await config update before dismissing trigger dialog

* ensure viewer roles are available in create user dialog

* admin-only endpoint to return unmaksed camera paths and go2rtc streams

* remove camera edit dropdown

pushing camera editing from the UI to 0.18

* clean up camera edit form

* rename component for clarity

CameraSettingsView is now CameraReviewSettingsView

* Catch case where user requsts clip for time that has no recordings

* ensure emergency cleanup also sets has_clip on overlapping events

improves https://github.com/blakeblackshear/frigate/discussions/20945

* use debug log instead of info

* update docs to recommend tmpfs

* improve display of in-progress events in explore tracking details

* improve seeking logic in tracking details

mimic the logic of DynamicVideoController

* only use ffprobe for duration to avoid blocking

fixes https://github.com/blakeblackshear/frigate/discussions/20737#discussioncomment-14999869

* Revert "only use ffprobe for duration to avoid blocking"

This reverts commit 8b15078005aebcfc6062fd0f773d749e3f4a4ee8.

* update readme to link to object detector docs

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

README.md

@@ -12,7 +12,7 @@
 
 A complete and local NVR designed for [Home Assistant](https://www.home-assistant.io) with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
 
-Use of a GPU or AI accelerator such as a [Google Coral](https://coral.ai/products/) or [Hailo](https://hailo.ai/) is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead.
+Use of a GPU or AI accelerator is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported [object detectors](https://docs.frigate.video/configuration/object_detectors/).
 
 - Tight integration with Home Assistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration)
 - Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary

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

@@ -320,6 +320,12 @@ http {
                 add_header Cache-Control "public";
             }
 
+            location /fonts/ {
+                access_log off;
+                expires 1y;
+                add_header Cache-Control "public";
+            }
+
             location /locales/ {
                 access_log off;
                 add_header Cache-Control "public";

