use a frigate docker image with `-rocm` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-rocm`.
 
-### Supported GPUs {#supported-gpus-rocm}
-
-The `-rocm` image includes ROCm support for these GPU chipsets, which work without any chipset override:
-
-| Chipset                                      | Example GPUs                                                             |
-| -------------------------------------------- | ------------------------------------------------------------------------ |
-| gfx1030 (RDNA2)                              | Radeon RX 6800 / 6800 XT / 6900 XT / 6950 XT, Radeon PRO W6800           |
-| gfx1100, gfx1101, gfx1102 (RDNA3)            | Radeon RX 7900 / 7800 / 7700 / 7600 series, Radeon PRO W7000 series      |
-| gfx1103 (RDNA3 integrated)                   | Radeon 780M / 760M in Ryzen 7040, 8040, 8000G, and 200 series processors |
-| gfx1150, gfx1151, gfx1152, gfx1153 (RDNA3.5) | Integrated GPUs in Ryzen AI 300 / 400 series and Ryzen AI Max processors |
-| gfx1200, gfx1201 (RDNA4)                     | Radeon RX 9060 / 9070 series, Radeon AI PRO R9700                        |
-
-Other RDNA2 GPUs (gfx1031 through gfx1036), such as the Radeon RX 6700 / 6600 / 6500 series and the Radeon 680M / 660M integrated GPUs, run on the gfx1030 support by [overriding the chipset](#docker-settings-for-overriding-the-gpu-chipset) to `10.3.0`.
-
-Older GPUs, including RDNA1 (Radeon RX 5000 series) and Vega based dedicated and integrated GPUs, are not supported.
-
 ### Docker settings for GPU access
 
 ROCm needs access to the `/dev/kfd` and `/dev/dri` devices. When docker or frigate is not run under root then also `video` (and possibly `render` and `ssl/_ssl`) groups should be added.
@@ -436,10 +414,19 @@ For reference on recommended settings see [running ROCm/pytorch in Docker](https
 
 ### Docker settings for overriding the GPU chipset
 
-A GPU whose chipset isn't in the [supported GPUs](#supported-gpus-rocm) list can run on the support for a closely related chipset by setting the `HSA_OVERRIDE_GFX_VERSION` environment variable. RDNA2 GPUs other than gfx1030 (gfx1031 through gfx1036) need this, using `10.3.0`:
+Your GPU might work just fine without any special configuration but in many cases they need manual settings. AMD/ROCm software stack comes with a limited set of GPU drivers and for newer or missing models you will have to override the chipset version to an older/generic version to get things working.
+
+Also AMD/ROCm does not "officially" support integrated GPUs. It still does work with most of them just fine but requires special settings. One has to configure the `HSA_OVERRIDE_GFX_VERSION` environment variable. See the [ROCm bug report](https://github.com/ROCm/ROCm/issues/1743) for context and examples.
+
+For the rocm frigate build there is some automatic detection:
+
+- gfx1031 -> 10.3.0
+- gfx1103 -> 11.0.0
+
+If you have something else you might need to override the `HSA_OVERRIDE_GFX_VERSION` at Docker launch. Suppose the version you want is `10.0.0`, then you should configure it from command line as:
 
 ```bash
-$ docker run -e HSA_OVERRIDE_GFX_VERSION=10.3.0 \
+$ docker run -e HSA_OVERRIDE_GFX_VERSION=10.0.0 \
     ...
 ```
 
@@ -450,17 +437,16 @@ services:
   frigate:
     ...
     environment:
-      HSA_OVERRIDE_GFX_VERSION: "10.3.0"
+      HSA_OVERRIDE_GFX_VERSION: "10.0.0"
 ```
 
-GPUs in the supported list don't need an override. An override that was set for the Radeon 780M / 760M (gfx1103) on an earlier version of Frigate is no longer needed and can be removed.
+Figuring out what version you need can be complicated as you can't tell the chipset name and driver from the AMD brand name.
 
-You can't tell the chipset from the AMD brand name, so check it in the container:
-
-- first make sure that the ROCm environment is running properly by running `/opt/rocm/bin/rocminfo` in the Frigate container. It should list both the CPU and the GPU with their properties
-- find the chipset version you have (gfxNNN) from the output of `rocminfo` (see below)
-- if the chipset isn't in the supported list, set `HSA_OVERRIDE_GFX_VERSION` to the closest supported chipset, written as major.minor.stepping (for example gfx1030 is `10.3.0`)
-- if things are not working check the Frigate docker logs
+- first make sure that rocm environment is running properly by running `/opt/rocm/bin/rocminfo` in the frigate container -- it should list both the CPU and the GPU with their properties
+- find the chipset version you have (gfxNNN) from the output of the `rocminfo` (see below)
+- use a search engine to query what `HSA_OVERRIDE_GFX_VERSION` you need for the given gfx name ("gfxNNN ROCm HSA_OVERRIDE_GFX_VERSION")
+- override the `HSA_OVERRIDE_GFX_VERSION` with relevant value
+- if things are not working check the frigate docker logs
 
 #### Figuring out if AMD/ROCm is working and found your GPU
 
@@ -498,7 +484,7 @@ See [ONNX supported models](#onnx) for supported models, there are some caveats:
 
 ## ONNX
 
-ONNX is an open format for building machine learning models, Frigate supports running ONNX models on CPU, OpenVINO, ROCm, TensorRT, and a Mac's Neural Engine. On startup Frigate will automatically try to use a GPU if one is available.
+ONNX is an open format for building machine learning models, Frigate supports running ONNX models on CPU, OpenVINO, ROCm, and TensorRT. On startup Frigate will automatically try to use a GPU if one is available.
 
 :::info
 
@@ -514,9 +500,6 @@ If the correct build is used for your GPU then the GPU will be detected and used
   - Nvidia GPUs will automatically be detected and used with the ONNX detector in the `-tensorrt` Frigate image.
   - Jetson devices will automatically be detected and used with the ONNX detector in the `-tensorrt-jp6` Frigate image.
 
-- **Apple Silicon Mac** <CommunityBadge />
-  - The Neural Engine will automatically be detected and used with the ONNX detector when Frigate runs under lighter with its Neural Engine device. See [Apple Neural Engine (lighter)](#apple-neural-engine-lighter).
-
 :::
 
 :::tip
@@ -532,22 +515,6 @@ models:
 
 :::
 
-### Apple Neural Engine (lighter) {#apple-neural-engine-lighter}
-
-[lighter](https://github.com/fieldwork-ai/lighter) is an open-source container runtime for macOS. A container started with its `lighter.sh/ane` device gets an ONNX Runtime execution provider that runs models on the Mac's Neural Engine, and the ONNX detector uses it automatically, with the same models and configuration as on any other hardware. It works on M1 and newer Macs with lighter 0.9.2 or newer.
-
-Give the Frigate container the Neural Engine device. With Docker Compose:
-
-```yaml
-services:
-  frigate:
-    image: ghcr.io/blakeblackshear/frigate:stable-standard-arm64
-    devices:
-      - lighter.sh/ane=all
-```
-
-Or with `docker run`, add `--device lighter.sh/ane=all`. Frigate then reports the Neural Engine under **Settings > System > Detection models**, and the ONNX detector's model loads on it. lighter can also decode camera streams on the Mac's media engine; see [Video Decoding](hardware_acceleration_video.md#apple-silicon-mac-lighter).
-
 ### Configuration {#configuration-onnx}
 
 <ModelConfigDropdown detectorTitle="ONNX" models={objectDetectorsModels.onnx.models} />
@@ -576,28 +543,6 @@ When using CPU detectors, you can add one CPU detector per camera. Adding more d
 
 # Community Supported Detectors
 
-## AMD XDNA2
-
-AMD Ryzen AI / XDNA2 NPUs can be used through the community-maintained
-[frigate-xdna](https://github.com/mitchins/frigate-xdna) detector sidecar.
-The sidecar runs separately from Frigate and connects using Frigate's ZMQ
-detector interface.
-
-Currently qualified on **Ryzen AI Max 300 / Strix Halo**. Other XDNA2 devices
-are not yet qualified; XDNA1 is unsupported.
-
-Follow the frigate-xdna setup instructions to prepare and start the sidecar
-before starting Frigate.
-
-### Configuration {#configuration-xdna2}
-
-Using the detector config below will connect Frigate to the sidecar:
-
-<ModelConfigDropdown detectorTitle="AMD XDNA2" models={objectDetectorsModels.xdna2.models} />
-
-The example assumes Frigate and the sidecar share a Docker network where the
-sidecar is named `xdna`.
-
 ## MemryX MX3
 
 This detector is available for use with the MemryX MX3 accelerator M.2 module. Frigate supports the MX3 on compatible hardware platforms, providing efficient and high-performance object detection.

docs/docs/configuration/object_filters.md

@@ -45,10 +45,10 @@ Any detection below `min_score` will be immediately thrown out and never tracked
 
 Navigate to <NavPath path="Settings > Global configuration > Objects" /> to set score filters globally.
 
-| Field                                              | Description                                                      |
-| -------------------------------------------------- | ---------------------------------------------------------------- |
-| **Object filters > Person > Minimum confidence**   | Minimum score for a single detection to initiate tracking        |
-| **Object filters > Person > Confidence threshold** | Minimum computed (median) score to be considered a true positive |
+| Field                                   | Description                                                      |
+| --------------------------------------- | ---------------------------------------------------------------- |
+| **Object filters > Person > Min Score** | Minimum score for a single detection to initiate tracking        |
+| **Object filters > Person > Threshold** | Minimum computed (median) score to be considered a true positive |
 
 To override score filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" /> and select the camera.
 
@@ -103,12 +103,12 @@ Conceptually, a ratio of 1 is a square, 0.5 is a "tall skinny" box, and 2 is a "
 
 Navigate to <NavPath path="Settings > Global configuration > Objects" /> to set shape filters globally.
 
-| Field                                              | Description                                                              |
-| -------------------------------------------------- | ------------------------------------------------------------------------ |
-| **Object filters > Person > Minimum object area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Maximum object area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Minimum aspect ratio** | Minimum width/height ratio of the bounding box                           |
-| **Object filters > Person > Maximum aspect ratio** | Maximum width/height ratio of the bounding box                           |
+| Field                                   | Description                                                              |
+| --------------------------------------- | ------------------------------------------------------------------------ |
+| **Object filters > Person > Min Area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Max Area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Min Ratio** | Minimum width/height ratio of the bounding box                           |
+| **Object filters > Person > Max Ratio** | Maximum width/height ratio of the bounding box                           |
 
 To override shape filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" /> and select the camera.
 

docs/docs/configuration/objects.md

@@ -70,14 +70,14 @@ Object filters help reduce false positives by constraining the size, shape, and
 
 Navigate to <NavPath path="Settings > Global configuration > Objects" />.
 
-| Field                                              | Description                                                              |
-| -------------------------------------------------- | ------------------------------------------------------------------------ |
-| **Object filters > Person > Minimum object area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Maximum object area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Minimum aspect ratio** | Minimum width/height ratio of the bounding box                           |
-| **Object filters > Person > Maximum aspect ratio** | Maximum width/height ratio of the bounding box                           |
-| **Object filters > Person > Minimum confidence**   | Minimum score for the object to initiate tracking                        |
-| **Object filters > Person > Confidence threshold** | Minimum computed score to be considered a true positive                  |
+| Field                                   | Description                                                              |
+| --------------------------------------- | ------------------------------------------------------------------------ |
+| **Object filters > Person > Min Area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Max Area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Min Ratio** | Minimum width/height ratio of the bounding box                           |
+| **Object filters > Person > Max Ratio** | Maximum width/height ratio of the bounding box                           |
+| **Object filters > Person > Min Score** | Minimum score for the object to initiate tracking                        |
+| **Object filters > Person > Threshold** | Minimum computed score to be considered a true positive                  |
 
 To override filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" />.
 

docs/docs/configuration/profiles.md

@@ -191,12 +191,14 @@ cameras:
     detect:
       enabled: false
     record:
-      enabled: true
+      enabled: false
     profiles:
       away:
         enabled: true
         detect:
           enabled: true
+        record:
+          enabled: true
       home:
         enabled: false
 ```
@@ -249,12 +251,6 @@ Leaving the `objects` section empty (or omitting `track`) does not clear the lis
 
 Fields that require a Frigate restart to take effect cannot be overridden by profiles, since profiles are applied at runtime without restarting. Those fields are hidden when editing a profile override and can only be changed on the base configuration.
 
-### Why can't a profile enable recording when it's disabled in the base config?
-
-Frigate only sets up a camera's recording stream at startup when recording is enabled in the base config, so enabling it later from a profile has no effect. The same applies to turning recording on from the UI or MQTT.
-
-To keep recording off by default, leave `record.enabled: true` in the base config and create a profile that sets `record.enabled: false`. Activate that profile and it will be restored automatically when Frigate starts.
-
 ### Can I schedule profiles to be enabled or disabled at certain times?
 
 Not within Frigate itself. Frigate is an NVR, not an automation platform, so it intentionally does not include a scheduler for activating profiles. Instead, activate profiles from an automation platform that already handles time- and event-based triggers well, such as [Home Assistant](https://www.home-assistant.io/) or [Node-RED](https://nodered.org/). These integrate with Frigate and give you far more robust and flexible scheduling than a built-in scheduler could.

docs/docs/configuration/semantic_search.md

@@ -133,12 +133,13 @@ Switching between V1 and V2 requires reindexing your embeddings. The embeddings
 
 ### GenAI Provider
 
-Frigate can use a GenAI provider for semantic search embeddings when that provider has the `embeddings` role. See [Provider support](/configuration/genai/genai_config#provider-support) for which providers can serve this role.
+Frigate can use a GenAI provider for semantic search embeddings when that provider has the `embeddings` role. Currently, only **llama.cpp** supports multimodal embeddings (both text and images).
 
-To use a GenAI provider for semantic search:
+To use llama.cpp for semantic search:
 
-1. Configure a GenAI provider with `embeddings` in its `roles`, using a multimodal embedding model (both text and images). See [Embedding models](/configuration/genai/genai_config#embedding-models) for recommendations, and your provider's section of the [GenAI docs](/configuration/genai/genai_config) for any extra setup it needs.
+1. Configure a GenAI provider with `embeddings` in its `roles`.
 2. Set the semantic search model to the GenAI config key (e.g. `default`).
+3. Start the llama.cpp server with `--embeddings` and `--mmproj` for image support.
 
 <ConfigTabs>
 <TabItem value="ui">
@@ -173,6 +174,8 @@ semantic_search:
 </TabItem>
 </ConfigTabs>
 
+The llama.cpp server must be started with `--embeddings` for the embeddings API, and a multi-modal embeddings model. See the [llama.cpp server documentation](https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md) for details.
+
 :::note
 
 Switching between Jina models and a GenAI provider requires reindexing. Embeddings from different backends are incompatible.
@@ -242,8 +245,8 @@ Triggers are best configured through the Frigate UI.
 1. Navigate to <NavPath path="Settings > Enrichments > Triggers" /> and select a camera from the dropdown menu.
 2. Click **Add Trigger** to create a new trigger or use the pencil icon to edit an existing one.
 3. In the **Create Trigger** wizard:
-   - Enter a **Name** for the trigger (e.g., "Red Car Alert"). Frigate derives the trigger's
-     internal **ID** from this name, which can be revealed and edited with the show/hide toggle.
+   - Enter a **Name** for the trigger (e.g., "Red Car Alert").
+   - Enter a descriptive **Friendly Name** for the trigger (e.g., "Red car on the driveway camera").
    - Select the **Type** (`Thumbnail` or `Description`).
    - For `Thumbnail`, select an image to trigger this action when a similar thumbnail image is detected, based on the threshold.
    - For `Description`, enter text to trigger this action when a similar tracked object description is detected.

docs/docs/configuration/zones.md

@@ -28,7 +28,7 @@ During testing, enable the Zones option for the [Debug view](/usage/live#the-sin
 1. Navigate to <NavPath path="Settings > Camera configuration > Masks / Zones" /> and select the desired camera.
 2. Under the **Zones** section, click the plus icon to add a new zone.
 3. Click on the camera's latest image to create the points for the zone boundary. Click the first point again to close the polygon.
-4. Configure zone options such as **Name**, **Objects**, **Loitering Time**, and **Inertia** in the zone editor.
+4. Configure zone options such as **Friendly name**, **Objects**, **Loitering time**, and **Inertia** in the zone editor.
 5. Press **Save** when finished.
 
 </TabItem>
@@ -200,7 +200,7 @@ When using loitering zones, a review item will behave in the following way:
 
 1. Navigate to <NavPath path="Settings > Camera configuration > Masks / Zones" /> and select the desired camera.
 2. Edit or create the zone (e.g., `sidewalk`).
-   - Set **Loitering Time** to the desired number of seconds (e.g., `4`)
+   - Set **Loitering time** to the desired number of seconds (e.g., `4`)
    - Under **Objects**, add the relevant object types (e.g., `person`)
 
 </TabItem>
@@ -291,7 +291,7 @@ Accurate real-world distance measurements are required to estimate speeds. These
 
 1. Navigate to <NavPath path="Settings > Camera configuration > Masks / Zones" /> and select the desired camera.
 2. Create or edit a zone with exactly 4 points aligned to the ground plane.
-3. In the zone editor, enable **Speed Estimation** and enter the real-world **Line A distance**, **Line B distance**, **Line C distance**, and **Line D distance** between each pair of consecutive points.
+3. In the zone editor, enter the real-world **Distances** between each pair of consecutive points.
    - For example, if the distance between the first and second points is 10 meters, between the second and third is 12 meters, etc.
 4. Distances are measured in meters (metric) or feet (imperial), depending on the **Unit system** setting.
 
@@ -358,7 +358,7 @@ Zones can be configured with a minimum speed requirement, meaning an object must
 
 1. Navigate to <NavPath path="Settings > Camera configuration > Masks / Zones" /> and select the desired camera.
 2. Edit or create the zone with distances configured.
-   - Set **Speed Threshold** to the desired minimum speed (e.g., `20`)
+   - Set **Speed threshold** to the desired minimum speed (e.g., `20`)
    - The unit is kph or mph, depending on the **Unit system** setting
 
 </TabItem>

docs/docs/frigate/glossary.md

@@ -54,7 +54,7 @@ An object filter mask drops any [bounding box](#bounding-box) whose bottom cente
 
 ## Min Score
 
-The lowest score a detected object can have to be kept during tracking. Anything scoring below the minimum is assumed to be a [false positive](#false-positive) and discarded. Set with `min_score` in the config, shown as **Minimum confidence** in the settings UI.
+The lowest score a detected object can have to be kept during tracking. Anything scoring below the minimum is assumed to be a [false positive](#false-positive) and discarded.
 
 ## Model
 
@@ -86,7 +86,7 @@ A more specific identity assigned to a [tracked object](#tracked-object-event-in
 
 ## Threshold
 
-The median score an object must reach to be considered a true positive. Set with `threshold` in the config, shown as **Confidence threshold** in the settings UI.
+The median score an object must reach to be considered a true positive.
 
 ## Top Score
 

docs/docs/frigate/hardware.md

@@ -72,19 +72,12 @@ Frigate supports multiple different detectors that work on different types of ha
 
 **AMD**
 
-- [ROCm](#rocm---amd-gpu): ROCm can run on AMD discrete and recent integrated GPUs to provide efficient object detection
+- [ROCm](#rocm---amd-gpu): ROCm can run on AMD Discrete GPUs to provide efficient object detection
   - [Supports limited model architectures](../../configuration/object_detectors#amdrocm-gpu-detector)
   - Runs best on discrete AMD GPUs
-- <CommunityBadge /> [XDNA2 (Ryzen AI)](#amd-xdna2): AMD XDNA2 NPU (sub-watt power AI/ML processor separate to the GPU) inside Strix and other "AI" branded AMD platforms
-  - Has only been tested with YOLOv9, in theory other graphs may be compiled too.
-  - Runs via ZMQ proxy which adds some latency, only recommended for local connection
 
 **Apple Silicon**
 
-- [ONNX via lighter](#apple-silicon): The ONNX detector runs on the Neural Engine of M1 and newer Macs when Frigate runs in the lighter container runtime
-  - [Supports the same model architectures as the ONNX detector](../../configuration/object_detectors#apple-neural-engine-lighter)
-  - Runs inside the Frigate container, with no separate detector process to set up
-  - The recommended way to run Frigate on a Mac
 - [Apple Silicon](#apple-silicon): Apple Silicon is usable on all M1 and newer Apple Silicon devices to provide efficient and fast object detection
   - [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#apple-silicon-detector)
   - Runs well with any size models including large
@@ -189,7 +182,7 @@ Frigate is able to utilize an Nvidia GPU which supports the 12.x series of CUDA
 
 #### Minimum Hardware Support
 
-12.x series of CUDA libraries are used which have minor version compatibility. The minimum driver version on the host system must be `>=545`. The oldest supported GPU generation for object detection is Pascal (Compute Capability 6.0 or greater). Older generations such as Maxwell are not supported but can still be used by following a [community workaround](https://github.com/blakeblackshear/frigate/discussions/20088). For other GPUs, check the NVIDIA GPU Compute Capability table linked below.
+12.x series of CUDA libraries are used which have minor version compatibility. The minimum driver version on the host system must be `>=545`. 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.
 
 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.
 
@@ -218,13 +211,7 @@ Inference is done with the `onnx` detector type. Speeds will vary greatly depend
 
 ### Apple Silicon
 
-Frigate on a Mac is best run in the [lighter](https://github.com/fieldwork-ai/lighter) container runtime, where the [ONNX detector](../configuration/object_detectors.md#apple-neural-engine-lighter) runs on the Neural Engine of M1 and newer Macs from inside the Frigate container. There is no separate detector process to install or keep running, and the same container can decode video on the Mac's media engine.
-
-| Name | YOLOv9 Inference Time                  | YOLO-NAS Inference Time | RF-DETR Inference Time |
-| ---- | -------------------------------------- | ----------------------- | ---------------------- |
-| M1   | t-320: 3.3 ms s-320: 7 ms s-640: 13 ms | 320: 6.6 ms             | Nano-320: 38 ms        |
-
-Alternatively, with the [Apple Silicon](../configuration/object_detectors.md#apple-silicon-detector) detector Frigate can take advantage of the NPU in M1 and newer Apple Silicon.
+With the [Apple Silicon](../configuration/object_detectors.md#apple-silicon-detector) detector Frigate can take advantage of the NPU in M1 and newer Apple Silicon.
 
