Merge 438df7d48429dc400ad7ac1c4223d9354e28c419 into fbf4388b378c8a3fd723c714a71019ab9286c4d0

* don't flatten the search result cache when updating

this would cause an infinite swr fetch if something was mutated and then fetch was called again

* Properly sort keys for recording summary in StorageMetrics

* tracked object description box tweaks

* Remove ability to right click on elements inside of face popup

* Update reprocess message

* don't show object track until video metadata is loaded

* fix blue line height calc for in progress events

* Use timeline tab by default for notifications but add a query arg for customization

* Try and improve notification opening behavior

* Reduce review item buffering behavior

* ensure logging config is passed to camera capture and tracker processes

* ensure on demand recording stops when browser closes

* improve active line progress height with resize observer

* remove icons and duplicate find similar link in explore context menu

* fix for initial broken image when creating trigger from explore

* display friendly names for triggers in toasts

* lpr and triggers docs updates

* remove icons from dropdowns in face and classification

* fix comma dangle linter issue

* re-add incorrectly removed face library button icons

* fix sidebar nav links on < 768px desktop layout

* allow text to wrap on mark as reviewed button

* match exact pixels

* clarify LPR docs

---------

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

.github/workflows/ci.yml

@@ -225,3 +225,29 @@ jobs:
           sources: |
             ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ env.SHORT_SHA }}-amd64
             ghcr.io/${{ steps.lowercaseRepo.outputs.lowercase }}:${{ env.SHORT_SHA }}-rpi
+  axera_build:
+    runs-on: ubuntu-22.04
+    name: AXERA Build
+    needs:
+      - amd64_build
+      - arm64_build
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v5
+        with:
+          persist-credentials: false
+      - name: Set up QEMU and Buildx
+        id: setup
+        uses: ./.github/actions/setup
+        with:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+      - name: Build and push Axera build
+        uses: docker/bake-action@v6
+        with:
+          source: .
+          push: true
+          targets: axcl
+          files: docker/axcl/axcl.hcl
+          set: |
+            axcl.tags=${{ steps.setup.outputs.image-name }}-axcl
+            *.cache-from=type=gha

docker/axcl/Dockerfile

@@ -0,0 +1,55 @@
+# syntax=docker/dockerfile:1.6
+
+# https://askubuntu.com/questions/972516/debian-frontend-environment-variable
+ARG DEBIAN_FRONTEND=noninteractive
+
+# Globally set pip break-system-packages option to avoid having to specify it every time
+ARG PIP_BREAK_SYSTEM_PACKAGES=1
+
+
+FROM frigate AS frigate-axcl
+ARG TARGETARCH
+ARG PIP_BREAK_SYSTEM_PACKAGES
+
+# Install axpyengine
+RUN wget https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3.rc1/axengine-0.1.3-py3-none-any.whl -O /axengine-0.1.3-py3-none-any.whl
+RUN pip3 install -i https://mirrors.aliyun.com/pypi/simple/ /axengine-0.1.3-py3-none-any.whl \
+    && rm /axengine-0.1.3-py3-none-any.whl
+
+# Install axcl
+RUN if [ "$TARGETARCH" = "amd64" ]; then \
+        echo "Installing x86_64 version of axcl"; \
+        wget https://github.com/ivanshi1108/assets/releases/download/v0.16.2/axcl_host_x86_64_V3.6.5_20250908154509_NO4973.deb -O /axcl.deb; \
+    else \
+        echo "Installing aarch64 version of axcl"; \
+        wget https://github.com/ivanshi1108/assets/releases/download/v0.16.2/axcl_host_aarch64_V3.6.5_20250908154509_NO4973.deb -O /axcl.deb; \
+    fi
+
+RUN mkdir /unpack_axcl && \
+    dpkg-deb -x /axcl.deb /unpack_axcl && \
+    cp -R /unpack_axcl/usr/bin/axcl /usr/bin/ && \
+    cp -R /unpack_axcl/usr/lib/axcl /usr/lib/ && \
+    rm -rf /unpack_axcl /axcl.deb
+
+
+# Install axcl ffmpeg
+RUN mkdir -p /usr/lib/ffmpeg/axcl
+
+RUN if [ "$TARGETARCH" = "amd64" ]; then \
+        wget https://github.com/ivanshi1108/assets/releases/download/v0.16.2/ffmpeg-x64 -O /usr/lib/ffmpeg/axcl/ffmpeg && \
+        wget https://github.com/ivanshi1108/assets/releases/download/v0.16.2/ffprobe-x64 -O /usr/lib/ffmpeg/axcl/ffprobe; \
+    else \
+        wget https://github.com/ivanshi1108/assets/releases/download/v0.16.2/ffmpeg-aarch64 -O /usr/lib/ffmpeg/axcl/ffmpeg && \
+        wget https://github.com/ivanshi1108/assets/releases/download/v0.16.2/ffprobe-aarch64 -O /usr/lib/ffmpeg/axcl/ffprobe; \
+    fi
+
+RUN chmod +x /usr/lib/ffmpeg/axcl/ffmpeg /usr/lib/ffmpeg/axcl/ffprobe
+
+# Set ldconfig path
+RUN echo "/usr/lib/axcl" > /etc/ld.so.conf.d/ax.conf
+
+# Set env
+ENV PATH="$PATH:/usr/bin/axcl"
+ENV LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/lib/axcl"
+
+ENTRYPOINT ["sh", "-c", "ldconfig && exec /init"]

docker/axcl/axcl.hcl

@@ -0,0 +1,13 @@
+target frigate {
+  dockerfile = "docker/main/Dockerfile"
+  platforms = ["linux/amd64", "linux/arm64"]
+  target = "frigate"
+}
+
+target axcl {
+  dockerfile = "docker/axcl/Dockerfile"
+  contexts = {
+    frigate = "target:frigate",
+  }
+  platforms = ["linux/amd64", "linux/arm64"]
+}

docker/axcl/axcl.mk

@@ -0,0 +1,15 @@
+BOARDS += axcl
+
+local-axcl: version
+	docker buildx bake --file=docker/axcl/axcl.hcl axcl \
+		--set axcl.tags=frigate:latest-axcl \
+		--load
+
+build-axcl: version
+	docker buildx bake --file=docker/axcl/axcl.hcl axcl \
+		--set axcl.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-axcl
+
+push-axcl: build-axcl
+	docker buildx bake --file=docker/axcl/axcl.hcl axcl \
+		--set axcl.tags=$(IMAGE_REPO):${GITHUB_REF_NAME}-$(COMMIT_HASH)-axcl \
+		--push

