Improve report context management

Cleanup and fixes
Integrate state changes with review items
2026-09-29 19:36:57 +03:00 · 2026-09-29 10:18:47 -06:00 · 2026-09-29 10:13:04 -06:00 · 2026-09-29 09:47:36 -06:00 · 2026-09-29 08:53:42 -05:00 · 2026-09-29 08:53:42 -05:00
371 changed files with 21813 additions and 3644 deletions
@@ -5,3 +5,4 @@
 /docker/rockchip/ @MarcA711
 /docker/rocm/ @harakas
 /docker/hailo8l/ @spanner3003
+/docker/deepx/ @sixfab
@@ -0,0 +1,131 @@
+#!/bin/bash
+
+# Installs the DEEPX NPU kernel driver and the DX-RT runtime on the Docker host,
+# then enables the vendor's dxrt.service. A container cannot load kernel
+# modules, so this runs outside the image; the driver creates the /dev/dxrt*
+# nodes and the daemon multiplexes the NPU across host and container.
+#
+# Driver, runtime and firmware versions must agree or inference hangs instead
+# of failing at startup. The set this script installs is pinned in
+# driver_version, runtime_version and firmware_version below; move them
+# together, never one at a time.
+#
+# DEEPX NPU support in Frigate is maintained by Sixfab (https://sixfab.com).
+
+set -euo pipefail
+
+driver_version="v2.6.0"
+# the commit the tag resolves to, since DEEPX signs neither tags nor releases
+# and this is compiled and installed as root. Update both together
+driver_commit="7074748e7104f470b02f517583abba652b3f05fa"
+firmware_version="v2.7.4"
+
+sudo apt-get update
+sudo apt-get install -y git build-essential "linux-headers-$(uname -r)" pciutils wget
+
+if ! lspci -d 1ff4: | grep -q .; then
+    echo "No DEEPX device found on the PCIe bus (lspci -d 1ff4:)."
+    echo "Check that the module is seated correctly before continuing."
+    exit 1
+fi
+
+# fetch the pinned commit rather than cloning the tag, so a retag cannot swap
+# in different source. The build directory is reused so a second run after a
+# failure does not stop on the directory already being there
+mkdir -p dx_rt_npu_linux_driver
+cd dx_rt_npu_linux_driver
+git init -q
+git remote get-url origin > /dev/null 2>&1 ||
+    git remote add origin https://github.com/DEEPX-AI/dx_rt_npu_linux_driver.git
+git fetch --depth 1 origin "${driver_commit}"
+git checkout -q FETCH_HEAD
+
+fetched_commit=$(git rev-parse HEAD)
+if [[ "${fetched_commit}" != "${driver_commit}" ]]; then
+    echo "Fetched commit ${fetched_commit} does not match pinned driver_commit ${driver_commit}."
+    echo "Refusing to build unverified driver source."
+    exit 1
+fi
+
+cd modules
+
+sudo ./build.sh -c install --reload
+
+sudo depmod -A
+
+# dx_dma is the PCIe transport, dxrt_driver the NPU driver on top of it
+for module in dx_dma dxrt_driver; do
+    if ! sudo modprobe "${module}"; then
+        echo "Unable to load the ${module} kernel module, common reasons are:"
+        echo "- Secure Boot is enabled and is rejecting the unsigned module."
+        echo "- The running kernel does not match the installed linux-headers."
+        exit 1
+    fi
+done
+
+if ! compgen -G "/dev/dxrt*" > /dev/null; then
+    echo "Modules loaded but no /dev/dxrt* device node appeared."
+    echo "Run ./sanity_check.sh from the driver repo to diagnose."
+    exit 1
+fi
+
+runtime_version="v3.4.0"
+declare -A runtime_sha256=(
+    [amd64]="736cfef009ce9e974ab1ab610d867239d19d72a426a53e367ddcbd53297b6e20"
+    [arm64]="eb6107f5f02f2ad76ae89f414e8b5f346f34fbc6f0888236136853a26be6f6a0"
+)
+
+runtime_release="${runtime_version#v}"
+deb_arch=$(dpkg --print-architecture)
+deb_file="/tmp/libdxrt-bin_${runtime_release}_${deb_arch}.deb"
+
+wget -qO "${deb_file}" \
+    "https://raw.githubusercontent.com/DEEPX-AI/dx_rt/${runtime_version}/release/${runtime_release}/libdxrt-bin_${runtime_release}_${deb_arch}.deb"
+
+expected_sha256="${runtime_sha256[${deb_arch}]:-}"
+if [[ -z "${expected_sha256}" ]]; then
+    echo "No pinned SHA-256 for architecture ${deb_arch}; refusing to install."
+    exit 1
+fi
+if [[ "$(sha256sum "${deb_file}" | cut -d' ' -f1)" != "${expected_sha256}" ]]; then
+    echo "SHA-256 mismatch for ${deb_file}; refusing to install."
+    exit 1
+fi
+
+sudo dpkg -i "${deb_file}"
+sudo ldconfig
+rm -f "${deb_file}"
+
+sudo cp /usr/share/libdxrt-bin/service/dxrt.service /etc/systemd/system/
+
+# With an endpoint set, dxrtd binds that path only, so the socket goes in a
+# directory Frigate can mount (kept across restarts so the mount stays valid)
+# and a symlink at the default /tmp path keeps host tools that do not set the
+# variable working through their own fallback.
+sudo mkdir -p /etc/systemd/system/dxrt.service.d
+sudo tee /etc/systemd/system/dxrt.service.d/frigate.conf > /dev/null <<'UNIT'
+[Service]
+RuntimeDirectory=dxrt
+RuntimeDirectoryMode=0755
+RuntimeDirectoryPreserve=yes
+Environment=DXRT_DYNAMIC_IPC_ENDPOINT=/run/dxrt/dxrt_dynamic_ipc.sock
+ExecStartPost=/bin/ln -sfn /run/dxrt/dxrt_dynamic_ipc.sock /tmp/dxrt_dynamic_ipc.sock
+UNIT
+
+sudo systemctl daemon-reload
+sudo systemctl enable dxrt.service
+sudo systemctl restart dxrt.service
+
+if ! sudo systemctl is-active --quiet dxrt.service; then
+    echo "dxrt.service did not start. Check: sudo journalctl -u dxrt.service"
+    exit 1
+fi
+
+echo "DEEPX driver and runtime installation complete."
+echo "Driver version:   $(modinfo -F version dxrt_driver) (expected ${driver_version#v})"
+echo "Runtime version:  ${runtime_release}"
+echo "Device node(s):   $(echo /dev/dxrt*)"
+echo
+echo "This driver expects NPU firmware ${firmware_version}. Check it with:"
+echo "  dxrt-cli --status"
+echo "Update the module if it does not match before starting Frigate."
@@ -27,7 +27,7 @@ pydantic == 2.10.*
 git+https://github.com/fbcotter/py3nvml#egg=py3nvml
 pytz == 2025.*
 pyzmq == 27.1.*
-ruamel.yaml == 0.18.*
+ruamel.yaml == 0.19.*
 tzlocal == 5.2
 requests == 2.33.*
 types-requests == 2.32.*
@@ -43,7 +43,7 @@ opencv-contrib-python == 4.11.0.*
 scipy == 1.16.*
 # OpenVino & ONNX
 openvino == 2025.4.*
-onnxruntime == 1.22.*
+onnxruntime == 1.30.*
 # Embeddings
 transformers == 4.45.*
 # Generative AI
@@ -58,7 +58,7 @@ pyclipper == 1.4.*
 shapely == 2.0.*
 rapidfuzz==3.12.*
 # HailoRT
-argcomplete==2.0.*
+argcomplete==3.7.*
 contextlib2==0.6.*
 future==0.18.*
 netaddr==1.3.*
@@ -37,6 +37,7 @@ device_globs=(
    "/dev/nvmap"
    "/dev/nvidia*"
    "/dev/memx*"
+    "/dev/dxrt*"
 )

 IFS=',' read -ra extra_globs <<< "${DEVICE_ACL_PATHS:-}"
@@ -967,6 +967,65 @@ memryx:
            # The .zip file must contain:
            # ├── ssdlite_mobilenet.dfp          (a file ending with .dfp)
            # └── ssdlite_mobilenet_post.onnx    (optional; only if the model includes a cropped post-processing network)
+deepx:
+  title: DEEPX NPU
+  models:
+    - key: yolo
+      label: YOLO
+      recommended: true
+      download: No model is bundled with Frigate. Download a pre-compiled YOLO `.dxnn` model from the [DEEPX ModelZoo](https://developer.deepx.ai/modelzoo) or compile your own with DX-COM, then bind-mount it into the container and point the model's `path` at it. The recommended model is `yolox-s_640x640_ppu.dxnn`. Its Post-Processing Unit (PPU) compile moves candidate selection onto the NPU, which makes it the fastest ModelZoo model measured through Frigate (about 13 ms on a DX-M1). The output layout is read from the compiled model, so anchor-based, anchor-free, NMS-in-head and PPU models (anchor-based or anchor-free) all need no extra configuration; prefer a `PPU` variant whenever the ModelZoo offers one. PPU models must be compiled with DX-COM 2.4.0 or later, which writes the head layout Frigate reads into the file.
+      ui: |-
+        Navigate to **Settings > System > Detection models** and select **DEEPX NPU** from the **Hardware** dropdown. Then, on the same model, open the **Custom Model** tab and configure:
+
+        | Field                                    | Value                                                |
+        | ---------------------------------------- | ---------------------------------------------------- |
+        | **Custom object detector model path**    | `/config/model_cache/deepx/yolox-s_640x640_ppu.dxnn` |
+        | **Label map for custom object detector** | `/labelmap/coco-80.txt`                              |
+        | **Object detection model input width**   | `640`                                                |
+        | **Object detection model input height**  | `640`                                                |
+        | **Model Input Pixel Color Format**       | `rgb` (Frigate's default value)                      |
+        | **Model Input Tensor Shape**             | `nhwc` (Frigate's default value)                     |
+        | **Model Input D Type**                   | `int` (Frigate's default value)                      |
+        | **Object Detection Model Type**          | `yolo-generic`                                       |
+
+        Quantization is baked into the compiled model, so no normalization is applied on the host and the input defaults do not need to be overridden.
+      yaml: |-
+        models:
+          - devices:
+              - deepx:PCIe:0
+            path: /config/model_cache/deepx/yolox-s_640x640_ppu.dxnn
+            labelmap_path: /labelmap/coco-80.txt
+            model_type: yolo-generic
+            width: 640
+            height: 640
+    - key: yolox
+      label: YOLOX
+      recommended: false
+      download: No model is bundled with Frigate. Download a pre-compiled YOLOX `.dxnn` model from the [DEEPX ModelZoo](https://developer.deepx.ai/modelzoo), then bind-mount it into the container and point the model's `path` at it. The `_ppu` variant is faster and also works with the `yolo-generic` model type; the plain export needs `yolox` so its raw head is decoded.
+      ui: |-
+        Navigate to **Settings > System > Detection models** and select **DEEPX NPU** from the **Hardware** dropdown. Then, on the same model, open the **Custom Model** tab and configure:
+
+        | Field                                    | Value                                    |
+        | ---------------------------------------- | ---------------------------------------- |
+        | **Custom object detector model path**    | `/config/model_cache/deepx/yolox-s_640x640.dxnn`|
+        | **Label map for custom object detector** | `/labelmap/coco-80.txt`                  |
+        | **Object detection model input width**   | `640`                                    |
+        | **Object detection model input height**  | `640`                                    |
+        | **Model Input Pixel Color Format**       | `rgb` (Frigate's default value)          |
+        | **Model Input Tensor Shape**             | `nhwc` (Frigate's default value)         |
+        | **Model Input D Type**                   | `int` (Frigate's default value)          |
+        | **Object Detection Model Type**          | `yolox`                                  |
+
+        The width and height must match the resolution the `.dxnn` file was compiled for.
+      yaml: |-
+        models:
+          - devices:
+              - deepx:PCIe:0
+            path: /config/model_cache/deepx/yolox-s_640x640.dxnn
+            labelmap_path: /labelmap/coco-80.txt
+            model_type: yolox
+            width: 640
+            height: 640
 tensorrt:
  title: TensorRT
  models:
@@ -85,6 +85,14 @@ 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:
@@ -17,17 +17,19 @@ 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-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-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   |

 <ConfigTabs>
 <TabItem value="ui">
@@ -201,6 +201,8 @@ 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
@@ -43,6 +43,10 @@ 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
@@ -533,3 +537,35 @@ 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).
@@ -24,6 +24,7 @@ Frigate supports multiple different detectors that work on different types of ha
 - [Coral EdgeTPU](#edge-tpu-detector): The Google Coral EdgeTPU is available in USB, Mini PCIe, and m.2 formats allowing for a wide range of compatibility with devices.
 - [Hailo](#hailo): The Hailo-8, Hailo-8L and Hailo-8R AI Acceleration modules are available in m.2 format with a HAT for RPi devices, offering a wide range of compatibility with devices.
 - <CommunityBadge /> [MemryX](#memryx-mx3): The MX3 Acceleration module is available in m.2 format, offering broad compatibility across various platforms.
+- <CommunityBadge /> [DEEPX](#deepx-npu): The DEEPX NPU is available in m.2 format and as a HAT+ for the Raspberry Pi 5, offering broad compatibility across various platforms.

 **AMD**

@@ -33,6 +34,7 @@ Frigate supports multiple different detectors that work on different types of ha
 **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**

@@ -483,7 +485,7 @@ 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, and TensorRT. 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, TensorRT, and a Mac's Neural Engine. On startup Frigate will automatically try to use a GPU if one is available.

 :::info

@@ -499,6 +501,9 @@ 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
@@ -514,6 +519,22 @@ 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} />
@@ -612,6 +633,63 @@ For detailed instructions on compiling models, refer to the [MemryX Compiler](ht

 ---

+## DEEPX NPU
+
+This detector is available for use with the DEEPX NPU, both the DX-M1 M.2 module and the DX-M1M on the Sixfab AI HAT+ for the Raspberry Pi 5. The configuration below applies unchanged to either form factor. DEEPX NPU support in Frigate is developed and maintained by [Sixfab](https://sixfab.com).
+
+See the [installation docs](../frigate/installation.md#deepx-npu) for information on installing the DEEPX kernel driver and runtime on the host and passing the NPU through to the container.
+
+To run a model on a DEEPX NPU, list a `deepx` device on that model.
+
+:::info
+
+The DX-RT Python bindings are not part of the Frigate image. They are downloaded and installed into `/config/.local` the first time a DEEPX device is configured, verified against pinned checksums, and updated automatically when a Frigate release pins a new version. If the container has no internet access, see [Detector runtimes](/frigate/network_requirements#detector-runtimes) for how to provide the files yourself.
+
+:::
+
+### Configuration {#configuration-deepx}
+
+<ModelConfigDropdown detectorTitle="DEEPX" models={objectDetectorsModels.deepx.models} />
+
+Frigate does not bundle a model for this detector. Models must be compiled to DEEPX's `.dxnn` format. Two model types are supported:
+
+- `yolo-generic` for YOLO object detection models, the recommended default. The detector reads the model's output layout from the compiled file, so anchor-based, anchor-free and NMS-in-head models all work with the same configuration, as do models compiled with DEEPX's Post-Processing Unit (PPU) support.
+- `yolox` for YOLOX models compiled without PPU support, whose raw head needs Frigate's YOLOX decoder. A YOLOX model compiled with PPU support works under either `yolox` or `yolo-generic`.
+
+The quickest way to get one is the [DEEPX ModelZoo](https://developer.deepx.ai/modelzoo), which publishes pre-compiled `.dxnn` files for a range of YOLO object detection models. Download the `.dxnn`, bind-mount it into the container, and point the model's `path` at it. Alternatively, compile your own model with the DX-COM compiler. The recommended starting point is `yolox-s_640x640_ppu.dxnn`, the fastest ModelZoo model measured through Frigate:
+
+```yaml
+models:
+  - devices:
+      - deepx:PCIe:0
+    path: /config/model_cache/deepx/yolox-s_640x640_ppu.dxnn
+    labelmap_path: /labelmap/coco-80.txt
+    model_type: yolo-generic
+    width: 640
+    height: 640
+```
+
+For PPU models, use a `.dxnn` compiled with DX-COM 2.4.0 or later. Frigate reads the PPU head layout the compiler writes into the file and refuses to load a PPU model without it.
+
+`model_type` must be set to `yolo-generic` or `yolox` to match the model; `yolo-generic` is the recommended default unless the model is a raw YOLOX export. Frigate defaults it to `ssd`, which this detector does not support, so the detector refuses to start on a model that leaves it unset.
+
+`width` and `height` must match the resolution the model was compiled for. Quantization parameters are baked into the `.dxnn` file at compile time, so no normalization is applied on the host and Frigate's default `input_tensor`, `input_pixel_format`, and `input_dtype` values do not need to be overridden.
+
+A DEEPX device is `PCIe:<index>`, as reported on the detector settings page. The NPU daemon multiplexes across processes, so the same device may be listed more than once to run additional inference processes against it:
+
+```yaml
+models:
+  - devices:
+      - deepx:PCIe:0
+      - deepx:PCIe:0
+```
+
+#### Label maps
+
+The object detection models in the DEEPX ModelZoo are trained on the standard 80-class COCO label set, so `labelmap_path` must be set to `/labelmap/coco-80.txt`. Frigate's default label map uses an extended 91-class COCO scheme, and leaving it in place will cause detections to be reported as the wrong object type. For `yolo-generic` models the label map is also what the detector uses to tell the output layout, so a label map with the wrong number of classes is reported as an error at startup.
+
+---
+
 ## NVidia TensorRT Detector

 Nvidia Jetson devices may be used for object detection using the TensorRT libraries. Due to the size of the additional libraries, this detector is only provided in images with the `-tensorrt-jp6` tag suffix, e.g. `ghcr.io/blakeblackshear/frigate:stable-tensorrt-jp6`. This detector is designed to work with Yolo models for object detection.
@@ -65,6 +65,11 @@ Frigate supports multiple different detectors that work on different types of ha
  - [Supports many model architectures](../../configuration/object_detectors#memryx-mx3)
  - Runs best with tiny, small, or medium-size models

+- <CommunityBadge /> [DEEPX](#deepx-npu): The DEEPX NPU is available in m.2 format and as a HAT+ for the Raspberry Pi 5, allowing for a wide range of compatibility with devices.
+  - [Supports YOLO model architectures](../../configuration/object_detectors#deepx-npu)
+  - Runs best with tiny or small size models
+  - Runs efficiently on low power hardware
+
 **AMD**

 - [ROCm](#rocm---amd-gpu): ROCm can run on AMD Discrete GPUs to provide efficient object detection
@@ -73,6 +78,10 @@ Frigate supports multiple different detectors that work on different types of ha

 **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
@@ -206,7 +215,13 @@ Inference is done with the `onnx` detector type. Speeds will vary greatly depend

 ### 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.
+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.

 :::warning

@@ -257,6 +272,32 @@ The MX3 is a pipelined architecture, where the maximum frames per second support

 Inference speeds may vary depending on the host platform. The above data was measured on an **Intel 13700 CPU**. Platforms like Raspberry Pi, Orange Pi, and other ARM-based SBCs have different levels of processing capability, which may limit total FPS.

+### DEEPX NPU
+
+Frigate supports the DEEPX NPU in both of its form factors: the **DX-M1** M.2 module, which works on x86 (Intel/AMD) and ARM-based SBCs such as the Raspberry Pi 5, and the **DX-M1M** on the [Sixfab AI HAT+](https://docs.sixfab.com/docs/ai-hat-plus-raspberry-pi-5-quickstart) for the Raspberry Pi 5. Both use the same driver and runtime, so the configuration is identical for either one. DEEPX NPU support in Frigate is developed and maintained by [Sixfab](https://sixfab.com).
+
+The DEEPX driver and runtime run on the Docker host rather than inside the Frigate container and must be installed before the NPU can be used. See the [installation docs](installation.md#deepx-npu) for the setup steps and [the detector docs](/configuration/object_detectors#deepx-npu) for the configuration.
+
+Frigate does not bundle a model for this detector. Models use DEEPX's `.dxnn` format, and pre-compiled YOLO models can be downloaded from the [DEEPX ModelZoo](https://developer.deepx.ai/modelzoo). Prefer a model with a `_ppu` suffix whenever one is available for the architecture you want: these run part of the post-processing on the NPU itself and are considerably faster, roughly 2.5x for the same architecture and input size. **YOLOX-S with PPU is the recommended starting point.**
+
+Inference times for a few recommended models, measured through Frigate's own stats on a DX-M1:
+
+| Model             | Input Size | DX-M1 Inference Time |
+| ----------------- | ---------- | -------------------- |
+| YOLOX-S (PPU)     | 640        | ~ 13 ms              |
+| YOLOv9-t (PPU)    | 640        | ~ 18 ms              |
+| YOLOv4 (PPU)      | 512        | ~ 20 ms              |
+| YOLOX-S           | 640        | ~ 34 ms              |
+| YOLOv9-s          | 640        | ~ 39 ms              |
+
+Other ModelZoo YOLO variants are also supported but have not been measured. Inference speeds vary with the host platform, so a slower host such as a Raspberry Pi 5 will report higher times than those above.
+
+:::note
+
+A few ModelZoo models can not be used with Frigate: SSD models (they are trained on Pascal VOC, so their labels do not match Frigate's), DAMO-YOLO models, face and pose models, and the PPU builds of YOLOv7.
+
+:::
+
 ### Nvidia Jetson

 Jetson devices are supported via the TensorRT or ONNX detectors when running Jetpack 6. It will [make use of the Jetson's hardware media engine](/configuration/hardware_acceleration_video#nvidia-jetson) when configured with the [appropriate presets](/configuration/ffmpeg_presets#hwaccel-presets), and will make use of the Jetson's GPU and DLA for object detection when configured with the [TensorRT detector](/configuration/object_detectors#nvidia-tensorrt-detector).
@@ -381,6 +381,99 @@ If you can't use Docker Compose, you can run the container with something simila

 Finally, configure [hardware object detection](/configuration/object_detectors#memryx-mx3) to complete the setup.

+### DEEPX NPU
+
+The DEEPX NPU is available in two form factors, and Frigate supports both:
+
+- **DX-M1** in the M.2 2280 form factor (like an NVMe SSD), for x86 (Intel/AMD) PCs, the Raspberry Pi 5, and other ARM SBCs with an exposed PCIe M.2 slot.
+- **DX-M1M** on the [Sixfab AI HAT+](https://docs.sixfab.com/docs/ai-hat-plus-raspberry-pi-5-quickstart), a HAT+ board that connects to the Raspberry Pi 5 over PCIe Gen 3 x1.
+
+Both present the NPU through the same PCIe driver and DX-RT runtime, so the setup below and the detector configuration are identical for either one. Nothing needs to change when moving between them.
+
+DEEPX NPU support in Frigate is developed and maintained by [Sixfab](https://sixfab.com).
+
+#### Versions
+
+A DEEPX install has several separately versioned pieces, and they all have to agree. The driver, the runtime, and the daemon live on the Docker host; Frigate itself carries only the Python bindings, which it downloads on first start:
+
+| Component      | Version  | Installed on | Installed by              |
+| -------------- | -------- | ------------ | ------------------------- |
+| Kernel driver  | `v2.6.0` | Host  | `user_installation.sh`    |
+| DX-RT runtime  | `v3.4.0` | Host  | `user_installation.sh`    |
+| NPU firmware   | `v2.7.4` | The module   | Flashed from the host     |
+| DX-RT bindings | `v3.4.0` | Frigate      | Downloaded at first start |
+
+:::warning
+
+A version mismatch does not produce a startup error. It typically shows up as inference requests that are accepted but never return a result, so detections simply stop appearing while Frigate looks healthy. If that happens after a Frigate upgrade, check every version in the table before anything else.
+
+:::
+
+The installation script installs the DX-RT runtime on the host and enables `dxrt.service`, so the daemon starts at boot and any other program on the host can share the NPU with Frigate. Check the firmware version with `dxrt-cli --status` and update the module if it does not match the table above.
+
+#### Installation
+
+The DEEPX kernel driver must be installed on the host rather than in the container, because containers share the host kernel and cannot load kernel modules. Installing it creates the `/dev/dxrt*` device nodes that are passed through to Frigate. The same script installs the DX-RT runtime and enables `dxrt.service`, the daemon that owns the NPU and hands work to it on behalf of Frigate and anything else on the host.
+
+1. Copy or download [this script](https://github.com/blakeblackshear/frigate/blob/dev/docker/deepx/user_installation.sh).
+2. Ensure it has execution permissions with `sudo chmod +x user_installation.sh`
+3. Run the script with `./user_installation.sh`
+4. **Restart your computer** to complete driver installation.
+
+Confirm the NPU is visible before continuing:
+
+```bash
+ls /dev/dxrt*
+```
+
+Then confirm the daemon is running and listening in `/run/dxrt`:
+
+```bash
+systemctl is-active dxrt.service
+ls /run/dxrt/
+```
+
+#### Setup
+
+To set up Frigate, follow the default installation instructions, for example: `ghcr.io/blakeblackshear/frigate:stable`
+
+#### Docker configuration
+
+Frigate needs the NPU device node and the directory holding the daemon's socket:
+
+```yaml
+services:
+  frigate:
+    devices:
+      - /dev/dxrt0:/dev/dxrt0
+    volumes:
+      - /run/dxrt:/run/dxrt
+```
+
+If you can't use Docker Compose, add `--device /dev/dxrt0:/dev/dxrt0 -v /run/dxrt:/run/dxrt` to your `docker run` command.
+
+Add one `--device` per NPU, contiguously from `/dev/dxrt0`, since the client stops enumerating at the first gap.
+
+The installation script configures `dxrt.service` to place its socket in `/run/dxrt` through a systemd drop-in. Mounting the directory rather than the socket file means the container sees the new socket after `dxrt.service` is restarted, rather than holding on to a deleted one.
+
+`dxrtd` listens on an abstract socket as well, but that one does not cross into a container, so Frigate names the filesystem socket through `DXRT_DYNAMIC_IPC_ENDPOINT` on your behalf. Set that variable on the container yourself only if the daemon listens somewhere else, which means you also set it for `dxrtd` through its own systemd drop-in. The script writes `/etc/systemd/system/dxrt.service.d/frigate.conf` for exactly that, and has `dxrt.service` link the socket to `/tmp/dxrt_dynamic_ipc.sock` when it starts, so the host's own `dxrt-cli` and `dxtop` keep finding it at the default path they fall back to.
+
+:::note
+
+The DX-RT client exits when `dxrt.service` stops, so restart the Frigate container after restarting `dxrt.service`.
+
+:::
+
+The device node is needed as well as the socket, because the client opens the NPU directly even though the daemon arbitrates access. Without it, inference fails with `Device not found`.
+
+`/dev/shm` does not need sharing.
+
+The DX-RT python bindings are not shipped in the Frigate image. Frigate downloads them on first start when a DEEPX detector is configured, and caches them under `/config`.
+
+#### Configuration
+
+Finally, configure [hardware object detection](/configuration/object_detectors#deepx-npu) to complete the setup.
+
 ### Rockchip platform

 Make sure that you use a linux distribution that comes with the rockchip BSP kernel 5.10 or 6.1 and necessary drivers (especially rkvdec2 and rknpu). To check, enter the following commands:
@@ -212,6 +212,7 @@ 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.

@@ -235,7 +236,8 @@ When the review activity has ended a final `end` message is published.
      "objects": ["person", "car"],
      "sub_labels": [],
      "zones": [],
-      "audio": []
+      "audio": [],
+      "classification_state_changes": []
    }
  },
  "after": {
@@ -254,7 +256,16 @@ When the review activity has ended a final `end` message is published.
      "objects": ["person", "car"],
      "sub_labels": ["Bob"],
      "zones": ["front_yard"],
-      "audio": []
+      "audio": [],
+      "classification_state_changes": [
+        // verified changes of state classification models on this camera
+        {
+          "model": "front_gate",
+          "from": "closed",
+          "to": "open",
+          "timestamp": 1718987131.52
+        }
+      ]
    }
  }
 }
@@ -184,6 +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, 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.
+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.

 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.
@@ -11375,15 +11375,15 @@
      }
    },
    "node_modules/image-size": {
-      "version": "2.0.2",
-      "resolved": "https://registry.npmjs.org/image-size/-/image-size-2.0.2.tgz",
-      "integrity": "sha512-IRqXKlaXwgSMAMtpNzZa1ZAe8m+Sa1770Dhk8VkSsP9LS+iHD62Zd8FQKs8fbPiagBE7BzoFX23cxFnwshpV6w==",
+      "version": "2.0.4",
+      "resolved": "https://registry.npmjs.org/image-size/-/image-size-2.0.4.tgz",
+      "integrity": "sha512-QRUkFFsRV/6fuESxb9Vkq+a0LkSrgKXuc2NEqfikiXxxN/G3tjWt5EVUlMaImRBZRZK/jRBEbYvpPYZL8t08Zw==",
      "license": "MIT",
      "bin": {
        "image-size": "bin/image-size.js"
      },
      "engines": {
-        "node": ">=16.x"
+        "node": ">=18"
      }
    },
    "node_modules/immer": {
@@ -4174,19 +4174,20 @@ paths:
        Get notices, most severe first.

        Args:
-            include_dismissed: Also return dismissed notices, for the history view
+            include_hidden: Also return acknowledged and muted notices, for the
+                hidden list

        Returns:
            The notices
      operationId: get_notices_notices_get
      parameters:
-        - name: include_dismissed
+        - name: include_hidden
          in: query
          required: false
          schema:
            type: boolean
            default: false
-            title: Include Dismissed
+            title: Include Hidden
      responses:
        '200':
          description: Successful Response
@@ -4221,16 +4222,16 @@ paths:
      security:
        - frigateAdminAuth: []
      x-required-role: admin
-  /notices/dismissed_checks:
+  /notices/muted_checks:
    get:
      tags:
        - Notices
-      summary: Get Dismissed Checks
+      summary: Get Muted Checks
      description: |-
        **Access:** Admin role required.

-        Get the dismissed config and stream check rows, newest first.
-      operationId: get_dismissed_checks_notices_dismissed_checks_get
+        Get the muted config and stream check rows, newest first.
+      operationId: get_muted_checks_notices_muted_checks_get
      responses:
        '200':
          description: Successful Response
@@ -4240,16 +4241,16 @@ paths:
      security:
        - frigateAdminAuth: []
      x-required-role: admin
-  /notices/dismissed:
+  /notices/hidden:
    delete:
      tags:
        - Notices
-      summary: Purge Dismissed
+      summary: Unhide All Notices
      description: |-
        **Access:** Admin role required.

-        Delete every dismissed notice and check row so each can show again.
-      operationId: purge_dismissed_notices_dismissed_delete
+        Show every acknowledged and muted notice and check row again.
+      operationId: unhide_all_notices_notices_hidden_delete
      responses:
        '200':
          description: Successful Response
@@ -4259,18 +4260,83 @@ paths:
      security:
        - frigateAdminAuth: []
      x-required-role: admin
-  /notices/{notice_id}/dismiss:
+  /notices/{notice_id}/acknowledge:
    post:
      tags:
        - Notices
-      summary: Dismiss Notice
+      summary: Acknowledge Notice
      description: |-
        **Access:** Admin role required.

-        Hide a notice or a config or stream check row.
+        Hide a notice until it happens again.

-        It stays hidden if the same problem happens again.
-      operationId: dismiss_notice_notices__notice_id__dismiss_post
+        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
      parameters:
        - name: notice_id
          in: path
@@ -99,6 +99,10 @@ def main() -> None:
        print("***    End Config Validation Errors                       ***")
        print("*************************************************************")

+        # force a non-zero exit code for config failures
+        if args.validate_config:
+            sys.exit(1)
+
        # attempt to start Frigate in recovery mode
        try:
            config = FrigateConfig.load(install=True, safe_load=True)
@@ -393,6 +393,11 @@ 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

@@ -429,6 +434,8 @@ 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",
@@ -51,6 +51,7 @@ 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
@@ -63,7 +63,6 @@ from frigate.util.recording_coverage import (
    null_audio_glitches,
    plan_clip,
    resolve_coverage,
-    stream_has_audio,
 )

 logger = logging.getLogger(__name__)
@@ -681,15 +680,10 @@ 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(intervals, main_audio, sub_audio),
+        null_audio_glitches(resolve_coverage(camera_name, start_ts, end_ts)),
        stream_preference,
    )

@@ -14,17 +14,18 @@ router = APIRouter(tags=[Tags.notices])


@router.get("/notices", dependencies=[Depends(require_role(["admin"]))])
-def get_notices(request: Request, include_dismissed: bool = False) -> JSONResponse:
+def get_notices(request: Request, include_hidden: bool = False) -> JSONResponse:
    """Get notices, most severe first.

    Args:
-        include_dismissed: Also return dismissed notices, for the history view
+        include_hidden: Also return acknowledged and muted notices, for the
+            hidden list

    Returns:
        The notices
    """
    return JSONResponse(
-        content=request.app.notice_registry.active(include_dismissed=include_dismissed)
+        content=request.app.notice_registry.active(include_hidden=include_hidden)
    )


@@ -34,37 +35,64 @@ def get_notice_stats(request: Request) -> JSONResponse:
    return JSONResponse(content=request.app.notice_registry.stats())


-@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.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.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"}
-    )
+@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"})


 # model notice ids contain a slash, so the id is a path parameter
@router.post(
-    "/notices/{notice_id:path}/dismiss",
+    "/notices/{notice_id:path}/acknowledge",
    dependencies=[Depends(require_role(["admin"]))],
 )
-def dismiss_notice(request: Request, notice_id: str) -> JSONResponse:
-    """Hide a notice or a config or stream check row.
+def acknowledge_notice(request: Request, notice_id: str) -> JSONResponse:
+    """Hide a notice until it happens again.

-    It stays hidden if the same problem happens again.
+    Config and stream check rows and the update notice never repeat, so they
+    can only be muted.
    """
-    if not request.app.notice_registry.dismiss(notice_id):
+    if not request.app.notice_registry.acknowledge(notice_id):
        return JSONResponse(
            content={"success": False, "message": "Notice not found"},
            status_code=404,
        )

-    return JSONResponse(content={"success": True, "message": "Notice dismissed"})
+    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"})
@@ -483,7 +483,7 @@ class FrigateApp:

    def start_audio_processor(self) -> None:
        self.audio_process = AudioProcessor(
-            self.config, self.camera_metrics, self.stop_event
+            self.config, self.camera_metrics, self.embeddings_metrics, self.stop_event
        )
        self.audio_process.start()
        self.processes["audio_detector"] = self.audio_process.pid or 0
@@ -556,10 +556,20 @@ class FrigateApp:
                "output",
                lambda: OutputProcess(self.config, self.stop_event),
            ),
+            (
+                "audio_process",
+                "audio_detector",
+                lambda: AudioProcessor(
+                    self.config,
+                    self.camera_metrics,
+                    self.embeddings_metrics,
+                    self.stop_event,
+                ),
+            ),
        ]

        for attr, key, factory in specs:
-            if not hasattr(self, attr):
+            if getattr(self, attr, None) is None:
                continue

            def on_restart(
@@ -12,6 +12,7 @@ class DetectionTypeEnum(str, Enum):
    video = "video"
    audio = "audio"
    lpr = "lpr"
+    classification_state = "classification_state"


 class DetectionPublisher(Publisher):
@@ -1,10 +1,10 @@
 """Frame annotations derived from object tracking data.

 Builds short notes describing what changed during a review item, keyed to the
-frames sampled from it. Everything here comes from tracked object data already
-in the database (each event's `path_data` trajectory and the timeline's
-stationary/active changes), so the notes can be stated to the model as fact
-rather than as something it must perceive.
+frames sampled from it. Everything here comes from data already recorded
+(each event's `path_data` trajectory, the timeline's stationary/active
+changes, and the review item's state classification changes), so the notes
+can be stated to the model as fact rather than as something it must perceive.
 """

 import logging
@@ -95,6 +95,15 @@ def event_name(event: dict[str, Any]) -> str:
    return f"{article} {label}"


+def describe_classification_change(change: dict[str, Any]) -> str:
+    """Phrase a state classification change, e.g. 'front gate changed from
+    closed to open'."""
+    model = str(change["model"]).replace("_", " ")
+    before = str(change["from"]).replace("_", " ")
+    after = str(change["to"]).replace("_", " ")
+    return f"{model} changed from {before} to {after}"
+
+
 def path_legs(points: list[Point]) -> list[Leg]:
    """Split a trajectory into runs of travel in a consistent direction.

@@ -359,25 +368,38 @@ def get_state_changes(detection_ids: list[str]) -> list[dict[str, Any]]:
 def build_frame_captions(
    detection_ids: list[str],
    frame_times: list[float],
+    classification_changes: Sequence[dict[str, Any]] = (),
 ) -> list[str]:
    """A caption for each sampled frame, in frame order.

