delete timeline entries when expiring events without clips

Events without a clip were deleted once their snapshot expired, but their timeline rows were only removed when clip retention expired, so they were orphaned indefinitely. The timeline cache also held entries forever for events that ended without ever being saved.

docs/data/object_detectors_models.yaml

@@ -894,6 +894,41 @@ deepstack:
             api_url: http://<your_codeproject_ai_server_ip>:<port>/v1/vision/detection
             type: deepstack
             api_timeout: 0.1 # seconds
+xdna2:
+  title: AMD XDNA2
+  models:
+    - key: yolov9
+      label: YOLOv9
+      recommended: true
+      download: |-
+        Prepare the model using the frigate-xdna setup instructions linked above. For local YOLO models, Frigate must have access to the same ONNX file bytes as the sidecar. The example below uses YOLOv9-C at 320x320. Frigate+ models may instead use the same `plus://MODEL_ID` in Frigate and the sidecar.
+      ui: |-
+        Navigate to **Settings > System > Detectors and model** and select **ZMQ IPC** from the detector type dropdown and click **Add**, then set the endpoint to `tcp://xdna:5555`. Then on the same page, in the **Custom Model** tab, configure:
+
+        | Field                                    | Value                                      |
+        | ---------------------------------------- | ------------------------------------------ |
+        | **Custom object detector model path**    | `/config/models/yolov9-c-320.onnx`       |
+        | **Label map for custom object detector** | `/labelmap/coco-80.txt`                   |
+        | **Object detection model input width**   | `320`                                    |
+        | **Object detection model input height**  | `320`                                    |
+        | **Model Input Pixel Color Format**       | `rgb` (Frigate's default value)          |
+        | **Model Input Tensor Shape**             | `nchw`                                   |
+        | **Model Input D Type**                   | `float`                                  |
+        | **Object Detection Model Type**          | `yolo-generic`                           |
+      yaml: |-
+        detectors:
+          xdna:
+            type: zmq
+            endpoint: tcp://xdna:5555
+
+        model:
+          model_type: yolo-generic
+          width: 320
+          height: 320
+          input_tensor: nchw
+          input_dtype: float
+          path: /config/models/yolov9-c-320.onnx
+          labelmap_path: /labelmap/coco-80.txt
 memryx:
   title: MemryX
   models:

docs/docs/configuration/advanced/reference.md

@@ -286,7 +286,7 @@ ffmpeg:
     # Optional: output args for detect streams (default: shown below)
     detect: -threads 2 -f rawvideo -pix_fmt yuv420p
     # Optional: output args for record streams (default: shown below)
-    record: preset-record-generic
+    record: preset-record-generic-audio-aac
   # Optional: Time in seconds to wait before ffmpeg retries connecting to the camera. (default: shown below)
   # If set too low, frigate will retry a connection to the camera's stream too frequently, using up the limited streams some cameras can allow at once
   # If set too high, then if a ffmpeg crash or camera stream timeout occurs, you could potentially lose up to a maximum of retry_interval second(s) of footage

docs/docs/configuration/license_plate_recognition.md

@@ -379,9 +379,9 @@ Navigate to <NavPath path="Settings > Camera configuration > Object detection" /
 Navigate to <NavPath path="Settings > Camera configuration > Objects" />.
 
 | Field                                                     | Description         |
-| ---------------------------------------------- | ------------------- |
+| --------------------------------------------------------- | ------------------- |
 | **Objects to track**                                      | Add `license_plate` |
-| **Object filters > License Plate > Threshold** | Set to `0.7`        |
+| **Object filters > License Plate > Confidence threshold** | Set to `0.7`        |
 
 Navigate to <NavPath path="Settings > Camera configuration > Motion detection" />.
 

docs/docs/configuration/object_detectors.md

@@ -29,6 +29,7 @@ Frigate supports multiple different detectors that work on different types of ha
 
 - [ROCm](#amdrocm-gpu-detector): ROCm can run on AMD Discrete GPUs to provide efficient object detection.
 - [ONNX](#onnx): ROCm will automatically be detected and used as a detector in the `-rocm` Frigate image when a supported ONNX model is configured.
+- <CommunityBadge /> [XDNA2](#amd-xdna2): AMD Ryzen AI / XDNA2 NPUs can run object detection through the community-maintained `frigate-xdna` ZMQ sidecar.
 
 **Apple Silicon**
 
@@ -508,6 +509,28 @@ To verify that the integration is working correctly, start Frigate and observe t
 
 # Community Supported Detectors
 
+## AMD XDNA2
+
+AMD Ryzen AI / XDNA2 NPUs can be used through the community-maintained
+[frigate-xdna](https://github.com/mitchins/frigate-xdna) detector sidecar.
+The sidecar runs separately from Frigate and connects using Frigate's ZMQ
+detector interface.
+
+Currently qualified on **Ryzen AI Max 300 / Strix Halo**. Other XDNA2 devices
+are not yet qualified; XDNA1 is unsupported.
+
+Follow the frigate-xdna setup instructions to prepare and start the sidecar
+before starting Frigate.
+
+### Configuration {#configuration-xdna2}
+
+Using the detector config below will connect Frigate to the sidecar:
+
+<ModelConfigDropdown detectorTitle="AMD XDNA2" models={objectDetectorsModels.xdna2.models} />
+
+The example assumes Frigate and the sidecar share a Docker network where the
+sidecar is named `xdna`.
+
 ## MemryX MX3
 
 This detector is available for use with the MemryX MX3 accelerator M.2 module. Frigate supports the MX3 on compatible hardware platforms, providing efficient and high-performance object detection.

docs/docs/configuration/object_filters.md

@@ -46,9 +46,9 @@ Any detection below `min_score` will be immediately thrown out and never tracked
 Navigate to <NavPath path="Settings > Global configuration > Objects" /> to set score filters globally.
 
 | Field                                              | Description                                                      |
-| --------------------------------------- | ---------------------------------------------------------------- |
+| -------------------------------------------------- | ---------------------------------------------------------------- |
-| **Object filters > Person > Min Score** | Minimum score for a single detection to initiate tracking        |
+| **Object filters > Person > Minimum confidence**   | Minimum score for a single detection to initiate tracking        |
-| **Object filters > Person > Threshold** | Minimum computed (median) score to be considered a true positive |
+| **Object filters > Person > Confidence threshold** | Minimum computed (median) score to be considered a true positive |
 
 To override score filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" /> and select the camera.
 
@@ -104,11 +104,11 @@ Conceptually, a ratio of 1 is a square, 0.5 is a "tall skinny" box, and 2 is a "
 Navigate to <NavPath path="Settings > Global configuration > Objects" /> to set shape filters globally.
 
 | Field                                              | Description                                                              |
-| --------------------------------------- | ------------------------------------------------------------------------ |
+| -------------------------------------------------- | ------------------------------------------------------------------------ |
-| **Object filters > Person > Min Area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Minimum object area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Max Area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Maximum object area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Min Ratio** | Minimum width/height ratio of the bounding box                           |
+| **Object filters > Person > Minimum aspect ratio** | Minimum width/height ratio of the bounding box                           |
-| **Object filters > Person > Max Ratio** | Maximum width/height ratio of the bounding box                           |
+| **Object filters > Person > Maximum aspect ratio** | Maximum width/height ratio of the bounding box                           |
 
 To override shape filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" /> and select the camera.
 

docs/docs/configuration/objects.md

@@ -71,13 +71,13 @@ Object filters help reduce false positives by constraining the size, shape, and
 Navigate to <NavPath path="Settings > Global configuration > Objects" />.
 
