add enabled field to camera profiles for enabling/disabling cameras

refactor _publish_updates to only publish ZMQ updates for
sections that actually changed, not all sections on affected cameras.

.gitignore

@@ -3,8 +3,6 @@ __pycache__
 .mypy_cache
 *.swp
 debug
-.claude/*
-.mcp.json
 .vscode/*
 !.vscode/launch.json
 config/*
@@ -21,4 +19,4 @@ web/.env
 core
 !/web/**/*.ts
 .idea/*
-.ipynb_checkpoints
+.ipynb_checkpoints

docker/tensorrt/requirements-amd64.txt

@@ -1,18 +1,18 @@
-# Nvidia ONNX Runtime GPU Support
+# NVidia TensorRT Support (amd64 only)
 --extra-index-url 'https://pypi.nvidia.com'
 cython==3.0.*; platform_machine == 'x86_64'
-nvidia-cuda-cupti-cu12==12.9.79; platform_machine == 'x86_64'
-nvidia-cublas-cu12==12.9.1.*; platform_machine == 'x86_64'
-nvidia-cudnn-cu12==9.19.0.*; platform_machine == 'x86_64'
-nvidia-cufft-cu12==11.4.1.*; platform_machine == 'x86_64'
-nvidia-curand-cu12==10.3.10.*; platform_machine == 'x86_64'
-nvidia-cuda-nvcc-cu12==12.9.86; platform_machine == 'x86_64'
-nvidia-cuda-nvrtc-cu12==12.9.86; platform_machine == 'x86_64'
-nvidia-cuda-runtime-cu12==12.9.79; platform_machine == 'x86_64'
-nvidia-cusolver-cu12==11.7.5.*; platform_machine == 'x86_64'
-nvidia-cusparse-cu12==12.5.10.*; platform_machine == 'x86_64'
-nvidia-nccl-cu12==2.29.7; platform_machine == 'x86_64'
-nvidia-nvjitlink-cu12==12.9.86; platform_machine == 'x86_64'
+nvidia_cuda_cupti_cu12==12.5.82; platform_machine == 'x86_64'
+nvidia-cublas-cu12==12.5.3.*; platform_machine == 'x86_64'
+nvidia-cudnn-cu12==9.3.0.*; platform_machine == 'x86_64'
+nvidia-cufft-cu12==11.2.3.*; platform_machine == 'x86_64'
+nvidia-curand-cu12==10.3.6.*; platform_machine == 'x86_64'
+nvidia_cuda_nvcc_cu12==12.5.82; platform_machine == 'x86_64'
+nvidia-cuda-nvrtc-cu12==12.5.82; platform_machine == 'x86_64'
+nvidia_cuda_runtime_cu12==12.5.82; platform_machine == 'x86_64'
+nvidia_cusolver_cu12==11.6.3.*; platform_machine == 'x86_64'
+nvidia_cusparse_cu12==12.5.1.*; platform_machine == 'x86_64'
+nvidia_nccl_cu12==2.23.4; platform_machine == 'x86_64'
+nvidia_nvjitlink_cu12==12.5.82; platform_machine == 'x86_64'
 onnx==1.16.*; platform_machine == 'x86_64'
-onnxruntime-gpu==1.24.*; platform_machine == 'x86_64'
+onnxruntime-gpu==1.22.*; platform_machine == 'x86_64'
 protobuf==3.20.3; platform_machine == 'x86_64'

docs/docs/configuration/motion_detection.md

@@ -38,6 +38,7 @@ Remember that motion detection is just used to determine when object detection s
 The threshold value dictates how much of a change in a pixels luminance is required to be considered motion.
 
 ```yaml
+# default threshold value
 motion:
   # Optional: The threshold passed to cv2.threshold to determine if a pixel is different enough to be counted as motion. (default: shown below)
   # Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive.
@@ -52,6 +53,7 @@ Watching the motion boxes in the debug view, increase the threshold until you on
 ### Contour Area
 
 ```yaml
+# default contour_area value
 motion:
   # Optional: Minimum size in pixels in the resized motion image that counts as motion (default: shown below)
   # Increasing this value will prevent smaller areas of motion from being detected. Decreasing will
@@ -79,49 +81,27 @@ However, if the preferred day settings do not work well at night it is recommend
 
 ## Tuning For Large Changes In Motion
 
-### Lightning Threshold
-
 ```yaml
+# default lightning_threshold:
 motion:
-  # Optional: The percentage of the image used to detect lightning or
-  #           other substantial changes where motion detection needs to
-  #           recalibrate. (default: shown below)
-  #           Increasing this value will make motion detection more likely
-  #           to consider lightning or IR mode changes as valid motion.
-  #           Decreasing this value will make motion detection more likely
-  #           to ignore large amounts of motion such as a person
-  #           approaching a doorbell camera.
+  # Optional: The percentage of the image used to detect lightning or other substantial changes where motion detection
+  #           needs to recalibrate. (default: shown below)
+  # Increasing this value will make motion detection more likely to consider lightning or ir mode changes as valid motion.
+  # Decreasing this value will make motion detection more likely to ignore large amounts of motion such as a person approaching
+  # a doorbell camera.
   lightning_threshold: 0.8
 ```
 
-Large changes in motion like PTZ moves and camera switches between Color and IR mode should result in a pause in object detection. `lightning_threshold` defines the percentage of the image used to detect these substantial changes. Increasing this value makes motion detection more likely to treat large changes (like IR mode switches) as valid motion. Decreasing it makes motion detection more likely to ignore large amounts of motion, such as a person approaching a doorbell camera.
-
-Note that `lightning_threshold` does **not** stop motion-based recordings from being saved — it only prevents additional motion analysis after the threshold is exceeded, reducing false positive object detections during high-motion periods (e.g. storms or PTZ sweeps) without interfering with recordings.
-
 :::warning
 
-Some cameras, like doorbell cameras, may have missed detections when someone walks directly in front of the camera and the `lightning_threshold` causes motion detection to recalibrate. In this case, it may be desirable to increase the `lightning_threshold` to ensure these objects are not missed.
+Some cameras like doorbell cameras may have missed detections when someone walks directly in front of the camera and the lightning_threshold causes motion detection to be re-calibrated. In this case, it may be desirable to increase the `lightning_threshold` to ensure these objects are not missed.
 
 :::
 
-### Skip Motion On Large Scene Changes
+:::note
 
-```yaml
-motion:
-  # Optional: Fraction of the frame that must change in a single update
-  #           before Frigate will completely ignore any motion in that frame.
-  #           Values range between 0.0 and 1.0, leave unset (null) to disable.
-  #           Setting this to 0.7 would cause Frigate to **skip** reporting
-  #           motion boxes when more than 70% of the image appears to change
-  #           (e.g. during lightning storms, IR/color mode switches, or other
-  #           sudden lighting events).
-  skip_motion_threshold: 0.7
-```
-
-This option is handy when you want to prevent large transient changes from triggering recordings or object detection. It differs from `lightning_threshold` because it completely suppresses motion instead of just forcing a recalibration.
-
-:::warning
-
-When the skip threshold is exceeded, **no motion is reported** for that frame, meaning **nothing is recorded** for that frame. That means you can miss something important, like a PTZ camera auto-tracking an object or activity while the camera is moving. If you prefer to guarantee that every frame is saved, leave this unset and accept occasional recordings containing scene noise — they typically only take up a few megabytes and are quick to scan in the timeline UI.
+Lightning threshold does not stop motion based recordings from being saved.
 
 :::
+
+Large changes in motion like PTZ moves and camera switches between Color and IR mode should result in a pause in object detection. This is done via the `lightning_threshold` configuration. It is defined as the percentage of the image used to detect lightning or other substantial changes where motion detection needs to recalibrate. Increasing this value will make motion detection more likely to consider lightning or IR mode changes as valid motion. Decreasing this value will make motion detection more likely to ignore large amounts of motion such as a person approaching a doorbell camera.

docs/docs/configuration/reference.md

@@ -480,16 +480,12 @@ motion:
   # Increasing this value will make motion detection less sensitive and decreasing it will make motion detection more sensitive.
   # The value should be between 1 and 255.
   threshold: 30
-  # Optional: The percentage of the image used to detect lightning or other substantial changes where motion detection needs
-  # to recalibrate and motion checks stop for that frame. Recordings are unaffected. (default: shown below)
+  # Optional: The percentage of the image used to detect lightning or other substantial changes where motion detection
+  #           needs to recalibrate. (default: shown below)
   # Increasing this value will make motion detection more likely to consider lightning or ir mode changes as valid motion.
-  # Decreasing this value will make motion detection more likely to ignore large amounts of motion such as a person approaching a doorbell camera.
+  # Decreasing this value will make motion detection more likely to ignore large amounts of motion such as a person approaching
+  # a doorbell camera.
   lightning_threshold: 0.8
-  # Optional: Fraction of the frame that must change in a single update before motion boxes are completely
-  # ignored. Values range between 0.0 and 1.0. When exceeded, no motion boxes are reported and **no motion
-  # recording** is created for that frame. Leave unset (null) to disable this feature. Use with care on PTZ
-  # cameras or other situations where you require guaranteed frame capture.
-  skip_motion_threshold: None
   # Optional: Minimum size in pixels in the resized motion image that counts as motion (default: shown below)
   # Increasing this value will prevent smaller areas of motion from being detected. Decreasing will
   # make motion detection more sensitive to smaller moving objects.

docs/docs/configuration/semantic_search.md

@@ -76,40 +76,6 @@ Switching between V1 and V2 requires reindexing your embeddings. The embeddings
 
 :::
 
-### GenAI Provider
-
-Frigate can use a GenAI provider for semantic search embeddings when that provider has the `embeddings` role. Currently, only **llama.cpp** supports multimodal embeddings (both text and images).
-
-To use llama.cpp for semantic search:
-
-1. Configure a GenAI provider in your config with `embeddings` in its `roles`.
-2. Set `semantic_search.model` to the GenAI config key (e.g. `default`).
-3. Start the llama.cpp server with `--embeddings` and `--mmproj` for image support:
-
-```yaml
-genai:
-  default:
-    provider: llamacpp
-    base_url: http://localhost:8080
-    model: your-model-name
-    roles:
-      - embeddings
-      - vision
-      - tools
-
-semantic_search:
-  enabled: True
-  model: default
-```
-
-The llama.cpp server must be started with `--embeddings` for the embeddings API, and a multi-modal embeddings model. See the [llama.cpp server documentation](https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md) for details.
-
-:::note
-
-Switching between Jina models and a GenAI provider requires reindexing. Embeddings from different backends are incompatible.
-
-:::
-
 ### GPU Acceleration
 
 The CLIP models are downloaded in ONNX format, and the `large` model can be accelerated using GPU hardware, when available. This depends on the Docker build that is used. You can also target a specific device in a multi-GPU installation.

docs/docs/integrations/mqtt.md

@@ -159,8 +159,7 @@ Published when a license plate is recognized on a car object. See the [License P
   "plate": "123ABC",
   "score": 0.95,
   "camera": "driveway_cam",
-  "timestamp": 1607123958.748393,
-  "plate_box": [917, 487, 1029, 529] // box coordinates of the detected license plate in the frame
+  "timestamp": 1607123958.748393
 }
 ```
 

docs/docs/troubleshooting/dummy-camera.md

@@ -3,67 +3,17 @@ id: dummy-camera
 title: Analyzing Object Detection
 ---
 
-Frigate provides several tools for investigating object detection and tracking behavior: reviewing recorded detections through the UI, using the built-in Debug Replay feature, and manually setting up a dummy camera for advanced scenarios.
+When investigating object detection or tracking problems, it can be helpful to replay an exported video as a temporary "dummy" camera. This lets you reproduce issues locally, iterate on configuration (detections, zones, enrichment settings), and capture logs and clips for analysis.
 
-## Reviewing Detections in the UI
+## When to use
 
-Before setting up a replay, you can often diagnose detection issues by reviewing existing recordings directly in the Frigate UI.
+- Replaying an exported clip to reproduce incorrect detections
+- Testing configuration changes (model settings, trackers, filters) against a known clip
+- Gathering deterministic logs and recordings for debugging or issue reports
 
-### Detail View (History)
+## Example Config
 
-The **Detail Stream** view in History shows recorded video with detection overlays (bounding boxes, path points, and zone highlights) drawn on top. Select a review item to see its tracked objects and lifecycle events. Clicking a lifecycle event seeks the video to that point so you can see exactly what the detector saw.
-
-### Tracking Details (Explore)
-
-In **Explore**, clicking a thumbnail opens the **Tracking Details** pane, which shows the full lifecycle of a single tracked object: every detection, zone entry/exit, and attribute change. The video plays back with the bounding box overlaid, letting you step through the object's entire lifecycle.
-
-### Annotation Offset
-
-Both views support an **Annotation Offset** setting (`detect.annotation_offset` in your camera config) that shifts the detection overlay in time relative to the recorded video. This compensates for the timing drift between the `detect` and `record` pipelines.
-
-These streams use fundamentally different clocks with different buffering and latency characteristics, so the detection data and the recorded video are never perfectly synchronized. The annotation offset shifts the overlay to visually align the bounding boxes with the objects in the recorded video.
-
-#### Why the offset varies between clips
-
-The base timing drift between detect and record is roughly constant for a given camera, so a single offset value works well on average. However, you may notice the alignment is not pixel-perfect in every clip. This is normal and caused by several factors:
-
-- **Keyframe-constrained seeking**: When the browser seeks to a timestamp, it can only land on the nearest keyframe. Each recording segment has keyframes at different positions relative to the detection timestamps, so the same offset may land slightly early in one clip and slightly late in another.
-- **Segment boundary trimming**: When a recording range starts mid-segment, the video is trimmed to the requested start point. This trim may not align with a keyframe, shifting the effective reference point.
-- **Capture-time jitter**: Network buffering, camera buffer flushes, and ffmpeg's own buffering mean the system-clock timestamp and the corresponding recorded frame are not always offset by exactly the same amount.
-
-The per-clip variation is typically quite low and is mostly an artifact of keyframe granularity rather than a change in the true drift. A "perfect" alignment would require per-frame, keyframe-aware offset compensation, which is not practical. Treat the annotation offset as a best-effort average for your camera.
-
-## Debug Replay
-
-Debug Replay lets you re-run Frigate's detection pipeline against a section of recorded video without manually configuring a dummy camera. It automatically extracts the recording, creates a temporary camera with the same detection settings as the original, and loops the clip through the pipeline so you can observe detections in real time.
-
-### When to use
-
-- Reproducing a detection or tracking issue from a specific time range
-- Testing configuration changes (model settings, zones, filters, motion) against a known clip
-- Gathering logs and debug overlays for a bug report
-
-:::note
-
-Only one replay session can be active at a time. If a session is already running, you will be prompted to navigate to it or stop it first.
-
-:::
-
-### Variables to consider
-
-- The replay will not always produce identical results to the original run. Different frames may be selected on replay, which can change detections and tracking.
-- Motion detection depends on the exact frames used; small frame shifts can change motion regions and therefore what gets passed to the detector.
-- Object detection is not fully deterministic: models and post-processing can yield slightly different results across runs.
-
-Treat the replay as a close approximation rather than an exact reproduction. Run multiple loops and examine the debug overlays and logs to understand the behavior.
-
-## Manual Dummy Camera
-
-For advanced scenarios — such as testing with a clip from a different source, debugging ffmpeg behavior, or running a clip through a completely custom configuration — you can set up a dummy camera manually.
-
-### Example config
-
-Place the clip you want to replay in a location accessible to Frigate (for example `/media/frigate/` or the repository `debug/` folder when developing). Then add a temporary camera to your `config/config.yml`:
+Place the clip you want to replay in a location accessible to Frigate (for example `/media/frigate/` or the repository `debug/` folder when developing). Then add a temporary camera to your `config/config.yml` like this:
 