    Every frame gets its index and elapsed time so the model can tell them
-    apart; frames where something changed also carry the tracker notes for
-    that moment. Returns an empty list when there is nothing to say, which
-    callers treat as a reason to fall back to sending plain frames.
+    apart; frames where something changed also carry the tracker and state
+    classification notes for that moment. Returns an empty list when there is
+    nothing to say, which callers treat as a reason to fall back to sending
+    plain frames.
    """
    if not frame_times:
        return []

+    span_end = frame_times[-1]
+    timeline: list[tuple[float, str]] = []
    events = get_tracked_events(detection_ids)

-    if not events:
-        logger.debug("No tracked events found for review item, skipping annotations")
-        return []
+    # audio and manual review items can have state changes but no tracked objects
+    if events:
+        timeline.extend(
+            (timestamp, f"[tracker] {note}")
+            for timestamp, note in build_timeline(
+                events, span_end, get_state_changes(detection_ids)
+            )
+        )

-    timeline = build_timeline(events, frame_times[-1], get_state_changes(detection_ids))
-    buckets = annotations_by_frame(timeline, frame_times)
+    timeline.extend(
+        (change["timestamp"], f"[state] {describe_classification_change(change)}")
+        for change in classification_changes
+        if change["timestamp"] <= span_end
+    )
+    buckets = annotations_by_frame(sorted(timeline, key=lambda m: m[0]), frame_times)

    if not buckets:
        return []
@@ -388,7 +410,7 @@ def build_frame_captions(

    for index, timestamp in enumerate(frame_times):
        lines = [f"Frame {index + 1} of {total} (+{timestamp - origin:.1f}s):"]
-        lines.extend(f"[tracker] {note}" for note in buckets.get(index, []))
+        lines.extend(buckets.get(index, []))
        captions.append("\n".join(lines))

    return captions
@@ -40,7 +40,7 @@ from frigate.util.image import get_image_from_recording

 from ..post.api import PostProcessorApi
 from ..types import DataProcessorMetrics
-from .review_annotations import build_frame_captions
+from .review_annotations import build_frame_captions, describe_classification_change

 logger = logging.getLogger(__name__)

@@ -254,6 +254,10 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                    "start_time": r["start_time"],
                    "end_time": r["end_time"],
                    "metadata": r["data"]["metadata"],
+                    "state_changes": [
+                        describe_classification_change(change)
+                        for change in sorted_classification_state_changes(r["data"])
+                    ],
                }
                for r in (
                    ReviewSegment.select(
@@ -298,6 +302,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                primary_item["start_time"] = primary_seg["start_time"]
                primary_item["end_time"] = primary_seg["end_time"]

+                if primary_seg["state_changes"]:
+                    primary_item["state_changes"] = primary_seg["state_changes"]
+
                # Find overlapping contextual items from other cameras
                primary_start = primary_seg["start_time"]
                primary_end = primary_seg["end_time"]
@@ -318,14 +325,25 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                    seg_end = seg["end_time"]

                    if seg_start < primary_end and primary_start < seg_end:
-                        # Avoid duplicates if same camera has multiple overlapping segments
-                        if seg_camera not in seen_contextual_cameras:
-                            contextual_item = copy.deepcopy(seg["metadata"])
-                            contextual_item["camera"] = seg_camera
-                            contextual_item["start_time"] = seg_start
-                            contextual_item["end_time"] = seg_end
-                            contextual_items.append(contextual_item)
-                            seen_contextual_cameras.add(seg_camera)
+                        # Avoid duplicates if same camera has multiple overlapping
+                        # segments. One with state changes is kept as its own item
+                        # so each change stays within its item's time range.
+                        if (
+                            seg_camera in seen_contextual_cameras
+                            and not seg["state_changes"]
+                        ):
+                            continue
+
+                        contextual_item = copy.deepcopy(seg["metadata"])
+                        contextual_item["camera"] = seg_camera
+                        contextual_item["start_time"] = seg_start
+                        contextual_item["end_time"] = seg_end
+
+                        if seg["state_changes"]:
+                            contextual_item["state_changes"] = seg["state_changes"]
+
+                        contextual_items.append(contextual_item)
+                        seen_contextual_cameras.add(seg_camera)

                # Add context array to primary item
                primary_item["context"] = contextual_items
@@ -439,6 +457,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
            captions = build_frame_captions(
                final_data["data"].get("detections") or [],
                [timestamp for _, timestamp in frames],
+                sorted_classification_state_changes(final_data["data"]),
            )

            if not captions:
@@ -688,6 +707,39 @@ def get_recording_buffer_extension(duration: float) -> float:
    return buffer_extension


+def sorted_classification_state_changes(
+    review_data: dict[str, Any],
+) -> list[dict[str, Any]]:
+    """A review item's state classification changes in time order."""
+    return sorted(
+        review_data.get("classification_state_changes") or [],
+        key=lambda change: change["timestamp"],
+    )
+
+
+def format_classification_state_changes(
+    changes: list[dict[str, Any]], start_time: float, end_time: float
+) -> list[str]:
+    """Phrase state classification changes with their timing in the activity.
+
+    Changes are attached while the review item is active, which runs past its
+    end_time by the review cutoff, and a few seconds before its start.
+    """
+    lines = []
+
+    for change in changes:
+        if change["timestamp"] < start_time:
+            when = "just before the activity started"
+        elif change["timestamp"] > end_time:
+            when = "after the activity ended"
+        else:
+            when = f"{round(change['timestamp'] - start_time)}s into the activity"
+
+        lines.append(f"{describe_classification_change(change)}, {when}")
+
+    return lines
+
+
 def run_analysis(
    requestor: InterProcessRequestor,
    genai_client: GenAIClient,
@@ -743,6 +795,13 @@ def run_analysis(
                unified_objects.append(object_type)

    analytics_data["unified_objects"] = unified_objects
+    analytics_data["classification_state_changes"] = (
+        format_classification_state_changes(
+            sorted_classification_state_changes(final_data["data"]),
+            final_data["start_time"],
+            final_data["end_time"],
+        )
+    )

    metadata = genai_client.generate_review_description(
        analytics_data,
@@ -91,8 +91,23 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
        self.tensor_input_details = self.interpreter.get_input_details()
        self.tensor_output_details = self.interpreter.get_output_details()
        self.labelmap = load_labels(labelmap_path, prefill=0, indexed=False)
+        self._forget_unknown_states()
        self.classifications_per_second.start()

+    def _forget_unknown_states(self) -> None:
+        """Drop verified states that are not labels of the loaded model.
+
+        A retrained model can rename or remove labels. Keeping a state it can
+        no longer produce would report its first verified state as a change
+        from that obsolete label.
+        """
+        labels = set(self.labelmap.values())
+        self.state_history = {
+            camera: history
+            for camera, history in self.state_history.items()
+            if history["current_state"] in labels
+        }
+
    def __update_metrics(self, duration: float) -> None:
        self.classifications_per_second.update()
        if self.inference_speed:
@@ -134,15 +149,20 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
        # Don't save if state is stable (detected_state == current_state) AND score is 100%
        return False

-    def verify_state_change(self, camera: str, detected_state: str) -> str | None:
+    def verify_state_change(
+        self, camera: str, detected_state: str, timestamp: float
+    ) -> tuple[str | None, float] | None:
        """
        Verify state change requires 3 consecutive identical states before publishing.
-        Returns state to publish or None if verification not complete.
+        Returns (previous state, time the new state was first seen) once verified,
+        or None if verification not complete. The previous state is None for the
+        first state verified on a camera.
        """
        if camera not in self.state_history:
            self.state_history[camera] = {
                "current_state": None,
                "pending_state": None,
+                "pending_since": 0.0,
                "consecutive_count": 0,
            }

@@ -157,12 +177,14 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
            verification["consecutive_count"] += 1

            if verification["consecutive_count"] >= 3:
+                previous_state = verification["current_state"]
                verification["current_state"] = detected_state
                verification["pending_state"] = None
                verification["consecutive_count"] = 0
-                return detected_state
+                return previous_state, verification["pending_since"]
        else:
            verification["pending_state"] = detected_state
+            verification["pending_since"] = timestamp
            verification["consecutive_count"] = 1
            logger.debug(
                f"New state '{detected_state}' detected for {camera}, need {3 - verification['consecutive_count']} more consecutive detections"
@@ -340,16 +362,19 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
            )
            return

-        verified_state = self.verify_state_change(camera, detected_state)
+        verified = self.verify_state_change(camera, detected_state, timestamp)

-        if verified_state is not None:
+        if verified is not None:
+            previous_state, changed_at = verified
            self._emit_result(
                {
                    "type": "classification",
                    "processor": "state",
                    "model_name": self.model_config.name,
                    "camera": camera,
-                    "state": verified_state,
+                    "state": detected_state,
+                    "previous_state": previous_state,
+                    "timestamp": changed_at,
                }
            )

@@ -46,8 +46,42 @@ _PROVIDER_LABELS = {
    "MIGraphXExecutionProvider": "MIGraphX",
    "OpenVINOExecutionProvider": "OpenVINO",
    "CPUExecutionProvider": "CPU",
+    "LighterANE": "Neural Engine",
 }

+# lighter (https://github.com/fieldwork-ai/lighter) places an ONNX Runtime plugin
+# execution provider in a container started with --device lighter.sh/ane=all,
+# which runs models on a Mac's Neural Engine; LIGHTER_ANE_EP names where it is
+LIGHTER_ANE_EP_NAME = "LighterANE"
+LIGHTER_ANE_LIBRARY = "/usr/lib/lighter/liblighter_ane_ep.so"
+
+
+def get_lighter_ane_devices() -> list[Any]:
+    """Get the Neural Engine devices lighter's provider offers, registering it once.
+
+    Returns:
+        The provider's ONNX Runtime devices, or an empty list without lighter's device
+    """
+    library = os.environ.get("LIGHTER_ANE_EP", LIGHTER_ANE_LIBRARY)
+
+    if not os.path.exists(library):
+        return []
+
+    devices = [d for d in ort.get_ep_devices() if d.ep_name == LIGHTER_ANE_EP_NAME]
+
+    if not devices:
+        try:
+            ort.register_execution_provider_library(LIGHTER_ANE_EP_NAME, library)
+        except Exception as e:
+            logger.warning(
+                f"Failed to load the Neural Engine provider from {library}: {e}"
+            )
+            return []
+
+        devices = [d for d in ort.get_ep_devices() if d.ep_name == LIGHTER_ANE_EP_NAME]
+
+    return devices
+

 def is_arm64_platform() -> bool:
    """Check if we're running on an ARM platform."""
@@ -689,6 +723,23 @@ def get_optimized_runner(
        if rknn_path:
            return _record_runner(model_path, model_type, RKNNModelRunner(rknn_path))

+    if device != "CPU" and (ane_devices := get_lighter_ane_devices()):
+        sess_options = get_ort_session_options(model_type) or ort.SessionOptions()
+        sess_options.add_provider_for_devices(ane_devices, {})
+
+        try:
+            session = ort.InferenceSession(model_path, sess_options=sess_options)
+        except Exception as e:
+            logger.warning(
+                f"Failed to load {model_path} on the Neural Engine, using the default providers: {e}"
+            )
+        else:
+            return _record_runner(
+                model_path,
+                model_type,
+                ONNXModelRunner(session, model_type=model_type),
+            )
+
    providers, options = get_ort_providers(device == "CPU", device, **kwargs)

    if providers[0] == "CPUExecutionProvider":
@@ -123,6 +123,7 @@ class ModelConfig(BaseModel):
    _all_attributes: list[str] = PrivateAttr()
    _all_attribute_logos: list[str] = PrivateAttr()
    _model_hash: str = PrivateAttr()
+    _plus_id: str | None = PrivateAttr(default=None)

    @property
    def merged_labelmap(self) -> dict[int, str]:
@@ -148,6 +149,11 @@ class ModelConfig(BaseModel):
    def model_hash(self) -> str:
        return self._model_hash

+    @property
+    def plus_id(self) -> str | None:
+        """The Frigate+ model id, once a plus:// path has been resolved."""
+        return self._plus_id
+
    def __init__(self, **config):
        super().__init__(**config)

@@ -178,6 +184,7 @@ class ModelConfig(BaseModel):
        os.makedirs(MODEL_CACHE_DIR, exist_ok=True)

        model_id = self.path[7:]
+        self._plus_id = model_id
        self.path = os.path.join(MODEL_CACHE_DIR, model_id)
        model_info_path = f"{self.path}.json"

@@ -25,6 +25,7 @@ SYS_ROOT = "/sys"
 DEV_ROOT = "/dev"
 PROC_ROOT = "/proc"
 ETC_ROOT = "/etc"
+LIB_ROOT = "/usr/lib"

 # a Coral reports as Global Unichip until its firmware is loaded, then as Google
 CORAL_USB_IDS = {("1a6e", "089a"), ("18d1", "9302")}
@@ -273,6 +274,16 @@ def detect_memryx() -> DetectionHardware | None:
    return _hardware("memryx", "memryx", "MemryX MX3", units)


+def detect_deepx() -> DetectionHardware | None:
+    """Find DEEPX NPUs by their device nodes."""
+    units = _dev_units("dxrt*", "deepx:PCIe:{index}", "PCIe")
+
+    if not units:
+        return None
+
+    return _hardware("deepx", "deepx", "DEEPX NPU", units)
+
+
 def detect_rockchip() -> DetectionHardware | None:
    """Find a Rockchip NPU by reading the SoC from the device tree."""
    compatible = _read(f"{PROC_ROOT}/device-tree/compatible")
@@ -307,6 +318,19 @@ def detect_synaptics() -> DetectionHardware | None:
    return _hardware("synaptics", "synaptics", "Synaptics NPU", units)


+def detect_lighter_ane() -> DetectionHardware | None:
+    """Find a Mac's Neural Engine by the provider library lighter's device places."""
+    library = os.environ.get(
+        "LIGHTER_ANE_EP", f"{LIB_ROOT}/lighter/liblighter_ane_ep.so"
+    )
+    if not os.path.exists(library):
+        return None
+
+    # runs through onnx, whose session picks lighter's provider when it is present
+    units = [HardwareUnit(device="onnx", label="Neural Engine")]
+    return _hardware("onnx:lighter", "onnx", "Apple Neural Engine", units)
+
+
 def detect_cpu() -> DetectionHardware:
    """The CPU, which is always available."""
    units = [HardwareUnit(device="cpu", label="CPU")]
@@ -319,6 +343,7 @@ PROBES = (
    detect_coral_usb,
    detect_hailo,
    detect_memryx,
+    detect_deepx,
    detect_intel_npu,
    detect_intel_gpu,
    detect_nvidia_gpu,
@@ -327,6 +352,7 @@ PROBES = (
    detect_rockchip,
    detect_axengine,
    detect_synaptics,
+    detect_lighter_ane,
    detect_cpu,
 )

@@ -1,7 +1,7 @@
 import json
 import logging
 import os
-from typing import Any, Literal
+from typing import Any, ClassVar, Literal

 import numpy as np
 import zmq
@@ -21,6 +21,7 @@ class ZmqDetectorConfig(BaseDetectorConfig):
    model_config = ConfigDict(
        title="ZMQ IPC",
    )
+    device_spec_field: ClassVar[str] = "endpoint"

    type: Literal[DETECTOR_KEY]
    endpoint: str = Field(
@@ -11,7 +11,11 @@ from typing import Any
 from peewee import DoesNotExist

 from frigate.comms.config_updater import ConfigSubscriber
-from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
+from frigate.comms.detections_updater import (
+    DetectionPublisher,
+    DetectionSubscriber,
+    DetectionTypeEnum,
+)
 from frigate.comms.embeddings_updater import (
    EmbeddingsRequestEnum,
    EmbeddingsResponder,
@@ -168,6 +172,7 @@ class EmbeddingMaintainer(threading.Thread):
        )
        self.review_subscriber = ReviewDataSubscriber("")
        self.detection_subscriber = DetectionSubscriber(DetectionTypeEnum.video.value)
+        self.detection_publisher = DetectionPublisher(DetectionTypeEnum.all.value)
        self.embeddings_responder = EmbeddingsResponder()
        self.frame_manager = SharedMemoryFrameManager()

@@ -356,6 +361,7 @@ class EmbeddingMaintainer(threading.Thread):
        self.event_end_subscriber.stop()
        self.recordings_subscriber.stop()
        self.detection_subscriber.stop()
+        self.detection_publisher.stop()
        self.event_metadata_publisher.stop()
        self.event_metadata_subscriber.stop()
        self.embeddings_responder.stop()
@@ -851,6 +857,21 @@ class EmbeddingMaintainer(threading.Thread):
                        f"{result['camera']}/classification/{result['model_name']}",
                        result["state"],
                    )
+
+                    # the first state verified after startup is not a change
+                    if result["previous_state"] is not None:
+                        self.detection_publisher.publish(
+                            (
+                                result["camera"],
+                                {
+                                    "model": result["model_name"],
+                                    "from": result["previous_state"],
+                                    "to": result["state"],
+                                    "timestamp": result["timestamp"],
+                                },
+                            ),
+                            DetectionTypeEnum.classification_state.value,
+                        )
                elif result["processor"] == "object":
                    object_id = result["object_id"]
                    camera = result["camera"]
@@ -11,6 +11,7 @@ from typing import Any

 import numpy as np

+from frigate.camera import CameraMetrics
 from frigate.comms.detections_updater import DetectionPublisher, DetectionTypeEnum
 from frigate.comms.inter_process import InterProcessRequestor
 from frigate.config import CameraConfig, CameraInput, FrigateConfig
@@ -36,6 +37,7 @@ from frigate.data_processing.common.audio_transcription.model import (
 from frigate.data_processing.real_time.audio_transcription import (
    AudioTranscriptionRealTimeProcessor,
 )
+from frigate.data_processing.types import DataProcessorMetrics
 from frigate.ffmpeg_presets import parse_preset_input
 from frigate.log import LogPipe, suppress_stderr_during
 from frigate.util.builtin import get_ffmpeg_arg_list, load_labels
@@ -86,6 +88,7 @@ class AudioProcessor(FrigateProcess):
        self,
        config: FrigateConfig,
        camera_metrics: DictProxy,
+        embeddings_metrics: DataProcessorMetrics,
        stop_event: MpEvent,
    ):
        super().__init__(
@@ -93,8 +96,38 @@ class AudioProcessor(FrigateProcess):
        )

        self.camera_metrics = camera_metrics
+        self.embeddings_metrics = embeddings_metrics
        self.config = config

+    def spawn_if_needed(self, camera: CameraConfig) -> None:
+        """Start an audio maintainer for the camera once everything it needs
+        has arrived. Returning early leaves the camera for the next poll."""
+        name = camera.name
+        if name is None or name in self.audio_threads:
+            return
+        if not camera.enabled or not camera.audio.enabled:
+            return
+        # ffmpeg update may not have arrived yet
+        if not any("audio" in i.roles for i in camera.ffmpeg.inputs):
+            return
+        # the camera maintainer creates metrics on its own poll of the same
+        # add update and may not have gotten there yet
+        metrics = self.camera_metrics.get(name)
+        if metrics is None:
+            return
+        thread = AudioEventMaintainer(
+            camera,
+            self.config,
+            metrics,
+            self.embeddings_metrics,
+            self.transcription_model_runner,
+            self.stop_event,  # type: ignore[arg-type]
+            self.genai_manager,
+        )
+        self.audio_threads[name] = thread
+        thread.start()
+        self.logger.info(f"Audio maintainer started for {name}")
+
    def __stop_audio_thread(self, camera: str) -> None:
        thread = self.audio_threads.pop(camera, None)
        if thread is None:
@@ -150,29 +183,8 @@ class AudioProcessor(FrigateProcess):
            ],
        )

-        def spawn_if_needed(camera: CameraConfig) -> None:
-            name = camera.name
-            if name is None or name in self.audio_threads:
-                return
-            if not camera.enabled or not camera.audio.enabled:
-                return
-            # ffmpeg update may not have arrived yet; wait for next poll
-            if not any("audio" in i.roles for i in camera.ffmpeg.inputs):
-                return
-            thread = AudioEventMaintainer(
-                camera,
-                self.config,
-                self.camera_metrics,
-                self.transcription_model_runner,
-                self.stop_event,  # type: ignore[arg-type]
-                self.genai_manager,
-            )
-            self.audio_threads[name] = thread
-            thread.start()
-            self.logger.info(f"Audio maintainer started for {name}")
-
        for camera in self.config.cameras.values():
-            spawn_if_needed(camera)
+            self.spawn_if_needed(camera)

        self.logger.info(f"Audio processor started (pid: {self.pid})")

@@ -182,15 +194,14 @@ class AudioProcessor(FrigateProcess):
            updated_topics = config_subscriber.check_for_updates()

            # stop maintainers for removed cameras so their ffmpeg process is
-            # torn down and they stop touching camera_metrics (which the camera
-            # maintainer has already popped for the removed camera)
+            # torn down
            for removed_camera in updated_topics.get(
                CameraConfigUpdateEnum.remove.name, []
            ):
                self.__stop_audio_thread(removed_camera)

            for camera in self.config.cameras.values():
-                spawn_if_needed(camera)
+                self.spawn_if_needed(camera)

        config_subscriber.stop()

@@ -212,7 +223,8 @@ class AudioEventMaintainer(threading.Thread):
        self,
        camera: CameraConfig,
        config: FrigateConfig,
-        camera_metrics: DictProxy,
+        metrics: CameraMetrics,
+        embeddings_metrics: DataProcessorMetrics,
        audio_transcription_model_runner: AudioTranscriptionModelRunner | None,
        stop_event: threading.Event,
        genai_manager: Any = None,
@@ -221,7 +233,11 @@ class AudioEventMaintainer(threading.Thread):

        self.config = config
        self.camera_config = camera
-        self.camera_metrics = camera_metrics
+        # hold the metrics object rather than indexing the manager dict per
+        # chunk, which costs an IPC round trip and breaks once the camera
+        # maintainer pops the entry on removal
+        self.metrics = metrics
+        self.embeddings_metrics = embeddings_metrics
        self.stop_event = stop_event
        # per-camera stop signal so a single maintainer can be torn down at
        # runtime (e.g. on camera removal) without stopping the whole process
@@ -265,7 +281,7 @@ class AudioEventMaintainer(threading.Thread):
                camera_config=self.camera_config,
                requestor=self.requestor,
                model_runner=self.audio_transcription_model_runner,
-                metrics=self.camera_metrics[self.camera_config.name],
+                metrics=self.embeddings_metrics,
                stop_event=self.stop_event,
                genai_manager=self.genai_manager,
            )
@@ -291,8 +307,8 @@ class AudioEventMaintainer(threading.Thread):
        audio_as_float: np.ndarray = audio.astype(np.float32)
        rms, dBFS = self.calculate_audio_levels(audio_as_float)

-        self.camera_metrics[self.camera_config.name].audio_rms.value = rms
-        self.camera_metrics[self.camera_config.name].audio_dBFS.value = dBFS
+        self.metrics.audio_rms.value = rms
+        self.metrics.audio_dBFS.value = dBFS

        audio_detections: list[tuple[str, float]] = []

@@ -377,7 +393,6 @@ class AudioEventMaintainer(threading.Thread):
                return

            time.sleep(self.camera_config.ffmpeg.retry_interval)
-            self.logpipe.dump()
            self.start_or_restart_ffmpeg()

        if self.audio_listener is None or self.audio_listener.stdout is None:
@@ -84,6 +84,8 @@ _user_agent_args = [
 PRESETS_HW_ACCEL_DECODE = {
    "preset-rpi-64-h264": "-c:v:1 h264_v4l2m2m",
    "preset-rpi-64-h265": "-c:v:1 hevc_v4l2m2m",
+    "preset-apple-silicon-h264": "-c:v h264_v4l2m2m",
+    "preset-apple-silicon-h265": "-c:v hevc_v4l2m2m",
    FFMPEG_HWACCEL_VAAPI: "-hwaccel_flags allow_profile_mismatch -hwaccel vaapi -hwaccel_device {3} -hwaccel_output_format vaapi",
    "preset-intel-qsv-h264": f"-hwaccel qsv -qsv_device {{3}} -hwaccel_output_format qsv -c:v h264_qsv{' -bsf:v dump_extra' if LIBAVFORMAT_VERSION_MAJOR >= 61 else ''}",  # https://trac.ffmpeg.org/ticket/9766#comment:17
    "preset-intel-qsv-h265": f"-load_plugin hevc_hw -hwaccel qsv -qsv_device {{3}} -hwaccel_output_format qsv{' -bsf:v dump_extra' if LIBAVFORMAT_VERSION_MAJOR >= 61 else ''}",  # https://trac.ffmpeg.org/ticket/9766#comment:17
@@ -120,6 +122,9 @@ PRESETS_HW_ACCEL_DECODE["preset-rk-h265"] = PRESETS_HW_ACCEL_DECODE[
 PRESETS_HW_ACCEL_SCALE = {
    "preset-rpi-64-h264": "-r {0} -vf fps={0},scale={1}:{2}",
    "preset-rpi-64-h265": "-r {0} -vf fps={0},scale={1}:{2}",
+    # ffmpeg's v4l2m2m decoders cannot scale, so frames are scaled on the CPU
+    "preset-apple-silicon-h264": "-r {0} -vf fps={0},scale={1}:{2}",
+    "preset-apple-silicon-h265": "-r {0} -vf fps={0},scale={1}:{2}",
    FFMPEG_HWACCEL_VAAPI: "-r {0} -vf fps={0},scale_vaapi=w={1}:h={2},hwdownload,format=nv12",
    "preset-intel-qsv-h264": "-r {0} -vf vpp_qsv=w={1}:h={2}:format=nv12,hwdownload,format=nv12,fps={0},format=yuv420p",
    "preset-intel-qsv-h265": "-r {0} -vf vpp_qsv=w={1}:h={2}:format=nv12,hwdownload,format=nv12,fps={0},format=yuv420p",
@@ -150,6 +155,8 @@ PRESETS_HW_ACCEL_SCALE["preset-rk-h265"] = PRESETS_HW_ACCEL_SCALE[FFMPEG_HWACCEL
 PRESETS_HW_ACCEL_ENCODE_BIRDSEYE = {
    "preset-rpi-64-h264": "{0} -hide_banner {1} -c:v h264_v4l2m2m {2}",
    "preset-rpi-64-h265": "{0} -hide_banner {1} -c:v hevc_v4l2m2m {2}",
+    "preset-apple-silicon-h264": "{0} -hide_banner {1} -c:v h264_v4l2m2m {2}",
+    "preset-apple-silicon-h265": "{0} -hide_banner {1} -c:v h264_v4l2m2m {2}",
    # -vaapi_device is required in addition to -hwaccel_device: this is the only
    # birdseye preset that uses hwupload, and ffmpeg 8 initializes filters before
    # the decoder creates a device, so hwupload cannot see an -hwaccel_device one.
@@ -184,6 +191,8 @@ PRESETS_HW_ACCEL_ENCODE_BIRDSEYE["preset-rk-h264"] = PRESETS_HW_ACCEL_ENCODE_BIR
 PRESETS_HW_ACCEL_ENCODE_TIMELAPSE = {
    "preset-rpi-64-h264": "{0} -hide_banner {1} -c:v h264_v4l2m2m -pix_fmt yuv420p {2}",
    "preset-rpi-64-h265": "{0} -hide_banner {1} -c:v hevc_v4l2m2m -pix_fmt yuv420p {2}",
+    "preset-apple-silicon-h264": "{0} -hide_banner {1} -c:v h264_v4l2m2m -pix_fmt yuv420p {2}",
+    "preset-apple-silicon-h265": "{0} -hide_banner {1} -c:v hevc_v4l2m2m -pix_fmt yuv420p {2}",
    FFMPEG_HWACCEL_VAAPI: "{0} -hide_banner -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device {3} {1} -c:v h264_vaapi {2}",
    "preset-intel-qsv-h264": "{0} -hide_banner {1} -c:v h264_qsv -profile:v high -level:v 4.1 -async_depth:v 1 {2}",
    "preset-intel-qsv-h265": "{0} -hide_banner {1} -c:v hevc_qsv -profile:v main -level:v 4.1 -async_depth:v 1 {2}",
@@ -103,11 +103,10 @@ class LlamaCppClient(GenAIClient):
    _supports_reasoning: bool
    _image_token_cache: dict[tuple[int, int], int]
    _text_baseline_tokens: int | None
-    _media_marker: str

    @property
    def supports_embeddings(self) -> bool:
-        """llama.cpp exposes an /embeddings endpoint for any loaded model."""
+        """llama.cpp exposes a /v1/embeddings endpoint for any loaded model."""
        return True

    def _auth_headers(self) -> dict | None:
@@ -159,7 +158,6 @@ class LlamaCppClient(GenAIClient):
        self._supports_reasoning = False
        self._image_token_cache = {}
        self._text_baseline_tokens = None
-        self._media_marker = "<__media__>"

        base_url = (
            self.genai_config.base_url.rstrip("/")
@@ -187,7 +185,6 @@ class LlamaCppClient(GenAIClient):
        self._supports_audio = info["supports_audio"]
        self._supports_tools = info["supports_tools"]
        self._supports_reasoning = info["supports_reasoning"]
-        self._media_marker = info["media_marker"]

        logger.info(
            "llama.cpp model '%s' initialized — context: %s, vision: %s, audio: %s, tools: %s, reasoning: %s",
@@ -215,9 +212,7 @@ class LlamaCppClient(GenAIClient):
        `architecture.input_modalities` (text/image/audio) — the primary
        source. When proxied through llama-swap, the same entry carries
        `status.args` (server launch argv) and, for the loaded model,
-        `meta.n_ctx`. /props remains the only source for `media_marker`,
-        which the server randomizes per startup unless LLAMA_MEDIA_MARKER
-        is set.
+        `meta.n_ctx`.
        """
        info: dict[str, Any] = {
            "context_size": None,
@@ -225,7 +220,6 @@ class LlamaCppClient(GenAIClient):
            "supports_audio": False,
            "supports_tools": False,
            "supports_reasoning": False,
-            "media_marker": "<__media__>",
        }

        model_entry: dict[str, Any] | None = None
@@ -314,16 +308,8 @@ class LlamaCppClient(GenAIClient):
            # in the Jinja chat template itself.
            chat_template = props.get("chat_template") or ""
            info["supports_reasoning"] = "enable_thinking" in chat_template
-
-            media_marker = props.get("media_marker")
-            if isinstance(media_marker, str) and media_marker:
-                info["media_marker"] = media_marker
        except Exception as e:
-            logger.warning(
-                "Failed to query llama.cpp /props endpoint: %s. "
-                "Image embeddings may fail if the server randomized its media marker.",
-                e,
-            )
+            logger.warning("Failed to query llama.cpp /props endpoint: %s", e)

        return info

@@ -474,9 +460,6 @@ class LlamaCppClient(GenAIClient):
    def _transcribe_via_chat(self, audio: bytes, language: str | None) -> str | None:
        """Transcribe through /v1/chat/completions, for servers without the
        transcriptions route.
-
-        The _media_marker / multimodal_data convention is an /embeddings-only
-        protocol, so no marker-refresh retry is needed here.
        """
        prompt = "Transcribe the speech in this audio verbatim. Respond with the transcript only, and with nothing at all if there is no speech."

@@ -794,41 +777,16 @@ class LlamaCppClient(GenAIClient):
            )
        return result if result else None

-    def _refresh_media_marker(self) -> bool:
-        """Re-fetch /props and update the cached media marker if it changed.
-
-        The server randomizes the marker per startup (unless LLAMA_MEDIA_MARKER
-        is set), so a stale marker indicates a restart. Returns True iff the
-        marker was updated to a new value — used to gate a one-shot retry of
-        a failed embeddings request.
-        """
-        if self.provider is None:
-            return False
-        try:
-            props = self._fetch_llama_props(self.provider, self.genai_config.model)
-        except Exception as e:
-            logger.warning("Failed to refresh llama.cpp media marker: %s", e)
-            return False
-
-        marker = props.get("media_marker")
-
-        if not isinstance(marker, str) or not marker or marker == self._media_marker:
-            return False
-
-        logger.info("llama.cpp media marker changed (server restart); refreshed")
-        self._media_marker = marker
-        return True
-
    def embed(
        self,
        texts: list[str] | None = None,
        images: list[bytes] | None = None,
    ) -> list[np.ndarray]:
-        """Generate embeddings via llama.cpp /embeddings endpoint.
+        """Generate embeddings via llama.cpp /v1/embeddings endpoint.

-        Supports batch requests. Uses content format with prompt_string and
-        multimodal_data for images (PR #15108). Server must be started with
-        --embeddings and --mmproj for multimodal support.
+        Each text or image is one entry in `input`, using the chat-style
+        content array from ggml-org/llama.cpp#29556. Server must be started
+        with --embeddings, and --mmproj for image support.
        """
        if self.provider is None:
            logger.warning(
@@ -843,49 +801,42 @@ class LlamaCppClient(GenAIClient):

        EMBEDDING_DIM = 768

-        encoded_images: list[str] = []
+        inputs: list[dict[str, Any]] = [
+            {"content": [{"type": "text", "text": text}]} for text in texts
+        ]
+
        for img in images:
            # llama.cpp uses STB which does not support WebP; convert to JPEG
            jpeg_bytes = _to_jpeg(img)
            to_encode = jpeg_bytes if jpeg_bytes is not None else img
-            encoded_images.append(base64.b64encode(to_encode).decode("utf-8"))
-
-        def build_content() -> list[dict[str, Any]]:
-            # prompt_string must contain the server's media marker placeholder
-            # for each image. The marker is randomized per server startup.
-            content: list[dict[str, Any]] = []
-            for text in texts:
-                content.append({"prompt_string": text})
-            for encoded in encoded_images:
-                content.append(
-                    {
-                        "prompt_string": f"{self._media_marker}\n",
-                        "multimodal_data": [encoded],
-                    }
-                )
-            return content
-
-        def post_embeddings() -> requests.Response:
-            return self._post(
-                f"{self.provider}/embeddings",
-                json={"model": self.genai_config.model, "content": build_content()},
-                timeout=self.timeout,
+            encoded = base64.b64encode(to_encode).decode("utf-8")
+            # The trailing newline keeps tokenization identical to the older
+            # "<__media__>\n" prompt_string format, so indexed vectors stay valid
+            inputs.append(
+                {
+                    "content": [
+                        {
+                            "type": "image_url",
+                            "image_url": {"url": f"data:image/jpeg;base64,{encoded}"},
+                        },
+                        {"type": "text", "text": "\n"},
+                    ]
+                }
            )

        try:
-            try:
-                response = post_embeddings()
-                response.raise_for_status()
-            except requests.exceptions.RequestException:
-                # The server may have restarted with a new media marker.
-                # Refresh from /props; only retry if the marker actually changed.
-                if not encoded_images or not self._refresh_media_marker():
-                    raise
-                response = post_embeddings()
-                response.raise_for_status()
-            result = response.json()
+            response = self._post(
+                f"{self.provider}/v1/embeddings",
+                json={
+                    "model": self.genai_config.model,
+                    "input": inputs,
+                    "encoding_format": "float",
+                },
+                timeout=self.timeout,
+            )
+            response.raise_for_status()
+            items = response.json().get("data")

-            items = result.get("data", result) if isinstance(result, dict) else result
            if not isinstance(items, list):
                logger.warning("llama.cpp embeddings returned unexpected format")
                return []
@@ -896,11 +847,7 @@ class LlamaCppClient(GenAIClient):
                if emb is None:
                    logger.warning("llama.cpp embeddings item missing embedding field")
                    continue
-                arr = np.array(emb, dtype=np.float32)
-                if arr.ndim > 1:
-                    # llama.cpp can return token-level embeddings; pool per item
-                    arr = arr.mean(axis=0)
-                arr = arr.flatten()
+                arr = np.array(emb, dtype=np.float32).flatten()
                orig_dim = arr.size
                if orig_dim != EMBEDDING_DIM:
                    if orig_dim > EMBEDDING_DIM:
@@ -104,6 +104,21 @@ def build_review_description_prompt(
        else:
            return "\n- (No objects detected)"

+    def get_state_changes_section() -> str:
+        # empty when nothing changed so the prompt is otherwise unaffected
+        changes = review_data.get("classification_state_changes")
+
+        if not changes:
+            return ""
+
+        return (
+            "\n\n## State Changes\n\n"
+            "The camera's state classifiers watch fixed areas of the scene and "
+            "reported these changes. They come from the classifiers rather than "
+            "from the images, and they are reliable. Describe each one where it "
+            "fits in the sequence of events.\n- " + "\n- ".join(changes)
+        )
+
    fields = get_review_field_guidelines(response_style)
    frame_guidance = f"\n{FRAME_ANNOTATION_GUIDANCE}" if frame_captions else ""

@@ -145,7 +160,7 @@ Respond with a JSON object matching the provided schema. Field-specific guidance
 - Camera: {review_data["camera"]}
 - Total frames: {len(thumbnails)} (Frame 1 = earliest, Frame {len(thumbnails)} = latest){frame_guidance}
 - Activity started at {review_data["start"]} and lasted {review_data["duration"]} seconds
- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}
+- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}{get_state_changes_section()}

 ## Objects in Scene

@@ -196,6 +211,17 @@ def build_review_summary_prompt(
        f" to "
        f"{datetime.datetime.fromtimestamp(end_ts).strftime('%B %d, %Y at %I:%M %p')}"
    )
+    has_state_changes = any(
+        "state_changes" in item
+        for event in events
+        for item in [event, *event.get("context", [])]
+    )
+    state_changes_format = (
+        '\n- "state_changes" (only on some events): changes to monitored areas '
+        "reported by the camera's state classifiers, which are reliable"
+        if has_state_changes
+        else ""
+    )
    prompt = f"""
 You are a security officer writing a concise security report.

@@ -203,7 +229,7 @@ Time range: {time_range}

 Input format: Each event is a JSON object with:
 - "title", "scene", "confidence", "potential_threat_level" (0-2), "other_concerns", "camera", "time", "start_time", "end_time"
- "context": array of related events from other cameras that occurred during overlapping time periods
+- "context": array of related events from other cameras that occurred during overlapping time periods{state_changes_format}

 **Note: Use the "scene" field for event descriptions in the report. Ignore any "shortSummary" field if present.**

@@ -144,6 +144,14 @@ class LogPipe(threading.Thread):
        self.pipeReader.close()

    def dump(self) -> None:
+        if not self.deque:
+            return
+
+        self.logger.log(
+            self.level,
+            "The following ffmpeg logs include the last 100 lines prior to exit.",
+        )
+
        while len(self.deque) > 0:
            self.logger.log(self.level, self.deque.popleft())

@@ -195,15 +195,20 @@ class Notice(Model):
    first_seen = DateTimeField()
    last_seen = DateTimeField()
    count = IntegerField(default=1)
-    dismissed_at = DateTimeField(null=True)
+    # hidden until the next occurrence
+    acknowledged_at = DateTimeField(null=True)
+    # hidden for good
+    muted_at = DateTimeField(null=True)


 class NoticeStats(Model):
    kind = CharField(null=False, primary_key=True, max_length=50)
    occurrences = IntegerField(default=0)
-    dismissals = IntegerField(default=0)
+    acknowledgements = IntegerField(default=0)
+    mutes = IntegerField(default=0)
    first_seen = DateTimeField()
    last_seen = DateTimeField()
    # watermarks for a future analytics reporter; unused until then
    reported_occurrences = IntegerField(default=0)
-    reported_dismissals = IntegerField(default=0)
+    reported_acknowledgements = IntegerField(default=0)
+    reported_mutes = IntegerField(default=0)
@@ -188,8 +188,12 @@ class ImprovedMotionDetector(MotionDetector):
            self.config.skip_motion_threshold is not None
            and pct_motion > self.config.skip_motion_threshold
        ):
-            # force a recalibration so we transition to the new background
+            # recalibrate so we transition to the new background. the frame
+            # still has to be blended in here, otherwise the background stays
+            # frozen and every subsequent frame skips as well
            self.calibrating = True
+            cv2.accumulateWeighted(resized_frame, self.avg_frame, 0.2)
+            self.motion_frame_count = 0
            return []

        # once the motion is less than 5% and the number of contours is < 4, assume its calibrated
@@ -5,7 +5,7 @@ import threading
 from collections.abc import Callable
 from dataclasses import dataclass
 from datetime import datetime
-from typing import Any
+from typing import Any, cast

 from frigate.const import REPLAY_CAMERA_PREFIX
 from frigate.models import Notice, NoticeStats
@@ -77,9 +77,8 @@ class NoticeRegistry:
    ) -> None:
        """Insert a notice or count another occurrence of it.

-        A dismissed notice stays dismissed when it is raised again, unless its
-        kind sets reopen_at_count. A kind that should come back after a
-        dismissal gives each episode its own scope.
+        Another occurrence shows an acknowledged notice again. A muted notice
+        stays hidden.
        """
        definition = NOTICE_KINDS.get(kind)

@@ -112,7 +111,6 @@ class NoticeRegistry:
                    first_seen=now,
                    last_seen=now,
                    count=1,
-                    dismissed_at=None,
                )
                self._bump_occurrences(kind, 1, now)

@@ -175,7 +173,7 @@ class NoticeRegistry:
            self._notify()

    def resolve_camera(self, camera: str) -> None:
-        """Drop the notices and check dismissals of a camera being deleted."""
+        """Drop the notices and check mutes of a camera being deleted."""
        camera_kinds = [
            key
            for key, definition in NOTICE_KINDS.items()
@@ -193,7 +191,7 @@ class NoticeRegistry:
            )

            # a stream id names its camera first; a config id ends with camera.<name>
-            for check in self.dismissed_checks():
+            for check in self.muted_checks():
                check_id = check["id"]

                if check_id.startswith(f"stream:{camera}:") or (
@@ -205,26 +203,50 @@ class NoticeRegistry:
        if deleted:
            self._notify()

-    def purge_dismissed(self) -> int:
-        """Delete every dismissed row so each can show again. Returns how many."""
-        with self._lock:
-            return int(
-                Notice.delete().where(Notice.dismissed_at.is_null(False)).execute()
-            )
+    def acknowledge(self, row_id: str) -> bool:
+        """Hide a notice until it happens again.