docker/axcl/user_installation.sh

@@ -0,0 +1,83 @@
+#!/bin/bash
+
+# Update package list and install dependencies
+sudo apt-get update
+sudo apt-get install -y build-essential cmake git wget pciutils kmod udev
+
+# Check if gcc-12 is needed
+current_gcc_version=$(gcc --version | head -n1 | awk '{print $NF}')
+gcc_major_version=$(echo $current_gcc_version | cut -d'.' -f1)
+
+if [[ $gcc_major_version -lt 12 ]]; then
+    echo "Current GCC version ($current_gcc_version) is lower than 12, installing gcc-12..."
+    sudo apt-get install -y gcc-12
+    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 12
+    echo "GCC-12 installed and set as default"
+else
+    echo "Current GCC version ($current_gcc_version) is sufficient, skipping GCC installation"
+fi
+
+# Determine architecture
+arch=$(uname -m)
+download_url=""
+
+if [[ $arch == "x86_64" ]]; then
+    download_url="https://github.com/ivanshi1108/assets/releases/download/v0.16.2/axcl_host_x86_64_V3.6.5_20250908154509_NO4973.deb"
+    deb_file="axcl_host_x86_64_V3.6.5_20250908154509_NO4973.deb"
+elif [[ $arch == "aarch64" ]]; then
+    download_url="https://github.com/ivanshi1108/assets/releases/download/v0.16.2/axcl_host_aarch64_V3.6.5_20250908154509_NO4973.deb"
+    deb_file="axcl_host_aarch64_V3.6.5_20250908154509_NO4973.deb"
+else
+    echo "Unsupported architecture: $arch"
+    exit 1
+fi
+
+# Download AXCL driver
+echo "Downloading AXCL driver for $arch..."
+wget "$download_url" -O "$deb_file"
+
+if [ $? -ne 0 ]; then
+    echo "Failed to download AXCL driver"
+    exit 1
+fi
+
+# Install AXCL driver
+echo "Installing AXCL driver..."
+sudo dpkg -i "$deb_file"
+
+if [ $? -ne 0 ]; then
+    echo "Failed to install AXCL driver, attempting to fix dependencies..."
+    sudo apt-get install -f -y
+    sudo dpkg -i "$deb_file"
+
+    if [ $? -ne 0 ]; then
+        echo "AXCL driver installation failed"
+        exit 1
+    fi
+fi
+
+# Update environment
+echo "Updating environment..."
+source /etc/profile
+
+# Verify installation
+echo "Verifying AXCL installation..."
+if command -v axcl-smi &> /dev/null; then
+    echo "AXCL driver detected, checking AI accelerator status..."
+
+    axcl_output=$(axcl-smi 2>&1)
+    axcl_exit_code=$?
+
+    echo "$axcl_output"
+
+    if [ $axcl_exit_code -eq 0 ]; then
+        echo "AXCL driver installation completed successfully!"
+    else
+        echo "AXCL driver installed but no AI accelerator detected or communication failed."
+        echo "Please check if the AI accelerator is properly connected and powered on."
+        exit 1
+    fi
+else
+    echo "axcl-smi command not found. AXCL driver installation may have failed."
+    exit 1
+fi

docs/docs/configuration/license_plate_recognition.md

@@ -3,18 +3,18 @@ id: license_plate_recognition
 title: License Plate Recognition (LPR)
 ---
 
-Frigate can recognize license plates on vehicles and automatically add the detected characters to the `recognized_license_plate` field or a known name as a `sub_label` to tracked objects of type `car` or `motorcycle`. A common use case may be to read the license plates of cars pulling into a driveway or cars passing by on a street.
+Frigate can recognize license plates on vehicles and automatically add the detected characters to the `recognized_license_plate` field or a [known](#matching) name as a `sub_label` to tracked objects of type `car` or `motorcycle`. A common use case may be to read the license plates of cars pulling into a driveway or cars passing by on a street.
 
 LPR works best when the license plate is clearly visible to the camera. For moving vehicles, Frigate continuously refines the recognition process, keeping the most confident result. When a vehicle becomes stationary, LPR continues to run for a short time after to attempt recognition.
 
 When a plate is recognized, the details are:
 
-- Added as a `sub_label` (if known) or the `recognized_license_plate` field (if unknown) to a tracked object.
-- Viewable in the Review Item Details pane in Review (sub labels).
+- Added as a `sub_label` (if [known](#matching)) or the `recognized_license_plate` field (if unknown) to a tracked object.
+- Viewable in the Details pane in Review/History.
 - Viewable in the Tracked Object Details pane in Explore (sub labels and recognized license plates).
 - Filterable through the More Filters menu in Explore.
-- Published via the `frigate/events` MQTT topic as a `sub_label` (known) or `recognized_license_plate` (unknown) for the `car` or `motorcycle` tracked object.
-- Published via the `frigate/tracked_object_update` MQTT topic with `name` (if known) and `plate`.
+- Published via the `frigate/events` MQTT topic as a `sub_label` ([known](#matching)) or `recognized_license_plate` (unknown) for the `car` or `motorcycle` tracked object.
+- Published via the `frigate/tracked_object_update` MQTT topic with `name` (if [known](#matching)) and `plate`.
 
 ## Model Requirements
 
@@ -31,6 +31,7 @@ In the default mode, Frigate's LPR needs to first detect a `car` or `motorcycle`
 ## Minimum System Requirements
 
 License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM is required.
+
 ## Configuration
 
 License plate recognition is disabled by default. Enable it in your config file:
@@ -73,8 +74,8 @@ Fine-tune the LPR feature using these optional parameters at the global level of
   - Default: `small`
   - This can be `small` or `large`.
   - The `small` model is fast and identifies groups of Latin and Chinese characters.
-  - The `large` model identifies Latin characters only, but uses an enhanced text detector and is more capable at finding characters on multi-line plates. It is significantly slower than the `small` model. Note that using the `large` model does not improve _text recognition_, but it may improve _text detection_.
-  - For most users, the `small` model is recommended.
+  - The `large` model identifies Latin characters only, and uses an enhanced text detector to find characters on multi-line plates. It is significantly slower than the `small` model.
+  - If your country or region does not use multi-line plates, you should use the `small` model as performance is much better for single-line plates.
 
 ### Recognition
 
@@ -177,7 +178,7 @@ lpr:
 
 :::note
 
-If you want to detect cars on cameras but don't want to use resources to run LPR on those cars, you should disable LPR for those specific cameras.
+If a camera is configured to detect `car` or `motorcycle` but you don't want Frigate to run LPR for that camera, disable LPR at the camera level:
 
 ```yaml
 cameras:
@@ -305,7 +306,7 @@ With this setup:
 - Review items will always be classified as a `detection`.
 - Snapshots will always be saved.
 - Zones and object masks are **not** used.
-- The `frigate/events` MQTT topic will **not** publish tracked object updates with the license plate bounding box and score, though `frigate/reviews` will publish if recordings are enabled. If a plate is recognized as a known plate, publishing will occur with an updated `sub_label` field. If characters are recognized, publishing will occur with an updated `recognized_license_plate` field.
+- The `frigate/events` MQTT topic will **not** publish tracked object updates with the license plate bounding box and score, though `frigate/reviews` will publish if recordings are enabled. If a plate is recognized as a [known](#matching) plate, publishing will occur with an updated `sub_label` field. If characters are recognized, publishing will occur with an updated `recognized_license_plate` field.
 - License plate snapshots are saved at the highest-scoring moment and appear in Explore.
 - Debug view will not show `license_plate` bounding boxes.
 

docs/docs/configuration/object_detectors.md

@@ -47,6 +47,11 @@ Frigate supports multiple different detectors that work on different types of ha
 
 - [Synaptics](#synaptics): synap models can run on Synaptics devices(e.g astra machina) with included NPUs.
 
+**AXERA**
+
+- [AXEngine](#axera): axmodels can run on AXERA AI acceleration.
+
+
 **For Testing**
 
 - [CPU Detector (not recommended for actual use](#cpu-detector-not-recommended): Use a CPU to run tflite model, this is not recommended and in most cases OpenVINO can be used in CPU mode with better results.
@@ -1169,6 +1174,41 @@ model: # required
   labelmap_path: /labelmap/coco-80.txt # required
 ```
 
+## AXERA
+
+Hardware accelerated object detection is supported on the following SoCs:
+
+- AX650N
+- AX8850N
+
+This implementation uses the [AXera Pulsar2 Toolchain](https://huggingface.co/AXERA-TECH/Pulsar2).
+
+See the [installation docs](../frigate/installation.md#axera) for information on configuring the AXEngine hardware.
+
+### Configuration
+
+When configuring the AXEngine detector, you have to specify the model name.
+
+#### yolov9
+
+A yolov9 model is provided in the container at /axmodels and is used by this detector type by default.
+
+Use the model configuration shown below when using the axengine detector with the default axmodel:
+
+```yaml
+detectors:  # required
+  axengine:  # required
+    type: axengine  # required
+
+model:  # required
+  path: frigate-yolov9-tiny  # required
+  model_type: yolo-generic # required
+  width: 320  # required
+  height: 320  # required
+  tensor_format: bgr  # required
+  labelmap_path: /labelmap/coco-80.txt  # required
+```
+
 ## Rockchip platform
 
 Hardware accelerated object detection is supported on the following SoCs:

docs/docs/configuration/semantic_search.md

@@ -141,7 +141,7 @@ Triggers are best configured through the Frigate UI.
      Check the `Add Attribute` box to add the trigger's internal ID (e.g., "red_car_alert") to a data attribute on the tracked object that can be processed via the API or MQTT.
 5. Save the trigger to update the configuration and store the embedding in the database.
 