 :::warning
 
@@ -240,7 +227,7 @@ Apple Silicon can not run within a container, so a ZMQ proxy is utilized to comm
 
 ### ROCm - AMD GPU
 
-With the [ROCm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many AMD discrete and integrated GPUs, see the [supported GPUs](../configuration/object_detectors.md#supported-gpus-rocm).
+With the [ROCm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many discrete AMD GPUs.
 
 | Name           | YOLOv9 Inference Time       | YOLO-NAS Inference Time   | RF-DETR Inference Time |
 | -------------- | --------------------------- | ------------------------- | ---------------------- |
@@ -341,32 +328,6 @@ The inference time of a rk3588 with all 3 cores enabled is typically 25-30 ms fo
 | ---------------- | ----------------------------------- |
 | yolov9-tiny      | ~ 4 ms                              |
 
-### AMD Ryzen AI / XDNA2
-
-Frigate supports AMD XDNA2 NPUs through the community-maintained
-frigate-xdna ZMQ sidecar. It works with stock Frigate and supports
-Frigate+ models or compatible local YOLO ONNX models. Models are compiled
-once on the target system and cached for subsequent use.
-
-Currently qualified on **Ryzen AI Max 300 / Strix Halo**. Other XDNA2
-devices are not yet qualified; XDNA1 is unsupported.
-
-Measured YOLOv9 detector latency on Strix Halo:
-
-| Model | 320 | 640 |
-| ----- | ---: | ---: |
-| YOLOv9-T | ~7.4 ms | unsupported |
-| YOLOv9-S | ~9.0 ms | ~20.0 ms |
-| YOLOv9-M | ~13.1 ms | ~34.4 ms |
-| YOLOv9-C | ~14.1 ms | ~35.2 ms |
-| YOLOv9-E | ~69.4 ms | ~224.8 ms |
-
-**YOLOv9-C at 320 is the recommended quality/performance balance.**
-C at 640 is also usable where the lower throughput is acceptable.
-
-Setup, model preparation, and compatibility details are available
-[in the frigate-xdna documentation](https://github.com/mitchins/frigate-xdna).
-
 ## 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.

docs/docs/frigate/installation.md

@@ -78,9 +78,9 @@ Users of the Snapcraft build of Docker cannot use storage locations outside your
 
 Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is **64MB**.
 
-Frigate needs about **210MB** for **2 cameras** detecting at **720p**. If Frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size, using [`--shm-size`](https://docs.docker.com/engine/reference/run/#runtime-constraints-on-resources) (or [`service.shm_size`](https://docs.docker.com/compose/compose-file/compose-file-v2/#shm_size) in Docker Compose). If raising the shm size does not help, check your [process and file limits](#process-and-file-limits) as well.
+The default shm size of **128MB** is fine for setups with **2 cameras** detecting at **720p**. If Frigate is exiting with "Bus error" messages, it is likely because you have too many high resolution cameras and you need to specify a higher shm size, using [`--shm-size`](https://docs.docker.com/engine/reference/run/#runtime-constraints-on-resources) (or [`service.shm_size`](https://docs.docker.com/compose/compose-file/compose-file-v2/#shm_size) in Docker Compose). If raising the shm size does not help, check your [process and file limits](#process-and-file-limits) as well.
 
-The Frigate container also stores logs and an nginx cache in shm, which can take up to **50MB**. The calculator below includes this, along with room for 2 cameras added while Frigate is running. Its result holds about 25 frames per camera, a little above the 20 frame minimum Frigate warns below. Frigate keeps up to 50 when there is room, which gives slow processes more time to read each frame.
+The Frigate container also stores logs in shm, which can take up to **40MB**, so make sure to take this into account in your math as well.
 
 <ShmCalculator/>
 

docs/docs/frigate/network_requirements.md

@@ -134,6 +134,15 @@ telemetry:
   version_check: false
 ```
 
+### Anonymous Analytics
+
+If [anonymous analytics](/configuration/advanced/analytics) sharing is turned on, Frigate sends one report a day to `https://analytics.frigate.video`. It's off by default, so no outbound connection happens unless you enable it:
+
+```yaml
+telemetry:
+  analytics: true
+```
+
 ### Push Notifications
 
 When [notifications](/configuration/notifications) are enabled and users have registered for push notifications in the web UI, Frigate sends push messages through the browser vendor's push service (e.g., Google FCM, Mozilla autopush). This requires internet access from the Frigate server to these push endpoints.
@@ -170,7 +179,7 @@ To run Frigate in an air-gapped or offline environment:
 2. **Pre-download the training base weights**: If you plan to train custom classification models, set `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` before training, then run one training job while online. Without this variable the base weights are cached outside `/config/` and are lost whenever the container is recreated, so a later training run will fail offline. If the machine never has internet access, copy the weights in manually as described below.
 3. **Disable version check**: Set `telemetry.version_check: false` in your configuration.
 4. **Block outbound model requests**: Set the `HF_HUB_OFFLINE=1` and `TRANSFORMERS_OFFLINE=1` environment variables to prevent HuggingFace and Transformers from attempting any network requests.
-5. **Avoid cloud features**: Do not configure Frigate+, Generative AI providers that require internet, or cloud MQTT brokers.
+5. **Avoid cloud features**: Do not configure Frigate+, Generative AI providers that require internet, or cloud MQTT brokers, and leave anonymous analytics off (its default).
 6. **Use local model mirrors**: If limited internet is available, set the `HF_ENDPOINT`, `GITHUB_ENDPOINT`, `GITHUB_RAW_ENDPOINT`, and `TF_KERAS_MOBILENET_V2_WEIGHTS_URL` environment variables to point to local mirrors.
 
 After these steps, Frigate will operate with no outbound internet connections.

docs/docs/frigate/updating.md

@@ -5,7 +5,7 @@ title: Updating
 
 # Updating Frigate
 
-The current stable version of Frigate is **0.18.2**. The release notes and any breaking changes for this version can be found on the [Frigate GitHub releases page](https://github.com/blakeblackshear/frigate/releases/tag/v0.18.2).
+The current stable version of Frigate is **0.18.0**. The release notes and any breaking changes for this version can be found on the [Frigate GitHub releases page](https://github.com/blakeblackshear/frigate/releases/tag/v0.18.0).
 
 Keeping Frigate up to date ensures you benefit from the latest features, performance improvements, and bug fixes. The update process varies slightly depending on your installation method (Docker, Home Assistant App, etc.). Below are instructions for the most common setups.
 
@@ -31,21 +31,21 @@ If you’re running Frigate via Docker (recommended method), follow these steps:
 
 2. **Update and Pull the Latest Image**:
    - If using Docker Compose:
-     - Edit your `docker-compose.yml` file to specify the desired version tag (e.g., `0.18.2` instead of `0.17.1`). For example:
+     - Edit your `docker-compose.yml` file to specify the desired version tag (e.g., `0.18.0` instead of `0.17.1`). For example:
        ```yaml
        services:
          frigate:
-           image: ghcr.io/blakeblackshear/frigate:0.18.2
+           image: ghcr.io/blakeblackshear/frigate:0.18.0
        ```
      - Then pull the image:
        ```bash
-       docker pull ghcr.io/blakeblackshear/frigate:0.18.2
+       docker pull ghcr.io/blakeblackshear/frigate:0.18.0
        ```
      - **Note for `stable` Tag Users**: If your `docker-compose.yml` uses the `stable` tag (e.g., `ghcr.io/blakeblackshear/frigate:stable`), you don’t need to update the tag manually. The `stable` tag always points to the latest stable release after pulling.
    - If using `docker run`:
-     - Pull the image with the appropriate tag (e.g., `0.18.2`, `0.18.2-tensorrt`, or `stable`):
+     - Pull the image with the appropriate tag (e.g., `0.18.0`, `0.18.0-tensorrt`, or `stable`):
        ```bash
-       docker pull ghcr.io/blakeblackshear/frigate:0.18.2
+       docker pull ghcr.io/blakeblackshear/frigate:0.18.0
        ```
 
 3. **Start the Container**:
@@ -100,7 +100,7 @@ If an update causes issues:
 1. Stop Frigate.
 2. Restore your backed-up config file and database.
 3. Revert to the previous image version:
-   - For Docker: Specify an older tag (e.g., `ghcr.io/blakeblackshear/frigate:0.18.1`) in your `docker run` command.
+   - For Docker: Specify an older tag (e.g., `ghcr.io/blakeblackshear/frigate:0.17.1`) in your `docker run` command.
    - For Docker Compose: Edit your `docker-compose.yml`, specify the older version tag (e.g., `ghcr.io/blakeblackshear/frigate:0.16.4`), and re-run `docker compose up -d`.
    - For Home Assistant: Restore from the app/addon backup you took before you updated.
 4. Verify the old version is running again.

docs/docs/guides/reverse_proxy.md

@@ -45,8 +45,6 @@ There are many solutions available to implement reverse proxies and the communit
 - [Nginx](#nginx-reverse-proxy)
 - [Traefik](#traefik-reverse-proxy)
 - [Caddy](#caddy-reverse-proxy)
-- [HAProxy](#haproxy)
-- [OPNSense HAProxy Add-on](#opnsense-haproxy-add-on)
 
 ## Apache2 Reverse Proxy
 
@@ -220,68 +218,3 @@ frigate.YOUR_DOMAIN.TLD {
 }
 
 ```
-
-## HAProxy
-
-This example is for a pure haproxy installation on a dedicated host. It assumes you have already combined the certificate parts in de cert file.
-
-The frontend config:
-```# Public Service: SSLSecured (Frigate)
-frontend SSLSecured
-    bind XXX.XXX.XXX.XXX:443 ssl crt /etc/haproxy/certs/frigate.cert
-    mode http
-    option http-keep-alive
-    default_backend NVR
-
-    # CONDITION: NVR
-    acl acl_frigate hdr(host) -i nvr.example.video
-
-    # RULE: NVR
-    use_backend NVR if acl_frigate
-```
-
-The backend config:
-```# Backend Pool: NVR (Frigate)
-backend NVR
-    mode http
-    balance source
-    # stickiness
-    stick-table type ipv4 size 50k expire 30m  
-    stick on src
-    http-reuse safe
-    server Frigate XXX.XXX.XXX.XXX:8971
-```
-The above config is created for a Layer 7 proxy (application layer, in this case http), if streaming the camera feeds are a little spotty or somewhat unstable, you can try to change the *mode* from http to tcp in both the frontend and backend config, which sets up a Layer 4 proxy (proxy by protocol). Make sure you change hdr(host) to req.ssl_sni in the frontend Condition to make the host based condition work on tcp traffic. 
-
-## OPNSense HAProxy add-on
-
-This guide is for the OPNSense firewall add-on *os-haproxy* and is configured and tested on version 5.1 of the add-on on OPNSense 26.7.
-The guide starts where you are already done setting up the system, *have a certificate added to the certificate store* and *installed the plugin/add-on*.
-
-Step by step plan:
-1. Go to Services -> HAProxy, click on Settings;
-2. Add a Real Server under *Real Servers*;
-3. Fill in the fields *Name or Prefix* and *Description*;
-4. set *Type* to **static**;
-5. fill in the frigate IP in the *FQDN or IP* field;
-6. under *Common Options* fill *Port* with the port number for your Frigate (e.g. 8971) and
-7. Click **Save** to store this configuration.
-8. Under *Virtual Services* open *Backend Pools*;
-9. Add a *Backend Pool*;
-10. Fill in the fields *Name or Prefix* and *Description* but use something else then what you used under *Real Servers* otherwise if and when rules and conditions are needed it gets really confusing really fast, the use of them is out of the scope of this guide for a basic functioning haproxy add-on;
-11. set *Mode* to **HTTP (Layer 7)**;
-12. set *Balancing Algorithm* to **Source-IP Hash**;
-13. set *Servers* by choosing the *Real Servers* instance you added in step 2->6;
-14. Click **Save** to store this configuration.
-15. Under *Virtual Services* open *Public Services*;
-16. Add a *Public Service*;
-17. Fill in the fields *Name or Prefix* and *Description* but use something else then what you used under *Real Servers* otherwise if and when rules and conditions are needed it gets really confusing really fast, the use of them is out of the scope of this guide for a basic functioning haproxy add-on;
-18. Fill in the external address the haproxy instance will be listening on in *Listen Addresses*;
-19. set *Type* to **HTTP/HTTPS (SSL offloading)**
-20. set *Default Backend Pool* to the option carrying *the name you used in step 9*;
-21. check *Enable SSL Offloading*;
-22. Under *SSL Offloading* you set *Default certificate* to the certificate you added before you started following this guide;
-23. Click **Save** to store this configuration.
-24. Click **Apply** to reload the haproxy config on the service running.
-
-**NOTE: This will forward _ALL_ requests on port 443 to your frigate instance.** If that is not what you want or have more then one website alive behind the haproxy you will need to create a *Condition* to trigger when the right URL is used and a *Rules* rule to use the right backend under *Rules & Checks* when the condition is met. This is a useful hint for those who need it, though it is out of the scope of this guide.

docs/docs/integrations/mqtt.md

@@ -11,12 +11,6 @@ MQTT requires a network connection to your broker. This is typically local, but
 
 :::
 
-:::note
-
-Wherever a topic below includes a camera, mask, or zone name, use its `ID` from the config, not its `friendly_name`. For example, a camera with `friendly_name: "Back Yard"` and ID `back_yard` publishes to `frigate/back_yard/...`, not `frigate/Back Yard/...`.
-
-:::
-
 ## General Frigate Topics
 
 ### `frigate/available`
@@ -218,7 +212,6 @@ An `update` with the same ID will be published when:
 - The severity changes from `detection` to `alert`
 - Additional objects are detected
 - An object is recognized via face, lpr, etc.
-- A [state classification](/configuration/custom_classification/state_classification#review-items) model changes state
 
 When the review activity has ended a final `end` message is published.
 
@@ -242,8 +235,7 @@ When the review activity has ended a final `end` message is published.
       "objects": ["person", "car"],
       "sub_labels": [],
       "zones": [],
-      "audio": [],
-      "classification_state_changes": []
+      "audio": []
     }
   },
   "after": {
@@ -262,16 +254,7 @@ When the review activity has ended a final `end` message is published.
       "objects": ["person", "car"],
       "sub_labels": ["Bob"],
       "zones": ["front_yard"],
-      "audio": [],
-      "classification_state_changes": [
-        // verified changes of state classification models on this camera
-        {
-          "model": "front_gate",
-          "from": "closed",
-          "to": "open",
-          "timestamp": 1718987131.52
-        }
-      ]
+      "audio": []
     }
   }
 }

docs/docs/integrations/third_party_extensions.md

@@ -27,10 +27,6 @@ The [Advanced Camera Card](https://card.camera/#/README) is a Home Assistant das
 It supports automatically setting the sub labels in Frigate for person objects that are detected and recognized.
 This is a fork (with fixed errors and new features) of [original Double Take](https://github.com/jakowenko/double-take) project which, unfortunately, isn't being maintained by author.
 
-## [frigate-abr](https://github.com/007hacky007/frigate-abr)
-
-[frigate-abr](https://github.com/007hacky007/frigate-abr) is a drop-in Docker image of Frigate that adds adaptive bitrate (ABR) playback for recordings: a sidecar transcodes footage to lower quality tiers on demand, for reviewing over slow remote connections. Segments are transcoded when played and cached, so no additional stream is recorded. Frigate itself is not modified.
-
 ## [Frigate Notify](https://github.com/0x2142/frigate-notify)
 
 [Frigate Notify](https://github.com/0x2142/frigate-notify) is a simple app designed to send notifications from Frigate to your favorite platforms. Intended to be used with standalone Frigate installations - Home Assistant not required, MQTT is optional but recommended.

docs/docs/plus/faq.md

@@ -21,13 +21,7 @@ Yes. Models and metadata are stored in the `model_cache` directory within the co
 
 ### Can I keep using my Frigate+ models even if I do not renew my subscription?
 
-Yes. Subscriptions to Frigate+ provide access to the infrastructure used to train the models. Models you train during an active subscription remain licensed for your continued use even after your subscription ends — models already in your model cache will keep working indefinitely. An active subscription is required to train new models and download new versions.
-
-### Can I use Frigate+ models commercially?
-
-A standard subscription covers use on camera systems you own or operate, including for your business. A shop, restaurant, warehouse, or office running Frigate+ at its own locations (including multiple locations) is exactly the kind of use the subscription is for.
-What the standard subscription does not cover is using Frigate+ models to provide a product or service to others. If you're deploying models at your customers' sites, bundling them with hardware you sell, or running them as part of a hosted or managed service, even if your customers never receive the model files themselves, you'll need a commercial license.
-Note that professional installers are fine under standard subscriptions when each customer holds their own Frigate+ subscription. The commercial license is for cases where your license powers your customers' sites.
+Yes. Subscriptions to Frigate+ provide access to the infrastructure used to train the models. Models trained with your subscription are yours to keep and use forever. However, do note that the terms and conditions prohibit you from sharing, reselling, or creating derivative products from the models.
 
 ### Why can't I submit images to Frigate+?
 

docs/docs/plus/first_model.md

@@ -63,20 +63,20 @@ Frigate+ models generally have much higher scores than the default model provide
 <ConfigTabs>
 <TabItem value="ui">
 
-Navigate to <NavPath path="Settings > Global configuration > Objects" />. Under **Object filters**, set **Minimum confidence** and **Confidence threshold** for each object type, then click **Save**.
+Navigate to <NavPath path="Settings > Global configuration > Objects" />. Under **Object filters**, set **Min Score** and **Threshold** for each object type, then click **Save**.
 
-| Object            | Minimum confidence | Confidence threshold |
-| ----------------- | ------------------ | -------------------- |
-| **dog**           | .7                 | .9                   |
-| **cat**           | .65                | .8                   |
-| **face**          | .7                 |                      |
-| **package**       | .65                | .9                   |
-| **license_plate** | .6                 |                      |
-| **amazon**        | .75                |                      |
-| **ups**           | .75                |                      |
-| **fedex**         | .75                |                      |
-| **person**        | .65                | .85                  |
-| **car**           | .65                | .85                  |
+| Object            | Min Score | Threshold |
+| ----------------- | --------- | --------- |
+| **dog**           | .7        | .9        |
+| **cat**           | .65       | .8        |
+| **face**          | .7        |           |
+| **package**       | .65       | .9        |
+| **license_plate** | .6        |           |
+| **amazon**        | .75       |           |
+| **ups**           | .75       |           |
+| **fedex**         | .75       |           |
+| **person**        | .65       | .85       |
+| **car**           | .65       | .85       |
 
 </TabItem>
 <TabItem value="yaml">

docs/docs/plus/index.md

@@ -65,11 +65,11 @@ Some users may find that Frigate+ models result in more false positives initiall
 
 Frigate+ models support a more relevant set of objects for security cameras. The labels for annotation in Frigate+ are configurable by editing the camera in the Cameras section of Frigate+. Currently, the following objects are supported:
 
-- **People**: `person`, `face`, `baby`
-- **Vehicles**: `car`, `motorcycle`, `bicycle`, `boat`, `school_bus`, `garbage truck`, `license_plate`
+- **People**: `person`, `face`
+- **Vehicles**: `car`, `motorcycle`, `bicycle`, `boat`, `school_bus`, `license_plate`
 - **Delivery Logos**: `amazon`, `usps`, `ups`, `fedex`, `dhl`, `an_post`, `purolator`, `postnl`, `nzpost`, `postnord`, `gls`, `dpd`, `canada_post`, `royal_mail`
-- **Animals**: `dog`, `cat`, `deer`, `horse`, `bird`, `raccoon`, `fox`, `bear`, `cow`, `squirrel`, `goat`, `rabbit`, `skunk`, `kangaroo`, `possum`, `rodent`
-- **Other**: `package`, `waste_bin`, `bbq_grill`, `robot_lawnmower`, `umbrella`, `baby_stroller`
+- **Animals**: `dog`, `cat`, `deer`, `horse`, `bird`, `raccoon`, `fox`, `bear`, `cow`, `squirrel`, `goat`, `rabbit`, `skunk`, `kangaroo`
+- **Other**: `package`, `waste_bin`, `bbq_grill`, `robot_lawnmower`, `umbrella`
 
 Other object types available in the default Frigate model are not available. Additional object types will be added in future releases.
 
@@ -77,12 +77,9 @@ Other object types available in the default Frigate model are not available. Add
 
 Candidate labels are also available for annotation. These labels don't have enough data to be included in the model yet, but using them will help add support sooner. You can enable these labels by editing the camera settings.
 
-Where possible, these labels are mapped to existing labels during training. For example, any `duck` labels are mapped to `bird` until support for new labels is added.
+Where possible, these labels are mapped to existing labels during training. For example, any `baby` labels are mapped to `person` until support for new labels is added.
 
-- **Vehicles**: `tractor`, `golf_cart`, `bus`, `airplane`, `helicopter`, `rickshaw`, `scooter`
-- **Delivery Logos**: `bpost`, `auspost`, `aramex`, `transoflex`, `parcelforce`, `hermes`, `cargus`, `fan_courier`, `sameday`, `la_poste`
-- **Animals**: `badger`, `chicken`, `duck`, `turkey`, `groundhog`, `boar`, `hedgehog`, `wombat`, `bobcat`, `mustelid`, `mountain_lion`, `crocodile`, `monkey`, `coyote`, `porcupine`, `sheep`, `snake`, `lizard`, `heron`, `elk`, `moose`, `pig`, `donkey`, `civet`
-- **Other**: `sports_ball`, `drone`, `lawnmower`
+The candidate labels are: `baby`, `bpost`, `badger`, `possum`, `rodent`, `chicken`, `groundhog`, `boar`, `hedgehog`, `tractor`, `golf cart`, `garbage truck`, `bus`, `sports ball`, `la_poste`, `lawnmower`, `heron`, `rickshaw`, `wombat`, `auspost`, `aramex`, `bobcat`, `mustelid`, `transoflex`, `airplane`, `drone`, `mountain_lion`, `crocodile`, `turkey`, `baby_stroller`, `monkey`, `coyote`, `porcupine`, `parcelforce`, `sheep`, `snake`, `helicopter`, `lizard`, `duck`, `hermes`, `cargus`, `fan_courier`, `sameday`
 
 Candidate labels are not available for automatic suggestions.
 

docs/docs/troubleshooting/faqs.md

@@ -53,14 +53,6 @@ go2rtc:
 
 Point the camera's inputs at the restream as described in the [restream docs](/configuration/restream.md), and swap `detect -> width` and `detect -> height` to match the rotated resolution.
 