docs/docs/configuration/genai.md

@@ -70,7 +70,7 @@ You should have at least 8 GB of RAM available (or VRAM if running on GPU) to ru
 genai:
   provider: ollama
   base_url: http://localhost:11434
-  model: llava:7b
+  model: qwen3-vl:4b
 ```
 
 ## Google Gemini

docs/docs/configuration/genai/config.md

@@ -35,19 +35,18 @@ Each model is available in multiple parameter sizes (3b, 4b, 8b, etc.). Larger s
 
 :::tip
 
-If you are trying to use a single model for Frigate and HomeAssistant, it will need to support vision and tools calling. https://github.com/skye-harris/ollama-modelfiles contains optimized model configs for this task.
+If you are trying to use a single model for Frigate and HomeAssistant, it will need to support vision and tools calling. qwen3-VL supports vision and tools simultaneously in Ollama.
 
 :::
 
 The following models are recommended:
 
-| Model             | Notes                                                       |
+| Model             | Notes                                                                |
-| ----------------- | ----------------------------------------------------------- |
+| ----------------- | -------------------------------------------------------------------- |
-| `qwen3-vl`        | Strong visual and situational understanding                 |
+| `qwen3-vl`        | Strong visual and situational understanding, higher vram requirement |
-| `Intern3.5VL`     | Relatively fast with good vision comprehension              |
+| `Intern3.5VL`     | Relatively fast with good vision comprehension                       |
-| `gemma3`          | Strong frame-to-frame understanding, slower inference times |
+| `gemma3`          | Strong frame-to-frame understanding, slower inference times          |
-| `qwen2.5-vl`      | Fast but capable model with good vision comprehension       |
+| `qwen2.5-vl`      | Fast but capable model with good vision comprehension                |
-| `llava-phi3`      | Lightweight and fast model with vision comprehension        |
 
 :::note
 

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

@@ -12,7 +12,11 @@ import { cn } from "@/lib/utils";
 import HlsVideoPlayer from "@/components/player/HlsVideoPlayer";
 import { baseUrl } from "@/api/baseUrl";
 import { REVIEW_PADDING } from "@/types/review";
-import { ASPECT_VERTICAL_LAYOUT, ASPECT_WIDE_LAYOUT } from "@/types/record";
+import {
+  ASPECT_VERTICAL_LAYOUT,
+  ASPECT_WIDE_LAYOUT,
+  Recording,
+} from "@/types/record";
 import {
   DropdownMenu,
   DropdownMenuTrigger,
@@ -75,6 +79,139 @@ export function TrackingDetails({
 
   const { data: config } = useSWR<FrigateConfig>("config");
 
+  // Fetch recording segments for the event's time range to handle motion-only gaps
+  const eventStartRecord = useMemo(
+    () => (event.start_time ?? 0) + annotationOffset / 1000,
+    [event.start_time, annotationOffset],
+  );
+  const eventEndRecord = useMemo(
+    () => (event.end_time ?? Date.now() / 1000) + annotationOffset / 1000,
+    [event.end_time, annotationOffset],
+  );
+
+  const { data: recordings } = useSWR<Recording[]>(
+    event.camera
+      ? [
+          `${event.camera}/recordings`,
+          {
+            after: eventStartRecord - REVIEW_PADDING,
+            before: eventEndRecord + REVIEW_PADDING,
+          },
+        ]
+      : null,
+  );
+
+  // Convert a timeline timestamp to actual video player time, accounting for
+  // motion-only recording gaps. Uses the same algorithm as DynamicVideoController.
+  const timestampToVideoTime = useCallback(
+    (timestamp: number): number => {
+      if (!recordings || recordings.length === 0) {
+        // Fallback to simple calculation if no recordings data
+        return timestamp - (eventStartRecord - REVIEW_PADDING);
+      }
+
+      const videoStartTime = eventStartRecord - REVIEW_PADDING;
+
+      // If timestamp is before video start, return 0
+      if (timestamp < videoStartTime) return 0;
+
+      // Check if timestamp is before the first recording or after the last
+      if (
+        timestamp < recordings[0].start_time ||
+        timestamp > recordings[recordings.length - 1].end_time
+      ) {
+        // No recording available at this timestamp
+        return 0;
+      }
+
+      // Calculate the inpoint offset - the HLS video may start partway through the first segment
+      let inpointOffset = 0;
+      if (
+        videoStartTime > recordings[0].start_time &&
+        videoStartTime < recordings[0].end_time
+      ) {
+        inpointOffset = videoStartTime - recordings[0].start_time;
+      }
+
+      let seekSeconds = 0;
+      for (const segment of recordings) {
+        // Skip segments that end before our timestamp
+        if (segment.end_time <= timestamp) {
+          // Add this segment's duration, but subtract inpoint offset from first segment
+          if (segment === recordings[0]) {
+            seekSeconds += segment.duration - inpointOffset;
+          } else {
+            seekSeconds += segment.duration;
+          }
+        } else if (segment.start_time <= timestamp) {
+          // The timestamp is within this segment
+          if (segment === recordings[0]) {
+            // For the first segment, account for the inpoint offset
+            seekSeconds +=
+              timestamp - Math.max(segment.start_time, videoStartTime);
+          } else {
+            seekSeconds += timestamp - segment.start_time;
+          }
+          break;
+        }
+      }
+
+      return seekSeconds;
+    },
+    [recordings, eventStartRecord],