-When a trigger fires, the UI highlights the trigger with a blue dot for 3 seconds for easy identification.
+When a trigger fires, the UI highlights the trigger with a blue dot for 3 seconds for easy identification. Additionally, the UI will show the last date/time and tracked object ID that activated your trigger. The last triggered timestamp is not saved to the database or persisted through restarts of Frigate.
 
 ### Usage and Best Practices
 

docs/docs/frigate/hardware.md

@@ -110,6 +110,14 @@ Frigate supports multiple different detectors that work on different types of ha
 | ssd mobilenet    | ~ 25 ms                         |
 | yolov5m          | ~ 118 ms                        |
 
+### AXERA
+
+- **AXEngine** Default model is **yolov9**
+
+| Name             | AXERA AX650N/AX8850N Inference Time |
+| ---------------- | ----------------------------------- |
+| yolov9-tiny      | ~ 4 ms                              |
+
 ### Hailo-8
 
 Frigate supports both the Hailo-8 and Hailo-8L AI Acceleration Modules on compatible hardware platforms—including the Raspberry Pi 5 with the PCIe hat from the AI kit. The Hailo detector integration in Frigate automatically identifies your hardware type and selects the appropriate default model when a custom model isn’t provided.

docs/docs/frigate/installation.md

@@ -287,6 +287,40 @@ or add these options to your `docker run` command:
 
 Next, you should configure [hardware object detection](/configuration/object_detectors#synaptics) and [hardware video processing](/configuration/hardware_acceleration_video#synaptics).
 
+### AXERA
+
+AXERA accelerators are available in an M.2 form factor, compatible with both Raspberry Pi and Orange Pi. This form factor has also been successfully tested on x86 platforms, making it a versatile choice for various computing environments.
+
+#### Installation
+
+Using AXERA accelerators requires the installation of the AXCL driver. We provide a convenient Linux script to complete this installation.
+
+Follow these steps for installation:
+
+1. Copy or download [this script](https://github.com/ivanshi1108/assets/releases/download/v0.16.2/user_installation.sh).
+2. Ensure it has execution permissions with `sudo chmod +x user_installation.sh`
+3. Run the script with `./user_installation.sh`
+
+#### Setup
+
+To set up Frigate, follow the default installation instructions, for example: `ghcr.io/blakeblackshear/frigate:stable`
+
+Next, grant Docker permissions to access your hardware by adding the following lines to your `docker-compose.yml` file:
+
+```yaml
+devices:
+  - /dev/axcl_host
+  - /dev/ax_mmb_dev
+  - /dev/msg_userdev
+```
+
+If you are using `docker run`, add this option to your command `--device /dev/axcl_host --device /dev/ax_mmb_dev --device /dev/msg_userdev`
+
+#### Configuration
+
+Finally, configure [hardware object detection](/configuration/object_detectors#axera) to complete the setup.
+
+
 ## Docker
 
 Running through Docker with Docker Compose is the recommended install method.

frigate/api/event.py

@@ -1781,9 +1781,8 @@ def create_trigger_embedding(
                 logger.debug(
                     f"Writing thumbnail for trigger with data {body.data} in {camera_name}."
                 )
-            except Exception as e:
-                logger.error(e.with_traceback())
-                logger.error(
+            except Exception:
+                logger.exception(
                     f"Failed to write thumbnail for trigger with data {body.data} in {camera_name}"
                 )
 
@@ -1807,8 +1806,8 @@ def create_trigger_embedding(
             status_code=200,
         )
 
-    except Exception as e:
-        logger.error(e.with_traceback())
+    except Exception:
+        logger.exception("Error creating trigger embedding")
         return JSONResponse(
             content={
                 "success": False,
@@ -1917,9 +1916,8 @@ def update_trigger_embedding(
                     logger.debug(
                         f"Deleted thumbnail for trigger with data {trigger.data} in {camera_name}."
                     )
-                except Exception as e:
-                    logger.error(e.with_traceback())
-                    logger.error(
+                except Exception:
+                    logger.exception(
                         f"Failed to delete thumbnail for trigger with data {trigger.data} in {camera_name}"
                     )
 
@@ -1958,9 +1956,8 @@ def update_trigger_embedding(
                 logger.debug(
                     f"Writing thumbnail for trigger with data {body.data} in {camera_name}."
                 )
-            except Exception as e:
-                logger.error(e.with_traceback())
-                logger.error(
+            except Exception:
+                logger.exception(
                     f"Failed to write thumbnail for trigger with data {body.data} in {camera_name}"
                 )
 
@@ -1972,8 +1969,8 @@ def update_trigger_embedding(
             status_code=200,
         )
 
-    except Exception as e:
-        logger.error(e.with_traceback())
+    except Exception:
+        logger.exception("Error updating trigger embedding")
         return JSONResponse(
             content={
                 "success": False,
@@ -2033,9 +2030,8 @@ def delete_trigger_embedding(
             logger.debug(
                 f"Deleted thumbnail for trigger with data {trigger.data} in {camera_name}."
             )
-        except Exception as e:
-            logger.error(e.with_traceback())
-            logger.error(
+        except Exception:
+            logger.exception(
                 f"Failed to delete thumbnail for trigger with data {trigger.data} in {camera_name}"
             )
 
@@ -2047,8 +2043,8 @@ def delete_trigger_embedding(
             status_code=200,
         )
 
-    except Exception as e:
-        logger.error(e.with_traceback())
+    except Exception:
+        logger.exception("Error deleting trigger embedding")
         return JSONResponse(
             content={
                 "success": False,

frigate/camera/maintainer.py

@@ -136,6 +136,7 @@ class CameraMaintainer(threading.Thread):
             self.ptz_metrics[name],
             self.region_grids[name],
             self.stop_event,
+            self.config.logger,
         )
         self.camera_processes[config.name] = camera_process
         camera_process.start()
@@ -156,7 +157,11 @@ class CameraMaintainer(threading.Thread):
             self.frame_manager.create(f"{config.name}_frame{i}", frame_size)
 
         capture_process = CameraCapture(
-            config, count, self.camera_metrics[name], self.stop_event
+            config,
+            count,
+            self.camera_metrics[name],
+            self.stop_event,
+            self.config.logger,
         )
         capture_process.daemon = True
         self.capture_processes[name] = capture_process

frigate/data_processing/post/review_descriptions.py

@@ -132,17 +132,15 @@ class ReviewDescriptionProcessor(PostProcessorApi):
 
             if image_source == ImageSourceEnum.recordings:
                 duration = final_data["end_time"] - final_data["start_time"]
-                buffer_extension = min(
-                    10, max(2, duration * RECORDING_BUFFER_EXTENSION_PERCENT)
-                )
+                buffer_extension = min(5, duration * RECORDING_BUFFER_EXTENSION_PERCENT)
 