-### Can I add a privacy mask to hide part of my camera's view?
-
-Frigate does not have privacy masks. [Motion masks and object filter masks](../configuration/masks.md) only affect detection, they don't hide anything in live view, recordings, or snapshots.
-
-Privacy masks are best configured in the camera's firmware settings so the area is blacked out before the video ever leaves the camera and no extra processing is needed. Check there first.
-
-If your camera does not support privacy masks, there is no efficient alternative. Frigate copies the camera's video into recordings and live view without decoding it, so part of the image can't be hidden without transcoding (re-encoding) the stream. This can be done with a custom ffmpeg filter in go2rtc, but it is not recommended. Every masked camera needs a continuous re-encode, which significantly increases CPU usage, especially for high resolution streams.
-
 ### My mjpeg stream or snapshots look green and crazy
 
 This almost always means that the width/height defined for your camera are not correct. Double check the resolution with VLC or another player. Also make sure you don't have the width and height values backwards.
@@ -192,6 +184,6 @@ Filters and masks only hide the incorrect result - they don't teach Frigate what
 
 ### Where do I see problems Frigate has detected?
 
-Open System > Health. The Notices list keeps a record of problems Frigate has found. Acknowledge an entry to hide it until the problem happens again, or mute it to hide it for good. Hidden entries stay listed under Show hidden in the filter. Ongoing conditions, such as an offline camera or recordings deleted before their retention period, appear in the status bar for admins until they clear, and the status bar links to the Notices list while it has entries showing. On mobile, tap the warning icon in the bottom navigation bar to see them.
+Open System > Health. The Notices list keeps a record of problems Frigate has found, and you can dismiss any entry to acknowledge it. Ongoing conditions, such as an offline camera or recordings deleted before their retention period, appear in the status bar for admins until they clear, and the status bar links to the Notices list while it has undismissed entries. On mobile, tap the warning icon in the bottom navigation bar to see them.
 
 The Hardware section below the notices shows whether the detection hardware, hardware acceleration, and enrichment devices in your config were found and are being used, so a GPU that silently fell back to the CPU shows up as a warning. Run stream checks to probe every camera's streams for the same problems the camera wizard reports.

docs/docs/troubleshooting/recordings.md

@@ -397,11 +397,19 @@ dmesg | grep -i -E "gpu|drm|reset|hang"
 
 Messages like `trying reset from guc_exec_queue_timedout_job` or similar GPU reset/hang messages indicate a driver or hardware issue. Ensure your kernel and GPU drivers (especially Intel) are up to date.
 
-#### Step 6: Verify go2rtc stream configuration
+#### Step 6: Verify hardware acceleration configuration
+
+An incorrect `hwaccel_args` preset can cause ffmpeg to fail silently or consume excessive CPU, starving the detector of resources.
+
+- After upgrading Frigate, verify your preset matches your hardware (e.g., `preset-intel-qsv-h264` instead of the deprecated `preset-vaapi`).
+- For h265 cameras, use the corresponding h265 preset (e.g., `preset-intel-qsv-h265`).
+- Note that `hwaccel_args` are only relevant for the detect stream. Frigate does not decode the record stream.
+
+#### Step 7: Verify go2rtc stream configuration
 
 Ensure that the ffmpeg source names in your go2rtc configuration match the correct camera stream. A misconfigured stream name (e.g., copying a config from one camera to another without updating the stream reference) will cause the wrong stream to be used or the stream to fail entirely.
 
-#### Step 7: Check system resources
+#### Step 8: Check system resources
 
 If none of the above apply, the issue may be a general resource constraint. Monitor the following on your host:
 

docs/docusaurus.config.ts

@@ -3,9 +3,6 @@ import * as path from "node:path";
 import type { Config, PluginConfig } from "@docusaurus/types";
 import type * as OpenApiPlugin from "docusaurus-plugin-openapi-docs";
 
-// Bump when a new stable release ships
-const STABLE_VERSION = "0.18";
-
 const config: Config = {
   title: "Frigate",
   tagline: "NVR With Realtime Object Detection for IP Cameras",
@@ -26,17 +23,17 @@ const config: Config = {
     mermaid: true,
   },
   i18n: {
-    defaultLocale: "en",
-    locales: ["en"],
+    defaultLocale: 'en',
+    locales: ['en'],
     localeConfigs: {
       en: {
-        label: "English",
-      },
+        label: 'English',
+      }
     },
   },
   themeConfig: {
     announcementBar: {
-      id: "frigate_plus",
+      id: 'frigate_plus',
       content: `
         <span style="margin-right: 8px; display: inline-block; animation: pulse 2s infinite;">🚀</span>
         Get more relevant and accurate detections with Frigate+ models.
@@ -48,8 +45,8 @@ const config: Config = {
             50%       { transform: scale(1.1); }
           }
         </style>`,
-      backgroundColor: "#005f73",
-      textColor: "#e0fbfc",
+      backgroundColor: '#005f73',
+      textColor: '#e0fbfc',
       isCloseable: false,
     },
     docs: {
@@ -86,15 +83,15 @@ const config: Config = {
       },
     },
     prism: {
-      magicComments: [
+      magicComments:[
         {
-          className: "theme-code-block-highlighted-line",
-          line: "highlight-next-line",
-          block: { start: "highlight-start", end: "highlight-end" },
+          className: 'theme-code-block-highlighted-line',
+          line: 'highlight-next-line',
+          block: {start: 'highlight-start', end: 'highlight-end'},
         },
         {
-          className: "code-block-error-line",
-          line: "highlight-error-line",
+          className: 'code-block-error-line',
+          line: 'highlight-error-line',
         },
       ],
       additionalLanguages: ["bash", "json"],
@@ -134,11 +131,6 @@ const config: Config = {
         srcDark: "img/branding/logo-dark.svg",
       },
       items: [
-        {
-          href: "https://github.com/blakeblackshear/frigate/releases",
-          label: `${STABLE_VERSION}`,
-          position: "left",
-        },
         {
           to: "/",
           activeBasePath: "docs",
@@ -156,19 +148,19 @@ const config: Config = {
           position: "right",
         },
         {
-          type: "localeDropdown",
-          position: "right",
+          type: 'localeDropdown',
+          position: 'right',
           dropdownItemsAfter: [
             {
-              label: "简体中文（社区翻译）",
-              href: "https://docs.frigate-cn.video",
-            },
-          ],
+              label: '简体中文（社区翻译）',
+              href: 'https://docs.frigate-cn.video',
+            }
+          ]
         },
         {
-          href: "https://github.com/blakeblackshear/frigate",
-          label: "GitHub",
-          position: "right",
+          href: 'https://github.com/blakeblackshear/frigate',
+          label: 'GitHub',
+          position: 'right',
         },
       ],
     },

docs/package-lock.json

@@ -7030,9 +7030,9 @@
       }
     },
     "node_modules/brace-expansion": {
-      "version": "1.1.21",
-      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.21.tgz",
-      "integrity": "sha512-9zeA+KLZNNzglF2TPKRQEDyx6Yby7daAkuy8MiPzpXPsYDWi/DRM8jmwUDxokQjYqBpv5DgPiwD4h4ZZSy1Ujw==",
+      "version": "1.1.18",
+      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.18.tgz",
+      "integrity": "sha512-Edep/X9fGqVNmzKBVsDYIOtD+z1tuezV70LBjdCst9Tqu76lsnvRiZ6oTic1n+/BIwX6QDGAO94PN4N2SADvtw==",
       "license": "MIT",
       "dependencies": {
         "balanced-match": "^1.0.0",
@@ -7698,15 +7698,14 @@
       }
     },
     "node_modules/compression": {
-      "version": "1.8.2",
-      "resolved": "https://registry.npmjs.org/compression/-/compression-1.8.2.tgz",
-      "integrity": "sha512-o8vI5RE5A6EVVOd9o41jKp41aJom+QTEO/Bx8MYNjexMo/Bv2WOjUfZr+aL0WnYSgymUy6zeguqLTsIhV0gMvQ==",
+      "version": "1.8.1",
+      "resolved": "https://registry.npmjs.org/compression/-/compression-1.8.1.tgz",
+      "integrity": "sha512-9mAqGPHLakhCLeNyxPkK4xVo746zQ/czLH1Ky+vkitMnWfWZps8r0qXuwhwizagCRttsL4lfG4pIOvaWLpAP0w==",
       "license": "MIT",
       "dependencies": {
         "bytes": "3.1.2",
         "compressible": "~2.0.18",
         "debug": "2.6.9",
-        "destroy": "1.2.0",
         "negotiator": "~0.6.4",
         "on-headers": "~1.1.0",
         "safe-buffer": "5.2.1",
@@ -7714,10 +7713,6 @@
       },
       "engines": {
         "node": ">= 0.8.0"
-      },
-      "funding": {
-        "type": "opencollective",
-        "url": "https://opencollective.com/express"
       }
     },
     "node_modules/compression/node_modules/bytes": {
@@ -9465,9 +9460,9 @@
       }
     },
     "node_modules/dompurify": {
-      "version": "3.4.16",
-      "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.4.16.tgz",
-      "integrity": "sha512-sqo+pNp3qRhCIpbgRi1y8Tgk27Bo2Ry7w0dC1NBeNTdZChWjz9Xb/KOoZbRP/R6pQZ80Qw8YhXw13hWWBbMRnQ==",
+      "version": "3.4.13",
+      "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.4.13.tgz",
+      "integrity": "sha512-2vmYIoqjze2d+kakP8S/nS5shfsl587kzwEjcGlTdiksUVgFHnFCsLYDVj/JNqJVOQZGSYBTmuycv0PodwmnMQ==",
       "license": "(MPL-2.0 OR Apache-2.0)",
       "optionalDependencies": {
         "@types/trusted-types": "^2.0.7"
@@ -10130,9 +10125,9 @@
       "license": "MIT"
     },
     "node_modules/fast-uri": {
-      "version": "3.1.8",
-      "resolved": "https://registry.npmjs.org/fast-uri/-/fast-uri-3.1.8.tgz",
-      "integrity": "sha512-GZMtZUTNRpOVIECoXwLNZS5xUGE+mVNbTB8h/7Rwh2TFWcBQiPzTgyZi05BF9UMZKkLJv8XBRJTlU7zg8+ZfMg==",
+      "version": "3.1.7",
+      "resolved": "https://registry.npmjs.org/fast-uri/-/fast-uri-3.1.7.tgz",
+      "integrity": "sha512-dOvZVzjdZdz7phd9v6jCbwxrBW3fK6n8Rc0CtdmM4bumzMnxywBYhuph6J819RRw/ku+rLbelwfMunktuzVVHg==",
       "funding": [
         {
           "type": "github",
@@ -11380,15 +11375,15 @@
       }
     },
     "node_modules/image-size": {
-      "version": "2.0.4",
-      "resolved": "https://registry.npmjs.org/image-size/-/image-size-2.0.4.tgz",
-      "integrity": "sha512-QRUkFFsRV/6fuESxb9Vkq+a0LkSrgKXuc2NEqfikiXxxN/G3tjWt5EVUlMaImRBZRZK/jRBEbYvpPYZL8t08Zw==",
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/image-size/-/image-size-2.0.2.tgz",
+      "integrity": "sha512-IRqXKlaXwgSMAMtpNzZa1ZAe8m+Sa1770Dhk8VkSsP9LS+iHD62Zd8FQKs8fbPiagBE7BzoFX23cxFnwshpV6w==",
       "license": "MIT",
       "bin": {
         "image-size": "bin/image-size.js"
       },
       "engines": {
-        "node": ">=18"
+        "node": ">=16.x"
       }
     },
     "node_modules/immer": {
@@ -17453,9 +17448,9 @@
       "license": "ISC"
     },
     "node_modules/proxy-addr": {
-      "version": "2.0.8",
-      "resolved": "https://registry.npmjs.org/proxy-addr/-/proxy-addr-2.0.8.tgz",
-      "integrity": "sha512-5nnx0yGyVUcY6t9RnWcARWtwT9F1D8O9rt08htPvnd49W1IgZtmLkhu9WfMzQj1cFxjHIO6connUNVW5k7AVyQ==",
+      "version": "2.0.7",
+      "resolved": "https://registry.npmjs.org/proxy-addr/-/proxy-addr-2.0.7.tgz",
+      "integrity": "sha512-llQsMLSUDUPT44jdrU/O37qlnifitDP+ZwrmmZcoSKyLKvtZxpyV0n2/bD/N4tBAAZ/gJEdZU7KMraoK1+XYAg==",
       "license": "MIT",
       "dependencies": {
         "forwarded": "0.2.0",
@@ -17463,10 +17458,6 @@
       },
       "engines": {
         "node": ">= 0.10"
-      },
-      "funding": {
-        "type": "opencollective",
-        "url": "https://opencollective.com/express"
       }
     },
     "node_modules/proxy-addr/node_modules/ipaddr.js": {
@@ -19238,9 +19229,9 @@
       }
     },
     "node_modules/shell-quote": {
-      "version": "1.12.0",
-      "resolved": "https://registry.npmjs.org/shell-quote/-/shell-quote-1.12.0.tgz",
-      "integrity": "sha512-PcByqNyT/38F2kDNi006HAMRJaULuBzq/FOsw3qdZvX/GA9W/jamDaRskgHjubHiftXK5sIFxLNkvrXUwcof6Q==",
+      "version": "1.10.0",
+      "resolved": "https://registry.npmjs.org/shell-quote/-/shell-quote-1.10.0.tgz",
+      "integrity": "sha512-w1aiOKwKuRgtwAReIIj89puqg+I7GvX4IbLrvmhXbzQsj1+Zwi4VO3+fa6ZF91TWSjIxoEkKnMeHcLEODK5ZXA==",
       "license": "MIT",
       "engines": {
         "node": ">= 0.4"
@@ -19522,9 +19513,9 @@
       }
     },
     "node_modules/source-map-js": {
-      "version": "1.2.2",
-      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.2.tgz",
-      "integrity": "sha512-KGj/8Y43x35aZVDtt+J4mK1hoLGHULMYfSkODJNQjNDC3oW1PqPoxMwo0pLUsWM/UEGzON/NxeHywEfNXNP3Vw==",
+      "version": "1.2.1",
+      "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz",
+      "integrity": "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA==",
       "license": "BSD-3-Clause",
       "engines": {
         "node": ">=0.10.0"

docs/sidebars.ts

@@ -130,6 +130,7 @@ const sidebars: SidebarsConfig = {
         label: "Advanced Configuration",
         items: [
           "configuration/advanced/system",
+          "configuration/advanced/analytics",
           "configuration/advanced/reference",
           {
             type: "link",

docs/src/components/AnalyticsFields/index.jsx

@@ -0,0 +1,60 @@
+import React from "react";
+import schema from "@site/static/frigate-analytics-schema.json";
+
+function resolve(node) {
+  if (!node) return node;
+  if (node.$ref) return schema.$defs[node.$ref.split("/").pop()];
+  if (node.anyOf) {
+    const inner = node.anyOf.find((option) => option.type !== "null");
+    return inner ? resolve(inner) : node;
+  }
+  return node;
+}
+
+function rows(properties, prefix = "") {
+  return Object.entries(properties).flatMap(([name, field]) => {
+    const path = prefix ? `${prefix}.${name}` : name;
+    const row = {
+      path,
+      description: field.description,
+      isPublic: field["x-public"],
+    };
+    const target = resolve(field);
+
+    if (target?.properties) return [row, ...rows(target.properties, path)];
+
+    const values = resolve(target?.additionalProperties);
+    if (values?.properties)
+      return [row, ...rows(values.properties, `${path}.<key>`)];
+
+    const items = resolve(target?.items);
+    if (items?.properties) return [row, ...rows(items.properties, `${path}[]`)];
+
+    return [row];
+  });
+}
+
+export default function AnalyticsFields() {
+  return (
+    <table>
+      <thead>
+        <tr>
+          <th>Field</th>
+          <th>Description</th>
+          <th>Public</th>
+        </tr>
+      </thead>
+      <tbody>
+        {rows(schema.properties).map((row) => (
+          <tr key={row.path}>
+            <td>
+              <code>{row.path}</code>
+            </td>
+            <td>{row.description}</td>
+            <td>{row.isPublic ? "Yes" : "No"}</td>
+          </tr>
+        ))}
+      </tbody>
+    </table>
+  );
+}

docs/src/components/ShmCalculator/index.jsx

@@ -2,53 +2,42 @@ import React, { useState, useEffect } from "react";
 import Admonition from "@theme/Admonition";
 import styles from "./styles.module.css";
 
-// follows calculate_shm_requirements() in frigate/util/services.py, but sizes
-// for 25 frames so float rounding can't land under its 20 frame warning
-const MB = 1048576;
-const RESERVED_MB = 50; // logs + nginx cache
-const TARGET_FRAMES = 25;
-const DEFAULT_FRAMES = 50;
-
-const frameMb = (width, height) =>
-  Math.round(((width * height * 1.5 + 270480) / MB) * 10) / 10;
-
-// room for 2 cameras added at runtime, sized as 720p
-const addedCamerasMb = 2 * frameMb(1280, 720);
-
 const ShmCalculator = () => {
   const [width, setWidth] = useState(1280);
   const [height, setHeight] = useState(720);
   const [cameraCount, setCameraCount] = useState(1);
-  const [result, setResult] = useState("-");
-  const [singleCameraShm, setSingleCameraShm] = useState("-");
-  const [addedCamerasShm, setAddedCamerasShm] = useState("-");
-  const [fullRingShm, setFullRingShm] = useState("-");
+  const [result, setResult] = useState("26.32MB");
+  const [singleCameraShm, setSingleCameraShm] = useState("26.32MB");
+  const [totalShm, setTotalShm] = useState("26.32MB");
 
   const calculate = () => {
     if (!width || !height || !cameraCount) {
       setResult("Please enter valid values");
       setSingleCameraShm("-");
-      setAddedCamerasShm("-");
-      setFullRingShm("-");
+      setTotalShm("-");
       return;
     }
 
-    const cameraFramesMb = cameraCount * frameMb(width, height) + addedCamerasMb;
+    // Single camera base SHM calculation (excluding logs)
+    // Formula: (width * height * 1.5 * 20 + 270480) / 1048576
+    const singleCameraBase =
+      (width * height * 1.5 * 20 + 270480) / 1048576;
+    setSingleCameraShm(`${singleCameraBase.toFixed(2)}mb`);
 
-    setSingleCameraShm(formatMb(frameMb(width, height) * TARGET_FRAMES));
-    setAddedCamerasShm(formatMb(addedCamerasMb * TARGET_FRAMES));
-    setResult(formatMb(Math.round(RESERVED_MB + cameraFramesMb * TARGET_FRAMES)));
-    setFullRingShm(
-      formatMb(Math.round(RESERVED_MB + cameraFramesMb * DEFAULT_FRAMES)),
-    );
-  };
+    // Total SHM calculation (multiple cameras, including logs)
+    const totalBase = singleCameraBase * cameraCount;
+    const finalResult = totalBase + 40; // Default includes logs +40mb
 
-  const formatMb = (value) => {
-    if (value >= 1024) {
-      return `${(value / 1024).toFixed(2)}gb`;
+    setTotalShm(`${(totalBase + 40).toFixed(2)}mb`);
+
+    // Format result
+    if (finalResult < 1) {
+      setResult(`${(finalResult * 1024).toFixed(2)}kb`);
+    } else if (finalResult >= 1024) {
+      setResult(`${(finalResult / 1024).toFixed(2)}gb`);
+    } else {
+      setResult(`${finalResult.toFixed(2)}mb`);
     }
-
-    return `${Number(value.toFixed(2))}mb`;
   };
 
   const formatWithUnit = (value) => {
@@ -158,27 +147,19 @@ const ShmCalculator = () => {
           </div>
           <div className={styles.formulaDisplay}>
             <p>
-              <strong>Per Camera:</strong> {formatWithUnit(singleCameraShm)}
+              <strong>Single Camera:</strong> {formatWithUnit(singleCameraShm)}
             </p>
             <p>
-              <strong>Formula:</strong> (width × height × 1.5 + 270480) ÷
-              1048576 × {TARGET_FRAMES} frames
+              <strong>Formula:</strong> (width × height × 1.5 × 20 + 270480) ÷
+              1048576
             </p>
+            {cameraCount > 1 && (
+              <p>
+                <strong>Total ({cameraCount} cameras):</strong> {formatWithUnit(totalShm)}
+              </p>
+            )}
             <p>
-              <strong>Room for 2 Added Cameras:</strong>{" "}
-              {formatWithUnit(addedCamerasShm)}
-            </p>
-            <p>
-              <strong>Logs and Cache:</strong> + {RESERVED_MB}
-              <span className={styles.unit}>mb</span>
-            </p>
-            <p>
-              <strong>Birdseye Restream:</strong> + 8
-              <span className={styles.unit}>mb</span> if enabled
-            </p>
-            <p>
-              <strong>For {DEFAULT_FRAMES} Frames:</strong>{" "}
-              {formatWithUnit(fullRingShm)}
+              <strong>With Logs:</strong> + 40<span className={styles.unit}>mb</span>
             </p>
           </div>
         </div>

docs/static/frigate-api.yaml

@@ -10,6 +10,25 @@ servers:
   - url: https://demo.frigate.video/api
   - url: http://localhost:5001/api
 paths:
+  /analytics/preview:
+    get:
+      tags:
+        - Analytics
+      summary: Get Analytics Preview
+      description: |-
+        **Access:** Admin role required.
+
+        Get the analytics report Frigate would send next, without sending it.
+      operationId: get_analytics_preview_analytics_preview_get
+      responses:
+        '200':
+          description: Successful Response
+          content:
+            application/json:
+              schema: {}
+      security:
+        - frigateAdminAuth: []
+      x-required-role: admin
   /auth/first_time_login:
     get:
       tags:
@@ -412,39 +431,6 @@ paths:
       security:
         - frigateAdminAuth: []
       x-required-role: admin
-  /go2rtc/streams/{stream_name}/bitrate:
-    get:
-      tags:
-        - Camera
-      summary: Go2Rtc Stream Bitrate
-      description: |-
-        **Access:** Admin role required.
-
-        Measure a go2rtc stream's bitrate over a few seconds.
-      operationId: 
-        go2rtc_stream_bitrate_go2rtc_streams__stream_name__bitrate_get
-      parameters:
-        - name: stream_name
-          in: path
-          required: true
-          schema:
-            type: string
-            title: Stream Name
-      responses:
-        '200':
-          description: Successful Response
-          content:
-            application/json:
-              schema: {}
-        '422':
-          description: Validation Error
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/HTTPValidationError'
-      security:
-        - frigateAdminAuth: []
-      x-required-role: admin
   /ffprobe:
     get:
       tags:
@@ -1088,7 +1074,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1132,7 +1117,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1287,7 +1271,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1647,7 +1630,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1695,7 +1677,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1743,7 +1724,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1785,7 +1765,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -1869,7 +1848,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -2131,7 +2109,7 @@ paths:
           required: false
           schema:
             type: string
-            default: UTC
+            default: utc
             title: Timezone
       responses:
         '200':
@@ -3266,7 +3244,7 @@ paths:
             anyOf:
               - type: string
               - type: 'null'
-            default: UTC
+            default: utc
             title: Timezone
       responses:
         '200':
@@ -3491,7 +3469,6 @@ paths:
           application/json:
             schema:
               type: object
-              additionalProperties: true
               title: Body
       responses:
         '200':
@@ -4216,20 +4193,19 @@ paths:
         Get notices, most severe first.
 