-    def dismiss(self, row_id: str) -> bool:
-        """Hide a notice or check row for good. Returns False for an unknown id."""
+        Returns False for an unknown id or a kind that never repeats, such as
+        a check row or the update notice.
+        """
        with self._lock:
            existing = Notice.get_or_none(Notice.id == row_id)

            if existing is None:
-                # a check row gets a notice row only once it is dismissed
+                return False
+
+            definition = NOTICE_KINDS.get(existing.kind)
+
+            if definition is None or not definition.counts_repeats:
+                return False
+
+            if existing.acknowledged_at is not None or existing.muted_at is not None:
+                return True
+
+            Notice.update(acknowledged_at=datetime.now().timestamp()).where(
+                Notice.id == row_id
+            ).execute()
+            NoticeStats.update(acknowledgements=NoticeStats.acknowledgements + 1).where(
+                NoticeStats.kind == existing.kind
+            ).execute()
+
+        self._notify()
+        return True
+
+    def mute(self, row_id: str) -> bool:
+        """Hide a notice or check row for good. Returns False for an unknown id."""
+        now = datetime.now().timestamp()
+
+        with self._lock:
+            existing = Notice.get_or_none(Notice.id == row_id)
+
+            if existing is None:
+                # a check row gets a notice row only once it is muted
                kind, _, scope = row_id.partition(":")

                if kind not in CHECK_KINDS or not scope:
                    return False

-                now = datetime.now().timestamp()
                Notice.create(
                    id=row_id,
                    kind=kind,
@@ -233,40 +255,78 @@ class NoticeRegistry:
                    first_seen=now,
                    last_seen=now,
                    count=1,
-                    dismissed_at=now,
+                    muted_at=now,
                )
                return True

-            if existing.dismissed_at is not None:
+            if existing.muted_at is not None:
                return True

            if existing.kind not in NOTICE_KINDS:
                return False

-            Notice.update(dismissed_at=datetime.now().timestamp()).where(
+            Notice.update(acknowledged_at=None, muted_at=now).where(
                Notice.id == row_id
            ).execute()
-            NoticeStats.update(dismissals=NoticeStats.dismissals + 1).where(
+            NoticeStats.update(mutes=NoticeStats.mutes + 1).where(
                NoticeStats.kind == existing.kind
            ).execute()

        self._notify()
        return True

-    def dismissed_checks(self) -> list[dict[str, Any]]:
-        """Dismissed config and stream check rows, newest first."""
+    def unhide(self, row_id: str) -> bool:
+        """Show an acknowledged or muted row again. Returns False for an unknown id."""
+        with self._lock:
+            existing = Notice.get_or_none(Notice.id == row_id)
+
+            if existing is None:
+                return False
+
+            if existing.kind in CHECK_KINDS:
+                Notice.delete_by_id(row_id)
+                return True
+
+            Notice.update(acknowledged_at=None, muted_at=None).where(
+                Notice.id == row_id
+            ).execute()
+
+        self._notify()
+        return True
+
+    def unhide_all(self) -> None:
+        """Show every acknowledged and muted row again."""
+        with self._lock:
+            for check in self.muted_checks():
+                Notice.delete_by_id(check["id"])
+
+            shown = (
+                Notice.update(acknowledged_at=None, muted_at=None)
+                .where(
+                    Notice.acknowledged_at.is_null(False)
+                    | Notice.muted_at.is_null(False)
+                )
+                .execute()
+            )
+
+        if shown:
+            self._notify()
+
+    def muted_checks(self) -> list[dict[str, Any]]:
+        """Muted config and stream check rows, newest first."""
        rows = (
            Notice.select()
            .where(Notice.kind.in_(list(CHECK_KINDS)))
-            .order_by(Notice.dismissed_at.desc())
+            .order_by(Notice.muted_at.desc())
        )
-        return [{"id": row.id, "dismissed_at": row.dismissed_at} for row in rows]
+        return [{"id": row.id, "muted_at": row.muted_at} for row in rows]

-    def active(self, include_dismissed: bool = False) -> list[dict[str, Any]]:
+    def active(self, include_hidden: bool = False) -> list[dict[str, Any]]:
        """Notices most severe first, then most recent first.

        Args:
-            include_dismissed: Also return dismissed notices, for the history view
+            include_hidden: Also return acknowledged and muted notices, for the
+                hidden list
        """
        rows = []

@@ -276,7 +336,9 @@ class NoticeRegistry:
            if definition is None:
                continue

-            if row.dismissed_at is not None and not include_dismissed:
+            hidden = row.acknowledged_at is not None or row.muted_at is not None
+
+            if hidden and not include_hidden:
                continue

            rows.append(
@@ -291,7 +353,9 @@ class NoticeRegistry:
                    "first_seen": row.first_seen,
                    "last_seen": row.last_seen,
                    "count": row.count,
-                    "dismissed_at": row.dismissed_at,
+                    "acknowledgeable": definition.counts_repeats,
+                    "acknowledged_at": row.acknowledged_at,
+                    "muted_at": row.muted_at,
                }
            )

@@ -309,11 +373,13 @@ class NoticeRegistry:
            {
                "kind": row.kind,
                "occurrences": row.occurrences,
-                "dismissals": row.dismissals,
+                "acknowledgements": row.acknowledgements,
+                "mutes": row.mutes,
                "first_seen": row.first_seen,
                "last_seen": row.last_seen,
                "reported_occurrences": row.reported_occurrences,
-                "reported_dismissals": row.reported_dismissals,
+                "reported_acknowledgements": row.reported_acknowledgements,
+                "reported_mutes": row.reported_mutes,
            }
            for row in NoticeStats.select()
            if row.kind in NOTICE_KINDS
@@ -327,18 +393,18 @@ class NoticeRegistry:
        last_seen: float,
        params: dict[str, Any],
    ) -> None:
-        # called with the lock held
-        fields: dict[str, Any] = {
-            "count": row.count + count,
-            "last_seen": last_seen,
-            "params": params,
-        }
-        reopen_at = NOTICE_KINDS[kind].reopen_at_count
+        # called with the lock held; held repeats from before an acknowledgement
+        # still count but leave the notice hidden
+        still_acknowledged = row.acknowledged_at is not None and (
+            last_seen <= cast(float, row.acknowledged_at)
+        )

-        if reopen_at is not None and row.count < reopen_at <= row.count + count:
-            fields["dismissed_at"] = None
-
-        Notice.update(**fields).where(Notice.id == row.id).execute()
+        Notice.update(
+            count=row.count + count,
+            last_seen=last_seen,
+            params=params,
+            acknowledged_at=row.acknowledged_at if still_acknowledged else None,
+        ).where(Notice.id == row.id).execute()
        self._bump_occurrences(kind, count, last_seen)

    def _prune(self, kind: str, keep: int) -> None:
@@ -362,7 +428,8 @@ class NoticeRegistry:
            NoticeStats.create(
                kind=kind,
                occurrences=count,
-                dismissals=0,
+                acknowledgements=0,
+                mutes=0,
                first_seen=now,
                last_seen=now,
            )
@@ -28,9 +28,9 @@ class NoticeKind:
        category: camera, detector, model, or system; a camera scope is a
            camera name, and the UI shows it
        link: app route or absolute URL for the row, filled in from params
-        counts_repeats: whether raising an existing notice counts another occurrence
+        counts_repeats: whether raising an existing notice counts another
+            occurrence, which also shows an acknowledged notice again
        batch_repeats: whether repeats wait in memory for the next flush
-        reopen_at_count: count at which a dismissed notice shows again
        keep_latest: rows of this kind to keep; a new row drops the oldest
        reportable: whether a future analytics reporter may send this kind's counts
    """
@@ -41,7 +41,6 @@ class NoticeKind:
    link: str | None = None
    counts_repeats: bool = True
    batch_repeats: bool = False
-    reopen_at_count: int | None = None
    keep_latest: int | None = None
    reportable: bool = True

@@ -67,6 +66,12 @@ _KINDS = (
        "camera",
        link="/system#cameras",
    ),
+    NoticeKind(
+        "ffmpeg_high_cpu", NoticeSeverity.warning, "camera", link="/system#cameras"
+    ),
+    NoticeKind(
+        "detect_high_cpu", NoticeSeverity.warning, "camera", link="/system#cameras"
+    ),
    NoticeKind("shm_too_low", NoticeSeverity.warning, "system", link="/system#storage"),
    # one row per user per burst; the login log lines carry the address
    NoticeKind(
@@ -75,10 +80,9 @@ _KINDS = (
        "system",
        link="/logs",
        batch_repeats=True,
-        reopen_at_count=5,
        keep_latest=100,
    ),
-    # one row per release, so a dismissal lasts until the next release
+    # one row per release, so muting it lasts until the next release
    NoticeKind(
        "update_available",
        NoticeSeverity.info,
@@ -92,7 +96,7 @@ _KINDS = (
 NOTICE_KINDS: dict[str, NoticeKind] = {kind.key: kind for kind in _KINDS}

 # the Health tab builds config and stream check rows in the browser, so a notice
-# row of these kinds only records a dismissal; its other fields are placeholders
+# row of these kinds only records a mute; its other fields are placeholders
 CHECK_KINDS = frozenset({"config", "stream"})


@@ -42,6 +42,8 @@ from frigate.util.ownership import chown_to_runtime
 from frigate.util.recording_coverage import (
    build_spans,
    known_video_codecs,
+    null_audio_glitches,
+    realized_timeline,
    resolve_coverage,
    stream_media_summary,
 )
@@ -84,10 +86,20 @@ class StreamRun:

@dataclass
 class _ChapterWindow:
-    """A merged-timeline slice, shaped like the recording rows chapters read."""
+    """A merged-timeline slice, shaped like the recording rows chapters read.
+
+    lead_in is the output time the slice's vod clip plays before start_time,
+    from snapping its first frame back to a keyframe.
+    """

    start_time: float
    end_time: float
+    lead_in: float = 0.0
+
+
+def _lead_in(recording: Any) -> float:
+    """Output seconds a chapter source plays before its first wall second."""
+    return recording.lead_in if isinstance(recording, _ChapterWindow) else 0.0


 # Matches the setpts factor used in timelapse exports (e.g. setpts=0.04*PTS).
@@ -376,15 +388,18 @@ class RecordingExporter(threading.Thread):
    def _resolve_coverage(self) -> tuple[list[list[Any]], set[str], bool]:
        """Resolve the export range into the spans the VOD manifest will serve.

-        Delegates to the same coverage resolution the manifest builder
-        uses, so what we plan around and what nginx-vod emits agree by
-        construction. Returns the spans (each [row, start, end, is_main]),
-        the known video codecs, and whether audio survives the range.
+        Delegates to the same coverage resolution and glitch nulling the
+        manifest builder uses, so what we plan around and what nginx-vod
+        emits agree by construction. Returns the spans (each [row, start,
+        end, is_main]), the known video codecs, and whether audio survives
+        the range.
        Memoized: several stages of the export ask the same question, and
        the recordings backing a finished range do not change under us.
        """
        if self._coverage is None:
-            intervals = resolve_coverage(self.camera, self.start_time, self.end_time)
+            intervals = null_audio_glitches(
+                resolve_coverage(self.camera, self.start_time, self.end_time)
+            )
            self._coverage = (
                build_spans(intervals, self.pinned_stream),
                known_video_codecs(intervals),
@@ -433,17 +448,57 @@ class RecordingExporter(threading.Thread):
            # hand-off to stage around
            return True

-        spans, codecs, keep_audio = self._resolve_coverage()
-        runs = self._stream_runs(spans)
+        _spans, codecs, keep_audio = self._resolve_coverage()
+        runs = self._planned_stream_runs()

        # a range one stream covers end to end has nothing to hand off,
        # so it stays on the existing path however long it is
        if len(runs) < 2:
            return True

-        runs = [piece for run in runs for piece in self._split_long_run(run)]
        return self._stage_stream_runs(runs, codecs, keep_audio)

+    def _planned_stream_runs(self) -> list[StreamRun]:
+        """The runs a mixed range is staged as, one pinned vod playlist each."""
+        runs = self._stream_runs(self._merged_spans())
+
+        if len(runs) < 2:
+            return runs
+
+        return [piece for run in runs for piece in self._split_long_run(run)]
+
+    def _staged_chapter_windows(self) -> list[_ChapterWindow]:
+        """Chapter windows for the staged files as they were rendered.
+
+        Each staged run comes from its own pinned vod playlist, whose first
+        clip snaps back to the preceding keyframe, so a staged file runs up
+        to a GOP longer than its slice of the merged timeline. Planning each
+        run the way its playlist does carries that lead-in into the chapter
+        offsets instead of letting it accumulate at every hand-off.
+        """
+        windows: list[_ChapterWindow] = []
+
+        for run in self._planned_stream_runs():
+            intervals = null_audio_glitches(
+                resolve_coverage(self.camera, run.start_time, run.end_time)
+            )
+
+            for clip in realized_timeline(intervals, run.stream_type):
+                # a skipped clip is absent from the playlist and the file
+                if clip["duration"] <= 0:
+                    continue
+
+                span = clip["end_time"] - clip["start_time"]
+                windows.append(
+                    _ChapterWindow(
+                        clip["start_time"],
+                        clip["end_time"],
+                        max(0.0, clip["duration"] / 1000 - span),
+                    )
+                )
+
+        return windows
+
    def _stream_runs(self, spans: list[list[Any]]) -> list[StreamRun]:
        """Collapse the merged spans into contiguous runs of one stream type.

@@ -840,6 +895,8 @@ class RecordingExporter(threading.Thread):
            clipped_end = min(float(rec.end_time), float(self.end_time))
            if clipped_end <= clipped_start:
                continue
+            # a staged window's keyframe lead-in plays before it
+            output_offset += _lead_in(rec)
            windows.append((clipped_start, clipped_end, output_offset))
            output_offset += clipped_end - clipped_start

@@ -987,9 +1044,13 @@ class RecordingExporter(threading.Thread):
            if duration_ms <= 0:
                continue

-            title = datetime.datetime.fromtimestamp(clipped_start, tz=tz).isoformat(
-                timespec="seconds"
-            )
+            # a staged window's keyframe lead-in opens its chapter, with
+            # frames captured that long before the window
+            lead_in = _lead_in(rec)
+            duration_ms += int(round(lead_in * 1000))
+            title = datetime.datetime.fromtimestamp(
+                clipped_start - lead_in, tz=tz
+            ).isoformat(timespec="seconds")
            chapter_blocks.append(
                "[CHAPTER]\n"
                "TIMEBASE=1/1000\n"
@@ -1128,12 +1189,12 @@ class RecordingExporter(threading.Thread):
        if self.staged_runs:
            # each run was already rendered to a temp file with a common
            # track timescale, so the concat demuxer has nothing left to
-            # reconcile and every chapter offset lines up with the merged
-            # timeline the staged files reproduce
-            recordings = [
-                _ChapterWindow(span_start, span_end)
-                for _row, span_start, span_end, _is_main in self._merged_spans()
-            ]
+            # reconcile
+            recordings = (
+                self._staged_chapter_windows()
+                if self.chapters not in (None, ChaptersEnum.none)
+                else []
+            )
            playlist_lines: list[str] = [f"file '{path}'" for path in self.staged_runs]
            ffmpeg_input = (
                "-y -protocol_whitelist pipe,file -f concat -safe 0 -i /dev/stdin"
@@ -1149,11 +1210,18 @@ class RecordingExporter(threading.Thread):
            # its own rows are the ones the chapters describe
            recordings = self._get_recordings_for_range(pin)
        else:
-            # never mix streams in one playlist; use main when available
-            # and fall back to sub for expired-main history
-            recordings = self._get_recordings_for_range(STREAM_TYPE_MAIN)
+            # an unstaged auto range resolves to at most one stream run, and
+            # its rows are the ones the chapters describe. Main rows the
+            # manifest drops (glitches, slivers at the edges of a sub range)
+            # must not stand in for it.
+            runs = self._stream_runs(self._merged_spans())
+            recordings = self._get_recordings_for_range(
+                runs[0].stream_type if runs else STREAM_TYPE_MAIN
+            )

-            if not recordings:
+            # never mix streams in one playlist; fall back to sub for
+            # expired-main history
+            if not recordings and not runs:
                recordings = self._get_recordings_for_range(STREAM_TYPE_SUB)

        playlist_lines = []
@@ -490,9 +490,17 @@ class RecordingMaintainer(threading.Thread):
                )
            reviews = reviews_by_camera[camera]

-            tasks.extend(
-                [self.validate_and_move_segment(camera, reviews, r) for r in recordings]
-            )
+            # probes run concurrently, but each segment's start chains off the
+            # previous segment's end, so starts resolve in segment order
+            previous: asyncio.Event | None = None
+            for recording in recordings:
+                resolved = asyncio.Event()
+                tasks.append(
+                    self._validate_in_order(
+                        camera, reviews, recording, previous, resolved
+                    )
+                )
+                previous = resolved

            # publish most recently available recording time and None if disabled
            if stream_type == STREAM_TYPE_MAIN:
@@ -550,12 +558,33 @@ class RecordingMaintainer(threading.Thread):
                while info and info[0][0] < expire_before:
                    info.pop(0)

+    async def _validate_in_order(
+        self,
+        camera: str,
+        reviews: Any,
+        recording: dict[str, Any],
+        previous_start: asyncio.Event | None,
+        start_resolved: asyncio.Event,
+    ) -> dict[str, Any] | None:
+        """Validate a segment, always releasing the next one in its stream."""
+        try:
+            return await self.validate_and_move_segment(
+                camera, reviews, recording, previous_start, start_resolved
+            )
+        finally:
+            start_resolved.set()
+
    def drop_segment(self, cache_path: str) -> None:
        Path(cache_path).unlink(missing_ok=True)
        self.end_time_cache.pop(cache_path, None)

    async def validate_and_move_segment(
-        self, camera: str, reviews: Any, recording: dict[str, Any]
+        self,
+        camera: str,
+        reviews: Any,
+        recording: dict[str, Any],
+        previous_start: asyncio.Event | None = None,
+        start_resolved: asyncio.Event | None = None,
    ) -> dict[str, Any] | None:
        cache_path: str = recording["cache_path"]
        start_time: datetime.datetime = recording["start_time"]
@@ -617,6 +646,9 @@ class RecordingMaintainer(threading.Thread):
                async with self.probe_semaphore:
                    keyframes = await get_keyframe_offsets(cache_path)

+                if previous_start is not None:
+                    await previous_start.wait()
+
                start_time = self._resolve_segment_start(
                    camera, stream_type, start_time, duration, cache_path
                )
@@ -654,6 +686,11 @@ class RecordingMaintainer(threading.Thread):
                RecordingsDataTypeEnum.valid.value,
            )

+        # the start is settled, so the next segment of the stream can chain
+        # off it while this one waits on retention and the move
+        if start_resolved is not None:
+            start_resolved.set()
+
        record_config = self.config.cameras[camera].record

        # sub's alerts/detections carry the retain mode directly, unlike
@@ -1090,6 +1127,7 @@ class RecordingMaintainer(threading.Thread):
                elif (
                    topic == DetectionTypeEnum.api.value
                    or topic == DetectionTypeEnum.lpr.value
+                    or topic == DetectionTypeEnum.classification_state.value
                ):
                    continue

@@ -40,6 +40,10 @@ logger = logging.getLogger(__name__)
 THUMB_HEIGHT = 180
 THUMB_WIDTH = 320

+# seconds before a review item starts that a state classification change is
+# still attached to it, e.g. a garage door opening before the car is visible
+CLASSIFICATION_STATE_PRE_ROLL = 5
+

 class PendingReviewSegment:
    def __init__(
@@ -61,6 +65,7 @@ class PendingReviewSegment:
        self.sub_labels = sub_labels
        self.zones = zones
        self.audio = audio
+        self.classification_state_changes: list[dict[str, Any]] = []
        self.thumb_time: float | None = None
        self.last_alert_time: float | None = None
        self.last_detection_time: float = frame_time
@@ -162,6 +167,7 @@ class PendingReviewSegment:
                    "sub_labels": list(self.sub_labels.values()),
                    "zones": self.zones,
                    "audio": list(self.audio),
+                    "classification_state_changes": self.classification_state_changes,
                    "thumb_time": self.thumb_time,
                    "metadata": None,
                },
@@ -293,6 +299,9 @@ class ReviewSegmentMaintainer(threading.Thread):
        # manual events
        self.indefinite_events: dict[str, dict[str, Any]] = {}

+        # state classification changes seen while a camera had no review item
+        self.recent_classification_state_changes: dict[str, list[dict[str, Any]]] = {}
+
        # ensure dirs
        Path(os.path.join(CLIPS_DIR, "review")).mkdir(exist_ok=True)

@@ -374,6 +383,43 @@ class ReviewSegmentMaintainer(threading.Thread):
        self.active_review_segments[segment.camera] = None
        return end_time

+    def _activate_segment(self, segment: PendingReviewSegment) -> None:
+        """Make a segment the camera's active one, attaching any state
+        classification changes seen just before it started."""
+        self.active_review_segments[segment.camera] = segment
+        recent = self.recent_classification_state_changes.pop(segment.camera, [])
+        segment.classification_state_changes.extend(
+            c
+            for c in recent
+            if c["timestamp"] >= segment.start_time - CLASSIFICATION_STATE_PRE_ROLL
+        )
+
+    def handle_classification_state_change(
+        self, camera: str, change: dict[str, Any]
+    ) -> None:
+        """Attach a verified state classification change to the active segment.
+
+        State changes never start, extend, or upgrade a segment. A change seen
+        with no active segment is held briefly for a segment starting right
+        after it.
+        """
+        segment = self.active_review_segments.get(camera)
+
+        if segment is None:
+            cutoff = change["timestamp"] - CLASSIFICATION_STATE_PRE_ROLL
+            self.recent_classification_state_changes[camera] = [
+                c
+                for c in self.recent_classification_state_changes.get(camera, [])
+                if c["timestamp"] >= cutoff
+            ] + [change]
+            return
+
+        prev_data = segment.get_data(False)
+        segment.classification_state_changes.append(change)
+        self._publish_segment_update(
+            segment, self.config.cameras[camera], None, [], prev_data
+        )
+
    def forcibly_end_segment(self, camera: str) -> Any:
        """Forcibly end the pending segment for a camera."""
        segment = self.active_review_segments.get(camera)
@@ -422,6 +468,7 @@ class ReviewSegmentMaintainer(threading.Thread):
        """Close out a deleted camera's segment so a reused name cannot inherit it."""
        self.forcibly_end_segment(camera)
        self.indefinite_events.pop(camera, None)
+        self.recent_classification_state_changes.pop(camera, None)

    def update_existing_segment(
        self,
@@ -579,7 +626,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                            audio=set(),
                            zones=list(new_zones),
                        )
-                        self.active_review_segments[segment.camera] = new_segment
+                        self._activate_segment(new_segment)
                        self._publish_segment_start(new_segment)
                        new_segment.last_detection_time = last_detection_time
            elif segment.severity == SeverityEnum.detection and frame_time > (
@@ -639,7 +686,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                    audio=set(),
                    zones=zones,
                )
-                self.active_review_segments[camera] = new_segment
+                self._activate_segment(new_segment)

                try:
                    yuv_frame = self.frame_manager.get(
@@ -713,6 +760,10 @@ class ReviewSegmentMaintainer(threading.Thread):

                if camera not in self.indefinite_events:
                    self.indefinite_events[camera] = {}
+            elif topic == DetectionTypeEnum.classification_state.value:
+                (camera, classification_change) = data
+            else:
+                continue

            if camera not in self.config.cameras:
                continue
@@ -723,6 +774,10 @@ class ReviewSegmentMaintainer(threading.Thread):
            ):
                continue

+            if topic == DetectionTypeEnum.classification_state:
+                self.handle_classification_state_change(camera, classification_change)
+                continue
+
            current_segment = self.active_review_segments.get(camera)

            # Check if the current segment should be processed based on enabled settings
@@ -864,14 +919,16 @@ class ReviewSegmentMaintainer(threading.Thread):
                                severity = SeverityEnum.detection

                    if severity:
-                        self.active_review_segments[camera] = PendingReviewSegment(
-                            camera,
-                            frame_time,
-                            severity,
-                            {},
-                            {},
-                            [],
-                            detections,
+                        self._activate_segment(
+                            PendingReviewSegment(
+                                camera,
+                                frame_time,
+                                severity,
+                                {},
+                                {},
+                                [],
+                                detections,
+                            )
                        )
                elif topic == DetectionTypeEnum.api:
                    severity = self.get_manual_event_severity(
@@ -888,7 +945,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                            [],
                            set(),
                        )
-                        self.active_review_segments[camera] = api_segment
+                        self._activate_segment(api_segment)

                        if manual_info["state"] == ManualEventState.start:
                            self.indefinite_events[camera][manual_info["event_id"]] = (
@@ -915,7 +972,7 @@ class ReviewSegmentMaintainer(threading.Thread):
                            [],
                            set(),
                        )
-                        self.active_review_segments[camera] = lpr_segment
+                        self._activate_segment(lpr_segment)

                        if manual_info["state"] == ManualEventState.start:
                            self.indefinite_events[camera][manual_info["event_id"]] = (
@@ -29,38 +29,59 @@ VERSION_REFRESH_S = 24 * 60 * 60
 # a camera skipping at least this percent of its frames is falling behind
 SKIPPED_DETECTIONS_PCT = 5

-# for at least this long before it becomes a notice
-SKIPPED_DETECTIONS_HOLD_S = 60
+# lifetime CPU averages at or above these are high; they match
+# CameraFfmpegThreshold.error and CameraDetectThreshold.error in the UI
+FFMPEG_HIGH_CPU_PCT = 20
+DETECT_HIGH_CPU_PCT = 40
+
+# a camera stays over a threshold this long before it becomes a notice
+EPISODE_HOLD_S = 60

 # detectors warm up after a start; the status bar waits this long too
 STARTUP_GRACE_S = 120


-class SkippedDetectionsTracker:
-    """Finds cameras whose skipped share stays high long enough for a notice."""
+def cpu_average(cpu_usages: dict[str, Any], pid: int | None) -> float | None:
+    """A process's CPU use averaged over its lifetime, or None if unknown."""
+    usage = cpu_usages.get(str(pid)) if pid else None

-    def __init__(self) -> None:
+    try:
+        return float(usage["cpu_average"]) if usage else None
+    except (KeyError, TypeError, ValueError):
+        return None
+
+
+class EpisodeTracker:
+    """Finds cameras whose value stays over a threshold long enough for a notice."""
+
+    def __init__(self, threshold: float) -> None:
+        self._threshold = threshold
        self._since: dict[str, float] = {}
        self._raised: set[str] = set()

-    def update(self, cameras: dict[str, dict[str, Any]], now: float) -> list[str]:
-        """Return the cameras whose episode qualified on this sample."""
+    def update(self, values: dict[str, float | None], now: float) -> list[str]:
+        """Return the cameras whose episode qualified on this sample.
+
+        Args:
+            values: Each camera's current value, or None when it has none
+            now: Sample time in seconds
+        """
        qualified: list[str] = []

        # a removed camera that comes back starts a new episode
-        for camera in self._since.keys() - cameras.keys():
+        for camera in self._since.keys() - values.keys():
            self._since.pop(camera)
            self._raised.discard(camera)

-        for camera, camera_stats in cameras.items():
-            if camera_stats["skipped_pct"] < SKIPPED_DETECTIONS_PCT:
+        for camera, value in values.items():
+            if value is None or value < self._threshold:
                self._since.pop(camera, None)
                self._raised.discard(camera)
                continue

            since = self._since.setdefault(camera, now)

-            if camera not in self._raised and now - since >= SKIPPED_DETECTIONS_HOLD_S:
+            if camera not in self._raised and now - since >= EPISODE_HOLD_S:
                self._raised.add(camera)
                qualified.append(camera)

@@ -80,7 +101,9 @@ class StatsEmitter(threading.Thread):
        self.stop_event = stop_event
        self.hardware_stats = HardwareStats(config)
        self.stats_history: list[dict[str, Any]] = []
-        self.skipped_detections = SkippedDetectionsTracker()
+        self.skipped_detections = EpisodeTracker(SKIPPED_DETECTIONS_PCT)
+        self.ffmpeg_cpu = EpisodeTracker(FFMPEG_HIGH_CPU_PCT)
+        self.detect_cpu = EpisodeTracker(DETECT_HIGH_CPU_PCT)

        # the shm notice's params as last sent, so only a change is written
        self._shm_checked = False
@@ -227,15 +250,38 @@ class StatsEmitter(threading.Thread):

    def _update_notices(self, stats: dict[str, Any], now: float) -> None:
        """Update notices based on current stats or time."""
-        # skipped detections
+        cameras = stats["cameras"]
+
+        # absent when CPU collection timed out or failed on this tick
+        cpu_usages = stats.get("cpu_usages", {})
+
        if stats["service"]["uptime"] >= STARTUP_GRACE_S:
-            for camera in self.skipped_detections.update(stats["cameras"], now):
+            # skipped detections
+            skipped = {
+                camera: camera_stats["skipped_pct"]
+                for camera, camera_stats in cameras.items()
+            }
+
+            for camera in self.skipped_detections.update(skipped, now):
                raise_notice(
                    "skipped_detections",
                    scope=camera,
-                    params={"pct": stats["cameras"][camera]["skipped_pct"]},
+                    params={"pct": skipped[camera]},
                )

+            # high ffmpeg and detect CPU
+            for tracker, kind, pid_key in (
+                (self.ffmpeg_cpu, "ffmpeg_high_cpu", "ffmpeg_pid"),
+                (self.detect_cpu, "detect_high_cpu", "pid"),
+            ):
+                averages = {
+                    camera: cpu_average(cpu_usages, camera_stats.get(pid_key))
+                    for camera, camera_stats in cameras.items()
+                }
+
+                for camera in tracker.update(averages, now):
+                    raise_notice(kind, scope=camera, params={"cpu": averages[camera]})
+
        # shm too small for the cameras
        self._update_shm_notice(stats["service"]["storage"]["/dev/shm"])

@@ -256,6 +256,17 @@ class HardwareStats:
        )
        self.update_config()

+    def set_config(self, config: FrigateConfig) -> None:
+        """Follow a runtime config swap and recalculate the monitored hardware.
+
+        The camera update subscriber has to follow too, or later camera updates
+        would land on the discarded config.
+        """
+        self.config = config
+        self._config_subscriber.config = config
+        self._config_subscriber.camera_configs = config.cameras
+        self.update_config()
+
    def update_config(self) -> None:
        """Recalculate all hardware that needs to be monitored from the config."""
        names = self._scan_ffmpeg() | self._scan_detectors() | self._scan_enrichments()
@@ -111,15 +111,18 @@ def get_detector_stats(
 ) -> dict[str, dict[str, Any]]:
    """Get stats for all detectors, including temperatures based on detector type."""
    detector_stats: dict[str, dict[str, Any]] = {}
-    detector_type_indices: dict[str, int] = {}
+    # detector type -> device -> index into that type's temperatures
+    device_indices: dict[str, dict[str, int]] = {}

    for name, detector in stats_tracking["detectors"].items():
        pid = detector.detect_process.pid if detector.detect_process else None
        detector_type = detector.detector_config.type

-        # Keep track of the index for each detector type to match temperatures correctly
-        current_index = detector_type_indices.get(detector_type, 0)
-        detector_type_indices[detector_type] = current_index + 1
+        # temperatures are per physical unit, so a repeated device
+        # ("hailo:PCIe#2", see runner_names) shares its unit's reading
+        device = name.partition("#")[0]
+        type_devices = device_indices.setdefault(detector_type, {})
+        current_index = type_devices.setdefault(device, len(type_devices))

        detector_stat = {
            "inference_speed": round(detector.avg_inference_speed.value * 1000, 2),  # type: ignore[attr-defined]
@@ -1,8 +1,10 @@
+import json
+import os
 from unittest.mock import Mock, patch

 import frigate.genai
 from frigate.config import GenAIProviderEnum
-from frigate.const import REDACTED_CREDENTIAL_SENTINEL
+from frigate.const import MODEL_CACHE_DIR, REDACTED_CREDENTIAL_SENTINEL
 from frigate.genai import GenAIClient
 from frigate.models import Event, Recordings, ReviewSegment
 from frigate.stats.emitter import StatsEmitter
@@ -90,6 +92,44 @@ class TestHttpApp(BaseTestHttp):
            mqtt = response.json()["mqtt"]
            assert mqtt["password"] == REDACTED_CREDENTIAL_SENTINEL

+    def test_config_response_keeps_plus_model_reference(self):
+        model_id = "test_plus_reference"
+        model_path = os.path.join(MODEL_CACHE_DIR, model_id)
+        os.makedirs(MODEL_CACHE_DIR, exist_ok=True)
+
+        with open(model_path, "w") as f:
+            f.write("model")
+
+        with open(f"{model_path}.json", "w") as f:
+            json.dump(
+                {
+                    "id": model_id,
+                    "type": "ssd",
+                    "supportedDetectors": ["cpu"],
+                    "width": 320,
+                    "height": 320,
+                    "inputShape": "nhwc",
+                    "pixelFormat": "rgb",
+                    "labelMap": {"0": "person"},
+                },
+                f,
+            )
+
+        self.addCleanup(os.remove, model_path)
+        self.addCleanup(os.remove, f"{model_path}.json")
+        self.minimal_config["models"] = [
+            {"path": f"plus://{model_id}", "devices": ["cpu"]}
+        ]
+        app = super().create_app()
+
+        with AuthTestClient(app) as client:
+            response = client.get("/config")
+            assert response.status_code == 200
+            assert response.json()["models"][0]["path"] == f"plus://{model_id}"
+
+        # detection still loads the resolved cache file
+        assert app.frigate_config.models[0].path == model_path
+
    ####################################################################################################################
    ###################################  POST /genai/probe Endpoint   ##################################################
    ####################################################################################################################
@@ -53,92 +53,108 @@ class TestHttpNotices(BaseTestHttp):
        self.assertEqual(response.json()[0]["kind"], "detector_stuck")
        self.assertEqual(response.json()[0]["occurrences"], 1)

-    def test_dismiss_hides_and_history_keeps_it(self):
+    def test_acknowledge_hides_and_the_hidden_list_keeps_it(self):
        self.registry.raise_notice(
            "detector_stuck", scope="ov", params={"detector": "ov"}
        )

        with self.client() as client:
-            response = client.post("/notices/detector_stuck:ov/dismiss")
+            response = client.post("/notices/detector_stuck:ov/acknowledge")
            listed = client.get("/notices").json()
-            history = client.get("/notices", params={"include_dismissed": True}).json()
+            hidden = client.get("/notices", params={"include_hidden": True}).json()

        self.assertEqual(response.status_code, 200)
        self.assertEqual(listed, [])
-        self.assertEqual([n["id"] for n in history], ["detector_stuck:ov"])
-        self.assertIsNotNone(history[0]["dismissed_at"])
+        self.assertEqual([n["id"] for n in hidden], ["detector_stuck:ov"])
+        self.assertIsNotNone(hidden[0]["acknowledged_at"])

-    def test_dismiss_an_id_with_a_slash(self):
+    def test_acknowledging_a_check_is_404(self):
+        with self.client() as client:
+            response = client.post(f"/notices/{CONFIG_CHECK}/acknowledge")
+
+        self.assertEqual(response.status_code, 404)
+
+    def test_mute_an_id_with_a_slash(self):
        self.registry.raise_notice(
            "model_download_failed", scope="yolo/model.onnx", params={}
        )

        with self.client() as client:
            response = client.post(
-                "/notices/model_download_failed:yolo/model.onnx/dismiss"
+                "/notices/model_download_failed:yolo/model.onnx/mute"
            )

        self.assertEqual(response.status_code, 200)
        self.assertEqual(self.registry.active(), [])

-    def test_dismiss_unknown_is_404(self):
+    def test_unknown_ids_are_404(self):
        with self.client() as client:
-            response = client.post("/notices/nope/dismiss")
+            responses = [
+                client.post("/notices/nope/acknowledge"),
+                client.post("/notices/nope/mute"),
+                client.delete("/notices/nope/hidden"),
+            ]

-        self.assertEqual(response.status_code, 404)
+        self.assertEqual([r.status_code for r in responses], [404, 404, 404])

    def test_requires_admin(self):
+        viewer = {"remote-user": "viewer", "remote-role": "viewer"}
+
        with TestClient(self.app) as client:
-            response = client.get(
-                "/notices", headers={"remote-user": "viewer", "remote-role": "viewer"}
-            )
+            responses = [
+                client.get("/notices", headers=viewer),
+                client.get("/notices/muted_checks", headers=viewer),
+                client.post("/notices/detector_stuck:ov/acknowledge", headers=viewer),
+                client.post("/notices/detector_stuck:ov/mute", headers=viewer),
+                client.delete("/notices/detector_stuck:ov/hidden", headers=viewer),
+                client.delete("/notices/hidden", headers=viewer),
+            ]

-        self.assertEqual(response.status_code, 403)
+        self.assertEqual([r.status_code for r in responses], [403] * 6)

-    def test_dismissed_checks_are_listed_once(self):
+    def test_muted_checks_are_listed_once(self):
        with self.client() as client:
-            first = client.post(f"/notices/{CONFIG_CHECK}/dismiss")
-            again = client.post(f"/notices/{CONFIG_CHECK}/dismiss")
-            listed = client.get("/notices/dismissed_checks").json()
-            history = client.get("/notices", params={"include_dismissed": True}).json()
+            first = client.post(f"/notices/{CONFIG_CHECK}/mute")
+            again = client.post(f"/notices/{CONFIG_CHECK}/mute")
+            listed = client.get("/notices/muted_checks").json()
+            hidden = client.get("/notices", params={"include_hidden": True}).json()

        self.assertEqual(first.status_code, 200)
        self.assertEqual(again.status_code, 200)
        self.assertEqual([check["id"] for check in listed], [CONFIG_CHECK])
-        self.assertIsNotNone(listed[0]["dismissed_at"])
+        self.assertIsNotNone(listed[0]["muted_at"])
        # the Health tab builds the row itself, so it never comes back as a notice
-        self.assertEqual(history, [])
+        self.assertEqual(hidden, [])

-    def test_dismissed_checks_require_admin(self):
-        with TestClient(self.app) as client:
-            response = client.get(
-                "/notices/dismissed_checks",
-                headers={"remote-user": "viewer", "remote-role": "viewer"},
-            )
-
-        self.assertEqual(response.status_code, 403)
-
-    def test_purge_dismissed_clears_notices_and_checks(self):
+    def test_unhide_one_row(self):
        self.registry.raise_notice(
            "detector_stuck", scope="ov", params={"detector": "ov"}
        )
-        self.registry.dismiss("detector_stuck:ov")
-        self.registry.dismiss(CONFIG_CHECK)
+        self.registry.mute("detector_stuck:ov")
+        self.registry.mute(CONFIG_CHECK)

        with self.client() as client:
-            response = client.delete("/notices/dismissed")
-            history = client.get("/notices", params={"include_dismissed": True}).json()
-            checks = client.get("/notices/dismissed_checks").json()
+            notice = client.delete("/notices/detector_stuck:ov/hidden")
+            check = client.delete(f"/notices/{CONFIG_CHECK}/hidden")
+            listed = client.get("/notices").json()
+            checks = client.get("/notices/muted_checks").json()

-        self.assertEqual(response.status_code, 200)
-        self.assertEqual(history, [])
+        self.assertEqual([notice.status_code, check.status_code], [200, 200])
+        self.assertEqual([n["id"] for n in listed], ["detector_stuck:ov"])
        self.assertEqual(checks, [])

-    def test_purge_dismissed_requires_admin(self):
-        with TestClient(self.app) as client:
-            response = client.delete(
-                "/notices/dismissed",
-                headers={"remote-user": "viewer", "remote-role": "viewer"},
-            )
+    def test_unhide_all_shows_notices_and_drops_check_mutes(self):
+        self.registry.raise_notice(
+            "detector_stuck", scope="ov", params={"detector": "ov"}
+        )
+        self.registry.acknowledge("detector_stuck:ov")
+        self.registry.mute(CONFIG_CHECK)