 | Field                                              | Description                                                              |
-| --------------------------------------- | ------------------------------------------------------------------------ |
+| -------------------------------------------------- | ------------------------------------------------------------------------ |
-| **Object filters > Person > Min Area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Minimum object area**  | Minimum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Max Area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
+| **Object filters > Person > Maximum object area**  | Maximum bounding box area in pixels (or decimal for percentage of frame) |
-| **Object filters > Person > Min Ratio** | Minimum width/height ratio of the bounding box                           |
+| **Object filters > Person > Minimum aspect ratio** | Minimum width/height ratio of the bounding box                           |
-| **Object filters > Person > Max Ratio** | Maximum width/height ratio of the bounding box                           |
+| **Object filters > Person > Maximum aspect ratio** | Maximum width/height ratio of the bounding box                           |
-| **Object filters > Person > Min Score** | Minimum score for the object to initiate tracking                        |
+| **Object filters > Person > Minimum confidence**   | Minimum score for the object to initiate tracking                        |
-| **Object filters > Person > Threshold** | Minimum computed score to be considered a true positive                  |
+| **Object filters > Person > Confidence threshold** | Minimum computed score to be considered a true positive                  |
 
 To override filters for a specific camera, navigate to <NavPath path="Settings > Camera configuration > Objects" />.
 

docs/docs/configuration/semantic_search.md

@@ -245,8 +245,8 @@ Triggers are best configured through the Frigate UI.
 1. Navigate to <NavPath path="Settings > Enrichments > Triggers" /> and select a camera from the dropdown menu.
 2. Click **Add Trigger** to create a new trigger or use the pencil icon to edit an existing one.
 3. In the **Create Trigger** wizard:
-   - Enter a **Name** for the trigger (e.g., "Red Car Alert").
+   - Enter a **Name** for the trigger (e.g., "Red Car Alert"). Frigate derives the trigger's
-   - Enter a descriptive **Friendly Name** for the trigger (e.g., "Red car on the driveway camera").
+     internal **ID** from this name, which can be revealed and edited with the show/hide toggle.
    - Select the **Type** (`Thumbnail` or `Description`).
    - For `Thumbnail`, select an image to trigger this action when a similar thumbnail image is detected, based on the threshold.
    - For `Description`, enter text to trigger this action when a similar tracked object description is detected.

docs/docs/configuration/zones.md

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

docs/docs/frigate/glossary.md

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

docs/docs/frigate/hardware.md

@@ -70,6 +70,9 @@ Frigate supports multiple different detectors that work on different types of ha
 - [ROCm](#rocm---amd-gpu): ROCm can run on AMD Discrete GPUs to provide efficient object detection
   - [Supports limited model architectures](../../configuration/object_detectors#amdrocm-gpu-detector)
   - Runs best on discrete AMD GPUs
+- <CommunityBadge /> [XDNA2 (Ryzen AI)](#amd-xdna2): AMD XDNA2 NPU (sub-watt power AI/ML processor separate to the GPU) inside Strix and other "AI" branded AMD platforms
+  - Has only been tested with YOLOv9, in theory other graphs may be compiled too.
+  - Runs via ZMQ proxy which adds some latency, only recommended for local connection
 
 **Apple Silicon**
 
@@ -296,6 +299,32 @@ The inference time of a rk3588 with all 3 cores enabled is typically 25-30 ms fo
 | ---------------- | ----------------------------------- |
 | yolov9-tiny      | ~ 4 ms                              |
 
+### AMD Ryzen AI / XDNA2
+
+Frigate supports AMD XDNA2 NPUs through the community-maintained
+frigate-xdna ZMQ sidecar. It works with stock Frigate and supports
+Frigate+ models or compatible local YOLO ONNX models. Models are compiled
+once on the target system and cached for subsequent use.
+
+Currently qualified on **Ryzen AI Max 300 / Strix Halo**. Other XDNA2
+devices are not yet qualified; XDNA1 is unsupported.
+
+Measured YOLOv9 detector latency on Strix Halo:
+
+| Model | 320 | 640 |
+| ----- | ---: | ---: |
+| YOLOv9-T | ~7.4 ms | unsupported |
+| YOLOv9-S | ~9.0 ms | ~20.0 ms |
+| YOLOv9-M | ~13.1 ms | ~34.4 ms |
+| YOLOv9-C | ~14.1 ms | ~35.2 ms |
+| YOLOv9-E | ~69.4 ms | ~224.8 ms |
+
+**YOLOv9-C at 320 is the recommended quality/performance balance.**
+C at 640 is also usable where the lower throughput is acceptable.
+
+Setup, model preparation, and compatibility details are available
+[in the frigate-xdna documentation](https://github.com/mitchins/frigate-xdna).
+
 ## What does Frigate use the CPU for and what does it use a detector for? (ELI5 Version)
 
 This is taken from a [user question on reddit](https://www.reddit.com/r/homeassistant/comments/q8mgau/comment/hgqbxh5/?utm_source=share&utm_medium=web2x&context=3). Modified slightly for clarity.

docs/docs/integrations/mqtt.md

@@ -11,6 +11,12 @@ MQTT requires a network connection to your broker. This is typically local, but
 
 :::
 
+:::note
+
+Wherever a topic below includes a camera, mask, or zone name, use its `ID` from the config, not its `friendly_name`. For example, a camera with `friendly_name: "Back Yard"` and ID `back_yard` publishes to `frigate/back_yard/...`, not `frigate/Back Yard/...`.
+
+:::
+
 ## General Frigate Topics
 
 ### `frigate/available`

docs/docs/plus/first_model.md

@@ -64,10 +64,10 @@ Frigate+ models generally have much higher scores than the default model provide
 <ConfigTabs>
 <TabItem value="ui">
 
-Navigate to <NavPath path="Settings > Global configuration > Objects" />. Under **Object filters**, set **Min Score** and **Threshold** for each object type, then click **Save**.
+Navigate to <NavPath path="Settings > Global configuration > Objects" />. Under **Object filters**, set **Minimum confidence** and **Confidence threshold** for each object type, then click **Save**.
 
-| Object            | Min Score | Threshold |
+| Object            | Minimum confidence | Confidence threshold |
-| ----------------- | --------- | --------- |
+| ----------------- | ------------------ | -------------------- |
 | **dog**           | .7                 | .9                   |
 | **cat**           | .65                | .8                   |
 | **face**          | .7                 |                      |

docs/docusaurus.config.ts

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

frigate/camera/activity_manager.py

@@ -103,12 +103,13 @@ class CameraActivityManager:
         all_objects: list[dict[str, Any]] = []
 
         for camera in new_activity.keys():
-            if camera not in self.config.cameras:
+            camera_config = self.config.cameras.get(camera)
+            if camera_config is None:
                 continue
 
             # handle cameras that were added dynamically
             if camera not in self.camera_all_object_counts:
-                self.__init_camera(self.config.cameras[camera])
+                self.__init_camera(camera_config)
 
             new_objects = new_activity[camera].get("objects", [])
             all_objects.extend(new_objects)
@@ -233,12 +234,13 @@ class AudioActivityManager:
         now = datetime.datetime.now().timestamp()
 
         for camera in new_activity.keys():
-            if camera not in self.config.cameras:
+            camera_config = self.config.cameras.get(camera)
+            if camera_config is None:
                 continue
 
             # handle cameras that were added dynamically
             if camera not in self.current_audio_detections:
-                self.__init_camera(self.config.cameras[camera])
+                self.__init_camera(camera_config)
 
             new_detections = new_activity[camera].get("detections", [])
             if self.compare_audio_activity(camera, new_detections, now):

frigate/db/sqlitevecq.py

@@ -1,8 +1,10 @@
 import logging
 import sqlite3
+import threading
 from typing import Any
 
 import regex
+from peewee import DatabaseError
 from playhouse.sqliteq import SqliteQueueDatabase
 
 logger = logging.getLogger(__name__)
@@ -17,6 +19,7 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
         self.load_vec_extension: bool = load_vec_extension
         # no extension necessary, sqlite will load correctly for each platform
         self.sqlite_vec_path = "/usr/local/lib/vec0"
+        self.upsert_lock = threading.Lock()
         super().__init__(*args, **kwargs)
 
     def _connect(self, *args: Any, **kwargs: Any) -> sqlite3.Connection:
@@ -53,6 +56,22 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
 
         conn.create_function("REGEXP", 2, regexp)
 
+    def execute_write(self, sql: str, params: Any = None) -> None:
+        """Run a write and wait for it, so that failures are raised here.
+
+        SqliteQueueDatabase hands non-SELECT statements to a writer thread and
+        stores any exception on the cursor it returns, so callers that ignore
+        that cursor never learn the write failed.
+        """
+        self.execute_sql(sql, params).fetchall()
+
+    def _table_exists(self, table: str) -> bool:
+        cursor = self.execute_sql(
+            "SELECT name FROM sqlite_master WHERE type = 'table' AND name = ?",
+            (table,),
+        )
+        return cursor.fetchone() is not None
+
     def _delete_embeddings(self, table: str, event_ids: list[str]) -> None:
         """Delete embeddings for the given events, if the table exists.
 