         Args:
-            include_hidden: Also return acknowledged and muted notices, for the
-                hidden list
+            include_dismissed: Also return dismissed notices, for the history view
 
         Returns:
             The notices
       operationId: get_notices_notices_get
       parameters:
-        - name: include_hidden
+        - name: include_dismissed
           in: query
           required: false
           schema:
             type: boolean
             default: false
-            title: Include Hidden
+            title: Include Dismissed
       responses:
         '200':
           description: Successful Response
@@ -4264,16 +4240,16 @@ paths:
       security:
         - frigateAdminAuth: []
       x-required-role: admin
-  /notices/muted_checks:
+  /notices/dismissed_checks:
     get:
       tags:
         - Notices
-      summary: Get Muted Checks
+      summary: Get Dismissed Checks
       description: |-
         **Access:** Admin role required.
 
-        Get the muted config and stream check rows, newest first.
-      operationId: get_muted_checks_notices_muted_checks_get
+        Get the dismissed config and stream check rows, newest first.
+      operationId: get_dismissed_checks_notices_dismissed_checks_get
       responses:
         '200':
           description: Successful Response
@@ -4283,16 +4259,16 @@ paths:
       security:
         - frigateAdminAuth: []
       x-required-role: admin
-  /notices/hidden:
+  /notices/dismissed:
     delete:
       tags:
         - Notices
-      summary: Unhide All Notices
+      summary: Purge Dismissed
       description: |-
         **Access:** Admin role required.
 
-        Show every acknowledged and muted notice and check row again.
-      operationId: unhide_all_notices_notices_hidden_delete
+        Delete every dismissed notice and check row so each can show again.
+      operationId: purge_dismissed_notices_dismissed_delete
       responses:
         '200':
           description: Successful Response
@@ -4302,83 +4278,18 @@ paths:
       security:
         - frigateAdminAuth: []
       x-required-role: admin
-  /notices/{notice_id}/acknowledge:
+  /notices/{notice_id}/dismiss:
     post:
       tags:
         - Notices
-      summary: Acknowledge Notice
+      summary: Dismiss Notice
       description: |-
         **Access:** Admin role required.
 
-        Hide a notice until it happens again.
+        Hide a notice or a config or stream check row.
 
-        Config and stream check rows and the update notice never repeat, so they
-        can only be muted.
-      operationId: acknowledge_notice_notices__notice_id__acknowledge_post
-      parameters:
-        - name: notice_id
-          in: path
-          required: true
-          schema:
-            type: string
-            title: Notice Id
-      responses:
-        '200':
-          description: Successful Response
-          content:
-            application/json:
-              schema: {}
-        '422':
-          description: Validation Error
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/HTTPValidationError'
-      security:
-        - frigateAdminAuth: []
-      x-required-role: admin
-  /notices/{notice_id}/mute:
-    post:
-      tags:
-        - Notices
-      summary: Mute Notice
-      description: |-
-        **Access:** Admin role required.
-
-        Hide a notice or a config or stream check row for good.
-      operationId: mute_notice_notices__notice_id__mute_post
-      parameters:
-        - name: notice_id
-          in: path
-          required: true
-          schema:
-            type: string
-            title: Notice Id
-      responses:
-        '200':
-          description: Successful Response
-          content:
-            application/json:
-              schema: {}
-        '422':
-          description: Validation Error
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/HTTPValidationError'
-      security:
-        - frigateAdminAuth: []
-      x-required-role: admin
-  /notices/{notice_id}/hidden:
-    delete:
-      tags:
-        - Notices
-      summary: Unhide Notice
-      description: |-
-        **Access:** Admin role required.
-
-        Show an acknowledged or muted notice or check row again.
-      operationId: unhide_notice_notices__notice_id__hidden_delete
+        It stays hidden if the same problem happens again.
+      operationId: dismiss_notice_notices__notice_id__dismiss_post
       parameters:
         - name: notice_id
           in: path
@@ -4502,16 +4413,6 @@ paths:
               - type: 'null'
             default: 100
             title: Limit
-        - name: offset
-          in: query
-          required: false
-          schema:
-            anyOf:
-              - type: integer
-                minimum: 0
-              - type: 'null'
-            default: 0
-            title: Offset
         - name: after
           in: query
           required: false
@@ -4666,7 +4567,7 @@ paths:
             anyOf:
               - type: string
               - type: 'null'
-            default: UTC
+            default: utc
             title: Timezone
       responses:
         '200':
@@ -4817,16 +4718,6 @@ paths:
               - type: 'null'
             default: 50
             title: Limit
-        - name: offset
-          in: query
-          required: false
-          schema:
-            anyOf:
-              - type: integer
-                minimum: 0
-              - type: 'null'
-            default: 0
-            title: Offset
         - name: cameras
           in: query
           required: false
@@ -4928,7 +4819,7 @@ paths:
             anyOf:
               - type: string
               - type: 'null'
-            default: UTC
+            default: utc
             title: Timezone
         - name: min_score
           in: query
@@ -5008,7 +4899,7 @@ paths:
             anyOf:
               - type: string
               - type: 'null'
-            default: UTC
+            default: utc
             title: Timezone
         - name: has_clip
           in: query
@@ -5661,7 +5552,6 @@ paths:
             application/json:
               schema:
                 type: object
-                additionalProperties: true
                 title: Response Create Trigger Embedding Trigger Embedding Post
         '422':
           description: Validation Error
@@ -5710,7 +5600,6 @@ paths:
             application/json:
               schema:
                 type: object
-                additionalProperties: true
                 title: Response Update Trigger Embedding Trigger Embedding  
                   Camera Name   Name  Put
         '422':
@@ -5753,7 +5642,6 @@ paths:
             application/json:
               schema:
                 type: object
-                additionalProperties: true
                 title: Response Delete Trigger Embedding Trigger Embedding  
                   Camera Name   Name  Delete
         '422':
@@ -5790,7 +5678,6 @@ paths:
             application/json:
               schema:
                 type: object
-                additionalProperties: true
                 title: Response Get Triggers Status Triggers Status  Camera Name  
                   Get
         '422':
@@ -7367,7 +7254,7 @@ paths:
           required: false
           schema:
             type: string
-            default: UTC
+            default: utc
             title: Timezone
         - name: cameras
           in: query
@@ -7417,7 +7304,7 @@ paths:
           required: false
           schema:
             type: string
-            default: UTC
+            default: utc
             title: Timezone
       responses:
         '200':
@@ -7587,7 +7474,6 @@ paths:
                 type: array
                 items:
                   type: object
-                  additionalProperties: true
                 title: Response No Recordings Recordings Unavailable Get
         '422':
           description: Validation Error
@@ -7791,19 +7677,13 @@ components:
           title: Update Topic
         config_data:
           anyOf:
-            - additionalProperties: true
-              type: object
+            - type: object
             - type: 'null'
           title: Config Data
         skip_save:
           type: boolean
           title: Skip Save
           default: false
-        replace_paths:
-          items:
-            type: string
-          type: array
-          title: Replace Paths
       type: object
       title: AppConfigSetBody
     AppPostLoginBody:
@@ -8032,7 +7912,7 @@ components:
       properties:
         file:
           type: string
-          contentMediaType: application/octet-stream
+          format: binary
           title: File
       type: object
       required:
@@ -8042,7 +7922,7 @@ components:
       properties:
         file:
           type: string
-          contentMediaType: application/octet-stream
+          format: binary
           title: File
       type: object
       required:
@@ -8140,7 +8020,6 @@ components:
         tool_calls:
           anyOf:
             - items:
-                additionalProperties: true
                 type: object
               type: array
             - type: 'null'
@@ -8436,7 +8315,6 @@ components:
             - type: 'null'
           title: Model Type
         data:
-          additionalProperties: true
           type: object
           title: Data
       type: object
@@ -8508,8 +8386,7 @@ components:
           default: true
         draw:
           anyOf:
-            - additionalProperties: true
-              type: object
+            - type: object
             - type: 'null'
           title: Draw
           default: {}
@@ -8752,8 +8629,7 @@ components:
           description: Error message for failed jobs
         results:
           anyOf:
-            - additionalProperties: true
-              type: object
+            - type: object
             - type: 'null'
           title: Results
           description: Result metadata for completed jobs
@@ -9003,7 +8879,6 @@ components:
             - type: 'null'
           title: Base Url
         provider_options:
-          additionalProperties: true
           type: object
           title: Provider Options
       type: object
@@ -9544,7 +9419,6 @@ components:
           type: string
           title: Tool Name
         arguments:
-          additionalProperties: true
           type: object
           title: Arguments
       type: object
@@ -9622,11 +9496,6 @@ components:
         type:
           type: string
           title: Error Type
-        input:
-          title: Input
-        ctx:
-          type: object
-          title: Context
       type: object
       required:
         - loc

frigate/__main__.py

@@ -15,9 +15,7 @@ from frigate.util.config import find_config_file
 
 
 def main() -> None:
-    # Fork this manager so the forkserver does not start until the first
-    # worker process, after the config has applied environment_vars.
-    manager = mp.get_context("fork").Manager()
+    manager = mp.Manager()
     faulthandler.enable()
 
     # Setup the logging thread

frigate/analytics/__init__.py

@@ -0,0 +1 @@
+"""Opt-in anonymous analytics reports."""

frigate/analytics/collectors/__init__.py

@@ -0,0 +1 @@
+"""One collector per report section."""

frigate/analytics/collectors/cameras.py

@@ -0,0 +1,223 @@
+"""Cameras section: counts and histograms across cameras, never per camera."""
+
+from collections import Counter
+from typing import Any
+from urllib.parse import urlsplit
+
+from frigate.analytics.collectors.common import closed, histogram
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import (
+    CamerasSection,
+    ConnectionQuality,
+    FpsBucket,
+    HeightBucket,
+    HwaccelKey,
+    InputPresetKey,
+    RetainBucket,
+    RetainDays,
+)
+from frigate.config import CameraConfig
+from frigate.config.camera.camera import CameraTypeEnum
+from frigate.config.camera.ffmpeg import CameraInput, CameraRoleEnum
+from frigate.const import REPLAY_CAMERA_PREFIX
+
+# the upper edge of every height bucket but the last
+HEIGHT_BUCKETS = (
+    (360, HeightBucket.le_360),
+    (540, HeightBucket.h480),
+    (900, HeightBucket.h720),
+    (1260, HeightBucket.h1080),
+    (1800, HeightBucket.h1440),
+)
+RESTREAM_HOSTS = frozenset({"127.0.0.1", "localhost"})
+RESTREAM_PORT = 8554
+QUALITIES = frozenset(ConnectionQuality)
+
+
+def height_bucket(height: int) -> HeightBucket:
+    for limit, bucket in HEIGHT_BUCKETS:
+        if height <= limit:
+            return bucket
+
+    return HeightBucket.ge_2160
+
+
+def fps_bucket(fps: int) -> FpsBucket:
+    if fps <= 5:
+        return FpsBucket.le_5
+
+    if fps <= 10:
+        return FpsBucket.f6_10
+
+    return FpsBucket.gt_10
+
+
+def retain_bucket(days: float) -> RetainBucket:
+    if days <= 0:
+        return RetainBucket.zero
+
+    if days <= 7:
+        return RetainBucket.d1_7
+
+    if days <= 30:
+        return RetainBucket.d8_30
+
+    return RetainBucket.gt_30
+
+
+def preset_key(args: str | list[str], enum: Any) -> Any:
+    """The preset's name, custom for hand written args, or none."""
+    if not args:
+        return enum("none")
+
+    if isinstance(args, str) and args.startswith("preset-"):
+        return closed(enum, args.removeprefix("preset-"), enum("custom"))
+
+    return enum("custom")
+
+
+def is_restream(path: str) -> bool:
+    try:
+        url = urlsplit(path)
+        return url.hostname in RESTREAM_HOSTS and url.port == RESTREAM_PORT
+    except ValueError:
+        return False
+
+
+def role_input(camera: CameraConfig, role: CameraRoleEnum) -> CameraInput | None:
+    return next((i for i in camera.ffmpeg.inputs if role in i.roles), None)
+
+
+def object_masks(camera: CameraConfig) -> int:
+    # parsing copies camera-wide masks into every filter as global_<id>
+    own = sum(1 for mask in camera.objects.mask.values() if mask is not None)
+    per_label = sum(
+        1
+        for label_filter in camera.objects.filters.values()
+        for mask_id, mask in label_filter.mask.items()
+        if mask is not None and not mask_id.startswith("global_")
+    )
+    return own + per_label
+
+
+def collect(ctx: ReportContext) -> CamerasSection:
+    cameras = {
+        name: camera
+        for name, camera in ctx.config.cameras.items()
+        if not name.startswith(REPLAY_CAMERA_PREFIX)
+    }
+    camera_stats = ctx.stats.get("cameras", {})
+
+    flags: Counter[str] = Counter()
+    types: Counter[CameraTypeEnum] = Counter()
+    heights: Counter[HeightBucket] = Counter()
+    fps: Counter[FpsBucket] = Counter()
+    hwaccel: Counter[Any] = Counter()
+    input_presets: Counter[Any] = Counter()
+    quality: Counter[ConnectionQuality] = Counter()
+    retain: dict[str, Counter[RetainBucket]] = {
+        period: Counter() for period in ("continuous", "motion", "alerts", "detections")
+    }
+
+    for name, camera in cameras.items():
+        detect_input = role_input(camera, CameraRoleEnum.detect)
+        record_input = role_input(camera, CameraRoleEnum.record)
+
+        # config validation requires a detect input, so this never skips
+        if detect_input is None:
+            continue
+
+        types[camera.type] += 1
+        fps[fps_bucket(camera.detect.fps)] += 1
+        hwaccel[
+            preset_key(
+                detect_input.hwaccel_args or camera.ffmpeg.hwaccel_args, HwaccelKey
+            )
+        ] += 1
+        input_presets[
+            preset_key(
+                detect_input.input_args or camera.ffmpeg.input_args, InputPresetKey
+            )
+        ] += 1
+
+        if camera.detect.height:
+            heights[height_bucket(camera.detect.height)] += 1
+
+        state = camera_stats.get(name, {}).get("connection_quality")
+
+        if state in QUALITIES:
+            quality[ConnectionQuality(state)] += 1
+
+        if camera.record.enabled:
+            retain["continuous"][retain_bucket(camera.record.continuous.days)] += 1
+            retain["motion"][retain_bucket(camera.record.motion.days)] += 1
+            retain["alerts"][retain_bucket(camera.record.alerts.retain.days)] += 1
+            retain["detections"][
+                retain_bucket(camera.record.detections.retain.days)
+            ] += 1
+
+        zones = len(camera.zones)
+        flags["enabled"] += camera.enabled
+        flags["go2rtc_restream"] += any(
+            is_restream(i.path) for i in camera.ffmpeg.inputs
+        )
+        flags["separate_detect_stream"] += (
+            record_input is not None and record_input.path != detect_input.path
+        )
+        flags["detect"] += camera.detect.enabled
+        flags["record"] += camera.record.enabled
+        flags["sub_stream_record"] += camera.record.sub.enabled
+        flags["snapshots"] += camera.snapshots.enabled
+        flags["audio"] += camera.audio.enabled
+        flags["audio_transcription"] += camera.audio_transcription.enabled
+        flags["birdseye"] += camera.birdseye.enabled
+        flags["onvif"] += bool(camera.onvif.host)
+        flags["autotracking"] += camera.onvif.autotracking.enabled
+        flags["face_recognition"] += camera.face_recognition.enabled
+        flags["lpr"] += camera.lpr.enabled
+        flags["review_genai"] += camera.review.genai.enabled
+        flags["object_genai"] += camera.objects.genai.enabled
+        flags["notifications"] += camera.notifications.enabled
+        flags["zones"] += zones
+        flags["cameras_with_zones"] += zones > 0
+        flags["motion_masks"] += sum(
+            1 for mask in camera.motion.mask.values() if mask is not None
+        )
+        flags["object_masks"] += object_masks(camera)
+
+    return CamerasSection(
+        total=len(cameras),
+        enabled=flags["enabled"],
+        types=histogram(types),
+        detect_height=histogram(heights),
+        detect_fps=histogram(fps),
+        hwaccel=histogram(hwaccel),
+        input_preset=histogram(input_presets),
+        go2rtc_restream=flags["go2rtc_restream"],
+        separate_detect_stream=flags["separate_detect_stream"],
+        detect=flags["detect"],
+        record=flags["record"],
+        sub_stream_record=flags["sub_stream_record"],
+        snapshots=flags["snapshots"],
+        audio=flags["audio"],
+        audio_transcription=flags["audio_transcription"],
+        birdseye=flags["birdseye"],
+        onvif=flags["onvif"],
+        autotracking=flags["autotracking"],
+        face_recognition=flags["face_recognition"],
+        lpr=flags["lpr"],
+        review_genai=flags["review_genai"],
+        object_genai=flags["object_genai"],
+        notifications=flags["notifications"],
+        zones=flags["zones"],
+        cameras_with_zones=flags["cameras_with_zones"],
+        motion_masks=flags["motion_masks"],
+        object_masks=flags["object_masks"],
+        connection_quality=histogram(quality),
+        retain_days=RetainDays(
+            continuous=histogram(retain["continuous"]),
+            motion=histogram(retain["motion"]),
+            alerts=histogram(retain["alerts"]),
+            detections=histogram(retain["detections"]),
+        ),
+    )

frigate/analytics/collectors/common.py

@@ -0,0 +1,37 @@
+"""Helpers the section collectors share."""
+
+import math
+from collections import Counter
+from enum import Enum
+from typing import Any, TypeVar
+
+E = TypeVar("E", bound=Enum)
+
+
+def closed(enum: type[E], value: Any, fallback: E) -> E:
+    """The member for a value, or the fallback for one the enum doesn't know."""
+    try:
+        return enum(str(value))
+    except ValueError:
+        return fallback
+
+
+def rate(value: Any) -> float:
+    """A finite, non-negative number rounded to 2 decimals, else 0.
+
+    A NaN would serialize as null and fail the schema's number type.
+    """
+    try:
+        number = float(value)
+    except (TypeError, ValueError):
+        return 0.0
+
+    if not math.isfinite(number):
+        return 0.0
+
+    return round(max(number, 0.0), 2)
+
+
+def histogram(counter: "Counter[E]") -> dict[E, int]:
+    """Drop the empty buckets, since an absent key means zero."""
+    return {key: total for key, total in counter.items() if total > 0}

frigate/analytics/collectors/detection.py

@@ -0,0 +1,65 @@
+"""Detection section: models, the detectors they run on, and inference speed."""
+
+import os
+
+from frigate.analytics.collectors.common import rate
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import DetectionModel, DetectionSection, ModelSource
+from frigate.config.config import DEFAULT_MODEL
+from frigate.const import MODEL_CACHE_DIR
+from frigate.detectors.detector_config import SceneEnum
+from frigate.detectors.detector_types import DetectorTypeEnum
+from frigate.detectors.device import runner_names
+
+# the paths FrigateConfig fills in for a model that sets none
+BUNDLED_MODEL_PATHS = frozenset(
+    {"/cpu_model.tflite", "/edgetpu_model.tflite", str(DEFAULT_MODEL["path"])}
+)
+
+
+def model_source(path: str | None) -> ModelSource:
+    """Default, Frigate+ (a cached model next to its info file), or custom.
+
+    Parsing rewrites plus://<id> to the model cache, so the prefix is gone by now.
+    """
+    if path is None or path in BUNDLED_MODEL_PATHS:
+        return ModelSource.default
+
+    if path.startswith(f"{MODEL_CACHE_DIR}/") and os.path.isfile(f"{path}.json"):
+        return ModelSource.plus
+
+    return ModelSource.custom
+
+
+def collect(ctx: ReportContext) -> DetectionSection:
+    config = ctx.config
+    detectors = ctx.stats.get("detectors", {})
+    model_specs = [(model, config.devices_for_model(model)) for model in config.models]
+
+    # FrigateApp.start_detectors names the processes in this same order
+    names = iter(runner_names([spec for _, specs in model_specs for spec in specs]))
+    models: dict[SceneEnum, DetectionModel] = {}
+
+    for model, specs in model_specs:
+        speeds: list[float] = []
+
+        for _ in specs:
+            speed = detectors.get(next(names), {}).get("inference_speed")
+
+            if isinstance(speed, int | float) and speed > 0:
+                speeds.append(float(speed))
+
+        models[model.scene] = DetectionModel(
+            detector=DetectorTypeEnum(specs[0].detector),
+            devices=len(specs),
+            model_type=model.model_type,
+            input=f"{model.width}x{model.height}",
+            source=model_source(model.path),
+            inference_ms=rate(sum(speeds) / len(speeds)) if speeds else None,
+        )
+
+    return DetectionSection(
+        models=models,
+        detection_fps=rate(ctx.stats.get("detection_fps")),
+        skipped_fps=rate(ctx.stats.get("skipped_fps")),
+    )