+  );
+
+  // Convert video player time back to timeline timestamp, accounting for
+  // motion-only recording gaps. Reverse of timestampToVideoTime.
+  const videoTimeToTimestamp = useCallback(
+    (playerTime: number): number => {
+      if (!recordings || recordings.length === 0) {
+        // Fallback to simple calculation if no recordings data
+        const videoStartTime = eventStartRecord - REVIEW_PADDING;
+        return playerTime + videoStartTime;
+      }
+
+      const videoStartTime = eventStartRecord - REVIEW_PADDING;
+
+      // Calculate the inpoint offset - the video may start partway through the first segment
+      let inpointOffset = 0;
+      if (
+        videoStartTime > recordings[0].start_time &&
+        videoStartTime < recordings[0].end_time
+      ) {
+        inpointOffset = videoStartTime - recordings[0].start_time;
+      }
+
+      let timestamp = 0;
+      let totalTime = 0;
+
+      for (const segment of recordings) {
+        const segmentDuration =
+          segment === recordings[0]
+            ? segment.duration - inpointOffset
+            : segment.duration;
+
+        if (totalTime + segmentDuration > playerTime) {
+          // The player time is within this segment
+          if (segment === recordings[0]) {
+            // For the first segment, add the inpoint offset
+            timestamp =
+              Math.max(segment.start_time, videoStartTime) +
+              (playerTime - totalTime);
+          } else {
+            timestamp = segment.start_time + (playerTime - totalTime);
+          }
+          break;
+        } else {
+          totalTime += segmentDuration;
+        }
+      }
+
+      return timestamp;
+    },
+    [recordings, eventStartRecord],
+  );
+
   eventSequence?.map((event) => {
     event.data.zones_friendly_names = event.data?.zones?.map((zone) => {
       return resolveZoneName(config, zone);
@@ -148,17 +285,14 @@ export function TrackingDetails({
         return;
       }
 
-      // For video mode: convert to video-relative time and seek player
+      // For video mode: convert to video-relative time (accounting for motion-only gaps)
-      const eventStartRecord =
+      const relativeTime = timestampToVideoTime(targetTimeRecord);
-        (event.start_time ?? 0) + annotationOffset / 1000;
-      const videoStartTime = eventStartRecord - REVIEW_PADDING;
-      const relativeTime = targetTimeRecord - videoStartTime;
 
       if (videoRef.current) {
         videoRef.current.currentTime = relativeTime;
       }
     },
-    [event.start_time, annotationOffset, displaySource],
+    [annotationOffset, displaySource, timestampToVideoTime],
   );
 
   const formattedStart = config
@@ -211,24 +345,14 @@ export function TrackingDetails({
     }
 
     // seekToTimestamp is a record stream timestamp
-    // event.start_time is detect stream time, convert to record
+    // Convert to video position (accounting for motion-only recording gaps)
-    // The video clip starts at (eventStartRecord - REVIEW_PADDING)
     if (!videoRef.current) return;
-    const eventStartRecord = event.start_time + annotationOffset / 1000;
+    const relativeTime = timestampToVideoTime(seekToTimestamp);
-    const videoStartTime = eventStartRecord - REVIEW_PADDING;
-    const relativeTime = seekToTimestamp - videoStartTime;
     if (relativeTime >= 0) {
       videoRef.current.currentTime = relativeTime;
     }
     setSeekToTimestamp(null);
-  }, [
+  }, [seekToTimestamp, displaySource, timestampToVideoTime]);
-    seekToTimestamp,
-    event.start_time,
-    annotationOffset,
-    apiHost,
-    event.camera,
-    displaySource,
-  ]);
 
   const isWithinEventRange = useMemo(() => {
     if (effectiveTime === undefined || event.start_time === undefined) {
@@ -335,14 +459,13 @@ export function TrackingDetails({
 
   const handleTimeUpdate = useCallback(
     (time: number) => {
-      // event.start_time is detect stream time, convert to record
+      // Convert video player time back to timeline timestamp
-      const eventStartRecord = event.start_time + annotationOffset / 1000;
+      // accounting for motion-only recording gaps
-      const videoStartTime = eventStartRecord - REVIEW_PADDING;
+      const absoluteTime = videoTimeToTimestamp(time);
-      const absoluteTime = time + videoStartTime;
 
       setCurrentTime(absoluteTime);
     },
-    [event.start_time, annotationOffset],
+    [videoTimeToTimestamp],
   );
 
   const [src, setSrc] = useState(

web/src/views/settings/TriggerView.tsx

@@ -198,9 +198,9 @@ export default function TriggerView({
 
             return axios
               .put("config/set", configBody)
-              .then((configResponse) => {
+              .then(async (configResponse) => {
                 if (configResponse.status === 200) {
-                  updateConfig();
+                  await updateConfig();
                   const displayName =
                     friendly_name && friendly_name !== ""
                       ? `${friendly_name} (${name})`
@@ -353,9 +353,9 @@ export default function TriggerView({
 
             return axios
               .put("config/set", configBody)
-              .then((configResponse) => {
+              .then(async (configResponse) => {
                 if (configResponse.status === 200) {
-                  updateConfig();
+                  await updateConfig();
                   const friendly =
                     config?.cameras?.[selectedCamera]?.semantic_search
                       ?.triggers?.[name]?.friendly_name;