-        self.assertEqual(response.status_code, 403)
+        with self.client() as client:
+            response = client.delete("/notices/hidden")
+            listed = client.get("/notices").json()
+            checks = client.get("/notices/muted_checks").json()
+
+        self.assertEqual(response.status_code, 200)
+        self.assertEqual([n["id"] for n in listed], ["detector_stuck:ov"])
+        self.assertEqual(checks, [])
@@ -0,0 +1,90 @@
+"""Tests for audio maintainer spawning on runtime camera adds."""
+
+import threading
+import unittest
+from unittest.mock import MagicMock, patch
+
+from frigate.config import FrigateConfig
+from frigate.events.audio import AudioProcessor
+
+
+def _build_config() -> FrigateConfig:
+    return FrigateConfig(
+        **{
+            "mqtt": {"host": "mqtt"},
+            "cameras": {
+                "front_door": {
+                    "ffmpeg": {
+                        "inputs": [
+                            {
+                                "path": "rtsp://10.0.0.1:554/video",
+                                "roles": ["detect", "audio"],
+                            }
+                        ]
+                    },
+                    "audio": {"enabled": True},
+                }
+            },
+        }
+    )
+
+
+class TestAudioSpawnIfNeeded(unittest.TestCase):
+    def _processor(self, config: FrigateConfig, camera_metrics: dict) -> AudioProcessor:
+        processor = AudioProcessor.__new__(AudioProcessor)
+        processor.config = config
+        processor.camera_metrics = camera_metrics
+        processor.embeddings_metrics = MagicMock()
+        processor.audio_threads = {}
+        processor.transcription_model_runner = None
+        processor.genai_manager = None
+        processor.stop_event = threading.Event()
+        processor.logger = MagicMock()
+        return processor
+
+    def test_skips_camera_whose_metrics_have_not_been_created_yet(self):
+        """The camera maintainer creates metrics on its own poll of the add
+        update, so the audio processor can see the camera first."""
+        config = _build_config()
+        processor = self._processor(config, {})
+
+        with patch("frigate.events.audio.AudioEventMaintainer") as maintainer:
+            processor.spawn_if_needed(config.cameras["front_door"])
+
+        maintainer.assert_not_called()
+        assert processor.audio_threads == {}
+
+    def test_spawns_once_metrics_exist_and_passes_the_metrics_object(self):
+        config = _build_config()
+        metrics = object()
+        processor = self._processor(config, {"front_door": metrics})
+
+        with patch("frigate.events.audio.AudioEventMaintainer") as maintainer:
+            processor.spawn_if_needed(config.cameras["front_door"])
+
+        assert maintainer.call_args.args[2] is metrics
+        assert "front_door" in processor.audio_threads
+        maintainer.return_value.start.assert_called_once()
+
+    def test_does_not_respawn_for_a_camera_already_running(self):
+        config = _build_config()
+        processor = self._processor(config, {"front_door": object()})
+        processor.audio_threads["front_door"] = MagicMock()
+
+        with patch("frigate.events.audio.AudioEventMaintainer") as maintainer:
+            processor.spawn_if_needed(config.cameras["front_door"])
+
+        maintainer.assert_not_called()
+
+    def test_skips_camera_whose_ffmpeg_update_has_not_arrived_yet(self):
+        """The add update carries the camera before its ffmpeg inputs are
+        applied, so the audio role can be briefly missing."""
+        config = _build_config()
+        camera = config.cameras["front_door"]
+        camera.ffmpeg.inputs[0].roles = ["detect"]
+        processor = self._processor(config, {"front_door": object()})
+
+        with patch("frigate.events.audio.AudioEventMaintainer") as maintainer:
+            processor.spawn_if_needed(camera)
+
+        maintainer.assert_not_called()
@@ -36,6 +36,31 @@ class TestEventsPerSecond(unittest.TestCase):
            clock[0] += 100.0
            self.assertEqual(eps.eps(), 0.0)

+    def test_burst_after_start_is_not_divided_by_a_tiny_window(self) -> None:
+        eps = EventsPerSecond(last_n_seconds=10)
+        clock = [1000.0]
+        with patch("frigate.util.builtin.time.monotonic", side_effect=lambda: clock[0]):
+            eps.start()
+            # eleven buffered frames arrive within 100 ms of starting
+            for _ in range(11):
+                clock[0] += 0.01
+                eps.update()
+            # 11 events over less than a second is at most 11 per second
+            self.assertLessEqual(eps.eps(), 11.0)
+
+    def test_subsecond_window_keeps_its_rate(self) -> None:
+        eps = EventsPerSecond(last_n_seconds=0.5)
+        clock = [1000.0]
+        with patch("frigate.util.builtin.time.monotonic", side_effect=lambda: clock[0]):
+            eps.start()
+            # twenty events per second for two seconds
+            for _ in range(40):
+                clock[0] += 0.05
+                eps.update()
+            # read between events, so none sits exactly on the window edge
+            clock[0] += 0.01
+            self.assertAlmostEqual(eps.eps(), 20.0)
+

 if __name__ == "__main__":
    unittest.main()
@@ -179,12 +179,16 @@ class TestReviewMaintainerRemoval(unittest.TestCase):
        maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
        maintainer.active_review_segments = {"deleted_cam": MagicMock()}
        maintainer.indefinite_events = {"deleted_cam": {"1234.5-abcdef": 1.0}}
+        maintainer.recent_classification_state_changes = {
+            "deleted_cam": [{"model": "gate", "from": "a", "to": "b", "timestamp": 1.0}]
+        }
        maintainer.forcibly_end_segment = MagicMock()

        maintainer._handle_camera_removed("deleted_cam")

        maintainer.forcibly_end_segment.assert_called_once_with("deleted_cam")
        self.assertNotIn("deleted_cam", maintainer.indefinite_events)
+        self.assertNotIn("deleted_cam", maintainer.recent_classification_state_changes)


 class TestAutotrackerMoveQueue(unittest.TestCase):
@@ -26,6 +26,7 @@ class TestSwapRuntimeConfig(unittest.TestCase):
        app.genai_manager.update_config.assert_called_once_with(config)
        app.profile_manager.update_config.assert_called_once_with(config)
        self.assertIs(app.stats_emitter.config, config)
+        app.stats_emitter.hardware_stats.set_config.assert_called_once_with(config)
        self.assertIs(app.dispatcher.config, config)
        for comm in app.dispatcher.comms:
            self.assertIs(comm.config, config)
@@ -0,0 +1,896 @@
+"""Tests for the DEEPX detector."""
+
+import json
+import os
+import struct
+import sys
+import tempfile
+import unittest
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+from pydantic import ValidationError
+
+from frigate.detectors.detector_config import ModelConfig, ModelTypeEnum
+from frigate.detectors.device import (
+    DeviceParseError,
+    build_detector_config,
+    parse_device,
+)
+from frigate.detectors.plugins.deepx import (
+    DEEPX_MANIFEST,
+    DXRT_VERSION,
+    PPU_RECORD_SIZE,
+    DeepxDetector,
+    DeepxDetectorConfig,
+    PpuLayout,
+    YoloLayout,
+    class_count,
+    decode_raw_anchor,
+    decode_raw_nms_in_head,
+    infer_yolo_layout,
+    read_ppu_layout,
+    resolve_device,
+    validate_yolox_outputs,
+)
+
+
+def model_with_type(model_type) -> ModelConfig:
+    return ModelConfig(
+        model_type=model_type,
+        labelmap_path=None,
+        labelmap={79: "toothbrush"},
+        width=640,
+        height=640,
+    )
+
+
+def build_ppu_record(box, score=0.9, label=0, grid=(7, 9, 2, 2)) -> np.ndarray:
+    record = np.zeros(PPU_RECORD_SIZE, dtype=np.uint8)
+    record[0:16] = np.array(box, dtype=np.float32).view(np.uint8)
+    record[16:20] = grid
+    record[20:24] = np.array([score], dtype=np.float32).view(np.uint8)
+    record[24:28] = np.array([label], dtype=np.uint32).view(np.uint8)
+    return record.reshape(1, 1, PPU_RECORD_SIZE)
+
+
+# compile_config.ppu as DX-COM writes it for the two head kinds
+ANCHOR_BASED_PPU = {"type": 0, "num_classes": 80, "activation": "Sigmoid"}
+ANCHOR_FREE_PPU = {"type": 1, "num_classes": 80}
+
+PPU_BBOX_NODE = "/head/Mul_2"
+
+# (grid_w, grid_h, entries) per scale, finest first; the grids give the
+# strides at a 640 input
+THREE_SCALE_ANCHORS = [(80, 80, 3), (40, 40, 3), (20, 20, 3)]
+TWO_SCALE_ANCHORS = [(40, 40, 3), (20, 20, 3)]
+FOUR_SCALE_ANCHORS = [(160, 160, 3), (80, 80, 3), (40, 40, 3), (20, 20, 3)]
+THREE_SCALE_FREE = [(80, 80, 1), (40, 40, 1), (20, 20, 1)]
+ONE_SCALE_FREE = [(100, 84, 1)]
+
+
+def proto_varint(value: int) -> bytes:
+    out = bytearray()
+    while True:
+        byte = value & 0x7F
+        value >>= 7
+        out.append(byte | (0x80 if value else 0))
+        if not value:
+            return bytes(out)
+
+
+def proto_bytes(field: int, payload: bytes) -> bytes:
+    return proto_varint(field << 3 | 2) + proto_varint(len(payload)) + payload
+
+
+def proto_number(field: int, value: int) -> bytes:
+    return proto_varint(field << 3) + proto_varint(value)
+
+
+def onnx_node(op_type: str, name: str, inputs: list, outputs: list) -> bytes:
+    body = b"".join(proto_bytes(1, tensor.encode()) for tensor in inputs)
+    body += b"".join(proto_bytes(2, tensor.encode()) for tensor in outputs)
+    return body + proto_bytes(3, name.encode()) + proto_bytes(4, op_type.encode())
+
+
+def onnx_box_graph(box_format: str) -> bytes:
+    if box_format == "broken":
+        return proto_varint(1 << 3 | 3)
+
+    unnamed = box_format == "unnamed"
+
+    def graph_node(op_type: str, name: str, inputs: list, outputs: list) -> bytes:
+        return onnx_node(op_type, "" if unnamed else name, inputs, outputs)
+
+    nodes = [
+        graph_node("Split", "dfl_split", ["dfl", "sizes"], ["lt", "rb"]),
+        graph_node("Sub", "corner_min", ["anchors", "lt"], ["x1y1"]),
+        graph_node("Add", "corner_max", ["rb", "anchors"], ["x2y2"]),
+    ]
+    if box_format in ("centre", "unnamed"):
+        nodes += [
+            graph_node("Add", "corner_sum", ["x1y1", "x2y2"], ["sum"]),
+            graph_node("Mul", "corner_mean", ["sum", "half"], ["cxy"]),
+            graph_node("Sub", "corner_span", ["x2y2", "x1y1"], ["wh"]),
+            graph_node("Concat", "box_concat", ["cxy", "wh"], ["box"]),
+        ]
+    elif box_format == "corner":
+        nodes.append(graph_node("Concat", "box_concat", ["x1y1", "x2y2"], ["box"]))
+    else:
+        nodes.append(graph_node("Concat", "box_concat", ["x1y1", "x1y1"], ["box"]))
+
+    box = "box"
+    if unnamed:
+        box = "box_flat"
+        nodes.append(graph_node("Reshape", "box_reshape", ["shape", "box"], [box]))
+
+    nodes.append(onnx_node("Mul", PPU_BBOX_NODE, [box, "strides"], ["bbox_out"]))
+    graph = b"".join(proto_bytes(1, node) for node in nodes)
+    graph += proto_bytes(5, b"weights")
+    return (
+        proto_number(1, 10)  # ir_version
+        + proto_bytes(2, b"onnx_frontend_compiler")  # producer_name
+        + proto_bytes(7, graph)
+    )
+
+
+def write_dxnn(
+    directory, ppu, layers, name="model.dxnn", table=True, box_format=None
+) -> str:
+    """A minimal .dxnn as DX-RT's parsers read it: the container header, a
+    compile_config carrying `ppu`, and either the PPU tensor table with one
+    entry per (layer, anchor) as a v8 file has, or with `table` False only
+    the rmap_info listing of the PPU output tensors, as a v7 file has.
+    `layers` is (grid_w, grid_h, entries) per scale, finest first; an
+    anchor-free scale has one entry, and grid_h 1 means a flattened
+    (1, cells, channels) tensor. `box_format`, "centre" or "corner", adds
+    the compiled graph that says how the head writes its boxes, along with
+    the compile_config layer naming the node the PPU reads them from."""
+    if box_format is not None and "layer" not in ppu:
+        ppu = dict(ppu, layer=[{"bbox": PPU_BBOX_NODE, "cls_conf": "/head/Sigmoid"}])
+
+    compile_config = json.dumps({"compile_version": "2.4.0", "ppu": ppu}).encode()
+    graph = onnx_box_graph(box_format) if box_format is not None else b""
+
+    if table:
+        part = bytearray(struct.pack("<BBBB", 1, sum(n for _, _, n in layers), 0, 0))
+        for conv, (grid_w, grid_h, entries) in enumerate(layers):
+            for anchor in range(entries):
+                part += struct.pack(
+                    "<HHfBBBBBBBB",
+                    128,
+                    80,
+                    0.001,
+                    conv,
+                    anchor,
+                    0,
+                    1,
+                    0,
+                    grid_w,
+                    grid_h,
+                    0,
+                )
+    else:
+        outputs = []
+        for conv, (grid_w, grid_h, entries) in enumerate(layers):
+            for anchor in range(entries):
+                name_ = f"PPU_Transpose_Output_{conv}"
+                if entries > 1:
+                    name_ += f"_anchor_{anchor}"
+                shape = [1, grid_w, 127] if grid_h == 1 else [1, grid_h, grid_w, 128]
+                outputs.append({"name": name_, "shape": shape, "layout": "PPU_YOLO"})
+        part = json.dumps({"inputs": [], "outputs": outputs}).encode()
+
+    data = {
+        "compile_config": {
+            "type": "str",
+            "offset": 0,
+            "size": len(compile_config),
+        },
+        "compiled_data": {
+            "M1A_4K": {
+                "npu_0": {
+                    "rmap": {"type": "bytes", "offset": 0, "size": 0},
+                    "ppu" if table else "rmap_info": {
+                        "type": "bytes" if table else "str",
+                        "offset": len(compile_config),
+                        "size": len(part),
+                    },
+                }
+            }
+        },
+    }
+    if graph:
+        data["vis_npu_models"] = {
+            "npu_0": {
+                "type": "bytes",
+                "offset": len(compile_config) + len(part),
+                "size": len(graph),
+            }
+        }
+
+    index = json.dumps(
+        {
+            "version": 8 if table else 7,
+            "signature": "DXNN",
+            "size": 8192,
+            "data": data,
+        }
+    ).encode()
+
+    path = os.path.join(directory, name)
+    with open(path, "wb") as model:
+        model.write(b"DXNN" + struct.pack("<I", 8))
+        model.write(index.ljust(8192 - 8, b"\0"))
+        model.write(compile_config + part + graph)
+
+    return path
+
+
+def layout_of(shapes, num_classes, ppu=False, dynamic_output=False) -> YoloLayout:
+    return infer_yolo_layout(shapes, num_classes, ppu, dynamic_output).layout
+
+
+class TestDeepxModelFile(unittest.TestCase):
+    def setUp(self):
+        self.tmp = tempfile.TemporaryDirectory()
+        self.addCleanup(self.tmp.cleanup)
+
+    def layout(self, ppu, layers, **kwargs) -> PpuLayout | None:
+        return read_ppu_layout(write_dxnn(self.tmp.name, ppu, layers, **kwargs))
+
+    def test_the_head_kind_and_one_grid_per_scale_are_read(self):
+        cases = {
+            "anchor-based: three anchors per scale collapse to one grid each": (
+                (ANCHOR_BASED_PPU, THREE_SCALE_ANCHORS, {}),
+                PpuLayout(anchor_based=True, grids=((80, 80), (40, 40), (20, 20))),
+            ),
+            "anchor-free, one scale flattened into a single tensor": (
+                (ANCHOR_FREE_PPU, ONE_SCALE_FREE, {"box_format": "centre"}),
+                PpuLayout(anchor_based=False, grids=((100, 84),), centre_boxes=True),
+            ),
+            "a head kind the compiler does not name still yields the scales": (
+                ({"type": 7}, [(80, 80, 3), (40, 40, 3)], {}),
+                PpuLayout(anchor_based=None, grids=((80, 80), (40, 40))),
+            ),
+            "no table: the per-anchor split says anchor-based": (
+                ({"num_classes": 80}, THREE_SCALE_ANCHORS, {"table": False}),
+                PpuLayout(anchor_based=True, grids=((80, 80), (40, 40), (20, 20))),
+            ),
+            "no table: compile_config places the scales ahead of the names": (
+                (
+                    {
+                        "type": 1,
+                        "outputs": {
+                            f"PPU_Transpose_Output_{i}": {"conv_idx": 2 - i}
+                            for i in range(3)
+                        },
+                    },
+                    [(20, 20, 1), (40, 40, 1), (80, 80, 1)],
+                    {"table": False},
+                ),
+                PpuLayout(anchor_based=False, grids=((80, 80), (40, 40), (20, 20))),
+            ),
+            "no table: every scale in one (1, cells, channels) tensor": (
+                (ANCHOR_FREE_PPU, [(8400, 1, 1)], {"table": False}),
+                PpuLayout(anchor_based=False, grids=((8400, 1),)),
+            ),
+        }
+
+        for head, ((ppu, layers, kwargs), expected) in cases.items():
+            with self.subTest(head=head):
+                self.assertEqual(self.layout(ppu, layers, **kwargs), expected)
+
+    def test_the_box_format_comes_from_the_compiled_graph(self):
+        for box_format, centre in (
+            ("centre", True),
+            ("corner", False),
+            ("unnamed", True),
+        ):
+            with self.subTest(box_format=box_format):
+                self.assertEqual(
+                    self.layout(ANCHOR_FREE_PPU, ONE_SCALE_FREE, box_format=box_format),
+                    PpuLayout(
+                        anchor_based=False, grids=((100, 84),), centre_boxes=centre
+                    ),
+                )
+
+    def test_a_box_format_the_graph_does_not_answer_is_left_open(self):
+        cases = {
+            "no compiled graph at all": (ANCHOR_FREE_PPU, ONE_SCALE_FREE, {}),
+            "a graph without the node compile_config names": (
+                dict(ANCHOR_FREE_PPU, layer=[{"bbox": "/head/Missing"}]),
+                ONE_SCALE_FREE,
+                {"box_format": "centre"},
+            ),
+            "a graph that builds its boxes from neither shape": (
+                ANCHOR_FREE_PPU,
+                ONE_SCALE_FREE,
+                {"box_format": "neither"},
+            ),
+            "a graph section the reader cannot make sense of": (
+                ANCHOR_FREE_PPU,
+                ONE_SCALE_FREE,
+                {"box_format": "broken"},
+            ),
+            "a grid-decoded head, where the question does not arise": (
+                ANCHOR_FREE_PPU,
+                THREE_SCALE_FREE,
+                {"box_format": "centre"},
+            ),
+        }
+
+        for graph, (ppu, layers, kwargs) in cases.items():
+            with self.subTest(graph=graph):
+                self.assertIsNone(self.layout(ppu, layers, **kwargs).centre_boxes)
+
+    def test_nothing_is_read_from_a_model_without_ppu_metadata(self):
+        self.assertIsNone(read_ppu_layout(os.path.join(self.tmp.name, "missing")))
+
+        path = write_dxnn(self.tmp.name, None, [(80, 80, 3)])
+        self.assertIsNone(read_ppu_layout(path))
+
+        with open(path, "wb") as model:
+            model.write(b"ONNX" + b"\0" * 100)
+        self.assertIsNone(read_ppu_layout(path))
+
+        path = write_dxnn(self.tmp.name, ANCHOR_BASED_PPU, [(80, 80, 3), (40, 40, 3)])
+        os.truncate(path, os.path.getsize(path) - 40)
+        self.assertIsNone(read_ppu_layout(path))
+
+
+class TestDeepxLayoutInference(unittest.TestCase):
+    def test_a_shape_and_class_count_pick_one_layout(self):
+        cases = {
+            "anchor-free, four columns ahead of the classes": (
+                [(1, 84, 8400)],
+                80,
+                YoloLayout.anchor_free,
+                84,
+            ),
+            "anchor-free, row-major": ([(1, 8400, 84)], 80, YoloLayout.anchor_free, 84),
+            "anchor-based, an objectness column as well": (
+                [(1, 25200, 85)],
+                80,
+                YoloLayout.anchor,
+                85,
+            ),
+            "anchor-based, channel-major": (
+                [(1, 85, 25200)],
+                80,
+                YoloLayout.anchor,
+                85,
+            ),
+            "NMS in the head, a fixed run of corner records": (
+                [(1, 300, 6)],
+                80,
+                YoloLayout.nms_in_head,
+                None,
+            ),
+            # only the label map can tell these two apart
+            "85 columns with 81 classes is anchor-free": (
+                [(1, 8400, 85)],
+                81,
+                YoloLayout.anchor_free,
+                85,
+            ),
+            "85 columns with 80 classes is anchor-based": (
+                [(1, 8400, 85)],
+                80,
+                YoloLayout.anchor,
+                85,
+            ),
+            # 6 columns is all three layouts, told apart by the row count
+            "6 columns and thousands of rows, one class": (
+                [(1, 25200, 6)],
+                1,
+                YoloLayout.anchor,
+                6,
+            ),
+            "6 columns and thousands of rows, two classes": (
+                [(1, 8400, 6)],
+                2,
+                YoloLayout.anchor_free,
+                6,
+            ),
+            "6 columns and a few hundred rows, one class": (
+                [(1, 300, 6)],
+                1,
+                YoloLayout.nms_in_head,
+                None,
+            ),
+            "7 columns with two classes is only anchor-based": (
+                [(1, 8400, 7)],
+                2,
+                YoloLayout.anchor,
+                7,
+            ),
+            # a square output matches the same width on both axes, which must
+            # not read as two candidate layouts
+            "a square output is not ambiguous with itself": (
+                [(1, 85, 85)],
+                80,
+                YoloLayout.anchor,
+                85,
+            ),
+            "three NCHW maps with 255 channels are feature maps": (
+                [(1, 255, 80, 80), (1, 255, 40, 40), (1, 255, 20, 20)],
+                80,
+                YoloLayout.multipart,
+                None,
+            ),
+        }
+
+        for head, (shapes, num_classes, layout, columns) in cases.items():
+            with self.subTest(head=head):
+                output = infer_yolo_layout(shapes, num_classes, False, False)
+
+                self.assertIs(output.layout, layout)
+                if columns is not None:
+                    self.assertEqual(output.columns, columns)
+
+    def test_the_runtime_flags_outrank_the_shapes(self):
+        self.assertIs(layout_of([(8400,)], 80, ppu=True), YoloLayout.ppu)
+        self.assertIs(
+            layout_of([(1, -1, 6)], 80, dynamic_output=True), YoloLayout.nms_in_head
+        )
+
+    def test_a_shape_no_layout_fits_is_refused_with_the_reason(self):
+        cases = {
+            "fits two layouts": ([(1, 84, 6)], 80),
+            "labelmap_path": ([(1, 8400, 84)], 91),
+            "no output tensor": ([], 80),
+            "255 channels": (
+                [(1, 80, 80, 255), (1, 40, 40, 255), (1, 20, 20, 255)],
+                80,
+            ),
+            "feature maps": ([(1, 8400, 80), (1, 8400, 4)], 80),
+            "80-class": ([(1, 24, 80, 80), (1, 24, 40, 40), (1, 24, 20, 20)], 3),
+        }
+
+        for reason, (shapes, num_classes) in cases.items():
+            with (
+                self.subTest(reason=reason),
+                self.assertRaisesRegex(ValueError, reason),
+            ):
+                layout_of(shapes, num_classes)
+
+
+class TestDeepxOutputValidation(unittest.TestCase):
+    def test_the_raw_yolox_head_is_read_for_the_configured_input(self):
+        for shapes, size in (
+            ([(1, 8400, 85)], 640),
+            ([(1, 85, 8400)], 640),
+            # 52*52 + 26*26 + 13*13 cells at 416
+            ([(1, 3549, 85)], 416),
+        ):
+            with self.subTest(shapes=shapes, size=size):
+                self.assertEqual(validate_yolox_outputs(shapes, 80, size, size), 85)
+
+    def test_another_head_under_yolox_is_refused_with_the_reason(self):
+        cases = {
+            "width and height": ([(1, 8400, 85)], 80, 416),
+            "labelmap_path": ([(1, 8400, 85)], 91, 640),
+            "yolo-generic": ([(1, 8400, 80), (1, 8400, 4)], 80, 640),
+        }
+
+        for reason, (shapes, num_classes, size) in cases.items():
+            with (
+                self.subTest(reason=reason),
+                self.assertRaisesRegex(ValueError, reason),
+            ):
+                validate_yolox_outputs(shapes, num_classes, size, size)
+
+    def test_the_label_map_bounds_the_class_count(self):
+        self.assertEqual(class_count({0: "person", 79: "toothbrush"}), 80)
+
+        with self.assertRaisesRegex(ValueError, "labelmap_path"):
+            class_count({})
+
+
+class TestDeepxRawDecode(unittest.TestCase):
+    def anchor_rows(self, rows) -> list:
+        out = np.zeros((1, len(rows), 85), dtype=np.float32)
+
+        for i, (cx, cy, w, h, obj, label, score) in enumerate(rows):
+            out[0, i, 0:4] = [cx, cy, w, h]
+            out[0, i, 4] = obj
+            out[0, i, 5 + label] = score
+
+        return [out]
+
+    def test_an_anchor_based_head_becomes_normalized_corners(self):
+        outputs = self.anchor_rows([(320.0, 160.0, 64.0, 32.0, 0.8, 3, 0.5)])
+
+        detections = decode_raw_anchor(outputs, 640, 640, 0.25, 0.45)
+
+        self.assertEqual(detections[0][0], 3)
+        self.assertAlmostEqual(detections[0][1], 0.4, places=5)
+        self.assertAlmostEqual(detections[0][2], 144 / 640, places=5)
+        self.assertAlmostEqual(detections[0][3], 288 / 640, places=5)
+        self.assertAlmostEqual(detections[0][4], 176 / 640, places=5)
+        self.assertAlmostEqual(detections[0][5], 352 / 640, places=5)
+
+    def test_a_channel_major_export_is_read_by_column_count(self):
+        outputs = self.anchor_rows([(320.0, 160.0, 64.0, 32.0, 1.0, 3, 0.9)])
+
+        detections = decode_raw_anchor(
+            [np.swapaxes(outputs[0], 1, 2)], 640, 640, 0.25, 0.45, columns=85
+        )
+
+        self.assertEqual(detections[0][0], 3)
+        self.assertAlmostEqual(detections[0][3], 288 / 640, places=5)
+
+    def test_rows_below_the_combined_threshold_are_dropped(self):
+        # 0.4 * 0.5 = 0.2, under the threshold both parts clear on their own
+        outputs = self.anchor_rows([(320.0, 320.0, 40.0, 80.0, 0.4, 3, 0.5)])
+
+        self.assertTrue(np.all(decode_raw_anchor(outputs, 640, 640, 0.25, 0.45) == 0))
+
+    def test_at_most_twenty_detections_are_returned(self):
+        rows = [(20.0 + 24 * i, 320.0, 16.0, 16.0, 1.0, i % 80, 0.9) for i in range(25)]
+
+        detections = decode_raw_anchor(self.anchor_rows(rows), 640, 640, 0.25, 0.45)
+
+        self.assertEqual(detections.shape, (20, 6))
+        self.assertEqual(int((detections[:, 1] > 0).sum()), 20)
+
+    def test_an_nms_in_head_output_is_read_without_running_nms(self):
+        out = np.array(
+            [
+                [
+                    [100.0, 100.0, 200.0, 200.0, 0.9, 2.0],
+                    [102.0, 102.0, 202.0, 202.0, 0.8, 2.0],
+                    [300.0, 300.0, 400.0, 400.0, 0.1, 5.0],
+                ]
+            ],
+            dtype=np.float32,
+        )
+
+        detections = decode_raw_nms_in_head([out], 640, 640, 0.25)
+
+        self.assertEqual(detections[0][0], 2)
+        self.assertAlmostEqual(detections[0][1], 0.9, places=5)
+        self.assertAlmostEqual(detections[0][3], 100 / 640, places=5)
+        self.assertEqual(detections[1][0], 2)
+        self.assertAlmostEqual(detections[1][1], 0.8, places=5)
+        self.assertTrue(np.all(detections[2] == 0))
+
+        empty = np.zeros((1, 0, 6), dtype=np.float32)
+        self.assertTrue(np.all(decode_raw_nms_in_head([empty], 640, 640, 0.25) == 0))
+
+
+class TestDeepxConfig(unittest.TestCase):
+    def test_a_device_string_resolves_to_an_npu_index(self):
+        for configured, index in (("PCIe:1", 1), ("2", 2), ("", 0)):
+            with self.subTest(device=configured):
+                self.assertEqual(resolve_device(configured), index)
+
+    def test_a_device_that_is_not_an_index_is_rejected(self):
+        """The whole string has to be an index. Reading only the tail would
+        take the 1 out of "PCIe:0,PCIe:1" and bind to an NPU the config never
+        named, and several NPUs are configured as separate devices entries."""
+        for configured in (
+            "PCIe:the-fast-one",
+            "PCIe:0,PCIe:1",
+            "0,1",
+            "PCIe:0 PCIe:1",
+            "PCIe:-1",
+            "PCIe:",
+        ):
+            with self.subTest(device=configured):
+                with self.assertRaises(ValueError):
+                    resolve_device(configured)
+
+                with self.assertRaises(ValidationError):
+                    DeepxDetectorConfig(type="deepx", device=configured)
+
+    def test_a_bad_device_is_refused_where_the_config_is_parsed(self):
+        """parse_device builds the detector config to surface a bad device at
+        startup, so the comma-separated form fails there rather than binding a
+        detector process to the wrong NPU."""
+        self.assertEqual(parse_device("deepx:PCIe:1").device, "PCIe:1")
+
+        for raw in ("deepx:PCIe:0,PCIe:1", "deepx:the-fast-one"):
+            with self.subTest(raw=raw), self.assertRaises(DeviceParseError):
+                parse_device(raw)
+
+    def test_a_device_string_builds_this_detector_config(self):
+        """Frigate turns a `deepx:PCIe:0` entry into the detector config with
+        the model already attached, which is the path app.py takes; a bare
+        constructor call does not exercise it."""
+        config = build_detector_config(
+            parse_device("deepx:PCIe:0"), model_with_type(ModelTypeEnum.yologeneric)
+        )
+
+        self.assertIsInstance(config, DeepxDetectorConfig)
+        self.assertEqual(config.device, "PCIe:0")
+        self.assertEqual(config.model.model_type, ModelTypeEnum.yologeneric)
+
+    def test_the_runtime_manifest_pins_its_wheels_to_the_version(self):
+        """A PyPI path carries a per-file digest, so bumping DXRT_VERSION has
+        to rewrite the whole URL; a stale one installs the old wheel and fails
+        the sha256 on every user's first start."""
+        self.assertEqual(DEEPX_MANIFEST.version, DXRT_VERSION)
+
+        for artifact in DEEPX_MANIFEST.artifacts:
+            with self.subTest(url=artifact.url):
+                self.assertIn(f"dx_engine-{DXRT_VERSION}-", artifact.url)
+
+    def test_a_model_less_config_still_validates(self):
+        config = DeepxDetectorConfig(type="deepx")
+
+        self.assertIsNone(config.model)
+
+
+class DeepxDetectorTestCase(unittest.TestCase):
+    def detector(
+        self,
+        model_type=ModelTypeEnum.yologeneric,
+        outputs_info=None,
+        ppu=False,
+        dynamic=False,
+        model_path="/nonexistent/model.dxnn",
+    ) -> DeepxDetector:
+        dx_engine = MagicMock()
+        dx_engine.Configuration.ITEM.SERVICE = object()
+        session = dx_engine.InferenceEngine.return_value
+        session.get_output_tensors_info.return_value = (
+            [{"shape": [8400]}] if ppu else outputs_info or []
+        )
+        session.is_ppu.return_value = ppu
+        session.has_dynamic_output.return_value = dynamic
+
+        config = DeepxDetectorConfig(type="deepx")
+        config.model = model_with_type(model_type)
+        config.model.path = model_path
+
+        with (
+            # the detector writes the endpoint into the environment, which the
+            # rest of the suite shares when it runs in one process
+            patch.dict(os.environ),
+            patch.dict(sys.modules, {"dx_engine": dx_engine}),
+            patch.object(DeepxDetector, "activate_dependencies"),
+            patch("os.path.isfile", return_value=True),
+        ):
+            return DeepxDetector(config)
+
+    def ppu_detector(
+        self, ppu, layers, model_type=ModelTypeEnum.yologeneric, box_format=None
+    ) -> DeepxDetector:
+        tmp = tempfile.TemporaryDirectory()
+        self.addCleanup(tmp.cleanup)
+
+        return self.detector(
+            model_type,
+            ppu=True,
+            model_path=write_dxnn(tmp.name, ppu, layers, box_format=box_format),
+        )
+
+    def detect(self, detector, outputs) -> np.ndarray:
+        detector.session.run.return_value = outputs
+        return detector.detect_raw(np.zeros((1, 640, 640, 3), np.uint8))
+
+
+class TestDeepxModelType(DeepxDetectorTestCase):
+    def test_a_model_type_with_no_decoder_is_rejected(self):
+        for model_type in (ModelTypeEnum.ssd, ModelTypeEnum.dfine):
+            with (
+                self.subTest(model_type=model_type),
+                self.assertRaisesRegex(ValueError, model_type.value),
+            ):
+                self.detector(model_type)
+
+    def test_supported_model_types_are_accepted(self):
+        for model_type, outputs_info in (
+            (ModelTypeEnum.yologeneric, [{"shape": [1, 84, 8400]}]),
+            (ModelTypeEnum.yolox, [{"shape": [1, 8400, 85]}]),
+        ):
+            with self.subTest(model_type=model_type):
+                detector = self.detector(model_type, outputs_info)
+
+                self.assertEqual(detector.model_type, model_type)
+
+
+class TestDeepxDetectorLoad(DeepxDetectorTestCase):
+    def test_the_layout_is_settled_at_load(self):
+        detector = self.detector(ModelTypeEnum.yologeneric, [{"shape": [1, 84, 8400]}])
+        self.assertIs(detector.output.layout, YoloLayout.anchor_free)
+        self.assertEqual(detector.output.columns, 84)
+
+        detector = self.detector(ModelTypeEnum.yolox, [{"shape": [1, 8400, 85]}])
+        self.assertIs(detector.output.layout, YoloLayout.yolox)
+
+        for model_type in (ModelTypeEnum.yologeneric, ModelTypeEnum.yolox):
+            with self.subTest(model_type=model_type):
+                detector = self.ppu_detector(
+                    ANCHOR_FREE_PPU, THREE_SCALE_FREE, model_type=model_type
+                )
+
+                self.assertIs(detector.output.layout, YoloLayout.ppu)
+                self.assertEqual(detector.ppu_layout.scale_count, 3)
+
+    def test_a_model_the_detector_cannot_decode_is_refused_at_load(self):
+        cases = {
+            "Cannot decode DEEPX model": lambda: self.detector(
+                ModelTypeEnum.yologeneric, [{"shape": [1, 8400, 7]}]
+            ),
+            "DX-COM 2.4.0": lambda: self.detector(ModelTypeEnum.yologeneric, ppu=True),
+            "face and pose": lambda: self.ppu_detector({"type": 2}, [(80, 80, 1)]),
+            "centre and size or as two corners": lambda: self.ppu_detector(
+                ANCHOR_FREE_PPU, ONE_SCALE_FREE
+            ),
+        }
+
+        for reason, load in cases.items():
+            with (
+                self.subTest(reason=reason),
+                self.assertRaisesRegex(ValueError, reason),
+            ):
+                load()
+
+
+class TestDeepxDetectRaw(DeepxDetectorTestCase):
+    def test_a_ppu_record_decodes_by_the_head_in_the_model(self):
+        cases = {
+            "anchor-based, layer 2 of 3 at stride 32, the 373x326 anchor": (
+                (ANCHOR_BASED_PPU, THREE_SCALE_ANCHORS, None),
+                build_ppu_record((0.6, 0.4, 0.3, 0.7), label=5),
+                (5, (0.0, 0.380094, 0.864187, 0.589906)),
+            ),
+            "anchor-based, layer 0 of 3 at stride 8, the 16x30 anchor": (
+                (ANCHOR_BASED_PPU, THREE_SCALE_ANCHORS, None),
+                build_ppu_record((0.6, 0.4, 0.3, 0.7), grid=(7, 9, 1, 0)),
+                (0, (None, 0.116750, None, None)),
+            ),
+            "anchor-based, two scales: layer 0 is stride 16, not stride 8": (
+                (ANCHOR_BASED_PPU, TWO_SCALE_ANCHORS, None),
+                build_ppu_record((0.6, 0.4, 0.3, 0.7), grid=(7, 9, 1, 0)),
+                (0, (0.141156, 0.236031, 0.223844, 0.248969)),
+            ),
+            "anchor-free, three scales: cell (10, 9) of stride 32": (
+                (ANCHOR_FREE_PPU, THREE_SCALE_FREE, None),
+                build_ppu_record((1.2, 0.5, 1.0, 0.5), grid=(9, 10, 0, 2), label=7),
+                (7, (0.433782, 0.492043, 0.516218, 0.627957)),
+            ),
+            "anchor-free, one scale: the box fields are already pixels": (
+                (ANCHOR_FREE_PPU, ONE_SCALE_FREE, "centre"),
+                build_ppu_record((320.0, 160.0, 64.0, 32.0), label=3),
+                (3, (144 / 640, 288 / 640, 176 / 640, 352 / 640)),
+            ),
+            "anchor-free, one scale: a sub-pixel box stays sub-pixel": (
+                (ANCHOR_FREE_PPU, ONE_SCALE_FREE, "centre"),
+                build_ppu_record((0.6, 0.4, 0.3, 0.7)),
+                (0, (None, 0.45 / 640, None, None)),
+            ),
+            "a corner-format head reads the record as two corners": (
+                (ANCHOR_FREE_PPU, ONE_SCALE_FREE, "corner"),
+                build_ppu_record((100.0, 50.0, 300.0, 250.0), label=2),
+                (2, (50 / 640, 100 / 640, 250 / 640, 300 / 640)),
+            ),
+            "a centre-format head reads it as a centre and size": (
+                (ANCHOR_FREE_PPU, ONE_SCALE_FREE, "centre"),
+                build_ppu_record((100.0, 50.0, 300.0, 250.0), label=2),
+                (2, (0.0, 0.0, 175 / 640, 250 / 640)),
+            ),
+        }
+
+        for head, ((ppu, layers, box_format), record, (label, box)) in cases.items():
+            with self.subTest(head=head):
+                detector = self.ppu_detector(ppu, layers, box_format=box_format)
+
+                detections = self.detect(detector, [record])
+
+                self.assertEqual(detections[0][0], label)
+                for i, expected in enumerate(box, start=2):
+                    if expected is not None:
+                        self.assertAlmostEqual(detections[0][i], expected, places=5)
+
+    def test_the_strides_come_from_the_grids_in_the_model(self):
+        detector = self.ppu_detector(
+            ANCHOR_FREE_PPU, [(40, 40, 1), (20, 20, 1), (10, 10, 1)]
+        )
+
+        detections = self.detect(
+            detector,
+            [build_ppu_record((1.2, 0.5, 1.0, 0.5), grid=(9, 10, 0, 0), label=7)],
+        )
+
+        # layer 0 is stride 16: centre (11.2, 9.5) * 16, size e * 16 x sqrt(e) * 16
+        self.assertEqual(detections[0][0], 7)
+        self.assertAlmostEqual(detections[0][2], (152 - np.exp(0.5) * 8) / 640, 5)
+        self.assertAlmostEqual(detections[0][3], (179.2 - np.exp(1.0) * 8) / 640, 5)
+
+    def test_the_head_stays_what_the_model_said_across_frames(self):
+        detector = self.ppu_detector(ANCHOR_BASED_PPU, THREE_SCALE_ANCHORS)
+
+        first = self.detect(
+            detector, [build_ppu_record((0.6, 0.4, 0.3, 0.7), grid=(7, 9, 1, 0))]
+        )
+        # layer 0 of 3: stride 8, anchor 16x30
+        self.assertAlmostEqual(first[0][3], 0.116750, places=5)
+
+        second = self.detect(
+            detector, [build_ppu_record((0.5, 0.5, 0.4, 0.4), grid=(3, 4, 0, 1))]
+        )
+        # layer 1 of 3: stride 16, anchor 30x61, not layer 1 of 2
+        self.assertAlmostEqual(second[0][3], 0.0975, places=5)
+
+        detector = self.ppu_detector(
+            ANCHOR_FREE_PPU, ONE_SCALE_FREE, box_format="centre"
+        )
+        record = [build_ppu_record((100.0, 50.0, 300.0, 250.0), label=2)]
+        # centre (100, 50), size 300 x 250: the right edge lands at 250
+        for frame in range(2):
+            with self.subTest(frame=frame):
+                self.assertAlmostEqual(
+                    self.detect(detector, record)[0][5], 250 / 640, places=5
+                )
+
+    def test_records_the_head_cannot_place_come_back_empty(self):
+        cases = {
+            "a level or box the anchor table does not carry": (
+                THREE_SCALE_ANCHORS,
+                [build_ppu_record((0.6, 0.4, 0.3, 0.7), grid=(7, 9, 2, 5))],
+            ),
+            "a scale count Frigate has no anchor table for": (
+                FOUR_SCALE_ANCHORS,
+                [build_ppu_record((0.6, 0.4, 0.3, 0.7))],
+            ),
+            "a record below the score threshold": (
+                THREE_SCALE_ANCHORS,
+                [build_ppu_record((0.6, 0.4, 0.3, 0.7), score=0.1)],
+            ),
+            "an unexpected record width": (
+                THREE_SCALE_ANCHORS,
+                [np.zeros((1, 3, 16), dtype=np.uint8)],
+            ),
+            **{
+                f"no records at all, shaped {shape}": (
+                    THREE_SCALE_ANCHORS,
+                    [np.zeros(shape, dtype=np.uint8)],
+                )
+                for shape in ((1, 0, PPU_RECORD_SIZE), (0, PPU_RECORD_SIZE), (0,))
+            },
+        }
+
+        for output, (layers, outputs) in cases.items():
+            with self.subTest(output=output):
+                detector = self.ppu_detector(ANCHOR_BASED_PPU, layers)
+
+                self.assertTrue(np.all(self.detect(detector, outputs) == 0))
+
+    def test_a_yolox_raw_head_is_decoded_through_the_grid(self):
+        detector = self.detector(ModelTypeEnum.yolox, [{"shape": [1, 8400, 85]}])
+
+        # cell (x 10, y 5) of the stride-8 grid is row 5 * 80 + 10
+        tensor = np.zeros((1, 8400, 85), np.float32)
+        tensor[0, 410, :5] = [0.5, 0.5, np.log(4.0), np.log(2.0), 0.9]
+        tensor[0, 410, 5 + 7] = 0.8
+
+        detections = self.detect(detector, [tensor])
+
+        # centre (84, 44), size 32 x 16
+        self.assertEqual(detections[0][0], 7)
+        self.assertAlmostEqual(detections[0][1], 0.72, places=5)
+        self.assertAlmostEqual(detections[0][2], 36 / 640, places=5)
+        self.assertAlmostEqual(detections[0][3], 68 / 640, places=5)
+        self.assertAlmostEqual(detections[0][4], 52 / 640, places=5)
+        self.assertAlmostEqual(detections[0][5], 100 / 640, places=5)
+
+        detector = self.detector(ModelTypeEnum.yolox, [{"shape": [1, 85, 8400]}])
+        detections = self.detect(detector, [np.swapaxes(tensor, 1, 2)])
+        self.assertAlmostEqual(detections[0][5], 100 / 640, places=5)
+
+    def test_a_raw_head_comes_back_as_frigates_detection_rows(self):
+        detector = self.detector(ModelTypeEnum.yologeneric, [{"shape": [1, 84, 8400]}])
+        output = np.zeros((1, 84, 8400), dtype=np.float32)
+        output[0, 0:4, 0] = [320.0, 160.0, 64.0, 32.0]
+        output[0, 4 + 2, 0] = 0.9
+
+        detections = self.detect(detector, [output])
+
+        self.assertEqual(detections.shape, (20, 6))
+        self.assertEqual(detections[0][0], 2)
+        self.assertAlmostEqual(detections[0][1], 0.9, places=5)
+        self.assertAlmostEqual(detections[0][3], 288 / 640, places=5)
@@ -59,6 +59,10 @@ class TestBuildDetectorConfig(unittest.TestCase):
    def test_detectors_that_name_the_field_something_else(self):
        self.assertEqual(self._build("cpu:4").num_threads, 4)
        self.assertEqual(self._build("rknn:2").num_cores, 2)
+        self.assertEqual(
+            self._build("zmq:tcp://host.docker.internal:5555").endpoint,
+            "tcp://host.docker.internal:5555",
+        )

    def test_device_is_coerced_to_the_detector_field_type(self):
        self.assertEqual(self._build("tensorrt:1").device, 1)
@@ -66,6 +70,7 @@ class TestBuildDetectorConfig(unittest.TestCase):
    def test_omitted_device_falls_back_to_the_detector_default(self):
        self.assertEqual(self._build("cpu").num_threads, 3)
        self.assertEqual(self._build("rknn").num_cores, 0)
+        self.assertEqual(self._build("zmq").endpoint, "ipc:///tmp/cache/zmq_detector")
        self.assertEqual(self._build("openvino").device, "AUTO")
        self.assertIsNone(self._build("edgetpu").device)