 ```yaml
 cameras:
@@ -82,10 +32,10 @@ cameras:
       enabled: false
 ```
 
-- `-re -stream_loop -1` tells ffmpeg to play the file in real time and loop indefinitely.
-- `-fflags +genpts` generates presentation timestamps when they are missing in the file.
+- `-re -stream_loop -1` tells `ffmpeg` to play the file in realtime and loop indefinitely, which is useful for long debugging sessions.
+- `-fflags +genpts` helps generate presentation timestamps when they are missing in the file.
 
-### Steps
+## Steps
 
 1. Export or copy the clip you want to replay to the Frigate host (e.g., `/media/frigate/` or `debug/clips/`). Depending on what you are looking to debug, it is often helpful to add some "pre-capture" time (where the tracked object is not yet visible) to the clip when exporting.
 2. Add the temporary camera to `config/config.yml` (example above). Use a unique name such as `test` or `replay_camera` so it's easy to remove later.
@@ -95,8 +45,16 @@ cameras:
 5. Iterate on camera or enrichment settings (model, fps, zones, filters) and re-check the replay until the behavior is resolved.
 6. Remove the temporary camera from your config after debugging to avoid spurious telemetry or recordings.
 
-### Troubleshooting
+## Variables to consider in object tracking
 
-- **No video**: verify the file path is correct and accessible from the Frigate process/container.
-- **FFmpeg errors**: check the log output and adjust `input_args` for your file format. You may also need to disable hardware acceleration (`hwaccel_args: ""`) for the dummy camera.
-- **No detections**: confirm the camera `roles` include `detect` and that the model/detector configuration is enabled.
+- The exported video will not always line up exactly with how it originally ran through Frigate (or even with the last loop). Different frames may be used on replay, which can change detections and tracking.
+- Motion detection depends on the frames used; small frame shifts can change motion regions and therefore what gets passed to the detector.
+- Object detection is not deterministic: models and post-processing can yield different results across runs, so you may not get identical detections or track IDs every time.
+
+When debugging, treat the replay as a close approximation rather than a byte-for-byte replay. Capture multiple runs, enable recording if helpful, and examine logs and saved event clips to understand variability.
+
+## Troubleshooting
+
+- No video: verify the path is correct and accessible from the Frigate process/container.
+- FFmpeg errors: check the log output for ffmpeg-specific flags and adjust `input_args` accordingly for your file/container. You may also need to disable hardware acceleration (`hwaccel_args: ""`) for the dummy camera.
+- No detections: confirm the camera `roles` include `detect`, and model/detector configuration is enabled.

frigate/api/app.py

@@ -628,38 +628,23 @@ def config_set(request: Request, body: AppConfigSetBody):
                 request.app.frigate_config = config
                 request.app.genai_manager.update_config(config)
 
-                if request.app.stats_emitter is not None:
-                    request.app.stats_emitter.config = config
-
                 if body.update_topic:
                     if body.update_topic.startswith("config/cameras/"):
                         _, _, camera, field = body.update_topic.split("/")
 
-                        if camera == "*":
-                            # Wildcard: fan out update to all cameras
-                            enum_value = CameraConfigUpdateEnum[field]
-                            for camera_name in config.cameras:
-                                settings = config.get_nested_object(
-                                    f"config/cameras/{camera_name}/{field}"
-                                )
-                                request.app.config_publisher.publish_update(
-                                    CameraConfigUpdateTopic(enum_value, camera_name),
-                                    settings,
-                                )
+                        if field == "add":
+                            settings = config.cameras[camera]
+                        elif field == "remove":
+                            settings = old_config.cameras[camera]
                         else:
-                            if field == "add":
-                                settings = config.cameras[camera]
-                            elif field == "remove":
-                                settings = old_config.cameras[camera]
-                            else:
-                                settings = config.get_nested_object(body.update_topic)
+                            settings = config.get_nested_object(body.update_topic)
 
-                            request.app.config_publisher.publish_update(
-                                CameraConfigUpdateTopic(
-                                    CameraConfigUpdateEnum[field], camera
-                                ),
-                                settings,
-                            )
+                        request.app.config_publisher.publish_update(
+                            CameraConfigUpdateTopic(
+                                CameraConfigUpdateEnum[field], camera
+                            ),
+                            settings,
+                        )
                     else:
                         # Generic handling for global config updates
                         settings = config.get_nested_object(body.update_topic)

frigate/api/auth.py

@@ -32,12 +32,6 @@ from frigate.models import User
 
 logger = logging.getLogger(__name__)
 
-# In-memory cache to track which clients we've logged for an anonymous access event.
-# Keyed by a hashed value combining remote address + user-agent. The value is
-# an expiration timestamp (float).
-FIRST_LOAD_TTL_SECONDS = 60 * 60 * 24 * 7  # 7 days
-_first_load_seen: dict[str, float] = {}
-
 
 def require_admin_by_default():
     """
@@ -290,15 +284,6 @@ def get_remote_addr(request: Request):
     return remote_addr or "127.0.0.1"
 
 
-def _cleanup_first_load_seen() -> None:
-    """Cleanup expired entries in the in-memory first-load cache."""
-    now = time.time()
-    # Build list for removal to avoid mutating dict during iteration
-    expired = [k for k, exp in _first_load_seen.items() if exp <= now]
-    for k in expired:
-        del _first_load_seen[k]
-
-
 def get_jwt_secret() -> str:
     jwt_secret = None
     # check env var
@@ -759,30 +744,10 @@ def profile(request: Request):
     roles_dict = request.app.frigate_config.auth.roles
     allowed_cameras = User.get_allowed_cameras(role, roles_dict, all_camera_names)
 
-    response = JSONResponse(
+    return JSONResponse(
         content={"username": username, "role": role, "allowed_cameras": allowed_cameras}
     )
 
-    if username == "anonymous":
-        try:
-            remote_addr = get_remote_addr(request)
-        except Exception:
-            remote_addr = (
-                request.client.host if hasattr(request, "client") else "unknown"
-            )
-
-        ua = request.headers.get("user-agent", "")
-        key_material = f"{remote_addr}|{ua}"
-        cache_key = hashlib.sha256(key_material.encode()).hexdigest()
-
-        _cleanup_first_load_seen()
-        now = time.time()
-        if cache_key not in _first_load_seen:
-            _first_load_seen[cache_key] = now + FIRST_LOAD_TTL_SECONDS
-            logger.info(f"Anonymous user access from {remote_addr} ua={ua[:200]}")
-
-    return response
-
 
 @router.get(
     "/logout",

frigate/api/camera.py

@@ -1,6 +1,5 @@
 """Camera apis."""
 
-import asyncio
 import json
 import logging
 import re
@@ -12,9 +11,7 @@ import httpx
 import requests
 from fastapi import APIRouter, Depends, Query, Request, Response
 from fastapi.responses import JSONResponse
-from filelock import FileLock, Timeout
 from onvif import ONVIFCamera, ONVIFError
-from ruamel.yaml import YAML
 from zeep.exceptions import Fault, TransportError
 from zeep.transports import AsyncTransport
 
@@ -24,14 +21,8 @@ from frigate.api.auth import (
     require_role,
 )
 from frigate.api.defs.tags import Tags
-from frigate.config import FrigateConfig
-from frigate.config.camera.updater import (
-    CameraConfigUpdateEnum,
-    CameraConfigUpdateTopic,
-)
+from frigate.config.config import FrigateConfig
 from frigate.util.builtin import clean_camera_user_pass
-from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
-from frigate.util.config import find_config_file
 from frigate.util.image import run_ffmpeg_snapshot
 from frigate.util.services import ffprobe_stream
 
@@ -1004,154 +995,3 @@ async def onvif_probe(
                     await onvif_camera.close()
             except Exception as e:
                 logger.debug(f"Error closing ONVIF camera session: {e}")
-
-
-@router.delete(
-    "/cameras/{camera_name}",
-    dependencies=[Depends(require_role(["admin"]))],
-)
-async def delete_camera(
-    request: Request,
-    camera_name: str,
-    delete_exports: bool = Query(default=False),
-):
-    """Delete a camera and all its associated data.
-
-    Removes the camera from config, stops processes, and cleans up
-    all database entries and media files.
-
-    Args:
-        camera_name: Name of the camera to delete
-        delete_exports: Whether to also delete exports for this camera
-    """
-    frigate_config: FrigateConfig = request.app.frigate_config
-
-    if camera_name not in frigate_config.cameras:
-        return JSONResponse(
-            content={
-                "success": False,
-                "message": f"Camera {camera_name} not found",
-            },
-            status_code=404,
-        )
-
-    old_camera_config = frigate_config.cameras[camera_name]
-    config_file = find_config_file()
-    lock = FileLock(f"{config_file}.lock", timeout=5)
-
-    try:
-        with lock:
-            with open(config_file, "r") as f:
-                old_raw_config = f.read()
-
-            try:
-                yaml = YAML()
-                yaml.indent(mapping=2, sequence=4, offset=2)
-
-                with open(config_file, "r") as f:
-                    data = yaml.load(f)
-
-                # Remove camera from config
-                if "cameras" in data and camera_name in data["cameras"]:
-                    del data["cameras"][camera_name]
-
-                # Remove camera from auth roles
-                auth = data.get("auth", {})
-                if auth and "roles" in auth:
-                    empty_roles = []
-                    for role_name, cameras_list in auth["roles"].items():
-                        if (
-                            isinstance(cameras_list, list)
-                            and camera_name in cameras_list
-                        ):
-                            cameras_list.remove(camera_name)
-                            # Custom roles can't be empty; mark for removal
-                            if not cameras_list and role_name not in (
-                                "admin",
-                                "viewer",
-                            ):
-                                empty_roles.append(role_name)
-                    for role_name in empty_roles:
-                        del auth["roles"][role_name]
-
-                with open(config_file, "w") as f:
-                    yaml.dump(data, f)
-
-                with open(config_file, "r") as f:
-                    new_raw_config = f.read()
-
-                try:
-                    config = FrigateConfig.parse(new_raw_config)
-                except Exception:
-                    with open(config_file, "w") as f:
-                        f.write(old_raw_config)
-                    logger.exception(
-                        "Config error after removing camera %s",
-                        camera_name,
-                    )
-                    return JSONResponse(
-                        content={
-                            "success": False,
-                            "message": "Error parsing config after camera removal",
-                        },
-                        status_code=400,
-                    )
-            except Exception as e:
-                logger.error(
-                    "Error updating config to remove camera %s: %s", camera_name, e
-                )
-                return JSONResponse(
-                    content={
-                        "success": False,
-                        "message": "Error updating config",
-                    },
-                    status_code=500,
-                )
-
-            # Update runtime config
-            request.app.frigate_config = config
-            request.app.genai_manager.update_config(config)
-
-            # Publish removal to stop ffmpeg processes and clean up runtime state
-            request.app.config_publisher.publish_update(
-                CameraConfigUpdateTopic(CameraConfigUpdateEnum.remove, camera_name),
-                old_camera_config,
-            )
-
-    except Timeout:
-        return JSONResponse(
-            content={
-                "success": False,
-                "message": "Another process is currently updating the config",
-            },
-            status_code=409,
-        )
-
-    # Clean up database entries
-    counts, export_paths = await asyncio.to_thread(
-        cleanup_camera_db, camera_name, delete_exports
-    )
-
-    # Clean up media files in background thread
-    await asyncio.to_thread(
-        cleanup_camera_files, camera_name, export_paths if delete_exports else None
-    )
-
-    # Best-effort go2rtc stream removal
-    try:
-        requests.delete(
-            "http://127.0.0.1:1984/api/streams",
-            params={"src": camera_name},
-            timeout=5,
-        )
-    except Exception:
-        logger.debug("Failed to remove go2rtc stream for %s", camera_name)
-
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": f"Camera {camera_name} has been deleted",
-            "cleanup": counts,
-        },
-        status_code=200,
-    )

frigate/api/defs/tags.py

@@ -11,7 +11,6 @@ class Tags(Enum):
     classification = "Classification"
     logs = "Logs"
     media = "Media"
-    motion_search = "Motion Search"
     notifications = "Notifications"
     preview = "Preview"
     recordings = "Recordings"

frigate/api/fastapi_app.py

@@ -22,7 +22,6 @@ from frigate.api import (
     event,
     export,
     media,
-    motion_search,
     notification,
     preview,
     record,
@@ -138,7 +137,6 @@ def create_fastapi_app(
     app.include_router(export.router)
     app.include_router(event.router)
     app.include_router(media.router)
-    app.include_router(motion_search.router)
     app.include_router(record.router)
     app.include_router(debug_replay.router)
     # App Properties

frigate/api/media.py

@@ -24,7 +24,6 @@ from tzlocal import get_localzone_name
 from frigate.api.auth import (
     allow_any_authenticated,
     require_camera_access,
-    require_role,
 )
 from frigate.api.defs.query.media_query_parameters import (
     Extension,
@@ -1006,23 +1005,6 @@ def grid_snapshot(
         )
 
 
-@router.delete(
-    "/{camera_name}/region_grid", dependencies=[Depends(require_role("admin"))]
-)
-def clear_region_grid(request: Request, camera_name: str):
-    """Clear the region grid for a camera."""
-    if camera_name not in request.app.frigate_config.cameras:
-        return JSONResponse(
-            content={"success": False, "message": "Camera not found"},
-            status_code=404,
-        )
-
-    Regions.delete().where(Regions.camera == camera_name).execute()
-    return JSONResponse(
-        content={"success": True, "message": "Region grid cleared"},
-    )
-
-
 @router.get(
     "/events/{event_id}/snapshot-clean.webp",
     dependencies=[Depends(require_camera_access)],
@@ -1281,13 +1263,6 @@ def preview_gif(
     else:
         # need to generate from existing images
         preview_dir = os.path.join(CACHE_DIR, "preview_frames")
-
-        if not os.path.isdir(preview_dir):
-            return JSONResponse(
-                content={"success": False, "message": "Preview not found"},
-                status_code=404,
-            )
-
         file_start = f"preview_{camera_name}"
         start_file = f"{file_start}-{start_ts}.{PREVIEW_FRAME_TYPE}"
         end_file = f"{file_start}-{end_ts}.{PREVIEW_FRAME_TYPE}"
@@ -1463,13 +1438,6 @@ def preview_mp4(
     else:
         # need to generate from existing images
         preview_dir = os.path.join(CACHE_DIR, "preview_frames")
-
-        if not os.path.isdir(preview_dir):
-            return JSONResponse(
-                content={"success": False, "message": "Preview not found"},
-                status_code=404,
-            )
-
         file_start = f"preview_{camera_name}"
         start_file = f"{file_start}-{start_ts}.{PREVIEW_FRAME_TYPE}"
         end_file = f"{file_start}-{end_ts}.{PREVIEW_FRAME_TYPE}"

frigate/api/motion_search.py

@@ -1,292 +0,0 @@
-"""Motion search API for detecting changes within a region of interest."""
-
-import logging
-from typing import Any, List, Optional
-
-from fastapi import APIRouter, Depends, Request
-from fastapi.responses import JSONResponse
-from pydantic import BaseModel, Field
-
-from frigate.api.auth import require_camera_access
-from frigate.api.defs.tags import Tags
-from frigate.jobs.motion_search import (
-    cancel_motion_search_job,
-    get_motion_search_job,
-    start_motion_search_job,
-)
-from frigate.types import JobStatusTypesEnum
-
-logger = logging.getLogger(__name__)
-
-router = APIRouter(tags=[Tags.motion_search])
-
-
-class MotionSearchRequest(BaseModel):
-    """Request body for motion search."""
-
-    start_time: float = Field(description="Start timestamp for the search range")
-    end_time: float = Field(description="End timestamp for the search range")
-    polygon_points: List[List[float]] = Field(
-        description="List of [x, y] normalized coordinates (0-1) defining the ROI polygon"
-    )
-    threshold: int = Field(
-        default=30,
-        ge=1,
-        le=255,
-        description="Pixel difference threshold (1-255)",
-    )
-    min_area: float = Field(
-        default=5.0,
-        ge=0.1,
-        le=100.0,
-        description="Minimum change area as a percentage of the ROI",
-    )
-    frame_skip: int = Field(
-        default=5,
-        ge=1,
-        le=30,
-        description="Process every Nth frame (1=all frames, 5=every 5th frame)",
-    )
-    parallel: bool = Field(
-        default=False,
-        description="Enable parallel scanning across segments",
-    )
-    max_results: int = Field(
-        default=25,
-        ge=1,
-        le=200,
-        description="Maximum number of search results to return",
-    )
-
-
-class MotionSearchResult(BaseModel):
-    """A single search result with timestamp and change info."""
-
-    timestamp: float = Field(description="Timestamp where change was detected")
-    change_percentage: float = Field(description="Percentage of ROI area that changed")
-
-
-class MotionSearchMetricsResponse(BaseModel):
-    """Metrics collected during motion search execution."""
-
-    segments_scanned: int = 0
-    segments_processed: int = 0
-    metadata_inactive_segments: int = 0
-    heatmap_roi_skip_segments: int = 0
-    fallback_full_range_segments: int = 0
-    frames_decoded: int = 0
-    wall_time_seconds: float = 0.0
-    segments_with_errors: int = 0
-
-
-class MotionSearchStartResponse(BaseModel):
-    """Response when motion search job starts."""
-
-    success: bool
-    message: str
-    job_id: str
-
-
-class MotionSearchStatusResponse(BaseModel):
-    """Response containing job status and results."""
-
-    success: bool
-    message: str
-    status: str  # "queued", "running", "success", "failed", or "cancelled"
-    results: Optional[List[MotionSearchResult]] = None
-    total_frames_processed: Optional[int] = None
-    error_message: Optional[str] = None
-    metrics: Optional[MotionSearchMetricsResponse] = None
-
-
-@router.post(
-    "/{camera_name}/search/motion",
-    response_model=MotionSearchStartResponse,
-    dependencies=[Depends(require_camera_access)],
-    summary="Start motion search job",
-    description="""Starts an asynchronous search for significant motion changes within
-    a user-defined Region of Interest (ROI) over a specified time range. Returns a job_id
-    that can be used to poll for results.""",
-)
-async def start_motion_search(
-    request: Request,
-    camera_name: str,
-    body: MotionSearchRequest,
-):
-    """Start an async motion search job."""
-    config = request.app.frigate_config
-
-    if camera_name not in config.cameras:
-        return JSONResponse(
-            content={"success": False, "message": f"Camera {camera_name} not found"},
-            status_code=404,
-        )
-
-    # Validate polygon has at least 3 points
-    if len(body.polygon_points) < 3:
-        return JSONResponse(
-            content={
-                "success": False,
-                "message": "Polygon must have at least 3 points",
-            },
-            status_code=400,
-        )
-
-    # Validate time range
-    if body.start_time >= body.end_time:
-        return JSONResponse(
-            content={
-                "success": False,
-                "message": "Start time must be before end time",
-            },
-            status_code=400,
-        )
-
-    # Start the job using the jobs module
-    job_id = start_motion_search_job(
-        config=config,
-        camera_name=camera_name,
-        start_time=body.start_time,
-        end_time=body.end_time,
-        polygon_points=body.polygon_points,
-        threshold=body.threshold,
-        min_area=body.min_area,
-        frame_skip=body.frame_skip,
-        parallel=body.parallel,
-        max_results=body.max_results,
-    )
-
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": "Search job started",
-            "job_id": job_id,
-        }
-    )
-
-
-@router.get(
-    "/{camera_name}/search/motion/{job_id}",
-    response_model=MotionSearchStatusResponse,
-    dependencies=[Depends(require_camera_access)],
-    summary="Get motion search job status",
-    description="Returns the status and results (if complete) of a motion search job.",
-)
-async def get_motion_search_status_endpoint(
-    request: Request,
-    camera_name: str,
-    job_id: str,
-):
-    """Get the status of a motion search job."""
-    config = request.app.frigate_config
-
-    if camera_name not in config.cameras:
-        return JSONResponse(
-            content={"success": False, "message": f"Camera {camera_name} not found"},
-            status_code=404,
-        )
-
-    job = get_motion_search_job(job_id)
-    if not job:
-        return JSONResponse(
-            content={"success": False, "message": "Job not found"},
-            status_code=404,
-        )
-
-    api_status = job.status
-
-    # Build response content
-    response_content: dict[str, Any] = {
-        "success": api_status != JobStatusTypesEnum.failed,
-        "status": api_status,
-    }
-
-    if api_status == JobStatusTypesEnum.failed:
-        response_content["message"] = job.error_message or "Search failed"
-        response_content["error_message"] = job.error_message
-    elif api_status == JobStatusTypesEnum.cancelled:
-        response_content["message"] = "Search cancelled"
-        response_content["total_frames_processed"] = job.total_frames_processed
-    elif api_status == JobStatusTypesEnum.success:
-        response_content["message"] = "Search complete"
-        if job.results:
-            response_content["results"] = job.results.get("results", [])
-            response_content["total_frames_processed"] = job.results.get(
-                "total_frames_processed", job.total_frames_processed
-            )
-        else:
-            response_content["results"] = []
-            response_content["total_frames_processed"] = job.total_frames_processed
-    else:
-        response_content["message"] = "Job processing"
-        response_content["total_frames_processed"] = job.total_frames_processed
-        # Include partial results if available (streaming)
-        if job.results:
-            response_content["results"] = job.results.get("results", [])
-            response_content["total_frames_processed"] = job.results.get(
-                "total_frames_processed", job.total_frames_processed
-            )
-
-    # Include metrics if available
-    if job.metrics:
-        response_content["metrics"] = job.metrics.to_dict()
-
-    return JSONResponse(content=response_content)
-
-
-@router.post(
-    "/{camera_name}/search/motion/{job_id}/cancel",
-    dependencies=[Depends(require_camera_access)],
-    summary="Cancel motion search job",
-    description="Cancels an active motion search job if it is still processing.",
-)
-async def cancel_motion_search_endpoint(
-    request: Request,
-    camera_name: str,
-    job_id: str,
-):
-    """Cancel an active motion search job."""
-    config = request.app.frigate_config
-
-    if camera_name not in config.cameras:
-        return JSONResponse(
-            content={"success": False, "message": f"Camera {camera_name} not found"},
-            status_code=404,
-        )
-
-    job = get_motion_search_job(job_id)
-    if not job:
-        return JSONResponse(
-            content={"success": False, "message": "Job not found"},
-            status_code=404,
-        )
-
-    # Check if already finished
-    api_status = job.status
-    if api_status not in (JobStatusTypesEnum.queued, JobStatusTypesEnum.running):
-        return JSONResponse(
-            content={
-                "success": True,
-                "message": "Job already finished",
-                "status": api_status,
-            }
-        )
-
-    # Request cancellation
-    cancelled = cancel_motion_search_job(job_id)
-    if cancelled:
-        return JSONResponse(
-            content={
-                "success": True,
-                "message": "Search cancelled",
-                "status": "cancelled",
-            }
-        )
-
-    return JSONResponse(
-        content={
-            "success": False,
-            "message": "Failed to cancel job",
-        },
-        status_code=500,
-    )

frigate/api/record.py

@@ -261,7 +261,6 @@ async def recordings(
             Recordings.segment_size,
             Recordings.motion,
             Recordings.objects,
-            Recordings.motion_heatmap,
             Recordings.duration,
         )
         .where(

frigate/app.py

@@ -52,7 +52,6 @@ from frigate.embeddings import EmbeddingProcess, EmbeddingsContext
 from frigate.events.audio import AudioProcessor
 from frigate.events.cleanup import EventCleanup
 from frigate.events.maintainer import EventProcessor
-from frigate.jobs.motion_search import stop_all_motion_search_jobs
 from frigate.log import _stop_logging
 from frigate.models import (
     Event,
@@ -617,9 +616,6 @@ class FrigateApp:
         # used by the docker healthcheck
         Path("/dev/shm/.frigate-is-stopping").touch()
 
-        # Cancel any running motion search jobs before setting stop_event
-        stop_all_motion_search_jobs()
-
         self.stop_event.set()
 
         # set an end_time on entries without an end_time before exiting

frigate/config/camera/camera.py

@@ -249,14 +249,6 @@ class CameraConfig(FrigateBaseModel):
     def create_ffmpeg_cmds(self):
         if "_ffmpeg_cmds" in self:
             return
-        self._build_ffmpeg_cmds()
-
-    def recreate_ffmpeg_cmds(self):
-        """Force regeneration of ffmpeg commands from current config."""
-        self._build_ffmpeg_cmds()
-
-    def _build_ffmpeg_cmds(self):
-        """Build ffmpeg commands from the current ffmpeg config."""
         ffmpeg_cmds = []
         for ffmpeg_input in self.ffmpeg.inputs:
             ffmpeg_cmd = self._get_ffmpeg_cmd(ffmpeg_input)

frigate/config/camera/motion.py

@@ -24,17 +24,10 @@ class MotionConfig(FrigateBaseModel):
     lightning_threshold: float = Field(
         default=0.8,
         title="Lightning threshold",
-        description="Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0). This does not prevent motion detection entirely; it merely causes the detector to stop analyzing additional frames once the threshold is exceeded. Motion-based recordings are still created during these events.",
+        description="Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0).",
         ge=0.3,
         le=1.0,
     )
-    skip_motion_threshold: Optional[float] = Field(
-        default=None,
-        title="Skip motion threshold",
-        description="If set to a value between 0.0 and 1.0, and more than this fraction of the image changes in a single frame, the detector will return no motion boxes and immediately recalibrate. This can save CPU and reduce false positives during lightning, storms, etc., but may miss real events such as a PTZ camera auto‑tracking an object. The trade‑off is between dropping a few megabytes of recordings versus reviewing a couple short clips. Leave unset (None) to disable this feature.",
-        ge=0.0,
-        le=1.0,
-    )
     improve_contrast: bool = Field(
         default=True,
         title="Improve contrast",

frigate/config/camera/profile.py

@@ -12,7 +12,6 @@ from .objects import ObjectConfig
 from .record import RecordConfig
 from .review import ReviewConfig
 from .snapshots import SnapshotsConfig
-from .zone import ZoneConfig
 
 __all__ = ["CameraProfileConfig"]
 
@@ -35,4 +34,3 @@ class CameraProfileConfig(FrigateBaseModel):
     record: Optional[RecordConfig] = None
     review: Optional[ReviewConfig] = None
     snapshots: Optional[SnapshotsConfig] = None
-    zones: Optional[dict[str, ZoneConfig]] = None

frigate/config/camera/updater.py

@@ -17,7 +17,6 @@ class CameraConfigUpdateEnum(str, Enum):
     birdseye = "birdseye"
     detect = "detect"
     enabled = "enabled"
-    ffmpeg = "ffmpeg"
     motion = "motion"  # includes motion and motion masks
     notifications = "notifications"
     objects = "objects"
@@ -92,9 +91,6 @@ class CameraConfigUpdateSubscriber:
 
         if update_type == CameraConfigUpdateEnum.audio:
             config.audio = updated_config
-        elif update_type == CameraConfigUpdateEnum.ffmpeg:
-            config.ffmpeg = updated_config
-            config.recreate_ffmpeg_cmds()
         elif update_type == CameraConfigUpdateEnum.audio_transcription:
             config.audio_transcription = updated_config
         elif update_type == CameraConfigUpdateEnum.birdseye:

frigate/config/classification.py

@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Dict, List, Optional, Union
+from typing import Dict, List, Optional
 
 from pydantic import ConfigDict, Field
 
@@ -173,10 +173,10 @@ class SemanticSearchConfig(FrigateBaseModel):
         title="Reindex on startup",
         description="Trigger a full reindex of historical tracked objects into the embeddings database.",
     )
-    model: Optional[Union[SemanticSearchModelEnum, str]] = Field(
+    model: Optional[SemanticSearchModelEnum] = Field(
         default=SemanticSearchModelEnum.jinav1,
-        title="Semantic search model or GenAI provider name",
-        description="The embeddings model to use for semantic search (for example 'jinav1'), or the name of a GenAI provider with the embeddings role.",
+        title="Semantic search model",
+        description="The embeddings model to use for semantic search (for example 'jinav1').",
     )
     model_size: str = Field(
         default="small",

frigate/config/config.py

@@ -61,7 +61,6 @@ from .classification import (
     FaceRecognitionConfig,
     LicensePlateRecognitionConfig,
     SemanticSearchConfig,
-    SemanticSearchModelEnum,
 )
 from .database import DatabaseConfig
 from .env import EnvVars
@@ -600,24 +599,6 @@ class FrigateConfig(FrigateBaseModel):
                     )
                 role_to_name[role] = name
 
-        # validate semantic_search.model when it is a GenAI provider name
-        if (
-            self.semantic_search.enabled
-            and isinstance(self.semantic_search.model, str)
-            and not isinstance(self.semantic_search.model, SemanticSearchModelEnum)
-        ):
-            if self.semantic_search.model not in self.genai:
-                raise ValueError(
-                    f"semantic_search.model '{self.semantic_search.model}' is not a "
-                    "valid GenAI config key. Must match a key in genai config."
-                )
-            genai_cfg = self.genai[self.semantic_search.model]
-            if GenAIRoleEnum.embeddings not in genai_cfg.roles:
-                raise ValueError(
-                    f"GenAI provider '{self.semantic_search.model}' must have "
-                    "'embeddings' in its roles for semantic search."
-                )
-
         # set default min_score for object attributes
         for attribute in self.model.all_attributes:
             if not self.objects.filters.get(attribute):

frigate/config/profile_manager.py

@@ -1,6 +1,5 @@
 """Profile manager for activating/deactivating named config profiles."""
 
-import copy
 import logging
 from pathlib import Path
 from typing import Optional
@@ -10,7 +9,6 @@ from frigate.config.camera.updater import (
     CameraConfigUpdatePublisher,
     CameraConfigUpdateTopic,
 )
-from frigate.config.camera.zone import ZoneConfig
 from frigate.const import CONFIG_DIR
 from frigate.util.builtin import deep_merge
 from frigate.util.config import apply_section_update
@@ -46,15 +44,13 @@ class ProfileManager:
         self.config_updater = config_updater
         self._base_configs: dict[str, dict[str, dict]] = {}
         self._base_enabled: dict[str, bool] = {}
-        self._base_zones: dict[str, dict[str, ZoneConfig]] = {}
         self._snapshot_base_configs()
 
     def _snapshot_base_configs(self) -> None:
-        """Snapshot each camera's current section configs, enabled, and zones."""
+        """Snapshot each camera's current section configs and enabled state."""
         for cam_name, cam_config in self.config.cameras.items():
             self._base_configs[cam_name] = {}
             self._base_enabled[cam_name] = cam_config.enabled
-            self._base_zones[cam_name] = copy.deepcopy(cam_config.zones)
             for section in PROFILE_SECTION_UPDATES:
                 section_config = getattr(cam_config, section, None)
                 if section_config is not None:
@@ -109,12 +105,6 @@ class ProfileManager:
                 cam_config.enabled = base_enabled
                 changed.setdefault(cam_name, set()).add("enabled")
 
-            # Restore zones
-            base_zones = self._base_zones.get(cam_name)
-            if base_zones is not None and cam_config.zones != base_zones:
-                cam_config.zones = copy.deepcopy(base_zones)
-                changed.setdefault(cam_name, set()).add("zones")
-
             # Restore section configs
             base = self._base_configs.get(cam_name, {})
             for section in PROFILE_SECTION_UPDATES:
@@ -146,14 +136,6 @@ class ProfileManager:
                 cam_config.enabled = profile.enabled
                 changed.setdefault(cam_name, set()).add("enabled")
 
-            # Apply zones override — merge profile zones into base zones
-            if profile.zones is not None:
-                base_zones = self._base_zones.get(cam_name, {})
-                merged_zones = copy.deepcopy(base_zones)