@@ -63,17 +82,17 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
             return
 
         # the embeddings tables are only created once semantic search has run
-        cursor = self.execute_sql(
+        if not self._table_exists(table):
-            "SELECT name FROM sqlite_master WHERE type = 'table' AND name = ?",
-            (table,),
-        )
-
-        if cursor.fetchone() is None:
             logger.debug("Skipping %s cleanup, table does not exist", table)
             return
 
         ids = ",".join(["?" for _ in event_ids])
-        self.execute_sql(f"DELETE FROM {table} WHERE id IN ({ids})", event_ids)
+
+        # callers treat cleanup as best effort, so log rather than propagate
+        try:
+            self.execute_write(f"DELETE FROM {table} WHERE id IN ({ids})", event_ids)
+        except DatabaseError:
+            logger.exception("Failed to delete embeddings from %s", table)
 
     def delete_embeddings_thumbnail(self, event_ids: list[str]) -> None:
         self._delete_embeddings("vec_thumbnails", event_ids)
@@ -81,25 +100,67 @@ class SqliteVecQueueDatabase(SqliteQueueDatabase):
     def delete_embeddings_description(self, event_ids: list[str]) -> None:
         self._delete_embeddings("vec_descriptions", event_ids)
 
+    def _restore_vec_info_table(self, table: str) -> None:
+        """Recreate the _info shadow table a legacy vec0 table is missing.
+
+        sqlite-vec added _info in 0.1.6 and drops it unconditionally when a
+        table is destroyed, so tables written by Frigate 0.17 and earlier fail
+        to drop. An empty stub is enough, and leaving it unseeded keeps the
+        table reading as pre-0.1.10 if the drop does not follow.
+        """
+        if not self._table_exists(table) or self._table_exists(f"{table}_info"):
+            return
+
+        logger.debug("Restoring the %s_info shadow table before dropping", table)
+        self.execute_write(
+            f'CREATE TABLE "{table}_info" (key TEXT PRIMARY KEY, value ANY)'
+        )
+
     def drop_embeddings_tables(self) -> None:
-        self.execute_sql("""
+        for table in ("vec_descriptions", "vec_thumbnails"):
-            DROP TABLE vec_descriptions;
+            self._restore_vec_info_table(table)
-        """)
+            self.execute_write(f"DROP TABLE IF EXISTS {table}")
-        self.execute_sql("""
-            DROP TABLE vec_thumbnails;
-        """)
 
     def create_embeddings_tables(self) -> None:
         """Create vec0 virtual table for embeddings"""
-        self.execute_sql("""
+        self.execute_write("""
             CREATE VIRTUAL TABLE IF NOT EXISTS vec_thumbnails USING vec0(
                 id TEXT PRIMARY KEY,
                 thumbnail_embedding FLOAT[768] distance_metric=cosine
             );
         """)
-        self.execute_sql("""
+        self.execute_write("""
             CREATE VIRTUAL TABLE IF NOT EXISTS vec_descriptions USING vec0(
                 id TEXT PRIMARY KEY,
                 description_embedding FLOAT[768] distance_metric=cosine
             );
         """)
+
+    def upsert_embeddings(
+        self, table: str, column: str, embeddings: dict[str, bytes]
+    ) -> None:
+        """Write embeddings for the given event ids, replacing any that exist.
+
+        vec0 implements neither REPLACE nor UPSERT, so rows that are already
+        there have to be deleted first.
+        """
+        if not embeddings:
+            return
+
+        event_ids = list(embeddings.keys())
+        ids = ",".join(["?" for _ in event_ids])
+        params: list[Any] = []
+
+        for event_id in event_ids:
+            params.extend((event_id, embeddings[event_id]))
+
+        values = ", ".join(["(?, ?)"] * len(event_ids))
+
+        # reindexing and live embedding run on separate threads, and each write
+        # is queued separately, so the delete and the insert have to be held
+        # together or an interleaved pair fails on the vec0 primary key
+        with self.upsert_lock:
+            self.execute_write(f"DELETE FROM {table} WHERE id IN ({ids})", event_ids)
+            self.execute_write(
+                f"INSERT INTO {table}(id, {column}) VALUES {values}", params
+            )

frigate/embeddings/embeddings.py

@@ -6,9 +6,10 @@ import logging
 import os
 import threading
 import time
+from typing import Any
 
 import numpy as np
-from peewee import DoesNotExist, IntegrityError
+from peewee import DatabaseError, DoesNotExist, IntegrityError
 from PIL import Image
 from playhouse.shortcuts import model_to_dict
 
@@ -207,12 +208,10 @@ class Embeddings:
         embedding = self.vision_embedding([thumbnail])[0]
 
         if upsert:
-            self.db.execute_sql(
+            self.db.upsert_embeddings(
-                """
+                "vec_thumbnails",
-                INSERT OR REPLACE INTO vec_thumbnails(id, thumbnail_embedding)
+                "thumbnail_embedding",
-                VALUES(?, ?)
+                {event_id: serialize(embedding)},
-                """,
-                (event_id, serialize(embedding)),
             )
 
         self.image_inference_speed.update(datetime.datetime.now().timestamp() - start)
@@ -251,19 +250,12 @@ class Embeddings:
         embeddings = self.vision_embedding(valid_thumbs)
 
         if upsert:
-            items = []
+            items = {}
             for i in range(len(valid_ids)):
-                items.append(valid_ids[i])
+                items[valid_ids[i]] = serialize(embeddings[i])
-                items.append(serialize(embeddings[i]))
                 self.image_eps.update()
 
-            self.db.execute_sql(
+            self.db.upsert_embeddings("vec_thumbnails", "thumbnail_embedding", items)
-                """
-                INSERT OR REPLACE INTO vec_thumbnails(id, thumbnail_embedding)
-                VALUES {}
-                """.format(", ".join(["(?, ?)"] * len(valid_ids))),
-                items,
-            )
 
         duration = datetime.datetime.now().timestamp() - start
         self.image_inference_speed.update(duration / len(valid_ids))
@@ -277,12 +269,10 @@ class Embeddings:
         embedding = self.text_embedding([description])[0]
 
         if upsert:
-            self.db.execute_sql(
+            self.db.upsert_embeddings(
-                """
+                "vec_descriptions",
-                INSERT OR REPLACE INTO vec_descriptions(id, description_embedding)
+                "description_embedding",
-                VALUES(?, ?)
+                {event_id: serialize(embedding)},
-                """,
-                (event_id, serialize(embedding)),
             )
 
         self.text_inference_speed.update(datetime.datetime.now().timestamp() - start)
@@ -302,19 +292,14 @@ class Embeddings:
 
         if upsert:
             ids = list(event_descriptions.keys())
-            items = []
+            items = {}
 
             for i in range(len(ids)):
-                items.append(ids[i])
+                items[ids[i]] = serialize(embeddings[i])
-                items.append(serialize(embeddings[i]))
                 self.text_eps.update()
 