                 # Ensure minimum total duration for short review items
                 # This provides better context for brief events
                 total_duration = duration + (2 * buffer_extension)
                 if total_duration < MIN_RECORDING_DURATION:
-                    # Expand buffer to reach minimum duration, still respecting max of 10s per side
+                    # Expand buffer to reach minimum duration, still respecting max of 5s per side
                     additional_buffer_per_side = (MIN_RECORDING_DURATION - duration) / 2
-                    buffer_extension = min(10, additional_buffer_per_side)
+                    buffer_extension = min(5, additional_buffer_per_side)
 
                 thumbs = self.get_recording_frames(
                     camera,

frigate/data_processing/real_time/face.py

@@ -424,7 +424,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
             if not res:
                 return {
-                    "message": "No face was recognized.",
+                    "message": "Model is still training, please try again in a few moments.",
                     "success": False,
                 }
 

frigate/detectors/plugins/axengine.py

@@ -0,0 +1,92 @@
+import logging
+import os.path
+import re
+import urllib.request
+from typing import Literal
+
+import cv2
+import numpy as np
+from pydantic import Field
+
+from frigate.const import MODEL_CACHE_DIR
+from frigate.detectors.detection_api import DetectionApi
+from frigate.detectors.detector_config import BaseDetectorConfig, ModelTypeEnum
+from frigate.util.model import post_process_yolo
+
+import axengine as axe
+from axengine import axclrt_provider_name, axengine_provider_name
+
+logger = logging.getLogger(__name__)
+
+DETECTOR_KEY = "axengine"
+
+supported_models = {
+    ModelTypeEnum.yologeneric: "frigate-yolov9-.*$",
+}
+
+model_cache_dir = os.path.join(MODEL_CACHE_DIR, "axengine_cache/")
+
+
+class AxengineDetectorConfig(BaseDetectorConfig):
+    type: Literal[DETECTOR_KEY]
+
+class Axengine(DetectionApi):
+    type_key = DETECTOR_KEY
+    def __init__(self, config: AxengineDetectorConfig):
+        logger.info("__init__ axengine")
+        super().__init__(config)
+        self.height = config.model.height
+        self.width = config.model.width
+        model_path = config.model.path or "frigate-yolov9-tiny"
+        model_props = self.parse_model_input(model_path)
+        self.session = axe.InferenceSession(model_props["path"])
+
+    def __del__(self):
+        pass
+
+    def parse_model_input(self, model_path):
+        model_props = {}
+        model_props["preset"] = True
+
+        model_matched = False
+
+        for model_type, pattern in supported_models.items():
+            if re.match(pattern, model_path):
+                model_matched = True
+                model_props["model_type"] = model_type
+
+        if model_matched:
+            model_props["filename"] = model_path + f".axmodel"
+            model_props["path"] = model_cache_dir + model_props["filename"]
+
+            if not os.path.isfile(model_props["path"]):
+                self.download_model(model_props["filename"])
+        else:
+            supported_models_str = ", ".join(
+                model[1:-1] for model in supported_models
+            )
+            raise Exception(
+                f"Model {model_path} is unsupported. Provide your own model or choose one of the following: {supported_models_str}"
+            )
+        return model_props
+
+    def download_model(self, filename):
+        if not os.path.isdir(model_cache_dir):
+            os.mkdir(model_cache_dir)
+
+        GITHUB_ENDPOINT = os.environ.get("GITHUB_ENDPOINT", "https://github.com")
+        urllib.request.urlretrieve(
+            f"{GITHUB_ENDPOINT}/ivanshi1108/assets/releases/download/v0.16.2/{filename}",
+            model_cache_dir + filename,
+        )
+
+    def detect_raw(self, tensor_input):
+        results = None
+        results = self.session.run(None, {"images": tensor_input})
+        if self.detector_config.model.model_type == ModelTypeEnum.yologeneric:
+            return post_process_yolo(results, self.width, self.height)
+        else:
+            raise ValueError(
+                f'Model type "{self.detector_config.model.model_type}" is currently not supported.'
+            )
+

frigate/video.py

@@ -16,7 +16,7 @@ from frigate.comms.recordings_updater import (
     RecordingsDataSubscriber,
     RecordingsDataTypeEnum,
 )
-from frigate.config import CameraConfig, DetectConfig, ModelConfig
+from frigate.config import CameraConfig, DetectConfig, LoggerConfig, ModelConfig
 from frigate.config.camera.camera import CameraTypeEnum
 from frigate.config.camera.updater import (
     CameraConfigUpdateEnum,
@@ -539,6 +539,7 @@ class CameraCapture(FrigateProcess):
         shm_frame_count: int,
         camera_metrics: CameraMetrics,
         stop_event: MpEvent,
+        log_config: LoggerConfig | None = None,
     ) -> None:
         super().__init__(
             stop_event,
@@ -549,9 +550,10 @@ class CameraCapture(FrigateProcess):
         self.config = config
         self.shm_frame_count = shm_frame_count
         self.camera_metrics = camera_metrics
+        self.log_config = log_config
 
     def run(self) -> None:
-        self.pre_run_setup()
+        self.pre_run_setup(self.log_config)
         camera_watchdog = CameraWatchdog(
             self.config,
             self.shm_frame_count,
@@ -577,6 +579,7 @@ class CameraTracker(FrigateProcess):
         ptz_metrics: PTZMetrics,
         region_grid: list[list[dict[str, Any]]],
         stop_event: MpEvent,
+        log_config: LoggerConfig | None = None,
     ) -> None:
         super().__init__(
             stop_event,
@@ -592,9 +595,10 @@ class CameraTracker(FrigateProcess):
         self.camera_metrics = camera_metrics
         self.ptz_metrics = ptz_metrics
         self.region_grid = region_grid
+        self.log_config = log_config
 
     def run(self) -> None:
-        self.pre_run_setup()
+        self.pre_run_setup(self.log_config)
         frame_queue = self.camera_metrics.frame_queue
         frame_shape = self.config.frame_shape
 

web/public/notifications-worker.js

@@ -44,11 +44,16 @@ self.addEventListener("notificationclick", (event) => {
     switch (event.action ?? "default") {
       case "markReviewed":
         if (event.notification.data) {
-          fetch("/api/reviews/viewed", {
-            method: "POST",
-            headers: { "Content-Type": "application/json", "X-CSRF-TOKEN": 1 },
-            body: JSON.stringify({ ids: [event.notification.data.id] }),
-          });
+          event.waitUntil(
+            fetch("/api/reviews/viewed", {
+              method: "POST",
+              headers: {
+                "Content-Type": "application/json",
+                "X-CSRF-TOKEN": 1,
+              },
+              body: JSON.stringify({ ids: [event.notification.data.id] }),
+            }), // eslint-disable-line comma-dangle
+          );
         }
         break;
       default:
@@ -58,7 +63,7 @@ self.addEventListener("notificationclick", (event) => {
           // eslint-disable-next-line no-undef
           if (clients.openWindow) {
             // eslint-disable-next-line no-undef
-            return clients.openWindow(url);
+            event.waitUntil(clients.openWindow(url));
           }
         }
     }

web/src/components/card/ClassificationCard.tsx

@@ -398,11 +398,7 @@ export function GroupedClassificationCard({
                     threshold={threshold}
                     selected={false}
                     i18nLibrary={i18nLibrary}
-                    onClick={(data, meta) => {
-                      if (meta || selectedItems.length > 0) {
-                        onClick(data);
-                      }
-                    }}
+                    onClick={() => {}}
                   >
                     {children?.(data)}
                   </ClassificationCard>