@@ -25,7 +25,7 @@ class HardwareProbeTestCase(unittest.TestCase):
        self.root = tempfile.TemporaryDirectory()
        self.addCleanup(self.root.cleanup)

-        for name in ("SYS_ROOT", "DEV_ROOT", "PROC_ROOT", "ETC_ROOT"):
+        for name in ("SYS_ROOT", "DEV_ROOT", "PROC_ROOT", "ETC_ROOT", "LIB_ROOT"):
            sub = os.path.join(self.root.name, name.split("_")[0].lower())
            os.makedirs(sub, exist_ok=True)
            patcher = patch.object(hardware, name, sub)
@@ -167,6 +167,29 @@ class TestNvidia(HardwareProbeTestCase):


 class TestAccelerators(HardwareProbeTestCase):
+    def test_the_neural_engine_is_found_by_lighters_provider_library(self):
+        write(os.path.join(self.lib_root, "lighter", "liblighter_ane_ep.so"))
+
+        with patch.dict(os.environ, clear=False) as env:
+            env.pop("LIGHTER_ANE_EP", None)
+            ane = self.probe()["onnx:lighter"]
+
+        self.assertEqual(ane.detector, "onnx")
+        self.assertEqual(ane.units[0].device, "onnx")
+        self.assertEqual(ane.units[0].label, "Neural Engine")
+
+    def test_the_neural_engine_is_found_where_lighter_ane_ep_points(self):
+        library = os.path.join(self.root.name, "elsewhere", "liblighter_ane_ep.so")
+        write(library)
+
+        with patch.dict(os.environ, {"LIGHTER_ANE_EP": library}):
+            self.assertIn("onnx:lighter", self.probe())
+
+    def test_no_neural_engine_is_reported_without_the_library(self):
+        with patch.dict(os.environ, clear=False) as env:
+            env.pop("LIGHTER_ANE_EP", None)
+            self.assertNotIn("onnx:lighter", self.probe())
+
    def test_hailo_is_found_by_its_device_node(self):
        write(os.path.join(self.dev_root, "hailo0"))

@@ -184,6 +207,26 @@ class TestAccelerators(HardwareProbeTestCase):
        )
        self.assertFalse(memryx.unlimited)

+    def test_each_deepx_node_is_a_unit(self):
+        write(os.path.join(self.dev_root, "dxrt0"))
+        write(os.path.join(self.dev_root, "dxrt1"))
+
+        deepx = self.probe()["deepx"]
+
+        self.assertEqual(
+            [unit.device for unit in deepx.units],
+            ["deepx:PCIe:0", "deepx:PCIe:1"],
+        )
+
+    def test_a_deepx_npu_is_unlimited(self):
+        # the host daemon multiplexes, so one module takes several processes
+        write(os.path.join(self.dev_root, "dxrt0"))
+
+        self.assertTrue(self.probe()["deepx"].unlimited)
+
+    def test_no_deepx_is_reported_without_a_node(self):
+        self.assertNotIn("deepx", self.probe())
+
    def test_a_supported_rockchip_soc_is_reported(self):
        write(
            os.path.join(self.proc_root, "device-tree", "compatible"),
@@ -0,0 +1,39 @@
+"""Tests for per-detector stats."""
+
+import unittest
+from unittest.mock import MagicMock, patch
+
+from frigate.stats.util import get_detector_stats
+
+
+def _detector(detector_type: str) -> MagicMock:
+    detector = MagicMock()
+    detector.detector_config.type = detector_type
+    detector.avg_inference_speed.value = 0.01
+    detector.detection_start.value = 0.0
+    detector.detect_process.pid = 1
+    return detector
+
+
+class TestDetectorTemperatures(unittest.TestCase):
+    def test_repeated_device_shares_its_unit_temperature(self):
+        stats_tracking = {
+            "detectors": {
+                "hailo:PCIe": _detector("hailo8l"),
+                "hailo:PCIe#2": _detector("hailo8l"),
+                "hailo:PCIe:1": _detector("hailo8l"),
+            }
+        }
+
+        with patch(
+            "frigate.stats.util.get_hardware_temperatures", return_value=[50.0, 60.0]
+        ):
+            stats = get_detector_stats(stats_tracking)
+
+        self.assertEqual(stats["hailo:PCIe"]["temperature"], 50.0)
+        self.assertEqual(stats["hailo:PCIe#2"]["temperature"], 50.0)
+        self.assertEqual(stats["hailo:PCIe:1"]["temperature"], 60.0)
+
+
+if __name__ == "__main__":
+    unittest.main()
@@ -543,6 +543,56 @@ class TestPinnedStream(unittest.TestCase):
        self.assertFalse(any("/vod/front/main/" in token for token in cmd))


+class TestExportTimelineAlignment(unittest.TestCase):
+    def test_unstaged_auto_reads_the_stream_it_serves(self) -> None:
+        # a sub-only range whose main rows are glitches the manifest drops
+        exporter = _make_exporter([_span("/s1.mp4", 1_000, 1_040, False)], {"h264"})
+        streams: list[str] = []
+
+        def rows(stream: str) -> list:
+            streams.append(stream)
+            return [_FakeRow(f"/{stream}.mp4")]
+
+        exporter._get_recordings_for_range = rows  # type: ignore[method-assign]
+        exporter.get_record_export_command("/exports/out.mp4")
+
+        self.assertEqual(streams, ["sub"])
+
+    def test_staged_chapters_carry_keyframe_lead_in(self) -> None:
+        exporter = _make_exporter(
+            [
+                _span("/m1.mp4", 1_000, 1_020, True),
+                _span("/s1.mp4", 1_020, 1_040, False),
+            ],
+            {"h264"},
+        )
+        exporter.config.ui.timezone = None
+
+        # each run's vod clip snaps 1.5s back to a keyframe
+        def timeline(_intervals: list, stream: str) -> list[dict]:
+            start, end = (1_000, 1_020) if stream == "main" else (1_020, 1_040)
+            return [
+                {
+                    "start_time": start,
+                    "end_time": end,
+                    "duration": (end - start + 1.5) * 1000,
+                }
+            ]
+
+        with (
+            patch("frigate.record.export.resolve_coverage", return_value=[]),
+            patch("frigate.record.export.realized_timeline", side_effect=timeline),
+        ):
+            windows = exporter._staged_chapter_windows()
+
+        path = exporter._build_recording_segment_chapter_metadata_file(windows)
+        self.addCleanup(os.remove, path)
+        content = Path(path).read_text()
+
+        self.assertIn("START=0\nEND=21500", content)
+        self.assertIn("START=21500\nEND=43000", content)
+
+
 class TestStagedFileCleanup(unittest.TestCase):
    """A staged path must be tracked before ffmpeg can write to it."""

@@ -51,6 +51,16 @@ class TestFfmpegPresets(unittest.TestCase):
            " ".join(frigate_config.cameras["back"].ffmpeg_cmds[0]["cmd"])
        )

+    def test_ffmpeg_hwaccel_apple_preset_decodes_every_stream(self):
+        self.default_ffmpeg["cameras"]["back"]["ffmpeg"]["hwaccel_args"] = (
+            "preset-apple-silicon-h265"
+        )
+        frigate_config = FrigateConfig(**self.default_ffmpeg)
+        cmd = " ".join(frigate_config.cameras["back"].ffmpeg_cmds[0]["cmd"])
+        assert "-c:v hevc_v4l2m2m" in cmd
+        assert "-c:v:1" not in cmd
+        assert "scale=1920:1080" in cmd
+
    def test_ffmpeg_hwaccel_not_preset(self):
        self.default_ffmpeg["cameras"]["back"]["ffmpeg"]["hwaccel_args"] = (
            "-other-hwaccel args"
@@ -7,6 +7,7 @@ from frigate.genai.prompts import (
    REVIEW_DESCRIPTION_FIELD_GUIDELINES,
    REVIEW_RESPONSE_STYLES,
    build_review_description_prompt,
+    build_review_summary_prompt,
    get_review_field_guidelines,
 )

@@ -83,5 +84,49 @@ class TestReviewResponseStyle(unittest.TestCase):
        )


+class TestClassificationStateChanges(unittest.TestCase):
+    def _build_prompt(self, **extra) -> str:
+        review_data = {
+            "camera": "Front Door",
+            "start": "Monday, 09:30 AM",
+            "duration": 25,
+            "zones": [],
+            "unified_objects": ["person"],
+            **extra,
+        }
+        return build_review_description_prompt(
+            review_data, [b"fake-image"], [], None, "activity context"
+        )
+
+    def test_no_changes_leaves_prompt_unchanged(self):
+        self.assertEqual(
+            self._build_prompt(classification_state_changes=[]),
+            self._build_prompt(),
+        )
+        self.assertNotIn("## State Changes", self._build_prompt())
+
+    def test_changes_are_listed_before_objects(self):
+        change = "front gate changed from closed to open, 12s into the activity"
+        prompt = self._build_prompt(classification_state_changes=[change])
+        self.assertIn(f"\n- {change}\n\n## Objects in Scene", prompt)
+        self.assertLess(
+            prompt.index("## Sequence Details"), prompt.index("## State Changes")
+        )
+
+    def test_summary_describes_state_changes_only_when_present(self):
+        event = {"title": "Person at door", "camera": "Front Door", "context": []}
+        without = build_review_summary_prompt(0, 3600, [event], None)
+        self.assertNotIn('"state_changes"', without)
+
+        context_event = {
+            **event,
+            "context": [
+                {"camera": "Driveway", "state_changes": ["gate changed from a to b"]}
+            ],
+        }
+        with_changes = build_review_summary_prompt(0, 3600, [context_event], None)
+        self.assertIn('- "state_changes"', with_changes)
+
+
 if __name__ == "__main__":
    unittest.main()
@@ -19,6 +19,8 @@ import unittest
 from types import SimpleNamespace
 from unittest.mock import AsyncMock, MagicMock, patch

+import requests
+
 from frigate.config import GenAIConfig, GenAIProviderEnum
 from frigate.genai import PROVIDERS, load_providers

@@ -566,7 +568,6 @@ class TestLlamaCppProvider(unittest.TestCase):
            "supports_audio": False,
            "supports_tools": False,
            "supports_reasoning": False,
-            "media_marker": "<__media__>",
        }
        cls = PROVIDERS[GenAIProviderEnum.llamacpp]
        with patch.object(cls, "_get_model_info", return_value=info):
@@ -589,6 +590,62 @@ class TestLlamaCppProvider(unittest.TestCase):
        with patch.object(client, "_fetch_models_data", return_value=models_data):
            self.assertEqual(client.list_models(), ["g4", "gemma", "qwen3-asr"])

+    @staticmethod
+    def _embeddings_response(vectors):
+        response = MagicMock()
+        response.status_code = 200
+        response.json.return_value = {
+            "object": "list",
+            "data": [
+                {"object": "embedding", "index": i, "embedding": v}
+                for i, v in enumerate(vectors)
+            ],
+        }
+        return response
+
+    def test_embed_posts_content_arrays_to_v1_embeddings(self):
+        client = self._client()
+        response = self._embeddings_response([[0.1] * 768, [0.2] * 768])
+
+        with patch.object(client, "_post", return_value=response) as post:
+            result = client.embed(texts=["a person"], images=[b"not an image"])
+
+        url = post.call_args.args[0]
+        payload = post.call_args.kwargs["json"]
+        self.assertEqual(url, "http://localhost:9999/v1/embeddings")
+        self.assertEqual(payload["model"], "m")
+        self.assertEqual(payload["encoding_format"], "float")
+        self.assertEqual(
+            payload["input"][0], {"content": [{"type": "text", "text": "a person"}]}
+        )
+        image_parts = payload["input"][1]["content"]
+        self.assertEqual(image_parts[0]["type"], "image_url")
+        self.assertEqual(
+            image_parts[0]["image_url"]["url"],
+            "data:image/jpeg;base64," + base64.b64encode(b"not an image").decode(),
+        )
+        self.assertEqual(image_parts[1], {"type": "text", "text": "\n"})
+        self.assertEqual(len(result), 2)
+        self.assertAlmostEqual(float(result[1][0]), 0.2, places=5)
+
+    def test_embed_normalizes_dimension(self):
+        client = self._client()
+        response = self._embeddings_response([[1.0] * 1024, [1.0] * 512])
+
+        with patch.object(client, "_post", return_value=response):
+            result = client.embed(texts=["long", "short"])
+
+        self.assertEqual([r.shape for r in result], [(768,), (768,)])
+        self.assertEqual(float(result[1][-1]), 0.0)
+
+    def test_embed_request_error_returns_empty(self):
+        client = self._client()
+        response = MagicMock()
+        response.raise_for_status.side_effect = requests.exceptions.HTTPError("400")
+
+        with patch.object(client, "_post", return_value=response):
+            self.assertEqual(client.embed(texts=["a"]), [])
+

 # ---------------------------------------------------------------------------
 # transcribe role
@@ -762,7 +819,6 @@ class TestLlamaCppTranscribe(unittest.TestCase):
            "supports_audio": supports_audio,
            "supports_tools": False,
            "supports_reasoning": False,
-            "media_marker": "<__media__>",
        }
        cls = PROVIDERS[GenAIProviderEnum.llamacpp]
        with patch.object(cls, "_get_model_info", return_value=info):
@@ -288,6 +288,17 @@ class TestUpdateConfig(HardwareStatsTestCase):

        self.assertEqual(set(stats._monitored), {"rockchip"})

+    def test_follows_a_runtime_config_swap(self):
+        stats = self.make_stats(self.make_config())
+        self.assertEqual(set(stats._monitored), set())
+
+        swapped = self.make_config("preset-rk-h264")
+        stats.set_config(swapped)
+
+        self.assertEqual(set(stats._monitored), {"rockchip"})
+        self.assertIs(self.subscriber.return_value.config, swapped)
+        self.assertIs(self.subscriber.return_value.camera_configs, swapped.cameras)
+

 class TestUpdateStats(HardwareStatsTestCase):
    def run_stats(self, stats: HardwareStats) -> dict:
@@ -34,6 +34,12 @@ class HwaccelRecommendationTestCase(unittest.TestCase):
        patcher.start()
        self.addCleanup(patcher.stop)

+        self.sys_root = os.path.join(self.root.name, "sys")
+        os.makedirs(self.sys_root)
+        patcher = patch.object(hwaccel, "SYS_ROOT", self.sys_root)
+        patcher.start()
+        self.addCleanup(patcher.stop)
+
        drm = patch.object(hwaccel, "enumerate_drm_devices", return_value={})
        self.drm = drm.start()
        self.addCleanup(drm.stop)
@@ -66,6 +72,12 @@ class HwaccelRecommendationTestCase(unittest.TestCase):
        with open(os.path.join(self.proc_root, "cpuinfo"), "w") as f:
            f.write(f"processor\t: 0\nmodel name\t: {model_name}\n")

+    def write_video_device(self, vendor: str) -> None:
+        device = os.path.join(self.sys_root, "class", "video4linux", "video0", "device")
+        os.makedirs(device)
+        with open(os.path.join(device, "vendor"), "w") as f:
+            f.write(f"{vendor}\n")
+
    def write_device_tree(self) -> None:
        os.makedirs(os.path.join(self.proc_root, "device-tree"), exist_ok=True)
        with open(os.path.join(self.proc_root, "device-tree", "compatible"), "w") as f:
@@ -191,6 +203,22 @@ class TestAvailableFamilies(HwaccelRecommendationTestCase):
        self.assertIn(recommended, [family.key for family in families])


+class TestLighter(HwaccelRecommendationTestCase):
+    def test_lighters_media_engine_is_recommended(self):
+        self.write_video_device(hwaccel.LIGHTER_VIRTIO_VENDOR)
+
+        self.assertEqual(self.recommend(codecs={"h264"}), "apple-silicon")
+        self.assertEqual(
+            self.presets()["apple-silicon"],
+            {"h264": "preset-apple-silicon-h264", "h265": "preset-apple-silicon-h265"},
+        )
+
+    def test_another_virtio_media_device_is_not_lighters(self):
+        self.write_video_device("0x554d4551")
+
+        self.assertEqual(self.available(), [])
+
+
 class TestCodecCoverage(HwaccelRecommendationTestCase):
    def test_a_family_carries_a_preset_per_codec(self):
        self.assertEqual(
@@ -1,7 +1,7 @@
 import datetime
 import sys
 import unittest
-from unittest.mock import MagicMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch

 # Mock complex imports before importing maintainer, saving originals so we can
 # restore them after import and avoid polluting sys.modules for other tests.
@@ -48,8 +48,11 @@ class TestMaintainer(unittest.IsolatedAsyncioTestCase):
                    "frigate.record.maintainer.psutil.process_iter", return_value=[]
                ):
                    with patch("frigate.record.maintainer.logger.warning") as warn:
-                        # Mock validate_and_move_segment to avoid further logic
-                        maintainer.validate_and_move_segment = MagicMock()
+                        # Mock validate_and_move_segment to avoid further logic.
+                        # The requestor is real when another test imported the
+                        # maintainer first, and it would block on a reply.
+                        maintainer.validate_and_move_segment = AsyncMock()
+                        maintainer.requestor = MagicMock()

                        try:
                            await maintainer.move_files()
@@ -73,6 +73,35 @@ class TestImprovedMotionDetector(unittest.TestCase):
            "Motion boxes should be empty when scene change exceeds skip threshold",
        )

+    def _bright_frame(self, offset: int) -> np.ndarray:
+        """Produce a bright frame with a small dark object that moves."""
+        frame = np.full((self.frame_shape[0], self.frame_shape[1]), 200, dtype=np.uint8)
+        x = 10 + (offset * 5) % 60
+        frame[40:60, x : x + 15] = 20
+        return frame
+
+    def test_skip_motion_threshold_recovers_after_skip(self):
+        """Skipped frames must still be blended into the background.
+
+        A bright scene differs from the zeroed background across the whole
+        frame, so the first frames are skipped. The background has to catch up
+        anyway, otherwise motion detection never returns.
+        """
+        self.config.skip_motion_threshold = 0.5
+        self.config.improve_contrast = False
+        self.detector.config = self.config
+        self.detector.update_mask()
+
+        boxes = [len(self.detector.detect(self._bright_frame(i))) for i in range(40)]
+
+        self.assertEqual(boxes[0], 0, "First frame should exceed the skip threshold")
+        self.assertGreater(
+            self.detector.avg_frame.max(),
+            0,
+            "Background was never updated while frames were skipped",
+        )
+        self.assertTrue(any(boxes), "Motion detection never recovered after a skip")
+
    def test_skip_motion_threshold_does_not_affect_calibration(self):
        """Even when skipping, the detector should go into calibrating state."""
        self.config.skip_motion_threshold = 0.4
@@ -16,9 +16,7 @@ from frigate.test.const import TEST_DB, TEST_DB_CLEANUPS

 # kinds that switch on the lifecycle knobs, so the tests do not depend on the
 # values the real catalog picks
-BATCHED = NoticeKind(
-    "batched", NoticeSeverity.warning, "system", batch_repeats=True, reopen_at_count=3
-)
+BATCHED = NoticeKind("batched", NoticeSeverity.warning, "system", batch_repeats=True)
 PRUNED = NoticeKind("pruned", NoticeSeverity.info, "system", keep_latest=2)
 TEST_KINDS = {kind.key: kind for kind in (BATCHED, PRUNED)}

@@ -77,6 +75,11 @@ class RegistryTestCase(unittest.TestCase):
            mock_datetime.now.return_value.timestamp.return_value = timestamp
            self.registry.raise_notice(kind, **kwargs)

+    def _acknowledge_at(self, timestamp: float, row_id: str) -> None:
+        with patch("frigate.notices.registry.datetime") as mock_datetime:
+            mock_datetime.now.return_value.timestamp.return_value = timestamp
+            self.registry.acknowledge(row_id)
+

 class TestNoticeRegistry(RegistryTestCase):
    def test_raise_inserts_and_counts_one_occurrence(self):
@@ -122,34 +125,98 @@ class TestNoticeRegistry(RegistryTestCase):
        self.assertEqual(self.registry.stats()[0]["occurrences"], 1)
        self.listener.assert_not_called()

-    def test_dismissal_survives_a_re_raise(self):
+    def test_acknowledged_notice_returns_on_a_re_raise(self):
+        self.registry.raise_notice("detector_stuck", scope="ov", params={})
+        self.assertTrue(self.registry.acknowledge("detector_stuck:ov"))
+        self.assertEqual(self.registry.active(), [])
+
+        self.registry.raise_notice("detector_stuck", scope="ov", params={})
+
+        notice = self.registry.active()[0]
+        self.assertEqual(notice["count"], 2)
+        self.assertIsNone(notice["acknowledged_at"])
+
+    def test_muted_notice_stays_hidden_on_a_re_raise(self):
        self.registry.raise_notice("skipped_detections", scope="front_door", params={})
-        self.assertTrue(self.registry.dismiss("skipped_detections:front_door"))
+        self.assertTrue(self.registry.mute("skipped_detections:front_door"))

        self.registry.raise_notice("skipped_detections", scope="front_door", params={})

        self.assertEqual(self.registry.active(), [])
-        history = self.registry.active(include_dismissed=True)
-        self.assertEqual(history[0]["count"], 2)
-        self.assertIsNotNone(history[0]["dismissed_at"])
+        hidden = self.registry.active(include_hidden=True)
+        self.assertEqual(hidden[0]["count"], 2)
+        self.assertIsNotNone(hidden[0]["muted_at"])

-    def test_dismiss_counts_once(self):
+    def test_muting_an_acknowledged_notice_replaces_the_acknowledgement(self):
        self.registry.raise_notice("detector_stuck", scope="ov", params={})
+        self.registry.acknowledge("detector_stuck:ov")

-        self.assertTrue(self.registry.dismiss("detector_stuck:ov"))
-        self.assertTrue(self.registry.dismiss("detector_stuck:ov"))
+        self.assertTrue(self.registry.mute("detector_stuck:ov"))

-        self.assertEqual(self.registry.stats()[0]["dismissals"], 1)
+        notice = self.registry.active(include_hidden=True)[0]
+        self.assertIsNone(notice["acknowledged_at"])
+        self.assertIsNotNone(notice["muted_at"])

-    def test_dismiss_unknown_id(self):
-        self.assertFalse(self.registry.dismiss("nope"))
-
-    def test_dismissed_hidden_unless_requested(self):
+    def test_acknowledging_a_muted_notice_keeps_it_muted(self):
        self.registry.raise_notice("detector_stuck", scope="ov", params={})
-        self.registry.dismiss("detector_stuck:ov")
+        self.registry.mute("detector_stuck:ov")
+
+        self.assertTrue(self.registry.acknowledge("detector_stuck:ov"))
+
+        notice = self.registry.active(include_hidden=True)[0]
+        self.assertIsNone(notice["acknowledged_at"])
+        self.assertIsNotNone(notice["muted_at"])
+
+    def test_acknowledge_and_mute_each_count_once(self):
+        self.registry.raise_notice("detector_stuck", scope="ov", params={})
+        self.registry.raise_notice("shm_too_low", params={})
+
+        self.assertTrue(self.registry.acknowledge("detector_stuck:ov"))
+        self.assertTrue(self.registry.acknowledge("detector_stuck:ov"))
+        self.assertTrue(self.registry.mute("shm_too_low"))
+        self.assertTrue(self.registry.mute("shm_too_low"))
+
+        stats = {s["kind"]: s for s in self.registry.stats()}
+        self.assertEqual(stats["detector_stuck"]["acknowledgements"], 1)
+        self.assertEqual(stats["detector_stuck"]["mutes"], 0)
+        self.assertEqual(stats["shm_too_low"]["mutes"], 1)
+
+    def test_unknown_ids_are_rejected(self):
+        self.assertFalse(self.registry.acknowledge("nope"))
+        self.assertFalse(self.registry.mute("nope"))
+        self.assertFalse(self.registry.unhide("nope"))
+
+    def test_kinds_that_never_repeat_cannot_be_acknowledged(self):
+        self.registry.raise_notice(
+            "update_available", scope="0.19.1", params={"version": "0.19.1"}
+        )
+
+        self.assertFalse(self.registry.acknowledge("update_available:0.19.1"))
+        self.assertFalse(
+            self.registry.acknowledge("config:detect:fps-greater-than-five:global")
+        )
+        self.assertEqual(self.registry.active()[0]["acknowledgeable"], False)
+
+    def test_hidden_notices_listed_only_when_requested(self):
+        self.registry.raise_notice("detector_stuck", scope="ov", params={})
+        self.registry.acknowledge("detector_stuck:ov")

        self.assertEqual(self.registry.active(), [])
-        self.assertEqual(len(self.registry.active(include_dismissed=True)), 1)
+        self.assertEqual(len(self.registry.active(include_hidden=True)), 1)
+
+    def test_unhide_shows_a_notice_and_drops_a_check_mute(self):
+        self.registry.raise_notice("detector_stuck", scope="ov", params={})
+        self.registry.mute("detector_stuck:ov")
+        self.registry.mute("config:detect:fps-greater-than-five:global")
+
+        self.assertTrue(self.registry.unhide("detector_stuck:ov"))
+        self.assertTrue(
+            self.registry.unhide("config:detect:fps-greater-than-five:global")
+        )
+
+        notice = self.registry.active()[0]
+        self.assertIsNone(notice["muted_at"])
+        self.assertEqual(self.registry.muted_checks(), [])

    def test_resolve_deletes_and_keeps_stats(self):
        self.registry.raise_notice(
@@ -160,7 +227,7 @@ class TestNoticeRegistry(RegistryTestCase):
        self.registry.resolve("model_download_failed", "yolo/model.onnx")
        self.registry.resolve("model_download_failed", "yolo/model.onnx")

-        self.assertEqual(self.registry.active(include_dismissed=True), [])
+        self.assertEqual(self.registry.active(include_hidden=True), [])
        self.assertEqual(self.registry.stats()[0]["occurrences"], 1)
        self.listener.assert_called_once()

@@ -237,45 +304,47 @@ class TestNoticeRegistry(RegistryTestCase):
            ids, ["model_download_failed:front_door", "skipped_detections:garage"]
        )

-    def test_resolve_camera_drops_that_cameras_check_dismissals(self):
+    def test_resolve_camera_drops_that_cameras_check_mutes(self):
        for check_id in (
            "stream:front_door:0:probe",
            "config:detect:fps-greater-than-five:camera.front_door",
            "config:detect:fps-greater-than-five:global",
            "stream:garage:0:probe",
        ):
-            self.assertTrue(self.registry.dismiss(check_id))
+            self.assertTrue(self.registry.mute(check_id))

        self.registry.resolve_camera("front_door")

-        ids = sorted(check["id"] for check in self.registry.dismissed_checks())
+        ids = sorted(check["id"] for check in self.registry.muted_checks())
        self.assertEqual(
            ids,
            ["config:detect:fps-greater-than-five:global", "stream:garage:0:probe"],
        )

-    def test_camera_named_global_keeps_global_check_dismissals(self):
-        self.registry.dismiss("config:detect:fps-greater-than-five:global")
-        self.registry.dismiss("config:detect:fps-greater-than-five:camera.global")
+    def test_camera_named_global_keeps_global_check_mutes(self):
+        self.registry.mute("config:detect:fps-greater-than-five:global")
+        self.registry.mute("config:detect:fps-greater-than-five:camera.global")

        self.registry.resolve_camera("global")

-        ids = [check["id"] for check in self.registry.dismissed_checks()]
+        ids = [check["id"] for check in self.registry.muted_checks()]
        self.assertEqual(ids, ["config:detect:fps-greater-than-five:global"])

-    def test_purge_dismissed_keeps_active_notices_and_counts(self):
+    def test_unhide_all_shows_every_notice_and_keeps_counts(self):
        self.registry.raise_notice("detector_stuck", scope="ov", params={})
        self.registry.raise_notice("skipped_detections", scope="garage", params={})
-        self.registry.dismiss("detector_stuck:ov")
-        self.registry.dismiss("config:detect:fps-greater-than-five:camera.garage")
+        self.registry.acknowledge("detector_stuck:ov")
+        self.registry.mute("skipped_detections:garage")
+        self.registry.mute("config:detect:fps-greater-than-five:camera.garage")

-        self.assertEqual(self.registry.purge_dismissed(), 2)
+        self.registry.unhide_all()

-        ids = [n["id"] for n in self.registry.active(include_dismissed=True)]
-        self.assertEqual(ids, ["skipped_detections:garage"])
-        self.assertEqual(self.registry.dismissed_checks(), [])
-        dismissals = {s["kind"]: s["dismissals"] for s in self.registry.stats()}
-        self.assertEqual(dismissals["detector_stuck"], 1)
+        ids = sorted(n["id"] for n in self.registry.active())
+        self.assertEqual(ids, ["detector_stuck:ov", "skipped_detections:garage"])
+        self.assertEqual(self.registry.muted_checks(), [])
+        stats = {s["kind"]: s for s in self.registry.stats()}
+        self.assertEqual(stats["detector_stuck"]["acknowledgements"], 1)
+        self.assertEqual(stats["skipped_detections"]["mutes"], 1)


 class TestApply(RegistryTestCase):
@@ -349,7 +418,7 @@ class TestLifecycleKnobs(RegistryTestCase):

        self.registry.flush()

-        self.assertEqual(self.registry.active(include_dismissed=True), [])
+        self.assertEqual(self.registry.active(include_hidden=True), [])
        self.listener.assert_not_called()

    def test_a_new_row_starts_without_stale_repeats(self):
@@ -362,32 +431,26 @@ class TestLifecycleKnobs(RegistryTestCase):

        self.assertEqual(self.registry.active()[0]["count"], 1)

-    def test_a_dismissed_notice_reopens_at_the_count(self):
-        self.registry.raise_notice("batched")
-        self.registry.dismiss("batched")
+    def test_an_acknowledged_notice_returns_when_a_later_repeat_flushes(self):
+        self._raise_at(1000.0, "batched")
+        self._acknowledge_at(1010.0, "batched")

-        self.registry.raise_notice("batched")
-        self.registry.flush()
+        self._raise_at(1020.0, "batched")
        self.assertEqual(self.registry.active(), [])

-        self.registry.raise_notice("batched")
        self.registry.flush()

-        notice = self.registry.active()[0]
-        self.assertEqual(notice["count"], BATCHED.reopen_at_count)
-        self.assertIsNone(notice["dismissed_at"])
+        self.assertEqual(self.registry.active()[0]["count"], 2)

-    def test_a_notice_dismissed_past_the_count_stays_dismissed(self):
-        for _ in range(3):
-            self.registry.raise_notice("batched")
-        self.registry.flush()
-        self.registry.dismiss("batched")
+    def test_repeats_held_from_before_an_acknowledgement_stay_hidden(self):
+        self._raise_at(1000.0, "batched")
+        self._raise_at(1005.0, "batched")
+        self._acknowledge_at(1010.0, "batched")

-        self.registry.raise_notice("batched")
        self.registry.flush()

        self.assertEqual(self.registry.active(), [])
-        self.assertEqual(self.registry.active(include_dismissed=True)[0]["count"], 4)
+        self.assertEqual(self.registry.active(include_hidden=True)[0]["count"], 2)

    def test_keep_latest_drops_the_oldest_rows(self):
        for index, scope in enumerate(("a", "b", "c")):
@@ -410,14 +473,13 @@ class TestCatalogLifecycles(RegistryTestCase):
        ids = [n["id"] for n in self.registry.active()]
        self.assertEqual(ids, ["update_available:0.19.1"])

-    def test_a_dismissed_failed_login_burst_reopens_at_five_attempts(self):
+    def test_an_acknowledged_failed_login_burst_returns_on_the_next_attempt(self):
        self.registry.raise_notice("failed_login", scope="1000")
-        self.registry.dismiss("failed_login:1000")
+        self.registry.acknowledge("failed_login:1000")

-        for _ in range(4):
-            self.registry.raise_notice("failed_login", scope="1000")
+        self.registry.raise_notice("failed_login", scope="1000")
        self.registry.flush()

        burst = self.registry.active()[0]
-        self.assertEqual(burst["count"], 5)
-        self.assertIsNone(burst["dismissed_at"])
+        self.assertEqual(burst["count"], 2)
+        self.assertIsNone(burst["acknowledged_at"])
@@ -1,5 +1,6 @@
 """Tests for sub stream cache segment handling in the recording maintainer."""