-            self.db.execute_sql(
+            self.db.upsert_embeddings(
-                """
+                "vec_descriptions", "description_embedding", items
-                INSERT OR REPLACE INTO vec_descriptions(id, description_embedding)
-                VALUES {}
-                """.format(", ".join(["(?, ?)"] * len(ids))),
-                items,
             )
 
         self.text_inference_speed.update(datetime.datetime.now().timestamp() - start)
@@ -322,6 +307,17 @@ class Embeddings:
         return embeddings
 
     def reindex(self) -> None:
+        """Rebuild every tracked object embedding from scratch."""
+        totals: dict[str, Any] = {"status": "indexing"}
+
+        try:
+            self._reindex(totals)
+        except DatabaseError:
+            logger.exception("Unable to reindex tracked object embeddings")
+            totals["status"] = "failed"
+            self.requestor.send_data(UPDATE_EMBEDDINGS_REINDEX_PROGRESS, totals)
+
+    def _reindex(self, totals: dict[str, Any]) -> None:
         logger.info("Indexing tracked object embeddings...")
 
         self.db.drop_embeddings_tables()
@@ -346,14 +342,18 @@ class Embeddings:
             batch_size = 32
         current_page = 1
 
-        totals = {
+        totals.update(
+            {
                 "thumbnails": 0,
                 "descriptions": 0,
-            "processed_objects": total_events - 1 if total_events < batch_size else 0,
+                "processed_objects": total_events - 1
+                if total_events < batch_size
+                else 0,
                 "total_objects": total_events,
                 "time_remaining": 0 if total_events < batch_size else -1,
                 "status": "indexing",
             }
+        )
 
         self.requestor.send_data(UPDATE_EMBEDDINGS_REINDEX_PROGRESS, totals)
 

frigate/events/cleanup.py

@@ -365,6 +365,7 @@ class EventCleanup(threading.Thread):
                     chunk = ids_to_delete[i : i + CHUNK_SIZE]
                     logger.debug(f"Deleting {len(chunk)} events from the database")
                     Event.delete().where(Event.id << chunk).execute()
+                    Timeline.delete().where(Timeline.source_id << chunk).execute()
 
                     # embeddings are always cleaned up, even when semantic search
                     # is disabled, so that they don't outlive their events

frigate/stats/util.py

@@ -352,8 +352,9 @@ def stats_snapshot(
     total_camera_fps = total_process_fps = total_skipped_fps = total_detection_fps = 0
 
     stats["cameras"] = {}
-    for name, camera_stats in camera_metrics.items():
+    for name, camera_stats in list(camera_metrics.items()):
-        if name not in config.cameras:
+        camera_config = config.cameras.get(name)
+        if camera_config is None:
             continue
 
         total_camera_fps += camera_stats.camera_fps.value
@@ -370,7 +371,7 @@ def stats_snapshot(
         # Calculate connection quality based on current state
         # This is computed at stats-collection time so offline cameras
         # correctly show as unusable rather than excellent
-        expected_fps = config.cameras[name].detect.fps
+        expected_fps = camera_config.detect.fps
         current_fps = camera_stats.camera_fps.value
         reconnects = camera_stats.reconnects_last_hour.value
         stalls = camera_stats.stalls_last_hour.value
@@ -398,7 +399,7 @@ def stats_snapshot(
             "process_fps": round(camera_stats.process_fps.value, 2),
             "skipped_fps": round(camera_stats.skipped_fps.value, 2),
             "detection_fps": round(camera_stats.detection_fps.value, 2),
-            "detection_enabled": config.cameras[name].detect.enabled,
+            "detection_enabled": camera_config.detect.enabled,
             "pid": pid,
             "capture_pid": capture_pid,
             "ffmpeg_pid": ffmpeg_pid,

frigate/test/test_sqlitevecq_embeddings.py

@@ -1,16 +1,24 @@
-"""Tests for embedding cleanup on the main Frigate database.
+"""Tests for embedding storage and cleanup on the main Frigate database.
 
 Embeddings are deleted whether or not semantic search is currently enabled, so
 the delete path has to tolerate databases where the vec0 tables were never
 created and installs where the sqlite-vec extension is unavailable.
+
+The write paths need the real extension, since the behavior under test belongs
+to vec0 itself, so those tests are skipped when it is not installed.
 """
 
 import os
+import struct
 import tempfile
 import unittest
 
+from peewee import OperationalError
+
 from frigate.db.sqlitevecq import SqliteVecQueueDatabase
 
+VEC_EXTENSION_PATH = "/usr/local/lib/vec0.so"
+
 
 class TestDeleteEmbeddings(unittest.TestCase):
     def setUp(self) -> None:
@@ -52,6 +60,21 @@ class TestDeleteEmbeddings(unittest.TestCase):
 
         self.assertEqual(self._thumbnail_ids(), ["b"])
 
+    def test_delete_failure_is_logged_not_raised(self) -> None:
+        self._create_thumbnails_table()
+        self.db.execute_sql(
+            """
+            CREATE TRIGGER vec_thumbnails_no_delete BEFORE DELETE ON vec_thumbnails
+            BEGIN SELECT RAISE(ABORT, 'delete blocked'); END
+            """
+        ).fetchall()
+
+        with self.assertLogs("frigate.db.sqlitevecq", level="ERROR") as logs:
+            self.db.delete_embeddings_thumbnail(event_ids=["a"])
+
+        self.assertIn("Failed to delete embeddings", logs.output[0])
+        self.assertEqual(self._thumbnail_ids(), ["a", "b"])
+
     def test_delete_skipped_without_extension(self) -> None:
         self._create_thumbnails_table()
         self.db.load_vec_extension = False
@@ -61,3 +84,104 @@ class TestDeleteEmbeddings(unittest.TestCase):
 
         # the vec0 tables cannot be written without the extension
         self.assertEqual(self._thumbnail_ids(), ["a", "b"])
+
+
+def _vector(value: float) -> bytes:
+    return struct.pack("768f", *([value] * 768))
+
+
+@unittest.skipUnless(
+    os.path.exists(VEC_EXTENSION_PATH), "sqlite-vec extension is not installed"
+)
+class TestEmbeddingsTableWrites(unittest.TestCase):
+    """Covers the vec0 writes behind semantic search reindexing."""
+
+    def setUp(self) -> None:
+        self.tmp_dir = tempfile.TemporaryDirectory()
+        self.db = SqliteVecQueueDatabase(
+            os.path.join(self.tmp_dir.name, "test.db"), load_vec_extension=True
+        )
+        self.db.start()
+        self.db.create_embeddings_tables()
+
+    def tearDown(self) -> None:
+        self.db.stop()
+        self.db.close()
+        self.tmp_dir.cleanup()
+
+    def _vec_tables(self) -> list[str]:
+        return [
+            row[0]
+            for row in self.db.execute_sql(
+                "SELECT name FROM sqlite_master WHERE name LIKE 'vec_%' ORDER BY name"
+            )
+        ]
+
+    def _make_legacy(self, table: str) -> None:
+        # sqlite-vec added the _info shadow table in 0.1.6, so tables written by
+        # Frigate 0.17 and earlier do not have one
+        self.db.execute_sql(f"DROP TABLE {table}_info").fetchall()
+
+    def _stored(self, table: str, column: str, event_id: str) -> str | None:
+        row = self.db.execute_sql(
+            f"SELECT vec_to_json({column}) FROM {table} WHERE id = ?", (event_id,)
+        ).fetchone()
+        return row[0] if row else None
+
+    def test_write_error_is_raised(self) -> None:
+        # queued writes hide their exception in the returned cursor
+        with self.assertRaises(OperationalError):
+            self.db.execute_write("INSERT INTO vec_missing(id) VALUES ('a')")
+
+    def test_drop_tables_removes_legacy_tables(self) -> None:
+        self._make_legacy("vec_thumbnails")
+        self._make_legacy("vec_descriptions")
+
+        self.db.drop_embeddings_tables()
+
+        self.assertEqual(self._vec_tables(), [])
+
+    def test_drop_tables_without_any_tables_does_not_raise(self) -> None:
+        self.db.drop_embeddings_tables()
+
+        self.db.drop_embeddings_tables()
+
+    def test_upsert_replaces_existing_embedding(self) -> None:
+        self.db.upsert_embeddings(
+            "vec_thumbnails", "thumbnail_embedding", {"evt1": _vector(0.01)}
+        )
+
+        self.db.upsert_embeddings(
+            "vec_thumbnails", "thumbnail_embedding", {"evt1": _vector(0.99)}
+        )
+
+        stored = self._stored("vec_thumbnails", "thumbnail_embedding", "evt1")
+        self.assertTrue(stored.startswith("[0.990000"), stored)
+
+    def test_upsert_keeps_one_row_per_event(self) -> None:
+        for _ in range(3):
+            self.db.upsert_embeddings(
+                "vec_descriptions", "description_embedding", {"evt1": _vector(0.5)}
+            )
+
+        count = self.db.execute_sql(
+            "SELECT count(*) FROM vec_descriptions WHERE id = 'evt1'"
+        ).fetchone()[0]
+        self.assertEqual(count, 1)
+
+    def test_reindex_cycle_rewrites_legacy_tables(self) -> None:
+        """The 0.18 upgrade path: old vectors in, new vectors out."""
+        self.db.upsert_embeddings(
+            "vec_thumbnails", "thumbnail_embedding", {"evt1": _vector(0.01)}
+        )
+        self._make_legacy("vec_thumbnails")
+        self._make_legacy("vec_descriptions")
+
+        self.db.drop_embeddings_tables()
+        self.db.create_embeddings_tables()
+        self.db.upsert_embeddings(
+            "vec_thumbnails", "thumbnail_embedding", {"evt1": _vector(0.99)}
+        )
+
+        stored = self._stored("vec_thumbnails", "thumbnail_embedding", "evt1")
+        self.assertTrue(stored.startswith("[0.990000"), stored)