web/src/components/menu/SearchResultActions.tsx

@@ -4,9 +4,7 @@ import { FrigateConfig } from "@/types/frigateConfig";
 import { baseUrl } from "@/api/baseUrl";
 import { toast } from "sonner";
 import axios from "axios";
-import { LuCamera, LuDownload, LuTrash2 } from "react-icons/lu";
 import { FiMoreVertical } from "react-icons/fi";
-import { MdImageSearch } from "react-icons/md";
 import { buttonVariants } from "@/components/ui/button";
 import {
   ContextMenu,
@@ -31,11 +29,8 @@ import {
   AlertDialogTitle,
 } from "@/components/ui/alert-dialog";
 import useSWR from "swr";
-
 import { Trans, useTranslation } from "react-i18next";
-import { BsFillLightningFill } from "react-icons/bs";
 import BlurredIconButton from "../button/BlurredIconButton";
-import { PiPath } from "react-icons/pi";
 
 type SearchResultActionsProps = {
   searchResult: SearchResult;
@@ -98,7 +93,6 @@ export default function SearchResultActions({
             href={`${baseUrl}api/events/${searchResult.id}/clip.mp4`}
             download={`${searchResult.camera}_${searchResult.label}.mp4`}
           >
-            <LuDownload className="mr-2 size-4" />
             <span>{t("itemMenu.downloadVideo.label")}</span>
           </a>
         </MenuItem>
@@ -110,7 +104,6 @@ export default function SearchResultActions({
             href={`${baseUrl}api/events/${searchResult.id}/snapshot.jpg`}
             download={`${searchResult.camera}_${searchResult.label}.jpg`}
           >
-            <LuCamera className="mr-2 size-4" />
             <span>{t("itemMenu.downloadSnapshot.label")}</span>
           </a>
         </MenuItem>
@@ -120,44 +113,31 @@ export default function SearchResultActions({
           aria-label={t("itemMenu.viewTrackingDetails.aria")}
           onClick={showTrackingDetails}
         >
-          <PiPath className="mr-2 size-4" />
           <span>{t("itemMenu.viewTrackingDetails.label")}</span>
         </MenuItem>
       )}
-      {config?.semantic_search?.enabled && isContextMenu && (
-        <MenuItem
-          aria-label={t("itemMenu.findSimilar.aria")}
-          onClick={findSimilar}
-        >
-          <MdImageSearch className="mr-2 size-4" />
-          <span>{t("itemMenu.findSimilar.label")}</span>
-        </MenuItem>
-      )}
-      {config?.semantic_search?.enabled &&
-        searchResult.data.type == "object" && (
-          <MenuItem
-            aria-label={t("itemMenu.addTrigger.aria")}
-            onClick={addTrigger}
-          >
-            <BsFillLightningFill className="mr-2 size-4" />
-            <span>{t("itemMenu.addTrigger.label")}</span>
-          </MenuItem>
-        )}
       {config?.semantic_search?.enabled &&
         searchResult.data.type == "object" && (
           <MenuItem
             aria-label={t("itemMenu.findSimilar.aria")}
             onClick={findSimilar}
           >
-            <MdImageSearch className="mr-2 size-4" />
             <span>{t("itemMenu.findSimilar.label")}</span>
           </MenuItem>
         )}
+      {config?.semantic_search?.enabled &&
+        searchResult.data.type == "object" && (
+          <MenuItem
+            aria-label={t("itemMenu.addTrigger.aria")}
+            onClick={addTrigger}
+          >
+            <span>{t("itemMenu.addTrigger.label")}</span>
+          </MenuItem>
+        )}
       <MenuItem
         aria-label={t("itemMenu.deleteTrackedObject.label")}
         onClick={() => setDeleteDialogOpen(true)}
       >
-        <LuTrash2 className="mr-2 size-4" />
         <span>{t("button.delete", { ns: "common" })}</span>
       </MenuItem>
     </>

web/src/components/navigation/NavItem.tsx

@@ -46,13 +46,13 @@ export default function NavItem({
       onClick={onClick}
       className={({ isActive }) =>
         cn(
-          "flex flex-col items-center justify-center rounded-lg",
+          "flex flex-col items-center justify-center rounded-lg p-[6px]",
           className,
           variants[item.variant ?? "primary"][isActive ? "active" : "inactive"],
         )
       }
     >
-      <Icon className="size-5 md:m-[6px]" />
+      <Icon className="size-5" />
     </NavLink>
   );
 

web/src/components/overlay/FaceSelectionDialog.tsx

@@ -12,6 +12,7 @@ import {
   DropdownMenuContent,
   DropdownMenuItem,
   DropdownMenuLabel,
+  DropdownMenuSeparator,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
 import {
@@ -20,7 +21,6 @@ import {
   TooltipTrigger,
 } from "@/components/ui/tooltip";
 import { isDesktop, isMobile } from "react-device-detect";
-import { LuPlus, LuScanFace } from "react-icons/lu";
 import { useTranslation } from "react-i18next";
 import { cn } from "@/lib/utils";
 import React, { ReactNode, useMemo, useState } from "react";
@@ -89,27 +89,26 @@ export default function FaceSelectionDialog({
             <DropdownMenuLabel>{t("trainFaceAs")}</DropdownMenuLabel>
             <div
               className={cn(
-                "flex max-h-[40dvh] flex-col overflow-y-auto",
+                "flex max-h-[40dvh] flex-col overflow-y-auto overflow-x-hidden",
                 isMobile && "gap-2 pb-4",
               )}
             >
-              <SelectorItem
-                className="flex cursor-pointer gap-2 smart-capitalize"
-                onClick={() => setNewFace(true)}
-              >
-                <LuPlus />
-                {t("createFaceLibrary.new")}
-              </SelectorItem>
               {faceNames.sort().map((faceName) => (
                 <SelectorItem
                   key={faceName}
                   className="flex cursor-pointer gap-2 smart-capitalize"
                   onClick={() => onTrainAttempt(faceName)}
                 >
-                  <LuScanFace />
                   {faceName}
                 </SelectorItem>
               ))}
+              <DropdownMenuSeparator />
+              <SelectorItem
+                className="flex cursor-pointer gap-2 smart-capitalize"
+                onClick={() => setNewFace(true)}
+              >
+                {t("createFaceLibrary.new")}
+              </SelectorItem>
             </div>
           </SelectorContent>
         </Selector>

web/src/components/overlay/ImagePicker.tsx

@@ -171,6 +171,18 @@ export default function ImagePicker({
                       alt={selectedImage?.label || "Selected image"}
                       className="size-16 rounded object-cover"
                       onLoad={() => handleImageLoad(selectedImageId || "")}
+                      onError={(e) => {
+                        // If trigger thumbnail fails to load, fall back to event thumbnail
+                        if (!selectedImage) {
+                          const target = e.target as HTMLImageElement;
+                          if (
+                            target.src.includes("clips/triggers") &&
+                            selectedImageId
+                          ) {
+                            target.src = `${apiHost}api/events/${selectedImageId}/thumbnail.webp`;
+                          }
+                        }
+                      }}
                       loading="lazy"
                     />
                     {selectedImageId && !loadedImages.has(selectedImageId) && (

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

@@ -683,6 +683,22 @@ function ObjectDetailsTab({
 
   const mutate = useGlobalMutation();
 