+import asyncio
 import datetime
 import os
 import tempfile
@@ -532,6 +533,59 @@ class TestSegmentStartChaining(unittest.IsolatedAsyncioTestCase):
        self.assertAlmostEqual(calls[1].args[2].timestamp(), self.T0 + 10.4, places=3)
        self.assertAlmostEqual(calls[1].args[3].timestamp(), self.T0 + 20.8, places=3)

+    async def test_out_of_order_probes_chain_in_segment_order(self):
+        maintainer = _build_chaining_maintainer(self.T0)
+
+        async def probe(_ffmpeg, cache_path, get_duration=False):
+            # the earlier segment's probe finishes last
+            if "chain0" in cache_path:
+                await asyncio.sleep(0.05)
+
+            return {"has_valid_video": True, "duration": 10.4}
+
+        recordings = [
+            {
+                "start_time": datetime.datetime.fromtimestamp(
+                    self.T0 + offset, tz=datetime.UTC
+                ),
+                "cache_path": f"/tmp/cache/test_cam@chain{offset}.mp4",
+                "stream_type": "main",
+            }
+            for offset in (0, 10)
+        ]
+        first_resolved = asyncio.Event()
+
+        with (
+            patch("frigate.record.maintainer.get_video_properties", probe),
+            patch(
+                "frigate.record.maintainer.get_keyframe_offsets",
+                AsyncMock(return_value=[0]),
+            ),
+            patch(
+                "frigate.record.maintainer.os.path.getmtime",
+                MagicMock(side_effect=OSError("missing")),
+            ),
+        ):
+            await asyncio.gather(
+                maintainer._validate_in_order(
+                    "test_cam", [], recordings[0], None, first_resolved
+                ),
+                maintainer._validate_in_order(
+                    "test_cam", [], recordings[1], first_resolved, asyncio.Event()
+                ),
+            )
+
+        starts = sorted(
+            call.args[2].timestamp() for call in maintainer.move_segment.await_args_list
+        )
+        self.assertEqual(starts[0], self.T0)
+        self.assertAlmostEqual(starts[1], self.T0 + 10.4, places=3)
+        self.assertAlmostEqual(
+            maintainer.last_segment_end[("test_cam", "main")],
+            self.T0 + 20.8,
+            places=3,
+        )
+
    async def test_genuine_gap_is_not_snapped(self):
        maintainer = _build_chaining_maintainer(self.T0)

@@ -1,10 +1,13 @@
 """Tests for tracker-derived review frame annotations."""

 import unittest
+from unittest.mock import patch

 from frigate.data_processing.post.review_annotations import (
    annotations_by_frame,
+    build_frame_captions,
    build_timeline,
+    describe_classification_change,
    describe_heading,
    describe_position,
    event_name,
@@ -312,5 +315,75 @@ class TestFrameBucketing(unittest.TestCase):
        self.assertEqual(annotations_by_frame([(1.0, "x")], []), {})


+class TestClassificationChangeCaptions(unittest.TestCase):
+    def setUp(self):
+        person = track(
+            "1789481994.684479-lpyc2z",
+            "person",
+            0.0,
+            straight_path((0.9, 0.6), (0.4, 0.3), 10, 0.0),
+        )
+        patcher = patch(
+            "frigate.data_processing.post.review_annotations.get_tracked_events",
+            return_value=[person],
+        )
+        patcher.start()
+        self.addCleanup(patcher.stop)
+        patcher = patch(
+            "frigate.data_processing.post.review_annotations.get_state_changes",
+            return_value=[],
+        )
+        patcher.start()
+        self.addCleanup(patcher.stop)
+
+    def test_change_is_phrased_without_underscores(self):
+        self.assertEqual(
+            describe_classification_change(
+                {"model": "trash_day", "from": "no_bins", "to": "bins_at_curb"}
+            ),
+            "trash day changed from no bins to bins at curb",
+        )
+
+    def test_change_is_noted_before_the_frame_it_precedes(self):
+        change = {"model": "front_gate", "from": "closed", "to": "open"}
+        captions = build_frame_captions(
+            ["1789481994.684479-lpyc2z"],
+            [0.0, 10.0, 20.0],
+            [{**change, "timestamp": 12.0}],
+        )
+        self.assertEqual(
+            captions[2],
+            "Frame 3 of 3 (+20.0s):\n[state] front gate changed from closed to open",
+        )
+        self.assertTrue(captions[0].splitlines()[1].startswith("[tracker] "))
+
+    def test_change_is_noted_without_tracked_objects(self):
+        with patch(
+            "frigate.data_processing.post.review_annotations.get_tracked_events",
+            return_value=[],
+        ):
+            captions = build_frame_captions(
+                [],
+                [0.0, 10.0],
+                [{"model": "gate", "from": "a", "to": "b", "timestamp": 5.0}],
+            )
+
+        self.assertEqual(
+            captions,
+            [
+                "Frame 1 of 2 (+0.0s):",
+                "Frame 2 of 2 (+10.0s):\n[state] gate changed from a to b",
+            ],
+        )
+
+    def test_change_after_the_last_frame_is_dropped(self):
+        captions = build_frame_captions(
+            ["1789481994.684479-lpyc2z"],
+            [0.0, 10.0, 20.0],
+            [{"model": "gate", "from": "a", "to": "b", "timestamp": 25.0}],
+        )
+        self.assertFalse(any("[state]" in caption for caption in captions))
+
+
 if __name__ == "__main__":
    unittest.main()
@@ -0,0 +1,258 @@
+"""Tests for attaching state classification changes to review items."""
+
+import unittest
+from unittest.mock import MagicMock, patch
+
+from frigate.comms.embeddings_updater import EmbeddingsRequestEnum
+from frigate.config import FrigateConfig
+from frigate.data_processing.post.review_descriptions import (
+    ReviewDescriptionProcessor,
+    format_classification_state_changes,
+)
+from frigate.data_processing.real_time.custom_classification import (
+    CustomStateClassificationProcessor,
+)
+from frigate.models import ReviewSegment
+from frigate.review.maintainer import (
+    CLASSIFICATION_STATE_PRE_ROLL,
+    PendingReviewSegment,
+    ReviewSegmentMaintainer,
+)
+from frigate.review.types import SeverityEnum
+
+CONFIG = """
+mqtt:
+  enabled: False
+cameras:
+  front_door:
+    ffmpeg:
+      inputs:
+        - path: rtsp://10.0.0.1:554/video
+          roles:
+            - detect
+    detect:
+      width: 1920
+      height: 1080
+      fps: 5
+"""
+
+
+def gate_change(timestamp: float, before: str = "closed", after: str = "open"):
+    return {"model": "front_gate", "from": before, "to": after, "timestamp": timestamp}
+
+
+class TestVerifyStateChange(unittest.TestCase):
+    def setUp(self):
+        self.processor = CustomStateClassificationProcessor.__new__(
+            CustomStateClassificationProcessor
+        )
+        self.processor.state_history = {}
+
+    def verify(self, state: str, timestamp: float):
+        return self.processor.verify_state_change("front_door", state, timestamp)
+
+    def test_first_verified_state_has_no_previous_state(self):
+        self.assertIsNone(self.verify("closed", 1.0))
+        self.assertIsNone(self.verify("closed", 2.0))
+        self.assertEqual(self.verify("closed", 3.0), (None, 1.0))
+
+    def test_change_reports_previous_state_and_first_sighting(self):
+        for timestamp in (1.0, 2.0, 3.0):
+            self.verify("closed", timestamp)
+
+        self.assertIsNone(self.verify("open", 10.0))
+        self.assertIsNone(self.verify("open", 11.0))
+        self.assertEqual(self.verify("open", 12.0), ("closed", 10.0))
+
+    def test_interrupted_verification_restarts_the_first_sighting(self):
+        for timestamp in (1.0, 2.0, 3.0):
+            self.verify("closed", timestamp)
+
+        self.verify("open", 10.0)
+        self.verify("closed", 11.0)
+        self.verify("open", 20.0)
+        self.verify("open", 21.0)
+        self.assertEqual(self.verify("open", 22.0), ("closed", 20.0))
+
+    def test_reload_forgets_states_the_model_no_longer_has(self):
+        for timestamp in (1.0, 2.0, 3.0):
+            self.verify("closed", timestamp)
+
+        self.processor.state_history["back_door"] = {"current_state": "open"}
+        self.processor.labelmap = {0: "open", 1: "shut"}
+        self.processor._forget_unknown_states()
+
+        self.assertEqual(list(self.processor.state_history), ["back_door"])
+        self.assertIsNone(self.verify("shut", 10.0))
+        self.assertIsNone(self.verify("shut", 11.0))
+        self.assertEqual(self.verify("shut", 12.0), (None, 10.0))
+
+
+class TestReviewSegmentAttachment(unittest.TestCase):
+    def setUp(self):
+        self.maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
+        self.maintainer.config = FrigateConfig.parse_yaml(CONFIG)
+        self.maintainer.active_review_segments = {}
+        self.maintainer.recent_classification_state_changes = {}
+        self.maintainer._publish_segment_update = MagicMock()
+
+    def segment(self, start_time: float) -> PendingReviewSegment:
+        return PendingReviewSegment(
+            "front_door",
+            start_time,
+            SeverityEnum.alert,
+            {"1.0-abcdef": "person"},
+            {},
+            [],
+            set(),
+        )
+
+    def test_change_during_segment_is_attached_and_published(self):
+        segment = self.segment(100.0)
+        self.maintainer.active_review_segments["front_door"] = segment
+
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(110.0)
+        )
+
+        self.assertEqual(segment.classification_state_changes, [gate_change(110.0)])
+        self.maintainer._publish_segment_update.assert_called_once()
+        prev_data = self.maintainer._publish_segment_update.call_args.args[4]
+        self.assertEqual(prev_data["data"]["classification_state_changes"], [])
+        self.assertEqual(
+            segment.get_data(False)["data"]["classification_state_changes"],
+            [gate_change(110.0)],
+        )
+
+    def test_change_never_starts_a_segment(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(110.0)
+        )
+
+        self.assertIsNone(self.maintainer.active_review_segments.get("front_door"))
+        self.maintainer._publish_segment_update.assert_not_called()
+
+    def test_change_just_before_a_segment_is_attached_when_it_starts(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(98.0)
+        )
+        segment = self.segment(100.0)
+
+        self.maintainer._activate_segment(segment)
+
+        self.assertIs(self.maintainer.active_review_segments["front_door"], segment)
+        self.assertEqual(segment.classification_state_changes, [gate_change(98.0)])
+        self.assertNotIn(
+            "front_door", self.maintainer.recent_classification_state_changes
+        )
+
+    def test_change_long_before_a_segment_is_not_attached(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(100.0 - CLASSIFICATION_STATE_PRE_ROLL - 1)
+        )
+        segment = self.segment(100.0)
+
+        self.maintainer._activate_segment(segment)
+
+        self.assertEqual(segment.classification_state_changes, [])
+
+    def test_held_changes_are_pruned(self):
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(10.0)
+        )
+        self.maintainer.handle_classification_state_change(
+            "front_door", gate_change(50.0, "open", "closed")
+        )
+
+        self.assertEqual(
+            self.maintainer.recent_classification_state_changes["front_door"],
+            [gate_change(50.0, "open", "closed")],
+        )
+
+
+class TestChangeTiming(unittest.TestCase):
+    def test_changes_are_placed_relative_to_the_activity(self):
+        lines = format_classification_state_changes(
+            [
+                gate_change(98.0),
+                gate_change(112.4, "open", "closed"),
+                gate_change(140.0),
+            ],
+            start_time=100.0,
+            end_time=130.0,
+        )
+
+        self.assertEqual(
+            lines,
+            [
+                "front gate changed from closed to open, "
+                "just before the activity started",
+                "front gate changed from open to closed, 12s into the activity",
+                "front gate changed from closed to open, after the activity ended",
+            ],
+        )
+
+
+class TestSummaryContext(unittest.TestCase):
+    def row(self, camera, start, end, threat, changes=()):
+        return {
+            "camera": camera,
+            "start_time": start,
+            "end_time": end,
+            "data": {
+                "metadata": {"title": camera, "potential_threat_level": threat},
+                "classification_state_changes": list(changes),
+            },
+        }
+
+    def summarize(self, rows):
+        processor = ReviewDescriptionProcessor.__new__(ReviewDescriptionProcessor)
+        processor.config = FrigateConfig.parse_yaml(CONFIG)
+        processor.genai_manager = MagicMock()
+        client = processor.genai_manager.description_client
+
+        with patch.object(ReviewSegment, "select") as select:
+            query = select.return_value.where.return_value.order_by.return_value
+            query.dicts.return_value.iterator.return_value = iter(rows)
+            processor.handle_request(
+                EmbeddingsRequestEnum.summarize_review.value,
+                {"start_ts": 0, "end_ts": 100},
+            )
+
+        return client.generate_review_summary.call_args.args[2]
+
+    def test_context_state_changes_stay_with_their_review(self):
+        events = self.summarize(
+            [
+                self.row("front_door", 10, 60, 1),
+                self.row("driveway", 15, 25, 0, [gate_change(20.0)]),
+                self.row("driveway", 30, 40, 0, [gate_change(35.0, "open", "closed")]),
+            ]
+        )
+
+        self.assertEqual(
+            [
+                (item["start_time"], item["end_time"], item["state_changes"])
+                for item in events[0]["context"]
+            ],
+            [
+                (15, 25, ["front gate changed from closed to open"]),
+                (30, 40, ["front gate changed from open to closed"]),
+            ],
+        )
+
+    def test_later_context_review_without_changes_is_deduplicated(self):
+        events = self.summarize(
+            [
+                self.row("front_door", 10, 60, 1),
+                self.row("driveway", 15, 25, 0, [gate_change(20.0)]),
+                self.row("driveway", 30, 40, 0),
+            ]
+        )
+
+        self.assertEqual(len(events[0]["context"]), 1)
+        self.assertEqual(events[0]["context"][0]["start_time"], 15)
+
+
+if __name__ == "__main__":
+    unittest.main()
@@ -1,5 +1,7 @@
 """Tests for the device each model runner reports after loading."""

+import os
+import tempfile
 import threading
 import unittest
 from unittest.mock import MagicMock, patch
@@ -38,6 +40,7 @@ class TestRunnerDeviceName(unittest.TestCase):
            self._onnx(["OpenVINOExecutionProvider"]).device_name, "OpenVINO"
        )
        self.assertEqual(self._onnx(["CPUExecutionProvider"]).device_name, "CPU")
+        self.assertEqual(self._onnx(["LighterANE"]).device_name, "Neural Engine")
        self.assertEqual(self._onnx(["ROCMExecutionProvider"]).device_name, "ROCM")
        self.assertEqual(self._onnx([]).device_name, "CPU")

@@ -129,3 +132,147 @@ class TestLoadedDeviceSnapshot(unittest.TestCase):
        finally:
            stop.set()
            thread.join(timeout=5)
+
+
+class TestLighterANE(unittest.TestCase):
+    """lighter's plugin provider, picked up by the ONNX session setup."""
+
+    def setUp(self):
+        loaded_devices.clear()
+        self.root = tempfile.TemporaryDirectory()
+        self.addCleanup(self.root.cleanup)
+        self.library = os.path.join(self.root.name, "liblighter_ane_ep.so")
+        env = patch.dict(os.environ, {"LIGHTER_ANE_EP": self.library})
+        env.start()
+        self.addCleanup(env.stop)
+
+    def _device(self) -> MagicMock:
+        device = MagicMock()
+        device.ep_name = "LighterANE"
+        return device
+
+    def test_no_devices_without_the_library(self):
+        with patch.object(detection_runners.ort, "get_ep_devices") as get_ep_devices:
+            self.assertEqual(detection_runners.get_lighter_ane_devices(), [])
+        get_ep_devices.assert_not_called()
+
+    def test_the_provider_is_registered_once(self):
+        open(self.library, "w").close()
+        device = self._device()
+        other = MagicMock()
+        other.ep_name = "CPUExecutionProvider"
+
+        with (
+            patch.object(
+                detection_runners.ort,
+                "get_ep_devices",
+                side_effect=[[other], [other, device], [other, device]],
+            ),
+            patch.object(
+                detection_runners.ort, "register_execution_provider_library"
+            ) as register,
+        ):
+            self.assertEqual(detection_runners.get_lighter_ane_devices(), [device])
+            self.assertEqual(detection_runners.get_lighter_ane_devices(), [device])
+
+        register.assert_called_once_with("LighterANE", self.library)
+
+    def test_a_provider_that_will_not_load_is_skipped(self):
+        open(self.library, "w").close()
+
+        with (
+            patch.object(detection_runners.ort, "get_ep_devices", return_value=[]),
+            patch.object(
+                detection_runners.ort,
+                "register_execution_provider_library",
+                side_effect=RuntimeError("not a provider"),
+            ),
+        ):
+            self.assertEqual(detection_runners.get_lighter_ane_devices(), [])
+
+    def test_the_session_runs_on_the_neural_engine(self):
+        device = self._device()
+        session = MagicMock()
+        session.get_providers.return_value = ["LighterANE", "CPUExecutionProvider"]
+        options = MagicMock()
+
+        with (
+            patch.object(detection_runners, "is_rknn_compatible", return_value=False),
+            patch.object(
+                detection_runners, "get_lighter_ane_devices", return_value=[device]
+            ),
+            patch.object(
+                detection_runners, "get_ort_session_options", return_value=options
+            ),
+            patch.object(
+                detection_runners.ort, "InferenceSession", return_value=session
+            ) as inference_session,
+        ):
+            runner = get_optimized_runner("/models/yolo.onnx", "AUTO", "yolo-generic")
+
+        options.add_provider_for_devices.assert_called_once_with([device], {})
+        inference_session.assert_called_once_with(
+            "/models/yolo.onnx", sess_options=options
+        )
+        self.assertIsInstance(runner, ONNXModelRunner)
+        self.assertEqual(
+            loaded_devices["/models/yolo.onnx"], ("yolo-generic", "Neural Engine")
+        )
+
+    def test_a_model_the_neural_engine_cannot_load_uses_the_default_providers(self):
+        session = MagicMock()
+        session.get_providers.return_value = ["CPUExecutionProvider"]
+
+        with (
+            patch.object(detection_runners, "is_rknn_compatible", return_value=False),
+            patch.object(
+                detection_runners, "get_lighter_ane_devices", return_value=[MagicMock()]
+            ),
+            patch.object(
+                detection_runners,
+                "get_ort_providers",
+                return_value=(["CPUExecutionProvider"], [{}]),
+            ),
+            patch.object(
+                detection_runners, "is_openvino_gpu_npu_available", return_value=False
+            ),
+            patch.object(
+                detection_runners.ort,
+                "InferenceSession",
+                side_effect=[RuntimeError("unsupported"), session],
+            ) as inference_session,
+            patch.object(
+                detection_runners, "get_ort_session_options", return_value=MagicMock()
+            ),
+            self.assertLogs(detection_runners.logger, level="WARNING"),
+        ):
+            runner = get_optimized_runner("/models/jina.onnx", "AUTO", "jina-v2")
+
+        self.assertEqual(inference_session.call_count, 2)
+        self.assertIsInstance(runner, ONNXModelRunner)
+        self.assertEqual(loaded_devices["/models/jina.onnx"], ("jina-v2", "CPU"))
+
+    def test_a_cpu_model_stays_on_the_cpu(self):
+        session = MagicMock()
+        session.get_providers.return_value = ["CPUExecutionProvider"]
+
+        with (
+            patch.object(detection_runners, "is_rknn_compatible", return_value=False),
+            patch.object(
+                detection_runners, "get_lighter_ane_devices", return_value=[MagicMock()]
+            ) as ane,
+            patch.object(
+                detection_runners,
+                "get_ort_providers",
+                return_value=(["CPUExecutionProvider"], [{}]),
+            ),
+            patch.object(
+                detection_runners.ort, "InferenceSession", return_value=session
+            ),
+            patch.object(
+                detection_runners, "get_ort_session_options", return_value=None
+            ),
+        ):
+            get_optimized_runner("/models/arcface.onnx", "CPU", "arcface")
+
+        ane.assert_not_called()
@@ -1,10 +1,14 @@
-"""Tests for the skipped detection rate and the notice it can raise."""
+"""Tests for the per-camera episode notices: skipped detections and high CPU."""

 import unittest
-from unittest.mock import patch
+from unittest.mock import call, patch

 from frigate.stats import emitter
-from frigate.stats.emitter import SkippedDetectionsTracker
+from frigate.stats.emitter import (
+    SKIPPED_DETECTIONS_PCT,
+    EpisodeTracker,
+    cpu_average,
+)
 from frigate.stats.util import skipped_percent


@@ -19,18 +23,18 @@ class TestSkippedPercent(unittest.TestCase):
        self.assertEqual(skipped_percent(2.0, 5.0, False), 0.0)


-class TestSkippedDetectionsTracker(unittest.TestCase):
+class TestEpisodeTracker(unittest.TestCase):
    def _cameras(self, pct: float) -> dict:
-        return {"front_door": {"skipped_pct": pct}}
+        return {"front_door": pct}

    def test_below_threshold_never_qualifies(self):
-        tracker = SkippedDetectionsTracker()
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)

        for tick in range(10):
            self.assertEqual(tracker.update(self._cameras(4.9), tick * 15.0), [])

    def test_qualifies_once_after_the_hold(self):
-        tracker = SkippedDetectionsTracker()
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)

        results = [
            tracker.update(self._cameras(10.0), tick * 15.0) for tick in range(8)
@@ -42,7 +46,7 @@ class TestSkippedDetectionsTracker(unittest.TestCase):
        self.assertEqual(results[5:], [[], [], []])

    def test_a_dip_restarts_the_hold(self):
-        tracker = SkippedDetectionsTracker()
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)

        for now, pct in ((0.0, 10.0), (15.0, 10.0), (30.0, 10.0), (45.0, 2.0)):
            self.assertEqual(tracker.update(self._cameras(pct), now), [])
@@ -51,7 +55,7 @@ class TestSkippedDetectionsTracker(unittest.TestCase):
        self.assertEqual(tracker.update(self._cameras(10.0), 120.0), ["front_door"])

    def test_recovery_then_relapse_is_a_new_episode(self):
-        tracker = SkippedDetectionsTracker()
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)
        tracker.update(self._cameras(10.0), 0.0)
        self.assertEqual(tracker.update(self._cameras(10.0), 60.0), ["front_door"])

@@ -61,17 +65,15 @@ class TestSkippedDetectionsTracker(unittest.TestCase):
        self.assertEqual(tracker.update(self._cameras(10.0), 150.0), ["front_door"])

    def test_cameras_are_tracked_separately(self):
-        tracker = SkippedDetectionsTracker()
-        tracker.update({"a": {"skipped_pct": 10.0}, "b": {"skipped_pct": 0.0}}, 0.0)
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)
+        tracker.update({"a": 10.0, "b": 0.0}, 0.0)

-        qualified = tracker.update(
-            {"a": {"skipped_pct": 10.0}, "b": {"skipped_pct": 10.0}}, 60.0
-        )
+        qualified = tracker.update({"a": 10.0, "b": 10.0}, 60.0)

        self.assertEqual(qualified, ["a"])

    def test_a_removed_camera_starts_a_new_episode(self):
-        tracker = SkippedDetectionsTracker()
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)
        tracker.update(self._cameras(10.0), 0.0)
        tracker.update({}, 15.0)
        tracker.update(self._cameras(10.0), 30.0)
@@ -79,6 +81,25 @@ class TestSkippedDetectionsTracker(unittest.TestCase):
        self.assertEqual(tracker.update(self._cameras(10.0), 60.0), [])
        self.assertEqual(tracker.update(self._cameras(10.0), 90.0), ["front_door"])

+    def test_a_missing_value_ends_the_episode(self):
+        tracker = EpisodeTracker(SKIPPED_DETECTIONS_PCT)
+        tracker.update(self._cameras(10.0), 0.0)
+        tracker.update({"front_door": None}, 30.0)
+
+        self.assertEqual(tracker.update(self._cameras(10.0), 60.0), [])
+
+
+class TestCpuAverage(unittest.TestCase):
+    def test_reads_the_lifetime_average(self):
+        usages = {"42": {"cpu": "80.0", "cpu_average": "25.0"}}
+
+        self.assertEqual(cpu_average(usages, 42), 25.0)
+
+    def test_unknown_process_has_no_average(self):
+        self.assertIsNone(cpu_average({}, 42))
+        self.assertIsNone(cpu_average({"42": {"cpu_average": "25.0"}}, None))
+        self.assertIsNone(cpu_average({"42": {"cpu_average": ""}}, 42))
+

 class TestEmitterNotices(unittest.TestCase):
    def setUp(self):
@@ -94,15 +115,25 @@ class TestEmitterNotices(unittest.TestCase):

    def _emitter(self) -> emitter.StatsEmitter:
        stats_emitter = emitter.StatsEmitter.__new__(emitter.StatsEmitter)
-        stats_emitter.skipped_detections = SkippedDetectionsTracker()
+        stats_emitter.skipped_detections = EpisodeTracker(SKIPPED_DETECTIONS_PCT)
+        stats_emitter.ffmpeg_cpu = EpisodeTracker(emitter.FFMPEG_HIGH_CPU_PCT)
+        stats_emitter.detect_cpu = EpisodeTracker(emitter.DETECT_HIGH_CPU_PCT)
        stats_emitter._shm_checked = False
        stats_emitter._shm_params = None
        return stats_emitter

-    def _stats(self, uptime: int, pct: float) -> dict:
+    def _stats(
+        self, uptime: int, pct: float, ffmpeg_cpu: str = "5.0", detect_cpu: str = "5.0"
+    ) -> dict:
        return {
            "service": {"uptime": uptime, "storage": {"/dev/shm": {}}},
-            "cameras": {"front_door": {"skipped_pct": pct}},
+            "cameras": {
+                "front_door": {"skipped_pct": pct, "ffmpeg_pid": 10, "pid": 11}
+            },
+            "cpu_usages": {
+                "10": {"cpu_average": ffmpeg_cpu},
+                "11": {"cpu_average": detect_cpu},
+            },
        }

    def test_qualified_camera_raises_a_notice(self):
@@ -115,6 +146,43 @@ class TestEmitterNotices(unittest.TestCase):
            "skipped_detections", scope="front_door", params={"pct": 12.5}
        )

+    def test_high_cpu_raises_a_notice_per_process(self):
+        stats_emitter = self._emitter()
+
+        for uptime, now in ((300, 0.0), (360, 60.0)):
+            stats_emitter._update_notices(
+                self._stats(uptime, 0.0, ffmpeg_cpu="25.0", detect_cpu="45.0"), now
+            )
+
+        self.assertEqual(
+            self.raise_notice.call_args_list,
+            [
+                call("ffmpeg_high_cpu", scope="front_door", params={"cpu": 25.0}),
+                call("detect_high_cpu", scope="front_door", params={"cpu": 45.0}),
+            ],
+        )
+
+    def test_cpu_below_each_threshold_raises_nothing(self):
+        stats_emitter = self._emitter()
+
+        for uptime, now in ((300, 0.0), (360, 60.0)):
+            stats_emitter._update_notices(
+                self._stats(uptime, 0.0, ffmpeg_cpu="19.0", detect_cpu="39.0"), now
+            )
+
+        self.raise_notice.assert_not_called()
+
+    def test_missing_cpu_stats_raise_nothing(self):
+        stats_emitter = self._emitter()
+
+        for uptime, now in ((300, 0.0), (360, 60.0)):
+            stats = self._stats(uptime, 0.0)
+            del stats["cpu_usages"]
+            stats_emitter._update_notices(stats, now)
+
+        self.raise_notice.assert_not_called()
+        self.assertEqual(self.flush_notices.call_count, 2)
+
    def test_startup_window_is_ignored(self):
        stats_emitter = self._emitter()

@@ -324,9 +324,7 @@ class NorfairTracker(ObjectTracker):
        ):
            tracker = self.get_tracker(obj["label"])
            tracker.tracked_objects = [
-                o
-                for o in tracker.tracked_objects
-                if str(o.global_id) != track_id and o.hit_counter < 0
+                o for o in tracker.tracked_objects if str(o.global_id) != track_id
            ]

        del self.track_id_map[track_id]
@@ -56,10 +56,13 @@ class EventsPerSecond:
            self._start = now
        # compute the (approximate) events in the last n seconds
        self.expire_timestamps(now)
-        seconds = min(now - self._start, self._last_n_seconds)
-        # avoid divide by zero
-        if seconds == 0:
-            seconds = 1
+        # rate over at least one second (or the whole window, if shorter),
+        # so a burst of events right after start() is not divided by a
+        # tiny window
+        seconds = max(
+            min(now - self._start, self._last_n_seconds),
+            min(1.0, self._last_n_seconds),
+        )
        return len(self._timestamps) / seconds

    # remove aged out timestamps
@@ -14,6 +14,10 @@ from frigate.util.file import FileLock

 logger = logging.getLogger(__name__)

+# (connect, read) seconds. The read timeout bounds each socket read rather than
+# the whole download, so large models still finish.
+DOWNLOAD_TIMEOUT = (15, 60)
+
 # target path -> first line of the last download error for it; every existing
 # download function swallows its exceptions, so this is how the downloader
 # thread learns why a file is still missing
@@ -124,7 +128,9 @@ class ModelDownloader:
            logger.info(f"Downloading model file from: {url}")

        try:
-            with requests.get(url, stream=True, allow_redirects=True) as r:
+            with requests.get(
+                url, stream=True, allow_redirects=True, timeout=DOWNLOAD_TIMEOUT
+            ) as r:
                r.raise_for_status()
                with open(temporary_filename, "wb") as f:
                    for chunk in r.iter_content(chunk_size=8192):
@@ -49,6 +49,9 @@ def start_or_restart_ffmpeg(
    if ffmpeg_process is not None:
        stop_ffmpeg(ffmpeg_process, logger)

+        # flush after the stop so the logs cover ffmpeg's output up to exit
+        logpipe.dump()
+
    if frame_size is None:
        process = sp.Popen(
            ffmpeg_cmd,
@@ -9,6 +9,7 @@ and resolve it per camera against that camera's detect stream.
 """

 import logging
+import os
 import re

 from pydantic import BaseModel, Field
@@ -23,14 +24,20 @@ from frigate.util.services import enumerate_drm_devices

 logger = logging.getLogger(__name__)

-# root the /proc reads use, so tests can point them at a fixture tree
+# roots the /proc and /sys reads use, so tests can point them at a fixture tree
 PROC_ROOT = "/proc"
+SYS_ROOT = "/sys"

 ANY_CODEC = "any"

 # a Raspberry Pi has no detection hardware of its own, so it gets a key here
 RASPBERRY_PI = "raspberrypi"

+# lighter (https://github.com/fieldwork-ai/lighter) decodes on a Mac's media
+# engine through virtio-media devices, which carry its virtio vendor id "LGHT"
+LIGHTER_MEDIA = "lighter"
+LIGHTER_VIRTIO_VENDOR = "0x4c474854"
+
 # ffprobe names h265 streams hevc
 CODEC_ALIASES = {"hevc": "h265"}

@@ -52,6 +59,7 @@ DECODE_HARDWARE = (
    "rknn",
    "openvino:GPU",
    "onnx:amd",
+    LIGHTER_MEDIA,
    RASPBERRY_PI,
 )

@@ -98,6 +106,10 @@ FAMILY_RPI = HwaccelFamily(
    key="rpi",
    presets={"h264": "preset-rpi-64-h264", "h265": "preset-rpi-64-h265"},
 )
+FAMILY_APPLE = HwaccelFamily(
+    key="apple-silicon",
+    presets={"h264": "preset-apple-silicon-h264", "h265": "preset-apple-silicon-h265"},
+)


 def _read(path: str) -> str | None:
@@ -139,6 +151,20 @@ def _is_raspberry_pi() -> bool:
    return "raspberrypi" in compatible


+def _has_lighter_media() -> bool:
+    video = f"{SYS_ROOT}/class/video4linux"
+
+    try:
+        devices = os.listdir(video)
+    except OSError:
+        return False
+
+    return any(
+        _read(f"{video}/{device}/device/vendor") == LIGHTER_VIRTIO_VENDOR
+        for device in devices
+    )
+
+
 def _intel_families(generation: int | None) -> list[HwaccelFamily]:
    """vaapi drives every Intel GPU, qsv only those from gen8 on."""
    if generation is not None and generation < INTEL_QSV_SUPPORTED_GEN:
@@ -164,6 +190,9 @@ def _families(key: str, generation: int | None) -> list[HwaccelFamily]:
    if key == "onnx:amd":
        return [FAMILY_VAAPI]

+    if key == LIGHTER_MEDIA:
+        return [FAMILY_APPLE]
+
    if key == RASPBERRY_PI:
        return [FAMILY_RPI]

@@ -193,6 +222,9 @@ def _decode_hardware(detector_key: str | None) -> list[str]:
    """
    present = {found.key for found in hardware_prober.probe()}

+    if _has_lighter_media():
+        present.add(LIGHTER_MEDIA)
+
    if _is_raspberry_pi():
        present.add(RASPBERRY_PI)

@@ -213,17 +213,19 @@ def stream_has_audio(intervals: list[CoverageInterval], main: bool) -> bool:
    )


-def null_audio_glitches(
-    intervals: list[CoverageInterval], main_audio: bool, sub_audio: bool
-) -> list[CoverageInterval]:
+def null_audio_glitches(intervals: list[CoverageInterval]) -> list[CoverageInterval]:
    """Treat video-only glitch rows on audio-bearing streams as no recording.

    nginx-vod requires every clip in a sequence to carry the same track
    count, so a truncated video-only segment (a backend restart can flush
    a sub-second file before any audio packet landed) poisons every
    manifest that includes it. Nulling the row turns the glitch into a
-    hole the span builder skips like any recording gap.
+    hole the span builder skips like any recording gap. Every consumer of
+    a window's coverage (the vod manifest, its realized timelines, and
+    exports) goes through here, so they all agree on which rows exist.
    """
+    main_audio = stream_has_audio(intervals, main=True)
+    sub_audio = stream_has_audio(intervals, main=False)
    result: list[CoverageInterval] = []
    for interval in intervals:
        main = interval.main
@@ -449,9 +451,7 @@ def realized_timelines(
    assembles each variant's realized spans. Keyframe snapping reads the
    per-row index stored at record time, so no file is touched.
    """
-    main_audio = stream_has_audio(intervals, main=True)
-    sub_audio = stream_has_audio(intervals, main=False)
-    nulled = null_audio_glitches(intervals, main_audio, sub_audio)
+    nulled = null_audio_glitches(intervals)

    return {
        "auto": realized_timeline(nulled, None),
@@ -319,9 +319,6 @@ class CameraWatchdog(threading.Thread):
                    f"Capture thread for {self.config.name} did not exit in time"
                )

-        self.logger.error(
-            "The following ffmpeg logs include the last 100 lines prior to exit."
-        )
        self.logpipe.dump()
        self.logger.info("Restarting ffmpeg...")
        self.start_ffmpeg_detect()
@@ -543,7 +540,6 @@ class CameraWatchdog(threading.Thread):
                        f"{self.config.name}/status/{role.value}", "offline"
                    )

-                p["logpipe"].dump()
                p["process"] = start_or_restart_ffmpeg(
                    p["cmd"], self.logger, p["logpipe"], ffmpeg_process=p["process"]
                )
@@ -18,18 +18,21 @@ def migrate(migrator, database, fake=False, **kwargs):
        '"first_seen" DATETIME NOT NULL, '
        '"last_seen" DATETIME NOT NULL, '
        '"count" INTEGER NOT NULL, '
-        '"dismissed_at" DATETIME)'
+        '"acknowledged_at" DATETIME, '
+        '"muted_at" DATETIME)'
    )
    migrator.sql('CREATE INDEX IF NOT EXISTS "notice_kind" ON "notice" ("kind")')
    migrator.sql(
        'CREATE TABLE IF NOT EXISTS "noticestats" ('
        '"kind" VARCHAR(50) NOT NULL PRIMARY KEY, '
        '"occurrences" INTEGER NOT NULL, '
-        '"dismissals" INTEGER NOT NULL, '
+        '"acknowledgements" INTEGER NOT NULL, '
+        '"mutes" INTEGER NOT NULL, '
        '"first_seen" DATETIME NOT NULL, '
        '"last_seen" DATETIME NOT NULL, '
        '"reported_occurrences" INTEGER NOT NULL DEFAULT 0, '
-        '"reported_dismissals" INTEGER NOT NULL DEFAULT 0)'
+        '"reported_acknowledgements" INTEGER NOT NULL DEFAULT 0, '
+        '"reported_mutes" INTEGER NOT NULL DEFAULT 0)'
    )


@@ -49,7 +49,7 @@ export interface ApiMockOverrides {
  };
  users?: { username: string; role: string }[];
  notices?: unknown[];
-  dismissedChecks?: unknown[];
+  mutedChecks?: unknown[];
  /** camera name to the ffprobe entries returned for `paths=camera:<name>` */
  ffprobe?: Record<string, unknown[]>;
 }
@@ -238,8 +238,8 @@ export class ApiMocker {
    await this.page.route("**/api/notices", (route) =>
      route.fulfill({ json: overrides?.notices ?? [] }),
    );
-    await this.page.route("**/api/notices/dismissed_checks", (route) =>
-      route.fulfill({ json: overrides?.dismissedChecks ?? [] }),
+    await this.page.route("**/api/notices/muted_checks", (route) =>
+      route.fulfill({ json: overrides?.mutedChecks ?? [] }),
    );

    // Users. GET lists them; POST/PUT (create, password) just succeed, so
@@ -0,0 +1,204 @@
+/**
+ * Helpers for the live dashboard's draggable grid layout: reading and seeding
+ * the persisted layout, and measuring rendered tiles.
+ *
+ * DraggableGridLayout persists through useUserPersistence, which namespaces
+ * keys by username, and every write is an async idb put. A test that seeds the
+ * bare key, or seeds before the app's own first write has landed, silently
+ * asserts against a key the app never reads. persistedLayoutKey() closes both
+ * holes, so prefer it over building the key by hand.
+ *
+ * Geometry has its own trap: the grid first lays out against window.innerWidth,
+ * then reflows narrower once useResizeObserver reports the real container.
+ * Tiles measured in separate round-trips can straddle that reflow and disagree
+ * on scale, so cameraBoxes() takes every measurement in one evaluate.
+ *
+ * Used by live-grid-aspect-modes.spec.ts and masonry-live-grid.spec.ts.
+ */
+
+import { expect, type Page } from "@playwright/test";
+
+export type LayoutItem = {
+  i: string;
+  x: number;
+  y: number;
+  w: number;
+  h: number;
+};
+
+export type PersistedLayout = {
+  version: number;
+  naturalAspect: boolean;
+  layout: LayoutItem[];
+};
+
+function layoutKeySuffix(group: string): string {
+  return `${group}-draggable-layout`;
+}
+
+/**
+ * The key the app has actually written an envelope to, or undefined while its
+ * first write is still in flight.
+ */
+function findWrittenKey(
+  page: Page,
+  group: string,
+): Promise<string | undefined> {
+  return page.evaluate(
+    (suffix) =>
+      new Promise<string | undefined>((resolve) => {
+        const open = indexedDB.open("keyval-store");
+        open.onsuccess = () => {
+          const store = open.result
+            .transaction("keyval", "readonly")
+            .objectStore("keyval");
+          // getAllKeys and getAll both return in key order, so the indexes align
+          const keys = store.getAllKeys();
+          const values = store.getAll();
+          keys.transaction.oncomplete = () => {
+            open.result.close();
+            const names = keys.result as string[];
+            const stored = values.result as { version?: number }[];
+            const match = names.findIndex(
+              (name, index) =>
+                (name === suffix || name.startsWith(`${suffix}:`)) &&
+                typeof stored[index]?.version === "number",
+            );
+            resolve(match === -1 ? undefined : names[match]);
+          };
+        };
+        open.onerror = () => resolve(undefined);
+      }),
+    layoutKeySuffix(group),
+  );
+}
+
+/**
+ * Wait for the grid to persist its own layout, then return the key it used.
+ * Waiting for that write is what makes a later seed meaningful: it proves the
+ * key is live, and it rules out the app overwriting the seed a moment later.
+ */
+export async function persistedLayoutKey(
+  page: Page,
+  group: string,
+): Promise<string> {
+  let key: string | undefined;
+
+  await expect
+    .poll(async () => (key = await findWrittenKey(page, group)), {
+      timeout: 10_000,
+      message: `grid never persisted a layout for group "${group}"`,
+    })
+    .not.toBeUndefined();
+
+  return key!;
+}
+
+/** Overwrite the stored layout, resolving only once the put has committed. */
+export function seedLayout(
+  page: Page,
+  key: string,
+  value: unknown,
+): Promise<void> {
+  return page.evaluate(
+    ([key, value]) =>
+      new Promise<void>((resolve, reject) => {
+        const open = indexedDB.open("keyval-store");
+        open.onupgradeneeded = () => open.result.createObjectStore("keyval");
+        open.onsuccess = () => {
+          const tx = open.result.transaction("keyval", "readwrite");
+          tx.objectStore("keyval").put(value, key as string);
+          tx.oncomplete = () => {
+            open.result.close();
+            resolve();
+          };
+          tx.onerror = () => reject(tx.error);
+        };
+        open.onerror = () => reject(open.error);
+      }),
+    [key, value] as const,
+  );
+}
+
+/** Read the stored layout back. Undefined until the app writes it. */
+export function readLayout(
+  page: Page,
+  key: string,
+): Promise<PersistedLayout | undefined> {
+  return page.evaluate(
+    (target) =>
+      new Promise((resolve) => {
+        const open = indexedDB.open("keyval-store");
+        open.onsuccess = () => {
+          const tx = open.result.transaction("keyval", "readonly");
+          const request = tx.objectStore("keyval").get(target);
+          tx.oncomplete = () => {
+            open.result.close();
+            resolve(request.result);
+          };
+        };
+        open.onerror = () => resolve(undefined);
+      }),
+    key,
+  ) as Promise<PersistedLayout | undefined>;
+}
+
+export type Box = { w: number; h: number; x: number; y: number };
+
+/** The card is the player root; the cell is the grid slot it sits in. */
+export type BoxTarget = "card" | "cell";
+
+/** One atomic snapshot, or null while any tile is missing or unlaid out. */
+function snapshotBoxes(
+  page: Page,
+  cameras: readonly string[],
+  target: BoxTarget,
+): Promise<Record<string, Box> | null> {
+  return page.evaluate(
+    ({ cams, target }) => {
+      const boxes: Record<string, Box> = {};
+
+      for (const cam of cams) {
+        const card = document.querySelector(`[data-camera='${cam}']`);
+        const el = target === "cell" ? card?.closest(".p-1") : card;
+
+        if (!el) {
+          return null;
+        }
+
+        const r = el.getBoundingClientRect();
+
+        // a re-rendering tile can briefly report no box at all
+        if (!r.width || !r.height) {
+          return null;
+        }
+
+        boxes[cam] = { w: r.width, h: r.height, x: r.x, y: r.y };
+      }
+
+      return boxes;
+    },
+    { cams: cameras as readonly string[], target },
+  );
+}
+
+/**
+ * Measure the given cameras' tiles together, once they have all rendered.
+ * Measuring in one evaluate is what keeps the numbers mutually comparable.
+ */
+export async function cameraBoxes<T extends string>(
+  page: Page,
+  cameras: readonly T[],
+  target: BoxTarget = "cell",
+): Promise<Record<T, Box>> {
+  let boxes: Record<string, Box> | null = null;
+
+  await expect
+    .poll(async () => (boxes = await snapshotBoxes(page, cameras, target)), {
+      timeout: 10_000,
+      message: `${target}s never rendered for ${cameras.join(", ")}`,
+    })
+    .not.toBeNull();
+
+  return boxes as unknown as Record<T, Box>;
+}
@@ -56,3 +56,14 @@ export async function waitForErrorMarker(
    .poll(() => hasErrorMarkers(page), { timeout: timeoutMs })
    .toBe(true);
 }
+
+/**
+ * Append a trailing comment so the editor content differs from the
+ * loaded config. The save buttons are disabled until then.
+ */
+export async function makeMonacoEdit(page: Page): Promise<void> {
+  const editor = page.locator(".monaco-editor").first();
+  await editor.click();
+  await page.keyboard.press("ControlOrMeta+End");
+  await page.keyboard.type("# edited by e2e", { delay: 0 });
+}
@@ -45,6 +45,11 @@ export class LivePage extends BasePage {
    );
  }