-                merged_zones.update(profile.zones)
-                cam_config.zones = merged_zones
-                changed.setdefault(cam_name, set()).add("zones")
-
             base = self._base_configs.get(cam_name, {})
 
             for section in PROFILE_SECTION_UPDATES:
@@ -193,15 +175,6 @@ class ProfileManager:
                     )
                     continue
 
-                if section == "zones":
-                    self.config_updater.publish_update(
-                        CameraConfigUpdateTopic(
-                            CameraConfigUpdateEnum.zones, cam_name
-                        ),
-                        cam_config.zones,
-                    )
-                    continue
-
                 update_enum = PROFILE_SECTION_UPDATES.get(section)
                 if update_enum is None:
                     continue

frigate/data_processing/common/license_plate/mixin.py

@@ -401,10 +401,35 @@ class LicensePlateProcessingMixin:
             all_confidences.append(flat_confidences)
             all_areas.append(combined_area)
 
-        # Step 3: Sort the combined plates
+        # Step 3: Filter and sort the combined plates
         if all_license_plates:
+            filtered_data = []
+            for plate, conf_list, area in zip(
+                all_license_plates, all_confidences, all_areas
+            ):
+                if len(plate) < self.lpr_config.min_plate_length:
+                    logger.debug(
+                        f"{camera}: Filtered out '{plate}' due to length ({len(plate)} < {self.lpr_config.min_plate_length})"
+                    )
+                    continue
+
+                if self.lpr_config.format:
+                    try:
+                        if not re.fullmatch(self.lpr_config.format, plate):
+                            logger.debug(
+                                f"{camera}: Filtered out '{plate}' due to format mismatch"
+                            )
+                            continue
+                    except re.error:
+                        # Skip format filtering if regex is invalid
+                        logger.error(
+                            f"{camera}: Invalid regex in LPR format configuration: {self.lpr_config.format}"
+                        )
+
+                filtered_data.append((plate, conf_list, area))
+
             sorted_data = sorted(
-                zip(all_license_plates, all_confidences, all_areas),
+                filtered_data,
                 key=lambda x: (x[2], len(x[0]), sum(x[1]) / len(x[1]) if x[1] else 0),
                 reverse=True,
             )
@@ -1225,8 +1250,6 @@ class LicensePlateProcessingMixin:
                 logger.debug(f"{camera}: License plate area below minimum threshold.")
                 return
 
-            plate_box = license_plate
-
             license_plate_frame = rgb[
                 license_plate[1] : license_plate[3],
                 license_plate[0] : license_plate[2],
@@ -1343,20 +1366,6 @@ class LicensePlateProcessingMixin:
                     logger.debug(f"{camera}: License plate is less than min_area")
                     return
 
-                # Scale back to original car coordinates and then to frame
-                plate_box_in_car = (
-                    license_plate[0] // 2,
-                    license_plate[1] // 2,
-                    license_plate[2] // 2,
-                    license_plate[3] // 2,
-                )
-                plate_box = (
-                    left + plate_box_in_car[0],
-                    top + plate_box_in_car[1],
-                    left + plate_box_in_car[2],
-                    top + plate_box_in_car[3],
-                )
-
                 license_plate_frame = car[
                     license_plate[1] : license_plate[3],
                     license_plate[0] : license_plate[2],
@@ -1420,8 +1429,6 @@ class LicensePlateProcessingMixin:
                     0, [license_plate_frame.shape[1], license_plate_frame.shape[0]] * 2
                 )
 
-                plate_box = tuple(int(x) for x in expanded_box)
-
                 # Crop using the expanded box
                 license_plate_frame = license_plate_frame[
                     int(expanded_box[1]) : int(expanded_box[3]),
@@ -1550,27 +1557,6 @@ class LicensePlateProcessingMixin:
                 f"{camera}: Clustering changed top plate '{top_plate}' (conf: {avg_confidence:.3f}) to rep '{rep_plate}' (conf: {rep_conf:.3f})"
             )
 
-        # Apply length and format filters to the clustered representative
-        # rather than individual OCR readings, so noisy variants still
-        # contribute to clustering even when they don't pass on their own.
-        if len(rep_plate) < self.lpr_config.min_plate_length:
-            logger.debug(
-                f"{camera}: Filtered out clustered plate '{rep_plate}' due to length ({len(rep_plate)} < {self.lpr_config.min_plate_length})"
-            )
-            return
-
-        if self.lpr_config.format:
-            try:
-                if not re.fullmatch(self.lpr_config.format, rep_plate):
-                    logger.debug(
-                        f"{camera}: Filtered out clustered plate '{rep_plate}' due to format mismatch"
-                    )
-                    return
-            except re.error:
-                logger.error(
-                    f"{camera}: Invalid regex in LPR format configuration: {self.lpr_config.format}"
-                )
-
         # Update stored rep
         self.detected_license_plates[id].update(
             {
@@ -1629,7 +1615,6 @@ class LicensePlateProcessingMixin:
                     "id": id,
                     "camera": camera,
                     "timestamp": start,
-                    "plate_box": plate_box,
                 }
             ),
         )

frigate/data_processing/post/api.py

@@ -50,16 +50,3 @@ class PostProcessorApi(ABC):
             None if request was not handled, otherwise return response.
         """
         pass
-
-    def update_config(self, topic: str, payload: Any) -> None:
-        """Handle a config change notification.
-
-        Called for every config update published under ``config/``.
-        Processors should override this to check the topic and act only
-        on changes relevant to them. Default is a no-op.
-
-        Args:
-            topic: The config topic that changed.
-            payload: The updated configuration object.
-        """
-        pass

frigate/data_processing/post/license_plate.py

@@ -47,16 +47,6 @@ class LicensePlatePostProcessor(LicensePlateProcessingMixin, PostProcessorApi):
         self.sub_label_publisher = sub_label_publisher
         super().__init__(config, metrics, model_runner)
 
-    CONFIG_UPDATE_TOPIC = "config/lpr"
-
-    def update_config(self, topic: str, payload: Any) -> None:
-        """Update LPR config at runtime."""
-        if topic != self.CONFIG_UPDATE_TOPIC:
-            return
-
-        self.lpr_config = payload
-        logger.debug("LPR post-processor config updated dynamically")
-
     def process_data(
         self, data: dict[str, Any], data_type: PostProcessDataEnum
     ) -> None:

frigate/data_processing/real_time/api.py

@@ -61,16 +61,3 @@ class RealTimeProcessorApi(ABC):
             None.
         """
         pass
-
-    def update_config(self, topic: str, payload: Any) -> None:
-        """Handle a config change notification.
-
-        Called for every config update published under ``config/``.
-        Processors should override this to check the topic and act only
-        on changes relevant to them. Default is a no-op.
-
-        Args:
-            topic: The config topic that changed.
-            payload: The updated configuration object.
-        """
-        pass

frigate/data_processing/real_time/bird.py

@@ -169,16 +169,6 @@ class BirdRealTimeProcessor(RealTimeProcessorApi):
         )
         self.detected_birds[obj_data["id"]] = score
 
-    CONFIG_UPDATE_TOPIC = "config/classification"
-
-    def update_config(self, topic: str, payload: Any) -> None:
-        """Update bird classification config at runtime."""
-        if topic != self.CONFIG_UPDATE_TOPIC:
-            return
-
-        self.config.classification = payload
-        logger.debug("Bird classification config updated dynamically")
-
     def handle_request(self, topic, request_data):
         return None
 

frigate/data_processing/real_time/face.py

@@ -95,23 +95,6 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
         self.recognizer.build()
 
-    CONFIG_UPDATE_TOPIC = "config/face_recognition"
-
-    def update_config(self, topic: str, payload: Any) -> None:
-        """Update face recognition config at runtime."""
-        if topic != self.CONFIG_UPDATE_TOPIC:
-            return
-
-        previous_min_area = self.config.face_recognition.min_area
-        self.config.face_recognition = payload
-        self.face_config = payload
-
-        for camera_config in self.config.cameras.values():
-            if camera_config.face_recognition.min_area == previous_min_area:
-                camera_config.face_recognition.min_area = payload.min_area
-
-        logger.debug("Face recognition config updated dynamically")
-
     def __download_models(self, path: str) -> None:
         try:
             file_name = os.path.basename(path)

frigate/data_processing/real_time/license_plate.py

@@ -40,23 +40,6 @@ class LicensePlateRealTimeProcessor(LicensePlateProcessingMixin, RealTimeProcess
         self.camera_current_cars: dict[str, list[str]] = {}
         super().__init__(config, metrics)
 
-    CONFIG_UPDATE_TOPIC = "config/lpr"
-
-    def update_config(self, topic: str, payload: Any) -> None:
-        """Update LPR config at runtime."""
-        if topic != self.CONFIG_UPDATE_TOPIC:
-            return
-
-        previous_min_area = self.config.lpr.min_area
-        self.config.lpr = payload
-        self.lpr_config = payload
-
-        for camera_config in self.config.cameras.values():
-            if camera_config.lpr.min_area == previous_min_area:
-                camera_config.lpr.min_area = payload.min_area
-
-        logger.debug("LPR config updated dynamically")
-
     def process_frame(
         self,
         obj_data: dict[str, Any],

frigate/debug_replay.py

@@ -21,8 +21,7 @@ from frigate.const import (
     REPLAY_DIR,
     THUMB_DIR,
 )
-from frigate.models import Recordings
-from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
+from frigate.models import Event, Recordings, ReviewSegment, Timeline
 from frigate.util.config import find_config_file
 
 logger = logging.getLogger(__name__)
@@ -358,13 +357,43 @@ class DebugReplayManager:
 
     def _cleanup_db(self, camera_name: str) -> None:
         """Defensively remove any database rows for the replay camera."""
-        cleanup_camera_db(camera_name)
+        try:
+            Event.delete().where(Event.camera == camera_name).execute()
+        except Exception as e:
+            logger.error("Failed to delete replay events: %s", e)
+
+        try:
+            Timeline.delete().where(Timeline.camera == camera_name).execute()
+        except Exception as e:
+            logger.error("Failed to delete replay timeline: %s", e)
+
+        try:
+            Recordings.delete().where(Recordings.camera == camera_name).execute()
+        except Exception as e:
+            logger.error("Failed to delete replay recordings: %s", e)
+
+        try:
+            ReviewSegment.delete().where(ReviewSegment.camera == camera_name).execute()
+        except Exception as e:
+            logger.error("Failed to delete replay review segments: %s", e)
 
     def _cleanup_files(self, camera_name: str) -> None:
         """Remove filesystem artifacts for the replay camera."""
-        cleanup_camera_files(camera_name)
+        dirs_to_clean = [
+            os.path.join(RECORD_DIR, camera_name),
+            os.path.join(CLIPS_DIR, camera_name),
+            os.path.join(THUMB_DIR, camera_name),
+        ]
 
-        # Remove replay-specific cache directory
+        for dir_path in dirs_to_clean:
+            if os.path.exists(dir_path):
+                try:
+                    shutil.rmtree(dir_path)
+                    logger.debug("Removed replay directory: %s", dir_path)
+                except Exception as e:
+                    logger.error("Failed to remove %s: %s", dir_path, e)
+
+        # Remove replay clip and any related files
         if os.path.exists(REPLAY_DIR):
             try:
                 shutil.rmtree(REPLAY_DIR)

frigate/embeddings/embeddings.py

@@ -28,7 +28,6 @@ from frigate.types import ModelStatusTypesEnum
 from frigate.util.builtin import EventsPerSecond, InferenceSpeed, serialize
 from frigate.util.file import get_event_thumbnail_bytes
 
-from .genai_embedding import GenAIEmbedding
 from .onnx.jina_v1_embedding import JinaV1ImageEmbedding, JinaV1TextEmbedding
 from .onnx.jina_v2_embedding import JinaV2Embedding
 
@@ -74,7 +73,6 @@ class Embeddings:
         config: FrigateConfig,
         db: SqliteVecQueueDatabase,
         metrics: DataProcessorMetrics,
-        genai_manager=None,
     ) -> None:
         self.config = config
         self.db = db
@@ -106,27 +104,7 @@ class Embeddings:
                 },
             )
 
-        model_cfg = self.config.semantic_search.model
-
-        if not isinstance(model_cfg, SemanticSearchModelEnum):
-            # GenAI provider
-            embeddings_client = (
-                genai_manager.embeddings_client if genai_manager else None
-            )
-            if not embeddings_client:
-                raise ValueError(
-                    f"semantic_search.model is '{model_cfg}' (GenAI provider) but "
-                    "no embeddings client is configured. Ensure the GenAI provider "
-                    "has 'embeddings' in its roles."
-                )
-            self.embedding = GenAIEmbedding(embeddings_client)
-            self.text_embedding = lambda input_data: self.embedding(
-                input_data, embedding_type="text"
-            )
-            self.vision_embedding = lambda input_data: self.embedding(
-                input_data, embedding_type="vision"
-            )
-        elif model_cfg == SemanticSearchModelEnum.jinav2:
+        if self.config.semantic_search.model == SemanticSearchModelEnum.jinav2:
             # Single JinaV2Embedding instance for both text and vision
             self.embedding = JinaV2Embedding(
                 model_size=self.config.semantic_search.model_size,
@@ -140,8 +118,7 @@ class Embeddings:
             self.vision_embedding = lambda input_data: self.embedding(
                 input_data, embedding_type="vision"
             )
-        else:
-            # Default to jinav1
+        else:  # Default to jinav1
             self.text_embedding = JinaV1TextEmbedding(
                 model_size=config.semantic_search.model_size,
                 requestor=self.requestor,
@@ -159,11 +136,8 @@ class Embeddings:
         self.metrics.text_embeddings_eps.value = self.text_eps.eps()
 
     def get_model_definitions(self):
-        model_cfg = self.config.semantic_search.model
-        if not isinstance(model_cfg, SemanticSearchModelEnum):
-            # GenAI provider: no ONNX models to download
-            models = []
-        elif model_cfg == SemanticSearchModelEnum.jinav2:
+        # Version-specific models
+        if self.config.semantic_search.model == SemanticSearchModelEnum.jinav2:
             models = [
                 "jinaai/jina-clip-v2-tokenizer",
                 "jinaai/jina-clip-v2-model_fp16.onnx"
@@ -338,12 +312,11 @@ class Embeddings:
         # Get total count of events to process
         total_events = Event.select().count()
 
-        if not isinstance(self.config.semantic_search.model, SemanticSearchModelEnum):
-            batch_size = 1
-        elif self.config.semantic_search.model == SemanticSearchModelEnum.jinav2:
-            batch_size = 4
-        else:
-            batch_size = 32
+        batch_size = (
+            4
+            if self.config.semantic_search.model == SemanticSearchModelEnum.jinav2
+            else 32
+        )
         current_page = 1
 
         totals = {

frigate/embeddings/genai_embedding.py

@@ -1,89 +0,0 @@
-"""GenAI-backed embeddings for semantic search."""
-
-import io
-import logging
-from typing import TYPE_CHECKING
-
-import numpy as np
-from PIL import Image
-
-if TYPE_CHECKING:
-    from frigate.genai import GenAIClient
-
-logger = logging.getLogger(__name__)
-
-EMBEDDING_DIM = 768
-
-
-class GenAIEmbedding:
-    """Embedding adapter that delegates to a GenAI provider's embed API.
-
-    Provides the same interface as JinaV2Embedding for semantic search:
-    __call__(inputs, embedding_type) -> list[np.ndarray]. Output embeddings are
-    normalized to 768 dimensions for Frigate's sqlite-vec schema.
-    """
-
-    def __init__(self, client: "GenAIClient") -> None:
-        self.client = client
-
-    def __call__(
-        self,
-        inputs: list[str] | list[bytes] | list[Image.Image],
-        embedding_type: str = "text",
-    ) -> list[np.ndarray]:
-        """Generate embeddings for text or images.
-
-        Args:
-            inputs: List of strings (text) or bytes/PIL images (vision).
-            embedding_type: "text" or "vision".
-
-        Returns:
-            List of 768-dim numpy float32 arrays.
-        """
-        if not inputs:
-            return []
-
-        if embedding_type == "text":
-            texts = [str(x) for x in inputs]
-            embeddings = self.client.embed(texts=texts)
-        elif embedding_type == "vision":
-            images: list[bytes] = []
-            for inp in inputs:
-                if isinstance(inp, bytes):
-                    images.append(inp)
-                elif isinstance(inp, Image.Image):
-                    buf = io.BytesIO()
-                    inp.convert("RGB").save(buf, format="JPEG")
-                    images.append(buf.getvalue())
-                else:
-                    logger.warning(
-                        "GenAIEmbedding: skipping unsupported vision input type %s",
-                        type(inp).__name__,
-                    )
-            if not images:
-                return []
-            embeddings = self.client.embed(images=images)
-        else:
-            raise ValueError(
-                f"Invalid embedding_type '{embedding_type}'. Must be 'text' or 'vision'."
-            )
-
-        result = []
-        for emb in embeddings:
-            arr = np.asarray(emb, dtype=np.float32)
-            if arr.ndim > 1:
-                # Some providers return token-level embeddings; pool to one vector.
-                arr = arr.mean(axis=0)
-            arr = arr.flatten()
-            if arr.size != EMBEDDING_DIM:
-                if arr.size > EMBEDDING_DIM:
-                    arr = arr[:EMBEDDING_DIM]
-                else:
-                    arr = np.pad(
-                        arr,
-                        (0, EMBEDDING_DIM - arr.size),
-                        mode="constant",
-                        constant_values=0,
-                    )
-            result.append(arr)
-        return result

frigate/embeddings/maintainer.py

@@ -96,7 +96,9 @@ class EmbeddingMaintainer(threading.Thread):
                 CameraConfigUpdateEnum.semantic_search,
             ],
         )
-        self.enrichment_config_subscriber = ConfigSubscriber("config/")
+        self.classification_config_subscriber = ConfigSubscriber(
+            "config/classification/custom/"
+        )
 
         # Configure Frigate DB
         db = SqliteVecQueueDatabase(
@@ -114,10 +116,8 @@ class EmbeddingMaintainer(threading.Thread):
         models = [Event, Recordings, ReviewSegment, Trigger]
         db.bind(models)
 
-        self.genai_manager = GenAIClientManager(config)
-
         if config.semantic_search.enabled:
-            self.embeddings = Embeddings(config, db, metrics, self.genai_manager)
+            self.embeddings = Embeddings(config, db, metrics)
 
             # Check if we need to re-index events
             if config.semantic_search.reindex:
@@ -144,6 +144,7 @@ class EmbeddingMaintainer(threading.Thread):
         self.frame_manager = SharedMemoryFrameManager()
 
         self.detected_license_plates: dict[str, dict[str, Any]] = {}
+        self.genai_manager = GenAIClientManager(config)
 
         # model runners to share between realtime and post processors
         if self.config.lpr.enabled:
@@ -271,7 +272,7 @@ class EmbeddingMaintainer(threading.Thread):
         """Maintain a SQLite-vec database for semantic search."""
         while not self.stop_event.is_set():
             self.config_updater.check_for_updates()
-            self._check_enrichment_config_updates()
+            self._check_classification_config_updates()
             self._process_requests()
             self._process_updates()
             self._process_recordings_updates()
@@ -282,7 +283,7 @@ class EmbeddingMaintainer(threading.Thread):
             self._process_event_metadata()
 
         self.config_updater.stop()
-        self.enrichment_config_subscriber.stop()
+        self.classification_config_subscriber.stop()
         self.event_subscriber.stop()
         self.event_end_subscriber.stop()
         self.recordings_subscriber.stop()
@@ -293,86 +294,67 @@ class EmbeddingMaintainer(threading.Thread):
         self.requestor.stop()
         logger.info("Exiting embeddings maintenance...")
 
-    def _check_enrichment_config_updates(self) -> None:
-        """Check for enrichment config updates and delegate to processors."""
-        topic, payload = self.enrichment_config_subscriber.check_for_update()
+    def _check_classification_config_updates(self) -> None:
+        """Check for classification config updates and add/remove processors."""
+        topic, model_config = self.classification_config_subscriber.check_for_update()
 
-        if topic is None:
-            return
+        if topic:
+            model_name = topic.split("/")[-1]
 
-        # Custom classification add/remove requires managing the processor list
-        if topic.startswith("config/classification/custom/"):
-            self._handle_custom_classification_update(topic, payload)
-            return
+            if model_config is None:
+                self.realtime_processors = [
+                    processor
+                    for processor in self.realtime_processors
+                    if not (
+                        isinstance(
+                            processor,
+                            (
+                                CustomStateClassificationProcessor,
+                                CustomObjectClassificationProcessor,
+                            ),
+                        )
+                        and processor.model_config.name == model_name
+                    )
+                ]
 
-        # Broadcast to all processors — each decides if the topic is relevant
-        for processor in self.realtime_processors:
-            processor.update_config(topic, payload)
+                logger.info(
+                    f"Successfully removed classification processor for model: {model_name}"
+                )
+            else:
+                self.config.classification.custom[model_name] = model_config
 
-        for processor in self.post_processors:
-            processor.update_config(topic, payload)
-
-    def _handle_custom_classification_update(
-        self, topic: str, model_config: Any
-    ) -> None:
-        """Handle add/remove of custom classification processors."""
-        model_name = topic.split("/")[-1]
-
-        if model_config is None:
-            self.realtime_processors = [
-                processor
-                for processor in self.realtime_processors
-                if not (
-                    isinstance(
+                # Check if processor already exists
+                for processor in self.realtime_processors:
+                    if isinstance(
                         processor,
                         (
                             CustomStateClassificationProcessor,
                             CustomObjectClassificationProcessor,
                         ),
+                    ):
+                        if processor.model_config.name == model_name:
+                            logger.debug(
+                                f"Classification processor for model {model_name} already exists, skipping"
+                            )
+                            return
+
+                if model_config.state_config is not None:
+                    processor = CustomStateClassificationProcessor(
+                        self.config, model_config, self.requestor, self.metrics
                     )
-                    and processor.model_config.name == model_name
+                else:
+                    processor = CustomObjectClassificationProcessor(
+                        self.config,
+                        model_config,
+                        self.event_metadata_publisher,
+                        self.requestor,
+                        self.metrics,
+                    )
+
+                self.realtime_processors.append(processor)
+                logger.info(
+                    f"Added classification processor for model: {model_name} (type: {type(processor).__name__})"
                 )
-            ]
-
-            logger.info(
-                f"Successfully removed classification processor for model: {model_name}"
-            )
-            return
-
-        self.config.classification.custom[model_name] = model_config
-
-        # Check if processor already exists
-        for processor in self.realtime_processors:
-            if isinstance(
-                processor,
-                (
-                    CustomStateClassificationProcessor,
-                    CustomObjectClassificationProcessor,
-                ),
-            ):
-                if processor.model_config.name == model_name:
-                    logger.debug(
-                        f"Classification processor for model {model_name} already exists, skipping"
-                    )
-                    return
-
-        if model_config.state_config is not None:
-            processor = CustomStateClassificationProcessor(
-                self.config, model_config, self.requestor, self.metrics
-            )
-        else:
-            processor = CustomObjectClassificationProcessor(
-                self.config,
-                model_config,
-                self.event_metadata_publisher,
-                self.requestor,
-                self.metrics,
-            )
-
-        self.realtime_processors.append(processor)
-        logger.info(
-            f"Added classification processor for model: {model_name} (type: {type(processor).__name__})"
-        )
 
     def _process_requests(self) -> None:
         """Process embeddings requests"""

frigate/genai/__init__.py

@@ -7,7 +7,6 @@ import os
 import re
 from typing import Any, Optional
 
-import numpy as np
 from playhouse.shortcuts import model_to_dict
 
 from frigate.config import CameraConfig, GenAIConfig, GenAIProviderEnum
@@ -305,25 +304,6 @@ Guidelines:
         """Get the context window size for this provider in tokens."""
         return 4096
 
-    def embed(
-        self,
-        texts: list[str] | None = None,
-        images: list[bytes] | None = None,
-    ) -> list[np.ndarray]:
-        """Generate embeddings for text and/or images.
-
-        Returns list of numpy arrays (one per input). Expected dimension is 768
-        for Frigate semantic search compatibility.
-
-        Providers that support embeddings should override this method.
-        """
-        logger.warning(
-            "%s does not support embeddings. "
-            "This method should be overridden by the provider implementation.",
-            self.__class__.__name__,
-        )
-        return []
-
     def chat_with_tools(
         self,
         messages: list[dict[str, Any]],

frigate/genai/llama_cpp.py

@@ -1,15 +1,12 @@
 """llama.cpp Provider for Frigate AI."""
 
 import base64
-import io
 import json
 import logging
 from typing import Any, Optional
 
 import httpx
-import numpy as np
 import requests
-from PIL import Image
 
 from frigate.config import GenAIProviderEnum
 from frigate.genai import GenAIClient, register_genai_provider
@@ -18,20 +15,6 @@ from frigate.genai.utils import parse_tool_calls_from_message
 logger = logging.getLogger(__name__)
 
 
-def _to_jpeg(img_bytes: bytes) -> bytes | None:
-    """Convert image bytes to JPEG. llama.cpp/STB does not support WebP."""
-    try:
-        img = Image.open(io.BytesIO(img_bytes))
-        if img.mode != "RGB":
-            img = img.convert("RGB")
-        buf = io.BytesIO()
-        img.save(buf, format="JPEG", quality=85)
-        return buf.getvalue()
-    except Exception as e:
-        logger.warning("Failed to convert image to JPEG: %s", e)
-        return None
-
-
 @register_genai_provider(GenAIProviderEnum.llamacpp)
 class LlamaCppClient(GenAIClient):
     """Generative AI client for Frigate using llama.cpp server."""
@@ -193,110 +176,6 @@ class LlamaCppClient(GenAIClient):
             )
         return result if result else None
 
-    def embed(
-        self,
-        texts: list[str] | None = None,
-        images: list[bytes] | None = None,
-    ) -> list[np.ndarray]:
-        """Generate embeddings via llama.cpp /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.
-        """
-        if self.provider is None:
-            logger.warning(
-                "llama.cpp provider has not been initialized. Check your llama.cpp configuration."
-            )
-            return []
-
-        texts = texts or []
-        images = images or []
-        if not texts and not images:
-            return []
-
-        EMBEDDING_DIM = 768
-
-        content = []
-        for text in texts:
-            content.append({"prompt_string": text})
-        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 = base64.b64encode(to_encode).decode("utf-8")
-            # prompt_string must contain <__media__> placeholder for image tokenization
-            content.append(
-                {
-                    "prompt_string": "<__media__>\n",
-                    "multimodal_data": [encoded],
-                }
-            )
-
-        try:
-            response = requests.post(
-                f"{self.provider}/embeddings",
-                json={"model": self.genai_config.model, "content": content},
-                timeout=self.timeout,
-            )
-            response.raise_for_status()
-            result = response.json()
-
-            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 []
-
-            embeddings = []
-            for item in items:
-                emb = item.get("embedding") if isinstance(item, dict) else None
-                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()
-                orig_dim = arr.size
-                if orig_dim != EMBEDDING_DIM:
-                    if orig_dim > EMBEDDING_DIM:
-                        arr = arr[:EMBEDDING_DIM]
-                        logger.debug(
-                            "Truncated llama.cpp embedding from %d to %d dimensions",
-                            orig_dim,
-                            EMBEDDING_DIM,
-                        )
-                    else:
-                        arr = np.pad(
-                            arr,
-                            (0, EMBEDDING_DIM - orig_dim),
-                            mode="constant",
-                            constant_values=0,
-                        )
-                        logger.debug(
-                            "Padded llama.cpp embedding from %d to %d dimensions",
-                            orig_dim,
-                            EMBEDDING_DIM,
-                        )
-                embeddings.append(arr)
-            return embeddings
-        except requests.exceptions.Timeout:
-            logger.warning("llama.cpp embeddings request timed out")
-            return []
-        except requests.exceptions.RequestException as e:
-            error_detail = str(e)
-            if hasattr(e, "response") and e.response is not None:
-                try:
-                    error_detail = f"{str(e)} - Response: {e.response.text[:500]}"
-                except Exception:
-                    pass
-            logger.warning("llama.cpp embeddings error: %s", error_detail)
-            return []
-        except Exception as e:
-            logger.warning("Unexpected error in llama.cpp embeddings: %s", str(e))
-            return []
-
     def chat_with_tools(
         self,
         messages: list[dict[str, Any]],

frigate/genai/ollama.py

@@ -1,6 +1,5 @@
 """Ollama Provider for Frigate AI."""
 
-import json
 import logging
 from typing import Any, Optional
 
@@ -109,22 +108,7 @@ class OllamaClient(GenAIClient):
             if msg.get("name"):
                 msg_dict["name"] = msg["name"]
             if msg.get("tool_calls"):
-                # Ollama requires tool call arguments as dicts, but the
-                # conversation format (OpenAI-style) stores them as JSON
-                # strings. Convert back to dicts for Ollama.
-                ollama_tool_calls = []
-                for tc in msg["tool_calls"]:
-                    func = tc.get("function") or {}
-                    args = func.get("arguments") or {}
-                    if isinstance(args, str):
-                        try:
-                            args = json.loads(args)
-                        except (json.JSONDecodeError, TypeError):
-                            args = {}
-                    ollama_tool_calls.append(
-                        {"function": {"name": func.get("name", ""), "arguments": args}}
-                    )
-                msg_dict["tool_calls"] = ollama_tool_calls
+                msg_dict["tool_calls"] = msg["tool_calls"]
             request_messages.append(msg_dict)
 
         request_params: dict[str, Any] = {
@@ -136,27 +120,25 @@ class OllamaClient(GenAIClient):
             request_params["stream"] = True
         if tools:
             request_params["tools"] = tools
+            if tool_choice:
+                request_params["tool_choice"] = (
+                    "none"
+                    if tool_choice == "none"
+                    else "required"
+                    if tool_choice == "required"
+                    else "auto"
+                )
         return request_params
 
     def _message_from_response(self, response: dict[str, Any]) -> dict[str, Any]:
         """Parse Ollama chat response into {content, tool_calls, finish_reason}."""
         if not response or "message" not in response:
-            logger.debug("Ollama response empty or missing 'message' key")
             return {
                 "content": None,
                 "tool_calls": None,
                 "finish_reason": "error",
             }
         message = response["message"]
-        logger.debug(
-            "Ollama response message keys: %s, content_len=%s, thinking_len=%s, "
-            "tool_calls=%s, done=%s",
-            list(message.keys()) if hasattr(message, "keys") else "N/A",
-            len(message.get("content", "") or "") if message.get("content") else 0,
-            len(message.get("thinking", "") or "") if message.get("thinking") else 0,
-            bool(message.get("tool_calls")),
-            response.get("done"),
-        )