frigate/analytics/collectors/features.py

@@ -0,0 +1,145 @@
+"""Features section: enrichments, GenAI, integrations, and users."""
+
+from collections import Counter
+
+from frigate.analytics.collectors.common import closed, histogram
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import (
+    BirdseyeUsage,
+    ClassificationUsage,
+    EnrichmentDevice,
+    EnrichmentUsage,
+    FeaturesSection,
+    GenAIUsage,
+    SemanticSearchModel,
+    SemanticSearchUsage,
+    TranscriptionModel,
+    TranscriptionUsage,
+    UserRole,
+)
+from frigate.config.camera.genai import GenAIProviderEnum, GenAIRoleEnum
+from frigate.const import REPLAY_CAMERA_PREFIX
+from frigate.models import User
+
+RUNTIME_DEVICES = {
+    "cpu": EnrichmentDevice.cpu,
+    "cuda": EnrichmentDevice.cuda,
+    "tensorrt": EnrichmentDevice.tensorrt,
+    "migraphx": EnrichmentDevice.migraphx,
+}
+OPENVINO_DEVICES = {
+    "cpu": EnrichmentDevice.openvino_cpu,
+    "gpu": EnrichmentDevice.openvino_gpu,
+    "npu": EnrichmentDevice.openvino_npu,
+}
+
+
+def enrichment_device(label: object) -> EnrichmentDevice | None:
+    """Map a runner's device label, like "CUDA" or "OpenVINO GPU.0,CPU"."""
+    if not isinstance(label, str) or not label:
+        return None
+
+    runtime, _, target = label.partition(" ")
+
+    if runtime == "OpenVINO":
+        first = target.split(",")[0].split(".")[0].strip().lower()
+        return OPENVINO_DEVICES.get(first, EnrichmentDevice.other)
+
+    return RUNTIME_DEVICES.get(label.lower(), EnrichmentDevice.other)
+
+
+def model_name(model: object) -> str | None:
+    if model is None:
+        return None
+
+    return str(getattr(model, "value", model))
+
+
+def semantic_model(model: object) -> SemanticSearchModel | None:
+    # any string that isn't a built-in model names a GenAI provider
+    name = model_name(model)
+
+    if name is None:
+        return None
+
+    if name in ("jinav1", "jinav2"):
+        return SemanticSearchModel(name)
+
+    return SemanticSearchModel.genai
+
+
+def transcription_model(model: object) -> TranscriptionModel | None:
+    name = model_name(model)
+
+    if name is None:
+        return None
+
+    return TranscriptionModel.whisper if name == "whisper" else TranscriptionModel.genai
+
+
+def users() -> dict[UserRole, int]:
+    roles: Counter[UserRole] = Counter(
+        closed(UserRole, user.role, UserRole.custom) for user in User.select(User.role)
+    )
+    return histogram(roles)
+
+
+def collect(ctx: ReportContext) -> FeaturesSection:
+    config = ctx.config
+    devices = ctx.stats.get("embeddings", {}).get("devices", {})
+    cameras = [
+        camera
+        for name, camera in config.cameras.items()
+        if not name.startswith(REPLAY_CAMERA_PREFIX)
+    ]
+    providers: Counter[GenAIProviderEnum] = Counter(
+        genai.provider for genai in config.genai.values()
+    )
+    roles: Counter[GenAIRoleEnum] = Counter(
+        role for genai in config.genai.values() for role in genai.roles
+    )
+    custom = list(config.classification.custom.values())
+
+    return FeaturesSection(
+        face_recognition=EnrichmentUsage(
+            enabled=config.face_recognition.enabled,
+            model_size=config.face_recognition.model_size,
+            device=enrichment_device(devices.get("face_recognition")),
+        ),
+        lpr=EnrichmentUsage(
+            enabled=config.lpr.enabled,
+            model_size=config.lpr.model_size,
+            device=enrichment_device(devices.get("lpr")),
+        ),
+        semantic_search=SemanticSearchUsage(
+            enabled=config.semantic_search.enabled,
+            model=semantic_model(config.semantic_search.model),
+            model_size=config.semantic_search.model_size,
+            device=enrichment_device(devices.get("semantic_search")),
+            triggers=sum(len(camera.semantic_search.triggers) for camera in cameras),
+        ),
+        audio_transcription=TranscriptionUsage(
+            enabled=config.audio_transcription.enabled,
+            model=transcription_model(config.audio_transcription.model),
+            model_size=config.audio_transcription.model_size,
+        ),
+        genai=GenAIUsage(providers=histogram(providers), roles=histogram(roles)),
+        classification_models=ClassificationUsage(
+            state=sum(1 for model in custom if model.state_config is not None),
+            object=sum(1 for model in custom if model.object_config is not None),
+        ),
+        birdseye=BirdseyeUsage(
+            enabled=config.birdseye.enabled,
+            modes=list(config.birdseye.modes),
+            restream=config.birdseye.restream,
+        ),
+        mqtt=config.mqtt.enabled,
+        notifications=config.notifications.enabled,
+        auth=config.auth.enabled,
+        proxy_auth=config.proxy.header_map.user is not None,
+        tls=config.tls.enabled,
+        users=users(),
+        camera_groups=len(config.camera_groups),
+        profiles=len(config.profiles),
+        plus_api_key=config.plus_api.is_active(),
+    )

frigate/analytics/collectors/hardware.py

@@ -0,0 +1,107 @@
+"""Hardware section: CPU, memory, GPUs, decode and detection hardware, storage."""
+
+import os
+from collections import Counter
+from typing import Any
+
+import psutil
+
+from frigate.analytics.collectors.common import closed, histogram
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import (
+    DecodeFamily,
+    GpuInfo,
+    GpuVendor,
+    HardwareKey,
+    HardwareSection,
+    StorageInfo,
+)
+from frigate.const import RECORD_DIR
+from frigate.detectors.hardware import hardware_prober
+from frigate.util.hwaccel import hwaccel_options
+
+DEVICE_TREE_MODEL = "/proc/device-tree/model"
+CPUINFO = "/proc/cpuinfo"
+
+
+def cpu_model() -> str:
+    """The board model on ARM boards, else the CPU's model name."""
+    try:
+        with open(DEVICE_TREE_MODEL) as f:
+            board = f.read().strip("\x00\n ")
+
+        if board:
+            return board[:64]
+    except OSError:
+        pass
+
+    try:
+        with open(CPUINFO) as f:
+            for line in f:
+                key, _, value = line.partition(":")
+
+                if key.strip() == "model name" and value.strip():
+                    return value.strip()[:64]
+    except OSError:
+        pass
+
+    return "unknown"
+
+
+def gpus(stats: dict[str, Any]) -> list[GpuInfo]:
+    found: list[GpuInfo] = []
+
+    for name, entry in stats.get("gpu_usages", {}).items():
+        vendor = entry.get("vendor") if isinstance(entry, dict) else None
+        found.append(
+            GpuInfo(
+                vendor=closed(GpuVendor, vendor, GpuVendor.other),
+                name=str(name)[:64],
+            )
+        )
+
+    return found
+
+
+def decode_families() -> list[DecodeFamily]:
+    _, available = hwaccel_options()
+    families = [
+        closed(DecodeFamily, family.key, DecodeFamily.other) for family in available
+    ]
+    return list(dict.fromkeys(families))
+
+
+def detection_hardware() -> dict[HardwareKey, int]:
+    units: Counter[HardwareKey] = Counter()
+
+    for found in hardware_prober.probe():
+        units[closed(HardwareKey, found.key, HardwareKey.other)] += found.count
+
+    return histogram(units)
+
+
+def storage(stats: dict[str, Any]) -> StorageInfo:
+    # stats report sizes in MB
+    entry = stats.get("service", {}).get("storage", {}).get(RECORD_DIR) or {}
+    total_mb = float(entry.get("total") or 0)
+    used_mb = float(entry.get("used") or 0)
+
+    return StorageInfo(
+        record_fs=str(entry.get("mount_type") or "unknown")[:16],
+        record_total_gb=round(total_mb / 1024),
+        record_used_pct=min(round(used_mb / total_mb * 100), 100)
+        if total_mb > 0
+        else 0,
+    )
+
+
+def collect(ctx: ReportContext) -> HardwareSection:
+    return HardwareSection(
+        cpu_model=cpu_model(),
+        cpu_cores=os.cpu_count() or 0,
+        memory_gb=round(psutil.virtual_memory().total / 2**30),
+        gpus=gpus(ctx.stats),
+        decode_families=decode_families(),
+        detection_hardware=detection_hardware(),
+        storage=storage(ctx.stats),
+    )

frigate/analytics/collectors/health.py

@@ -0,0 +1,59 @@
+"""Health section: uptime, CPU, enrichment speed, and notice counts."""
+
+from typing import Any
+
+from frigate.analytics.collectors.common import rate
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import (
+    EnrichmentTiming,
+    HealthSection,
+    NoticeCounts,
+    NoticeKindKey,
+)
+
+TIMING_STATS = {
+    EnrichmentTiming.face: "face_recognition_speed",
+    EnrichmentTiming.lpr: "plate_recognition_speed",
+    EnrichmentTiming.plate_detection: "yolov9_plate_detection_speed",
+    EnrichmentTiming.image_embedding: "image_embedding_speed",
+    EnrichmentTiming.text_embedding: "text_embedding_speed",
+    EnrichmentTiming.review_description: "review_description_speed",
+    EnrichmentTiming.object_description: "object_description_speed",
+}
+REPORTABLE_KINDS = frozenset(key.value for key in NoticeKindKey)
+
+
+def notice_deltas(notice_stats: list[dict[str, Any]]) -> dict[Any, NoticeCounts]:
+    """What changed since the last accepted report, per reportable kind."""
+    deltas: dict[Any, NoticeCounts] = {}
+
+    for row in notice_stats:
+        if row["kind"] not in REPORTABLE_KINDS:
+            continue
+
+        occurrences = max(row["occurrences"] - row["reported_occurrences"], 0)
+        dismissals = max(row["dismissals"] - row["reported_dismissals"], 0)
+
+        if occurrences or dismissals:
+            deltas[NoticeKindKey(row["kind"])] = NoticeCounts(
+                occurrences=occurrences, dismissals=dismissals
+            )
+
+    return deltas
+
+
+def collect(ctx: ReportContext) -> HealthSection:
+    service = ctx.stats.get("service", {})
+    embeddings = ctx.stats.get("embeddings", {})
+    cpu = ctx.stats.get("cpu_usages", {}).get("frigate.full_system", {}).get("cpu")
+    timings = {
+        timing: rate(embeddings.get(key)) for timing, key in TIMING_STATS.items()
+    }
+
+    return HealthSection(
+        uptime_hours=int(rate(service.get("uptime")) // 3600),
+        cpu_percent=min(round(rate(cpu)), 100),
+        enrichment_ms={timing: value for timing, value in timings.items() if value > 0},
+        retention_unmet=bool(service.get("retention_unmet", False)),
+        notices=notice_deltas(ctx.notice_stats),
+    )

frigate/analytics/collectors/install.py

@@ -0,0 +1,63 @@
+"""Install section: version, image variant, install type, platform."""
+
+import os
+import platform
+import re
+
+from frigate.analytics.collectors.common import closed
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import Arch, ImageVariant, InstallSection, InstallType
+from frigate.version import VERSION
+
+KERNEL_PATTERN = re.compile(r"^(\d{1,3})\.(\d{1,3})")
+
+
+def image_variant(value: str | None) -> ImageVariant:
+    """The published image from the build-time FRIGATE_IMAGE_VARIANT, dev when unset."""
+    if not value:
+        return ImageVariant.dev
+
+    return closed(ImageVariant, value, ImageVariant.other)
+
+
+def install_type() -> InstallType:
+    # the add-on is a container too, so it has to be checked first
+    if os.path.isfile("/data/options.json"):
+        return InstallType.ha_addon
+
+    if os.environ.get("KUBERNETES_SERVICE_HOST"):
+        return InstallType.kubernetes
+
+    if os.path.exists("/run/.containerenv"):
+        return InstallType.podman
+
+    if os.path.exists("/.dockerenv"):
+        return InstallType.docker
+
+    return InstallType.unknown
+
+
+def arch(machine: str) -> Arch:
+    match machine.lower():
+        case "x86_64" | "amd64":
+            return Arch.x86_64
+        case "aarch64" | "arm64":
+            return Arch.aarch64
+        case _:
+            return Arch.other
+
+
+def kernel(release: str) -> str:
+    match = KERNEL_PATTERN.match(release)
+    return f"{match.group(1)}.{match.group(2)}" if match else "unknown"
+
+
+def collect(ctx: ReportContext) -> InstallSection:
+    return InstallSection(
+        version=VERSION[:32],
+        image_variant=image_variant(os.environ.get("FRIGATE_IMAGE_VARIANT")),
+        install_type=install_type(),
+        arch=arch(platform.machine()),
+        kernel=kernel(platform.release()),
+        run_as_root=os.geteuid() == 0,
+    )

frigate/analytics/context.py

@@ -0,0 +1,13 @@
+"""What the collectors read, gathered once per report."""
+
+from dataclasses import dataclass, field
+from typing import Any
+
+from frigate.config import FrigateConfig
+
+
+@dataclass(frozen=True)
+class ReportContext:
+    config: FrigateConfig
+    stats: dict[str, Any]
+    notice_stats: list[dict[str, Any]] = field(default_factory=list)

frigate/analytics/report.py

@@ -0,0 +1,88 @@
+"""Build a report from the section collectors."""
+
+import logging
+import time
+from collections.abc import Callable
+from typing import TYPE_CHECKING, Any
+from uuid import uuid4
+
+from pydantic import BaseModel
+
+from frigate.analytics.collectors import (
+    cameras,
+    detection,
+    features,
+    hardware,
+    health,
+    install,
+)
+from frigate.analytics.context import ReportContext
+from frigate.analytics.schema import SCHEMA_VERSION, AnalyticsReport
+from frigate.analytics.state import load_state
+from frigate.config import FrigateConfig
+
+if TYPE_CHECKING:
+    from frigate.notices.registry import NoticeRegistry
+    from frigate.stats.emitter import StatsEmitter
+
+logger = logging.getLogger(__name__)
+
+COLLECTORS: dict[str, Callable[[ReportContext], BaseModel | None]] = {
+    "install": install.collect,
+    "hardware": hardware.collect,
+    "detection": detection.collect,
+    "cameras": cameras.collect,
+    "features": features.collect,
+    "health": health.collect,
+}
+
+# shown in the preview until the first report creates a real ID
+PREVIEW_INSTALL_ID = "0" * 32
+
+
+def build_report(
+    ctx: ReportContext, install_id: str, sent_at: int | None = None
+) -> AnalyticsReport:
+    """Run every collector; one that fails sends its section as null."""
+    sections: dict[str, Any] = {}
+
+    for name, collect in COLLECTORS.items():
+        try:
+            sections[name] = collect(ctx)
+        except Exception:
+            # a collector bug must cost one section, never the whole report
+            logger.warning("Analytics %s section failed", name, exc_info=True)
+            sections[name] = None
+
+    return AnalyticsReport.model_validate(
+        {
+            "schema_version": SCHEMA_VERSION,
+            "install_id": install_id,
+            "report_id": str(uuid4()),
+            "sent_at": int(time.time()) if sent_at is None else sent_at,
+            **sections,
+        }
+    )
+
+
+def gather_context(
+    config: FrigateConfig,
+    stats_emitter: "StatsEmitter | None",
+    notice_registry: "NoticeRegistry | None",
+) -> ReportContext:
+    return ReportContext(
+        config=config,
+        stats=stats_emitter.get_latest_stats() if stats_emitter is not None else {},
+        notice_stats=notice_registry.stats() if notice_registry is not None else [],
+    )
+
+
+def preview_report(
+    config: FrigateConfig,
+    stats_emitter: "StatsEmitter | None",
+    notice_registry: "NoticeRegistry | None",
+) -> AnalyticsReport:
+    """The report the next send would carry, without sending it."""
+    state = load_state()
+    ctx = gather_context(config, stats_emitter, notice_registry)
+    return build_report(ctx, state.install_id if state else PREVIEW_INSTALL_ID)

frigate/analytics/reporter.py

@@ -0,0 +1,177 @@
+"""Send one analytics report a day while the admin has opted in."""
+
+import logging
+import random
+import threading
+import time
+from collections.abc import Callable
+from multiprocessing.synchronize import Event as MpEvent
+from typing import TYPE_CHECKING
+
+from frigate.analytics.context import ReportContext
+from frigate.analytics.report import build_report
+from frigate.analytics.state import (
+    STATE_PATH,
+    AnalyticsState,
+    delete_state,
+    load_state,
+    new_state,
+    save_state,
+)
+from frigate.analytics.transport import SendOutcome, send_report
+from frigate.config import FrigateConfig
+from frigate.config.holder import ConfigHolder
+from frigate.const import ANALYTICS_URL
+from frigate.notices import raise_notice, resolve_notice
+
+if TYPE_CHECKING:
+    from frigate.notices.registry import NoticeRegistry
+    from frigate.stats.emitter import StatsEmitter
+
+logger = logging.getLogger(__name__)
+
+WAKE_S = 10 * 60
+INTERVAL_S = 24 * 60 * 60
+JITTER_S = 60 * 60
+FIRST_DELAY_S = (15 * 60, 45 * 60)
+PROMPT_KIND = "analytics_prompt"
+
+
+class AnalyticsReporter(threading.Thread):
+    """Follows the live config, so a settings save needs no restart."""
+
+    def __init__(
+        self,
+        config_holder: ConfigHolder,
+        stats_emitter: "StatsEmitter",
+        notice_registry: "NoticeRegistry",
+        stop_event: MpEvent | threading.Event,
+        *,
+        state_path: str = STATE_PATH,
+        url: str = ANALYTICS_URL,
+        send: Callable[[str, str], SendOutcome] = send_report,
+        clock: Callable[[], float] = time.time,
+        rng: random.Random | None = None,
+    ) -> None:
+        super().__init__(name="analytics_reporter", daemon=True)
+        self.config_holder = config_holder
+        self.stats_emitter = stats_emitter
+        self.notice_registry = notice_registry
+        self.stop_event = stop_event
+        self.state_path = state_path
+        self.url = url
+        self.send = send
+        self.clock = clock
+        self.rng = rng or random.Random()
+        self.first_due = clock() + self.rng.uniform(*FIRST_DELAY_S)
+        self.interval = self._next_interval()
+        self.opted_in: bool | None = None
+        self.warned_unwritable = False
+        # a settings save runs on an API thread while a wake may be mid-attempt
+        self._lock = threading.Lock()
+        config_holder.subscribe(self._on_config)
+
+    def _next_interval(self) -> float:
+        return INTERVAL_S + self.rng.uniform(-JITTER_S, JITTER_S)
+
+    def run(self) -> None:
+        while True:
+            try:
+                self.tick()
+            except Exception:
+                logger.exception("Analytics reporter failed")
+
+            if self.stop_event.wait(WAKE_S):
+                break
+
+    def _on_config(self, config: FrigateConfig) -> None:
+        # a save can turn sharing off and back on between two wakes, so an
+        # opt-out is handled when it's saved rather than at the next wake
+        with self._lock:
+            if not config.safe_mode:
+                self._apply_consent(config.telemetry.analytics)
+
+    def _apply_consent(self, opted_in: bool) -> None:
+        # called with the lock held
+        if opted_in == self.opted_in:
+            return
+
+        self.opted_in = opted_in
+
+        if opted_in:
+            resolve_notice(PROMPT_KIND)
+        else:
+            raise_notice(PROMPT_KIND)
+            delete_state(self.state_path)
+
+    def tick(self) -> None:
+        with self._lock:
+            config = self.config_holder.config
+
+            # safe mode parses a default config where analytics reads as off,
+            # and handling that as an opt-out would delete the install ID
+            if config.safe_mode:
+                return
+
+            self._apply_consent(config.telemetry.analytics)
+
+            if not config.telemetry.analytics:
+                return
+
+            now = self.clock()
+
+            if now < self.first_due:
+                return
+
+            state = load_state(self.state_path) or new_state()
+
+            if not self._due(state.last_attempt_at, now):
+                return
+
+            # saved before sending, so a failing endpoint or a crash mid-send
+            # still waits a full interval; without saved state every boot would
+            # send under a new install ID
+            if not save_state(AnalyticsState(state.install_id, now), self.state_path):
+                if not self.warned_unwritable:
+                    logger.warning(
+                        "Analytics is on, but %s isn't writable, so no report is sent",
+                        self.state_path,
+                    )
+                    self.warned_unwritable = True
+
+                return
+
+            self.interval = self._next_interval()
+
+        # the lock stays free during the request, so a save never waits on it
+        self._send(state.install_id, now)
+
+    def _due(self, last_attempt_at: float, now: float) -> bool:
+        # a last attempt stamped in the future came from a wrong clock
+        return (
+            now >= last_attempt_at + self.interval or last_attempt_at > now + INTERVAL_S
+        )
+
+    def _send(self, install_id: str, now: float) -> None:
+        notice_stats = self.notice_registry.stats()
+        ctx = ReportContext(
+            config=self.config_holder.config,
+            stats=self.stats_emitter.get_latest_stats(),
+            notice_stats=notice_stats,
+        )
+        report = build_report(ctx, install_id, sent_at=int(now))
+        body = report.model_dump_json()
+
+        # consent can be withdrawn while the report builds
+        if not self.config_holder.config.telemetry.analytics:
+            return
+
+        if self.send(self.url, body) is not SendOutcome.accepted:
+            return
+
+        # a failed health section sent no notice counts, so they stay pending
+        if report.health is not None:
+            self.notice_registry.mark_reported(notice_stats)
+
+        logger.info("Sent the daily analytics report")
+        logger.debug("Analytics report: %s", body)