+  /** Edit-layout toggle on the draggable grid (desktop, custom groups). */
+  get editLayoutButton(): Locator {
+    return this.page.getByTestId("toggle-edit-layout");
+  }
+
  /** Open the right-click context menu on a camera card (desktop only). */
  async openContextMenuOn(cameraName: string): Promise<Locator> {
    await this.cameraCard(cameraName).first().click({ button: "right" });
@@ -11,6 +11,7 @@ import { installWsFrameCapture, waitForWsFrame } from "../helpers/ws-frames";
 import { grantClipboardPermissions, readClipboard } from "../helpers/clipboard";
 import {
  getMonacoVisibleText,
+  makeMonacoEdit,
  replaceMonacoValue,
  waitForErrorMarker,
 } from "../helpers/monaco";
@@ -71,6 +72,7 @@ test.describe("Config Editor — Save @medium", () => {
    await expect(frigateApp.page.locator(".monaco-editor").first()).toBeVisible(
      { timeout: 15_000 },
    );
+    await makeMonacoEdit(frigateApp.page);
    await frigateApp.page.getByLabel("Save Only").click();
    await expect
      .poll(() => capture.capturedUrl(), { timeout: 5_000 })
@@ -92,6 +94,7 @@ test.describe("Config Editor — Save @medium", () => {
    await expect(frigateApp.page.locator(".monaco-editor").first()).toBeVisible(
      { timeout: 15_000 },
    );
+    await makeMonacoEdit(frigateApp.page);
    await frigateApp.page.getByLabel("Save Only").click();
    await expect(frigateApp.page.getByText(/Invalid field/i)).toBeVisible({
      timeout: 5_000,
@@ -117,6 +120,7 @@ test.describe("Config Editor — Save and Restart @medium", () => {
      { timeout: 15_000 },
    );

+    await makeMonacoEdit(frigateApp.page);
    await frigateApp.page.getByLabel("Save & Restart").click();
    const dialog = frigateApp.page.getByRole("alertdialog");
    await expect(dialog).toBeVisible({ timeout: 5_000 });
@@ -140,6 +144,7 @@ test.describe("Config Editor — Save and Restart @medium", () => {
      { timeout: 15_000 },
    );

+    await makeMonacoEdit(frigateApp.page);
    await frigateApp.page.getByLabel("Save & Restart").click();
    const dialog = frigateApp.page.getByRole("alertdialog");
    await expect(dialog).toBeVisible({ timeout: 5_000 });
@@ -0,0 +1,185 @@
+/**
+ * Live grid aspect modes.
+ *
+ * Bucketed mode (the default) snaps every camera to a wide, landscape or tall
+ * tile, and converts layouts saved by pre-masonry versions instead of
+ * discarding them. Natural mode sizes each tile to its own camera.
+ */
+
+import { test, expect } from "../fixtures/frigate-test";
+import { LivePage } from "../pages/live.page";
+import {
+  cameraBoxes,
+  persistedLayoutKey,
+  readLayout,
+  seedLayout,
+  type LayoutItem,
+} from "../helpers/grid-layout";
+
+const GROUP = "outdoor";
+const GRID_COLS = 96;
+
+test.describe("Live grid aspect modes @critical", () => {
+  test.skip(
+    ({ frigateApp }) => frigateApp.isMobile,
+    "Draggable grid is desktop-only",
+  );
+
+  test("an ultra-wide camera gets a 32:9 tile in bucketed mode @mobile", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.installDefaults({
+      config: {
+        cameras: { backyard: { detect: { width: 2560, height: 720 } } },
+      },
+    });
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("backyard").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    const { backyard: wide, front_door: normal } = await cameraBoxes(
+      frigateApp.page,
+      ["backyard", "front_door"] as const,
+    );
+
+    expect(wide.w / wide.h).toBeCloseTo(32 / 9, 1);
+    expect(wide.w / normal.w).toBeCloseTo(2, 1);
+    expect(wide.h).toBeCloseTo(normal.h, 0);
+  });
+
+  test("a letterboxed still image rounds its own corners", async ({
+    frigateApp,
+  }) => {
+    // A portrait camera pillarboxes inside its 8:9 bucket, so the card's
+    // overflow-hidden clip never reaches the picture's corners. The image has
+    // to carry the radius itself or it renders with square edges on the tile.
+    await frigateApp.installDefaults({
+      config: {
+        cameras: { backyard: { detect: { width: 720, height: 1280 } } },
+      },
+    });
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("backyard").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    const radii = await frigateApp.page.evaluate(() => {
+      const card = document.querySelector("[data-camera='backyard']");
+      const img = card?.querySelector("img");
+      return {
+        card: card ? getComputedStyle(card).borderTopLeftRadius : null,
+        img: img ? getComputedStyle(img).borderTopLeftRadius : null,
+      };
+    });
+
+    expect(radii.card).not.toBe("0px");
+    expect(radii.img).toBe(radii.card);
+  });
+
+  test("a pre-masonry layout is converted, keeping resized tiles", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // 0.17/0.18 shape: bare array on a 12-column grid, 4x4 standard tiles.
+    // backyard was manually resized to 8x8 and sits beside front_door's column,
+    // front_door is a standard tile on the row below.
+    const key = await persistedLayoutKey(frigateApp.page, GROUP);
+    await seedLayout(frigateApp.page, key, [
+      { i: "backyard", x: 4, y: 0, w: 8, h: 8, moved: false, static: false },
+      { i: "front_door", x: 0, y: 8, w: 4, h: 4, moved: false, static: false },
+    ]);
+    await frigateApp.page.reload();
+    await frigateApp.page.waitForSelector("#pageRoot", { timeout: 10_000 });
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // The conversion is written back on first load, replacing the legacy array
+    // with an envelope. Poll for it: that write is an async idb put.
+    await expect
+      .poll(async () => (await readLayout(frigateApp.page, key))?.version, {
+        timeout: 10_000,
+      })
+      .toBe(2);
+
+    const stored = (await readLayout(frigateApp.page, key))!;
+    expect(stored).toMatchObject({ version: 2, naturalAspect: false });
+
+    // x and w scale 8x (12 -> 96 columns), y and h scale 18x (4 -> 72 rows per
+    // standard tile), so the manual resize survives instead of snapping back.
+    expect(
+      stored.layout.find((i: LayoutItem) => i.i === "backyard"),
+    ).toMatchObject({
+      x: 32,
+      y: 0,
+      w: 64,
+      h: 144,
+    });
+    expect(
+      stored.layout.find((i: LayoutItem) => i.i === "front_door"),
+    ).toMatchObject({
+      x: 0,
+      y: 144,
+      w: 32,
+      h: 72,
+    });
+
+    // arrangement on screen: backyard indented, front_door below it
+    const { backyard, front_door: frontDoor } = await cameraBoxes(
+      frigateApp.page,
+      ["backyard", "front_door"] as const,
+    );
+    expect(backyard.x).toBeGreaterThan(frontDoor.x + frontDoor.w / 2);
+    expect(frontDoor.y).toBeGreaterThan(backyard.y + backyard.h / 2);
+  });
+
+  test("conversion is a pure scale, so odd sizes and positions survive", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // The old grid exposed all four resize corners with no aspect constraint,
+    // so a stored tile can be any size. These two are adjacent and non-standard.
+    const key = await persistedLayoutKey(frigateApp.page, GROUP);
+    await seedLayout(frigateApp.page, key, [
+      { i: "front_door", x: 0, y: 3, w: 5, h: 5 },
+      { i: "backyard", x: 5, y: 3, w: 7, h: 5 },
+    ]);
+    await frigateApp.page.reload();
+    await frigateApp.page.waitForSelector("#pageRoot", { timeout: 10_000 });
+    await expect(live.cameraCard("backyard").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    await expect
+      .poll(async () => (await readLayout(frigateApp.page, key))?.version, {
+        timeout: 10_000,
+      })
+      .toBe(2);
+
+    const stored = (await readLayout(frigateApp.page, key))!;
+    const frontDoor = stored.layout.find(
+      (i: LayoutItem) => i.i === "front_door",
+    )!;
+    const backyard = stored.layout.find((i: LayoutItem) => i.i === "backyard")!;
+
+    expect(frontDoor).toMatchObject({ x: 0, y: 54, w: 40, h: 90 });
+    expect(backyard).toMatchObject({ x: 40, y: 54, w: 56, h: 90 });
+
+    // still adjacent, still inside the grid, still not overlapping
+    expect(frontDoor.x + frontDoor.w).toBe(backyard.x);
+    expect(backyard.x + backyard.w).toBe(GRID_COLS);
+  });
+});
@@ -0,0 +1,298 @@
+/**
+ * Masonry live grid -- custom-group draggable layout.
+ *
+ * Verifies natural-aspect tile sizing and that a saved layout the current
+ * version cannot read is regenerated cleanly. The grid renders only for a
+ * custom camera group (here: "outdoor") on desktop; mobile keeps the static
+ * grid, which the @mobile block below guards.
+ */
+
+import { test, expect } from "../fixtures/frigate-test";
+import { LivePage } from "../pages/live.page";
+import {
+  cameraBoxes,
+  persistedLayoutKey,
+  readLayout,
+  seedLayout,
+} from "../helpers/grid-layout";
+
+const GROUP = "outdoor"; // custom group: front_door + backyard
+
+test.describe("Masonry live grid @critical", () => {
+  test.skip(
+    ({ frigateApp }) => frigateApp.isMobile,
+    "Draggable masonry grid is desktop-only",
+  );
+
+  test("custom group renders its cameras in the draggable grid", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+    await expect(live.cameraCard("backyard").first()).toBeVisible();
+  });
+
+  test("tiles render at their camera's natural aspect ratio", async ({
+    frigateApp,
+  }) => {
+    // backyard is 9:16, which bucketed mode would snap to an 8:9 tile
+    await frigateApp.installDefaults({
+      config: {
+        cameras: { backyard: { detect: { width: 720, height: 1280 } } },
+      },
+    });
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    await seedLayout(frigateApp.page, "naturalAspectLayout:admin", true);
+    await frigateApp.page.reload();
+    await expect(live.cameraCard("backyard").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    const { front_door: landscape, backyard: portrait } = await cameraBoxes(
+      frigateApp.page,
+      ["front_door", "backyard"] as const,
+      "card",
+    );
+
+    expect(landscape.w / landscape.h).toBeCloseTo(16 / 9, 1);
+    expect(portrait.w / portrait.h).toBeCloseTo(9 / 16, 1);
+  });
+
+  test("dragging a tile does not shove other tiles far away", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    await live.editLayoutButton.click();
+
+    const cameras = ["front_door", "backyard"] as const;
+    const { front_door: fixedBefore, backyard: draggedBox } = await cameraBoxes(
+      frigateApp.page,
+      cameras,
+      "card",
+    );
+
+    // Drag backyard onto front_door's position (a deliberate collision). With
+    // free-placement + prevent-collision, front_door must NOT be shoved down.
+    const from = {
+      x: draggedBox.x + draggedBox.w / 2,
+      y: draggedBox.y + draggedBox.h / 2,
+    };
+    const to = {
+      x: fixedBefore.x + fixedBefore.w / 2,
+      y: fixedBefore.y + fixedBefore.h / 2,
+    };
+    await frigateApp.page.mouse.move(from.x, from.y);
+    await frigateApp.page.mouse.down();
+    await frigateApp.page.mouse.move(to.x, to.y, { steps: 15 });
+    await frigateApp.page.mouse.up();
+
+    const { front_door: fixedAfter } = await cameraBoxes(
+      frigateApp.page,
+      cameras,
+      "card",
+    );
+    // Allow a few px of snap; a collision-push would move it a whole tile down.
+    expect(Math.abs(fixedAfter.y - fixedBefore.y)).toBeLessThan(40);
+  });
+
+  test("resizing a top-row tile preserves its aspect ratio (no pillarboxing)", async ({
+    frigateApp,
+  }) => {
+    // A lone top tile has room to grow sideways, which is what exposed the bug:
+    // a top-edge handle let width grow while height stayed clamped at y=0.
+    await frigateApp.installDefaults({
+      config: { camera_groups: { outdoor: { cameras: ["front_door"] } } },
+    });
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+    await live.editLayoutButton.click();
+
+    const tile = frigateApp.page.locator(".react-grid-item", {
+      has: frigateApp.page.locator("[data-camera='front_door']"),
+    });
+    const only = ["front_door"] as const;
+    const { front_door: before } = await cameraBoxes(
+      frigateApp.page,
+      only,
+      "card",
+    );
+    const aspect = before.w / before.h;
+
+    // Regression: if a top-edge handle is exposed, dragging it up/out must NOT
+    // distort the aspect (the old bug grew width while height stayed clamped).
+    const ne = tile.locator(".react-resizable-handle-ne");
+    if (await ne.count()) {
+      await ne.dragTo(tile, {
+        force: true,
+        targetPosition: { x: 1000, y: -160 },
+      });
+      const { front_door: afterNe } = await cameraBoxes(
+        frigateApp.page,
+        only,
+        "card",
+      );
+      // It must actually resize (not a silent no-op) AND keep its aspect.
+      expect(afterNe.w).toBeGreaterThan(before.w);
+      expect(Math.abs(afterNe.w / afterNe.h - aspect)).toBeLessThan(0.2);
+    }
+
+    // Positive: growing from the bottom-right corner resizes and keeps aspect.
+    const se = tile.locator(".react-resizable-handle-se");
+    await se.dragTo(tile, { force: true, targetPosition: { x: 1000, y: 520 } });
+    const { front_door: grown } = await cameraBoxes(
+      frigateApp.page,
+      only,
+      "card",
+    );
+    expect(grown.w).toBeGreaterThan(before.w);
+    expect(Math.abs(grown.w / grown.h - aspect)).toBeLessThan(0.2);
+  });
+
+  test("the grid keeps its measured width after a back navigation", async ({
+    frigateApp,
+  }) => {
+    // The grid sizes itself from window.innerWidth until its container is
+    // measured. On a warm back navigation nothing re-renders after that
+    // container mounts, so an observer that never attaches leaves every tile
+    // sized against the full window: the layout widens by the sidebar's width
+    // and the rightmost column clips on a full row.
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // total width the tiles span; tracks the width the grid laid out against
+    const span = () =>
+      frigateApp.page.evaluate(() => {
+        const tiles = [...document.querySelectorAll(".react-grid-item")];
+
+        if (!tiles.length) {
+          return null;
+        }
+
+        const rects = tiles.map((tile) => tile.getBoundingClientRect());
+        return +(
+          Math.max(...rects.map((r) => r.right)) -
+          Math.min(...rects.map((r) => r.left))
+        ).toFixed(1);
+      });
+
+    let fresh: number | null = null;
+    await expect
+      .poll(async () => (fresh = await span()), { timeout: 10_000 })
+      .not.toBeNull();
+
+    await live.cameraCard("front_door").first().click();
+    await expect(frigateApp.page).toHaveURL(/#front_door/);
+
+    await frigateApp.page.goBack();
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // the layout must settle back to the measured width, not window.innerWidth
+    await expect
+      .poll(span, { timeout: 10_000 })
+      .toBeLessThanOrEqual(fresh! + 2);
+  });
+
+  test("a camera added to a saved layout fills an open column", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // one tall tile in the first column; backyard is missing from the layout
+    const key = await persistedLayoutKey(frigateApp.page, GROUP);
+    await seedLayout(frigateApp.page, key, {
+      version: 2,
+      naturalAspect: false,
+      layout: [{ i: "front_door", x: 0, y: 0, w: 32, h: 400 }],
+    });
+    await frigateApp.page.reload();
+
+    await expect
+      .poll(async () => {
+        const stored = await readLayout(frigateApp.page, key);
+        return stored?.layout.find((item) => item.i === "backyard");
+      })
+      .toMatchObject({ x: 32, y: 0 });
+  });
+
+  test("saved layout from an unreadable version regenerates without error", async ({
+    frigateApp,
+  }) => {
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, true);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+
+    // A bare array is converted rather than discarded (covered in
+    // live-grid-aspect-modes), so use a version the current grid cannot read.
+    const key = await persistedLayoutKey(frigateApp.page, GROUP);
+    await seedLayout(frigateApp.page, key, {
+      version: 1,
+      naturalAspect: false,
+      layout: [{ i: "front_door", x: 0, y: 0, w: 4, h: 3 }],
+    });
+
+    await frigateApp.page.reload();
+    await frigateApp.page.waitForSelector("#pageRoot", { timeout: 10_000 });
+
+    // Grid regenerated; both cameras still render and the error collector
+    // (frigate-test fixture) catches any crash.
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+    await expect(live.cameraCard("backyard").first()).toBeVisible();
+
+    // The app must have replaced the value it could not read. Without this the
+    // test would still pass against a key the app never touches.
+    await expect
+      .poll(async () => (await readLayout(frigateApp.page, key))?.version, {
+        timeout: 10_000,
+      })
+      .toBeGreaterThan(1);
+  });
+});
+
+test.describe("Masonry live grid on mobile @critical @mobile", () => {
+  test("custom group keeps the static grid, with no draggable layout", async ({
+    frigateApp,
+  }) => {
+    test.skip(!frigateApp.isMobile, "Mobile-only");
+
+    await frigateApp.goto(`/?group=${GROUP}`);
+    const live = new LivePage(frigateApp.page, false);
+    await expect(live.cameraCard("front_door").first()).toBeVisible({
+      timeout: 10_000,
+    });
+    await expect(live.cameraCard("backyard").first()).toBeVisible();
+
+    // isMobileOnly routes around DraggableGridLayout entirely, so neither the
+    // grid items nor the edit-layout toggle may appear.
+    await expect(frigateApp.page.locator(".react-grid-item")).toHaveCount(0);
+    await expect(live.editLayoutButton).toHaveCount(0);
+  });
+});
@@ -217,6 +217,23 @@ test.describe("Detection models settings @high", () => {
    ).toBeDisabled();
  });

+  test("shareable hardware another model uses can still be picked", async ({
+    frigateApp,
+  }) => {
+    await installRoutes(frigateApp.page, [
+      { scene: "all", devices: ["openvino:GPU.0"] },
+      { scene: "outdoor", devices: ["openvino:GPU.1"] },
+    ]);
+    await openPage(frigateApp);
+
+    await expect(
+      frigateApp.page.locator("#models-0-openvino\\:GPU\\.1").first(),
+    ).toBeEnabled();
+    await expect(frigateApp.page.locator("#pageRoot")).not.toContainText(
+      "used by outdoor",
+    );
+  });
+
  test("adding a model appends a card with an unused scene", async ({
    frigateApp,
  }) => {
@@ -248,15 +265,13 @@ test.describe("Detection models settings @high", () => {
  test("a saved Frigate+ model opens on the Frigate+ tab", async ({
    frigateApp,
  }) => {
-    // the backend resolves plus:// to a cache path before serving the config
-    // back, so the plus metadata is the only signal the model is a Plus one
    await installRoutes(
      frigateApp.page,
      [
        {
          scene: "all",
          devices: ["openvino:GPU.0"],
-          path: "/config/model_cache/abc123",
+          path: "plus://abc123",
          plus: PLUS_MODEL,
        },
      ],
@@ -302,6 +317,65 @@ test.describe("Detection models settings @high", () => {
    expect(saves.at(-1)?.config_data?.models?.[0].path).toBe("plus://abc123");
  });

+  test("saving a Frigate+ model keeps its reference without the Frigate+ fields", async ({
+    frigateApp,
+  }) => {
+    // the backend fills these in from the Frigate+ model info when it loads
+    const saves = await installRoutes(
+      frigateApp.page,
+      [
+        {
+          scene: "all",
+          devices: ["openvino:GPU.0"],
+          path: "plus://abc123",
+          plus: PLUS_MODEL,
+          width: 320,
+          height: 320,
+          input_tensor: "nchw",
+          input_dtype: "float",
+          model_type: "yolo-generic",
+        },
+      ],
+      true,
+    );
+    await openPage(frigateApp);
+
+    await frigateApp.page.locator("#models-0-openvino\\:GPU\\.1").click();
+    await frigateApp.page.getByRole("button", { name: /^Save$/ }).click();
+    await expect.poll(() => saves.length).toBeGreaterThan(0);
+
+    const model = saves.at(-1)?.config_data?.models?.[0];
+    expect(model?.path).toBe("plus://abc123");
+    expect(model?.devices).toEqual(["openvino:GPU.0", "openvino:GPU.1"]);
+    expect(model).not.toHaveProperty("width");
+    expect(model).not.toHaveProperty("input_tensor");
+    expect(model).not.toHaveProperty("model_type");
+    // a leftover dtype from a custom model must not override the int default
+    expect(model).not.toHaveProperty("input_dtype");
+  });
+
+  test("a Frigate+ model only shows its path without a Frigate+ API key", async ({
+    frigateApp,
+  }) => {
+    await installRoutes(frigateApp.page, [
+      {
+        scene: "all",
+        devices: ["openvino:GPU.0"],
+        path: "plus://abc123",
+        width: 320,
+        height: 320,
+      },
+    ]);
+    await openPage(frigateApp);
+
+    const root = frigateApp.page.locator("#pageRoot");
+    await expect(root).toContainText("Custom object detector model path");
+    await expect(root).not.toContainText("Object detection model input width");
+    await expect(root).not.toContainText(
+      "Label map for custom object detector",
+    );
+  });
+
  test("a Frigate+ Hailo model is listed by the device it was built for", async ({
    frigateApp,
  }) => {
@@ -124,6 +124,65 @@ test.describe("genai provider settings @medium", () => {
    await expect(frigateApp.page.getByText(UNSAVED)).toBeVisible();
  });

+  test("switching back to the saved provider drops the other provider's model", async ({
+    frigateApp,
+  }) => {
+    await installRoutes(
+      frigateApp.page,
+      {
+        provider: "openai",
+        model: "gpt-4o",
+        roles: ["descriptions"],
+      },
+      { models: ["gpt-4o", "qwen3"], supports_transcription: true },
+    );
+    await frigateApp.goto(SETTINGS_URL);
+
+    const model = frigateApp.page.locator(`#root_${ENTRY}_model`);
+    const provider = frigateApp.page.locator(`#root_${ENTRY}_provider`);
+    await expect(model).toHaveText("gpt-4o");
+
+    await provider.click();
+    await frigateApp.page.getByRole("option", { name: "llamacpp" }).click();
+    await model.click();
+    await frigateApp.page.getByRole("option", { name: "qwen3" }).click();
+    await expect(model).toHaveText("qwen3");
+
+    // the model picked for llamacpp must not carry over to openai, and the
+    // saved one isn't filled back in since the endpoint may have changed
+    await provider.click();
+    await frigateApp.page
+      .getByRole("option", { name: "openai", exact: true })
+      .click();
+
+    await expect(model).toHaveText(MODEL_PLACEHOLDER);
+  });
+
+  test("undo after switching provider brings back the saved model", async ({
+    frigateApp,
+  }) => {
+    await installRoutes(
+      frigateApp.page,
+      {
+        provider: "openai",
+        model: "gpt-4o",
+        roles: ["descriptions"],
+      },
+      { models: ["gpt-4o"], supports_transcription: true },
+    );
+    await frigateApp.goto(SETTINGS_URL);
+
+    const model = frigateApp.page.locator(`#root_${ENTRY}_model`);
+    await frigateApp.page.locator(`#root_${ENTRY}_provider`).click();
+    await frigateApp.page.getByRole("option", { name: "llamacpp" }).click();
+    await expect(model).toHaveText(MODEL_PLACEHOLDER);
+
+    await frigateApp.page.getByRole("button", { name: "Undo" }).click();
+
+    await expect(model).toHaveText("gpt-4o");
+    await expect(frigateApp.page.getByText(UNSAVED)).toBeHidden();
+  });
+
  test("picking a model that cannot transcribe strips the role", async ({
    frigateApp,
  }) => {
@@ -13,7 +13,26 @@ import type { Page } from "@playwright/test";
 const OUTDOOR_LAYOUT_KEY = "outdoor-draggable-layout:admin";
 const STREAMING_KEY = "streaming-settings:admin";

-const OUTDOOR_LAYOUT = [
+// the shape DraggableGridLayout writes
+const OUTDOOR_LAYOUT = {
+  version: 2,
+  naturalAspect: false,
+  layout: [
+    { i: "front_door", x: 0, y: 0, w: 32, h: 72 },
+    { i: "backyard", x: 32, y: 0, w: 32, h: 72 },
+  ],
+};
+
+const NATURAL_OUTDOOR_LAYOUT = {
+  version: 2,
+  naturalAspect: true,
+  layout: [
+    { i: "front_door", x: 0, y: 0, w: 32, h: 72 },
+    { i: "backyard", x: 32, y: 0, w: 24, h: 96 },
+  ],
+};
+
+const LEGACY_OUTDOOR_LAYOUT = [
  { i: "front_door", x: 0, y: 0, w: 6, h: 4 },
  { i: "backyard", x: 6, y: 0, w: 6, h: 4 },
 ];
@@ -159,6 +178,160 @@ test.describe("UI settings import/export @medium", () => {
    expect(payload.sections.preferences.playbackRate).toBe(2);
  });

+  test("exports only layouts built for the current tile sizing mode", async ({
+    frigateApp,
+  }) => {
+    // a group not opened since the mode changed still holds a layout from
+    // the other mode, which would import into a mode that cannot show it
+    await frigateApp.goto("/settings?page=uiSettings");
+
+    await writeIdb(frigateApp.page, {
+      [OUTDOOR_LAYOUT_KEY]: OUTDOOR_LAYOUT,
+      "default-draggable-layout:admin": NATURAL_OUTDOOR_LAYOUT,
+      "naturalAspectLayout:admin": true,
+    });
+
+    const downloadPromise = frigateApp.page.waitForEvent("download");
+    await frigateApp.page
+      .getByRole("button", { name: "Export Settings" })
+      .click();
+    const download = await downloadPromise;
+    const payload = JSON.parse(readFileSync((await download.path())!, "utf-8"));
+
+    expect(payload.sections.layouts).toEqual({
+      default: NATURAL_OUTDOOR_LAYOUT,
+    });
+  });
+
+  test("toggling tile sizing mode clears stored layouts", async ({
+    frigateApp,
+  }) => {
+    test.skip(frigateApp.isMobile, "The setting is hidden on phones");
+    await frigateApp.goto("/settings?page=uiSettings");
+    await writeIdb(frigateApp.page, { [OUTDOOR_LAYOUT_KEY]: OUTDOOR_LAYOUT });
+
+    await frigateApp.page.locator("#natural-aspect-desktop").click();
+    await frigateApp.page
+      .getByRole("alertdialog")
+      .getByRole("button", { name: "Enable" })
+      .click();
+
+    await expect
+      .poll(() => readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY))
+      .toBeNull();
+    expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
+      true,
+    );
+  });
+
+  test("round-trips a layout left unconverted by an upgrade", async ({
+    frigateApp,
+  }) => {
+    test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
+    // DraggableGridLayout rewrites a pre-0.19 layout only when that group's
+    // dashboard is opened, so exporting first carries the bare array into the
+    // file. Import must accept it back rather than rejecting the whole file.
+    await frigateApp.goto("/settings?page=uiSettings");
+
+    await writeIdb(frigateApp.page, {
+      [OUTDOOR_LAYOUT_KEY]: LEGACY_OUTDOOR_LAYOUT,
+      "playbackRate:admin": 2,
+    });
+
+    const downloadPromise = frigateApp.page.waitForEvent("download");
+    await frigateApp.page
+      .getByRole("button", { name: "Export Settings" })
+      .click();
+    const download = await downloadPromise;
+    const contents = readFileSync((await download.path())!, "utf-8");
+
+    expect(JSON.parse(contents).sections.layouts.outdoor).toEqual(
+      LEGACY_OUTDOOR_LAYOUT,
+    );
+
+    await clearIdb(frigateApp.page);
+    await chooseImportText(frigateApp.page, contents);
+    await confirmImport(frigateApp.page);
+
+    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
+      LEGACY_OUTDOOR_LAYOUT,
+    );
+    // the rest of the file must survive alongside it
+    expect(await readIdb(frigateApp.page, "playbackRate:admin")).toBe(2);
+  });
+
+  test("legacy layouts import turns natural aspect off so they display", async ({
+    frigateApp,
+  }) => {
+    test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
+    // Bare-array layouts only render in bucketed mode; with natural aspect on
+    // they would be discarded and regenerated on the next dashboard visit. The
+    // import applies the mode the layouts were built for, and the file's own
+    // naturalAspectLayout preference must not override that.
+    await frigateApp.goto("/settings?page=uiSettings");
+    await writeIdb(frigateApp.page, { "naturalAspectLayout:admin": true });
+
+    await chooseImportFile(
+      frigateApp.page,
+      importPayload({
+        sections: {
+          layouts: { outdoor: LEGACY_OUTDOOR_LAYOUT },
+          streaming: {},
+          preferences: { naturalAspectLayout: true },
+        },
+      }),
+    );
+
+    const note = frigateApp.page.getByText(/standard tile sizing/);
+    await expect(note).toBeVisible();
+
+    // the note is about the layouts section, so it follows its switch
+    await frigateApp.page.getByText("Camera group layouts (1 group)").click();
+    await expect(note).toBeHidden();
+    await frigateApp.page.getByText("Camera group layouts (1 group)").click();
+    await expect(note).toBeVisible();
+
+    await confirmImport(frigateApp.page);
+
+    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
+      LEGACY_OUTDOOR_LAYOUT,
+    );
+    expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
+      false,
+    );
+  });
+
+  test("natural aspect layouts import turns the setting on", async ({
+    frigateApp,
+  }) => {
+    test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
+    await frigateApp.goto("/settings?page=uiSettings");
+
+    await chooseImportFile(
+      frigateApp.page,
+      importPayload({
+        sections: {
+          layouts: { outdoor: NATURAL_OUTDOOR_LAYOUT },
+          streaming: {},
+          preferences: {},
+        },
+      }),
+    );
+
+    await expect(
+      frigateApp.page.getByText(/camera aspect ratio tile sizing/),
+    ).toBeVisible();
+
+    await confirmImport(frigateApp.page);
+
+    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
+      NATURAL_OUTDOOR_LAYOUT,
+    );
+    expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
+      true,
+    );
+  });
+
  test("omits settings that were never stored", async ({ frigateApp }) => {
    await frigateApp.goto("/settings?page=uiSettings");

@@ -190,12 +363,15 @@ test.describe("UI settings import/export @medium", () => {
    await expect(
      frigateApp.page.getByText("UI preferences (2 settings)"),
    ).toBeVisible();
-    await expect(frigateApp.page.getByText(/patio/)).toBeVisible();
+    // patio is layout-only, so its warning follows the layouts section
+    await expect(frigateApp.page.getByText(/patio/)).toBeVisible({
+      visible: !frigateApp.isMobile,
+    });

    await confirmImport(frigateApp.page);

    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
-      OUTDOOR_LAYOUT,
+      frigateApp.isMobile ? null : OUTDOOR_LAYOUT,
    );
    expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual(
      STREAMING_SETTINGS,
@@ -206,6 +382,7 @@ test.describe("UI settings import/export @medium", () => {
  test("hides the unknown-group warning when layouts are switched off", async ({
    frigateApp,
  }) => {
+    test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
    await frigateApp.goto("/settings?page=uiSettings");

    // patio is a layout-only group absent from this server, so the warning
@@ -235,7 +412,39 @@ test.describe("UI settings import/export @medium", () => {

    expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual({});
    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
-      OUTDOOR_LAYOUT,
+      frigateApp.isMobile ? null : OUTDOOR_LAYOUT,
+    );
+  });
+
+  test("phones refuse layouts and say why @mobile", async ({ frigateApp }) => {
+    test.skip(!frigateApp.isMobile, "Phone-only");
+
+    await frigateApp.goto("/settings?page=uiSettings");
+    await writeIdb(frigateApp.page, { "naturalAspectLayout:admin": false });
+
+    await chooseImportFile(frigateApp.page, importPayload());
+
+    await expect(
+      frigateApp.page.getByText(/aren't imported on phones/),
+    ).toBeVisible();
+
+    // the section is still listed, but cannot be switched on
+    await expect(
+      frigateApp.page.getByText("Camera group layouts (2 groups)"),
+    ).toBeVisible();
+    await expect(
+      frigateApp.page.locator('[id="Camera group layouts (2 groups)"]'),
+    ).toBeDisabled();
+
+    await confirmImport(frigateApp.page);
+
+    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toBeNull();
+    expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual(
+      STREAMING_SETTINGS,
+    );
+    // a layouts import is what flips this, so it must stay put
+    expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
+      false,
    );
  });

@@ -325,7 +534,7 @@ test.describe("UI settings import/export @medium", () => {
    await confirmImport(frigateApp.page);

    expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
-      OUTDOOR_LAYOUT,
+      frigateApp.isMobile ? null : OUTDOOR_LAYOUT,
    );
    expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual(
      STREAMING_SETTINGS,
@@ -1,7 +1,8 @@
 /**
 * Health tab tests -- MEDIUM tier.
 *
- * Default tab, notice list rendering, dismiss, empty state, update notice.
+ * Default tab, notice list rendering, acknowledge and mute, empty state,
+ * update notice.
 */

 import { test, expect } from "../fixtures/frigate-test";
@@ -23,7 +24,9 @@ const ERROR_NOTICE = {
  first_seen: NOW - 600,
  last_seen: NOW,
  count: 2,
-  dismissed_at: null,
+  acknowledgeable: true,
+  acknowledged_at: null,
+  muted_at: null,
 };

 const EVENT_NOTICE = {
@@ -37,7 +40,9 @@ const EVENT_NOTICE = {
  first_seen: NOW - 7200,
  last_seen: NOW - 60,
  count: 3,
-  dismissed_at: null,
+  acknowledgeable: true,
+  acknowledged_at: null,
+  muted_at: null,
 };

 test.describe("System — Health tab @medium", () => {
@@ -63,54 +68,61 @@ test.describe("System — Health tab @medium", () => {
      "Downloading model.onnx for yolo failed: timeout",
    );
    await expect(rows.nth(0)).toContainText("2 times");
-    await expect(
-      rows.nth(0).getByRole("button", { name: "Dismiss" }),
-    ).toBeVisible();
    await expect(rows.nth(1)).toContainText("Detector ov was restarted");
    await expect(rows.nth(1)).toContainText("3 times");
-    await expect(
-      rows.nth(1).getByRole("button", { name: "Dismiss" }),
-    ).toBeVisible();
+    for (const index of [0, 1]) {
+      await expect(
+        rows.nth(index).getByRole("button", { name: "Acknowledge" }),
+      ).toBeVisible();
+      await expect(
+        rows.nth(index).getByRole("button", { name: "Mute", exact: true }),
+      ).toBeVisible();
+    }
  });

-  test("dismiss posts and removes the row", async ({ frigateApp }) => {
-    await frigateApp.installDefaults({
-      stats: QUIET_STATS,
-      notices: [EVENT_NOTICE],
+  for (const action of ["acknowledge", "mute"] as const) {
+    test(`${action} posts and removes the row`, async ({ frigateApp }) => {
+      await frigateApp.installDefaults({
+        stats: QUIET_STATS,
+        notices: [EVENT_NOTICE],
+      });
+
+      // the list shrinks after the POST so the refetch shows the row gone
+      let hidden = false;
+      await frigateApp.page.route("**/api/notices", (route) =>
+        route.fulfill({ json: hidden ? [] : [EVENT_NOTICE] }),
+      );
+      await frigateApp.page.route(
+        `**/api/notices/detector_stuck/${action}`,
+        (route) => {
+          hidden = true;
+          return route.fulfill({ json: { success: true } });
+        },
+      );
+
+      await frigateApp.goto("/system#health");
+      const request = frigateApp.page.waitForRequest(
+        (req) =>
+          req.url().includes(`/api/notices/detector_stuck/${action}`) &&
+          req.method() === "POST",
+      );
+      await frigateApp.page
+        .getByTestId("health-problem-notice:detector_stuck")
+        .getByRole("button", {
+          name: action === "mute" ? "Mute" : "Acknowledge",
+          exact: true,
+        })
+        .click();
+      await request;
+
+      await expect(
+        frigateApp.page.locator("[data-testid^='health-problem-']"),
+      ).toHaveCount(0, { timeout: 5_000 });
+      await expect(
+        frigateApp.page.getByText("Your Frigate installation is healthy"),
+      ).toBeVisible();
    });
-
-    // the list shrinks after the dismiss so the refetch shows the row gone
-    let dismissed = false;
-    await frigateApp.page.route("**/api/notices", (route) =>
-      route.fulfill({ json: dismissed ? [] : [EVENT_NOTICE] }),
-    );
-    await frigateApp.page.route(
-      "**/api/notices/detector_stuck/dismiss",
-      (route) => {
-        dismissed = true;
-        return route.fulfill({ json: { success: true } });
-      },
-    );
-
-    await frigateApp.goto("/system#health");
-    const request = frigateApp.page.waitForRequest(
-      (req) =>
-        req.url().includes("/api/notices/detector_stuck/dismiss") &&
-        req.method() === "POST",
-    );
-    await frigateApp.page
-      .getByTestId("health-problem-notice:detector_stuck")
-      .getByRole("button", { name: "Dismiss" })
-      .click();
-    await request;
-
-    await expect(
-      frigateApp.page.locator("[data-testid^='health-problem-']"),
-    ).toHaveCount(0, { timeout: 5_000 });
-    await expect(
-      frigateApp.page.getByText("Your Frigate installation is healthy"),
-    ).toBeVisible();
-  });
+  }

  test("empty state with no notices", async ({ frigateApp }) => {
    await frigateApp.installDefaults({ stats: QUIET_STATS });
@@ -140,7 +152,9 @@ test.describe("System — Health tab @medium", () => {
          first_seen: NOW - 3600,
          last_seen: NOW,
          count: 1,
-          dismissed_at: null,
+          acknowledgeable: false,
+          acknowledged_at: null,
+          muted_at: null,
        },
      ],
    });
@@ -156,10 +170,23 @@ test.describe("System — Health tab @medium", () => {
      "href",
      "https://github.com/blakeblackshear/frigate/releases/tag/v0.19.0",
    );
-    await expect(row.getByRole("button", { name: "Dismiss" })).toBeVisible();
+    await expect(
+      row.getByRole("button", { name: "Mute", exact: true }),
+    ).toBeVisible();
+    await expect(row.getByRole("button", { name: "Acknowledge" })).toHaveCount(
+      0,
+    );
  });