         content = message.get("content", "").strip() if message.get("content") else None
         tool_calls = parse_tool_calls_from_message(message)
         finish_reason = "error"
@@ -216,13 +198,7 @@ class OllamaClient(GenAIClient):
         tools: Optional[list[dict[str, Any]]] = None,
         tool_choice: Optional[str] = "auto",
     ):
-        """Stream chat with tools; yields content deltas then final message.
-
-        When tools are provided, Ollama streaming does not include tool_calls
-        in the response chunks. To work around this, we use a non-streaming
-        call when tools are present to ensure tool calls are captured, then
-        emit the content as a single delta followed by the final message.
-        """
+        """Stream chat with tools; yields content deltas then final message."""
         if self.provider is None:
             logger.warning(
                 "Ollama provider has not been initialized. Check your Ollama configuration."
@@ -237,27 +213,6 @@ class OllamaClient(GenAIClient):
             )
             return
         try:
-            # Ollama does not return tool_calls in streaming mode, so fall
-            # back to a non-streaming call when tools are provided.
-            if tools:
-                logger.debug(
-                    "Ollama: tools provided, using non-streaming call for tool support"
-                )
-                request_params = self._build_request_params(
-                    messages, tools, tool_choice, stream=False
-                )
-                async_client = OllamaAsyncClient(
-                    host=self.genai_config.base_url,
-                    timeout=self.timeout,
-                )
-                response = await async_client.chat(**request_params)
-                result = self._message_from_response(response)
-                content = result.get("content")
-                if content:
-                    yield ("content_delta", content)
-                yield ("message", result)
-                return
-
             request_params = self._build_request_params(
                 messages, tools, tool_choice, stream=True
             )
@@ -278,10 +233,11 @@ class OllamaClient(GenAIClient):
                     yield ("content_delta", delta)
                 if chunk.get("done"):
                     full_content = "".join(content_parts).strip() or None
+                    tool_calls = parse_tool_calls_from_message(msg)
                     final_message = {
                         "content": full_content,
-                        "tool_calls": None,
-                        "finish_reason": "stop",
+                        "tool_calls": tool_calls,
+                        "finish_reason": "tool_calls" if tool_calls else "stop",
                     }
                     break
 

frigate/genai/utils.py

@@ -23,26 +23,21 @@ def parse_tool_calls_from_message(
     if not raw or not isinstance(raw, list):
         return None
     result = []
-    for idx, tool_call in enumerate(raw):
+    for tool_call in raw:
         function_data = tool_call.get("function") or {}
-        raw_arguments = function_data.get("arguments") or {}
-        if isinstance(raw_arguments, dict):
-            arguments = raw_arguments
-        elif isinstance(raw_arguments, str):
-            try:
-                arguments = json.loads(raw_arguments)
-            except (json.JSONDecodeError, KeyError, TypeError) as e:
-                logger.warning(
-                    "Failed to parse tool call arguments: %s, tool: %s",
-                    e,
-                    function_data.get("name", "unknown"),
-                )
-                arguments = {}
-        else:
+        try:
+            arguments_str = function_data.get("arguments") or "{}"
+            arguments = json.loads(arguments_str)
+        except (json.JSONDecodeError, KeyError, TypeError) as e:
+            logger.warning(
+                "Failed to parse tool call arguments: %s, tool: %s",
+                e,
+                function_data.get("name", "unknown"),
+            )
             arguments = {}
         result.append(
             {
-                "id": tool_call.get("id", "") or f"call_{idx}",
+                "id": tool_call.get("id", ""),
                 "name": function_data.get("name", ""),
                 "arguments": arguments,
             }

frigate/jobs/motion_search.py

@@ -1,864 +0,0 @@
-"""Motion search job management with background execution and parallel verification."""
-
-import logging
-import os
-import threading
-from concurrent.futures import Future, ThreadPoolExecutor, as_completed
-from dataclasses import asdict, dataclass, field
-from datetime import datetime
-from typing import Any, Optional
-
-import cv2
-import numpy as np
-
-from frigate.comms.inter_process import InterProcessRequestor
-from frigate.config import FrigateConfig
-from frigate.const import UPDATE_JOB_STATE
-from frigate.jobs.job import Job
-from frigate.jobs.manager import (
-    get_job_by_id,
-    set_current_job,
-)
-from frigate.models import Recordings
-from frigate.types import JobStatusTypesEnum
-
-logger = logging.getLogger(__name__)
-
-# Constants
-HEATMAP_GRID_SIZE = 16
-
-
-@dataclass
-class MotionSearchMetrics:
-    """Metrics collected during motion search execution."""
-
-    segments_scanned: int = 0
-    segments_processed: int = 0
-    metadata_inactive_segments: int = 0
-    heatmap_roi_skip_segments: int = 0
-    fallback_full_range_segments: int = 0
-    frames_decoded: int = 0
-    wall_time_seconds: float = 0.0
-    segments_with_errors: int = 0
-
-    def to_dict(self) -> dict[str, Any]:
-        """Convert to dictionary."""
-        return asdict(self)
-
-
-@dataclass
-class MotionSearchResult:
-    """A single search result with timestamp and change info."""
-
-    timestamp: float
-    change_percentage: float
-
-    def to_dict(self) -> dict[str, Any]:
-        """Convert to dictionary."""
-        return asdict(self)
-
-
-@dataclass
-class MotionSearchJob(Job):
-    """Job state for motion search operations."""
-
-    job_type: str = "motion_search"
-    camera: str = ""
-    start_time_range: float = 0.0
-    end_time_range: float = 0.0
-    polygon_points: list[list[float]] = field(default_factory=list)
-    threshold: int = 30
-    min_area: float = 5.0
-    frame_skip: int = 5
-    parallel: bool = False
-    max_results: int = 25
-
-    # Track progress
-    total_frames_processed: int = 0
-
-    # Metrics for observability
-    metrics: Optional[MotionSearchMetrics] = None
-
-    def to_dict(self) -> dict[str, Any]:
-        """Convert to dictionary for WebSocket transmission."""
-        d = asdict(self)
-        if self.metrics:
-            d["metrics"] = self.metrics.to_dict()
-        return d
-
-
-def create_polygon_mask(
-    polygon_points: list[list[float]], frame_width: int, frame_height: int
-) -> np.ndarray:
-    """Create a binary mask from normalized polygon coordinates."""
-    motion_points = np.array(
-        [[int(p[0] * frame_width), int(p[1] * frame_height)] for p in polygon_points],
-        dtype=np.int32,
-    )
-    mask = np.zeros((frame_height, frame_width), dtype=np.uint8)
-    cv2.fillPoly(mask, [motion_points], 255)
-    return mask
-
-
-def compute_roi_bbox_normalized(
-    polygon_points: list[list[float]],
-) -> tuple[float, float, float, float]:
-    """Compute the bounding box of the ROI in normalized coordinates (0-1).
-
-    Returns (x_min, y_min, x_max, y_max) in normalized coordinates.
-    """
-    if not polygon_points:
-        return (0.0, 0.0, 1.0, 1.0)
-
-    x_coords = [p[0] for p in polygon_points]
-    y_coords = [p[1] for p in polygon_points]
-    return (min(x_coords), min(y_coords), max(x_coords), max(y_coords))
-
-
-def heatmap_overlaps_roi(
-    heatmap: dict[str, int], roi_bbox: tuple[float, float, float, float]
-) -> bool:
-    """Check if a sparse motion heatmap has any overlap with the ROI bounding box.
-
-    Args:
-        heatmap: Sparse dict mapping cell index (str) to intensity (1-255).
-        roi_bbox: (x_min, y_min, x_max, y_max) in normalized coordinates (0-1).
-
-    Returns:
-        True if there is overlap (any active cell in the ROI region).
-    """
-    if not isinstance(heatmap, dict):
-        # Invalid heatmap, assume overlap to be safe
-        return True
-
-    x_min, y_min, x_max, y_max = roi_bbox
-
-    # Convert normalized coordinates to grid cells (0-15)
-    grid_x_min = max(0, int(x_min * HEATMAP_GRID_SIZE))
-    grid_y_min = max(0, int(y_min * HEATMAP_GRID_SIZE))
-    grid_x_max = min(HEATMAP_GRID_SIZE - 1, int(x_max * HEATMAP_GRID_SIZE))
-    grid_y_max = min(HEATMAP_GRID_SIZE - 1, int(y_max * HEATMAP_GRID_SIZE))
-
-    # Check each cell in the ROI bbox
-    for y in range(grid_y_min, grid_y_max + 1):
-        for x in range(grid_x_min, grid_x_max + 1):
-            idx = str(y * HEATMAP_GRID_SIZE + x)
-            if idx in heatmap:
-                return True
-
-    return False
-
-
-def segment_passes_activity_gate(recording: Recordings) -> bool:
-    """Check if a segment passes the activity gate.
-
-    Returns True if any of motion, objects, or regions is non-zero/non-null.
-    Returns True if all are null (old segments without data).
-    """
-    motion = recording.motion
-    objects = recording.objects
-    regions = recording.regions
-
-    # Old segments without metadata - pass through (conservative)
-    if motion is None and objects is None and regions is None:
-        return True
-
-    # Pass if any activity indicator is positive
-    return bool(motion) or bool(objects) or bool(regions)
-
-
-def segment_passes_heatmap_gate(
-    recording: Recordings, roi_bbox: tuple[float, float, float, float]
-) -> bool:
-    """Check if a segment passes the heatmap overlap gate.
-
-    Returns True if:
-    - No heatmap is stored (old segments).
-    - The heatmap overlaps with the ROI bbox.
-    """
-    heatmap = getattr(recording, "motion_heatmap", None)
-    if heatmap is None:
-        # No heatmap stored, fall back to activity gate
-        return True
-
-    return heatmap_overlaps_roi(heatmap, roi_bbox)
-
-
-class MotionSearchRunner(threading.Thread):
-    """Thread-based runner for motion search jobs with parallel verification."""
-
-    def __init__(
-        self,
-        job: MotionSearchJob,
-        config: FrigateConfig,
-        cancel_event: threading.Event,
-    ) -> None:
-        super().__init__(daemon=True, name=f"motion_search_{job.id}")
-        self.job = job
-        self.config = config
-        self.cancel_event = cancel_event
-        self.internal_stop_event = threading.Event()
-        self.requestor = InterProcessRequestor()
-        self.metrics = MotionSearchMetrics()
-        self.job.metrics = self.metrics
-
-        # Worker cap: min(4, cpu_count)
-        cpu_count = os.cpu_count() or 1
-        self.max_workers = min(4, cpu_count)
-
-    def run(self) -> None:
-        """Execute the motion search job."""
-        try:
-            self.job.status = JobStatusTypesEnum.running
-            self.job.start_time = datetime.now().timestamp()
-            self._broadcast_status()
-
-            results = self._execute_search()
-
-            if self.cancel_event.is_set():
-                self.job.status = JobStatusTypesEnum.cancelled
-            else:
-                self.job.status = JobStatusTypesEnum.success
-                self.job.results = {
-                    "results": [r.to_dict() for r in results],
-                    "total_frames_processed": self.job.total_frames_processed,
-                }
-
-            self.job.end_time = datetime.now().timestamp()
-            self.metrics.wall_time_seconds = self.job.end_time - self.job.start_time
-            self.job.metrics = self.metrics
-
-            logger.debug(
-                "Motion search job %s completed: status=%s, results=%d, frames=%d",
-                self.job.id,
-                self.job.status,
-                len(results),
-                self.job.total_frames_processed,
-            )
-            self._broadcast_status()
-
-        except Exception as e:
-            logger.exception("Motion search job %s failed: %s", self.job.id, e)
-            self.job.status = JobStatusTypesEnum.failed
-            self.job.error_message = str(e)
-            self.job.end_time = datetime.now().timestamp()
-            self.metrics.wall_time_seconds = self.job.end_time - (
-                self.job.start_time or 0
-            )
-            self.job.metrics = self.metrics
-            self._broadcast_status()
-
-        finally:
-            if self.requestor:
-                self.requestor.stop()
-
-    def _broadcast_status(self) -> None:
-        """Broadcast job status update via IPC to WebSocket subscribers."""
-        if self.job.status == JobStatusTypesEnum.running and self.job.start_time:
-            self.metrics.wall_time_seconds = (
-                datetime.now().timestamp() - self.job.start_time
-            )
-
-        try:
-            self.requestor.send_data(UPDATE_JOB_STATE, self.job.to_dict())
-        except Exception as e:
-            logger.warning("Failed to broadcast motion search status: %s", e)
-
-    def _should_stop(self) -> bool:
-        """Check if processing should stop due to cancellation or internal limits."""
-        return self.cancel_event.is_set() or self.internal_stop_event.is_set()
-
-    def _execute_search(self) -> list[MotionSearchResult]:
-        """Main search execution logic."""
-        camera_name = self.job.camera
-        camera_config = self.config.cameras.get(camera_name)
-        if not camera_config:
-            raise ValueError(f"Camera {camera_name} not found")
-
-        frame_width = camera_config.detect.width
-        frame_height = camera_config.detect.height
-
-        # Create polygon mask
-        polygon_mask = create_polygon_mask(
-            self.job.polygon_points, frame_width, frame_height
-        )
-
-        if np.count_nonzero(polygon_mask) == 0:
-            logger.warning("Polygon mask is empty for job %s", self.job.id)
-            return []
-
-        # Compute ROI bbox in normalized coordinates for heatmap gate
-        roi_bbox = compute_roi_bbox_normalized(self.job.polygon_points)
-
-        # Query recordings
-        recordings = list(
-            Recordings.select()
-            .where(
-                (
-                    Recordings.start_time.between(
-                        self.job.start_time_range, self.job.end_time_range
-                    )
-                )
-                | (
-                    Recordings.end_time.between(
-                        self.job.start_time_range, self.job.end_time_range
-                    )
-                )
-                | (
-                    (self.job.start_time_range > Recordings.start_time)
-                    & (self.job.end_time_range < Recordings.end_time)
-                )
-            )
-            .where(Recordings.camera == camera_name)
-            .order_by(Recordings.start_time.asc())
-        )
-
-        if not recordings:
-            logger.debug("No recordings found for motion search job %s", self.job.id)
-            return []
-
-        logger.debug(
-            "Motion search job %s: queried %d recording segments for camera %s "
-            "(range %.1f - %.1f)",
-            self.job.id,
-            len(recordings),
-            camera_name,
-            self.job.start_time_range,
-            self.job.end_time_range,
-        )
-
-        self.metrics.segments_scanned = len(recordings)
-
-        # Apply activity and heatmap gates
-        filtered_recordings = []
-        for recording in recordings:
-            if not segment_passes_activity_gate(recording):
-                self.metrics.metadata_inactive_segments += 1
-                self.metrics.segments_processed += 1
-                logger.debug(
-                    "Motion search job %s: segment %s skipped by activity gate "
-                    "(motion=%s, objects=%s, regions=%s)",
-                    self.job.id,
-                    recording.id,
-                    recording.motion,
-                    recording.objects,
-                    recording.regions,
-                )
-                continue
-            if not segment_passes_heatmap_gate(recording, roi_bbox):
-                self.metrics.heatmap_roi_skip_segments += 1
-                self.metrics.segments_processed += 1
-                logger.debug(
-                    "Motion search job %s: segment %s skipped by heatmap gate "
-                    "(heatmap present=%s, roi_bbox=%s)",
-                    self.job.id,
-                    recording.id,
-                    recording.motion_heatmap is not None,
-                    roi_bbox,
-                )
-                continue
-            filtered_recordings.append(recording)
-
-        self._broadcast_status()
-
-        # Fallback: if all segments were filtered out, scan all segments
-        # This allows motion search to find things the detector missed
-        if not filtered_recordings and recordings:
-            logger.info(
-                "All %d segments filtered by gates, falling back to full scan",
-                len(recordings),
-            )
-            self.metrics.fallback_full_range_segments = len(recordings)
-            filtered_recordings = recordings
-
-        logger.debug(
-            "Motion search job %s: %d/%d segments passed gates "
-            "(activity_skipped=%d, heatmap_skipped=%d)",
-            self.job.id,
-            len(filtered_recordings),
-            len(recordings),
-            self.metrics.metadata_inactive_segments,
-            self.metrics.heatmap_roi_skip_segments,
-        )
-
-        if self.job.parallel:
-            return self._search_motion_parallel(filtered_recordings, polygon_mask)
-
-        return self._search_motion_sequential(filtered_recordings, polygon_mask)
-
-    def _search_motion_parallel(
-        self,
-        recordings: list[Recordings],
-        polygon_mask: np.ndarray,
-    ) -> list[MotionSearchResult]:
-        """Search for motion in parallel across segments, streaming results."""
-        all_results: list[MotionSearchResult] = []
-        total_frames = 0
-        next_recording_idx_to_merge = 0
-
-        logger.debug(
-            "Motion search job %s: starting motion search with %d workers "
-            "across %d segments",
-            self.job.id,
-            self.max_workers,
-            len(recordings),
-        )
-
-        # Initialize partial results on the job so they stream to the frontend
-        self.job.results = {"results": [], "total_frames_processed": 0}
-
-        with ThreadPoolExecutor(max_workers=self.max_workers) as executor:
-            futures: dict[Future, int] = {}
-            completed_segments: dict[int, tuple[list[MotionSearchResult], int]] = {}
-
-            for idx, recording in enumerate(recordings):
-                if self._should_stop():
-                    break
-
-                future = executor.submit(
-                    self._process_recording_for_motion,
-                    recording.path,
-                    recording.start_time,
-                    recording.end_time,
-                    self.job.start_time_range,
-                    self.job.end_time_range,
-                    polygon_mask,
-                    self.job.threshold,
-                    self.job.min_area,
-                    self.job.frame_skip,
-                )
-                futures[future] = idx
-
-            for future in as_completed(futures):
-                if self._should_stop():
-                    # Cancel remaining futures
-                    for f in futures:
-                        f.cancel()
-                    break
-
-                recording_idx = futures[future]
-                recording = recordings[recording_idx]
-
-                try:
-                    results, frames = future.result()
-                    self.metrics.segments_processed += 1
-                    completed_segments[recording_idx] = (results, frames)
-
-                    while next_recording_idx_to_merge in completed_segments:
-                        segment_results, segment_frames = completed_segments.pop(
-                            next_recording_idx_to_merge
-                        )
-
-                        all_results.extend(segment_results)
-                        total_frames += segment_frames
-                        self.job.total_frames_processed = total_frames
-                        self.metrics.frames_decoded = total_frames
-
-                        if segment_results:
-                            deduped = self._deduplicate_results(all_results)
-                            self.job.results = {
-                                "results": [
-                                    r.to_dict() for r in deduped[: self.job.max_results]
-                                ],
-                                "total_frames_processed": total_frames,
-                            }
-
-                        self._broadcast_status()
-
-                        if segment_results and len(deduped) >= self.job.max_results:
-                            self.internal_stop_event.set()
-                            for pending_future in futures:
-                                pending_future.cancel()
-                            break
-
-                        next_recording_idx_to_merge += 1
-
-                    if self.internal_stop_event.is_set():
-                        break
-
-                except Exception as e:
-                    self.metrics.segments_processed += 1
-                    self.metrics.segments_with_errors += 1
-                    self._broadcast_status()
-                    logger.warning(
-                        "Error processing segment %s: %s",
-                        recording.path,
-                        e,
-                    )
-
-        self.job.total_frames_processed = total_frames
-        self.metrics.frames_decoded = total_frames
-
-        logger.debug(
-            "Motion search job %s: motion search complete, "
-            "found %d raw results, decoded %d frames, %d segment errors",
-            self.job.id,
-            len(all_results),
-            total_frames,
-            self.metrics.segments_with_errors,
-        )
-
-        # Sort and deduplicate results
-        all_results.sort(key=lambda x: x.timestamp)
-        return self._deduplicate_results(all_results)[: self.job.max_results]
-
-    def _search_motion_sequential(
-        self,
-        recordings: list[Recordings],
-        polygon_mask: np.ndarray,
-    ) -> list[MotionSearchResult]:
-        """Search for motion sequentially across segments, streaming results."""
-        all_results: list[MotionSearchResult] = []
-        total_frames = 0
-
-        logger.debug(
-            "Motion search job %s: starting sequential motion search across %d segments",
-            self.job.id,
-            len(recordings),
-        )
-
-        self.job.results = {"results": [], "total_frames_processed": 0}
-
-        for recording in recordings:
-            if self.cancel_event.is_set():
-                break
-
-            try:
-                results, frames = self._process_recording_for_motion(
-                    recording.path,
-                    recording.start_time,
-                    recording.end_time,
-                    self.job.start_time_range,
-                    self.job.end_time_range,
-                    polygon_mask,
-                    self.job.threshold,
-                    self.job.min_area,
-                    self.job.frame_skip,
-                )
-                all_results.extend(results)
-                total_frames += frames
-
-                self.job.total_frames_processed = total_frames
-                self.metrics.frames_decoded = total_frames
-                self.metrics.segments_processed += 1
-
-                if results:
-                    all_results.sort(key=lambda x: x.timestamp)
-                    deduped = self._deduplicate_results(all_results)[
-                        : self.job.max_results
-                    ]
-                    self.job.results = {
-                        "results": [r.to_dict() for r in deduped],
-                        "total_frames_processed": total_frames,
-                    }
-
-                self._broadcast_status()
-
-                if results and len(deduped) >= self.job.max_results:
-                    break
-
-            except Exception as e:
-                self.metrics.segments_processed += 1
-                self.metrics.segments_with_errors += 1
-                self._broadcast_status()
-                logger.warning("Error processing segment %s: %s", recording.path, e)
-
-        self.job.total_frames_processed = total_frames
-        self.metrics.frames_decoded = total_frames
-
-        logger.debug(
-            "Motion search job %s: sequential motion search complete, "
-            "found %d raw results, decoded %d frames, %d segment errors",
-            self.job.id,
-            len(all_results),
-            total_frames,
-            self.metrics.segments_with_errors,
-        )
-
-        all_results.sort(key=lambda x: x.timestamp)
-        return self._deduplicate_results(all_results)[: self.job.max_results]
-
-    def _deduplicate_results(
-        self, results: list[MotionSearchResult], min_gap: float = 1.0
-    ) -> list[MotionSearchResult]:
-        """Deduplicate results that are too close together."""
-        if not results:
-            return results
-
-        deduplicated: list[MotionSearchResult] = []
-        last_timestamp = 0.0
-
-        for result in results:
-            if result.timestamp - last_timestamp >= min_gap:
-                deduplicated.append(result)
-                last_timestamp = result.timestamp
-
-        return deduplicated
-
-    def _process_recording_for_motion(
-        self,
-        recording_path: str,
-        recording_start: float,
-        recording_end: float,
-        search_start: float,
-        search_end: float,
-        polygon_mask: np.ndarray,
-        threshold: int,
-        min_area: float,
-        frame_skip: int,
-    ) -> tuple[list[MotionSearchResult], int]:
-        """Process a single recording file for motion detection.
-
-        This method is designed to be called from a thread pool.
-
-        Args:
-            min_area: Minimum change area as a percentage of the ROI (0-100).
-        """
-        results: list[MotionSearchResult] = []
-        frames_processed = 0
-
-        if not os.path.exists(recording_path):
-            logger.warning("Recording file not found: %s", recording_path)
-            return results, frames_processed
-
-        cap = cv2.VideoCapture(recording_path)
-        if not cap.isOpened():
-            logger.error("Could not open recording: %s", recording_path)
-            return results, frames_processed
-
-        try:
-            fps = cap.get(cv2.CAP_PROP_FPS) or 30.0
-            total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-            recording_duration = recording_end - recording_start
-
-            # Calculate frame range
-            start_offset = max(0, search_start - recording_start)
-            end_offset = min(recording_duration, search_end - recording_start)
-            start_frame = int(start_offset * fps)
-            end_frame = int(end_offset * fps)
-            start_frame = max(0, min(start_frame, total_frames - 1))
-            end_frame = max(0, min(end_frame, total_frames))
-
-            if start_frame >= end_frame:
-                return results, frames_processed
-
-            cap.set(cv2.CAP_PROP_POS_FRAMES, start_frame)
-
-            # Get ROI bounding box
-            roi_bbox = cv2.boundingRect(polygon_mask)
-            roi_x, roi_y, roi_w, roi_h = roi_bbox
-
-            prev_frame_gray = None
-            frame_step = max(frame_skip, 1)
-            frame_idx = start_frame
-
-            while frame_idx < end_frame:
-                if self._should_stop():
-                    break
-
-                ret, frame = cap.read()
-                if not ret:
-                    frame_idx += 1
-                    continue
-
-                if (frame_idx - start_frame) % frame_step != 0:
-                    frame_idx += 1
-                    continue
-
-                frames_processed += 1
-
-                gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-
-                # Handle frame dimension changes
-                if gray.shape != polygon_mask.shape:
-                    resized_mask = cv2.resize(
-                        polygon_mask, (gray.shape[1], gray.shape[0]), cv2.INTER_NEAREST
-                    )
-                    current_bbox = cv2.boundingRect(resized_mask)
-                else:
-                    resized_mask = polygon_mask
-                    current_bbox = roi_bbox
-
-                roi_x, roi_y, roi_w, roi_h = current_bbox
-                cropped_gray = gray[roi_y : roi_y + roi_h, roi_x : roi_x + roi_w]
-                cropped_mask = resized_mask[
-                    roi_y : roi_y + roi_h, roi_x : roi_x + roi_w
-                ]
-
-                cropped_mask_area = np.count_nonzero(cropped_mask)
-                if cropped_mask_area == 0:
-                    frame_idx += 1
-                    continue
-
-                # Convert percentage to pixel count for this ROI
-                min_area_pixels = int((min_area / 100.0) * cropped_mask_area)
-
-                masked_gray = cv2.bitwise_and(
-                    cropped_gray, cropped_gray, mask=cropped_mask
-                )
-
-                if prev_frame_gray is not None:
-                    diff = cv2.absdiff(prev_frame_gray, masked_gray)
-                    diff_blurred = cv2.GaussianBlur(diff, (3, 3), 0)
-                    _, thresh = cv2.threshold(
-                        diff_blurred, threshold, 255, cv2.THRESH_BINARY
-                    )
-                    thresh_dilated = cv2.dilate(thresh, None, iterations=1)
-                    thresh_masked = cv2.bitwise_and(
-                        thresh_dilated, thresh_dilated, mask=cropped_mask
-                    )
-
-                    change_pixels = cv2.countNonZero(thresh_masked)
-                    if change_pixels > min_area_pixels:
-                        contours, _ = cv2.findContours(
-                            thresh_masked, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
-                        )
-                        total_change_area = sum(
-                            cv2.contourArea(c)
-                            for c in contours
-                            if cv2.contourArea(c) >= min_area_pixels
-                        )
-                        if total_change_area > 0:
-                            frame_time_offset = (frame_idx - start_frame) / fps
-                            timestamp = (
-                                recording_start + start_offset + frame_time_offset
-                            )
-                            change_percentage = (
-                                total_change_area / cropped_mask_area
-                            ) * 100
-                            results.append(
-                                MotionSearchResult(
-                                    timestamp=timestamp,
-                                    change_percentage=round(change_percentage, 2),
-                                )
-                            )
-
-                prev_frame_gray = masked_gray
-                frame_idx += 1
-
-        finally:
-            cap.release()
-
-        logger.debug(
-            "Motion search segment complete: %s, %d frames processed, %d results found",
-            recording_path,
-            frames_processed,
-            len(results),
-        )
-        return results, frames_processed
-
-
-# Module-level state for managing per-camera jobs
-_motion_search_jobs: dict[str, tuple[MotionSearchJob, threading.Event]] = {}
-_jobs_lock = threading.Lock()
-
-
-def stop_all_motion_search_jobs() -> None:
-    """Cancel all running motion search jobs for clean shutdown."""
-    with _jobs_lock:
-        for job_id, (job, cancel_event) in _motion_search_jobs.items():
-            if job.status in (JobStatusTypesEnum.queued, JobStatusTypesEnum.running):
-                cancel_event.set()
-                logger.debug("Signalling motion search job %s to stop", job_id)
-
-
-def start_motion_search_job(
-    config: FrigateConfig,
-    camera_name: str,
-    start_time: float,
-    end_time: float,
-    polygon_points: list[list[float]],
-    threshold: int = 30,
-    min_area: float = 5.0,
-    frame_skip: int = 5,
-    parallel: bool = False,
-    max_results: int = 25,
-) -> str:
-    """Start a new motion search job.
-
-    Returns the job ID.
-    """
-    job = MotionSearchJob(
-        camera=camera_name,
-        start_time_range=start_time,
-        end_time_range=end_time,
-        polygon_points=polygon_points,
-        threshold=threshold,
-        min_area=min_area,
-        frame_skip=frame_skip,
-        parallel=parallel,
-        max_results=max_results,
-    )
-
-    cancel_event = threading.Event()
-
-    with _jobs_lock:
-        _motion_search_jobs[job.id] = (job, cancel_event)
-
-    set_current_job(job)
-
-    runner = MotionSearchRunner(job, config, cancel_event)
-    runner.start()
-
-    logger.debug(
-        "Started motion search job %s for camera %s: "
-        "time_range=%.1f-%.1f, threshold=%d, min_area=%.1f%%, "
-        "frame_skip=%d, parallel=%s, max_results=%d, polygon_points=%d vertices",
-        job.id,
-        camera_name,
-        start_time,
-        end_time,
-        threshold,
-        min_area,
-        frame_skip,
-        parallel,
-        max_results,
-        len(polygon_points),
-    )
-    return job.id
-
-
-def get_motion_search_job(job_id: str) -> Optional[MotionSearchJob]:
-    """Get a motion search job by ID."""
-    with _jobs_lock:
-        job_entry = _motion_search_jobs.get(job_id)
-        if job_entry:
-            return job_entry[0]
-    # Check completed jobs via manager
-    return get_job_by_id("motion_search", job_id)
-
-
-def cancel_motion_search_job(job_id: str) -> bool:
-    """Cancel a motion search job.
-
-    Returns True if cancellation was initiated, False if job not found.
-    """
-    with _jobs_lock:
-        job_entry = _motion_search_jobs.get(job_id)
-        if not job_entry:
-            return False
-
-        job, cancel_event = job_entry
-
-        if job.status not in (JobStatusTypesEnum.queued, JobStatusTypesEnum.running):
-            # Already finished
-            return True
-
-        cancel_event.set()
-        job.status = JobStatusTypesEnum.cancelled
-        job_payload = job.to_dict()
-        logger.info("Cancelled motion search job %s", job_id)
-
-    requestor: Optional[InterProcessRequestor] = None
-    try:
-        requestor = InterProcessRequestor()
-        requestor.send_data(UPDATE_JOB_STATE, job_payload)
-    except Exception as e:
-        logger.warning(
-            "Failed to broadcast cancelled motion search job %s: %s", job_id, e
-        )
-    finally:
-        if requestor:
-            requestor.stop()
-
-    return True

frigate/models.py

@@ -78,7 +78,6 @@ class Recordings(Model):
     dBFS = IntegerField(null=True)
     segment_size = FloatField(default=0)  # this should be stored as MB
     regions = IntegerField(null=True)