frigate/analytics/schema.py

@@ -0,0 +1,407 @@
+"""Models for the analytics report, the contract with the ingest endpoint.
+
+Every field carries a description and an x-public flag, and no field accepts
+user-entered text, so a report can't carry camera names or other free text.
+"""
+
+from enum import StrEnum
+from typing import Any
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from frigate.config.camera.birdseye import BirdseyeModeEnum
+from frigate.config.camera.camera import CameraTypeEnum
+from frigate.config.camera.genai import GenAIProviderEnum, GenAIRoleEnum
+from frigate.config.classification import ModelSizeEnum
+from frigate.detectors.detector_config import ModelTypeEnum, SceneEnum
+from frigate.detectors.detector_types import DetectorTypeEnum
+from frigate.ffmpeg_presets import PRESETS_HW_ACCEL_DECODE, PRESETS_INPUT
+from frigate.notices.types import NOTICE_KINDS
+
+SCHEMA_VERSION = 1
+
+
+class ImageVariant(StrEnum):
+    standard = "standard"
+    rpi = "rpi"
+    tensorrt = "tensorrt"
+    tensorrt_jp6 = "tensorrt-jp6"
+    rocm = "rocm"
+    rk = "rk"
+    synaptics = "synaptics"
+    dev = "dev"
+    other = "other"
+
+
+class InstallType(StrEnum):
+    ha_addon = "ha_addon"
+    docker = "docker"
+    podman = "podman"
+    kubernetes = "kubernetes"
+    unknown = "unknown"
+
+
+class Arch(StrEnum):
+    x86_64 = "x86_64"
+    aarch64 = "aarch64"
+    other = "other"
+
+
+class GpuVendor(StrEnum):
+    intel = "intel"
+    amd = "amd"
+    nvidia = "nvidia"
+    rockchip = "rockchip"
+    rpi = "rpi"
+    other = "other"
+
+
+class DecodeFamily(StrEnum):
+    nvidia = "nvidia"
+    vaapi = "vaapi"
+    rkmpp = "rkmpp"
+    intel_qsv = "intel-qsv"
+    jetson = "jetson"
+    rpi = "rpi"
+    other = "other"
+
+
+class HardwareKey(StrEnum):
+    edgetpu_pci = "edgetpu:pci"
+    edgetpu_usb = "edgetpu:usb"
+    openvino_gpu = "openvino:GPU"
+    openvino_npu = "openvino:NPU"
+    onnx_amd = "onnx:amd"
+    onnx_nvidia = "onnx:nvidia"
+    tensorrt = "tensorrt"
+    hailo = "hailo"
+    memryx = "memryx"
+    deepx = "deepx"
+    rknn = "rknn"
+    axengine = "axengine"
+    synaptics = "synaptics"
+    cpu = "cpu"
+    other = "other"
+
+
+class ModelSource(StrEnum):
+    default = "default"
+    plus = "plus"
+    custom = "custom"
+
+
+class HeightBucket(StrEnum):
+    le_360 = "le_360"
+    h480 = "480"
+    h720 = "720"
+    h1080 = "1080"
+    h1440 = "1440"
+    ge_2160 = "ge_2160"
+
+
+class FpsBucket(StrEnum):
+    le_5 = "le_5"
+    f6_10 = "6_10"
+    gt_10 = "gt_10"
+
+
+class RetainBucket(StrEnum):
+    zero = "0"
+    d1_7 = "1_7"
+    d8_30 = "8_30"
+    gt_30 = "gt_30"
+
+
+class ConnectionQuality(StrEnum):
+    excellent = "excellent"
+    fair = "fair"
+    poor = "poor"
+    unusable = "unusable"
+
+
+class EnrichmentDevice(StrEnum):
+    cpu = "cpu"
+    cuda = "cuda"
+    tensorrt = "tensorrt"
+    migraphx = "migraphx"
+    openvino_cpu = "openvino_cpu"
+    openvino_gpu = "openvino_gpu"
+    openvino_npu = "openvino_npu"
+    other = "other"
+
+
+class SemanticSearchModel(StrEnum):
+    jinav1 = "jinav1"
+    jinav2 = "jinav2"
+    genai = "genai"
+
+
+class TranscriptionModel(StrEnum):
+    whisper = "whisper"
+    genai = "genai"
+
+
+class UserRole(StrEnum):
+    admin = "admin"
+    viewer = "viewer"
+    custom = "custom"
+
+
+class EnrichmentTiming(StrEnum):
+    face = "face"
+    lpr = "lpr"
+    plate_detection = "plate_detection"
+    image_embedding = "image_embedding"
+    text_embedding = "text_embedding"
+    review_description = "review_description"
+    object_description = "object_description"
+
+
+def _preset_keys(presets: dict[str, Any]) -> dict[str, str]:
+    keys = [name.removeprefix("preset-") for name in presets]
+    return {key: key for key in [*keys, "custom", "none"]}
+
+
+# built from the registries they mirror, so a new preset or notice kind reaches
+# the schema through generate_analytics_schema.py instead of a hand edit
+HwaccelKey = StrEnum("HwaccelKey", _preset_keys(PRESETS_HW_ACCEL_DECODE))  # type: ignore[misc]
+InputPresetKey = StrEnum("InputPresetKey", _preset_keys(PRESETS_INPUT))  # type: ignore[misc]
+NoticeKindKey = StrEnum(  # type: ignore[misc]
+    "NoticeKindKey",
+    {key: key for key, kind in NOTICE_KINDS.items() if kind.reportable},
+)
+
+
+class AnalyticsModel(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+
+
+def metric(description: str, *, public: bool = True, **kwargs: Any) -> Any:
+    """Declare a report field; the description and flag land in the schema."""
+    return Field(
+        description=description, json_schema_extra={"x-public": public}, **kwargs
+    )
+
+
+def count(description: str) -> Any:
+    return metric(description, ge=0)
+
+
+class InstallSection(AnalyticsModel):
+    version: str = metric("Frigate version string", max_length=32)
+    image_variant: ImageVariant = metric("Published image the install runs")
+    install_type: InstallType = metric("How Frigate is installed")
+    arch: Arch = metric("CPU architecture")
+    kernel: str = metric(
+        "Host kernel as major.minor", pattern=r"^(\d{1,3}\.\d{1,3}|unknown)$"
+    )
+    run_as_root: bool = metric("Whether the main process runs as root")
+
+
+class GpuInfo(AnalyticsModel):
+    vendor: GpuVendor = metric("GPU vendor")
+    name: str = metric("GPU name as the hardware reports it", max_length=64)
+
+
+class StorageInfo(AnalyticsModel):
+    record_fs: str = metric("Filesystem of the recordings volume", max_length=16)
+    record_total_gb: int = count("Size of the recordings volume in GB")
+    record_used_pct: int = metric(
+        "Percent of the recordings volume in use", ge=0, le=100
+    )
+
+
+class HardwareSection(AnalyticsModel):
+    cpu_model: str = metric(
+        "CPU or board model as the hardware reports it", max_length=64
+    )
+    cpu_cores: int = count("Logical CPU count")
+    memory_gb: int = count("Total memory in GB")
+    gpus: list[GpuInfo] = metric("GPUs the stats collector found")
+    decode_families: list[DecodeFamily] = metric(
+        "Hardware decode families this system can use"
+    )
+    detection_hardware: dict[HardwareKey, int] = metric(
+        "Detection hardware found, as unit counts by kind"
+    )
+    storage: StorageInfo = metric("Recordings storage")
+
+
+class DetectionModel(AnalyticsModel):
+    detector: DetectorTypeEnum = metric("Detector type the model runs on")
+    devices: int = count("Devices the model runs on")
+    model_type: ModelTypeEnum = metric("Model architecture")
+    input: str = metric("Model input size as WxH", pattern=r"^\d{1,5}x\d{1,5}$")
+    source: ModelSource = metric("Where the model came from", public=False)
+    inference_ms: float | None = metric(
+        "Mean inference time across the model's detector processes, null before the first stats",
+        ge=0,
+    )
+
+
+class DetectionSection(AnalyticsModel):
+    models: dict[SceneEnum, DetectionModel] = metric("Detection models keyed by scene")
+    detection_fps: float = metric("Detections per second across cameras", ge=0)
+    skipped_fps: float = metric("Frames per second skipped across cameras", ge=0)
+
+
+class RetainDays(AnalyticsModel):
+    continuous: dict[RetainBucket, int] = metric(
+        "Recording cameras by continuous retention in days"
+    )
+    motion: dict[RetainBucket, int] = metric(
+        "Recording cameras by motion retention in days"
+    )
+    alerts: dict[RetainBucket, int] = metric(
+        "Recording cameras by alert retention in days"
+    )
+    detections: dict[RetainBucket, int] = metric(
+        "Recording cameras by detection retention in days"
+    )
+
+
+class CamerasSection(AnalyticsModel):
+    total: int = count("Configured cameras")
+    enabled: int = count("Enabled cameras")
+    types: dict[CameraTypeEnum, int] = metric("Cameras by type")
+    detect_height: dict[HeightBucket, int] = metric(
+        "Cameras by detect resolution height"
+    )
+    detect_fps: dict[FpsBucket, int] = metric("Cameras by detect fps")
+    hwaccel: dict[HwaccelKey, int] = metric(
+        "Cameras by the resolved hwaccel preset of the detect input"
+    )
+    input_preset: dict[InputPresetKey, int] = metric(
+        "Cameras by the input preset of the detect input"
+    )
+    go2rtc_restream: int = count("Cameras with an input from the go2rtc restream")
+    separate_detect_stream: int = count(
+        "Cameras whose detect input differs from their record input"
+    )
+    detect: int = count("Cameras with detection on")
+    record: int = count("Cameras with recording on")
+    sub_stream_record: int = count("Cameras with sub stream recording on")
+    snapshots: int = count("Cameras with snapshots on")
+    audio: int = count("Cameras with audio detection on")
+    audio_transcription: int = count("Cameras with audio transcription on")
+    birdseye: int = count("Cameras in birdseye")
+    onvif: int = count("Cameras with an ONVIF host")
+    autotracking: int = count("Cameras with PTZ autotracking on")
+    face_recognition: int = count("Cameras with face recognition on")
+    lpr: int = count("Cameras with license plate recognition on")
+    review_genai: int = count("Cameras with GenAI review summaries on")
+    object_genai: int = count("Cameras with GenAI object descriptions on")
+    notifications: int = count("Cameras with notifications on")
+    zones: int = count("Zones across cameras")
+    cameras_with_zones: int = count("Cameras with at least one zone")
+    motion_masks: int = count("Motion masks across cameras")
+    object_masks: int = count("Object masks across cameras")
+    connection_quality: dict[ConnectionQuality, int] = metric(
+        "Cameras by connection quality at send time"
+    )
+    retain_days: RetainDays = metric("Recording retention")
+
+
+class EnrichmentUsage(AnalyticsModel):
+    enabled: bool = metric("Whether the enrichment is on")
+    model_size: ModelSizeEnum = metric("Configured model size")
+    device: EnrichmentDevice | None = metric(
+        "Device the model loaded on, null when it isn't loaded"
+    )
+
+
+class SemanticSearchUsage(AnalyticsModel):
+    enabled: bool = metric("Whether semantic search is on")
+    model: SemanticSearchModel | None = metric(
+        "Embedding model, genai for a GenAI provider"
+    )
+    model_size: ModelSizeEnum = metric("Configured model size")
+    device: EnrichmentDevice | None = metric(
+        "Device the model loaded on, null when it isn't loaded"
+    )
+    triggers: int = count("Semantic search triggers across cameras")
+
+
+class TranscriptionUsage(AnalyticsModel):
+    enabled: bool = metric("Whether audio transcription is on")
+    model: TranscriptionModel | None = metric(
+        "Transcription model, genai for a GenAI provider"
+    )
+    model_size: ModelSizeEnum = metric("Configured model size")
+
+
+class GenAIUsage(AnalyticsModel):
+    providers: dict[GenAIProviderEnum, int] = metric(
+        "Configured GenAI providers by type"
+    )
+    roles: dict[GenAIRoleEnum, int] = metric("Configured GenAI providers by role")
+
+
+class ClassificationUsage(AnalyticsModel):
+    state: int = count("Custom state classification models")
+    object: int = count("Custom object classification models")
+
+
+class BirdseyeUsage(AnalyticsModel):
+    enabled: bool = metric("Whether birdseye is on")
+    modes: list[BirdseyeModeEnum] = metric("Birdseye modes")
+    restream: bool = metric("Whether birdseye is restreamed")
+
+
+class FeaturesSection(AnalyticsModel):
+    face_recognition: EnrichmentUsage = metric("Face recognition")
+    lpr: EnrichmentUsage = metric("License plate recognition")
+    semantic_search: SemanticSearchUsage = metric("Semantic search")
+    audio_transcription: TranscriptionUsage = metric("Audio transcription")
+    genai: GenAIUsage = metric("Generative AI providers")
+    classification_models: ClassificationUsage = metric("Custom classification models")
+    birdseye: BirdseyeUsage = metric("Birdseye")
+    mqtt: bool = metric("Whether MQTT is on")
+    notifications: bool = metric("Whether web push notifications are on")
+    auth: bool = metric("Whether authentication is on")
+    proxy_auth: bool = metric("Whether a proxy supplies the user header")
+    tls: bool = metric("Whether TLS is on")
+    users: dict[UserRole, int] = metric("Users by role")
+    camera_groups: int = count("Camera groups")
+    profiles: int = count("Profiles")
+    plus_api_key: bool = metric("Whether a Frigate+ API key is set", public=False)
+
+
+class NoticeCounts(AnalyticsModel):
+    occurrences: int = count("Occurrences since the last accepted report")
+    dismissals: int = count("Dismissals since the last accepted report")
+
+
+class HealthSection(AnalyticsModel):
+    uptime_hours: int = count("Hours since Frigate started")
+    cpu_percent: int = metric("System CPU use at send time", ge=0, le=100)
+    enrichment_ms: dict[EnrichmentTiming, float] = metric(
+        "Mean enrichment inference times in milliseconds"
+    )
+    retention_unmet: bool = metric(
+        "Whether storage can't keep the configured retention"
+    )
+    notices: dict[NoticeKindKey, NoticeCounts] = metric(
+        "Notice counts by kind since the last accepted report", public=False
+    )
+
+
+class AnalyticsReport(AnalyticsModel):
+    schema_version: int = metric("Report format version", ge=1)
+    install_id: str = metric(
+        "Random install identifier", public=False, pattern=r"^[0-9a-f]{32}$"
+    )
+    report_id: str = metric(
+        "Random identifier of this report",
+        public=False,
+        pattern=r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$",
+    )
+    sent_at: int = count("Unix time the report was built")
+    install: InstallSection | None = metric("Install, null if its collector failed")
+    hardware: HardwareSection | None = metric("Hardware, null if its collector failed")
+    detection: DetectionSection | None = metric(
+        "Object detection, null if its collector failed"
+    )
+    cameras: CamerasSection | None = metric("Cameras, null if its collector failed")
+    features: FeaturesSection | None = metric("Features, null if its collector failed")
+    health: HealthSection | None = metric("Health, null if its collector failed")

frigate/analytics/state.py

@@ -0,0 +1,85 @@
+"""The install's analytics identity and last attempt time, kept under /config."""
+
+import json
+import logging
+import os
+import re
+from dataclasses import dataclass
+from uuid import uuid4
+
+from frigate.const import CONFIG_DIR
+
+logger = logging.getLogger(__name__)
+
+STATE_PATH = os.path.join(CONFIG_DIR, ".analytics.json")
+INSTALL_ID_PATTERN = re.compile(r"[0-9a-f]{32}")
+
+
+@dataclass(frozen=True)
+class AnalyticsState:
+    install_id: str
+    last_attempt_at: float
+
+
+def new_state() -> AnalyticsState:
+    return AnalyticsState(install_id=uuid4().hex, last_attempt_at=0.0)
+
+
+def load_state(path: str = STATE_PATH) -> AnalyticsState | None:
+    """The saved state, or None when the file is missing or unusable."""
+    try:
+        with open(path) as f:
+            data = json.load(f)
+    except FileNotFoundError:
+        return None
+    except (OSError, ValueError):
+        logger.warning("Ignoring unreadable analytics state at %s", path)
+        return None
+
+    if not isinstance(data, dict):
+        return None
+
+    install_id = data.get("install_id")
+    last_attempt_at = data.get("last_attempt_at")
+
+    if (
+        not isinstance(install_id, str)
+        or not INSTALL_ID_PATTERN.fullmatch(install_id)
+        or isinstance(last_attempt_at, bool)
+        or not isinstance(last_attempt_at, int | float)
+    ):
+        logger.warning("Ignoring invalid analytics state at %s", path)
+        return None
+
+    return AnalyticsState(install_id=install_id, last_attempt_at=float(last_attempt_at))
+
+
+def save_state(state: AnalyticsState, path: str = STATE_PATH) -> bool:
+    """Write the state atomically, returning False when it can't be written."""
+    temp_path = f"{path}.tmp"
+
+    try:
+        with open(temp_path, "w") as f:
+            json.dump(
+                {
+                    "install_id": state.install_id,
+                    "last_attempt_at": state.last_attempt_at,
+                },
+                f,
+            )
+
+        os.replace(temp_path, path)
+    except OSError:
+        return False
+
+    return True
+
+
+def delete_state(path: str = STATE_PATH) -> None:
+    """Forget the install ID, so a later opt-in starts a fresh identity."""
+    try:
+        os.remove(path)
+    except FileNotFoundError:
+        pass
+    except OSError:
+        logger.warning("Unable to delete analytics state at %s", path)

frigate/analytics/transport.py

@@ -0,0 +1,54 @@
+"""POST a report to the ingest endpoint."""
+
+import logging
+from enum import Enum
+
+import requests
+
+from frigate.version import VERSION
+
+logger = logging.getLogger(__name__)
+
+TIMEOUT_S = 30
+
+
+class SendOutcome(Enum):
+    accepted = "accepted"
+    rejected = "rejected"
+    rate_limited = "rate_limited"
+    failed = "failed"
+
+
+def send_report(url: str, body: str) -> SendOutcome:
+    """Send one report. Never raises; the outcome says what happened."""
+    try:
+        # a redirect would turn the POST into a GET, so it counts as a failure
+        response = requests.post(
+            url,
+            data=body.encode(),
+            headers={
+                "Content-Type": "application/json",
+                "User-Agent": f"Frigate/{VERSION}",
+            },
+            timeout=TIMEOUT_S,
+            allow_redirects=False,
+        )
+    except requests.RequestException as err:
+        logger.warning("Unable to send the analytics report: %s", err)
+        return SendOutcome.failed
+
+    status = response.status_code
+
+    if 200 <= status < 300:
+        return SendOutcome.accepted
+
+    if status == 400:
+        logger.warning("The analytics report was rejected: %s", response.text[:200])
+        return SendOutcome.rejected
+
+    if status == 429:
+        logger.debug("The analytics endpoint is rate limiting this install")
+        return SendOutcome.rate_limited
+
+    logger.warning("The analytics endpoint returned %s", status)
+    return SendOutcome.failed

frigate/api/analytics.py

@@ -0,0 +1,25 @@
+"""Analytics APIs."""
+
+import logging
+
+from fastapi import APIRouter, Depends, Request
+from fastapi.responses import JSONResponse
+
+from frigate.analytics.report import preview_report
+from frigate.api.auth import require_role
+from frigate.api.defs.tags import Tags
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(tags=[Tags.analytics])
+
+
+@router.get("/analytics/preview", dependencies=[Depends(require_role(["admin"]))])
+def get_analytics_preview(request: Request) -> JSONResponse:
+    """Get the analytics report Frigate would send next, without sending it."""
+    report = preview_report(
+        request.app.frigate_config,
+        request.app.stats_emitter,
+        request.app.notice_registry,
+    )
+    return JSONResponse(content=report.model_dump(mode="json"))

frigate/api/app.py

@@ -63,7 +63,6 @@ from frigate.util.builtin import (
     flatten_config_data,
     load_labels,
     process_config_query_string,
-    split_config_key_path,
     update_yaml_file_bulk,
 )
 from frigate.util.config import (
@@ -71,15 +70,9 @@ from frigate.util.config import (
     find_config_file,
     redact_credential,
 )
-from frigate.util.live_streams import (
-    generated_transcode_streams,
-    sync_transcode_streams,
-)
 from frigate.util.object_names import get_categorized_object_names
 from frigate.util.schema import get_config_schema
 from frigate.util.services import (
-    Go2rtcStreamIssue,
-    find_restricted_go2rtc_stream_changes,
     get_nvidia_driver_info,
     process_logs,
     restart_frigate,
@@ -313,12 +306,9 @@ def config(request: Request):
         mode="json", warnings="none", exclude_none=True
     )
 
-    is_admin = request.headers.get("remote-role") == "admin"
-
-    # hide environment_vars and the notification email from non-admin users
-    if not is_admin:
+    # remove environment_vars for non-admin users
+    if request.headers.get("remote-role") != "admin":
         config.pop("environment_vars", None)
-        redact_credential(config["notifications"], "email")
 
     # redact mqtt credentials
     redact_credential(config["mqtt"], "password")
@@ -375,15 +365,7 @@ def config(request: Request):
                 camera_name
             )
             if base_sections:
-                # copy so redaction below can't alter the profile manager's cache
-                camera_dict["base_config"] = copy.deepcopy(base_sections)
-
-        # cameras inherit the global notification email
-        if not is_admin:
-            redact_credential(camera_dict["notifications"], "email")
-            redact_credential(
-                camera_dict.get("base_config", {}).get("notifications", {}), "email"
-            )
+                camera_dict["base_config"] = base_sections
 
     # remove go2rtc stream passwords
     go2rtc: dict[str, Any] = config_obj.go2rtc.model_dump(
@@ -411,11 +393,6 @@ def config(request: Request):
         model_dict["non_logo_attributes"] = model.non_logo_attributes
         model_dict["labelmap"] = model.merged_labelmap
 
-        # report the configured reference rather than the resolved cache path,
-        # so saving the config back doesn't lose the Frigate+ model
-        if model.plus_id:
-            model_dict["path"] = f"plus://{model.plus_id}"
-
         if not config["plus"]["enabled"]:
             continue
 
@@ -452,8 +429,6 @@ def ffmpeg_presets():
         hwaccel_presets = [
             "preset-rpi-64-h264",
             "preset-rpi-64-h265",
-            "preset-apple-silicon-h264",
-            "preset-apple-silicon-h265",
             "preset-jetson-h264",
             "preset-jetson-h265",
             "preset-rkmpp",
@@ -548,63 +523,6 @@ def config_raw():
         )
 