frigate/test/test_timeline.py

@@ -0,0 +1,66 @@
+import unittest
+from unittest.mock import MagicMock, patch
+
+from frigate.events.types import EventStateEnum
+from frigate.models import Timeline
+from frigate.timeline import TimelineProcessor
+
+
+def make_event(has_clip: bool, has_snapshot: bool) -> dict:
+    return {
+        "id": "event-1",
+        "frame_time": 1000.0,
+        "box": [0, 0, 10, 10],
+        "region": [0, 0, 100, 100],
+        "label": "car",
+        "sub_label": None,
+        "score": 0.8,
+        "has_clip": has_clip,
+        "has_snapshot": has_snapshot,
+        "current_zones": [],
+        "stationary": False,
+        "attributes": {},
+        "current_attributes": [],
+    }
+
+
+class TestTimelineProcessor(unittest.TestCase):
+    def setUp(self):
+        camera_config = MagicMock()
+        camera_config.detect.width = 1280
+        camera_config.detect.height = 720
+        config = MagicMock()
+        config.cameras.get.return_value = camera_config
+        self.processor = TimelineProcessor(config, MagicMock(), MagicMock())
+
+    @patch.object(Timeline, "insert")
+    def test_unsaved_event_writes_no_timeline_rows(self, insert):
+        event = make_event(has_clip=False, has_snapshot=False)
+        self.processor.handle_object_detection(
+            "front", EventStateEnum.start, None, event
+        )
+        self.processor.handle_object_detection(
+            "front", EventStateEnum.end, event, event
+        )
+
+        insert.assert_not_called()
+        self.assertEqual(self.processor.pre_event_cache, {})
+
+    @patch.object(Timeline, "insert")
+    def test_cached_entries_flush_when_event_is_saved(self, insert):
+        start = make_event(has_clip=False, has_snapshot=False)
+        self.processor.handle_object_detection(
+            "front", EventStateEnum.start, None, start
+        )
+        insert.assert_not_called()
+
+        end = make_event(has_clip=True, has_snapshot=False)
+        self.processor.handle_object_detection("front", EventStateEnum.end, start, end)
+
+        class_types = [c.args[0][Timeline.class_type] for c in insert.call_args_list]
+        self.assertEqual(class_types, ["visible", "gone"])
+        self.assertEqual(self.processor.pre_event_cache, {})
+
+
+if __name__ == "__main__":
+    unittest.main()

frigate/timeline.py

@@ -191,6 +191,9 @@ class TimelineProcessor(threading.Thread):
             timeline_entry[Timeline.class_type] = "gone"
             self.insert_or_save(timeline_entry, prev_event_data, event_data)
 
+            # drop entries for events that ended without being saved
+            self.pre_event_cache.pop(event_id, None)
+
     def handle_api_entry(
         self,
         camera: str,

frigate/track/object_processing.py

@@ -24,6 +24,7 @@ from frigate.comms.event_metadata_updater import (
 from frigate.comms.events_updater import EventEndSubscriber, EventUpdatePublisher
 from frigate.comms.inter_process import InterProcessRequestor
 from frigate.config import (
+    CameraConfig,
     CameraMqttConfig,
     FrigateConfig,
     RecordConfig,
@@ -128,8 +129,10 @@ class TrackedObjectProcessor(threading.Thread):
             )
 
         def update(camera: str, obj: TrackedObject, frame_name: str) -> None:
-            obj.has_snapshot = self.should_save_snapshot(camera, obj)
+            obj.has_snapshot = self.should_save_snapshot(
-            obj.has_clip = self.should_retain_recording(camera, obj)
+                camera_state.camera_config, obj
+            )
+            obj.has_clip = self.should_retain_recording(camera_state.camera_config, obj)
             after = obj.to_dict()
             message = {
                 "before": obj.previous,
@@ -153,8 +156,10 @@ class TrackedObjectProcessor(threading.Thread):
 
         def end(camera: str, obj: TrackedObject, frame_name: str) -> None:
             # populate has_snapshot
-            obj.has_snapshot = self.should_save_snapshot(camera, obj)
+            obj.has_snapshot = self.should_save_snapshot(
-            obj.has_clip = self.should_retain_recording(camera, obj)
+                camera_state.camera_config, obj
+            )
+            obj.has_clip = self.should_retain_recording(camera_state.camera_config, obj)
 
             # write thumbnail to disk if it will be saved as an event
             if obj.has_snapshot or obj.has_clip:
@@ -184,8 +189,8 @@ class TrackedObjectProcessor(threading.Thread):
             )
 
         def snapshot(camera: str, obj: TrackedObject) -> bool:
-            mqtt_config: CameraMqttConfig = self.config.cameras[camera].mqtt
+            mqtt_config: CameraMqttConfig = camera_state.camera_config.mqtt
-            if mqtt_config.enabled and self.should_mqtt_snapshot(camera, obj):
+            if mqtt_config.enabled and self.should_mqtt_snapshot(mqtt_config, obj):
                 jpg_bytes, _ = obj.get_img_bytes(
                     ext="jpg",
                     timestamp=mqtt_config.timestamp,
@@ -238,11 +243,13 @@ class TrackedObjectProcessor(threading.Thread):
         camera_state.on("camera_activity", camera_activity)
         self.camera_states[camera] = camera_state
 
-    def should_save_snapshot(self, camera: str, obj: TrackedObject) -> bool:
+    def should_save_snapshot(
+        self, camera_config: CameraConfig, obj: TrackedObject
+    ) -> bool:
         if obj.false_positive:
             return False
 
-        snapshot_config: SnapshotsConfig = self.config.cameras[camera].snapshots
+        snapshot_config: SnapshotsConfig = camera_config.snapshots
 
         if not snapshot_config.enabled:
             return False
@@ -261,11 +268,13 @@ class TrackedObjectProcessor(threading.Thread):
 
         return True
 
-    def should_retain_recording(self, camera: str, obj: TrackedObject) -> bool:
+    def should_retain_recording(
+        self, camera_config: CameraConfig, obj: TrackedObject
+    ) -> bool:
         if obj.false_positive:
             return False
 