-    motion_heatmap = JSONField(null=True)  # 16x16 grid, 256 values (0-255)
 
 
 class ExportCase(Model):

frigate/motion/improved_motion.py

@@ -176,32 +176,11 @@ class ImprovedMotionDetector(MotionDetector):
             motion_boxes = []
             pct_motion = 0
 
-        # skip motion entirely if the scene change percentage exceeds configured
-        # threshold. this is useful to ignore lighting storms, IR mode switches,
-        # etc. rather than registering them as brief motion and then recalibrating.
-        # note: skipping means the frame is dropped and **no recording will be
-        # created**, which could hide a legitimate object if the camera is actively
-        # auto‑tracking. the alternative is to allow motion and accept a small
-        # recording that can be reviewed in the timeline. disabled by default (None).
-        if (
-            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
-            self.calibrating = True
-            return []
-
         # once the motion is less than 5% and the number of contours is < 4, assume its calibrated
         if pct_motion < 0.05 and len(motion_boxes) <= 4:
             self.calibrating = False
 
-        # if calibrating or the motion contours are > 80% of the image area
-        # (lightning, ir, ptz) recalibrate. the lightning threshold does **not**
-        # stop motion detection entirely; it simply halts additional processing for
-        # the current frame once the percentage crosses the threshold. this helps
-        # reduce false positive object detections and CPU usage during high‑motion
-        # events. recordings continue to be generated because users expect data
-        # while a PTZ camera is moving.
+        # if calibrating or the motion contours are > 80% of the image area (lightning, ir, ptz) recalibrate
         if self.calibrating or pct_motion > self.config.lightning_threshold:
             self.calibrating = True
 

frigate/output/birdseye.py

@@ -273,13 +273,17 @@ class BirdsEyeFrameManager:
         stop_event: mp.Event,
     ):
         self.config = config
+        self.mode = config.birdseye.mode
         width, height = get_canvas_shape(config.birdseye.width, config.birdseye.height)
         self.frame_shape = (height, width)
         self.yuv_shape = (height * 3 // 2, width)
         self.frame = np.ndarray(self.yuv_shape, dtype=np.uint8)
         self.canvas = Canvas(width, height, config.birdseye.layout.scaling_factor)
         self.stop_event = stop_event
-        self.last_refresh_time = 0
+        self.inactivity_threshold = config.birdseye.inactivity_threshold
+
+        if config.birdseye.layout.max_cameras:
+            self.last_refresh_time = 0
 
         # initialize the frame as black and with the Frigate logo
         self.blank_frame = np.zeros(self.yuv_shape, np.uint8)
@@ -422,7 +426,7 @@ class BirdsEyeFrameManager:
                 and self.config.cameras[cam].enabled
                 and cam_data["last_active_frame"] > 0
                 and cam_data["current_frame_time"] - cam_data["last_active_frame"]
-                < self.config.birdseye.inactivity_threshold
+                < self.inactivity_threshold
             ]
         )
         logger.debug(f"Active cameras: {active_cameras}")

frigate/output/output.py

@@ -15,7 +15,6 @@ from ws4py.server.wsgirefserver import (
 )
 from ws4py.server.wsgiutils import WebSocketWSGIApplication
 
-from frigate.comms.config_updater import ConfigSubscriber
 from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
 from frigate.comms.ws import WebSocket
 from frigate.config import FrigateConfig
@@ -139,7 +138,6 @@ class OutputProcess(FrigateProcess):
                 CameraConfigUpdateEnum.record,
             ],
         )
-        birdseye_config_subscriber = ConfigSubscriber("config/birdseye", exact=True)
 
         jsmpeg_cameras: dict[str, JsmpegCamera] = {}
         birdseye: Birdseye | None = None
@@ -169,20 +167,6 @@ class OutputProcess(FrigateProcess):
         websocket_thread.start()
 
         while not self.stop_event.is_set():
-            update_topic, birdseye_config = (
-                birdseye_config_subscriber.check_for_update()
-            )
-
-            if update_topic is not None:
-                previous_global_mode = self.config.birdseye.mode
-                self.config.birdseye = birdseye_config
-
-                for camera_config in self.config.cameras.values():
-                    if camera_config.birdseye.mode == previous_global_mode:
-                        camera_config.birdseye.mode = birdseye_config.mode
-
-                logger.debug("Applied dynamic birdseye config update")
-
             # check if there is an updated config
             updates = config_subscriber.check_for_updates()
 
@@ -313,7 +297,6 @@ class OutputProcess(FrigateProcess):
             birdseye.stop()
 
         config_subscriber.stop()
-        birdseye_config_subscriber.stop()
         websocket_server.manager.close_all()
         websocket_server.manager.stop()
         websocket_server.manager.join()

frigate/record/maintainer.py

@@ -50,13 +50,11 @@ class SegmentInfo:
         active_object_count: int,
         region_count: int,
         average_dBFS: int,
-        motion_heatmap: dict[str, int] | None = None,
     ) -> None:
         self.motion_count = motion_count
         self.active_object_count = active_object_count
         self.region_count = region_count
         self.average_dBFS = average_dBFS
-        self.motion_heatmap = motion_heatmap
 
     def should_discard_segment(self, retain_mode: RetainModeEnum) -> bool:
         keep = False
@@ -456,59 +454,6 @@ class RecordingMaintainer(threading.Thread):
             if end_time < retain_cutoff:
                 self.drop_segment(cache_path)
 
-    def _compute_motion_heatmap(
-        self, camera: str, motion_boxes: list[tuple[int, int, int, int]]
-    ) -> dict[str, int] | None:
-        """Compute a 16x16 motion intensity heatmap from motion boxes.
-
-        Returns a sparse dict mapping cell index (as string) to intensity (1-255).
-        Only cells with motion are included.
-
-        Args:
-            camera: Camera name to get detect dimensions from.
-            motion_boxes: List of (x1, y1, x2, y2) pixel coordinates.
-
-        Returns:
-            Sparse dict like {"45": 3, "46": 5}, or None if no boxes.
-        """
-        if not motion_boxes:
-            return None
-
-        camera_config = self.config.cameras.get(camera)
-        if not camera_config:
-            return None
-
-        frame_width = camera_config.detect.width
-        frame_height = camera_config.detect.height
-
-        if frame_width <= 0 or frame_height <= 0:
-            return None
-
-        GRID_SIZE = 16
-        counts: dict[int, int] = {}
-
-        for box in motion_boxes:
-            if len(box) < 4:
-                continue
-            x1, y1, x2, y2 = box
-
-            # Convert pixel coordinates to grid cells
-            grid_x1 = max(0, int((x1 / frame_width) * GRID_SIZE))
-            grid_y1 = max(0, int((y1 / frame_height) * GRID_SIZE))
-            grid_x2 = min(GRID_SIZE - 1, int((x2 / frame_width) * GRID_SIZE))
-            grid_y2 = min(GRID_SIZE - 1, int((y2 / frame_height) * GRID_SIZE))
-
-            for y in range(grid_y1, grid_y2 + 1):
-                for x in range(grid_x1, grid_x2 + 1):
-                    idx = y * GRID_SIZE + x
-                    counts[idx] = min(255, counts.get(idx, 0) + 1)
-
-        if not counts:
-            return None
-
-        # Convert to string keys for JSON storage
-        return {str(k): v for k, v in counts.items()}
-
     def segment_stats(
         self, camera: str, start_time: datetime.datetime, end_time: datetime.datetime
     ) -> SegmentInfo:
@@ -516,8 +461,6 @@ class RecordingMaintainer(threading.Thread):
         active_count = 0
         region_count = 0
         motion_count = 0
-        all_motion_boxes: list[tuple[int, int, int, int]] = []
-
         for frame in self.object_recordings_info[camera]:
             # frame is after end time of segment
             if frame[0] > end_time.timestamp():
@@ -536,8 +479,6 @@ class RecordingMaintainer(threading.Thread):
             )
             motion_count += len(frame[2])
             region_count += len(frame[3])
-            # Collect motion boxes for heatmap computation
-            all_motion_boxes.extend(frame[2])
 
         audio_values = []
         for frame in self.audio_recordings_info[camera]:
@@ -557,14 +498,8 @@ class RecordingMaintainer(threading.Thread):
 
         average_dBFS = 0 if not audio_values else np.average(audio_values)
 
-        motion_heatmap = self._compute_motion_heatmap(camera, all_motion_boxes)
-
         return SegmentInfo(
-            motion_count,
-            active_count,
-            region_count,
-            round(average_dBFS),
-            motion_heatmap,
+            motion_count, active_count, region_count, round(average_dBFS)
         )
 
     async def move_segment(
@@ -655,7 +590,6 @@ class RecordingMaintainer(threading.Thread):
                     Recordings.regions.name: segment_info.region_count,
                     Recordings.dBFS.name: segment_info.average_dBFS,
                     Recordings.segment_size.name: segment_size,
-                    Recordings.motion_heatmap.name: segment_info.motion_heatmap,
                 }
         except Exception as e:
             logger.error(f"Unable to store recording segment {cache_path}")

frigate/test/http_api/test_http_config_set.py

@@ -1,261 +0,0 @@
-"""Tests for the config_set endpoint's wildcard camera propagation."""
-
-import os
-import tempfile
-import unittest
-from unittest.mock import MagicMock, Mock, patch
-
-import ruamel.yaml
-
-from frigate.config import FrigateConfig
-from frigate.config.camera.updater import (
-    CameraConfigUpdateEnum,
-    CameraConfigUpdatePublisher,
-    CameraConfigUpdateTopic,
-)
-from frigate.models import Event, Recordings, ReviewSegment
-from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
-
-
-class TestConfigSetWildcardPropagation(BaseTestHttp):
-    """Test that wildcard camera updates fan out to all cameras."""
-
-    def setUp(self):
-        super().setUp(models=[Event, Recordings, ReviewSegment])
-        self.minimal_config = {
-            "mqtt": {"host": "mqtt"},
-            "cameras": {
-                "front_door": {
-                    "ffmpeg": {
-                        "inputs": [
-                            {"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
-                        ]
-                    },
-                    "detect": {
-                        "height": 1080,
-                        "width": 1920,
-                        "fps": 5,
-                    },
-                },
-                "back_yard": {
-                    "ffmpeg": {
-                        "inputs": [
-                            {"path": "rtsp://10.0.0.2:554/video", "roles": ["detect"]}
-                        ]
-                    },
-                    "detect": {
-                        "height": 720,
-                        "width": 1280,
-                        "fps": 10,
-                    },
-                },
-            },
-        }
-
-    def _create_app_with_publisher(self):
-        """Create app with a mocked config publisher."""
-        from fastapi import Request
-
-        from frigate.api.auth import get_allowed_cameras_for_filter, get_current_user
-        from frigate.api.fastapi_app import create_fastapi_app
-
-        mock_publisher = Mock(spec=CameraConfigUpdatePublisher)
-        mock_publisher.publisher = MagicMock()
-
-        app = create_fastapi_app(
-            FrigateConfig(**self.minimal_config),
-            self.db,
-            None,
-            None,
-            None,
-            None,
-            None,
-            None,
-            mock_publisher,
-            None,
-            enforce_default_admin=False,
-        )
-
-        async def mock_get_current_user(request: Request):
-            username = request.headers.get("remote-user")
-            role = request.headers.get("remote-role")
-            return {"username": username, "role": role}
-
-        async def mock_get_allowed_cameras_for_filter(request: Request):
-            return list(self.minimal_config.get("cameras", {}).keys())
-
-        app.dependency_overrides[get_current_user] = mock_get_current_user
-        app.dependency_overrides[get_allowed_cameras_for_filter] = (
-            mock_get_allowed_cameras_for_filter
-        )
-
-        return app, mock_publisher
-
-    def _write_config_file(self):
-        """Write the minimal config to a temp YAML file and return the path."""
-        yaml = ruamel.yaml.YAML()
-        f = tempfile.NamedTemporaryFile(mode="w", suffix=".yml", delete=False)
-        yaml.dump(self.minimal_config, f)
-        f.close()
-        return f.name
-
-    @patch("frigate.api.app.find_config_file")
-    def test_wildcard_detect_update_fans_out_to_all_cameras(self, mock_find_config):
-        """config/cameras/*/detect fans out to all cameras."""
-        config_path = self._write_config_file()
-        mock_find_config.return_value = config_path
-
-        try:
-            app, mock_publisher = self._create_app_with_publisher()
-            with AuthTestClient(app) as client:
-                resp = client.put(
-                    "/config/set",
-                    json={
-                        "config_data": {"detect": {"fps": 15}},
-                        "update_topic": "config/cameras/*/detect",
-                        "requires_restart": 0,
-                    },
-                )
-
-                self.assertEqual(resp.status_code, 200)
-                data = resp.json()
-                self.assertTrue(data["success"])
-
-                # Verify publish_update called for each camera
-                self.assertEqual(mock_publisher.publish_update.call_count, 2)
-
-                published_cameras = set()
-                for c in mock_publisher.publish_update.call_args_list:
-                    topic = c[0][0]
-                    self.assertIsInstance(topic, CameraConfigUpdateTopic)
-                    self.assertEqual(topic.update_type, CameraConfigUpdateEnum.detect)
-                    published_cameras.add(topic.camera)
-
-                self.assertEqual(published_cameras, {"front_door", "back_yard"})
-
-                # Global publisher should NOT be called for wildcard
-                mock_publisher.publisher.publish.assert_not_called()
-        finally:
-            os.unlink(config_path)
-
-    @patch("frigate.api.app.find_config_file")
-    def test_wildcard_motion_update_fans_out(self, mock_find_config):
-        """config/cameras/*/motion fans out to all cameras."""
-        config_path = self._write_config_file()
-        mock_find_config.return_value = config_path
-
-        try:
-            app, mock_publisher = self._create_app_with_publisher()
-            with AuthTestClient(app) as client:
-                resp = client.put(
-                    "/config/set",
-                    json={
-                        "config_data": {"motion": {"threshold": 30}},
-                        "update_topic": "config/cameras/*/motion",
-                        "requires_restart": 0,
-                    },
-                )
-
-                self.assertEqual(resp.status_code, 200)
-
-                published_cameras = set()
-                for c in mock_publisher.publish_update.call_args_list:
-                    topic = c[0][0]
-                    self.assertEqual(topic.update_type, CameraConfigUpdateEnum.motion)
-                    published_cameras.add(topic.camera)
-
-                self.assertEqual(published_cameras, {"front_door", "back_yard"})
-        finally:
-            os.unlink(config_path)
-
-    @patch("frigate.api.app.find_config_file")
-    def test_camera_specific_topic_only_updates_one_camera(self, mock_find_config):
-        """config/cameras/front_door/detect only updates front_door."""
-        config_path = self._write_config_file()
-        mock_find_config.return_value = config_path
-
-        try:
-            app, mock_publisher = self._create_app_with_publisher()
-            with AuthTestClient(app) as client:
-                resp = client.put(
-                    "/config/set",
-                    json={
-                        "config_data": {
-                            "cameras": {"front_door": {"detect": {"fps": 20}}}
-                        },
-                        "update_topic": "config/cameras/front_door/detect",
-                        "requires_restart": 0,
-                    },
-                )
-
-                self.assertEqual(resp.status_code, 200)
-
-                # Only one camera updated
-                self.assertEqual(mock_publisher.publish_update.call_count, 1)
-                topic = mock_publisher.publish_update.call_args[0][0]
-                self.assertEqual(topic.camera, "front_door")
-                self.assertEqual(topic.update_type, CameraConfigUpdateEnum.detect)
-
-                # Global publisher should NOT be called
-                mock_publisher.publisher.publish.assert_not_called()
-        finally:
-            os.unlink(config_path)
-
-    @patch("frigate.api.app.find_config_file")
-    def test_wildcard_sends_merged_per_camera_config(self, mock_find_config):
-        """Wildcard fan-out sends each camera's own merged config."""
-        config_path = self._write_config_file()
-        mock_find_config.return_value = config_path
-
-        try:
-            app, mock_publisher = self._create_app_with_publisher()
-            with AuthTestClient(app) as client:
-                resp = client.put(
-                    "/config/set",
-                    json={
-                        "config_data": {"detect": {"fps": 15}},
-                        "update_topic": "config/cameras/*/detect",
-                        "requires_restart": 0,
-                    },
-                )
-
-                self.assertEqual(resp.status_code, 200)
-
-                for c in mock_publisher.publish_update.call_args_list:
-                    camera_detect_config = c[0][1]
-                    self.assertIsNotNone(camera_detect_config)
-                    self.assertTrue(hasattr(camera_detect_config, "fps"))
-        finally:
-            os.unlink(config_path)
-
-    @patch("frigate.api.app.find_config_file")
-    def test_non_camera_global_topic_uses_generic_publish(self, mock_find_config):
-        """Non-camera topics (e.g. config/live) use the generic publisher."""
-        config_path = self._write_config_file()
-        mock_find_config.return_value = config_path
-
-        try:
-            app, mock_publisher = self._create_app_with_publisher()
-            with AuthTestClient(app) as client:
-                resp = client.put(
-                    "/config/set",
-                    json={
-                        "config_data": {"live": {"height": 720}},
-                        "update_topic": "config/live",
-                        "requires_restart": 0,
-                    },
-                )
-
-                self.assertEqual(resp.status_code, 200)
-
-                # Global topic publisher called
-                mock_publisher.publisher.publish.assert_called_once()
-
-                # Camera-level publish_update NOT called
-                mock_publisher.publish_update.assert_not_called()
-        finally:
-            os.unlink(config_path)
-
-
-if __name__ == "__main__":
-    unittest.main()

frigate/test/test_motion_detector.py

@@ -1,91 +0,0 @@
-import unittest
-
-import numpy as np
-
-from frigate.config.camera.motion import MotionConfig
-from frigate.motion.improved_motion import ImprovedMotionDetector
-
-
-class TestImprovedMotionDetector(unittest.TestCase):
-    def setUp(self):
-        # small frame for testing; actual frames are grayscale
-        self.frame_shape = (100, 100)  # height, width
-        self.config = MotionConfig()
-        # motion detector assumes a rasterized_mask attribute exists on config
-        # when update_mask() is called; add one manually by bypassing pydantic.
-        object.__setattr__(
-            self.config,
-            "rasterized_mask",
-            np.ones((self.frame_shape[0], self.frame_shape[1]), dtype=np.uint8),
-        )
-
-        # create minimal PTZ metrics stub to satisfy detector checks
-        class _Stub:
-            def __init__(self, value=False):
-                self.value = value
-
-            def is_set(self):
-                return bool(self.value)
-
-        class DummyPTZ:
-            def __init__(self):
-                self.autotracker_enabled = _Stub(False)
-                self.motor_stopped = _Stub(False)
-                self.stop_time = _Stub(0)
-
-        self.detector = ImprovedMotionDetector(
-            self.frame_shape, self.config, fps=30, ptz_metrics=DummyPTZ()
-        )
-
-        # establish a baseline frame (all zeros)
-        base_frame = np.zeros(
-            (self.frame_shape[0], self.frame_shape[1]), dtype=np.uint8
-        )
-        self.detector.detect(base_frame)
-
-    def _half_change_frame(self) -> np.ndarray:
-        """Produce a frame where roughly half of the pixels are different."""
-        frame = np.zeros((self.frame_shape[0], self.frame_shape[1]), dtype=np.uint8)
-        # flip the top half to white
-        frame[: self.frame_shape[0] // 2, :] = 255
-        return frame
-
-    def test_skip_motion_threshold_default(self):
-        """With the default (None) setting, motion should always be reported."""
-        frame = self._half_change_frame()
-        boxes = self.detector.detect(frame)
-        self.assertTrue(
-            boxes, "Expected motion boxes when skip threshold is unset (disabled)"
-        )
-
-    def test_skip_motion_threshold_applied(self):
-        """Setting a low skip threshold should prevent any boxes from being returned."""
-        # change the config and update the detector reference
-        self.config.skip_motion_threshold = 0.4
-        self.detector.config = self.config
-        self.detector.update_mask()
-
-        frame = self._half_change_frame()
-        boxes = self.detector.detect(frame)
-        self.assertEqual(
-            boxes,
-            [],
-            "Motion boxes should be empty when scene change exceeds skip threshold",
-        )
-
-    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
-        self.detector.config = self.config
-        self.detector.update_mask()
-
-        frame = self._half_change_frame()
-        _ = self.detector.detect(frame)
-        self.assertTrue(
-            self.detector.calibrating,
-            "Detector should be in calibrating state after skip event",
-        )
-
-
-if __name__ == "__main__":
-    unittest.main()

frigate/test/test_profiles.py

@@ -70,24 +70,6 @@ class TestCameraProfileConfig(unittest.TestCase):
         profile = CameraProfileConfig()
         assert profile.enabled is None
 
-    def test_zones_field(self):
-        """Profile with zones override."""
-        profile = CameraProfileConfig(
-            zones={
-                "driveway": {
-                    "coordinates": "0.1,0.1,0.9,0.1,0.9,0.9,0.1,0.9",
-                    "objects": ["car"],
-                }
-            }
-        )
-        assert profile.zones is not None
-        assert "driveway" in profile.zones
-
-    def test_zones_default_none(self):
-        """Zones defaults to None when not set."""
-        profile = CameraProfileConfig()
-        assert profile.zones is None
-
     def test_none_sections_not_in_dump(self):
         """Sections left as None should not appear in exclude_unset dump."""
         profile = CameraProfileConfig(detect={"enabled": False})
@@ -398,81 +380,6 @@ class TestProfileManager(unittest.TestCase):
         self.manager.activate_profile(None)
         assert self.config.cameras["front"].enabled is True
 
-    @patch.object(ProfileManager, "_persist_active_profile")
-    def test_activate_profile_adds_zone(self, mock_persist):
-        """Profile with zones adds/overrides zones on camera."""
-        from frigate.config.camera.profile import CameraProfileConfig
-        from frigate.config.camera.zone import ZoneConfig
-
-        self.config.cameras["front"].profiles["away"] = CameraProfileConfig(
-            zones={
-                "driveway": ZoneConfig(
-                    coordinates="0.1,0.1,0.9,0.1,0.9,0.9,0.1,0.9",
-                    objects=["car"],
-                )
-            }
-        )
-        self.manager = ProfileManager(self.config, self.mock_updater)
-
-        assert "driveway" not in self.config.cameras["front"].zones
-
-        err = self.manager.activate_profile("away")
-        assert err is None
-        assert "driveway" in self.config.cameras["front"].zones
-
-    @patch.object(ProfileManager, "_persist_active_profile")
-    def test_deactivate_restores_zones(self, mock_persist):
-        """Deactivating a profile restores base zones."""
-        from frigate.config.camera.profile import CameraProfileConfig
-        from frigate.config.camera.zone import ZoneConfig
-
-        self.config.cameras["front"].profiles["away"] = CameraProfileConfig(
-            zones={
-                "driveway": ZoneConfig(
-                    coordinates="0.1,0.1,0.9,0.1,0.9,0.9,0.1,0.9",
-                    objects=["car"],
-                )
-            }
-        )
-        self.manager = ProfileManager(self.config, self.mock_updater)
-
-        self.manager.activate_profile("away")
-        assert "driveway" in self.config.cameras["front"].zones
-
-        self.manager.activate_profile(None)
-        assert "driveway" not in self.config.cameras["front"].zones
-
-    @patch.object(ProfileManager, "_persist_active_profile")
-    def test_zones_zmq_published(self, mock_persist):
-        """ZMQ update is published for zones change."""
-        from frigate.config.camera.profile import CameraProfileConfig
-        from frigate.config.camera.updater import (
-            CameraConfigUpdateEnum,
-            CameraConfigUpdateTopic,
-        )
-        from frigate.config.camera.zone import ZoneConfig
-
-        self.config.cameras["front"].profiles["away"] = CameraProfileConfig(
-            zones={
-                "driveway": ZoneConfig(
-                    coordinates="0.1,0.1,0.9,0.1,0.9,0.9,0.1,0.9",
-                    objects=["car"],
-                )
-            }
-        )
-        self.manager = ProfileManager(self.config, self.mock_updater)
-        self.mock_updater.reset_mock()
-
-        self.manager.activate_profile("away")
-
-        zones_calls = [
-            call
-            for call in self.mock_updater.publish_update.call_args_list
-            if call[0][0]
-            == CameraConfigUpdateTopic(CameraConfigUpdateEnum.zones, "front")
-        ]
-        assert len(zones_calls) == 1
-
     @patch.object(ProfileManager, "_persist_active_profile")
     def test_enabled_zmq_published(self, mock_persist):
         """ZMQ update is published for enabled state change."""

frigate/util/camera_cleanup.py

@@ -1,153 +0,0 @@
-"""Utilities for cleaning up camera data from database and filesystem."""
-
-import glob
-import logging
-import os
-import shutil
-
-from frigate.const import CLIPS_DIR, RECORD_DIR, THUMB_DIR
-from frigate.models import (
-    Event,
-    Export,
-    Previews,
-    Recordings,
-    Regions,
-    ReviewSegment,
-    Timeline,
-    Trigger,
-)
-
-logger = logging.getLogger(__name__)
-
-
-def cleanup_camera_db(
-    camera_name: str, delete_exports: bool = False
-) -> tuple[dict[str, int], list[str]]:
-    """Remove all database rows for a camera.
-
-    Args:
-        camera_name: The camera name to clean up
-        delete_exports: Whether to also delete export records
-
-    Returns:
-        Tuple of (deletion counts dict, list of export file paths to remove)
-    """
-    counts: dict[str, int] = {}
-    export_paths: list[str] = []
-
-    try:
-        counts["events"] = Event.delete().where(Event.camera == camera_name).execute()
-    except Exception as e:
-        logger.error("Failed to delete events for camera %s: %s", camera_name, e)
-
-    try:
-        counts["timeline"] = (
-            Timeline.delete().where(Timeline.camera == camera_name).execute()
-        )
-    except Exception as e:
-        logger.error("Failed to delete timeline for camera %s: %s", camera_name, e)
-
-    try:
-        counts["recordings"] = (
-            Recordings.delete().where(Recordings.camera == camera_name).execute()
-        )
-    except Exception as e:
-        logger.error("Failed to delete recordings for camera %s: %s", camera_name, e)
-
-    try:
-        counts["review_segments"] = (
-            ReviewSegment.delete().where(ReviewSegment.camera == camera_name).execute()
-        )
-    except Exception as e:
-        logger.error(
-            "Failed to delete review segments for camera %s: %s", camera_name, e
-        )
-
-    try:
-        counts["previews"] = (
-            Previews.delete().where(Previews.camera == camera_name).execute()
-        )
-    except Exception as e:
-        logger.error("Failed to delete previews for camera %s: %s", camera_name, e)
-
-    try:
-        counts["regions"] = (
-            Regions.delete().where(Regions.camera == camera_name).execute()
-        )
-    except Exception as e:
-        logger.error("Failed to delete regions for camera %s: %s", camera_name, e)
-
-    try:
-        counts["triggers"] = (
-            Trigger.delete().where(Trigger.camera == camera_name).execute()
-        )
-    except Exception as e:
-        logger.error("Failed to delete triggers for camera %s: %s", camera_name, e)
-
-    if delete_exports:
-        try:
-            exports = Export.select(Export.video_path, Export.thumb_path).where(
-                Export.camera == camera_name
-            )
-            for export in exports:
-                export_paths.append(export.video_path)
-                export_paths.append(export.thumb_path)
-
-            counts["exports"] = (
-                Export.delete().where(Export.camera == camera_name).execute()
-            )
-        except Exception as e:
-            logger.error("Failed to delete exports for camera %s: %s", camera_name, e)
-
-    return counts, export_paths
-
-
-def cleanup_camera_files(
-    camera_name: str, export_paths: list[str] | None = None
-) -> None:
-    """Remove filesystem artifacts for a camera.
-
-    Args:
-        camera_name: The camera name to clean up
-        export_paths: Optional list of export file paths to remove
-    """
-    dirs_to_clean = [
-        os.path.join(RECORD_DIR, camera_name),
-        os.path.join(CLIPS_DIR, camera_name),
-        os.path.join(THUMB_DIR, camera_name),
-        os.path.join(CLIPS_DIR, "previews", camera_name),
-    ]
-
-    for dir_path in dirs_to_clean:
-        if os.path.exists(dir_path):
-            try:
-                shutil.rmtree(dir_path)
-                logger.debug("Removed directory: %s", dir_path)
-            except Exception as e:
-                logger.error("Failed to remove %s: %s", dir_path, e)
-
-    # Remove event snapshot files
-    for snapshot in glob.glob(os.path.join(CLIPS_DIR, f"{camera_name}-*.jpg")):
-        try:
-            os.remove(snapshot)
-        except Exception as e:
-            logger.error("Failed to remove snapshot %s: %s", snapshot, e)
-
-    # Remove review thumbnail files
-    for thumb in glob.glob(
-        os.path.join(CLIPS_DIR, "review", f"thumb-{camera_name}-*.webp")
-    ):
-        try:
-            os.remove(thumb)
-        except Exception as e:
-            logger.error("Failed to remove review thumbnail %s: %s", thumb, e)
-
-    # Remove export files if requested
-    if export_paths:
-        for path in export_paths:
-            if path and os.path.exists(path):
-                try:
-                    os.remove(path)
-                    logger.debug("Removed export file: %s", path)
-                except Exception as e:
-                    logger.error("Failed to remove export file %s: %s", path, e)

frigate/util/media.py

@@ -151,9 +151,7 @@ def sync_recordings(
 
             max_inserts = 1000
             for batch in chunked(recordings_to_delete, max_inserts):
-                RecordingsToDelete.insert_many(
-                    [{"id": r["id"]} for r in batch]
-                ).execute()
+                RecordingsToDelete.insert_many(batch).execute()
 
             try:
                 deleted = (

frigate/util/rknn_converter.py

@@ -110,7 +110,6 @@ def ensure_torch_dependencies() -> bool:
                     "pip",
                     "install",
                     "--break-system-packages",
-                    "setuptools<81",
                     "torch",
                     "torchvision",
                 ],

frigate/video.py

@@ -214,11 +214,7 @@ class CameraWatchdog(threading.Thread):
         self.config_subscriber = CameraConfigUpdateSubscriber(
             None,
             {config.name: config},
-            [
-                CameraConfigUpdateEnum.enabled,
-                CameraConfigUpdateEnum.ffmpeg,
-                CameraConfigUpdateEnum.record,
-            ],
+            [CameraConfigUpdateEnum.enabled, CameraConfigUpdateEnum.record],
         )
         self.requestor = InterProcessRequestor()
         self.was_enabled = self.config.enabled
@@ -258,13 +254,9 @@ class CameraWatchdog(threading.Thread):
             self._last_record_status = status
             self._last_status_update_time = now
 
-    def _check_config_updates(self) -> dict[str, list[str]]:
-        """Check for config updates and return the update dict."""
-        return self.config_subscriber.check_for_updates()
-
     def _update_enabled_state(self) -> bool:
         """Fetch the latest config and update enabled state."""
-        self._check_config_updates()
+        self.config_subscriber.check_for_updates()
         return self.config.enabled
 
     def reset_capture_thread(
@@ -325,24 +317,7 @@ class CameraWatchdog(threading.Thread):
 
         # 1 second watchdog loop
         while not self.stop_event.wait(1):
-            updates = self._check_config_updates()
-
-            # Handle ffmpeg config changes by restarting all ffmpeg processes
-            if "ffmpeg" in updates and self.config.enabled:
-                self.logger.debug(
-                    "FFmpeg config updated for %s, restarting ffmpeg processes",
-                    self.config.name,
-                )
-                self.stop_all_ffmpeg()
-                self.start_all_ffmpeg()
-                self.latest_valid_segment_time = 0
-                self.latest_invalid_segment_time = 0
-                self.latest_cache_segment_time = 0
-                self.record_enable_time = datetime.now().astimezone(timezone.utc)
-                last_restart_time = datetime.now().timestamp()
-                continue
-
-            enabled = self.config.enabled
+            enabled = self._update_enabled_state()
             if enabled != self.was_enabled:
                 if enabled:
                     self.logger.debug(f"Enabling camera {self.config.name}")

migrations/035_add_motion_heatmap.py

@@ -1,34 +0,0 @@
-"""Peewee migrations -- 035_add_motion_heatmap.py.
-
-Some examples (model - class or model name)::
-
-    > Model = migrator.orm['model_name']            # Return model in current state by name
-
-    > migrator.sql(sql)                             # Run custom SQL