 
-def _go2rtc_streams(raw_config: str) -> Any:
-    """Load go2rtc.streams with the same loader Frigate and go2rtc startup use.
-
-    Raises ruamel.yaml.YAMLError when the config cannot be parsed.
-    """
-    loaded = ruamel.yaml.YAML().load(raw_config)
-    go2rtc = loaded.get("go2rtc") if isinstance(loaded, dict) else None
-    return go2rtc.get("streams") if isinstance(go2rtc, dict) else None
-
-
-def _restricted_go2rtc_streams_response(
-    old_raw_config: str, new_raw_config: str
-) -> JSONResponse | None:
-    """Reject config changes that add restricted go2rtc stream sources.
-
-    The same sources are rejected by PUT /go2rtc/streams, and go2rtc would
-    otherwise load them from the saved config on the next restart.
-    """
-    try:
-        new_streams = _go2rtc_streams(new_raw_config)
-    except ruamel.yaml.YAMLError:
-        logger.warning("Rejected config change that could not be parsed")
-        return JSONResponse(
-            content={"success": False, "message": "Unable to parse config"},
-            status_code=400,
-        )
-
-    try:
-        old_streams = _go2rtc_streams(old_raw_config)
-    except ruamel.yaml.YAMLError:
-        # with no readable saved config, every source is treated as new
-        old_streams = None
-
-    issues = find_restricted_go2rtc_stream_changes(old_streams, new_streams)
-    if not issues:
-        return None
-
-    messages = []
-    for issue, label in (
-        (Go2rtcStreamIssue.restricted, "Restricted go2rtc stream source in"),
-        (Go2rtcStreamIssue.unknown_variable, "Unknown variable in go2rtc stream"),
-        (
-            Go2rtcStreamIssue.invalid_placeholder,
-            "Invalid variable placeholder in go2rtc stream",
-        ),
-    ):
-        names = [name for name, found in issues.items() if found == issue]
-        if names:
-            messages.append(f"{label}: {', '.join(names)}")
-
-    logger.warning("Rejected config change: %s", "; ".join(messages))
-    return JSONResponse(
-        content={"success": False, "message": "; ".join(messages)},
-        status_code=400,
-    )
-
-
 @router.post("/config/save", dependencies=[Depends(require_role(["admin"]))])
 def config_save(save_option: str, body: Any = Body(media_type="text/plain")):
     new_config = body.decode()
@@ -681,22 +599,10 @@ def config_save(save_option: str, body: Any = Body(media_type="text/plain")):
             status_code=400,
         )
 
-    config_file = find_config_file()
-
-    try:
-        with open(config_file) as f:
-            old_raw_config = f.read()
-    except OSError:
-        old_raw_config = ""
-
-    restricted_response = _restricted_go2rtc_streams_response(
-        old_raw_config, new_config
-    )
-    if restricted_response is not None:
-        return restricted_response
-
     # Save the config to file
     try:
+        config_file = find_config_file()
+
         with open(config_file, "w") as f:
             f.write(new_config)
             f.close()
@@ -902,17 +808,6 @@ def _config_set_in_memory(request: Request, body: AppConfigSetBody) -> JSONRespo
         )
 
 
-def _config_path_exists(data: Any, key_path: str) -> bool:
-    """Return whether a dotted config path is present in parsed yaml."""
-    for key in split_config_key_path(key_path):
-        if not isinstance(data, dict) or key not in data:
-            return False
-
-        data = data[key]
-
-    return True
-
-
 @router.put("/config/set", dependencies=[Depends(require_role(["admin"]))])
 def config_set(request: Request, body: AppConfigSetBody):
     config_file = find_config_file()
@@ -967,19 +862,6 @@ def config_set(request: Request, body: AppConfigSetBody):
                         status_code=400,
                     )
 
-                # delete replaced paths first so their maps are rewritten in
-                # the order sent; update_yaml would otherwise keep old order
-                if body.replace_paths:
-                    old_yaml = ruamel.yaml.YAML(typ="safe").load(old_raw_config) or {}
-                    updates = {
-                        **{
-                            path: ""
-                            for path in body.replace_paths
-                            if _config_path_exists(old_yaml, path)
-                        },
-                        **updates,
-                    }
-
                 # apply all updates in a single operation
                 update_yaml_file_bulk(config_file, updates)
 
@@ -1031,13 +913,6 @@ def config_set(request: Request, body: AppConfigSetBody):
                         ),
                         status_code=400,
                     )
-                restricted_response = _restricted_go2rtc_streams_response(
-                    old_raw_config, new_raw_config
-                )
-                if restricted_response is not None:
-                    with open(config_file, "w") as f:
-                        f.write(old_raw_config)
-                    return restricted_response
             except Exception as e:
                 logging.error(f"Error updating config: {e}")
                 return JSONResponse(
@@ -1050,15 +925,9 @@ def config_set(request: Request, body: AppConfigSetBody):
             if request.app.dispatcher is not None:
                 request.app.dispatcher.clear_runtime_state_for_yaml_keys(updates.keys())
 
-            go2rtc_synced = True
-
             if body.requires_restart == 0 or body.update_topic:
                 old_config: FrigateConfig = request.app.frigate_config
                 swap_runtime_config(request.app, config)
-                go2rtc_synced = sync_transcode_streams(
-                    generated_transcode_streams(old_config),
-                    generated_transcode_streams(config),
-                )
 
                 if body.update_topic:
                     if body.update_topic.startswith("config/cameras/"):
@@ -1118,7 +987,6 @@ def config_set(request: Request, body: AppConfigSetBody):
                             if body.requires_restart == 0
                             else "Config successfully updated, restart to apply"
                         ),
-                        "go2rtc_synced": go2rtc_synced,
                     }
                 ),
                 status_code=200,

frigate/api/auth.py

@@ -12,9 +12,8 @@ import threading
 import time
 from datetime import datetime
 from pathlib import Path
-from urllib.parse import parse_qs
+from urllib.parse import parse_qs, urlparse
 
-import requests
 from fastapi import APIRouter, Depends, HTTPException, Request, Response
 from fastapi.responses import JSONResponse, RedirectResponse
 from joserfc import jwt
@@ -32,8 +31,6 @@ from frigate.api.media_auth import (
     check_camera_access,
     deny_response_for_media_uri,
     is_role_restricted,
-    normalize_request_path,
-    split_request_uri,
 )
 from frigate.config import AuthConfig, ProxyConfig
 from frigate.const import CONFIG_DIR, JWT_SECRET_ENV_VAR, PASSWORD_HASH_ALGORITHM
@@ -133,18 +130,23 @@ def require_admin_by_default():
         if path.startswith(EXEMPT_PREFIXES):
             return
 
-        # Camera routes enforce per-camera access via route-level dependencies
-        # (e.g. require_camera_access). Match on the route template, not the raw
-        # path, so a camera named like another namespace (e.g. "faces") can't
-        # waive the admin check for that namespace's routes.
-        route = request.scope.get("route")
-        if (
-            route is not None
-            and route.path.startswith("/{camera_name}")
-            and request.path_params.get("camera_name")
-            in request.app.frigate_config.cameras
-        ):
-            return
+        # Dynamic camera path exemption:
+        # Any path whose first segment matches a configured camera name should
+        # bypass the global admin requirement. These endpoints enforce access
+        # via route-level dependencies (e.g. require_camera_access) to ensure
+        # per-camera authorization. This allows non-admin authenticated users
+        # (e.g. viewer role) to access camera-specific resources without
+        # needing admin privileges.
+        try:
+            if path.startswith("/"):
+                first_segment = path.split("/", 2)[1]
+                if (
+                    first_segment
+                    and first_segment in request.app.frigate_config.cameras
+                ):
+                    return
+        except Exception:
+            pass
 
         # For all other paths, require admin role
         # Internal port requests have admin role set automatically
@@ -316,19 +318,17 @@ def get_remote_addr(request: Request):
 
     route = list(reversed(forwarded_for.split(",")))
     logger.debug(f"IP Route: {[r for r in route]}")
-    trusted_proxies = [
-        ipaddress.ip_network(proxy, strict=False)
-        for proxy in request.app.frigate_config.auth.trusted_proxies
-    ]
+    trusted_proxies = []
+    for proxy in request.app.frigate_config.auth.trusted_proxies:
+        try:
+            network = ipaddress.ip_network(proxy)
+        except ValueError:
+            logger.warning(f"Unable to parse trusted network: {proxy}")
+        trusted_proxies.append(network)
 
     # return the first remote address that is not trusted
     for addr in route:
-        try:
-            ip = ipaddress.ip_address(addr.strip())
-        except ValueError:
-            logger.debug("Invalid address in X-Forwarded-For header")
-            return direct_addr or "127.0.0.1"
-
+        ip = ipaddress.ip_address(addr.strip())
         logger.debug(f"Checking {ip} (v{ip.version})")
         trusted = False
         for trusted_proxy in trusted_proxies:
@@ -473,11 +473,12 @@ def create_encoded_jwt(user, role, expiration, secret):
 
 def set_jwt_cookie(response: Response, cookie_name, encoded_jwt, max_age, secure):
     # TODO: ideally this would set secure as well, but that requires TLS
-    # Starlette sets SameSite=Lax by default. The cookie is still sent to
-    # same-site iframes (e.g. Home Assistant on the same host or domain), but
-    # not to cross-site ones. CSRF is also mitigated by requiring a custom
-    # X-CSRF-TOKEN header, which cross-origin pages cannot set without a CORS
-    # preflight that Frigate never grants (see check_csrf in api/fastapi_app.py).
+    # SameSite is intentionally left unset (browsers default to Lax). Setting
+    # SameSite=Lax/Strict would stop the cookie from being sent in cross-origin
+    # iframes, breaking embedded views such as the Home Assistant Frigate card.
+    # CSRF is instead mitigated by requiring a custom X-CSRF-TOKEN header, which
+    # cross-origin pages cannot set without a CORS preflight that Frigate never
+    # grants (see check_csrf in api/fastapi_app.py).
     response.set_cookie(
         key=cookie_name,
         value=encoded_jwt,
@@ -1002,7 +1003,7 @@ def create_user(
     HASH_ITERATIONS = request.app.frigate_config.auth.hash_iterations
     config_roles = list(request.app.frigate_config.auth.roles.keys())
 
-    if not re.match(r"^(?!\.+$)[A-Za-z0-9._]+$", body.username):
+    if not re.match("^[A-Za-z0-9._]+$", body.username):
         return JSONResponse(content={"message": "Invalid username"}, status_code=400)
 
     if body.role not in config_roles:
@@ -1228,44 +1229,11 @@ def _get_stream_owner_cameras(request: Request, stream_name: str) -> set[str]:
     return owner_cameras
 
 
-def _is_existing_go2rtc_stream(request: Request, stream_name: str) -> bool:
-    """Check that `stream_name` names a stream go2rtc already knows about.
-
-    go2rtc turns any `src` that is not an existing stream name into a new ad hoc
-    stream and starts the producer it describes, so the proxied live-stream
-    paths must only ever reference existing streams.
-    """
-    frigate_config = request.app.frigate_config
-
-    if _get_stream_owner_cameras(request, stream_name):
-        return True
-
-    config_streams = getattr(frigate_config.go2rtc, "streams", None) or {}
-    if stream_name in config_streams:
-        return True
-
-    # streams added at runtime through PUT /go2rtc/streams only exist in go2rtc
-    try:
-        r = requests.get("http://127.0.0.1:1984/api/streams", timeout=2)
-    except requests.RequestException:
-        logger.warning("Unable to fetch streams from go2rtc to authorize request")
-        return False
-
-    if not r.ok:
-        return False
-
-    try:
-        return stream_name in r.json()
-    except ValueError:
-        return False
-
-
 # nginx proxies these paths straight to go2rtc with authentication-only checks
 # (see auth_request.conf). Each names the desired stream via the `src` query
 # param, so the camera-level check must happen here in the `/auth` subrequest —
 # `require_go2rtc_stream_access` only guards the REST `/go2rtc/streams/{name}`
-# endpoint, not these proxied live-stream paths. The nginx locations are prefix
-# matches, so anything under these paths is proxied too.
+# endpoint, not these proxied live-stream paths.
 GO2RTC_STREAM_PROXY_PATHS = frozenset(
     {
         "/live/mse/api/ws",
@@ -1275,48 +1243,31 @@ GO2RTC_STREAM_PROXY_PATHS = frozenset(
 )
 
 
-def _is_go2rtc_stream_proxy_request(path: str, request: Request) -> bool:
-    # nginx marks requests routed through the go2rtc stream locations, and the
-    # normalized path catches them if that marker is ever missing
-    if request.headers.get("x-go2rtc-stream-proxy") == "1":
-        return True
-
-    normalized = normalize_request_path(path)
-    return any(normalized.startswith(p) for p in GO2RTC_STREAM_PROXY_PATHS)
-
-
 def deny_response_for_go2rtc_stream(
     original_url: str | None, role: str | None, request: Request
 ) -> int | None:
-    """Block go2rtc live-stream requests the current role may not make.
+    """Block role-restricted users from go2rtc live streams they cannot access.
 
-    Returns 403 when any `src` named in `original_url` is not an existing go2rtc
-    stream (for every role), or when it resolves to a camera outside a
-    restricted role's allow-list (or no `src` is provided for such a role),
-    otherwise None. Mirrors the resolution logic in
+    Returns 403 when any `src` stream named in `original_url` resolves to a
+    camera outside the role's allow-list (or when no `src` is provided on a
+    stream-proxy path), otherwise None. Mirrors the resolution logic in
     `require_go2rtc_stream_access` so substream names map to their owning
     camera correctly.
     """
     if not original_url:
         return None
 
-    path, query = split_request_uri(original_url)
-    if not _is_go2rtc_stream_proxy_request(path, request):
+    parsed = urlparse(original_url)
+    if parsed.path not in GO2RTC_STREAM_PROXY_PATHS:
         return None
 
     frigate_config = request.app.frigate_config
-    sources = parse_qs(query, keep_blank_values=True).get("src", [])
-
-    # an unknown src would make go2rtc create an ad hoc stream from it, which
-    # bypasses the restricted-source checks on PUT /go2rtc/streams
-    for src in sources:
-        if not _is_existing_go2rtc_stream(request, src):
-            return 403
 
     # admin and full-access roles (no allow-list) bypass the camera check
     if not role or not is_role_restricted(role, frigate_config):
         return None
 
+    sources = parse_qs(parsed.query).get("src", [])
     if not sources:
         # a stream-proxy request naming no stream has nothing legitimate to
         # show a restricted user

frigate/api/camera.py

@@ -33,25 +33,16 @@ from frigate.config.camera.updater import (
     CameraConfigUpdateEnum,
     CameraConfigUpdateTopic,
 )
+from frigate.config.env import UnknownVariableError, substitute_frigate_vars
 from frigate.models import User
-from frigate.util.builtin import (
-    clean_camera_user_pass,
-    clear_orphaned_comments,
-    get_record_segment_time,
-)
+from frigate.util.builtin import clean_camera_user_pass, get_record_segment_time
 from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
 from frigate.util.config import find_config_file
-from frigate.util.env import UnknownVariableError, substitute_frigate_vars
 from frigate.util.image import run_ffmpeg_snapshot
-from frigate.util.live_streams import (
-    generated_transcode_streams,
-    measure_stream_bitrate,
-    sync_transcode_streams,
-)
 from frigate.util.services import (
     analyze_record_keyframes,
     ffprobe_stream,
-    is_restricted_go2rtc_api_source,
+    is_restricted_go2rtc_source,
 )
 
 logger = logging.getLogger(__name__)
@@ -157,9 +148,9 @@ def go2rtc_camera_stream(request: Request, stream_name: str):
 )
 def go2rtc_add_stream(request: Request, stream_name: str, src: str = ""):
     """Add or update a go2rtc stream configuration."""
-    if src and is_restricted_go2rtc_api_source(src):
+    if src and is_restricted_go2rtc_source(src):
         logger.warning(
-            "Rejected go2rtc stream '%s' with restricted source",
+            "Rejected go2rtc stream '%s' with restricted source type (echo/expr/exec)",
             stream_name,
         )
         return JSONResponse(
@@ -178,9 +169,9 @@ def go2rtc_add_stream(request: Request, stream_name: str, src: str = ""):
             except UnknownVariableError:
                 resolved_src = src
 
-            if is_restricted_go2rtc_api_source(resolved_src):
+            if is_restricted_go2rtc_source(resolved_src):
                 logger.warning(
-                    "Rejected go2rtc stream '%s' with restricted source",
+                    "Rejected go2rtc stream '%s' with restricted source type (echo/expr/exec)",
                     stream_name,
                 )
                 return JSONResponse(
@@ -257,34 +248,6 @@ def go2rtc_delete_stream(stream_name: str):
         )
 
 
-@router.get(
-    "/go2rtc/streams/{stream_name}/bitrate",
-    dependencies=[Depends(require_role(["admin"]))],
-)
-async def go2rtc_stream_bitrate(request: Request, stream_name: str):
-    """Measure a go2rtc stream's bitrate over a few seconds."""
-    config: FrigateConfig = request.app.frigate_config
-    known = set(config.go2rtc.model_dump().get("streams") or {}) | set(
-        generated_transcode_streams(config)
-    )
-
-    if stream_name not in known:
-        return JSONResponse(
-            content={"success": False, "message": "Unknown stream"},
-            status_code=404,
-        )
-
-    kbps = await asyncio.to_thread(measure_stream_bitrate, stream_name)
-
-    if kbps is None:
-        return JSONResponse(
-            content={"success": False, "message": "Stream sent no data"},
-            status_code=502,
-        )
-
-    return JSONResponse(content={"success": True, "kbps": round(kbps)})
-
-
 @router.get("/ffprobe", dependencies=[Depends(require_role(["admin"]))])
 def ffprobe(request: Request, paths: str = "", detailed: bool = False):
     path_param = paths
@@ -1277,7 +1240,6 @@ async def delete_camera(
                 # Remove camera from config
                 if "cameras" in data and camera_name in data["cameras"]:
                     del data["cameras"][camera_name]
-                    clear_orphaned_comments(data["cameras"], data, "cameras")
 
                 # Remove camera from auth roles
                 auth = data.get("auth", {})
@@ -1380,12 +1342,6 @@ async def delete_camera(
     except Exception:
         logger.debug("Failed to remove go2rtc stream for %s", camera_name)
 
-    await asyncio.to_thread(
-        sync_transcode_streams,
-        generated_transcode_streams(frigate_config),
-        generated_transcode_streams(request.app.frigate_config),
-    )
-
     return JSONResponse(
         content={
             "success": True,

frigate/api/classification.py

@@ -1,6 +1,5 @@
 """Object classification APIs."""
 
-import asyncio
 import datetime
 import logging
 import os
@@ -49,9 +48,6 @@ logger = logging.getLogger(__name__)
 
 router = APIRouter(tags=[Tags.classification])
 
-# concurrent collections for one model share its temp and train directories
-example_collection_lock = asyncio.Lock()
-
 
 def invalid_name_response(value: str) -> JSONResponse:
     """Response for a name that cannot be used as a path component."""
@@ -1294,10 +1290,7 @@ async def generate_object_examples(request: Request, body: GenerateObjectExample
     if model_name is None:
         return invalid_name_response(body.model_name)
 
-    async with example_collection_lock:
-        await asyncio.to_thread(
-            collect_object_classification_examples, model_name, body.label
-        )
+    collect_object_classification_examples(model_name, body.label)
 
     return JSONResponse(
         content={"success": True, "message": "Example generation completed"},

frigate/api/config_util.py

@@ -51,7 +51,6 @@ def swap_runtime_config(app: FastAPI, config: FrigateConfig) -> None:
 
     if app.stats_emitter is not None:
         app.stats_emitter.config = config
-        app.stats_emitter.hardware_stats.set_config(config)
 
     if app.dispatcher is not None:
         app.dispatcher.config = config

frigate/api/defs/query/app_query_parameters.py

@@ -7,4 +7,4 @@ class AppTimelineHourlyQueryParameters(BaseModel):
     after: float | None = None
     before: float | None = None
     limit: int | None = 200
-    timezone: str | None = "UTC"
+    timezone: str | None = "utc"

frigate/api/defs/query/events_query_parameters.py

@@ -14,7 +14,6 @@ class EventsQueryParams(BaseModel):
     zone: str | None = "all"
     zones: str | None = "all"
     limit: int | None = 100
-    offset: int | None = Field(0, ge=0)
     after: float | None = None
     before: float | None = None
     time_range: str | None = DEFAULT_TIME_RANGE
@@ -40,7 +39,7 @@ class EventsQueryParams(BaseModel):
     max_length: float | None = None
     event_id: str | None = None
     sort: str | None = None
-    timezone: str | None = "UTC"
+    timezone: str | None = "utc"
 
 
 class EventsSearchQueryParams(BaseModel):
@@ -56,7 +55,6 @@ class EventsSearchQueryParams(BaseModel):
         deprecated=True,
     )
     limit: int | None = 50
-    offset: int | None = Field(0, ge=0)
     cameras: str | None = "all"
     labels: str | None = "all"
     sub_labels: str | None = "all"
@@ -68,7 +66,7 @@ class EventsSearchQueryParams(BaseModel):
     has_clip: bool | None = None
     has_snapshot: bool | None = None
     is_submitted: bool | None = None
-    timezone: str | None = "UTC"
+    timezone: str | None = "utc"
     min_score: float | None = None
     max_score: float | None = None
     min_speed: float | None = None
@@ -78,6 +76,6 @@ class EventsSearchQueryParams(BaseModel):
 
 
 class EventsSummaryQueryParams(BaseModel):
-    timezone: str | None = "UTC"
+    timezone: str | None = "utc"
     has_clip: int | None = None
     has_snapshot: int | None = None

frigate/api/defs/query/recordings_query_parameters.py

@@ -3,7 +3,7 @@ from pydantic.json_schema import SkipJsonSchema
 
 
 class MediaRecordingsSummaryQueryParams(BaseModel):
-    timezone: str = "UTC"
+    timezone: str = "utc"
     cameras: str | None = "all"
 
 

frigate/api/defs/query/review_query_parameters.py

@@ -19,7 +19,7 @@ class ReviewSummaryQueryParams(BaseModel):
     cameras: str = "all"
     labels: str = "all"
     zones: str = "all"
-    timezone: str = "UTC"
+    timezone: str = "utc"
 
 
 class ReviewActivityMotionQueryParams(BaseModel):

frigate/api/defs/request/app_body.py

@@ -10,8 +10,6 @@ class AppConfigSetBody(BaseModel):
     update_topic: str | None = None
     config_data: dict[str, Any] | None = None
     skip_save: bool = False
-    # paths rewritten whole, so a map saves in the order sent
-    replace_paths: list[str] = Field(default_factory=list)
 
 
 class GenAIProbeBody(BaseModel):

frigate/api/defs/tags.py

@@ -2,6 +2,7 @@ from enum import Enum
 
 
 class Tags(Enum):
+    analytics = "Analytics"
     app = "App"
     auth = "Auth"
     camera = "Camera"

frigate/api/event.py

@@ -129,7 +129,6 @@ def events(
         zones = zone
 
     limit = params.limit
-    offset = params.offset
     after = params.after
     before = params.before
     time_range = params.time_range
@@ -362,15 +361,11 @@ def events(
     else:
         order_by = Event.start_time.desc()
 