+  // Helper to map over SWR cached search results while preserving
+  // either paginated format (SearchResult[][]) or flat format (SearchResult[])
+  const mapSearchResults = useCallback(
+    (
+      currentData: SearchResult[][] | SearchResult[] | undefined,
+      fn: (event: SearchResult) => SearchResult,
+    ) => {
+      if (!currentData) return currentData;
+      if (Array.isArray(currentData[0])) {
+        return (currentData as SearchResult[][]).map((page) => page.map(fn));
+      }
+      return (currentData as SearchResult[]).map(fn);
+    },
+    [],
+  );
+
   // users
 
   const isAdmin = useIsAdmin();
@@ -810,17 +826,12 @@ function ObjectDetailsTab({
             (key.includes("events") ||
               key.includes("events/search") ||
               key.includes("events/explore")),
-          (currentData: SearchResult[][] | SearchResult[] | undefined) => {
-            if (!currentData) return currentData;
-            // optimistic update
-            return currentData
-              .flat()
-              .map((event) =>
-                event.id === search.id
-                  ? { ...event, data: { ...event.data, description: desc } }
-                  : event,
-              );
-          },
+          (currentData: SearchResult[][] | SearchResult[] | undefined) =>
+            mapSearchResults(currentData, (event) =>
+              event.id === search.id
+                ? { ...event, data: { ...event.data, description: desc } }
+                : event,
+            ),
           {
             optimisticData: true,
             rollbackOnError: true,
@@ -843,7 +854,7 @@ function ObjectDetailsTab({
         );
         setDesc(search.data.description);
       });
-  }, [desc, search, mutate, t]);
+  }, [desc, search, mutate, t, mapSearchResults]);
 
   const regenerateDescription = useCallback(
     (source: "snapshot" | "thumbnails") => {
@@ -915,9 +926,8 @@ function ObjectDetailsTab({
                 (key.includes("events") ||
                   key.includes("events/search") ||
                   key.includes("events/explore")),
-              (currentData: SearchResult[][] | SearchResult[] | undefined) => {
-                if (!currentData) return currentData;
-                return currentData.flat().map((event) =>
+              (currentData: SearchResult[][] | SearchResult[] | undefined) =>
+                mapSearchResults(currentData, (event) =>
                   event.id === search.id
                     ? {
                         ...event,
@@ -928,8 +938,7 @@ function ObjectDetailsTab({
                         },
                       }
                     : event,
-                );
-              },
+                ),
               {
                 optimisticData: true,
                 rollbackOnError: true,
@@ -963,7 +972,7 @@ function ObjectDetailsTab({
           );
         });
     },
-    [search, apiHost, mutate, setSearch, t],
+    [search, apiHost, mutate, setSearch, t, mapSearchResults],
   );
 
   // recognized plate
@@ -992,9 +1001,8 @@ function ObjectDetailsTab({
                 (key.includes("events") ||
                   key.includes("events/search") ||
                   key.includes("events/explore")),
-              (currentData: SearchResult[][] | SearchResult[] | undefined) => {
-                if (!currentData) return currentData;
-                return currentData.flat().map((event) =>
+              (currentData: SearchResult[][] | SearchResult[] | undefined) =>
+                mapSearchResults(currentData, (event) =>
                   event.id === search.id
                     ? {
                         ...event,
@@ -1005,8 +1013,7 @@ function ObjectDetailsTab({
                         },
                       }
                     : event,
-                );
-              },
+                ),
               {
                 optimisticData: true,
                 rollbackOnError: true,
@@ -1040,7 +1047,7 @@ function ObjectDetailsTab({
           );
         });
     },
-    [search, apiHost, mutate, setSearch, t],
+    [search, apiHost, mutate, setSearch, t, mapSearchResults],
   );
 
   // speech transcription
@@ -1102,17 +1109,12 @@ function ObjectDetailsTab({
           (key.includes("events") ||
             key.includes("events/search") ||
             key.includes("events/explore")),
-        (currentData: SearchResult[][] | SearchResult[] | undefined) => {
-          if (!currentData) return currentData;
-          // optimistic update
-          return currentData
-            .flat()
-            .map((event) =>
-              event.id === search.id
-                ? { ...event, plus_id: "new_upload" }
-                : event,
-            );
-        },
+        (currentData: SearchResult[][] | SearchResult[] | undefined) =>
+          mapSearchResults(currentData, (event) =>
+            event.id === search.id
+              ? { ...event, plus_id: "new_upload" }
+              : event,
+          ),
         {
           optimisticData: true,
           rollbackOnError: true,
@@ -1120,7 +1122,7 @@ function ObjectDetailsTab({
         },
       );
     },
-    [search, mutate],
+    [search, mutate, mapSearchResults],
   );
 
   const popoverContainerRef = useRef<HTMLDivElement | null>(null);
@@ -1503,7 +1505,7 @@ function ObjectDetailsTab({
         ) : (
           <div className="flex flex-col gap-2">
             <Textarea
-              className="text-md h-32"
+              className="text-md h-32 md:text-sm"
               placeholder={t("details.description.placeholder")}
               value={desc}
               onChange={(e) => setDesc(e.target.value)}
@@ -1511,25 +1513,7 @@ function ObjectDetailsTab({
               onBlur={handleDescriptionBlur}
               autoFocus
             />
-            <div className="flex flex-row justify-end gap-4">
-              <Tooltip>
-                <TooltipTrigger asChild>
-                  <button
-                    aria-label={t("button.save", { ns: "common" })}
-                    className="text-primary/40 hover:text-primary/80"
-                    onClick={() => {
-                      setIsEditingDesc(false);
-                      updateDescription();
-                    }}
-                  >
-                    <FaCheck className="size-4" />
-                  </button>
-                </TooltipTrigger>
-                <TooltipContent>
-                  {t("button.save", { ns: "common" })}
-                </TooltipContent>
-              </Tooltip>
-
+            <div className="mb-10 flex flex-row justify-end gap-5">
               <Tooltip>
                 <TooltipTrigger asChild>
                   <button
@@ -1540,13 +1524,31 @@ function ObjectDetailsTab({
                       setDesc(originalDescRef.current ?? "");
                     }}
                   >
-                    <FaTimes className="size-4" />
+                    <FaTimes className="size-5" />
                   </button>
                 </TooltipTrigger>
                 <TooltipContent>
                   {t("button.cancel", { ns: "common" })}
                 </TooltipContent>
               </Tooltip>
+
+              <Tooltip>
+                <TooltipTrigger asChild>
+                  <button
+                    aria-label={t("button.save", { ns: "common" })}
+                    className="text-primary/40 hover:text-primary/80"
+                    onClick={() => {
+                      setIsEditingDesc(false);
+                      updateDescription();
+                    }}
+                  >
+                    <FaCheck className="size-5" />
+                  </button>
+                </TooltipTrigger>
+                <TooltipContent>
+                  {t("button.save", { ns: "common" })}
+                </TooltipContent>
+              </Tooltip>
             </div>
           </div>
         )}

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

@@ -1,5 +1,6 @@
 import useSWR from "swr";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { useResizeObserver } from "@/hooks/resize-observer";
 import { Event } from "@/types/event";
 import ActivityIndicator from "@/components/indicators/activity-indicator";
 import { TrackingDetailsSequence } from "@/types/timeline";
@@ -89,9 +90,16 @@ export function TrackingDetails({
   }, [manualOverride, currentTime, annotationOffset]);
 
   const containerRef = useRef<HTMLDivElement | null>(null);
+  const timelineContainerRef = useRef<HTMLDivElement | null>(null);
+  const rowRefs = useRef<(HTMLDivElement | null)[]>([]);
   const [_selectedZone, setSelectedZone] = useState("");
   const [_lifecycleZones, setLifecycleZones] = useState<string[]>([]);
   const [seekToTimestamp, setSeekToTimestamp] = useState<number | null>(null);
+  const [lineBottomOffsetPx, setLineBottomOffsetPx] = useState<number>(32);
+  const [lineTopOffsetPx, setLineTopOffsetPx] = useState<number>(8);
+  const [blueLineHeightPx, setBlueLineHeightPx] = useState<number>(0);
+
+  const [timelineSize] = useResizeObserver(timelineContainerRef);
 
   const aspectRatio = useMemo(() => {
     if (!config) {
@@ -221,60 +229,74 @@ export function TrackingDetails({
     displaySource,
   ]);
 