-        record_config: RecordConfig = self.config.cameras[camera].record
+        record_config: RecordConfig = camera_config.record
 
         # Recording is disabled
         if not record_config.enabled:
@@ -281,13 +290,15 @@ class TrackedObjectProcessor(threading.Thread):
 
         return True
 
-    def should_mqtt_snapshot(self, camera: str, obj: TrackedObject) -> bool:
+    def should_mqtt_snapshot(
+        self, mqtt_config: CameraMqttConfig, obj: TrackedObject
+    ) -> bool:
         # object never changed position
         if obj.is_stationary():
             return False
 
         # if there are required zones and there is no overlap
-        required_zones = self.config.cameras[camera].mqtt.required_zones
+        required_zones = mqtt_config.required_zones
         if len(required_zones) > 0 and not set(obj.entered_zones) & set(required_zones):
             logger.debug(
                 f"Not sending mqtt for {obj.obj_data['id']} because it did not enter required zones"
@@ -297,7 +308,11 @@ class TrackedObjectProcessor(threading.Thread):
         return True
 
     def update_mqtt_motion(
-        self, camera: str, frame_time: float, motion_boxes: list
+        self,
+        camera: str,
+        camera_config: CameraConfig,
+        frame_time: float,
+        motion_boxes: list,
     ) -> None:
         # publish if motion is currently being detected
         if motion_boxes:
@@ -312,7 +327,7 @@ class TrackedObjectProcessor(threading.Thread):
             # always updated latest motion
             self.last_motion_detected[camera] = frame_time
         elif self.last_motion_detected.get(camera, 0) > 0:
-            mqtt_delay = self.config.cameras[camera].motion.mqtt_off_delay
+            mqtt_delay = camera_config.motion.mqtt_off_delay
 
             # If no motion, make sure the off_delay has passed
             if frame_time - self.last_motion_detected.get(camera, 0) >= mqtt_delay:
@@ -783,7 +798,7 @@ class TrackedObjectProcessor(threading.Thread):
                 frame_name, frame_time, current_tracked_objects, motion_boxes, regions
             )
 
-            self.update_mqtt_motion(camera, frame_time, motion_boxes)
+            self.update_mqtt_motion(camera, camera_config, frame_time, motion_boxes)
 
             tracked_objects = [
                 o.to_dict() for o in camera_state.tracked_objects.values()

frigate/video/ffmpeg.py

@@ -34,6 +34,8 @@ from frigate.util.process import FrigateProcess
 
 logger = logging.getLogger(__name__)
 
+RECORD_GRACE_SECONDS = 90
+
 
 def capture_frames(
     ffmpeg_process: sp.Popen[Any],
@@ -164,6 +166,7 @@ class CameraWatchdog(threading.Thread):
         self.latest_invalid_segment_time: float = 0
         self.latest_cache_segment_time: float = 0
         self.record_enable_time: datetime | None = None
+        self.record_grace_until: datetime | None = None
 
         # `valid` segments are published with the segment's start time, so the
         # gap between consecutive publishes can reach 2 * segment_time. Pad the
@@ -280,6 +283,7 @@ class CameraWatchdog(threading.Thread):
                 self.latest_valid_segment_time = 0
                 self.latest_invalid_segment_time = 0
                 self.latest_cache_segment_time = 0
+                self.record_grace_until = None
                 self.record_enable_time = datetime.now().astimezone(UTC)
                 last_restart_time = datetime.now().timestamp()
                 continue
@@ -294,6 +298,7 @@ class CameraWatchdog(threading.Thread):
                     self.latest_valid_segment_time = 0
                     self.latest_invalid_segment_time = 0
                     self.latest_cache_segment_time = 0
+                    self.record_grace_until = None
                     self.record_enable_time = datetime.now().astimezone(UTC)
                 else:
                     self.logger.debug(f"Disabling camera {self.config.name}")
@@ -318,6 +323,7 @@ class CameraWatchdog(threading.Thread):
                     self.latest_valid_segment_time = 0
                     self.latest_invalid_segment_time = 0
                     self.latest_cache_segment_time = 0
+                    self.record_grace_until = None
                     self.record_enable_time = datetime.now().astimezone(UTC)
                     last_restart_time = datetime.now().timestamp()
                 self.was_record_enabled_in_config = record_enabled_in_config
@@ -404,11 +410,16 @@ class CameraWatchdog(threading.Thread):
                 if self.config.record.enabled and "record" in p["roles"]:
                     now_utc = datetime.now().astimezone(UTC)
 
-                    # Check if we're within the grace period after enabling recording
+                    # ffmpeg needs time to create a first segment after
-                    # Grace period: 90 seconds allows time for ffmpeg to start and create first segment
+                    # recording is enabled and after a restart
-                    in_grace_period = self.record_enable_time is not None and (
+                    in_grace_period = (
-                        now_utc - self.record_enable_time
+                        self.record_enable_time is not None
-                    ) < timedelta(seconds=90)
+                        and (now_utc - self.record_enable_time)
+                        < timedelta(seconds=RECORD_GRACE_SECONDS)
+                    ) or (
+                        self.record_grace_until is not None
+                        and now_utc < self.record_grace_until
+                    )
 
                     latest_cache_dt = (
                         datetime.fromtimestamp(self.latest_cache_segment_time, tz=UTC)
@@ -445,8 +456,9 @@ class CameraWatchdog(threading.Thread):
                         <= self.latest_invalid_segment_time
                     )
                     invalid_stale = invalid_stale_condition
+                    stale = cache_stale or valid_stale or invalid_stale
 
-                    if cache_stale or valid_stale or invalid_stale:
+                    if stale and can_restart:
                         if cache_stale:
                             reason = "No new recording segments were created"
                         elif valid_stale:
@@ -471,8 +483,13 @@ class CameraWatchdog(threading.Thread):
                                 f"{self.config.name}/status/{role.value}", "offline"
                             )
 
+                        self.record_grace_until = now_utc + timedelta(
+                            seconds=RECORD_GRACE_SECONDS
+                        )
+                        last_restart_time = now
+
                         continue
-                    else:
+                    elif not stale:
                         self._send_record_status("online", now)
                         p["latest_segment_time"] = self.latest_cache_segment_time
 

web/e2e/specs/explore.spec.ts

@@ -216,6 +216,18 @@ test.describe("Explore — content @high", () => {
 // Similarity search URL param
 // ---------------------------------------------------------------------------
 
+test.describe("Explore: back button @high", () => {
+  test("direct visits do not show a back button", async ({ frigateApp }) => {
+    await frigateApp.goto("/explore?labels=person");
+    await expect(frigateApp.page.getByLabel("Labels").first()).toBeVisible({
+      timeout: 10_000,
+    });
+    await expect(
+      frigateApp.page.getByRole("button", { name: "Go back" }),
+    ).toHaveCount(0);
+  });
+});
+
 test.describe("Explore — similarity search (desktop) @high", () => {
   test.skip(
     ({ frigateApp }) => frigateApp.isMobile,

web/e2e/specs/face-library.spec.ts

@@ -30,10 +30,7 @@ function groupedFacesMock() {
   });
 }
 
-async function installGroupedFaces(app: FrigateApp) {
+const GROUPED_EVENT = {
-  await app.api.install({
-    events: [
-      {
   id: GROUPED_EVENT_ID,
   label: "person",
   sub_label: null,
@@ -60,10 +57,24 @@ async function installGroupedFaces(app: FrigateApp) {
     type: "object",
     path_data: [],
   },
-      },
+};
-    ],
+
+async function installGroupedFaces(
+  app: FrigateApp,
+  opts: { withEventIds?: boolean } = {},
+) {
+  await app.api.install({
+    events: [GROUPED_EVENT],
     faces: groupedFacesMock(),
   });
+
+  // api-mocker does not cover /api/event_ids, which the card needs to link to
+  // Explore. Registered after install so it takes precedence.
+  if (opts.withEventIds) {
+    await app.page.route("**/api/event_ids**", (route) =>
+      route.fulfill({ json: [GROUPED_EVENT] }),
+    );
+  }
 }
 
 async function openGroupedFaceDialog(app: FrigateApp): Promise<Locator> {
@@ -512,6 +523,34 @@ test.describe("FaceSelectionDialog @high", () => {
   });
 });
 