-    # offset paging needs a stable order when scores or speeds tie
-    tiebreaker = [Event.id] if sort and sort.startswith(("score", "speed")) else []
-
     events = (
         Event.select(*selected_columns)
         .where(reduce(operator.and_, clauses))
-        .order_by(order_by, *tiebreaker)
+        .order_by(order_by)
         .limit(limit)
-        .offset(offset)
         .dicts()
         .iterator()
     )
@@ -539,7 +534,6 @@ def events_search(
     search_type = params.search_type
     include_thumbnails = params.include_thumbnails
     limit = params.limit
-    offset = params.offset
     sort = params.sort
 
     # Filters
@@ -846,9 +840,6 @@ def events_search(
     if search_results:
         events_query = events_query.where(Event.id << list(search_results.keys()))
 
-    # sorts below are stable, so this orders ties for offset paging
-    events_query = events_query.order_by(Event.id)
-
     # Fetch events and process them in a single pass
     processed_events = []
     for event in events_query.dicts():
@@ -906,7 +897,7 @@ def events_search(
         processed_events.sort(key=lambda x: x["start_time"], reverse=True)
 
     # Limit the number of events returned
-    processed_events = processed_events[offset:][:limit]
+    processed_events = processed_events[:limit]
 
     return JSONResponse(content=processed_events)
 

frigate/api/export.py

@@ -58,7 +58,6 @@ from frigate.api.defs.response.export_response import (
 )
 from frigate.api.defs.response.generic_response import GenericResponse
 from frigate.api.defs.tags import Tags
-from frigate.api.media_auth import deny_response_for_media_uri
 from frigate.const import CLIPS_DIR, EXPORT_DIR
 from frigate.jobs.export import (
     ExportJob,
@@ -80,7 +79,6 @@ from frigate.record.export import (
     validate_ffmpeg_args,
 )
 from frigate.util.path import sanitize_contained_path
-from frigate.util.recording_coverage import recording_overlap
 from frigate.util.time import is_current_hour
 
 logger = logging.getLogger(__name__)
@@ -136,7 +134,6 @@ def _validate_export_case(export_case_id: str | None) -> JSONResponse | None:
 
 
 def _sanitize_existing_image(
-    request: Request,
     image_path: str | None,
 ) -> tuple[str | None, JSONResponse | None]:
     if not image_path:
@@ -144,15 +141,6 @@ def _sanitize_existing_image(
 
     existing_image = sanitize_contained_path(image_path, CLIPS_DIR)
 
-    # CLIPS_DIR is shared by every camera, so the caller must also be allowed
-    # to read the image.
-    if existing_image is not None and deny_response_for_media_uri(
-        f"/clips/{quote(os.path.relpath(existing_image, CLIPS_DIR))}",
-        request.headers.get("remote-role"),
-        request.app.frigate_config,
-    ):
-        existing_image = None
-
     if existing_image is None:
         return None, JSONResponse(
             content={"success": False, "message": "Invalid image path"},
@@ -178,7 +166,15 @@ def _validate_export_source(
 ) -> str | None:
     if playback_source == PlaybackSourceEnum.recordings:
         query = Recordings.select().where(
-            recording_overlap(start_time, end_time) & (Recordings.camera == camera_name)
+            (
+                Recordings.start_time.between(start_time, end_time)
+                | Recordings.end_time.between(start_time, end_time)
+                | (
+                    (start_time > Recordings.start_time)
+                    & (end_time < Recordings.end_time)
+                )
+            )
+            & (Recordings.camera == camera_name)
         )
 
         # a pinned export reads only that stream, so the other stream's
@@ -243,7 +239,9 @@ def _get_item_recording_export_errors(
 
         query = Recordings.select(Recordings.start_time, Recordings.end_time).where(
             Recordings.camera == camera_name,
-            recording_overlap(min_start, max_end),
+            Recordings.start_time.between(min_start, max_end)
+            | Recordings.end_time.between(min_start, max_end)
+            | ((min_start > Recordings.start_time) & (max_end < Recordings.end_time)),
         )
 
         # a pinned batch reads only that stream, so the other stream's
@@ -703,7 +701,7 @@ def export_recordings_batch(
     sanitized_images: list[str | None] = []
     for item in body.items:
         existing_image, image_validation_error = _sanitize_existing_image(
-            request, item.image_path
+            item.image_path
         )
         if image_validation_error is not None:
             return image_validation_error
@@ -851,9 +849,7 @@ def export_recording(
 
     playback_source = body.source
     friendly_name = body.name
-    existing_image, image_validation_error = _sanitize_existing_image(
-        request, body.image_path
-    )
+    existing_image, image_validation_error = _sanitize_existing_image(body.image_path)
     if image_validation_error is not None:
         return image_validation_error
 
@@ -1048,9 +1044,7 @@ def export_recording_custom(
 
     playback_source = body.source
     friendly_name = body.name
-    existing_image, image_validation_error = _sanitize_existing_image(
-        request, body.image_path
-    )
+    existing_image, image_validation_error = _sanitize_existing_image(body.image_path)
     if image_validation_error is not None:
         return image_validation_error
     ffmpeg_input_args = body.ffmpeg_input_args

frigate/api/fastapi_app.py

@@ -1,7 +1,6 @@
 import asyncio
 import logging
 import re
-from contextlib import asynccontextmanager
 
 from fastapi import Depends, FastAPI, Request
 from fastapi.responses import JSONResponse
@@ -13,8 +12,8 @@ from slowapi.middleware import SlowAPIMiddleware
 from starlette_context import middleware, plugins
 from starlette_context.plugins import Plugin
 
-from frigate.api import app as main_app
 from frigate.api import (
+    analytics,
     auth,
     camera,
     chat,
@@ -31,6 +30,7 @@ from frigate.api import (
     record,
     review,
 )
+from frigate.api import app as main_app
 from frigate.api.auth import get_jwt_secret, limiter, require_admin_by_default
 from frigate.comms.dispatcher import Dispatcher
 from frigate.comms.event_metadata_updater import (
@@ -82,20 +82,9 @@ def create_fastapi_app(
     config_holder: ConfigHolder | None = None,
     notice_registry: NoticeRegistry | None = None,
 ):
-    @asynccontextmanager
-    async def lifespan(app: FastAPI):
-        logger.info("FastAPI started")
-        asyncio.create_task(
-            debug_replay_auto_stop_watchdog(
-                replay_manager, frigate_config, config_publisher
-            )
-        )
-        yield
-
     logger.info("Starting FastAPI app")
     app = FastAPI(
         debug=False,
-        lifespan=lifespan,
         swagger_ui_parameters={"apisSorter": "alpha", "operationsSorter": "alpha"},
         dependencies=[Depends(require_admin_by_default())]
         if enforce_default_admin
@@ -131,6 +120,15 @@ def create_fastapi_app(
             database.close()
         return response
 
+    @app.on_event("startup")
+    async def startup():
+        logger.info("FastAPI started")
+        asyncio.create_task(
+            debug_replay_auto_stop_watchdog(
+                replay_manager, frigate_config, config_publisher
+            )
+        )
+
     # Rate limiter (used for login endpoint)
     if frigate_config.auth.failed_login_rate_limit is None:
         limiter.enabled = False
@@ -143,6 +141,7 @@ def create_fastapi_app(
 
     # Routes
     # Order of include_router matters: https://fastapi.tiangolo.com/tutorial/path-params/#order-matters
+    app.include_router(analytics.router)
     app.include_router(auth.router)
     app.include_router(camera.router)
     app.include_router(chat.router)

frigate/api/media.py

@@ -14,10 +14,10 @@ from enum import Enum
 from pathlib import Path as FilePath
 from typing import IO, Any
 from urllib.parse import unquote
-from zoneinfo import ZoneInfo
 
 import cv2
 import numpy as np
+import pytz
 from fastapi import APIRouter, Depends, Path, Query, Request, Response
 from fastapi.responses import FileResponse, JSONResponse, StreamingResponse
 from pathvalidate import sanitize_filename
@@ -62,10 +62,9 @@ from frigate.util.recording_coverage import (
     build_spans,
     null_audio_glitches,
     plan_clip,
-    recording_overlap,
     resolve_coverage,
+    stream_has_audio,
 )
-from frigate.util.time import get_normalized_tz_name
 
 logger = logging.getLogger(__name__)
 
@@ -297,15 +296,10 @@ async def latest_frame(
         and request.app.frigate_config.birdseye.enabled
         and request.app.frigate_config.birdseye.restream
     ):
-        frame = frame_processor.get_current_frame(camera_name)
-
-        if frame is None:
-            return JSONResponse(
-                content={"success": False, "message": "Unable to get valid frame"},
-                status_code=500,
-            )
-
-        frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
+        frame = cv2.cvtColor(
+            frame_processor.get_current_frame(camera_name),
+            cv2.COLOR_YUV2BGR_I420,
+        )
 
         height = int(params.height or str(frame.shape[0]))
         width = int(height * frame.shape[1] / frame.shape[0])
@@ -353,7 +347,10 @@ async def get_snapshot_from_recording(
                 Recordings.path,
                 Recordings.start_time,
             )
-            .where(recording_overlap(frame_time, frame_time))
+            .where(
+                (frame_time >= Recordings.start_time)
+                & (frame_time <= Recordings.end_time)
+            )
             .where(Recordings.camera == camera_name)
             .order_by(Recordings.stream_type.asc(), Recordings.start_time.desc())
             .limit(1)
@@ -369,7 +366,10 @@ async def get_snapshot_from_recording(
                     Recordings.path,
                     Recordings.start_time,
                 )
-                .where(recording_overlap(frame_time, frame_time))
+                .where(
+                    (frame_time >= Recordings.start_time)
+                    & (frame_time <= Recordings.end_time)
+                )
                 .where(Recordings.camera == camera_name)
                 .order_by(Recordings.stream_type.asc(), Recordings.start_time.desc())
                 .limit(1)
@@ -384,13 +384,8 @@ async def get_snapshot_from_recording(
         mime_type = "png" if format == "png" else "jpeg"
         config: FrigateConfig = request.app.frigate_config
 
-        image_data = await asyncio.to_thread(
-            get_image_from_recording,
-            config.ffmpeg,
-            recording.path,
-            time_in_segment,
-            codec,
-            height,
+        image_data = get_image_from_recording(
+            config.ffmpeg, recording.path, time_in_segment, codec, height
         )
 
         if not image_data:
@@ -432,7 +427,9 @@ async def submit_recording_snapshot_to_plus(
             Recordings.path,
             Recordings.start_time,
         )
-        .where(recording_overlap(frame_time, frame_time))
+        .where(
+            (frame_time >= Recordings.start_time) & (frame_time <= Recordings.end_time)
+        )
         .where(Recordings.camera == camera_name)
         .order_by(Recordings.stream_type.asc(), Recordings.start_time.desc())
         .limit(1)
@@ -442,12 +439,8 @@ async def submit_recording_snapshot_to_plus(
         config: FrigateConfig = request.app.frigate_config
         recording: Recordings = recording_query.get()
         time_in_segment = frame_time - recording.start_time
-        image_data = await asyncio.to_thread(
-            get_image_from_recording,
-            config.ffmpeg,
-            recording.path,
-            time_in_segment,
-            "png",
+        image_data = get_image_from_recording(
+            config.ffmpeg, recording.path, time_in_segment, "png"
         )
 
         if not image_data:
@@ -546,7 +539,11 @@ async def recording_clip(
                 Recordings.start_time,
                 Recordings.end_time,
             )
-            .where(recording_overlap(start_ts, end_ts))
+            .where(
+                (Recordings.start_time.between(start_ts, end_ts))
+                | (Recordings.end_time.between(start_ts, end_ts))
+                | ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
+            )
             .where(Recordings.camera == camera_name)
             .where(Recordings.stream_type == stream_type)
             .order_by(Recordings.start_time.asc())
@@ -684,10 +681,15 @@ async def _vod_response(
         end_ts,
         force_discontinuity,
     )
+    intervals = resolve_coverage(camera_name, start_ts, end_ts)
+
     # rows contradicting their stream's audio composition are
     # truncated-shutdown glitches
+    main_audio = stream_has_audio(intervals, main=True)
+    sub_audio = stream_has_audio(intervals, main=False)
+
     spans = build_spans(
-        null_audio_glitches(resolve_coverage(camera_name, start_ts, end_ts)),
+        null_audio_glitches(intervals, main_audio, sub_audio),
         stream_preference,
     )
 
@@ -841,9 +843,7 @@ async def vod_hour(
     parts = year_month.split("-")
     start_date = (
         datetime(int(parts[0]), int(parts[1]), day, hour, tzinfo=UTC)
-        - datetime.now(
-            ZoneInfo(get_normalized_tz_name(tz_name.replace(",", "/")))
-        ).utcoffset()
+        - datetime.now(pytz.timezone(tz_name.replace(",", "/"))).utcoffset()
     )
     end_date = start_date + timedelta(hours=1) - timedelta(milliseconds=1)
     start_ts = start_date.timestamp()

frigate/api/media_auth.py

@@ -13,9 +13,8 @@ from __future__ import annotations
 
 import logging
 import os
-import re
 from enum import Enum
-from urllib.parse import unquote
+from urllib.parse import unquote, urlparse
 
 from peewee import DoesNotExist
 
@@ -25,8 +24,6 @@ from frigate.models import Export, User
 
 logger = logging.getLogger(__name__)
 
-_URI_SCHEME_AND_AUTHORITY = re.compile(r"^[A-Za-z][A-Za-z0-9+.-]*://[^/?]*")
-
 
 class MediaAuthResolution(str, Enum):
     """Classification of an `X-Original-URL` path for media-auth purposes."""
@@ -44,36 +41,6 @@ class MediaAuthResolution(str, Enum):
     UNKNOWN = "unknown"
 
 
-def split_request_uri(request_uri: str) -> tuple[str, str]:
-    """Split a raw request URI into its path and query string.
-
-    urlparse is not used since it reads a path starting with `//` as a host.
-    nginx ends the URI at a literal `#`, so anything after it is dropped.
-    """
-    uri = _URI_SCHEME_AND_AUTHORITY.sub("", request_uri, count=1)
-    path, _, query = uri.partition("#")[0].partition("?")
-    return path, query
-
-
-def normalize_request_path(path: str) -> str:
-    """Normalize a raw request path the way nginx does before matching locations.
-
-    nginx percent-decodes the path, merges repeated slashes and resolves dot
-    segments, while `X-Original-URL` carries the raw `$request_uri`.
-    """
-    segments: list[str] = []
-    for segment in unquote(path).split("/"):
-        if segment in ("", "."):
-            continue
-        if segment == "..":
-            if segments:
-                segments.pop()
-            continue
-        segments.append(segment)
-
-    return "/" + "/".join(segments)
-
-
 def extract_path(original_url: str | None) -> str | None:
     """Return the decoded path component of nginx's `X-Original-URL` header.
 
@@ -82,14 +49,14 @@ def extract_path(original_url: str | None) -> str | None:
     request like `/recordings/.../allowed_cam/../forbidden_cam/file.mp4`
     would (1) parse as the allowed camera in our auth check, (2) be served
     as the forbidden camera by nginx. To close the bypass we reject any URI
-    whose path contains `.` or `..` segments outright. Repeated slashes are
-    merged, as nginx does before matching locations.
+    whose path contains `.` or `..` segments outright.
     """
     if not original_url:
         return None
 
-    path, _ = split_request_uri(original_url)
-    decoded = re.sub(r"/{2,}", "/", unquote(path))
+    parsed = urlparse(original_url)
+    raw_path = parsed.path or original_url
+    decoded = unquote(raw_path)
     if not decoded:
         return None
 
@@ -285,11 +252,12 @@ def deny_response_for_media_uri(
     path = extract_path(original_url)
 
     # `extract_path` returns None for URIs containing `.` or `..` segments.
-    # Deny them when nginx would resolve them under a media root, and pass
-    # the rest through to nginx and the backend.
+    # For media-root URIs that's a traversal attempt — deny outright. For
+    # non-media URIs, pass through (nginx / the backend handle them).
     if path is None:
-        normalized = normalize_request_path(split_request_uri(original_url)[0])
-        first = normalized.lstrip("/").split("/", 1)[0]
+        raw = urlparse(original_url).path or original_url
+        decoded = unquote(raw)
+        first = decoded.lstrip("/").split("/", 1)[0] if decoded else ""
         if first in ("clips", "recordings", "exports"):
             return 403
         return None

frigate/api/notices.py

@@ -14,18 +14,17 @@ router = APIRouter(tags=[Tags.notices])
 
 
 @router.get("/notices", dependencies=[Depends(require_role(["admin"]))])
-def get_notices(request: Request, include_hidden: bool = False) -> JSONResponse:
+def get_notices(request: Request, include_dismissed: bool = False) -> JSONResponse:
     """Get notices, most severe first.
 
     Args:
-        include_hidden: Also return acknowledged and muted notices, for the
-            hidden list
+        include_dismissed: Also return dismissed notices, for the history view
 
     Returns:
         The notices
     """
     return JSONResponse(
-        content=request.app.notice_registry.active(include_hidden=include_hidden)
+        content=request.app.notice_registry.active(include_dismissed=include_dismissed)
     )
 
 
@@ -35,64 +34,37 @@ def get_notice_stats(request: Request) -> JSONResponse:
     return JSONResponse(content=request.app.notice_registry.stats())
 
 
-@router.get("/notices/muted_checks", dependencies=[Depends(require_role(["admin"]))])
-def get_muted_checks(request: Request) -> JSONResponse:
-    """Get the muted config and stream check rows, newest first."""
-    return JSONResponse(content=request.app.notice_registry.muted_checks())
+@router.get(
+    "/notices/dismissed_checks", dependencies=[Depends(require_role(["admin"]))]
+)
+def get_dismissed_checks(request: Request) -> JSONResponse:
+    """Get the dismissed config and stream check rows, newest first."""
+    return JSONResponse(content=request.app.notice_registry.dismissed_checks())
 
 
-@router.delete("/notices/hidden", dependencies=[Depends(require_role(["admin"]))])
-def unhide_all_notices(request: Request) -> JSONResponse:
-    """Show every acknowledged and muted notice and check row again."""
-    request.app.notice_registry.unhide_all()
-    return JSONResponse(content={"success": True, "message": "Notices shown again"})
+@router.delete("/notices/dismissed", dependencies=[Depends(require_role(["admin"]))])
+def purge_dismissed(request: Request) -> JSONResponse:
+    """Delete every dismissed notice and check row so each can show again."""
+    request.app.notice_registry.purge_dismissed()
+    return JSONResponse(
+        content={"success": True, "message": "Dismissed notices cleared"}
+    )
 
 
 # model notice ids contain a slash, so the id is a path parameter
 @router.post(
-    "/notices/{notice_id:path}/acknowledge",
+    "/notices/{notice_id:path}/dismiss",
     dependencies=[Depends(require_role(["admin"]))],
 )
-def acknowledge_notice(request: Request, notice_id: str) -> JSONResponse:
-    """Hide a notice until it happens again.
+def dismiss_notice(request: Request, notice_id: str) -> JSONResponse:
+    """Hide a notice or a config or stream check row.
 
-    Config and stream check rows and the update notice never repeat, so they
-    can only be muted.
+    It stays hidden if the same problem happens again.
     """
-    if not request.app.notice_registry.acknowledge(notice_id):
+    if not request.app.notice_registry.dismiss(notice_id):
         return JSONResponse(
             content={"success": False, "message": "Notice not found"},
             status_code=404,
         )
 
-    return JSONResponse(content={"success": True, "message": "Notice acknowledged"})
-
-
-@router.post(
-    "/notices/{notice_id:path}/mute",
-    dependencies=[Depends(require_role(["admin"]))],
-)
-def mute_notice(request: Request, notice_id: str) -> JSONResponse:
-    """Hide a notice or a config or stream check row for good."""
-    if not request.app.notice_registry.mute(notice_id):
-        return JSONResponse(
-            content={"success": False, "message": "Notice not found"},
-            status_code=404,
-        )
-
-    return JSONResponse(content={"success": True, "message": "Notice muted"})
-
-
-@router.delete(
-    "/notices/{notice_id:path}/hidden",
-    dependencies=[Depends(require_role(["admin"]))],
-)
-def unhide_notice(request: Request, notice_id: str) -> JSONResponse:
-    """Show an acknowledged or muted notice or check row again."""
-    if not request.app.notice_registry.unhide(notice_id):
-        return JSONResponse(
-            content={"success": False, "message": "Notice not found"},
-            status_code=404,
-        )
-
-    return JSONResponse(content={"success": True, "message": "Notice shown again"})
+    return JSONResponse(content={"success": True, "message": "Notice dismissed"})

frigate/api/notification.py

@@ -9,6 +9,7 @@ from urllib.parse import urlparse
 from cryptography.hazmat.primitives import serialization
 from fastapi import APIRouter, Depends, Request
 from fastapi.responses import JSONResponse
+from peewee import DoesNotExist
 from py_vapid import Vapid01, utils
 
 from frigate.api.auth import allow_any_authenticated
@@ -172,22 +173,16 @@ def register_notifications(request: Request, body: dict = None):
             status_code=400,
         )
 
-    updated = (
-        User.update(notification_tokens=User.notification_tokens.append(sub))
-        .where(User.username == username)
-        .execute()
-    )
-
-    if not updated:
-        logger.warning(
-            "Rejected notification registration for unknown user %s", username
+    try:
+        User.update(notification_tokens=User.notification_tokens.append(sub)).where(
+            User.username == username
+        ).execute()
+        return JSONResponse(
+            content=({"success": True, "message": "Successfully saved token."}),
+            status_code=200,
         )
+    except DoesNotExist:
         return JSONResponse(
             content=({"success": False, "message": "Could not find user."}),
             status_code=404,
         )
-
-    return JSONResponse(
-        content=({"success": True, "message": "Successfully saved token."}),
-        status_code=200,
-    )