-  const isWithinEventRange =
-    effectiveTime !== undefined &&
-    event.start_time !== undefined &&
-    event.end_time !== undefined &&
-    effectiveTime >= event.start_time &&
-    effectiveTime <= event.end_time;
-
-  // Calculate how far down the blue line should extend based on effectiveTime
-  const calculateLineHeight = useCallback(() => {
-    if (!eventSequence || eventSequence.length === 0 || !isWithinEventRange) {
-      return 0;
+  const isWithinEventRange = useMemo(() => {
+    if (effectiveTime === undefined || event.start_time === undefined) {
+      return false;
     }
-
-    const currentTime = effectiveTime ?? 0;
-
-    // Find which events have been passed
-    let lastPassedIndex = -1;
-    for (let i = 0; i < eventSequence.length; i++) {
-      if (currentTime >= (eventSequence[i].timestamp ?? 0)) {
-        lastPassedIndex = i;
-      } else {
-        break;
+    // If an event has not ended yet, fall back to last timestamp in eventSequence
+    let eventEnd = event.end_time;
+    if (eventEnd == null && eventSequence && eventSequence.length > 0) {
+      const last = eventSequence[eventSequence.length - 1];
+      if (last && last.timestamp !== undefined) {
+        eventEnd = last.timestamp;
       }
     }
 
-    // No events passed yet
-    if (lastPassedIndex < 0) return 0;
+    if (eventEnd == null) {
+      return false;
+    }
+    return effectiveTime >= event.start_time && effectiveTime <= eventEnd;
+  }, [effectiveTime, event.start_time, event.end_time, eventSequence]);
 
-    // All events passed
-    if (lastPassedIndex >= eventSequence.length - 1) return 100;
+  // Dynamically compute pixel offsets so the timeline line starts at the
+  // first row midpoint and ends at the last row midpoint. For accuracy,
+  // measure the center Y of each lifecycle row and interpolate the current
+  // effective time into a pixel position; then set the blue line height
+  // so it reaches the center dot at the same time the dot becomes active.
+  useEffect(() => {
+    if (!timelineContainerRef.current || !eventSequence) return;
 
-    // Calculate percentage based on item position, not time
-    // Each item occupies an equal visual space regardless of time gaps
-    const itemPercentage = 100 / (eventSequence.length - 1);
+    const containerRect = timelineContainerRef.current.getBoundingClientRect();
+    const validRefs = rowRefs.current.filter((r) => r !== null);
+    if (validRefs.length === 0) return;
 
-    // Find progress between current and next event for smooth transition
-    const currentEvent = eventSequence[lastPassedIndex];
-    const nextEvent = eventSequence[lastPassedIndex + 1];
-    const currentTimestamp = currentEvent.timestamp ?? 0;
-    const nextTimestamp = nextEvent.timestamp ?? 0;
+    const centers = validRefs.map((n) => {
+      const r = n.getBoundingClientRect();
+      return r.top + r.height / 2 - containerRect.top;
+    });
 
-    // Calculate interpolation between the two events
-    const timeBetween = nextTimestamp - currentTimestamp;
-    const timeElapsed = currentTime - currentTimestamp;
-    const interpolation = timeBetween > 0 ? timeElapsed / timeBetween : 0;
-
-    // Base position plus interpolated progress to next item
-    return Math.min(
-      100,
-      lastPassedIndex * itemPercentage + interpolation * itemPercentage,
+    const topOffset = Math.max(0, centers[0]);
+    const bottomOffset = Math.max(
+      0,
+      containerRect.height - centers[centers.length - 1],
     );
-  }, [eventSequence, effectiveTime, isWithinEventRange]);
 
-  const blueLineHeight = calculateLineHeight();
+    setLineTopOffsetPx(Math.round(topOffset));
+    setLineBottomOffsetPx(Math.round(bottomOffset));
+
+    const eff = effectiveTime ?? 0;
+    const timestamps = eventSequence.map((s) => s.timestamp ?? 0);
+
+    let pixelPos = centers[0];
+    if (eff <= timestamps[0]) {
+      pixelPos = centers[0];
+    } else if (eff >= timestamps[timestamps.length - 1]) {
+      pixelPos = centers[centers.length - 1];
+    } else {
+      for (let i = 0; i < timestamps.length - 1; i++) {
+        const t1 = timestamps[i];
+        const t2 = timestamps[i + 1];
+        if (eff >= t1 && eff <= t2) {
+          const ratio = t2 > t1 ? (eff - t1) / (t2 - t1) : 0;
+          pixelPos = centers[i] + ratio * (centers[i + 1] - centers[i]);
+          break;
+        }
+      }
+    }
+
+    const bluePx = Math.round(Math.max(0, pixelPos - topOffset));
+    setBlueLineHeightPx(bluePx);
+  }, [eventSequence, timelineSize.width, timelineSize.height, effectiveTime]);
 
   const videoSource = useMemo(() => {
     // event.start_time and event.end_time are in DETECT stream time
@@ -531,12 +553,21 @@ export function TrackingDetails({
                     {t("detail.noObjectDetailData", { ns: "views/events" })}
                   </div>
                 ) : (
-                  <div className="-pb-2 relative mx-0">
-                    <div className="absolute -top-2 bottom-8 left-6 z-0 w-0.5 -translate-x-1/2 bg-secondary-foreground" />
+                  <div
+                    className="-pb-2 relative mx-0"
+                    ref={timelineContainerRef}
+                  >
+                    <div
+                      className="absolute -top-2 left-6 z-0 w-0.5 -translate-x-1/2 bg-secondary-foreground"
+                      style={{ bottom: lineBottomOffsetPx }}
+                    />
                     {isWithinEventRange && (
                       <div
-                        className="absolute left-6 top-2 z-[5] max-h-[calc(100%-3rem)] w-0.5 -translate-x-1/2 bg-selected transition-all duration-300"
-                        style={{ height: `${blueLineHeight}%` }}
+                        className="absolute left-6 z-[5] w-0.5 -translate-x-1/2 bg-selected transition-all duration-300"
+                        style={{
+                          top: `${lineTopOffsetPx}px`,
+                          height: `${blueLineHeightPx}px`,
+                        }}
                       />
                     )}
                     <div className="space-y-2">
@@ -589,20 +620,26 @@ export function TrackingDetails({
                             : undefined;
 
                         return (
-                          <LifecycleIconRow
+                          <div
                             key={`${item.timestamp}-${item.source_id ?? ""}-${idx}`}
-                            item={item}
-                            isActive={isActive}
-                            formattedEventTimestamp={formattedEventTimestamp}
-                            ratio={ratio}
-                            areaPx={areaPx}
-                            areaPct={areaPct}
-                            onClick={() => handleLifecycleClick(item)}
-                            setSelectedZone={setSelectedZone}
-                            getZoneColor={getZoneColor}
-                            effectiveTime={effectiveTime}
-                            isTimelineActive={isWithinEventRange}
-                          />
+                            ref={(el) => {
+                              rowRefs.current[idx] = el;
+                            }}
+                          >
+                            <LifecycleIconRow
+                              item={item}
+                              isActive={isActive}
+                              formattedEventTimestamp={formattedEventTimestamp}
+                              ratio={ratio}
+                              areaPx={areaPx}
+                              areaPct={areaPct}
+                              onClick={() => handleLifecycleClick(item)}
+                              setSelectedZone={setSelectedZone}
+                              getZoneColor={getZoneColor}
+                              effectiveTime={effectiveTime}
+                              isTimelineActive={isWithinEventRange}
+                            />
+                          </div>
                         );
                       })}
                     </div>

web/src/components/player/HlsVideoPlayer.tsx

@@ -318,6 +318,7 @@ export default function HlsVideoPlayer({
         {isDetailMode &&
           camera &&
           currentTime &&
+          loadedMetadata &&
           videoDimensions.width > 0 &&
           videoDimensions.height > 0 && (
             <div className="absolute z-50 size-full">

web/src/pages/Events.tsx

@@ -15,6 +15,7 @@ import {
   ReviewSummary,
   SegmentedReviewData,
 } from "@/types/review";
+import { TimelineType } from "@/types/timeline";
 import {
   getBeginningOfDayTimestamp,
   getEndOfDayTimestamp,
@@ -49,6 +50,16 @@ export default function Events() {
     false,
   );
 