+test.describe("Face Library: return from Explore @high", () => {
+  test("Explore back button returns to an outlined collection", async ({
+    frigateApp,
+  }) => {
+    await installGroupedFaces(frigateApp, { withEventIds: true });
+    await frigateApp.goto("/faces");
+
+    // Mobile opens the collection as a MobilePage, which has no dialog role
+    const card = frigateApp.page
+      .locator('img[src*="clips/faces/train/"]')
+      .first()
+      .locator("xpath=..");
+    await card.click();
+    await frigateApp.page.getByLabel("View in Explore").click();
+    await expect(frigateApp.page).toHaveURL(
+      new RegExp(`/explore\\?event_id=${GROUPED_EVENT_ID}`),
+    );
+
+    const back = frigateApp.page.getByRole("button", { name: "Go back" });
+    await expect(back).toBeVisible({ timeout: 5_000 });
+    await back.click();
+    await expect(frigateApp.page).toHaveURL(/\/faces/);
+
+    await expect(card).toHaveClass(/outline-selected/, { timeout: 5_000 });
+    await expect(card).not.toHaveClass(/outline-selected/, { timeout: 5_000 });
+  });
+});
+
 test.describe("Face Library — mobile @high @mobile", () => {
   test.skip(({ frigateApp }) => !frigateApp.isMobile, "Mobile-only");
 

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

@@ -233,6 +233,7 @@
     "detectHighCpuUsage": "{{camera}} has high detect CPU usage ({{detectAvg}}%)",
     "healthy": "System is healthy",
     "reindexingEmbeddings": "Reindexing embeddings ({{processed}}% complete)",
+    "reindexEmbeddingsFailed": "Reindexing embeddings failed, check the logs",
     "cameraIsOffline": "{{camera}} is offline",
     "detectIsSlow": "{{detect}} is slow ({{speed}} ms)",
     "detectIsVerySlow": "{{detect}} is very slow ({{speed}} ms)",

web/src/components/Statusbar.tsx

@@ -71,8 +71,9 @@ export default function Statusbar() {
 
   useEffect(() => {
     if (reindexState) {
-      if (reindexState.status == "indexing") {
       clearMessages("embeddings-reindex");
+
+      if (reindexState.status === "indexing") {
         addMessage(
           "embeddings-reindex",
           t("stats.reindexingEmbeddings", {
@@ -82,9 +83,8 @@ export default function Statusbar() {
             ),
           }),
         );
-      }
+      } else if (reindexState.status === "failed") {
-      if (reindexState.status === "completed") {
+        addMessage("embeddings-reindex", t("stats.reindexEmbeddingsFailed"));
-        clearMessages("embeddings-reindex");
       }
     }
   }, [reindexState, addMessage, clearMessages, t]);

web/src/components/card/ClassificationCard.tsx

@@ -1,12 +1,20 @@
 import { baseUrl } from "@/api/baseUrl";
 import useContextMenu from "@/hooks/use-contextmenu";
+import { useOverlayState } from "@/hooks/use-overlay-state";
 import { cn } from "@/lib/utils";
 import {
   ClassificationItemData,
   ClassificationThreshold,
   ClassifiedEvent,
 } from "@/types/classification";
-import { forwardRef, useEffect, useMemo, useRef, useState } from "react";
+import {
+  forwardRef,
+  useEffect,
+  useImperativeHandle,
+  useMemo,
+  useRef,
+  useState,
+} from "react";
 import { isDesktop, isIOS, isMobile, isMobileOnly } from "react-device-detect";
 import { useTranslation } from "react-i18next";
 import TimeAgo from "../dynamic/TimeAgo";
@@ -16,6 +24,7 @@ import { LuSearch, LuInfo } from "react-icons/lu";
 import { TooltipPortal } from "@radix-ui/react-tooltip";
 import { useNavigate } from "react-router-dom";
 import { HiSquare2Stack } from "react-icons/hi2";
+import scrollIntoView from "scroll-into-view-if-needed";
 import { ImageShadowOverlay } from "../overlay/ImageShadowOverlay";
 import {
   Dialog,
@@ -85,9 +94,14 @@ export const ClassificationCard = forwardRef<
 
   // interaction
 
+  const cardRef = useRef<HTMLDivElement | null>(null);
   const imgRef = useRef<HTMLImageElement | null>(null);
 
-  useContextMenu(imgRef, () => {
+  useImperativeHandle(ref, () => cardRef.current!);
+
+  // Listen on the whole card, since overlays cover most of the image
+
+  useContextMenu(cardRef, () => {
     onClick(data, true);
   });
 
@@ -101,9 +115,9 @@ export const ClassificationCard = forwardRef<
 
   return (
     <div
-      ref={ref}
+      ref={cardRef}
       className={cn(
-        "relative flex size-full flex-col overflow-hidden rounded-lg outline outline-[3px]",
+        "relative flex size-full select-none flex-col overflow-hidden rounded-lg outline outline-[3px]",
         className,
         selected
           ? "shadow-selected outline-selected"
@@ -117,11 +131,7 @@ export const ClassificationCard = forwardRef<
         }
         onClick(data, isMeta);
       }}
-      onContextMenu={(e) => {
+      style={isIOS ? { WebkitTouchCallout: "none" } : undefined}
-        e.preventDefault();
-        e.stopPropagation();
-        onClick(data, true);
-      }}
     >
       <img
         ref={imgRef}
@@ -130,14 +140,6 @@ export const ClassificationCard = forwardRef<
           imgClassName,
           isMobile && "w-full",
         )}
-        style={
-          isIOS
-            ? {
-                WebkitUserSelect: "none",
-                WebkitTouchCallout: "none",
-              }
-            : undefined
-        }
         draggable={false}
         loading="lazy"
         onLoad={() => setImageLoaded(true)}
@@ -156,7 +158,7 @@ export const ClassificationCard = forwardRef<
         </div>
       )}
       <div className="absolute bottom-0 left-0 right-0 h-[50%] bg-gradient-to-t from-black/60 to-transparent" />
-      <div className="absolute bottom-0 flex w-full select-none flex-row items-center justify-between gap-2 p-2">
+      <div className="absolute bottom-0 flex w-full flex-row items-center justify-between gap-2 p-2">
         <div
           className={cn(
             "flex flex-col items-start text-white",
@@ -216,6 +218,41 @@ export function GroupedClassificationCard({
   const { t } = useTranslation(["views/explore", i18nLibrary]);
   const [detailOpen, setDetailOpen] = useState(false);
 