-    > migrator.python(func, *args, **kwargs)        # Run python code
-    > migrator.create_model(Model)                  # Create a model (could be used as decorator)
-    > migrator.remove_model(model, cascade=True)    # Remove a model
-    > migrator.add_fields(model, **fields)          # Add fields to a model
-    > migrator.change_fields(model, **fields)       # Change fields
-    > migrator.remove_fields(model, *field_names, cascade=True)
-    > migrator.rename_field(model, old_field_name, new_field_name)
-    > migrator.rename_table(model, new_table_name)
-    > migrator.add_index(model, *col_names, unique=False)
-    > migrator.drop_index(model, *col_names)
-    > migrator.add_not_null(model, *field_names)
-    > migrator.drop_not_null(model, *field_names)
-    > migrator.add_default(model, field_name, default)
-
-"""
-
-import peewee as pw
-
-SQL = pw.SQL
-
-
-def migrate(migrator, database, fake=False, **kwargs):
-    migrator.sql('ALTER TABLE "recordings" ADD COLUMN "motion_heatmap" TEXT NULL')
-
-
-def rollback(migrator, database, fake=False, **kwargs):
-    pass

web/package-lock.json

@@ -22,7 +22,6 @@
         "@radix-ui/react-hover-card": "^1.1.6",
         "@radix-ui/react-label": "^2.1.2",
         "@radix-ui/react-popover": "^1.1.6",
-        "@radix-ui/react-progress": "^1.1.8",
         "@radix-ui/react-radio-group": "^1.2.3",
         "@radix-ui/react-scroll-area": "^1.2.3",
         "@radix-ui/react-select": "^2.1.6",
@@ -2923,68 +2922,6 @@
         }
       }
     },
-    "node_modules/@radix-ui/react-progress": {
-      "version": "1.1.8",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-progress/-/react-progress-1.1.8.tgz",
-      "integrity": "sha512-+gISHcSPUJ7ktBy9RnTqbdKW78bcGke3t6taawyZ71pio1JewwGSJizycs7rLhGTvMJYCQB1DBK4KQsxs7U8dA==",
-      "license": "MIT",
-      "dependencies": {
-        "@radix-ui/react-context": "1.1.3",
-        "@radix-ui/react-primitive": "2.1.4"
-      },
-      "peerDependencies": {
-        "@types/react": "*",
-        "@types/react-dom": "*",
-        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
-        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
-      },
-      "peerDependenciesMeta": {
-        "@types/react": {
-          "optional": true
-        },
-        "@types/react-dom": {
-          "optional": true
-        }
-      }
-    },
-    "node_modules/@radix-ui/react-progress/node_modules/@radix-ui/react-context": {
-      "version": "1.1.3",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-context/-/react-context-1.1.3.tgz",
-      "integrity": "sha512-ieIFACdMpYfMEjF0rEf5KLvfVyIkOz6PDGyNnP+u+4xQ6jny3VCgA4OgXOwNx2aUkxn8zx9fiVcM8CfFYv9Lxw==",
-      "license": "MIT",
-      "peerDependencies": {
-        "@types/react": "*",
-        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
-      },
-      "peerDependenciesMeta": {
-        "@types/react": {
-          "optional": true
-        }
-      }
-    },
-    "node_modules/@radix-ui/react-progress/node_modules/@radix-ui/react-primitive": {
-      "version": "2.1.4",
-      "resolved": "https://registry.npmjs.org/@radix-ui/react-primitive/-/react-primitive-2.1.4.tgz",
-      "integrity": "sha512-9hQc4+GNVtJAIEPEqlYqW5RiYdrr8ea5XQ0ZOnD6fgru+83kqT15mq2OCcbe8KnjRZl5vF3ks69AKz3kh1jrhg==",
-      "license": "MIT",
-      "dependencies": {
-        "@radix-ui/react-slot": "1.2.4"
-      },
-      "peerDependencies": {
-        "@types/react": "*",
-        "@types/react-dom": "*",
-        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
-        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
-      },
-      "peerDependenciesMeta": {
-        "@types/react": {
-          "optional": true
-        },
-        "@types/react-dom": {
-          "optional": true
-        }
-      }
-    },
     "node_modules/@radix-ui/react-radio-group": {
       "version": "1.3.8",
       "resolved": "https://registry.npmjs.org/@radix-ui/react-radio-group/-/react-radio-group-1.3.8.tgz",

web/package.json

@@ -28,7 +28,6 @@
     "@radix-ui/react-hover-card": "^1.1.6",
     "@radix-ui/react-label": "^2.1.2",
     "@radix-ui/react-popover": "^1.1.6",
-    "@radix-ui/react-progress": "^1.1.8",
     "@radix-ui/react-radio-group": "^1.2.3",
     "@radix-ui/react-scroll-area": "^1.2.3",
     "@radix-ui/react-select": "^2.1.6",

web/public/locales/en/config/cameras.json

@@ -264,11 +264,7 @@
     },
     "lightning_threshold": {
       "label": "Lightning threshold",
-      "description": "Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0). This does not prevent motion detection entirely; it merely causes the detector to stop analyzing additional frames once the threshold is exceeded. Motion-based recordings are still created during these events."
-    },
-    "skip_motion_threshold": {
-      "label": "Skip motion threshold",
-      "description": "If more than this fraction of the image changes in a single frame, the detector will return no motion boxes and immediately recalibrate. This can save CPU and reduce false positives during lightning, storms, etc., but may miss real events such as a PTZ camera auto‑tracking an object. The trade‑off is between dropping a few megabytes of recordings versus reviewing a couple short clips. Range 0.0 to 1.0."
+      "description": "Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0)."
     },
     "improve_contrast": {
       "label": "Improve contrast",
@@ -868,8 +864,7 @@
       "description": "A user-friendly name for the zone, displayed in the Frigate UI. If not set, a formatted version of the zone name will be used."
     },
     "enabled": {
-      "label": "Enabled",
-      "description": "Enable or disable this zone. Disabled zones are ignored at runtime."
+      "label": "Whether this zone is active. Disabled zones are ignored at runtime."
     },
     "enabled_in_config": {
       "label": "Keep track of original state of zone."

web/public/locales/en/config/global.json

@@ -1391,11 +1391,7 @@
     },
     "lightning_threshold": {
       "label": "Lightning threshold",
-      "description": "Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0). This does not prevent motion detection entirely; it merely causes the detector to stop analyzing additional frames once the threshold is exceeded. Motion-based recordings are still created during these events."
-    },
-    "skip_motion_threshold": {
-      "label": "Skip motion threshold",
-      "description": "If more than this fraction of the image changes in a single frame, the detector will return no motion boxes and immediately recalibrate. This can save CPU and reduce false positives during lightning, storms, etc., but may miss real events such as a PTZ camera auto‑tracking an object. The trade‑off is between dropping a few megabytes of recordings versus reviewing a couple short clips. Range 0.0 to 1.0."
+      "description": "Threshold to detect and ignore brief lighting spikes (lower is more sensitive, values between 0.3 and 1.0)."
     },
     "improve_contrast": {
       "label": "Improve contrast",

web/public/locales/en/views/events.json

@@ -61,25 +61,5 @@
   "detected": "detected",
   "normalActivity": "Normal",
   "needsReview": "Needs review",
-  "securityConcern": "Security concern",
-  "motionSearch": {
-    "menuItem": "Motion search",
-    "openMenu": "Camera options"
-  },
-  "motionPreviews": {
-    "menuItem": "View motion previews",
-    "title": "Motion previews: {{camera}}",
-    "mobileSettingsTitle": "Motion Preview Settings",
-    "mobileSettingsDesc": "Adjust playback speed and dimming, and choose a date to review motion-only clips.",
-    "dim": "Dim",
-    "dimAria": "Adjust dimming intensity",
-    "dimDesc": "Increase dimming to increase motion area visibility.",
-    "speed": "Speed",
-    "speedAria": "Select preview playback speed",
-    "speedDesc": "Choose how quickly preview clips play.",
-    "back": "Back",
-    "empty": "No previews available",
-    "noPreview": "Preview unavailable",
-    "seekAria": "Seek {{camera}} player to {{time}}"
-  }
+  "securityConcern": "Security concern"
 }

web/public/locales/en/views/motionSearch.json

@@ -1,75 +0,0 @@
-{
-  "documentTitle": "Motion Search - Frigate",
-  "title": "Motion Search",
-  "description": "Draw a polygon to define the region of interest, and specify a time range to search for motion changes within that region.",
-  "selectCamera": "Motion Search is loading",
-  "startSearch": "Start Search",
-  "searchStarted": "Search started",
-  "searchCancelled": "Search cancelled",
-  "cancelSearch": "Cancel",
-  "searching": "Search in progress.",
-  "searchComplete": "Search complete",
-  "noResultsYet": "Run a search to find motion changes in the selected region",
-  "noChangesFound": "No pixel changes detected in the selected region",
-  "changesFound_one": "Found {{count}} motion change",
-  "changesFound_other": "Found {{count}} motion changes",
-  "framesProcessed": "{{count}} frames processed",
-  "jumpToTime": "Jump to this time",
-  "results": "Results",
-  "showSegmentHeatmap": "Heatmap",
-  "newSearch": "New Search",
-  "clearResults": "Clear Results",
-  "clearROI": "Clear polygon",
-  "polygonControls": {
-    "points_one": "{{count}} point",
-    "points_other": "{{count}} points",
-    "undo": "Undo last point",
-    "reset": "Reset polygon"
-  },
-  "motionHeatmapLabel": "Motion Heatmap",
-  "dialog": {
-    "title": "Motion Search",
-    "cameraLabel": "Camera",
-    "previewAlt": "Camera preview for {{camera}}"
-  },
-  "timeRange": {
-    "title": "Search Range",
-    "start": "Start time",
-    "end": "End time"
-  },
-  "settings": {
-    "title": "Search Settings",
-    "parallelMode": "Parallel mode",
-    "parallelModeDesc": "Scan multiple recording segments at the same time (faster, but significantly more CPU intensive)",
-    "threshold": "Sensitivity Threshold",
-    "thresholdDesc": "Lower values detect smaller changes (1-255)",
-    "minArea": "Minimum Change Area",
-    "minAreaDesc": "Minimum percentage of the region of interest that must change to be considered significant",
-    "frameSkip": "Frame Skip",
-    "frameSkipDesc": "Process every Nth frame. Set this to your camera's frame rate to process one frame per second (e.g. 5 for a 5 FPS camera, 30 for a 30 FPS camera). Higher values will be faster, but may miss short motion events.",
-    "maxResults": "Maximum Results",
-    "maxResultsDesc": "Stop after this many matching timestamps"
-  },
-  "errors": {
-    "noCamera": "Please select a camera",
-    "noROI": "Please draw a region of interest",
-    "noTimeRange": "Please select a time range",
-    "invalidTimeRange": "End time must be after start time",
-    "searchFailed": "Search failed: {{message}}",
-    "polygonTooSmall": "Polygon must have at least 3 points",
-    "unknown": "Unknown error"
-  },
-  "changePercentage": "{{percentage}}% changed",
-  "metrics": {
-    "title": "Search Metrics",
-    "segmentsScanned": "Segments scanned",
-    "segmentsProcessed": "Processed",
-    "segmentsSkippedInactive": "Skipped (no activity)",
-    "segmentsSkippedHeatmap": "Skipped (no ROI overlap)",
-    "fallbackFullRange": "Fallback full-range scan",
-    "framesDecoded": "Frames decoded",
-    "wallTime": "Search time",
-    "segmentErrors": "Segment errors",
-    "seconds": "{{seconds}}s"
-  }
-}

web/public/locales/en/views/settings.json

@@ -83,8 +83,7 @@
     "triggers": "Triggers",
     "debug": "Debug",
     "frigateplus": "Frigate+",
-    "mediaSync": "Media sync",
-    "regionGrid": "Region grid"
+    "maintenance": "Maintenance"
   },
   "dialog": {
     "unsavedChanges": {
@@ -422,18 +421,6 @@
   "cameraManagement": {
     "title": "Manage Cameras",
     "addCamera": "Add New Camera",
-    "deleteCamera": "Delete Camera",
-    "deleteCameraDialog": {
-      "title": "Delete Camera",
-      "description": "Deleting a camera will permanently remove all recordings, tracked objects, and configuration for that camera. Any go2rtc streams associated with this camera may still need to be manually removed.",
-      "selectPlaceholder": "Choose camera...",
-      "confirmTitle": "Are you sure?",
-      "confirmWarning": "Deleting <strong>{{cameraName}}</strong> cannot be undone.",
-      "deleteExports": "Also delete exports for this camera",
-      "confirmButton": "Delete Permanently",
-      "success": "Camera {{cameraName}} deleted successfully",
-      "error": "Failed to delete camera {{cameraName}}"
-    },
     "editCamera": "Edit Camera:",
     "selectCamera": "Select a Camera",
     "backToSettings": "Back to Camera Settings",
@@ -1245,16 +1232,6 @@
       "previews": "Previews",
       "exports": "Exports",
       "recordings": "Recordings"
-    },
-    "regionGrid": {
-      "title": "Region Grid",
-      "desc": "The region grid is an optimization that learns where objects of different sizes typically appear in each camera's field of view. Frigate uses this data to efficiently size detection regions. The grid is automatically built over time from tracked object data.",
-      "clear": "Clear region grid",
-      "clearConfirmTitle": "Clear Region Grid",
-      "clearConfirmDesc": "Clearing the region grid is not recommended unless you have recently changed your detector model size or have changed your camera's physical position and are having object tracking issues. The grid will be automatically rebuilt over time as objects are tracked. A Frigate restart is required for changes to take effect.",
-      "clearSuccess": "Region grid cleared successfully",
-      "clearError": "Failed to clear region grid",
-      "restartRequired": "Restart required for region grid changes to take effect"
     }
   },
   "configForm": {

web/src/App.tsx

@@ -11,6 +11,7 @@ import { Redirect } from "./components/navigation/Redirect";
 import { cn } from "./lib/utils";
 import { isPWA } from "./utils/isPWA";
 import ProtectedRoute from "@/components/auth/ProtectedRoute";
+import { AuthProvider } from "@/context/auth-context";
 import useSWR from "swr";
 import { FrigateConfig } from "./types/frigateConfig";
 import ActivityIndicator from "@/components/indicators/activity-indicator";
@@ -38,11 +39,13 @@ function App() {
 
   return (
     <Providers>
-      <BrowserRouter basename={window.baseUrl}>
-        <Wrapper>
-          {config?.safe_mode ? <SafeAppView /> : <DefaultAppView />}
-        </Wrapper>
-      </BrowserRouter>
+      <AuthProvider>
+        <BrowserRouter basename={window.baseUrl}>
+          <Wrapper>
+            {config?.safe_mode ? <SafeAppView /> : <DefaultAppView />}
+          </Wrapper>
+        </BrowserRouter>
+      </AuthProvider>
     </Providers>
   );
 }
@@ -82,13 +85,17 @@ function DefaultAppView() {
             : "bottom-8 left-[52px]",
         )}
       >
-        <Suspense
-          fallback={
-            <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
-          }
-        >
+        <Suspense>
           <Routes>
-            <Route element={<ProtectedRoute requiredRoles={mainRouteRoles} />}>
+            <Route
+              element={
+                mainRouteRoles ? (
+                  <ProtectedRoute requiredRoles={mainRouteRoles} />
+                ) : (
+                  <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
+                )
+              }
+            >
               <Route index element={<Live />} />
               <Route path="/review" element={<Events />} />
               <Route path="/explore" element={<Explore />} />

web/src/components/auth/ProtectedRoute.tsx

@@ -10,7 +10,7 @@ import {
 export default function ProtectedRoute({
   requiredRoles,
 }: {
-  requiredRoles?: string[];
+  requiredRoles: string[];
 }) {
   const { auth } = useContext(AuthContext);
 
@@ -36,13 +36,6 @@ export default function ProtectedRoute({
     );
   }
 
-  // Wait for config to provide required roles
-  if (!requiredRoles) {
-    return (
-      <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
-    );
-  }
-
   if (auth.isLoading) {
     return (
       <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />

web/src/components/config-form/section-configs/audio.ts

@@ -25,7 +25,14 @@ const audio: SectionConfigOverrides = {
     },
   },
   global: {
-    restartRequired: ["num_threads"],
+    restartRequired: [
+      "enabled",
+      "listen",
+      "filters",
+      "min_volume",
+      "max_not_heard",
+      "num_threads",
+    ],
   },
   camera: {
     restartRequired: ["num_threads"],

web/src/components/config-form/section-configs/birdseye.ts

@@ -28,7 +28,10 @@ const birdseye: SectionConfigOverrides = {
       "width",
       "height",
       "quality",
+      "mode",
       "layout.scaling_factor",
+      "inactivity_threshold",
+      "layout.max_cameras",
       "idle_heartbeat_fps",
     ],
     uiSchema: {

web/src/components/config-form/section-configs/classification.ts

@@ -3,7 +3,7 @@ import type { SectionConfigOverrides } from "./types";
 const classification: SectionConfigOverrides = {
   base: {
     sectionDocs: "/configuration/custom_classification/object_classification",
-    restartRequired: ["bird.enabled"],
+    restartRequired: ["bird.enabled", "bird.threshold"],
     hiddenFields: ["custom"],
     advancedFields: [],
   },

web/src/components/config-form/section-configs/detect.ts

@@ -31,21 +31,18 @@ const detect: SectionConfigOverrides = {
   },
   global: {
     restartRequired: [
-      "fps",
+      "enabled",
       "width",
       "height",
+      "fps",
       "min_initialized",
       "max_disappeared",
+      "annotation_offset",
+      "stationary",
     ],
   },
   camera: {
-    restartRequired: [
-      "fps",
-      "width",
-      "height",
-      "min_initialized",
-      "max_disappeared",
-    ],
+    restartRequired: ["width", "height", "min_initialized", "max_disappeared"],
   },
 };
 

web/src/components/config-form/section-configs/face_recognition.ts

@@ -32,7 +32,18 @@ const faceRecognition: SectionConfigOverrides = {
       "blur_confidence_filter",
       "device",
     ],
-    restartRequired: ["enabled", "model_size", "device"],
+    restartRequired: [
+      "enabled",
+      "model_size",
+      "unknown_score",
+      "detection_threshold",
+      "recognition_threshold",
+      "min_area",
+      "min_faces",
+      "save_attempts",
+      "blur_confidence_filter",
+      "device",
+    ],
   },
 };
 

web/src/components/config-form/section-configs/ffmpeg.ts

@@ -116,7 +116,16 @@ const ffmpeg: SectionConfigOverrides = {
     },
   },
   global: {
-    restartRequired: [],
+    restartRequired: [
+      "path",
+      "global_args",
+      "hwaccel_args",
+      "input_args",
+      "output_args",
+      "retry_interval",
+      "apple_compatibility",
+      "gpu",
+    ],
     fieldOrder: [
       "hwaccel_args",
       "path",
@@ -153,7 +162,17 @@ const ffmpeg: SectionConfigOverrides = {
     fieldGroups: {
       cameraFfmpeg: ["input_args", "hwaccel_args", "output_args"],
     },
-    restartRequired: [],
+    restartRequired: [
+      "inputs",
+      "path",
+      "global_args",
+      "hwaccel_args",
+      "input_args",
+      "output_args",
+      "retry_interval",
+      "apple_compatibility",
+      "gpu",
+    ],
   },
 };
 

web/src/components/config-form/section-configs/lpr.ts

@@ -40,7 +40,21 @@ const lpr: SectionConfigOverrides = {
       "device",
       "replace_rules",
     ],
-    restartRequired: ["model_size", "enhancement", "device"],
+    restartRequired: [
+      "enabled",
+      "model_size",
+      "detection_threshold",
+      "min_area",
+      "recognition_threshold",
+      "min_plate_length",
+      "format",
+      "match_distance",
+      "known_plates",
+      "enhancement",
+      "debug_save_plates",
+      "device",
+      "replace_rules",
+    ],
     uiSchema: {
       format: {
         "ui:options": { size: "md" },

web/src/components/config-form/section-configs/motion.ts

@@ -3,18 +3,11 @@ import type { SectionConfigOverrides } from "./types";
 const motion: SectionConfigOverrides = {
   base: {
     sectionDocs: "/configuration/motion_detection",
-    fieldDocs: {
-      lightning_threshold:
-        "/configuration/motion_detection#lightning_threshold",
-      skip_motion_threshold:
-        "/configuration/motion_detection#skip_motion_on_large_scene_changes",
-    },
     restartRequired: [],
     fieldOrder: [
       "enabled",
       "threshold",
       "lightning_threshold",
-      "skip_motion_threshold",
       "improve_contrast",
       "contour_area",
       "delta_alpha",
@@ -26,20 +19,9 @@ const motion: SectionConfigOverrides = {
       sensitivity: ["enabled", "threshold", "contour_area"],
       algorithm: ["improve_contrast", "delta_alpha", "frame_alpha"],
     },
-    uiSchema: {
-      skip_motion_threshold: {
-        "ui:widget": "optionalField",
-        "ui:options": {
-          innerWidget: "range",
-          step: 0.05,
-          suppressMultiSchema: true,
-        },
-      },
-    },
     hiddenFields: ["enabled_in_config", "mask", "raw_mask"],
     advancedFields: [
       "lightning_threshold",
-      "skip_motion_threshold",
       "delta_alpha",
       "frame_alpha",
       "frame_height",
@@ -47,7 +29,17 @@ const motion: SectionConfigOverrides = {
     ],
   },
   global: {
-    restartRequired: ["frame_height"],
+    restartRequired: [
+      "enabled",
+      "threshold",
+      "lightning_threshold",
+      "improve_contrast",
+      "contour_area",
+      "delta_alpha",
+      "frame_alpha",
+      "frame_height",
+      "mqtt_off_delay",
+    ],
   },
   camera: {
     restartRequired: ["frame_height"],
@@ -74,7 +66,7 @@ const motion: SectionConfigOverrides = {
       "frame_alpha",
       "frame_height",
     ],
-    advancedFields: ["lightning_threshold", "skip_motion_threshold"],
+    advancedFields: ["lightning_threshold"],
   },
 };
 

web/src/components/config-form/section-configs/objects.ts

@@ -83,7 +83,7 @@ const objects: SectionConfigOverrides = {
     },
   },
   global: {
-    restartRequired: [],
+    restartRequired: ["track", "alert", "detect", "filters", "genai"],
     hiddenFields: [
       "enabled_in_config",
       "mask",

web/src/components/config-form/section-configs/record.ts

@@ -29,7 +29,16 @@ const record: SectionConfigOverrides = {
     },
   },
   global: {
-    restartRequired: [],
+    restartRequired: [
+      "enabled",
+      "expire_interval",
+      "continuous",
+      "motion",
+      "alerts",
+      "detections",
+      "preview",
+      "export",
+    ],
   },
   camera: {
     restartRequired: [],

web/src/components/config-form/section-configs/review.ts

@@ -44,7 +44,7 @@ const review: SectionConfigOverrides = {
     },
   },
   global: {
-    restartRequired: [],
+    restartRequired: ["alerts", "detections", "genai"],
   },
   camera: {
     restartRequired: [],

web/src/components/config-form/section-configs/snapshots.ts

@@ -27,7 +27,14 @@ const snapshots: SectionConfigOverrides = {
     },
   },
   global: {
-    restartRequired: [],
+    restartRequired: [
+      "enabled",
+      "bounding_box",
+      "crop",
+      "quality",
+      "timestamp",
+      "retain",
+    ],
     hiddenFields: ["enabled_in_config", "required_zones"],
   },
   camera: {

web/src/components/config-form/section-configs/telemetry.ts

@@ -3,7 +3,14 @@ import type { SectionConfigOverrides } from "./types";
 const telemetry: SectionConfigOverrides = {
   base: {
     sectionDocs: "/configuration/reference",
-    restartRequired: ["version_check"],
+    restartRequired: [
+      "network_interfaces",
+      "stats.amd_gpu_stats",
+      "stats.intel_gpu_stats",
+      "stats.intel_gpu_device",
+      "stats.network_bandwidth",
+      "version_check",
+    ],
     fieldOrder: ["network_interfaces", "stats", "version_check"],
     advancedFields: [],
   },

web/src/components/config-form/sections/BaseSection.tsx

@@ -56,7 +56,6 @@ import ActivityIndicator from "@/components/indicators/activity-indicator";
 import { StatusBarMessagesContext } from "@/context/statusbar-provider";
 import {
   cameraUpdateTopicMap,
-  globalCameraDefaultSections,
   buildOverrides,
   buildConfigDataForPath,
   sanitizeSectionData as sharedSanitizeSectionData,
@@ -235,10 +234,7 @@ export function ConfigSection({
       ? cameraUpdateTopicMap[sectionPath]
         ? `config/cameras/${cameraName}/${cameraUpdateTopicMap[sectionPath]}`
         : undefined
-      : globalCameraDefaultSections.has(sectionPath) &&
-          cameraUpdateTopicMap[sectionPath]
-        ? `config/cameras/*/${cameraUpdateTopicMap[sectionPath]}`
-        : `config/${sectionPath}`;
+      : `config/${sectionPath}`;
   // Default: show title for camera level (since it might be collapsible), hide for global
   const shouldShowTitle = showTitle ?? effectiveLevel === "camera";
 
@@ -831,7 +827,7 @@ export function ConfigSection({
 
       <div
         className={cn(
-          "w-full border-t border-secondary bg-background pt-0",
+          "w-full border-t border-secondary bg-background pb-5 pt-0",
           !noStickyButtons && "sticky bottom-0 z-50",
         )}
       >

web/src/components/config-form/theme/frigateTheme.ts

@@ -26,7 +26,6 @@ import { FfmpegArgsWidget } from "./widgets/FfmpegArgsWidget";
 import { InputRolesWidget } from "./widgets/InputRolesWidget";
 import { TimezoneSelectWidget } from "./widgets/TimezoneSelectWidget";
 import { CameraPathWidget } from "./widgets/CameraPathWidget";
-import { OptionalFieldWidget } from "./widgets/OptionalFieldWidget";
 
 import { FieldTemplate } from "./templates/FieldTemplate";
 import { ObjectFieldTemplate } from "./templates/ObjectFieldTemplate";
@@ -74,7 +73,6 @@ export const frigateTheme: FrigateTheme = {
     audioLabels: AudioLabelSwitchesWidget,
     zoneNames: ZoneSwitchesWidget,
     timezoneSelect: TimezoneSelectWidget,
-    optionalField: OptionalFieldWidget,
   },
   templates: {
     FieldTemplate: FieldTemplate as React.ComponentType<FieldTemplateProps>,

web/src/components/config-form/theme/widgets/OptionalFieldWidget.tsx

@@ -1,64 +0,0 @@
-// Optional Field Widget - wraps any inner widget with an enable/disable switch
-// Used for nullable fields where None means "disabled" (not the same as 0)
-
-import type { WidgetProps } from "@rjsf/utils";
-import { getWidget } from "@rjsf/utils";
-import { Switch } from "@/components/ui/switch";
-import { cn } from "@/lib/utils";
-import { getNonNullSchema } from "../fields/nullableUtils";
-
-export function OptionalFieldWidget(props: WidgetProps) {
-  const { id, value, disabled, readonly, onChange, schema, options, registry } =
-    props;
-
-  const innerWidgetName = (options.innerWidget as string) || undefined;
-  const isEnabled = value !== undefined && value !== null;
-
-  // Extract the non-null branch from anyOf [Type, null]
-  const innerSchema = getNonNullSchema(schema) ?? schema;
-
-  const InnerWidget = getWidget(innerSchema, innerWidgetName, registry.widgets);
-
-  const getDefaultValue = () => {
-    if (innerSchema.default !== undefined && innerSchema.default !== null) {
-      return innerSchema.default;
-    }
-    if (innerSchema.minimum !== undefined) {
-      return innerSchema.minimum;
-    }
-    if (innerSchema.type === "integer" || innerSchema.type === "number") {
-      return 0;
-    }
-    if (innerSchema.type === "string") {
-      return "";
-    }
-    return 0;
-  };
-
-  const handleToggle = (checked: boolean) => {
-    onChange(checked ? getDefaultValue() : undefined);
-  };
-
-  const innerProps: WidgetProps = {
-    ...props,
-    schema: innerSchema,
-    disabled: disabled || readonly || !isEnabled,
-    value: isEnabled ? value : getDefaultValue(),
-  };
-
-  return (
-    <div className="flex items-center gap-3">
-      <Switch
-        id={`${id}-toggle`}
-        checked={isEnabled}
-        disabled={disabled || readonly}
-        onCheckedChange={handleToggle}
-      />
-      <div
-        className={cn("flex-1", !isEnabled && "pointer-events-none opacity-40")}
-      >
-        <InnerWidget {...innerProps} />
-      </div>
-    </div>
-  );
-}

web/src/components/overlay/ActionsDropdown.tsx

@@ -20,7 +20,7 @@ export default function ActionsDropdown({
   const { t } = useTranslation(["components/dialog", "views/replay", "common"]);
 
   return (
-    <DropdownMenu modal={false}>
+    <DropdownMenu>
       <DropdownMenuTrigger asChild>
         <Button
           className="flex items-center gap-2"

web/src/components/overlay/detail/AnnotationOffsetSlider.tsx

@@ -7,16 +7,10 @@ import axios from "axios";
 import { useSWRConfig } from "swr";
 import { toast } from "sonner";
 import { Trans, useTranslation } from "react-i18next";
-import { LuExternalLink, LuInfo, LuMinus, LuPlus } from "react-icons/lu";
+import { LuInfo } from "react-icons/lu";
 import { cn } from "@/lib/utils";
 import { isMobile } from "react-device-detect";
 import { useIsAdmin } from "@/hooks/use-is-admin";
-import { useDocDomain } from "@/hooks/use-doc-domain";
-import { Link } from "react-router-dom";
-
-const OFFSET_MIN = -2500;
-const OFFSET_MAX = 2500;
-const OFFSET_STEP = 50;
 
 type Props = {
   className?: string;
@@ -25,7 +19,6 @@ type Props = {
 export default function AnnotationOffsetSlider({ className }: Props) {
   const { annotationOffset, setAnnotationOffset, camera } = useDetailStream();
   const isAdmin = useIsAdmin();
-  const { getLocaleDocUrl } = useDocDomain();
   const { mutate } = useSWRConfig();
   const { t } = useTranslation(["views/explore"]);
   const [isSaving, setIsSaving] = useState(false);
@@ -39,16 +32,6 @@ export default function AnnotationOffsetSlider({ className }: Props) {
     [setAnnotationOffset],
   );
 
-  const stepOffset = useCallback(
-    (delta: number) => {
-      setAnnotationOffset((prev) => {
-        const next = prev + delta;
-        return Math.max(OFFSET_MIN, Math.min(OFFSET_MAX, next));
-      });
-    },
-    [setAnnotationOffset],
-  );
-
   const reset = useCallback(() => {
     setAnnotationOffset(0);
   }, [setAnnotationOffset]);
@@ -89,18 +72,11 @@ export default function AnnotationOffsetSlider({ className }: Props) {
   return (
     <div
       className={cn(
-        "flex flex-col gap-1.5",
+        "flex flex-col gap-0.5",
         isMobile && "landscape:gap-3",
         className,
       )}
     >
-      <div className="flex items-center gap-2 text-sm">
-        <span>{t("trackingDetails.annotationSettings.offset.label")}:</span>
-        <span className="font-mono tabular-nums text-primary-variant">
-          {annotationOffset > 0 ? "+" : ""}
-          {annotationOffset}ms
-        </span>
-      </div>
       <div
         className={cn(
           "flex items-center gap-3",
@@ -108,81 +84,57 @@ export default function AnnotationOffsetSlider({ className }: Props) {
             "landscape:flex-col landscape:items-start landscape:gap-4",
         )}
       >
-        <Button
-          type="button"
-          variant="outline"
-          size="icon"
-          className="size-8 shrink-0"
-          aria-label="-50ms"
-          onClick={() => stepOffset(-OFFSET_STEP)}
-          disabled={annotationOffset <= OFFSET_MIN}
-        >
-          <LuMinus className="size-4" />
-        </Button>
+        <div className="flex max-w-28 flex-row items-center gap-2 text-sm md:max-w-48">
+          <span className="max-w-24 md:max-w-44">
+            {t("trackingDetails.annotationSettings.offset.label")}:
+          </span>
+          <span className="text-primary-variant">{annotationOffset}</span>
+        </div>
         <div className="w-full flex-1 landscape:flex">
           <Slider
             value={[annotationOffset]}
-            min={OFFSET_MIN}
-            max={OFFSET_MAX}
-            step={OFFSET_STEP}
+            min={-2500}
+            max={2500}
+            step={50}
             onValueChange={handleChange}
           />
         </div>
-        <Button
-          type="button"
-          variant="outline"
-          size="icon"
-          className="size-8 shrink-0"
-          aria-label="+50ms"
-          onClick={() => stepOffset(OFFSET_STEP)}
-          disabled={annotationOffset >= OFFSET_MAX}
-        >
-          <LuPlus className="size-4" />
-        </Button>
+        <div className="flex items-center gap-2">
+          <Button size="sm" variant="ghost" onClick={reset}>
+            {t("button.reset", { ns: "common" })}
+          </Button>
+          {isAdmin && (
+            <Button size="sm" onClick={save} disabled={isSaving}>
+              {isSaving
+                ? t("button.saving", { ns: "common" })
+                : t("button.save", { ns: "common" })}
+            </Button>
+          )}
+        </div>
       </div>
-      <div className="flex items-start gap-1.5 text-xs text-muted-foreground">
+      <div
+        className={cn(
+          "flex items-center gap-2 text-xs text-muted-foreground",
+          isMobile && "landscape:flex-col landscape:items-start",
+        )}
+      >
         <Trans ns="views/explore">
           trackingDetails.annotationSettings.offset.millisecondsToOffset
         </Trans>
         <Popover>
           <PopoverTrigger asChild>
             <button
-              className="mt-px shrink-0 focus:outline-none"
+              className="focus:outline-none"
               aria-label={t("trackingDetails.annotationSettings.offset.tips")}
             >
-              <LuInfo className="size-3.5" />
+              <LuInfo className="size-4" />
             </button>
           </PopoverTrigger>
           <PopoverContent className="w-80 text-sm">
             {t("trackingDetails.annotationSettings.offset.tips")}
-            <div className="mt-2 flex items-center text-primary-variant">
-              <Link
-                to={getLocaleDocUrl(
-                  "troubleshooting/dummy-camera#annotation-offset",
-                )}
-                target="_blank"
-                rel="noopener noreferrer"
-                className="inline"
-              >
-                {t("readTheDocumentation", { ns: "common" })}
-                <LuExternalLink className="ml-2 inline-flex size-3" />
-              </Link>
-            </div>
           </PopoverContent>
         </Popover>
       </div>
-      <div className="flex items-center justify-end gap-2">
-        <Button size="sm" variant="ghost" onClick={reset}>
-          {t("button.reset", { ns: "common" })}
-        </Button>
-        {isAdmin && (
-          <Button size="sm" onClick={save} disabled={isSaving}>
-            {isSaving
-              ? t("button.saving", { ns: "common" })
-              : t("button.save", { ns: "common" })}
-          </Button>
-        )}
-      </div>
     </div>
   );
 }

web/src/components/overlay/detail/AnnotationSettingsPane.tsx

@@ -1,23 +1,31 @@
 import { Event } from "@/types/event";
 import { FrigateConfig } from "@/types/frigateConfig";
+import { zodResolver } from "@hookform/resolvers/zod";
 import axios from "axios";
 import { useCallback, useState } from "react";
-import { LuExternalLink, LuMinus, LuPlus } from "react-icons/lu";
+import { useForm } from "react-hook-form";
+import { LuExternalLink } from "react-icons/lu";
 import { Link } from "react-router-dom";
 import { toast } from "sonner";
 import useSWR from "swr";
+import {
+  Form,
+  FormControl,
+  FormDescription,
+  FormField,
+  FormItem,
+  FormLabel,
+  FormMessage,
+} from "@/components/ui/form";
+import { z } from "zod";
 import { Button } from "@/components/ui/button";
 import ActivityIndicator from "@/components/indicators/activity-indicator";
+import { Input } from "@/components/ui/input";