+  const [notificationTab, setNotificationTab] =
+    useState<TimelineType>("timeline");
+
+  useSearchEffect("tab", (tab: string) => {
+    if (tab === "timeline" || tab === "events" || tab === "detail") {
+      setNotificationTab(tab as TimelineType);
+    }
+    return true;
+  });
+
   useSearchEffect("id", (reviewId: string) => {
     axios
       .get(`review/${reviewId}`)
@@ -66,7 +77,7 @@ export default function Events() {
               camera: resp.data.camera,
               startTime,
               severity: resp.data.severity,
-              timelineType: "detail",
+              timelineType: notificationTab,
             },
             true,
           );

web/src/types/record.ts

@@ -1,4 +1,5 @@
 import { ReviewSeverity } from "./review";
+import { TimelineType } from "./timeline";
 
 export type Recording = {
   id: string;
@@ -37,7 +38,7 @@ export type RecordingStartingPoint = {
   camera: string;
   startTime: number;
   severity: ReviewSeverity;
-  timelineType?: "timeline" | "events" | "detail";
+  timelineType?: TimelineType;
 };
 
 export type RecordingPlayerError = "stalled" | "startup";

web/src/views/classification/ModelSelectionView.tsx

@@ -16,7 +16,6 @@ import { useCallback, useEffect, useMemo, useState } from "react";
 import { useTranslation } from "react-i18next";
 import { FaFolderPlus } from "react-icons/fa";
 import { MdModelTraining } from "react-icons/md";
-import { LuPencil, LuTrash2 } from "react-icons/lu";
 import { FiMoreVertical } from "react-icons/fi";
 import useSWR from "swr";
 import Heading from "@/components/ui/heading";
@@ -352,11 +351,9 @@ function ModelCard({ config, onClick, onUpdate, onDelete }: ModelCardProps) {
               onClick={(e) => e.stopPropagation()}
             >
               <DropdownMenuItem onClick={handleEditClick}>
-                <LuPencil className="mr-2 size-4" />
                 <span>{t("button.edit", { ns: "common" })}</span>
               </DropdownMenuItem>
               <DropdownMenuItem onClick={handleDeleteClick}>
-                <LuTrash2 className="mr-2 size-4" />
                 <span>{t("button.delete", { ns: "common" })}</span>
               </DropdownMenuItem>
             </DropdownMenuContent>

web/src/views/events/EventView.tsx

@@ -799,7 +799,7 @@ function DetectionReview({
             (itemsToReview ?? 0) > 0 && (
               <div className="col-span-full flex items-center justify-center">
                 <Button
-                  className="text-white"
+                  className="text-balance text-white"
                   aria-label={t("markTheseItemsAsReviewed")}
                   variant="select"
                   onClick={() => {

web/src/views/live/LiveCameraView.tsx

@@ -850,6 +850,29 @@ function FrigateCameraFeatures({
     }
   }, [activeToastId, t]);
 
+  const endEventViaBeacon = useCallback(() => {
+    if (!recordingEventIdRef.current) return;
+
+    const url = `${window.location.origin}/api/events/${recordingEventIdRef.current}/end`;
+    const payload = JSON.stringify({
+      end_time: Math.ceil(Date.now() / 1000),
+    });
+
+    // this needs to be a synchronous XMLHttpRequest to guarantee the PUT
+    // reaches the server before the browser kills the page
+    const xhr = new XMLHttpRequest();
+    try {
+      xhr.open("PUT", url, false);
+      xhr.setRequestHeader("Content-Type", "application/json");
+      xhr.setRequestHeader("X-CSRF-TOKEN", "1");
+      xhr.setRequestHeader("X-CACHE-BYPASS", "1");
+      xhr.withCredentials = true;
+      xhr.send(payload);
+    } catch (e) {
+      // Silently ignore errors during unload
+    }
+  }, []);
+
   const handleEventButtonClick = useCallback(() => {
     if (isRecording) {
       endEvent();
@@ -887,8 +910,19 @@ function FrigateCameraFeatures({
   }, [camera.name, isRestreamed, preferredLiveMode, t]);
 
   useEffect(() => {
+    // Handle page unload/close (browser close, tab close, refresh, navigation to external site)
+    const handleBeforeUnload = () => {
+      if (recordingEventIdRef.current) {
+        endEventViaBeacon();
+      }
+    };
+
+    window.addEventListener("beforeunload", handleBeforeUnload);
+
     // ensure manual event is stopped when component unmounts
     return () => {
+      window.removeEventListener("beforeunload", handleBeforeUnload);
+
       if (recordingEventIdRef.current) {
         endEvent();
       }

web/src/views/settings/TriggerView.tsx

@@ -201,12 +201,17 @@ export default function TriggerView({
               .then((configResponse) => {
                 if (configResponse.status === 200) {
                   updateConfig();
+                  const displayName =
+                    friendly_name && friendly_name !== ""
+                      ? `${friendly_name} (${name})`
+                      : name;
+
                   toast.success(
                     t(
                       isEdit
                         ? "triggers.toast.success.updateTrigger"
                         : "triggers.toast.success.createTrigger",
-                      { name },
+                      { name: displayName },
                     ),
                     { position: "top-center" },
                   );
@@ -351,8 +356,19 @@ export default function TriggerView({
               .then((configResponse) => {
                 if (configResponse.status === 200) {
                   updateConfig();
+                  const friendly =
+                    config?.cameras?.[selectedCamera]?.semantic_search
+                      ?.triggers?.[name]?.friendly_name;
+
+                  const displayName =
+                    friendly && friendly !== ""
+                      ? `${friendly} (${name})`
+                      : name;
+
                   toast.success(
-                    t("triggers.toast.success.deleteTrigger", { name }),
+                    t("triggers.toast.success.deleteTrigger", {
+                      name: displayName,
+                    }),
                     {
                       position: "top-center",
                     },
@@ -381,7 +397,7 @@ export default function TriggerView({
           setIsLoading(false);
         });
     },
-    [t, updateConfig, selectedCamera, setUnsavedChanges],
+    [t, updateConfig, selectedCamera, setUnsavedChanges, config],
   );
 
   useEffect(() => {
@@ -843,7 +859,14 @@ export default function TriggerView({
       />
       <DeleteTriggerDialog
         show={showDelete}
-        triggerName={selectedTrigger?.name ?? ""}
+        triggerName={
+          selectedTrigger
+            ? selectedTrigger.friendly_name &&
+              selectedTrigger.friendly_name !== ""
+              ? `${selectedTrigger.friendly_name} (${selectedTrigger.name})`
+              : selectedTrigger.name
+            : ""
+        }
         isLoading={isLoading}
         onCancel={() => {
           setShowDelete(false);

web/src/views/system/StorageMetrics.tsx

@@ -72,8 +72,7 @@ export default function StorageMetrics({
   const earliestDate = useMemo(() => {
     const keys = Object.keys(recordingsSummary || {});
     return keys.length
-      ? new TZDate(keys[keys.length - 1] + "T00:00:00", timezone).getTime() /
-          1000
+      ? new TZDate(keys[0] + "T00:00:00", timezone).getTime() / 1000
       : null;
   }, [recordingsSummary, timezone]);