+  // Explore stores this event in history state so going back can point out the
+  // card the user came from
+
+  const cardRef = useRef<HTMLDivElement | null>(null);
+  const [returnEventId, setReturnEventId] = useOverlayState<string | undefined>(
+    "returnEventId",
+  );
+  const [highlighted, setHighlighted] = useState(false);
+
+  useEffect(() => {
+    if (!returnEventId || classifiedEvent?.id !== returnEventId) {
+      return;
+    }
+
+    setReturnEventId(undefined, true);
+    setHighlighted(true);
+  }, [classifiedEvent?.id, returnEventId, setReturnEventId]);
+
+  useEffect(() => {
+    if (!highlighted) {
+      return;
+    }
+
+    if (cardRef.current) {
+      scrollIntoView(cardRef.current, {
+        block: "center",
+        behavior: "smooth",
+        scrollMode: "if-needed",
+      });
+    }
+
+    const timeout = setTimeout(() => setHighlighted(false), 3000);
+    return () => clearTimeout(timeout);
+  }, [highlighted]);
+
   // If the component unmounts while the detail overlay is open, we need to
   // pop the history state that was pushed by useHistoryBack, otherwise it
   // leaves a stale entry that breaks back navigation.
@@ -308,9 +345,10 @@ export function GroupedClassificationCard({
   return (
     <>
       <ClassificationCard
+        ref={cardRef}
         data={bestItem}
         threshold={threshold}
-        selected={selectedItems.includes(bestItem.filename)}
+        selected={highlighted || selectedItems.includes(bestItem.filename)}
         clickable={true}
         i18nLibrary={i18nLibrary}
         count={group.length}
@@ -404,13 +442,19 @@ export function GroupedClassificationCard({
                     isMobile && "absolute right-4 top-8",
                   )}
                 >
-                  <Tooltip>
+                  <Tooltip open={isDesktop ? undefined : false}>
                     <TooltipTrigger asChild>
                       <div
                         className="cursor-pointer"
                         tabIndex={-1}
+                        aria-label={t("details.item.button.viewInExplore", {
+                          ns: "views/explore",
+                        })}
                         onClick={() => {
-                          navigate(`/explore?event_id=${classifiedEvent.id}`);
+                          setReturnEventId(classifiedEvent.id, true);
+                          navigate(`/explore?event_id=${classifiedEvent.id}`, {
+                            state: { canGoBack: true },
+                          });
                         }}
                       >
                         <LuSearch className="size-4 text-secondary-foreground" />

web/src/components/navigation/Bottombar.tsx

@@ -133,8 +133,9 @@ function StatusAlertNav({ className, large }: StatusAlertNavProps) {
 
   useEffect(() => {
     if (reindexState) {
-      if (reindexState.status == "indexing") {
       clearMessages("embeddings-reindex");
+
+      if (reindexState.status === "indexing") {
         addMessage(
           "embeddings-reindex",
           t("stats.reindexingEmbeddings", {
@@ -144,9 +145,8 @@ function StatusAlertNav({ className, large }: StatusAlertNavProps) {
             ),
           }),
         );
-      }
+      } else if (reindexState.status === "failed") {
-      if (reindexState.status === "completed") {
+        addMessage("embeddings-reindex", t("stats.reindexEmbeddingsFailed"));
-        clearMessages("embeddings-reindex");
       }
     }
   }, [reindexState, addMessage, clearMessages, t]);

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

@@ -845,6 +845,7 @@ export function TrackingDetails({
                       <div className="text-sm text-secondary-foreground">
                         <Link
                           to={`/explore?recognized_license_plate=${event.data.recognized_license_plate}`}
+                          state={{ canGoBack: true }}
                           className="text-sm"
                         >
                           {event.data.recognized_license_plate}

web/src/components/timeline/DetailStream.tsx

@@ -727,6 +727,7 @@ function EventList({
                     <div className="text-sm text-secondary-foreground">
                       <Link
                         to={`/explore?recognized_license_plate=${event.data.recognized_license_plate}`}
+                        state={{ canGoBack: true }}
                         className="text-sm"
                       >
                         {event.data.recognized_license_plate}

web/src/components/timeline/EventMenu.tsx

@@ -135,7 +135,9 @@ export default function EventMenu({
             <DropdownMenuItem
               className="cursor-pointer"
               onSelect={() => {
-                navigate(`/explore?event_id=${event.id}`);
+                navigate(`/explore?event_id=${event.id}`, {
+                  state: { canGoBack: true },
+                });
               }}
             >
               {t("details.item.button.viewInExplore")}
@@ -177,6 +179,7 @@ export default function EventMenu({
                   else
                     navigate(
                       `/explore?search_type=similarity&event_id=${event.id}`,
+                      { state: { canGoBack: true } },
                     );
                 }}
               >

web/src/views/search/SearchView.tsx

@@ -9,7 +9,7 @@ import { cn } from "@/lib/utils";
 import { FrigateConfig } from "@/types/frigateConfig";
 import { SearchFilter, SearchResult, SearchSource } from "@/types/search";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
-import { isMobileOnly } from "react-device-detect";
+import { isDesktop, isMobileOnly } from "react-device-detect";
 import { LuImage, LuSearchX, LuText } from "react-icons/lu";
 import useSWR from "swr";
 import ExploreView from "../explore/ExploreView";
@@ -32,7 +32,9 @@ import { TooltipPortal } from "@radix-ui/react-tooltip";
 import SearchActionGroup from "@/components/filter/SearchActionGroup";
 import { Trans, useTranslation } from "react-i18next";
 import { use24HourTime } from "@/hooks/use-date-utils";
-import { useNavigate } from "react-router-dom";
+import { useLocation, useNavigate } from "react-router-dom";
+import { Button } from "@/components/ui/button";
+import { IoMdArrowRoundBack } from "react-icons/io";
 import { useAllowedCameras } from "@/hooks/use-allowed-cameras";
 
 type SearchViewProps = {
@@ -80,6 +82,10 @@ export default function SearchView({
   });
   const is24Hour = use24HourTime(config);
   const navigate = useNavigate();
+  const location = useLocation();
+
+  // set by in-app links, since an iOS home screen app has no back gesture
+  const canGoBack = location.state?.canGoBack === true;
 
   const { data: exploreEvents } = useSWR<SearchResult[]>(
     (!searchFilter || Object.keys(searchFilter).length === 0) &&
@@ -535,8 +541,28 @@ export default function SearchView({
           isMobileOnly && "mb-2 h-auto flex-wrap gap-2 space-y-0",
         )}
       >
+        {(canGoBack || config?.semantic_search?.enabled) && (
+          <div
+            className={cn(
+              "z-[41] flex w-full flex-row items-start gap-2 lg:absolute lg:top-0 lg:w-1/3",
+            )}
+          >
+            {canGoBack && (
+              <Button
+                className="flex shrink-0 items-center gap-2.5 rounded-lg"
+                aria-label={t("label.back", { ns: "common" })}
+                onClick={() => navigate(-1)}
+              >
+                <IoMdArrowRoundBack className="size-5 text-secondary-foreground" />
+                {isDesktop && (
+                  <div className="text-primary">
+                    {t("button.back", { ns: "common" })}
+                  </div>
+                )}
+              </Button>
+            )}
             {config?.semantic_search?.enabled && (
-          <div className={cn("z-[41] w-full lg:absolute lg:top-0 lg:w-1/3")}>
+              <div className="min-w-0 flex-1">
                 <InputWithTags
                   inputFocused={inputFocused}
                   setInputFocused={setInputFocused}
@@ -548,6 +574,8 @@ export default function SearchView({
                 />
               </div>
             )}
+          </div>
+        )}
 
         {hasExistingSearch && (
           <ScrollArea className="w-full whitespace-nowrap lg:ml-[35%]">

web/src/views/settings/TriggerView.tsx

@@ -574,6 +574,7 @@ export default function TriggerView({
                               </Badge>
                               <Link
                                 to={`/explore?event_id=${trigger_status?.triggers[trigger.name]?.triggering_event_id || ""}`}
+                                state={{ canGoBack: true }}
                                 className={cn(
                                   "flex items-center gap-1.5 text-xs text-muted-foreground",
                                   !trigger_status?.triggers[trigger.name]
@@ -735,6 +736,7 @@ export default function TriggerView({
                             <TableCell>
                               <Link
                                 to={`/explore?event_id=${trigger_status?.triggers[trigger.name]?.triggering_event_id || ""}`}
+                                state={{ canGoBack: true }}
                                 className={cn(
                                   "flex items-center gap-1.5 text-sm",
                                   !trigger_status?.triggers[trigger.name]