 import { Separator } from "@/components/ui/separator";
-import { Slider } from "@/components/ui/slider";
 import { Trans, useTranslation } from "react-i18next";
 import { useDocDomain } from "@/hooks/use-doc-domain";
 import { useIsAdmin } from "@/hooks/use-is-admin";
 
-const OFFSET_MIN = -2500;
-const OFFSET_MAX = 2500;
-const OFFSET_STEP = 50;
-
 type AnnotationSettingsPaneProps = {
   event: Event;
   annotationOffset: number;
@@ -37,69 +45,93 @@ export function AnnotationSettingsPane({
 
   const [isLoading, setIsLoading] = useState(false);
 
-  const handleSliderChange = useCallback(
-    (values: number[]) => {
-      if (!values || values.length === 0) return;
-      setAnnotationOffset(values[0]);
+  const formSchema = z.object({
+    annotationOffset: z.coerce.number().optional().or(z.literal("")),
+  });
+
+  const form = useForm<z.infer<typeof formSchema>>({
+    resolver: zodResolver(formSchema),
+    mode: "onChange",
+    defaultValues: {
+      annotationOffset: annotationOffset,
     },
-    [setAnnotationOffset],
-  );
+  });
 
-  const stepOffset = useCallback(
-    (delta: number) => {
-      setAnnotationOffset((prev) => {
-        const next = prev + delta;
-        return Math.max(OFFSET_MIN, Math.min(OFFSET_MAX, next));
-      });
-    },
-    [setAnnotationOffset],
-  );
-
-  const reset = useCallback(() => {
-    setAnnotationOffset(0);
-  }, [setAnnotationOffset]);
-
-  const saveToConfig = useCallback(async () => {
-    if (!config || !event) return;
-
-    setIsLoading(true);
-    try {
-      const res = await axios.put(
-        `config/set?cameras.${event.camera}.detect.annotation_offset=${annotationOffset}`,
-        { requires_restart: 0 },
-      );
-      if (res.status === 200) {
-        toast.success(
-          t("trackingDetails.annotationSettings.offset.toast.success", {
-            camera: event.camera,
-          }),
-          { position: "top-center" },
-        );
-        updateConfig();
-      } else {
-        toast.error(
-          t("toast.save.error.title", {
-            errorMessage: res.statusText,
-            ns: "common",
-          }),
-          { position: "top-center" },
-        );
+  const saveToConfig = useCallback(
+    async (annotation_offset: number | string) => {
+      if (!config || !event) {
+        return;
       }
-    } catch (error: unknown) {
-      const err = error as {
-        response?: { data?: { message?: string; detail?: string } };
-      };
-      const errorMessage =
-        err?.response?.data?.message ||
-        err?.response?.data?.detail ||
-        "Unknown error";
-      toast.error(t("toast.save.error.title", { errorMessage, ns: "common" }), {
-        position: "top-center",
-      });
-    } finally {
-      setIsLoading(false);
+
+      axios
+        .put(
+          `config/set?cameras.${event?.camera}.detect.annotation_offset=${annotation_offset}`,
+          {
+            requires_restart: 0,
+          },
+        )
+        .then((res) => {
+          if (res.status === 200) {
+            toast.success(
+              t("trackingDetails.annotationSettings.offset.toast.success", {
+                camera: event?.camera,
+              }),
+              {
+                position: "top-center",
+              },
+            );
+            updateConfig();
+          } else {
+            toast.error(
+              t("toast.save.error.title", {
+                errorMessage: res.statusText,
+                ns: "common",
+              }),
+              {
+                position: "top-center",
+              },
+            );
+          }
+        })
+        .catch((error) => {
+          const errorMessage =
+            error.response?.data?.message ||
+            error.response?.data?.detail ||
+            "Unknown error";
+          toast.error(
+            t("toast.save.error.title", { errorMessage, ns: "common" }),
+            {
+              position: "top-center",
+            },
+          );
+        })
+        .finally(() => {
+          setIsLoading(false);
+        });
+    },
+    [updateConfig, config, event, t],
+  );
+
+  function onSubmit(values: z.infer<typeof formSchema>) {
+    if (!values || values.annotationOffset == null || !config) {
+      return;
     }
-  }, [annotationOffset, config, event, updateConfig, t]);
+    setIsLoading(true);
+
+    saveToConfig(values.annotationOffset);
+  }
+
+  function onApply(values: z.infer<typeof formSchema>) {
+    if (
+      !values ||
+      values.annotationOffset === null ||
+      values.annotationOffset === "" ||
+      !config
+    ) {
+      return;
+    }
+    setAnnotationOffset(values.annotationOffset ?? 0);
+  }
 
   return (
     <div className="p-4">
@@ -108,100 +140,91 @@ export function AnnotationSettingsPane({
       </div>
 
       <Separator className="mb-4 flex bg-secondary" />
-
-      <div className="flex flex-col gap-4">
-        <div className="flex flex-col gap-1">
-          <div className="text-sm font-medium">
-            {t("trackingDetails.annotationSettings.offset.label")}
-          </div>
-          <div className="text-sm text-muted-foreground">
-            <Trans ns="views/explore">
-              trackingDetails.annotationSettings.offset.millisecondsToOffset
-            </Trans>
-          </div>
-        </div>
-
-        <div className="flex items-center gap-3">
-          <Button
-            type="button"
-            variant="outline"
-            size="icon"
-            className="size-8 shrink-0"
-            aria-label="-50ms"
-            onClick={() => stepOffset(-OFFSET_STEP)}
-            disabled={annotationOffset <= OFFSET_MIN}
-          >
-            <LuMinus className="size-4" />
-          </Button>
-          <Slider
-            value={[annotationOffset]}
-            min={OFFSET_MIN}
-            max={OFFSET_MAX}
-            step={OFFSET_STEP}
-            onValueChange={handleSliderChange}
-            className="flex-1"
-          />
-          <Button
-            type="button"
-            variant="outline"
-            size="icon"
-            className="size-8 shrink-0"
-            aria-label="+50ms"
-            onClick={() => stepOffset(OFFSET_STEP)}
-            disabled={annotationOffset >= OFFSET_MAX}
-          >
-            <LuPlus className="size-4" />
-          </Button>
-        </div>
-
-        <div className="flex items-center justify-between">
-          <span className="font-mono text-sm tabular-nums text-primary-variant">
-            {annotationOffset > 0 ? "+" : ""}
-            {annotationOffset}ms
-          </span>
-          <Button type="button" variant="ghost" size="sm" onClick={reset}>
-            {t("button.reset", { ns: "common" })}
-          </Button>
-        </div>
-
-        <div className="text-sm text-secondary-foreground">
-          {t("trackingDetails.annotationSettings.offset.tips")}
-          <div className="mt-2 flex items-center text-primary-variant">
-            <Link
-              to={getLocaleDocUrl(
-                "troubleshooting/dummy-camera#annotation-offset",
-              )}
-              target="_blank"
-              rel="noopener noreferrer"
-              className="inline"
-            >
-              {t("readTheDocumentation", { ns: "common" })}
-              <LuExternalLink className="ml-2 inline-flex size-3" />
-            </Link>
-          </div>
-        </div>
-
-        {isAdmin && (
-          <>
-            <Separator className="bg-secondary" />
-            <Button
-              variant="select"
-              aria-label={t("button.save", { ns: "common" })}
-              disabled={isLoading}
-              onClick={saveToConfig}
-            >
-              {isLoading ? (
-                <div className="flex flex-row items-center gap-2">
-                  <ActivityIndicator />
-                  <span>{t("button.saving", { ns: "common" })}</span>
+      <Form {...form}>
+        <form
+          onSubmit={form.handleSubmit(onSubmit)}
+          className="flex flex-1 flex-col space-y-3"
+        >
+          <FormField
+            control={form.control}
+            name="annotationOffset"
+            render={({ field }) => (
+              <>
+                <FormItem className="flex flex-row items-start justify-between space-x-2">
+                  <div className="flex flex-col gap-1">
+                    <FormLabel>
+                      {t("trackingDetails.annotationSettings.offset.label")}
+                    </FormLabel>
+                    <FormDescription>
+                      <Trans ns="views/explore">
+                        trackingDetails.annotationSettings.offset.millisecondsToOffset
+                      </Trans>
+                      <FormMessage />
+                    </FormDescription>
+                  </div>
+                  <div className="flex flex-col gap-3">
+                    <div className="min-w-24">
+                      <FormControl>
+                        <Input
+                          className="text-md w-full border border-input bg-background p-2 text-center hover:bg-accent hover:text-accent-foreground dark:[color-scheme:dark]"
+                          placeholder="0"
+                          {...field}
+                        />
+                      </FormControl>
+                    </div>
+                  </div>
+                </FormItem>
+                <div className="mt-1 text-sm text-secondary-foreground">
+                  {t("trackingDetails.annotationSettings.offset.tips")}
+                  <div className="mt-2 flex items-center text-primary-variant">
+                    <Link
+                      to={getLocaleDocUrl("configuration/reference")}
+                      target="_blank"
+                      rel="noopener noreferrer"
+                      className="inline"
+                    >
+                      {t("readTheDocumentation", { ns: "common" })}
+                      <LuExternalLink className="ml-2 inline-flex size-3" />
+                    </Link>
+                  </div>
                 </div>
-              ) : (
-                t("button.save", { ns: "common" })
+              </>
+            )}
+          />
+
+          <div className="flex flex-1 flex-col justify-end">
+            <div className="flex flex-row gap-2 pt-5">
+              <Button
+                className="flex flex-1"
+                variant="default"
+                aria-label={t("button.apply", { ns: "common" })}
+                type="button"
+                onClick={form.handleSubmit(onApply)}
+              >
+                {t("button.apply", { ns: "common" })}
+              </Button>
+              {isAdmin && (
+                <Button
+                  variant="select"
+                  aria-label={t("button.save", { ns: "common" })}
+                  disabled={isLoading}
+                  className="flex flex-1"
+                  type="submit"
+                >
+                  {isLoading ? (
+                    <div className="flex flex-row items-center gap-2">
+                      <ActivityIndicator />
+                      <span>{t("button.saving", { ns: "common" })}</span>
+                    </div>
+                  ) : (
+                    t("button.save", { ns: "common" })
+                  )}
+                </Button>
               )}
-            </Button>
-          </>
-        )}
-      </div>
+            </div>
+          </div>
+        </form>
+      </Form>
     </div>
   );
 }

web/src/components/overlay/detail/SearchDetailDialog.tsx

@@ -323,7 +323,6 @@ function DialogContentComponent({
       <TrackingDetails
         className={cn(isDesktop ? "size-full" : "flex flex-col gap-4")}
         event={search as unknown as Event}
-        isAnnotationSettingsOpen={isPopoverOpen}
         tabs={
           isDesktop ? (
             <TabsWithActions
@@ -496,15 +495,6 @@ export default function SearchDetailDialog({
     }
   }, [search]);
 
-  useEffect(() => {
-    if (!isDesktop || !onPrevious || !onNext) {
-      setShowNavigationButtons(false);
-      return;
-    }
-
-    setShowNavigationButtons(isOpen);
-  }, [isOpen, onNext, onPrevious]);
-
   // show/hide annotation settings is handled inside TabsWithActions
 
   const searchTabs = useMemo(() => {

web/src/components/overlay/detail/TrackingDetails.tsx

@@ -47,14 +47,12 @@ type TrackingDetailsProps = {
   event: Event;
   fullscreen?: boolean;
   tabs?: React.ReactNode;
-  isAnnotationSettingsOpen?: boolean;
 };
 
 export function TrackingDetails({
   className,
   event,
   tabs,
-  isAnnotationSettingsOpen = false,
 }: TrackingDetailsProps) {
   const videoRef = useRef<HTMLVideoElement | null>(null);
   const { t } = useTranslation(["views/explore"]);
@@ -71,14 +69,6 @@ export function TrackingDetails({
   // user (eg, clicking a lifecycle row). When null we display `currentTime`.
   const [manualOverride, setManualOverride] = useState<number | null>(null);
 
-  // Capture the annotation offset used for building the video source URL.
-  // This only updates when the event changes, NOT on every slider drag,
-  // so the HLS player doesn't reload while the user is adjusting the offset.
-  const sourceOffsetRef = useRef(annotationOffset);
-  useEffect(() => {
-    sourceOffsetRef.current = annotationOffset;
-  }, [event.id]); // eslint-disable-line react-hooks/exhaustive-deps
-
   // event.start_time is detect time, convert to record, then subtract padding
   const [currentTime, setCurrentTime] = useState(
     (event.start_time ?? 0) + annotationOffset / 1000 - REVIEW_PADDING,
@@ -100,19 +90,14 @@ export function TrackingDetails({
 
   const { data: config } = useSWR<FrigateConfig>("config");
 
-  // Fetch recording segments for the event's time range to handle motion-only gaps.
-  // Use the source offset (stable per event) so recordings don't refetch on every
-  // slider drag while adjusting annotation offset.
+  // Fetch recording segments for the event's time range to handle motion-only gaps
   const eventStartRecord = useMemo(
-    () => (event.start_time ?? 0) + sourceOffsetRef.current / 1000,
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-    [event.start_time, event.id],
+    () => (event.start_time ?? 0) + annotationOffset / 1000,
+    [event.start_time, annotationOffset],
   );
   const eventEndRecord = useMemo(
-    () =>
-      (event.end_time ?? Date.now() / 1000) + sourceOffsetRef.current / 1000,
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-    [event.end_time, event.id],
+    () => (event.end_time ?? Date.now() / 1000) + annotationOffset / 1000,
+    [event.end_time, annotationOffset],
   );
 
   const { data: recordings } = useSWR<Recording[]>(
@@ -313,53 +298,6 @@ export function TrackingDetails({
     setSelectedObjectIds([event.id]);
   }, [event.id, setSelectedObjectIds]);
 
-  // When the annotation settings popover is open, pin the video to a specific
-  // lifecycle event (detect-stream timestamp). As the user drags the offset
-  // slider, the video re-seeks to show the recording frame at
-  // pinnedTimestamp + newOffset, while the bounding box stays fixed at the
-  // pinned detect timestamp. This lets the user visually align the box to
-  // the car in the video.
-  const pinnedDetectTimestampRef = useRef<number | null>(null);
-  const wasAnnotationOpenRef = useRef(false);
-
-  // On popover open: pause, pin first lifecycle item, and seek.
-  useEffect(() => {
-    if (isAnnotationSettingsOpen && !wasAnnotationOpenRef.current) {
-      if (videoRef.current && displaySource === "video") {
-        videoRef.current.pause();
-      }
-      if (eventSequence && eventSequence.length > 0) {
-        pinnedDetectTimestampRef.current = eventSequence[0].timestamp;
-      }
-    }
-    if (!isAnnotationSettingsOpen) {
-      pinnedDetectTimestampRef.current = null;
-    }
-    wasAnnotationOpenRef.current = isAnnotationSettingsOpen;
-  }, [isAnnotationSettingsOpen, displaySource, eventSequence]);
-
-  // When the pinned timestamp or offset changes, re-seek the video and
-  // explicitly update currentTime so the overlay shows the pinned event's box.
-  useEffect(() => {
-    const pinned = pinnedDetectTimestampRef.current;
-    if (!isAnnotationSettingsOpen || pinned == null) return;
-    if (!videoRef.current || displaySource !== "video") return;
-
-    const targetTimeRecord = pinned + annotationOffset / 1000;
-    const relativeTime = timestampToVideoTime(targetTimeRecord);
-    videoRef.current.currentTime = relativeTime;
-
-    // Explicitly update currentTime state so the overlay's effectiveCurrentTime
-    // resolves back to the pinned detect timestamp:
-    //   effectiveCurrentTime = targetTimeRecord - annotationOffset/1000 = pinned
-    setCurrentTime(targetTimeRecord);
-  }, [
-    isAnnotationSettingsOpen,
-    annotationOffset,
-    displaySource,
-    timestampToVideoTime,
-  ]);
-
   const handleLifecycleClick = useCallback(
     (item: TrackingDetailsSequence) => {
       if (!videoRef.current && !imgRef.current) return;
@@ -515,23 +453,19 @@ export function TrackingDetails({
 
   const videoSource = useMemo(() => {
     // event.start_time and event.end_time are in DETECT stream time
-    // Convert to record stream time, then create video clip with padding.
-    // Use sourceOffsetRef (stable per event) so the HLS player doesn't
-    // reload while the user is dragging the annotation offset slider.
-    const sourceOffset = sourceOffsetRef.current;
-    const eventStartRec = event.start_time + sourceOffset / 1000;
-    const eventEndRec =
-      (event.end_time ?? Date.now() / 1000) + sourceOffset / 1000;
-    const startTime = eventStartRec - REVIEW_PADDING;
-    const endTime = eventEndRec + REVIEW_PADDING;
+    // Convert to record stream time, then create video clip with padding
+    const eventStartRecord = event.start_time + annotationOffset / 1000;
+    const eventEndRecord =
+      (event.end_time ?? Date.now() / 1000) + annotationOffset / 1000;
+    const startTime = eventStartRecord - REVIEW_PADDING;
+    const endTime = eventEndRecord + REVIEW_PADDING;
     const playlist = `${baseUrl}vod/clip/${event.camera}/start/${startTime}/end/${endTime}/index.m3u8`;
 
     return {
       playlist,
       startPosition: 0,
     };
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [event]);
+  }, [event, annotationOffset]);
 
   // Determine camera aspect ratio category
   const cameraAspect = useMemo(() => {

web/src/components/overlay/dialog/DeleteCameraDialog.tsx

@@ -1,215 +0,0 @@
-import { useCallback, useState } from "react";
-import { useTranslation } from "react-i18next";
-import { Trans } from "react-i18next";
-import axios from "axios";
-import { toast } from "sonner";
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogFooter,
-  DialogHeader,
-  DialogTitle,
-} from "@/components/ui/dialog";
-import { Button } from "@/components/ui/button";
-import {
-  Select,
-  SelectContent,
-  SelectItem,
-  SelectTrigger,
-  SelectValue,
-} from "@/components/ui/select";
-import { Label } from "@/components/ui/label";
-import ActivityIndicator from "@/components/indicators/activity-indicator";
-import { Switch } from "@/components/ui/switch";
-
-type DeleteCameraDialogProps = {
-  show: boolean;
-  cameras: string[];
-  onClose: () => void;
-  onDeleted: () => void;
-};
-
-export default function DeleteCameraDialog({
-  show,
-  cameras,
-  onClose,
-  onDeleted,
-}: DeleteCameraDialogProps) {
-  const { t } = useTranslation(["views/settings", "common"]);
-  const [phase, setPhase] = useState<"select" | "confirm">("select");
-  const [selectedCamera, setSelectedCamera] = useState<string>("");
-  const [deleteExports, setDeleteExports] = useState(false);
-  const [isDeleting, setIsDeleting] = useState(false);
-
-  const handleClose = useCallback(() => {
-    if (isDeleting) return;
-    setPhase("select");
-    setSelectedCamera("");
-    setDeleteExports(false);
-    onClose();
-  }, [isDeleting, onClose]);
-
-  const handleDelete = useCallback(() => {
-    setPhase("confirm");
-  }, []);
-
-  const handleBack = useCallback(() => {
-    setPhase("select");
-  }, []);
-
-  const handleConfirmDelete = useCallback(async () => {
-    if (!selectedCamera || isDeleting) return;
-
-    setIsDeleting(true);
-
-    try {
-      await axios.delete(
-        `cameras/${selectedCamera}?delete_exports=${deleteExports}`,
-      );
-      toast.success(
-        t("cameraManagement.deleteCameraDialog.success", {
-          cameraName: selectedCamera,
-        }),
-        { position: "top-center" },
-      );
-      setPhase("select");
-      setSelectedCamera("");
-      setDeleteExports(false);
-      onDeleted();
-    } catch (error) {
-      const errorMessage =
-        axios.isAxiosError(error) &&
-        (error.response?.data?.message || error.response?.data?.detail)
-          ? error.response?.data?.message || error.response?.data?.detail
-          : t("cameraManagement.deleteCameraDialog.error", {
-              cameraName: selectedCamera,
-            });
-
-      toast.error(errorMessage, { position: "top-center" });
-    } finally {
-      setIsDeleting(false);
-    }
-  }, [selectedCamera, deleteExports, isDeleting, onDeleted, t]);
-
-  return (
-    <Dialog open={show} onOpenChange={handleClose}>
-      <DialogContent className="sm:max-w-[425px]">
-        {phase === "select" ? (
-          <>
-            <DialogHeader>
-              <DialogTitle>
-                {t("cameraManagement.deleteCameraDialog.title")}
-              </DialogTitle>
-              <DialogDescription>
-                {t("cameraManagement.deleteCameraDialog.description")}
-              </DialogDescription>
-            </DialogHeader>
-            <Select value={selectedCamera} onValueChange={setSelectedCamera}>
-              <SelectTrigger>
-                <SelectValue
-                  placeholder={t(
-                    "cameraManagement.deleteCameraDialog.selectPlaceholder",
-                  )}
-                />
-              </SelectTrigger>
-              <SelectContent>
-                {cameras.map((camera) => (
-                  <SelectItem key={camera} value={camera}>
-                    {camera}
-                  </SelectItem>
-                ))}
-              </SelectContent>
-            </Select>
-            <DialogFooter className="flex gap-3 sm:justify-end">
-              <div className="flex flex-1 flex-col justify-end">
-                <div className="flex flex-row gap-2 pt-5">
-                  <Button
-                    className="flex flex-1"
-                    aria-label={t("button.cancel", { ns: "common" })}
-                    onClick={handleClose}
-                    type="button"
-                  >
-                    {t("button.cancel", { ns: "common" })}
-                  </Button>
-                  <Button
-                    variant="destructive"
-                    aria-label={t("button.delete", { ns: "common" })}
-                    className="flex flex-1 text-white"
-                    onClick={handleDelete}
-                    disabled={!selectedCamera}
-                  >
-                    {t("button.delete", { ns: "common" })}
-                  </Button>
-                </div>
-              </div>
-            </DialogFooter>
-          </>
-        ) : (
-          <>
-            <DialogHeader>
-              <DialogTitle>
-                {t("cameraManagement.deleteCameraDialog.confirmTitle")}
-              </DialogTitle>
-              <DialogDescription>
-                <Trans
-                  ns="views/settings"
-                  values={{ cameraName: selectedCamera }}
-                  components={{ strong: <span className="font-medium" /> }}
-                >
-                  cameraManagement.deleteCameraDialog.confirmWarning
-                </Trans>
-              </DialogDescription>
-            </DialogHeader>
-            <div className="flex items-center space-x-2">
-              <Switch
-                id="delete-exports"
-                checked={deleteExports}
-                onCheckedChange={(checked) =>
-                  setDeleteExports(checked === true)
-                }
-              />
-              <Label htmlFor="delete-exports" className="cursor-pointer">
-                {t("cameraManagement.deleteCameraDialog.deleteExports")}
-              </Label>
-            </div>
-            <DialogFooter className="flex gap-3 sm:justify-end">
-              <div className="flex flex-1 flex-col justify-end">
-                <div className="flex flex-row gap-2 pt-5">
-                  <Button
-                    className="flex flex-1"
-                    aria-label={t("button.back", { ns: "common" })}
-                    onClick={handleBack}
-                    type="button"
-                    disabled={isDeleting}
-                  >
-                    {t("button.back", { ns: "common" })}
-                  </Button>
-                  <Button
-                    variant="destructive"
-                    className="flex flex-1 text-white"
-                    onClick={handleConfirmDelete}
-                    disabled={isDeleting}
-                  >
-                    {isDeleting ? (
-                      <div className="flex flex-row items-center gap-2">
-                        <ActivityIndicator />
-                        <span>
-                          {t(
-                            "cameraManagement.deleteCameraDialog.confirmButton",
-                          )}
-                        </span>
-                      </div>
-                    ) : (
-                      t("cameraManagement.deleteCameraDialog.confirmButton")
-                    )}
-                  </Button>
-                </div>
-              </div>
-            </DialogFooter>
-          </>
-        )}
-      </DialogContent>
-    </Dialog>
-  );
-}

web/src/components/player/HlsVideoPlayer.tsx

@@ -1,6 +1,5 @@
 import {
   MutableRefObject,
-  ReactNode,
   useCallback,
   useEffect,
   useRef,
@@ -58,7 +57,6 @@ type HlsVideoPlayerProps = {
   isDetailMode?: boolean;
   camera?: string;
   currentTimeOverride?: number;
-  transformedOverlay?: ReactNode;
 };
 
 export default function HlsVideoPlayer({
@@ -83,7 +81,6 @@ export default function HlsVideoPlayer({
   isDetailMode = false,
   camera,
   currentTimeOverride,
-  transformedOverlay,
 }: HlsVideoPlayerProps) {
   const { t } = useTranslation("components/player");
   const { data: config } = useSWR<FrigateConfig>("config");
@@ -353,162 +350,157 @@ export default function HlsVideoPlayer({
           height: isMobile ? "100%" : undefined,
         }}
       >
-        <div className="relative size-full">
-          {transformedOverlay}
-          {isDetailMode &&
-            camera &&
-            currentTime &&
-            loadedMetadata &&
-            videoDimensions.width > 0 &&
-            videoDimensions.height > 0 && (
-              <div
-                className={cn(
-                  "absolute inset-0 z-50",
-                  isDesktop
-                    ? "size-full"
-                    : "mx-auto flex items-center justify-center portrait:max-h-[50dvh]",
-                )}
-                style={{
-                  aspectRatio: `${videoDimensions.width} / ${videoDimensions.height}`,
-                }}
-              >
-                <ObjectTrackOverlay
-                  key={`overlay-${currentTime}`}
-                  camera={camera}
-                  showBoundingBoxes={!isPlaying}
-                  currentTime={currentTime}
-                  videoWidth={videoDimensions.width}
-                  videoHeight={videoDimensions.height}
-                  className="absolute inset-0 z-10"
-                  onSeekToTime={(timestamp, play) => {
-                    if (onSeekToTime) {
-                      onSeekToTime(timestamp, play);
-                    }
-                  }}
-                />
-              </div>
-            )}
-          <video
-            ref={videoRef}
-            className={`size-full rounded-lg bg-black md:rounded-2xl ${loadedMetadata ? "" : "invisible"} cursor-pointer`}
-            preload="auto"
-            autoPlay
-            controls={!frigateControls}
-            playsInline
-            muted={muted}
-            onClick={
-              isDesktop
-                ? () => {
-                    if (zoomScale == 1.0) onPlayPause(!isPlaying);
+        {isDetailMode &&
+          camera &&
+          currentTime &&
+          loadedMetadata &&
+          videoDimensions.width > 0 &&
+          videoDimensions.height > 0 && (
+            <div
+              className={cn(
+                "absolute inset-0 z-50",
+                isDesktop
+                  ? "size-full"
+                  : "mx-auto flex items-center justify-center portrait:max-h-[50dvh]",
+              )}
+              style={{
+                aspectRatio: `${videoDimensions.width} / ${videoDimensions.height}`,
+              }}
+            >
+              <ObjectTrackOverlay
+                key={`overlay-${currentTime}`}
+                camera={camera}
+                showBoundingBoxes={!isPlaying}
+                currentTime={currentTime}
+                videoWidth={videoDimensions.width}
+                videoHeight={videoDimensions.height}
+                className="absolute inset-0 z-10"
+                onSeekToTime={(timestamp, play) => {
+                  if (onSeekToTime) {
+                    onSeekToTime(timestamp, play);
                   }
-                : undefined
+                }}
+              />
+            </div>
+          )}
+        <video
+          ref={videoRef}
+          className={`size-full rounded-lg bg-black md:rounded-2xl ${loadedMetadata ? "" : "invisible"} cursor-pointer`}
+          preload="auto"
+          autoPlay
+          controls={!frigateControls}
+          playsInline
+          muted={muted}
+          onClick={
+            isDesktop
+              ? () => {
+                  if (zoomScale == 1.0) onPlayPause(!isPlaying);
+                }
+              : undefined
+          }
+          onVolumeChange={() => {
+            setVolume(videoRef.current?.volume ?? 1.0, true);
+            if (!frigateControls) {
+              setMuted(videoRef.current?.muted);
             }
-            onVolumeChange={() => {
-              setVolume(videoRef.current?.volume ?? 1.0, true);
-              if (!frigateControls) {
-                setMuted(videoRef.current?.muted);
-              }
-            }}
-            onPlay={() => {
-              setIsPlaying(true);
+          }}
+          onPlay={() => {
+            setIsPlaying(true);
 
-              if (isMobile) {
-                setControls(true);
-                setMobileCtrlTimeout(
-                  setTimeout(() => setControls(false), 4000),
-                );
-              }
-            }}
-            onPlaying={onPlaying}
-            onPause={() => {
-              setIsPlaying(false);
-              clearTimeout(bufferTimeout);
+            if (isMobile) {
+              setControls(true);
+              setMobileCtrlTimeout(setTimeout(() => setControls(false), 4000));
+            }
+          }}
+          onPlaying={onPlaying}
+          onPause={() => {
+            setIsPlaying(false);
+            clearTimeout(bufferTimeout);
 
-              if (isMobile && mobileCtrlTimeout) {
-                clearTimeout(mobileCtrlTimeout);
-              }
-            }}
-            onWaiting={() => {
-              if (onError != undefined) {
-                if (videoRef.current?.paused) {
-                  return;
-                }
-
-                setBufferTimeout(
-                  setTimeout(() => {
-                    if (
-                      document.visibilityState === "visible" &&
-                      videoRef.current
-                    ) {
-                      onError("stalled");
-                    }
-                  }, 3000),
-                );
-              }
-            }}
-            onProgress={() => {
-              if (onError != undefined) {
-                if (videoRef.current?.paused) {
-                  return;
-                }
-
-                if (bufferTimeout) {
-                  clearTimeout(bufferTimeout);
-                  setBufferTimeout(undefined);
-                }
-              }
-            }}
-            onTimeUpdate={() => {
-              if (!onTimeUpdate) {
+            if (isMobile && mobileCtrlTimeout) {
+              clearTimeout(mobileCtrlTimeout);
+            }
+          }}
+          onWaiting={() => {
+            if (onError != undefined) {
+              if (videoRef.current?.paused) {
                 return;
               }
 
-              const frameTime = getVideoTime();
-
-              if (frameTime) {
-                onTimeUpdate(frameTime);
+              setBufferTimeout(
+                setTimeout(() => {
+                  if (
+                    document.visibilityState === "visible" &&
+                    videoRef.current
+                  ) {
+                    onError("stalled");
+                  }
+                }, 3000),
+              );
+            }
+          }}
+          onProgress={() => {
+            if (onError != undefined) {
+              if (videoRef.current?.paused) {
+                return;
               }
-            }}
-            onLoadedData={() => {
-              onPlayerLoaded?.();
-              handleLoadedMetadata();
 
-              if (videoRef.current) {
-                if (playbackRate) {
-                  videoRef.current.playbackRate = playbackRate;
-                }
+              if (bufferTimeout) {
+                clearTimeout(bufferTimeout);
+                setBufferTimeout(undefined);
+              }
+            }
+          }}
+          onTimeUpdate={() => {
+            if (!onTimeUpdate) {
+              return;
+            }
 
-                if (volume) {
-                  videoRef.current.volume = volume;
-                }
+            const frameTime = getVideoTime();
+
+            if (frameTime) {
+              onTimeUpdate(frameTime);
+            }
+          }}
+          onLoadedData={() => {
+            onPlayerLoaded?.();
+            handleLoadedMetadata();
+
+            if (videoRef.current) {
+              if (playbackRate) {
+                videoRef.current.playbackRate = playbackRate;
               }
-            }}
-            onEnded={() => {
-              if (onClipEnded) {
-                onClipEnded(getVideoTime() ?? 0);
+
+              if (volume) {
+                videoRef.current.volume = volume;
               }
-            }}
-            onError={(e) => {
-              if (
-                !hlsRef.current &&
+            }
+          }}
+          onEnded={() => {
+            if (onClipEnded) {
+              onClipEnded(getVideoTime() ?? 0);
+            }
+          }}
+          onError={(e) => {
+            if (
+              !hlsRef.current &&
+              // @ts-expect-error code does exist
+              unsupportedErrorCodes.includes(e.target.error.code) &&
+              videoRef.current
+            ) {
+              setLoadedMetadata(false);
+              setUseHlsCompat(true);
+            } else {
+              toast.error(
                 // @ts-expect-error code does exist
-                unsupportedErrorCodes.includes(e.target.error.code) &&
-                videoRef.current
-              ) {
-                setLoadedMetadata(false);