-  test("the filter shows dismissed notices without a Dismiss button", async ({
+  const ACKNOWLEDGED_NOTICE = {
+    ...EVENT_NOTICE,
+    id: "detector_stuck:coral",
+    params: { detector: "coral" },
+    acknowledged_at: NOW - 60,
+  };
+  const MUTED_NOTICE = { ...ERROR_NOTICE, muted_at: NOW - 120 };
+
+  test("the filter shows hidden notices marked by how they were hidden", async ({
    frigateApp,
  }) => {
    await frigateApp.installDefaults({
@@ -169,33 +196,85 @@ test.describe("System — Health tab @medium", () => {
    await frigateApp.page.route(
      (url) =>
        url.pathname.endsWith("/api/notices") &&
-        url.searchParams.get("include_dismissed") === "true",
+        url.searchParams.get("include_hidden") === "true",
      (route) =>
        route.fulfill({
-          json: [EVENT_NOTICE, { ...ERROR_NOTICE, dismissed_at: NOW - 120 }],
+          json: [EVENT_NOTICE, ACKNOWLEDGED_NOTICE, MUTED_NOTICE],
        }),
    );
    await frigateApp.goto("/system#health");

    await frigateApp.page.getByRole("button", { name: "Filter" }).click();
-    const showDismissed = frigateApp.page.getByRole("switch", {
-      name: "Show dismissed",
+    const showHidden = frigateApp.page.getByRole("switch", {
+      name: "Show hidden",
    });
-    await expect(showDismissed).toHaveAttribute("aria-checked", "false");
-    await showDismissed.click();
+    await expect(showHidden).toHaveAttribute("aria-checked", "false");
+    await showHidden.click();
+    // mobile opens the filter as a modal drawer, which hides the rows' roles
+    await frigateApp.page.keyboard.press("Escape");

-    const row = frigateApp.page.getByTestId(
+    const acknowledged = frigateApp.page.getByTestId(
+      "health-problem-notice:detector_stuck:coral",
+    );
+    await expect(acknowledged).toBeVisible({ timeout: 15_000 });
+    await expect(acknowledged).toContainText("Acknowledged");
+    await expect(
+      acknowledged.getByRole("button", { name: "Show again" }),
+    ).toBeVisible();
+    await expect(
+      acknowledged.getByRole("button", { name: "Acknowledge" }),
+    ).toHaveCount(0);
+
+    const muted = frigateApp.page.getByTestId(
      "health-problem-notice:model_download_failed:yolo/model.onnx",
    );
-    await expect(row).toBeVisible({ timeout: 15_000 });
-    await expect(row).toContainText("Dismissed");
-    await expect(row.getByRole("button", { name: "Dismiss" })).toHaveCount(0);
+    await expect(muted).toContainText("Muted");
+    await expect(muted.getByRole("button", { name: "Unmute" })).toBeVisible();
+    await expect(
+      muted.getByRole("button", { name: "Mute", exact: true }),
+    ).toHaveCount(0);

-    await showDismissed.click();
-    await expect(row).toHaveCount(0);
+    await frigateApp.page.getByRole("button", { name: "Filter" }).click();
+    await showHidden.click();
+    await expect(muted).toHaveCount(0);
  });

-  test("clear dismissed deletes the dismissed rows after confirming", async ({
+  test("unmute deletes the row's hidden state", async ({ frigateApp }) => {
+    await frigateApp.installDefaults({ stats: QUIET_STATS, notices: [] });
+    await frigateApp.page.route(
+      (url) =>
+        url.pathname.endsWith("/api/notices") &&
+        url.searchParams.get("include_hidden") === "true",
+      (route) => route.fulfill({ json: [MUTED_NOTICE] }),
+    );
+    await frigateApp.page.route(
+      "**/api/notices/model_download_failed:yolo/model.onnx/hidden",
+      (route) => route.fulfill({ json: { success: true } }),
+    );
+    await frigateApp.goto("/system#health");
+
+    await frigateApp.page.getByRole("button", { name: "Filter" }).click();
+    await frigateApp.page.getByRole("switch", { name: "Show hidden" }).click();
+    await frigateApp.page.keyboard.press("Escape");
+
+    const request = frigateApp.page.waitForRequest(
+      (req) =>
+        req
+          .url()
+          .endsWith(
+            "/api/notices/model_download_failed:yolo/model.onnx/hidden",
+          ) && req.method() === "DELETE",
+    );
+    await frigateApp.page
+      .getByTestId(
+        "health-problem-notice:model_download_failed:yolo/model.onnx",
+      )
+      .getByRole("button", { name: "Unmute" })
+      .click({ timeout: 15_000 });
+    await request;
+  });
+
+  test("show all again unhides every row after confirming", async ({
    frigateApp,
  }) => {
    await frigateApp.installDefaults({
@@ -203,29 +282,25 @@ test.describe("System — Health tab @medium", () => {
      notices: [EVENT_NOTICE],
    });

-    // the history loses its dismissed row once the DELETE lands
+    // the hidden list loses its muted row once the DELETE lands
    let cleared = false;
    await frigateApp.page.route(
      (url) =>
        url.pathname.endsWith("/api/notices") &&
-        url.searchParams.get("include_dismissed") === "true",
+        url.searchParams.get("include_hidden") === "true",
      (route) =>
        route.fulfill({
-          json: cleared
-            ? [EVENT_NOTICE]
-            : [EVENT_NOTICE, { ...ERROR_NOTICE, dismissed_at: NOW - 120 }],
+          json: cleared ? [EVENT_NOTICE] : [EVENT_NOTICE, MUTED_NOTICE],
        }),
    );
-    await frigateApp.page.route("**/api/notices/dismissed", (route) => {
+    await frigateApp.page.route("**/api/notices/hidden", (route) => {
      cleared = true;
      return route.fulfill({ json: { success: true } });
    });
    await frigateApp.goto("/system#health");

    await frigateApp.page.getByRole("button", { name: "Filter" }).click();
-    await frigateApp.page
-      .getByRole("switch", { name: "Show dismissed" })
-      .click();
+    await frigateApp.page.getByRole("switch", { name: "Show hidden" }).click();
    const row = frigateApp.page.getByTestId(
      "health-problem-notice:model_download_failed:yolo/model.onnx",
    );
@@ -233,23 +308,20 @@ test.describe("System — Health tab @medium", () => {
    await frigateApp.page.keyboard.press("Escape");

    await frigateApp.page
-      .getByRole("button", { name: "Clear dismissed" })
+      .getByRole("button", { name: "Show all again" })
      .click();
    const request = frigateApp.page.waitForRequest(
      (req) =>
-        req.url().endsWith("/api/notices/dismissed") &&
-        req.method() === "DELETE",
+        req.url().endsWith("/api/notices/hidden") && req.method() === "DELETE",
    );
    await frigateApp.page
      .getByRole("alertdialog")
-      .getByRole("button", { name: "Clear dismissed" })
+      .getByRole("button", { name: "Show all again" })
      .click();
    await request;

    await expect(row).toHaveCount(0);
-    await expect(
-      frigateApp.page.getByText("No dismissed notices"),
-    ).toBeVisible();
+    await expect(frigateApp.page.getByText("No hidden notices")).toBeVisible();
  });

  test("severity switches hide notices of that severity", async ({
@@ -290,7 +362,9 @@ test.describe("System — Health tab @medium", () => {
      first_seen: start,
      last_seen: start + 60,
      count,
-      dismissed_at: null,
+      acknowledgeable: true,
+      acknowledged_at: null,
+      muted_at: null,
    });
    await frigateApp.installDefaults({
      stats: QUIET_STATS,
@@ -332,7 +406,9 @@ test.describe("System — Health tab @medium", () => {
          first_seen: NOW - 600,
          last_seen: NOW - 600,
          count: 1,
-          dismissed_at: null,
+          acknowledgeable: true,
+          acknowledged_at: null,
+          muted_at: null,
        },
      ],
    });
@@ -363,7 +439,9 @@ test.describe("System — Health tab @medium", () => {
          first_seen: NOW - 600,
          last_seen: NOW - 600,
          count: 1,
-          dismissed_at: null,
+          acknowledgeable: true,
+          acknowledged_at: null,
+          muted_at: null,
        },
      ],
    });
@@ -695,7 +773,7 @@ test.describe("System — Health notices sources @medium", () => {

    // the status bar shows a problem, so stats have loaded
    await expect(
-      frigateApp.page.getByText("Front Door is offline"),
+      frigateApp.page.getByText("Recordings are being deleted"),
    ).toBeVisible({ timeout: 15_000 });
    await expect(
      frigateApp.page.locator("[data-testid^='health-problem-']"),
@@ -1046,7 +1124,7 @@ test.describe("System — Health notices sources @medium", () => {
    await expect(frigateApp.page).toHaveURL(/\/system#health/);
  });

-  test("status bar counts undismissed notices next to the health text", async ({
+  test("status bar counts shown notices next to the health text", async ({
    frigateApp,
  }) => {
    test.skip(frigateApp.isMobile, "Status bar is desktop-only");
@@ -1089,41 +1167,61 @@ test.describe("System — Health notices sources @medium", () => {
    await expect(frigateApp.page.getByText("System is healthy")).toHaveCount(0);
  });

-  test("a config row can be dismissed", async ({ frigateApp }) => {
-    const id = "config:detect:fps-greater-than-five:camera.garage";
-    await frigateApp.installDefaults({
-      config: {
-        cameras: {
-          garage: { detect: { width: 2560, height: 1440, fps: 10 } },
-        },
-      },
-      stats: QUIET_STATS,
-    });
+  // the slow detector warning is added before the offline error
+  const TWO_PROBLEM_STATS = {
+    detectors: { cpu: { inference_speed: 60 } },
+    cameras: { front_door: { camera_fps: 0 } },
+  };

-    // the list gains the dismissal after the POST so the refetch hides the row
-    let dismissed = false;
-    await frigateApp.page.route(`**/api/notices/${id}/dismiss`, (route) => {
-      dismissed = true;
-      return route.fulfill({ json: { success: true } });
-    });
-    await frigateApp.page.route("**/api/notices/dismissed_checks", (route) =>
-      route.fulfill({ json: dismissed ? [{ id, dismissed_at: NOW }] : [] }),
-    );
-    await frigateApp.goto("/system#health");
+  test("status bar collapses several problems behind the most severe", async ({
+    frigateApp,
+  }) => {
+    test.skip(frigateApp.isMobile, "Status bar is desktop-only");
+    await frigateApp.installDefaults({ stats: TWO_PROBLEM_STATS });
+    await frigateApp.goto("/");

-    const row = frigateApp.page.getByTestId(`health-problem-${id}`);
-    await expect(row).toBeVisible({ timeout: 15_000 });
-    const request = frigateApp.page.waitForRequest(
-      (req) =>
-        req.url().includes(`/api/notices/${id}/dismiss`) &&
-        req.method() === "POST",
-    );
-    await row.getByRole("button", { name: "Dismiss" }).click();
-    await request;
-    await expect(row).toHaveCount(0);
+    const summary = frigateApp.page.getByRole("button", {
+      name: "Front Door is offline +1",
+    });
+    await expect(summary).toBeVisible({ timeout: 15_000 });
+    await expect(frigateApp.page.getByText("Cpu is slow")).toHaveCount(0);
+
+    await summary.click();
+    const list = frigateApp.page.getByTestId("status-message-list");
+    await expect(list.getByRole("link")).toHaveText([
+      "Front Door is offline",
+      "Cpu is slow (60 ms)",
+    ]);
+
+    await list.getByRole("link", { name: "Cpu is slow (60 ms)" }).click();
+    await expect(frigateApp.page).toHaveURL(/\/system#general/);
+    await expect(list).toHaveCount(0);
  });

-  test("dismissed config rows move to the dismissed list", async ({
+  test("mobile status drawer stacks every problem", async ({ frigateApp }) => {
+    test.skip(!frigateApp.isMobile, "Mobile-only");
+    await frigateApp.installDefaults({ stats: TWO_PROBLEM_STATS });
+    await frigateApp.goto("/");
+
+    await frigateApp.page
+      .getByTestId("status-alert-trigger")
+      .click({ timeout: 15_000 });
+    const items = frigateApp.page
+      .getByTestId("status-message-list")
+      .getByRole("link");
+    await expect(items).toHaveText([
+      "Front Door is offline",
+      "Cpu is slow (60 ms)",
+    ]);
+
+    const [first, second] = await Promise.all([
+      items.nth(0).boundingBox(),
+      items.nth(1).boundingBox(),
+    ]);
+    expect(second!.y).toBeGreaterThan(first!.y);
+  });
+
+  test("a config row can be muted but not acknowledged", async ({
    frigateApp,
  }) => {
    const id = "config:detect:fps-greater-than-five:camera.garage";
@@ -1134,12 +1232,49 @@ test.describe("System — Health notices sources @medium", () => {
        },
      },
      stats: QUIET_STATS,
-      dismissedChecks: [{ id, dismissed_at: NOW - 120 }],
+    });
+
+    // the list gains the mute after the POST so the refetch hides the row
+    let muted = false;
+    await frigateApp.page.route(`**/api/notices/${id}/mute`, (route) => {
+      muted = true;
+      return route.fulfill({ json: { success: true } });
+    });
+    await frigateApp.page.route("**/api/notices/muted_checks", (route) =>
+      route.fulfill({ json: muted ? [{ id, muted_at: NOW }] : [] }),
+    );
+    await frigateApp.goto("/system#health");
+
+    const row = frigateApp.page.getByTestId(`health-problem-${id}`);
+    await expect(row).toBeVisible({ timeout: 15_000 });
+    await expect(row.getByRole("button", { name: "Acknowledge" })).toHaveCount(
+      0,
+    );
+    const request = frigateApp.page.waitForRequest(
+      (req) =>
+        req.url().includes(`/api/notices/${id}/mute`) &&
+        req.method() === "POST",
+    );
+    await row.getByRole("button", { name: "Mute", exact: true }).click();
+    await request;
+    await expect(row).toHaveCount(0);
+  });
+
+  test("muted config rows move to the hidden list", async ({ frigateApp }) => {
+    const id = "config:detect:fps-greater-than-five:camera.garage";
+    await frigateApp.installDefaults({
+      config: {
+        cameras: {
+          garage: { detect: { width: 2560, height: 1440, fps: 10 } },
+        },
+      },
+      stats: QUIET_STATS,
+      mutedChecks: [{ id, muted_at: NOW - 120 }],
    });
    await frigateApp.page.route(
      (url) =>
        url.pathname.endsWith("/api/notices") &&
-        url.searchParams.get("include_dismissed") === "true",
+        url.searchParams.get("include_hidden") === "true",
      (route) => route.fulfill({ json: [] }),
    );
    await frigateApp.goto("/system#health");
@@ -1153,12 +1288,14 @@ test.describe("System — Health notices sources @medium", () => {
    await expect(row).toHaveCount(0);

    await frigateApp.page.getByRole("button", { name: "Filter" }).click();
-    await frigateApp.page
-      .getByRole("switch", { name: "Show dismissed" })
-      .click();
+    await frigateApp.page.getByRole("switch", { name: "Show hidden" }).click();
+    await frigateApp.page.keyboard.press("Escape");

    await expect(row).toBeVisible();
-    await expect(row).toContainText("Dismissed");
-    await expect(row.getByRole("button", { name: "Dismiss" })).toHaveCount(0);
+    await expect(row).toContainText("Muted");
+    await expect(row.getByRole("button", { name: "Unmute" })).toBeVisible();
+    await expect(
+      row.getByRole("button", { name: "Mute", exact: true }),
+    ).toHaveCount(0);
  });
 });
@@ -15,10 +15,6 @@
    "bandwidth": {
      "title": "العرض الترددي:",
      "short": "العرض الترددي"
-    },
-    "latency": {
-      "title": "التأخير:",
-      "value": "{{seconds}} ثانية"
    }
  },
  "streamOffline": {
@@ -21,8 +21,8 @@
    "1hour": "1 гадзіна",
    "12hours": "12 гадзін",
    "24hours": "24 гадзіны",
-    "pm": "вечара",
-    "am": "раніцы",
+    "pm": "pm",
+    "am": "am",
    "yr": "{{time}} г",
    "year_one": "{{time}} год",
    "year_few": "{{time}} гады",
@@ -168,13 +168,16 @@
    "saveAll": "Захаваць усё",
    "savingAll": "Захаванне ўсяго…",
    "undoAll": "Адрабіць усё",
-    "retry": "Паўтарыць"
+    "retry": "Паўтарыць",
+    "expand": "Разгарнуць",
+    "collapse": "Згарнуць",
+    "reload": "Перазагрузіць"
  },
  "menu": {
    "system": "Сістэма",
-    "systemMetrics": "Сістэмныя метрыкі",
+    "systemMetrics": "Стан і метрыкі",
    "configuration": "Канфігурацыя",
-    "systemLogs": "Журналы сістэмы",
+    "systemLogs": "Журналы",
    "profiles": "Профілі",
    "settings": "Налады",
    "configurationEditor": "Рэдактар канфігурацыі",
@@ -225,7 +228,7 @@
      "withSystem": {
        "label": "Выкарыстоўваць мову з налад сістэмы"
      },
-      "be": "Беларуская"
+      "be": "Беларуская (беларуская)"
    },
    "appearance": "Выгляд",
    "darkMode": {
@@ -328,5 +331,36 @@
  "validation_errors": "Памылкі праверкі",
  "credentialField": {
    "savedPlaceholder": "Захавана - пакіньце пустым, каб не мяняць"
+  },
+  "error": {
+    "title": "Гэтая старонка перастала працаваць",
+    "desc": "На старонцы адбылася нечаканая памылка. Звычайна дапамагае перазагрузка. Калі гэта паўтараецца, скапіюйце падрабязнасці і дадайце іх да абмеркавання на GitHub.",
+    "staleTitle": "Патрэбна перазагрузка",
+    "staleDesc": "Частка інтэрфейсу не загрузілася - звычайна гэта значыць, што Frigate абнавіўся, пакуль гэтая ўкладка была адкрытая. Перазагрузіце, каб атрымаць новую версію.",
+    "partial": "Частка інтэрфейсу перастала працаваць.",
+    "copyDetails": "Скапіяваць падрабязнасці",
+    "copyFailed": "Не ўдалося скапіяваць падрабязнасці ў буфер абмену"
+  },
+  "commandMenu": {
+    "title": "Меню каманд",
+    "description": "Пошук старонак, камер, налад і дзеянняў",
+    "placeholder": "Пошук старонак, камер, налад і дзеянняў",
+    "empty": "Няма супадзенняў",
+    "hint": "{{key}} або / каб адкрыць, Enter каб выканаць",
+    "section": {
+      "recent": "Апошнія",
+      "pages": "Старонкі",
+      "cameras": "Камеры",
+      "cameraGroups": "Групы камер",
+      "settings": "Налады",
+      "actions": "Дзеянні"
+    },
+    "camera": {
+      "live": "Эфір",
+      "review": "Разгляд"
+    },
+    "action": {
+      "toggleTheme": "Пераключыць светлы і цёмны рэжым"
+    }
  }
 }
@@ -137,6 +137,15 @@
      "queueingExport": "Экспарт ставіцца ў чаргу…",
      "previewExport": "Перадпрагляд экспарту",
      "useThisRange": "Ужыць гэты прамежак"
+    },
+    "stream": {
+      "label": "Якасць",
+      "auto": "Аўта",
+      "main": "Зыходная",
+      "sub": "Нізкая",
+      "autoDesc": "Выкарыстоўвае асноўную плынь, а дзе яна недаступная - пераходзіць на дадатковую плынь ніжэйшай якасці.",
+      "mainDesc": "Экспартуе толькі асноўную плынь зыходнай якасці. Прамежкі часу, дзе асноўная плынь недаступная, будуць адсутнічаць.",
+      "subDesc": "Экспартуе толькі дадатковую плынь ніжэйшай якасці. Прамежкі часу, дзе дадатковая плынь недаступная, будуць адсутнічаць."
    }
  },
  "streaming": {
@@ -190,7 +199,14 @@
      "export": "Экспарт",
      "markAsReviewed": "Пазначыць як разгледжанае",
      "markAsUnreviewed": "Пазначыць як неразгледжанае",
-      "deleteNow": "Выдаліць зараз"
+      "deleteNow": "Выдаліць зараз",
+      "generateDescription": "Стварыць апісанне"
+    },
+    "genaiDescription": {
+      "toast": {
+        "success": "Апісанне GenAI запытана для гэтага элемента разгляду.",
+        "error": "Не ўдалося запытаць апісанне: {{error}}"
+      }
    }
  },
  "imagePicker": {
@@ -22,14 +22,6 @@
      "title": "Паласа прапускання:",
      "short": "Паласа"
    },
-    "latency": {
-      "title": "Затрымка:",
-      "value": "{{seconds}} сек",
-      "short": {
-        "title": "Затрымка",
-        "value": "{{seconds}} с"
-      }
-    },
    "totalFrames": "Усяго кадраў:",
    "droppedFrames": {
      "title": "Страчаныя кадры:",
@@ -46,7 +38,22 @@
      "submittedFrigatePlus": "Кадр паспяхова адпраўлены ў Frigate+"
    },
    "error": {
-      "submitFrigatePlusFailed": "Не ўдалося адправіць кадр у Frigate+"
+      "submitFrigatePlusFailed": "Не ўдалося адправіць кадр у Frigate+",
+      "playRecordingsFailed": "Не ўдалося прайграць запісы (памылка {{code}}): {{message}}"
    }
+  },
+  "quality": {
+    "auto": "Аўта",
+    "autoLow": "Прайграецца нізкая якасць (абмежаваная паласа прапускання)",
+    "autoLowCodec": "Прайграецца нізкая якасць (зыходная не падтрымліваецца гэтым браўзерам)",
+    "autoLowSaveData": "Прайграецца нізкая якасць (эканомія трафіку)",
+    "main": "Зыходная",
+    "sub": "Нізкая",
+    "notSupportedBrowser": "Не падтрымліваецца гэтым браўзерам",
+    "label": "Якасць",
+    "noAudio": "Без гуку",
+    "audioRate": "Гук {{rate}} кГц",
+    "audioCodecRate": "{{codec}} {{rate}} кГц",
+    "noRecordings": "Няма запісаў у гэтым прамежку часу"
  }
 }
@@ -70,7 +70,7 @@
        },
        "objects": {
            "label": "Аб'екты-трыгеры",
-            "description": "Спіс тыпаў аб'ектаў (з labelmap), якія могуць спрацаваць у гэтай зоне. Можа быць радком або спісам радкоў. Калі пуста, улічваюцца ўсе аб'екты."
+            "description": "Спіс тыпаў аб'ектаў (з карты метак), якія могуць спрацаваць у гэтай зоне. Можа быць радком або спісам радкоў. Калі пуста, улічваюцца ўсе аб'екты."
        }
    },
    "label": "CameraConfig",
@@ -120,6 +120,10 @@
        "num_threads": {
            "label": "Патокі дэтэктавання",
            "description": "Колькасць патокаў для апрацоўкі дэтэктавання гуку."
+        },
+        "labelmap": {
+            "label": "Змяненне карты метак гуку",
+            "description": "Перавызначэнні або пераназначэнні, якія аб'ядноўваюцца са стандартнай картай метак гуку."
        }
    },
    "audio_transcription": {
@@ -147,6 +151,10 @@
        "order": {
            "label": "Пазіцыя",
            "description": "Лічбавае становішча, якое вызначае парадак камеры ў раскладцы Birdseye."
+        },
+        "modes": {
+            "label": "Тыпы актыўнасці",
+            "description": "Тыпы актыўнасці, пры якіх камеры паказваюцца ў Birdseye."
        }
    },
    "detect": {
@@ -207,6 +215,10 @@
        "annotation_offset": {
            "label": "Зрух анатацый",
            "description": "На колькі мілісекунд зрушыць прамавугольнікі аб'ектаў, каб яны супадалі з запісаным відэа: плыні «detect» і «record» рэдка ідэальна сінхронныя. Можа быць дадатным або адмоўным."
+        },
+        "scene": {
+            "label": "Сцэна дэтэктавання",
+            "description": "Асяроддзе, на якое глядзіць гэтая камера; паводле яго выбіраецца, якая з наладжаных мадэлей на ёй працуе. Камеры са значэннем «all» выкарыстоўваюць мадэль, наладжаную са сцэнай «all»."
        }
    },
    "face_recognition": {
@@ -250,6 +262,10 @@
            "record": {
                "label": "Выходныя аргументы для record",
                "description": "Прадвызначаныя выходныя аргументы для плыняў з роляй «record»."
+            },
+            "record_sub": {
+                "label": "Выходныя аргументы запісу дадатковай плыні",
+                "description": "Выходныя аргументы для плыняў з роляй «record_sub». Калі не зададзена, выкарыстоўваюцца выходныя аргументы запісу."
            }
        },
        "retry_interval": {
@@ -579,6 +595,54 @@
        "enabled_in_config": {
            "label": "Зыходны стан запісу",
            "description": "Паказвае, ці быў запіс уключаны ў зыходнай статычнай канфігурацыі."
+        },
+        "sub": {
+            "label": "Запіс дадатковай плыні",
+            "description": "Налады запісу другой плыні ніжэйшай якасці.",
+            "enabled": {
+                "label": "Уключыць запіс дадатковай плыні",
+                "description": "Уключыць запіс другой плыні ніжэйшай якасці для прайгравання з адаптыўнай якасцю і падоўжанага захоўвання."
+            },
+            "continuous": {
+                "label": "Бесперапыннае захоўванне дадатковай плыні",
+                "description": "Колькасць дзён захоўвання запісаў дадатковай плыні незалежна ад аб'ектаў пад адсочваннем або руху.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Дзён захоўвання запісаў."
+                }
+            },
+            "motion": {
+                "label": "Захоўванне дадатковай плыні па руху",
+                "description": "Колькасць дзён захоўвання запісаў дадатковай плыні, выкліканых рухам.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Дзён захоўвання запісаў."
+                }
+            },
+            "alerts": {
+                "label": "Захоўванне абвестак дадатковай плыні",
+                "description": "Налады захоўвання запісаў абвестак дадатковай плыні.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Колькасць дзён захоўвання запісаў падзей дэтэктавання."
+                },
+                "mode": {
+                    "label": "Рэжым захоўвання",
+                    "description": "Рэжым захоўвання: all (усе сегменты), motion (сегменты з рухам) або active_objects (сегменты з актыўнымі аб'ектамі)."
+                }
+            },
+            "detections": {
+                "label": "Захоўванне дэтэктаванняў дадатковай плыні",
+                "description": "Налады захоўвання запісаў дэтэктаванняў дадатковай плыні.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Колькасць дзён захоўвання запісаў падзей дэтэктавання."
+                },
+                "mode": {
+                    "label": "Рэжым захоўвання",
+                    "description": "Рэжым захоўвання: all (усе сегменты), motion (сегменты з рухам) або active_objects (сегменты з актыўнымі аб'ектамі)."
+                }
+            }
        }
    },
    "review": {
@@ -670,6 +734,10 @@
            "activity_context_prompt": {
                "label": "Прампт кантэксту актыўнасці",
                "description": "Уласны прампт, які апісвае, якая актыўнасць падазроная, а якая не, каб даць кантэкст для зводак GenAI."
+            },
+            "response_style": {
+                "label": "Стыль адказу",
+                "description": "Гатовы стыль пісьма для створаных апісанняў разгляду. Гатовыя стылі наладжваюць тон і падрабязнасць загалоўка, зводкі і апісання сцэны, якія бачыць карыстальнік; «default» пакідае ўбудаваны прампт без змен."
            }
        }
    },
@@ -33,7 +33,11 @@
            "label": "Патокі дэтэктавання",
            "description": "Колькасць патокаў для апрацоўкі дэтэктавання гуку."
        },
-        "description": "Налады дэтэктавання падзей па гуку для ўсіх камер. Можна перавызначыць для кожнай камеры."
+        "description": "Налады дэтэктавання падзей па гуку для ўсіх камер. Можна перавызначыць для кожнай камеры.",
+        "labelmap": {
+            "label": "Змяненне карты метак гуку",
+            "description": "Перавызначэнні або пераназначэнні, якія аб'ядноўваюцца са стандартнай картай метак гуку."
+        }
    },
    "audio_transcription": {
        "label": "Транскрыпцыя гуку",
@@ -105,6 +109,10 @@
        "idle_heartbeat_fps": {
            "label": "FPS сігналу пры прастоі",
            "description": "Колькі разоў на секунду паўтараць апошні кадр Birdseye пры прастоі. 0 адключае."
+        },
+        "modes": {
+            "label": "Тыпы актыўнасці",
+            "description": "Тыпы актыўнасці, пры якіх камеры паказваюцца ў Birdseye."
        }
    },
    "detect": {
@@ -165,6 +173,10 @@
        "annotation_offset": {
            "label": "Зрух анатацый",
            "description": "На колькі мілісекунд зрушыць прамавугольнікі аб'ектаў, каб яны супадалі з запісаным відэа: плыні «detect» і «record» рэдка ідэальна сінхронныя. Можа быць дадатным або адмоўным."
+        },
+        "scene": {
+            "label": "Сцэна дэтэктавання",
+            "description": "Асяроддзе, на якое глядзіць гэтая камера; паводле яго выбіраецца, якая з наладжаных мадэлей на ёй працуе. Камеры са значэннем «all» выкарыстоўваюць мадэль, наладжаную са сцэнай «all»."
        }
    },
    "face_recognition": {
@@ -238,6 +250,10 @@
            "record": {
                "label": "Выходныя аргументы для record",
                "description": "Прадвызначаныя выходныя аргументы для плыняў з роляй «record»."
+            },
+            "record_sub": {
+                "label": "Выходныя аргументы запісу дадатковай плыні",
+                "description": "Выходныя аргументы для плыняў з роляй «record_sub». Калі не зададзена, выкарыстоўваюцца выходныя аргументы запісу."
            }
        },
        "retry_interval": {
@@ -650,7 +666,55 @@
            "label": "Зыходны стан запісу",
            "description": "Паказвае, ці быў запіс уключаны ў зыходнай статычнай канфігурацыі."
        },
-        "description": "Налады запісу і захоўвання для камер, калі яны не перавызначаны асобна."
+        "description": "Налады запісу і захоўвання для камер, калі яны не перавызначаны асобна.",
+        "sub": {
+            "label": "Запіс дадатковай плыні",
+            "description": "Налады запісу другой плыні ніжэйшай якасці.",
+            "enabled": {
+                "label": "Уключыць запіс дадатковай плыні",
+                "description": "Уключыць запіс другой плыні ніжэйшай якасці для прайгравання з адаптыўнай якасцю і падоўжанага захоўвання."
+            },
+            "continuous": {
+                "label": "Бесперапыннае захоўванне дадатковай плыні",
+                "description": "Колькасць дзён захоўвання запісаў дадатковай плыні незалежна ад аб'ектаў пад адсочваннем або руху.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Дзён захоўвання запісаў."
+                }
+            },
+            "motion": {
+                "label": "Захоўванне дадатковай плыні па руху",
+                "description": "Колькасць дзён захоўвання запісаў дадатковай плыні, выкліканых рухам.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Дзён захоўвання запісаў."
+                }
+            },
+            "alerts": {
+                "label": "Захоўванне абвестак дадатковай плыні",
+                "description": "Налады захоўвання запісаў абвестак дадатковай плыні.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Колькасць дзён захоўвання запісаў падзей дэтэктавання."
+                },
+                "mode": {
+                    "label": "Рэжым захоўвання",
+                    "description": "Рэжым захоўвання: all (усе сегменты), motion (сегменты з рухам) або active_objects (сегменты з актыўнымі аб'ектамі)."
+                }
+            },
+            "detections": {
+                "label": "Захоўванне дэтэктаванняў дадатковай плыні",
+                "description": "Налады захоўвання запісаў дэтэктаванняў дадатковай плыні.",
+                "days": {
+                    "label": "Дні захоўвання",
+                    "description": "Колькасць дзён захоўвання запісаў падзей дэтэктавання."
+                },
+                "mode": {
+                    "label": "Рэжым захоўвання",
+                    "description": "Рэжым захоўвання: all (усе сегменты), motion (сегменты з рухам) або active_objects (сегменты з актыўнымі аб'ектамі)."
+                }
+            }
+        }
    },
    "review": {
        "label": "Разгляд",
@@ -740,6 +804,10 @@
            "activity_context_prompt": {
                "label": "Прампт кантэксту актыўнасці",
                "description": "Уласны прампт, які апісвае, якая актыўнасць падазроная, а якая не, каб даць кантэкст для зводак GenAI."
+            },
+            "response_style": {
+                "label": "Стыль адказу",
+                "description": "Гатовы стыль пісьма для створаных апісанняў разгляду. Гатовыя стылі наладжваюць тон і падрабязнасць загалоўка, зводкі і апісання сцэны, якія бачыць карыстальнік; «default» пакідае ўбудаваны прампт без змен."
            }
        },
        "description": "Налады, якія кіруюць абвесткамі, дэтэктаваннямі і зводкамі разгляду GenAI для інтэрфейсу і сховішча."
@@ -1173,7 +1241,7 @@
        },
        "default_role": {
            "label": "Прадвызначаная роля",
-            "description": "Роля, якая прызначаецца карыстальнікам, аўтарызаваным праз проксі, калі супастаўленне роляў не спрацавала."
+            "description": "Роля, якая прызначаецца карыстальнікам, аўтарызаваным праз проксі, калі супастаўленне роляў не спрацавала. Задайце «none», каб адмовіць у доступе карыстальнікам без супастаўлення."
        },
        "separator": {
            "label": "Сімвал-раздзяляльнік",
@@ -1399,5 +1467,57 @@
            "label": "Паказваць у разглядзе",
            "description": "Ці бачная гэта камера ў разглядзе (старонка разгляду і яе фільтр камер, разгляд руху і выгляд гісторыі)."
        }
+    },
+    "models": {
+        "label": "Мадэлі дэтэктавання",
+        "description": "Мадэлі дэтэктавання аб'ектаў і абсталяванне, на якім працуе кожная з іх. Камера выбірае мадэль, супастаўляючы свой detect.scene са сцэнай мадэлі.",
+        "scene": {
+            "label": "Сцэна мадэлі",
+            "description": "Асяроддзе камеры, для якога прызначана гэтая мадэль. Камера выбірае мадэль, задаючы detect.scene з адпаведным значэннем, а «all» выкарыстоўвае любая камера, якая нічога не задала."
+        },
+        "devices": {
+            "label": "Абсталяванне дэтэктавання",
+            "description": "Абсталяванне, на якім працуе гэтая мадэль, у выглядзе «<detector>» або «<detector>:<device>» (напрыклад «edgetpu:pci:0» ці «openvino:GPU»). Калі адна прылада пазначана некалькі разоў, на ёй запускаюцца дадатковыя працэсы вывядзення."
+        },
+        "path": {
+            "label": "Шлях да мадэлі свайго дэтэктара аб'ектаў",
+            "description": "Шлях да файла свае мадэлі дэтэктавання (або plus://<model_id> для мадэлей Frigate+)."
+        },
+        "labelmap_path": {
+            "label": "Карта метак для свайго дэтэктара аб'ектаў",
+            "description": "Шлях да файла карты метак, які супастаўляе лікавыя класы з тэкставымі меткамі для дэтэктара."
+        },
+        "width": {
+            "label": "Шырыня ўваходу мадэлі дэтэктавання аб'ектаў",
+            "description": "Шырыня ўваходнага тэнзара мадэлі ў пікселях."
+        },
+        "height": {
+            "label": "Вышыня ўваходу мадэлі дэтэктавання аб'ектаў",
+            "description": "Вышыня ўваходнага тэнзара мадэлі ў пікселях."
+        },
+        "labelmap": {
+            "label": "Змяненне карты метак",
+            "description": "Перавызначэнні або пераназначэнні, якія аб'ядноўваюцца са стандартнай картай метак."
+        },
+        "attributes_map": {
+            "label": "Карта метак аб'ектаў да іх метак атрыбутаў",
+            "description": "Супастаўленне метак аб'ектаў з меткамі атрыбутаў, якія дадаюць метаданыя (напрыклад «car» -> ['license_plate'])."
+        },
+        "input_tensor": {
+            "label": "Форма ўваходнага тэнзара мадэлі",
+            "description": "Фармат тэнзара, якога чакае мадэль: «nhwc» або «nchw»."
+        },
+        "input_pixel_format": {
+            "label": "Фармат колеру пікселяў на ўваходзе мадэлі",
+            "description": "Каляровая прастора пікселяў, якой чакае мадэль: «rgb», «bgr» або «yuv»."
+        },
+        "input_dtype": {
+            "label": "Тып даных на ўваходзе мадэлі",
+            "description": "Тып даных уваходнага тэнзара мадэлі (напрыклад «float32»)."
+        },
+        "model_type": {
+            "label": "Тып мадэлі дэтэктавання аб'ектаў",
+            "description": "Тып архітэктуры мадэлі дэтэктара (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine), які некаторыя дэтэктары выкарыстоўваюць для аптымізацыі."
+        }
    }
 }
@@ -31,5 +31,8 @@
    },
    "detect": {
        "dimensionMustBeEven": "Мусіць быць цотным лікам."
+    },
+    "models": {
+        "defaultRequired": "Адна мадэль мусіць выкарыстоўваць сцэну «All cameras». Без гэтага камера, якая не выбрала сцэну, не мае мадэлі, да якой можна вярнуцца."
    }
 }
@@ -55,6 +55,12 @@
        "auto_scroll": {
            "title": "Аўтапракрутка",
            "desc": "Сачыць за новымі паведамленнямі па меры паступлення."
+        },
+        "always_allow": {
+            "title": "Заўсёды дазволеныя дзеянні",
+            "desc": "Дзеянні, якія памочнік можа выконваць без папярэдняга запыту.",
+            "none": "Няма",
+            "reset": "Скінуць"
        }
    },
    "stats": {
@@ -68,5 +74,15 @@
    },
    "thinking": {
        "toggle": "Пераключыць разважанне"
+    },
+    "approval": {
+        "title": "Ухваліць {{tool}}?",
+        "desc": "Гэтае дзеянне нешта змяняе ў Frigate. Праглядзіце падрабязнасці перад ухваленнем.",
+        "approve": "Ухваліць",
+        "always_allow": "Заўсёды дазваляць",
+        "reject": "Адхіліць",
+        "approved": "Ухвалена",
+        "rejected": "Адхілена",
+        "placeholder": "Ухваліце або адхіліце дзеянне ў чаканні, каб працягнуць"
    }
 }
@@ -91,5 +91,6 @@
    "crop": "Абрэзаць па фільтры",
    "cropAria": "Пераключыць абрэзку перадпрагляду па выбраных вобласцях",
    "cropDesc": "Набліжаць перадпрагляды да выбраных вобласцей фільтра замест паказу ўсяго кадра."
-  }
+  },
+  "subOnlyQuality": "У гэтым прамежку часу даступныя толькі запісы нізкай якасці"
 }
@@ -63,7 +63,8 @@
    "copying": "Капіяванне",
    "encoding": "Кадаванне",
    "encodingRetry": "Кадаванне (паўтор)",
-    "finalizing": "Завяршэнне"
+    "finalizing": "Завяршэнне",
+    "merging": "Аб'яднанне"
  },
  "caseView": {
    "noDescription": "Без апісання",
--- a/Show More
+++ b/Show More