-                setUseHlsCompat(true);
-              } else {
-                toast.error(
-                  // @ts-expect-error code does exist
-                  `Failed to play recordings (error ${e.target.error.code}): ${e.target.error.message}`,
-                  {
-                    position: "top-center",
-                  },
-                );
-              }
-            }}
-          />
-        </div>
+                `Failed to play recordings (error ${e.target.error.code}): ${e.target.error.message}`,
+                {
+                  position: "top-center",
+                },
+              );
+            }
+          }}
+        />
       </TransformComponent>
     </TransformWrapper>
   );

web/src/components/player/dynamic/DynamicVideoPlayer.tsx

@@ -1,11 +1,4 @@
-import {
-  ReactNode,
-  useCallback,
-  useEffect,
-  useMemo,
-  useRef,
-  useState,
-} from "react";
+import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { useApiHost } from "@/api";
 import useSWR from "swr";
 import { FrigateConfig } from "@/types/frigateConfig";
@@ -47,7 +40,6 @@ type DynamicVideoPlayerProps = {
   setFullResolution: React.Dispatch<React.SetStateAction<VideoResolutionType>>;
   toggleFullscreen: () => void;
   containerRef?: React.MutableRefObject<HTMLDivElement | null>;
-  transformedOverlay?: ReactNode;
 };
 export default function DynamicVideoPlayer({
   className,
@@ -66,7 +58,6 @@ export default function DynamicVideoPlayer({
   setFullResolution,
   toggleFullscreen,
   containerRef,
-  transformedOverlay,
 }: DynamicVideoPlayerProps) {
   const { t } = useTranslation(["components/player"]);
   const apiHost = useApiHost();
@@ -321,7 +312,6 @@ export default function DynamicVideoPlayer({
           isDetailMode={isDetailMode}
           camera={contextCamera || camera}
           currentTimeOverride={currentTime}
-          transformedOverlay={transformedOverlay}
         />
       )}
       <PreviewPlayer

web/src/components/timeline/DetailStream.tsx

@@ -1,4 +1,4 @@
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { useEffect, useMemo, useRef, useState } from "react";
 import { TrackingDetailsSequence } from "@/types/timeline";
 import { getLifecycleItemDescription } from "@/utils/lifecycleUtil";
 import { useDetailStream } from "@/context/detail-stream-context";
@@ -33,7 +33,6 @@ import { MdAutoAwesome } from "react-icons/md";
 import { isPWA } from "@/utils/isPWA";
 import { isInIframe } from "@/utils/isIFrame";
 import { GenAISummaryDialog } from "../overlay/chip/GenAISummaryChip";
-import { Separator } from "../ui/separator";
 
 type DetailStreamProps = {
   reviewItems?: ReviewSegment[];
@@ -50,8 +49,7 @@ export default function DetailStream({
 }: DetailStreamProps) {
   const { data: config } = useSWR<FrigateConfig>("config");
   const { t } = useTranslation("views/events");
-  const { annotationOffset, selectedObjectIds, setSelectedObjectIds } =
-    useDetailStream();
+  const { annotationOffset } = useDetailStream();
   const scrollRef = useRef<HTMLDivElement>(null);
 
   const [activeReviewId, setActiveReviewId] = useState<string | undefined>(
@@ -69,69 +67,9 @@ export default function DetailStream({
     true,
   );
 
-  // When the settings panel opens, pin to the nearest review with detections
-  // so the user can visually align the bounding box using the offset slider
-  const pinnedDetectTimestampRef = useRef<number | null>(null);
-  const wasControlsExpandedRef = useRef(false);
-  const selectedBeforeExpandRef = useRef<string[]>([]);
-
-  const onSeekCheckPlaying = useCallback(
-    (timestamp: number) => {
-      onSeek(timestamp, isPlaying);
-    },
-    [onSeek, isPlaying],
-  );
-
-  useEffect(() => {
-    if (controlsExpanded && !wasControlsExpandedRef.current) {
-      selectedBeforeExpandRef.current = selectedObjectIds;
-
-      const items = (reviewItems ?? []).filter(
-        (r) => r.data?.detections?.length > 0,
-      );
-      if (items.length > 0) {
-        // Pick the nearest review to current effective time
-        let nearest = items[0];
-        let minDiff = Math.abs(effectiveTime - nearest.start_time);
-        for (const r of items) {
-          const diff = Math.abs(effectiveTime - r.start_time);
-          if (diff < minDiff) {
-            nearest = r;
-            minDiff = diff;
-          }
-        }
-
-        const nearestId = `review-${nearest.id ?? nearest.start_time ?? Math.floor(nearest.start_time ?? 0)}`;
-        setActiveReviewId(nearestId);
-
-        const detectionId = nearest.data.detections[0];
-        setSelectedObjectIds([detectionId]);
-
-        // Use the detection's actual start timestamp (parsed from its ID)
-        // rather than review.start_time, which can be >10ms away from any
-        // lifecycle event and would fail the bounding-box TOLERANCE check.
-        const detectTimestamp = parseFloat(detectionId);
-        pinnedDetectTimestampRef.current = detectTimestamp;
-        const recordTime = detectTimestamp + annotationOffset / 1000;
-        onSeek(recordTime, false);
-      }
-    }
-    if (!controlsExpanded && wasControlsExpandedRef.current) {
-      pinnedDetectTimestampRef.current = null;
-      setSelectedObjectIds(selectedBeforeExpandRef.current);
-    }
-    wasControlsExpandedRef.current = controlsExpanded;
-    // Only trigger on expand/collapse transition
-    // eslint-disable-next-line react-hooks/exhaustive-deps
-  }, [controlsExpanded]);
-
-  // Re-seek on annotation offset change while settings panel is open
-  useEffect(() => {
-    const pinned = pinnedDetectTimestampRef.current;
-    if (!controlsExpanded || pinned == null) return;
-    const recordTime = pinned + annotationOffset / 1000;
-    onSeek(recordTime, false);
-  }, [controlsExpanded, annotationOffset, onSeek]);
+  const onSeekCheckPlaying = (timestamp: number) => {
+    onSeek(timestamp, isPlaying);
+  };
 
   // Ensure we initialize the active review when reviewItems first arrive.
   // This helps when the component mounts while the video is already
@@ -276,12 +214,6 @@ export default function DetailStream({
       />
 
       <div className="relative flex h-full flex-col">
-        {controlsExpanded && (
-          <div
-            className="absolute inset-0 z-20 cursor-pointer bg-black/50"
-            onClick={() => setControlsExpanded(false)}
-          />
-        )}
         <div
           ref={scrollRef}
           className="scrollbar-container flex-1 overflow-y-auto overflow-x-hidden pb-14"
@@ -335,9 +267,8 @@ export default function DetailStream({
             )}
           </button>
           {controlsExpanded && (
-            <div className="space-y-4 px-3 pb-5 pt-2">
+            <div className="space-y-3 px-3 pb-3">
               <AnnotationOffsetSlider />
-              <Separator />
               <div className="flex flex-col gap-1">
                 <div className="flex items-center justify-between">
                   <label className="text-sm font-medium">

web/src/components/timeline/MotionReviewTimeline.tsx

@@ -25,7 +25,6 @@ export type MotionReviewTimelineProps = {
   timestampSpread: number;
   timelineStart: number;
   timelineEnd: number;
-  scrollToTime?: number;
   showHandlebar?: boolean;
   handlebarTime?: number;
   setHandlebarTime?: React.Dispatch<React.SetStateAction<number>>;
@@ -59,7 +58,6 @@ export function MotionReviewTimeline({
   timestampSpread,
   timelineStart,
   timelineEnd,
-  scrollToTime,
   showHandlebar = false,
   handlebarTime,
   setHandlebarTime,
@@ -178,15 +176,6 @@ export function MotionReviewTimeline({
     [],
   );
 
-  // allow callers to request the timeline center on a specific time
-  useEffect(() => {
-    if (scrollToTime == undefined) return;
-
-    setTimeout(() => {
-      scrollToSegment(alignStartDateToTimeline(scrollToTime), true, "auto");
-    }, 0);
-  }, [scrollToTime, scrollToSegment, alignStartDateToTimeline]);
-
   // keep handlebar centered when zooming
   useEffect(() => {
     setTimeout(() => {

web/src/components/timeline/ReviewTimeline.tsx

@@ -343,12 +343,9 @@ export function ReviewTimeline({
 
   useEffect(() => {
     if (onHandlebarDraggingChange) {
-      // Keep existing callback name but treat it as a generic dragging signal.
-      // This allows consumers (e.g. export-handle timelines) to correctly
-      // enable preview scrubbing while dragging export handles.
-      onHandlebarDraggingChange(isDragging);
+      onHandlebarDraggingChange(isDraggingHandlebar);
     }
-  }, [isDragging, onHandlebarDraggingChange]);
+  }, [isDraggingHandlebar, onHandlebarDraggingChange]);
 
   const isHandlebarInNoRecordingPeriod = useMemo(() => {
     if (!getRecordingAvailability || handlebarTime === undefined) return false;

web/src/components/ui/progress.tsx

@@ -1,26 +0,0 @@
-import * as React from "react"
-import * as ProgressPrimitive from "@radix-ui/react-progress"
-
-import { cn } from "@/lib/utils"
-
-const Progress = React.forwardRef<
-  React.ElementRef<typeof ProgressPrimitive.Root>,
-  React.ComponentPropsWithoutRef<typeof ProgressPrimitive.Root>
->(({ className, value, ...props }, ref) => (
-  <ProgressPrimitive.Root
-    ref={ref}
-    className={cn(
-      "relative h-4 w-full overflow-hidden rounded-full bg-secondary",
-      className
-    )}
-    {...props}
-  >
-    <ProgressPrimitive.Indicator
-      className="h-full w-full flex-1 bg-primary transition-all"
-      style={{ transform: `translateX(-${100 - (value || 0)}%)` }}
-    />
-  </ProgressPrimitive.Root>
-))
-Progress.displayName = ProgressPrimitive.Root.displayName
-
-export { Progress }

web/src/hooks/use-camera-activity.ts

@@ -8,19 +8,14 @@ import {
 import { CameraConfig, FrigateConfig } from "@/types/frigateConfig";
 import { MotionData, ReviewSegment } from "@/types/review";
 import { useCallback, useEffect, useMemo, useState } from "react";
-import { AudioDetection, ObjectType } from "@/types/ws";
 import { useTimelineUtils } from "./use-timeline-utils";
+import { AudioDetection, ObjectType } from "@/types/ws";
 import useDeepMemo from "./use-deep-memo";
 import { isEqual } from "lodash";
 import { useAutoFrigateStats } from "./use-stats";
 import useSWR from "swr";
 import { getAttributeLabels } from "@/utils/iconUtil";
 
-export type MotionOnlyRange = {
-  start_time: number;
-  end_time: number;
-};
-
 type useCameraActivityReturn = {
   enabled?: boolean;
   activeTracking: boolean;
@@ -209,9 +204,9 @@ export function useCameraMotionNextTimestamp(
       return [];
     }
 
-    const ranges: [number, number][] = [];
-    let currentSegmentStart: number | null = null;
-    let currentSegmentEnd: number | null = null;
+    const ranges = [];
+    let currentSegmentStart = null;
+    let currentSegmentEnd = null;
 
     // align motion start to timeline start
     const offset =
@@ -220,19 +215,13 @@ export function useCameraMotionNextTimestamp(
       segmentDuration;
 
     const startIndex = Math.abs(Math.floor(offset / 15));
-    const now = Date.now() / 1000;
 
     for (
       let i = startIndex;
       i < motionData.length;
       i = i + segmentDuration / 15
     ) {
-      const motionStart = motionData[i]?.start_time;
-
-      if (motionStart == undefined) {
-        continue;
-      }
-
+      const motionStart = motionData[i].start_time;
       const motionEnd = motionStart + segmentDuration;
 
       const segmentMotion = motionData
@@ -241,10 +230,10 @@ export function useCameraMotionNextTimestamp(
       const overlappingReviewItems = reviewItems.some(
         (item) =>
           (item.start_time >= motionStart && item.start_time < motionEnd) ||
-          ((item.end_time ?? now) > motionStart &&
-            (item.end_time ?? now) <= motionEnd) ||
+          ((item.end_time ?? Date.now() / 1000) > motionStart &&
+            (item.end_time ?? Date.now() / 1000) <= motionEnd) ||
           (item.start_time <= motionStart &&
-            (item.end_time ?? now) >= motionEnd),
+            (item.end_time ?? Date.now() / 1000) >= motionEnd),
       );
 
       if (!segmentMotion || overlappingReviewItems) {
@@ -252,14 +241,16 @@ export function useCameraMotionNextTimestamp(
           currentSegmentStart = motionStart;
         }
         currentSegmentEnd = motionEnd;
-      } else if (currentSegmentStart !== null && currentSegmentEnd !== null) {
-        ranges.push([currentSegmentStart, currentSegmentEnd]);
-        currentSegmentStart = null;
-        currentSegmentEnd = null;
+      } else {
+        if (currentSegmentStart !== null) {
+          ranges.push([currentSegmentStart, currentSegmentEnd]);
+          currentSegmentStart = null;
+          currentSegmentEnd = null;
+        }
       }
     }
 
-    if (currentSegmentStart !== null && currentSegmentEnd !== null) {
+    if (currentSegmentStart !== null) {
       ranges.push([currentSegmentStart, currentSegmentEnd]);
     }
 
@@ -313,93 +304,3 @@ export function useCameraMotionNextTimestamp(
 
   return nextTimestamp;
 }
-
-export function useCameraMotionOnlyRanges(
-  segmentDuration: number,
-  reviewItems: ReviewSegment[],
-  motionData: MotionData[],
-) {
-  const motionOnlyRanges = useMemo(() => {
-    if (!motionData?.length || !reviewItems) {
-      return [];
-    }
-
-    const fallbackBucketDuration = Math.max(1, segmentDuration / 2);
-    const normalizedMotionData = Array.from(
-      motionData
-        .reduce((accumulator, item) => {
-          const currentMotion = accumulator.get(item.start_time) ?? 0;
-          accumulator.set(
-            item.start_time,
-            Math.max(currentMotion, item.motion ?? 0),
-          );
-          return accumulator;
-        }, new Map<number, number>())
-        .entries(),
-    )
-      .map(([start_time, motion]) => ({ start_time, motion }))
-      .sort((left, right) => left.start_time - right.start_time);
-
-    const bucketRanges: MotionOnlyRange[] = [];
-    const now = Date.now() / 1000;
-
-    for (let i = 0; i < normalizedMotionData.length; i++) {
-      const motionStart = normalizedMotionData[i].start_time;
-      const motionEnd = motionStart + fallbackBucketDuration;
-
-      const overlappingReviewItems = reviewItems.some(
-        (item) =>
-          (item.start_time >= motionStart && item.start_time < motionEnd) ||
-          ((item.end_time ?? now) > motionStart &&
-            (item.end_time ?? now) <= motionEnd) ||
-          (item.start_time <= motionStart &&
-            (item.end_time ?? now) >= motionEnd),
-      );
-
-      const isMotionOnlySegment =
-        (normalizedMotionData[i].motion ?? 0) > 0 && !overlappingReviewItems;
-
-      if (!isMotionOnlySegment) {
-        continue;
-      }
-
-      bucketRanges.push({
-        start_time: motionStart,
-        end_time: motionEnd,
-      });
-    }
-
-    if (!bucketRanges.length) {
-      return [];
-    }
-
-    const mergedRanges = bucketRanges.reduce<MotionOnlyRange[]>(
-      (ranges, range) => {
-        if (!ranges.length) {
-          return [range];
-        }
-
-        const previousRange = ranges[ranges.length - 1];
-        const isContiguous =
-          range.start_time <= previousRange.end_time + 0.001 &&
-          range.start_time >= previousRange.end_time - 0.001;
-
-        if (isContiguous) {
-          previousRange.end_time = Math.max(
-            previousRange.end_time,
-            range.end_time,
-          );
-          return ranges;
-        }
-
-        ranges.push(range);
-        return ranges;
-      },
-      [],
-    );
-
-    return mergedRanges;
-  }, [motionData, reviewItems, segmentDuration]);
-
-  return motionOnlyRanges;
-}

web/src/hooks/use-overlay-state.tsx

@@ -1,4 +1,4 @@
-import { useCallback, useContext, useEffect, useMemo, useRef } from "react";
+import { useCallback, useContext, useEffect, useMemo } from "react";
 import { useLocation, useNavigate, useSearchParams } from "react-router-dom";
 import { usePersistence } from "./use-persistence";
 import { useUserPersistence } from "./use-user-persistence";
@@ -12,28 +12,20 @@ export function useOverlayState<S>(
   const location = useLocation();
   const navigate = useNavigate();
 
-  const locationRef = useRef(location);
-  locationRef.current = location;
+  const currentLocationState = useMemo(() => location.state, [location]);
 
   const setOverlayStateValue = useCallback(
     (value: S, replace: boolean = false) => {
-      const loc = locationRef.current;
-      const currentValue = loc.state?.[key] as S | undefined;
-
-      if (Object.is(currentValue, value)) {
-        return;
-      }
-
-      const newLocationState = { ...loc.state };
+      const newLocationState = { ...currentLocationState };
       newLocationState[key] = value;
-      navigate(loc.pathname + (preserveSearch ? loc.search : ""), {
+      navigate(location.pathname + (preserveSearch ? location.search : ""), {
         state: newLocationState,
         replace,
       });
     },
-    // locationRef is stable so we don't need it in deps
+    // we know that these deps are correct
     // eslint-disable-next-line react-hooks/exhaustive-deps
-    [key, navigate, preserveSearch],
+    [key, currentLocationState, navigate],
   );
 
   const overlayStateValue = useMemo<S | undefined>(
@@ -55,9 +47,7 @@ export function usePersistedOverlayState<S extends string>(
 ] {
   const location = useLocation();
   const navigate = useNavigate();
-
-  const locationRef = useRef(location);
-  locationRef.current = location;
+  const currentLocationState = useMemo(() => location.state, [location]);
 
   // currently selected value
 
@@ -73,21 +63,14 @@ export function usePersistedOverlayState<S extends string>(
 
   const setOverlayStateValue = useCallback(
     (value: S | undefined, replace: boolean = false) => {
-      const loc = locationRef.current;
-      const currentValue = loc.state?.[key] as S | undefined;
-
-      if (Object.is(currentValue, value)) {
-        return;
-      }
-
       setPersistedValue(value);
-      const newLocationState = { ...loc.state };
+      const newLocationState = { ...currentLocationState };
       newLocationState[key] = value;
-      navigate(loc.pathname, { state: newLocationState, replace });
+      navigate(location.pathname, { state: newLocationState, replace });
     },
-    // locationRef is stable so we don't need it in deps
+    // we know that these deps are correct
     // eslint-disable-next-line react-hooks/exhaustive-deps
-    [key, navigate, setPersistedValue],
+    [key, currentLocationState, navigate],
   );
 
   return [
@@ -115,9 +98,7 @@ export function useUserPersistedOverlayState<S extends string>(
   const { auth } = useContext(AuthContext);
   const location = useLocation();
   const navigate = useNavigate();
-
-  const locationRef = useRef(location);
-  locationRef.current = location;
+  const currentLocationState = useMemo(() => location.state, [location]);
 
   // currently selected value from URL state
   const overlayStateValue = useMemo<S | undefined>(
@@ -131,21 +112,14 @@ export function useUserPersistedOverlayState<S extends string>(
 
   const setOverlayStateValue = useCallback(
     (value: S | undefined, replace: boolean = false) => {
-      const loc = locationRef.current;
-      const currentValue = loc.state?.[key] as S | undefined;
-
-      if (Object.is(currentValue, value)) {
-        return;
-      }
-
       setPersistedValue(value);
-      const newLocationState = { ...loc.state };
+      const newLocationState = { ...currentLocationState };
       newLocationState[key] = value;
-      navigate(loc.pathname, { state: newLocationState, replace });
+      navigate(location.pathname, { state: newLocationState, replace });
     },
-    // locationRef is stable so we don't need it in deps
+    // we know that these deps are correct
     // eslint-disable-next-line react-hooks/exhaustive-deps
-    [key, navigate, setPersistedValue],
+    [key, currentLocationState, navigate, setPersistedValue],
   );
 
   // Don't return a value until auth has finished loading
@@ -168,21 +142,17 @@ export function useHashState<S extends string>(): [
   const location = useLocation();
   const navigate = useNavigate();
 
-  const locationRef = useRef(location);
-  locationRef.current = location;
-
   const setHash = useCallback(
     (value: S | undefined) => {
-      const loc = locationRef.current;
       if (!value) {
-        navigate(loc.pathname);
+        navigate(location.pathname);
       } else {
-        navigate(`${loc.pathname}#${value}`, { state: loc.state });
+        navigate(`${location.pathname}#${value}`, { state: location.state });
       }
     },
-    // locationRef is stable so we don't need it in deps
+    // we know that these deps are correct
     // eslint-disable-next-line react-hooks/exhaustive-deps
-    [navigate],
+    [location, navigate],
   );
 
   const hash = useMemo(

web/src/hooks/use-user-persistence.ts

@@ -116,11 +116,6 @@ export function useUserPersistence<S>(
       return;
     }
 
-    // Skip reload if we're already loaded for this key
-    if (loadedKeyRef.current === namespacedKey) {
-      return;
-    }
-
     // Reset state when key changes - this prevents stale writes
     loadedKeyRef.current = null;
     migrationAttemptedRef.current = false;

web/src/lib/const.ts

@@ -1,6 +1,3 @@
-/** ONNX embedding models that require local model downloads. GenAI providers are not in this list. */
-export const JINA_EMBEDDING_MODELS = ["jinav1", "jinav2"] as const;
-
 export const supportedLanguageKeys = [
   "en",
   "es",

web/src/pages/Events.tsx

@@ -1,6 +1,5 @@
 import ActivityIndicator from "@/components/indicators/activity-indicator";
 import useApiFilter from "@/hooks/use-api-filter";
-import { useAllowedCameras } from "@/hooks/use-allowed-cameras";
 import { useCameraPreviews } from "@/hooks/use-camera-previews";
 import { useTimezone } from "@/hooks/use-date-utils";
 import { useOverlayState, useSearchEffect } from "@/hooks/use-overlay-state";
@@ -22,7 +21,6 @@ import {
   getEndOfDayTimestamp,
 } from "@/utils/dateUtil";
 import EventView from "@/views/events/EventView";
-import MotionSearchView from "@/views/motion-search/MotionSearchView";
 import { RecordingView } from "@/views/recording/RecordingView";
 import axios from "axios";
 import { useCallback, useEffect, useMemo, useState } from "react";
@@ -36,7 +34,6 @@ export default function Events() {
     revalidateOnFocus: false,
   });
   const timezone = useTimezone(config);
-  const allowedCameras = useAllowedCameras();
 
   // recordings viewer
 
@@ -55,74 +52,6 @@ export default function Events() {
     undefined,
     false,
   );
-  const [motionPreviewsCamera, setMotionPreviewsCamera] = useOverlayState<
-    string | undefined
-  >("motionPreviewsCamera", undefined);
-
-  const [motionSearchCamera, setMotionSearchCamera] = useState<string | null>(
-    null,
-  );
-  const [motionSearchDay, setMotionSearchDay] = useState<Date | undefined>(
-    undefined,
-  );
-
-  const motionSearchCameras = useMemo(() => {
-    if (!config?.cameras) {
-      return [] as string[];
-    }
-
-    return Object.keys(config.cameras).filter((cam) =>
-      allowedCameras.includes(cam),
-    );
-  }, [allowedCameras, config?.cameras]);
-
-  const selectedMotionSearchCamera = useMemo(() => {
-    if (!motionSearchCamera) {
-      return null;
-    }
-
-    if (motionSearchCameras.includes(motionSearchCamera)) {
-      return motionSearchCamera;
-    }
-
-    return motionSearchCameras[0] ?? null;
-  }, [motionSearchCamera, motionSearchCameras]);
-
-  const motionSearchTimeRange = useMemo(() => {
-    if (motionSearchDay) {
-      return {
-        after: getBeginningOfDayTimestamp(new Date(motionSearchDay)),
-        before: getEndOfDayTimestamp(new Date(motionSearchDay)),
-      };
-    }
-
-    const now = Date.now() / 1000;
-    return {
-      after: now - 86400,
-      before: now,
-    };
-  }, [motionSearchDay]);
-
-  const closeMotionSearch = useCallback(() => {
-    setMotionSearchCamera(null);
-    setMotionSearchDay(undefined);
-    setBeforeTs(Date.now() / 1000);
-  }, []);
-
-  const handleMotionSearchCameraSelect = useCallback((camera: string) => {
-    setMotionSearchCamera(camera);
-  }, []);
-
-  const handleMotionSearchDaySelect = useCallback((day: Date | undefined) => {
-    if (day == undefined) {
-      setMotionSearchDay(undefined);
-      return;
-    }
-
-    const normalizedDay = new Date(day);
-    normalizedDay.setHours(0, 0, 0, 0);
-    setMotionSearchDay(normalizedDay);
-  }, []);
 
   const [notificationTab, setNotificationTab] =
     useState<TimelineType>("timeline");
@@ -579,24 +508,7 @@ export default function Events() {
       );
     }
   } else {
-    return motionSearchCamera ? (
-      !config || !selectedMotionSearchCamera ? (
-        <ActivityIndicator />
-      ) : (
-        <MotionSearchView
-          config={config}
-          cameras={motionSearchCameras}
-          selectedCamera={selectedMotionSearchCamera}
-          onCameraSelect={handleMotionSearchCameraSelect}
-          cameraLocked={true}
-          selectedDay={motionSearchDay}
-          onDaySelect={handleMotionSearchDaySelect}
-          timeRange={motionSearchTimeRange}
-          timezone={timezone}
-          onBack={closeMotionSearch}
-        />
-      )
-    ) : (
+    return (
       <EventView
         reviewItems={reviewItems}
         currentReviewItems={currentItems}
@@ -613,11 +525,6 @@ export default function Events() {
         markItemAsReviewed={markItemAsReviewed}
         markAllItemsAsReviewed={markAllItemsAsReviewed}
         onOpenRecording={setRecording}
-        motionPreviewsCamera={motionPreviewsCamera ?? null}
-        setMotionPreviewsCamera={(camera) =>
-          setMotionPreviewsCamera(camera ?? undefined)
-        }
-        setMotionSearchCamera={setMotionSearchCamera}
         pullLatestData={reloadData}
         updateFilter={onUpdateFilter}
       />

web/src/pages/Explore.tsx

@@ -23,7 +23,6 @@ import { toast } from "sonner";
 import useSWR from "swr";
 import useSWRInfinite from "swr/infinite";
 import { useDocDomain } from "@/hooks/use-doc-domain";
-import { JINA_EMBEDDING_MODELS } from "@/lib/const";
 
 const API_LIMIT = 25;
 
@@ -294,12 +293,7 @@ export default function Explore() {
   const modelVersion = config?.semantic_search.model || "jinav1";
   const modelSize = config?.semantic_search.model_size || "small";
 
-  // GenAI providers have no local models to download
-  const isGenaiEmbeddings =
-    typeof modelVersion === "string" &&
-    !(JINA_EMBEDDING_MODELS as readonly string[]).includes(modelVersion);
-
-  // Text model state (skipped for GenAI - no local models)
+  // Text model state
   const { payload: textModelState } = useModelState(
     modelVersion === "jinav1"
       ? "jinaai/jina-clip-v1-text_model_fp16.onnx"
@@ -334,10 +328,6 @@ export default function Explore() {
   );
 
   const allModelsLoaded = useMemo(() => {
-    if (isGenaiEmbeddings) {
-      return true;
-    }
-
     return (
       textModelState === "downloaded" &&
       textTokenizerState === "downloaded" &&
@@ -345,7 +335,6 @@ export default function Explore() {
       visionFeatureExtractorState === "downloaded"
     );
   }, [
-    isGenaiEmbeddings,
     textModelState,
     textTokenizerState,
     visionModelState,
@@ -369,11 +358,10 @@ export default function Explore() {
     !defaultViewLoaded ||
     (config?.semantic_search.enabled &&
       (!reindexState ||
-        (!isGenaiEmbeddings &&
-          (!textModelState ||
-            !textTokenizerState ||
-            !visionModelState ||
-            !visionFeatureExtractorState))))
+        !textModelState ||
+        !textTokenizerState ||
+        !visionModelState ||
+        !visionFeatureExtractorState))
   ) {
     return (
       <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />

web/src/pages/MotionSearch.tsx

@@ -1,112 +0,0 @@
-import { useEffect, useMemo, useState, useCallback } from "react";
-import { useTranslation } from "react-i18next";
-import useSWR from "swr";
-import { FrigateConfig } from "@/types/frigateConfig";
-import { useTimezone } from "@/hooks/use-date-utils";
-import MotionSearchView from "@/views/motion-search/MotionSearchView";
-import {
-  getBeginningOfDayTimestamp,
-  getEndOfDayTimestamp,
-} from "@/utils/dateUtil";
-import { useAllowedCameras } from "@/hooks/use-allowed-cameras";
-import { useSearchEffect } from "@/hooks/use-overlay-state";
-import ActivityIndicator from "@/components/indicators/activity-indicator";
-
-export default function MotionSearch() {
-  const { t } = useTranslation(["views/motionSearch"]);
-
-  const { data: config } = useSWR<FrigateConfig>("config", {
-    revalidateOnFocus: false,
-  });
-
-  const timezone = useTimezone(config);
-
-  useEffect(() => {
-    document.title = t("documentTitle");
-  }, [t]);
-
-  // Get allowed cameras
-  const allowedCameras = useAllowedCameras();
-
-  const cameras = useMemo(() => {
-    if (!config?.cameras) return [];
-    return Object.keys(config.cameras).filter((cam) =>
-      allowedCameras.includes(cam),
-    );
-  }, [config?.cameras, allowedCameras]);
-
-  // Selected camera state
-  const [selectedCamera, setSelectedCamera] = useState<string | null>(null);
-  const [cameraLocked, setCameraLocked] = useState(false);
-
-  useSearchEffect("camera", (camera: string) => {
-    if (cameras.length > 0 && cameras.includes(camera)) {
-      setSelectedCamera(camera);
-      setCameraLocked(true);
-    }
-    return false;
-  });
-
-  // Initialize with first camera when available (only if not set by camera param)
-  useEffect(() => {
-    if (cameras.length === 0) return;
-    if (!selectedCamera) {
-      setSelectedCamera(cameras[0]);
-    }
-  }, [cameras, selectedCamera]);
-
-  // Time range state - default to last 24 hours
-  const [selectedDay, setSelectedDay] = useState<Date | undefined>(undefined);
-
-  const timeRange = useMemo(() => {
-    if (selectedDay) {
-      return {
-        after: getBeginningOfDayTimestamp(new Date(selectedDay)),
-        before: getEndOfDayTimestamp(new Date(selectedDay)),
-      };
-    }
-    // Default to last 24 hours
-    const now = Date.now() / 1000;
-    return {
-      after: now - 86400,
-      before: now,
-    };
-  }, [selectedDay]);
-
-  const handleCameraSelect = useCallback((camera: string) => {
-    setSelectedCamera(camera);
-  }, []);
-
-  const handleDaySelect = useCallback((day: Date | undefined) => {
-    if (day == undefined) {
-      setSelectedDay(undefined);
-      return;
-    }
-
-    const normalizedDay = new Date(day);
-    normalizedDay.setHours(0, 0, 0, 0);
-    setSelectedDay(normalizedDay);
-  }, []);
-
-  if (!config || cameras.length === 0) {
-    return (
-      <div className="flex size-full items-center justify-center">
-        <ActivityIndicator />
-      </div>
-    );
-  }
-
-  return (
-    <MotionSearchView
-      config={config}
-      cameras={cameras}
-      selectedCamera={selectedCamera ?? null}
-      onCameraSelect={handleCameraSelect}
-      cameraLocked={cameraLocked}
-      selectedDay={selectedDay}
-      onDaySelect={handleDaySelect}
-      timeRange={timeRange}
-      timezone={timezone}
-    />
-  );
-}

web/src/pages/Settings.tsx

@@ -40,8 +40,7 @@ import UsersView from "@/views/settings/UsersView";
 import RolesView from "@/views/settings/RolesView";
 import UiSettingsView from "@/views/settings/UiSettingsView";
 import FrigatePlusSettingsView from "@/views/settings/FrigatePlusSettingsView";
-import MediaSyncSettingsView from "@/views/settings/MediaSyncSettingsView";
-import RegionGridSettingsView from "@/views/settings/RegionGridSettingsView";
+import MaintenanceSettingsView from "@/views/settings/MaintenanceSettingsView";
 import SystemDetectionModelSettingsView from "@/views/settings/SystemDetectionModelSettingsView";
 import {
   SingleSectionPage,
@@ -155,8 +154,7 @@ const allSettingsViews = [
   "roles",
   "notifications",
   "frigateplus",
-  "mediaSync",
-  "regionGrid",
+  "maintenance",
 ] as const;
 type SettingsType = (typeof allSettingsViews)[number];
 
@@ -446,10 +444,7 @@ const settingsGroups = [
   },
   {
     label: "maintenance",
-    items: [
-      { key: "mediaSync", component: MediaSyncSettingsView },
-      { key: "regionGrid", component: RegionGridSettingsView },
-    ],
+    items: [{ key: "maintenance", component: MaintenanceSettingsView }],
   },
 ];
 
@@ -476,10 +471,15 @@ const CAMERA_SELECT_BUTTON_PAGES = [
   "masksAndZones",
   "motionTuner",
   "triggers",
-  "regionGrid",
 ];
 
-const ALLOWED_VIEWS_FOR_VIEWER = ["profileSettings", "notifications"];
+const ALLOWED_VIEWS_FOR_VIEWER = ["ui", "debug", "notifications"];
+
+const LARGE_BOTTOM_MARGIN_PAGES = [
+  "masksAndZones",
+  "motionTuner",
+  "maintenance",
+];
 
 // keys for camera sections
 const CAMERA_SECTION_MAPPING: Record<string, SettingsType> = {
@@ -1355,9 +1355,9 @@ export default function Settings() {
           )}
         </div>
       </div>
-      <SidebarProvider className="relative h-full min-h-0 flex-1">
-        <Sidebar variant="inset" className="absolute h-full pl-0 pt-0">
-          <SidebarContent className="scrollbar-container overflow-y-auto border-r-[1px] border-secondary bg-background py-2">
+      <SidebarProvider>
+        <Sidebar variant="inset" className="relative mb-8 pl-0 pt-0">
+          <SidebarContent className="scrollbar-container mb-24 overflow-y-auto border-r-[1px] border-secondary bg-background py-2">
             <SidebarMenu>
               {settingsGroups.map((group) => {
                 const filteredItems = group.items.filter((item) =>
@@ -1445,7 +1445,8 @@ export default function Settings() {
         <SidebarInset>
           <div
             className={cn(
-              "scrollbar-container flex-1 overflow-y-auto pl-2 pr-0 pt-2",
+              "scrollbar-container mb-16 flex-1 overflow-y-auto p-2 pr-0",
+              LARGE_BOTTOM_MARGIN_PAGES.includes(pageToggle) && "mb-24",
             )}
           >
             {(() => {

web/src/types/frigateConfig.ts

@@ -106,7 +106,6 @@ export interface CameraConfig {
     frame_height: number;
     improve_contrast: boolean;
     lightning_threshold: number;
-    skip_motion_threshold: number | null;
     mask: {
       [maskId: string]: {
         friendly_name?: string;

web/src/types/motionSearch.ts

@@ -1,46 +0,0 @@
-/**
- * Types for the Motion Search feature
- */
-
-export interface MotionSearchResult {
-  timestamp: number;
-  change_percentage: number;
-}
-
-export interface MotionSearchRequest {
-  start_time: number;
-  end_time: number;
-  polygon_points: number[][];
-  parallel?: boolean;
-  threshold?: number;
-  min_area?: number;
-  frame_skip?: number;
-  max_results?: number;
-}
-
-export interface MotionSearchStartResponse {
-  success: boolean;
-  message: string;
-  job_id: string;
-}
-
-export interface MotionSearchMetrics {
-  segments_scanned: number;
-  segments_processed: number;
-  metadata_inactive_segments: number;
-  heatmap_roi_skip_segments: number;
-  fallback_full_range_segments: number;
-  frames_decoded: number;
-  wall_time_seconds: number;
-  segments_with_errors: number;
-}
-
-export interface MotionSearchStatusResponse {
-  success: boolean;
-  message: string;
-  status: "queued" | "running" | "success" | "failed" | "cancelled";
-  results?: MotionSearchResult[];
-  total_frames_processed?: number;
-  error_message?: string;
-  metrics?: MotionSearchMetrics;
-}

web/src/types/record.ts

@@ -11,7 +11,6 @@ export type Recording = {
   duration: number;
   motion: number;
   objects: number;
-  motion_heatmap?: Record<string, number> | null;
   dBFS: number;
 };