Merge 256817d5c2640b4cd1167272ec606d6bbf9eb772 into 6fd7f862f51bdd2efc0634d6db7b92ca75547fbb

* Catch case where detector overflows

* Add more debug logs

* Cleanup

* Adjust no class wording

* Adjustments

README.md

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

docker/main/install_memryx.sh

@@ -2,9 +2,9 @@
 set -e
 
 # Download the MxAccl for Frigate github release
-wget https://github.com/memryx/mx_accl_frigate/archive/refs/heads/main.zip -O /tmp/mxaccl.zip
+wget https://github.com/memryx/mx_accl_frigate/archive/refs/tags/v2.1.0.zip -O /tmp/mxaccl.zip
 unzip /tmp/mxaccl.zip -d /tmp
-mv /tmp/mx_accl_frigate-main /opt/mx_accl_frigate
+mv /tmp/mx_accl_frigate-2.1.0 /opt/mx_accl_frigate
 rm /tmp/mxaccl.zip
 
 # Install Python dependencies

docker/main/requirements-wheels.txt

@@ -56,7 +56,7 @@ pywebpush == 2.0.*
 # alpr
 pyclipper == 1.3.*
 shapely == 2.0.*
-Levenshtein==0.26.*
+rapidfuzz==3.12.*
 # HailoRT Wheels
 appdirs==1.4.*
 argcomplete==2.0.*

docker/memryx/user_installation.sh

@@ -24,10 +24,13 @@ echo "Adding MemryX GPG key and repository..."
 wget -qO- https://developer.memryx.com/deb/memryx.asc | sudo tee /etc/apt/trusted.gpg.d/memryx.asc >/dev/null
 echo 'deb https://developer.memryx.com/deb stable main' | sudo tee /etc/apt/sources.list.d/memryx.list >/dev/null
 
-# Update and install memx-drivers
-echo "Installing memx-drivers..."
+# Update and install specific SDK 2.1 packages
+echo "Installing MemryX SDK 2.1 packages..."
 sudo apt update
-sudo apt install -y memx-drivers
+sudo apt install -y memx-drivers=2.1.* memx-accl=2.1.* mxa-manager=2.1.*
+
+# Hold packages to prevent automatic upgrades
+sudo apt-mark hold memx-drivers memx-accl mxa-manager
 
 # ARM-specific board setup
 if [[ "$arch" == "aarch64" || "$arch" == "arm64" ]]; then
@@ -37,11 +40,5 @@ fi
 
 echo -e "\n\n\033[1;31mYOU MUST RESTART YOUR COMPUTER NOW\033[0m\n\n"
 
-# Install other runtime packages
-packages=("memx-accl" "mxa-manager")
-for pkg in "${packages[@]}"; do
-    echo "Installing $pkg..."
-    sudo apt install -y "$pkg"
-done
+echo "MemryX SDK 2.1 installation complete!"
 
-echo "MemryX installation complete!"

docker/tensorrt/requirements-arm64.txt

@@ -1 +1,2 @@
 cuda-python == 12.6.*; platform_machine == 'aarch64'
+numpy == 1.26.*; platform_machine == 'aarch64'

docs/docs/configuration/pwa.md

@@ -11,7 +11,7 @@ This adds features including the ability to deep link directly into the app.
 
 In order to install Frigate as a PWA, the following requirements must be met:
 
-- Frigate must be accessed via a secure context (localhost, secure https, etc.)
+- Frigate must be accessed via a secure context (localhost, secure https, VPN, etc.)
 - On Android, Firefox, Chrome, Edge, Opera, and Samsung Internet Browser all support installing PWAs.
 - On iOS 16.4 and later, PWAs can be installed from the Share menu in Safari, Chrome, Edge, Firefox, and Orion.
 
@@ -22,3 +22,7 @@ Installation varies slightly based on the device that is being used:
 - Desktop: Use the install button typically found in right edge of the address bar
 - Android: Use the `Install as App` button in the more options menu for Chrome, and the `Add app to Home screen` button for Firefox
 - iOS: Use the `Add to Homescreen` button in the share menu
+
+## Usage
+
+Once setup, the Frigate app can be used wherever it has access to Frigate. This means it can be setup as local-only, VPN-only, or fully accessible depending on your needs.

docs/docs/frigate/hardware.md

@@ -129,10 +129,16 @@ In real-world deployments, even with multiple cameras running concurrently, Frig
 
 ### Google Coral TPU
 
+:::warning
+
+The Coral is no longer recommended for new Frigate installations, except in deployments with particularly low power requirements or hardware incapable of utilizing alternative AI accelerators for object detection. Instead, we suggest using one of the numerous other supported object detectors. Frigate will continue to provide support for the Coral TPU for as long as practicably possible given its still one of the most power-efficient devices for executing object detection models.
+
+:::
+
 Frigate supports both the USB and M.2 versions of the Google Coral.
 
 - The USB version is compatible with the widest variety of hardware and does not require a driver on the host machine. However, it does lack the automatic throttling features of the other versions.
-- The PCIe and M.2 versions require installation of a driver on the host. Follow the instructions for your version from https://coral.ai
+- The PCIe and M.2 versions require installation of a driver on the host. https://github.com/jnicolson/gasket-builder should be used.
 
 A single Coral can handle many cameras using the default model and will be sufficient for the majority of users. You can calculate the maximum performance of your Coral based on the inference speed reported by Frigate. With an inference speed of 10, your Coral will top out at `1000/10=100`, or 100 frames per second. If your detection fps is regularly getting close to that, you should first consider tuning motion masks. If those are already properly configured, a second Coral may be needed.
 

docs/docs/frigate/installation.md

@@ -302,7 +302,7 @@ services:
     shm_size: "512mb" # update for your cameras based on calculation above
     devices:
       - /dev/bus/usb:/dev/bus/usb # Passes the USB Coral, needs to be modified for other versions
-      - /dev/apex_0:/dev/apex_0 # Passes a PCIe Coral, follow driver instructions here https://coral.ai/docs/m2/get-started/#2a-on-linux
+      - /dev/apex_0:/dev/apex_0 # Passes a PCIe Coral, follow driver instructions here https://github.com/jnicolson/gasket-builder
       - /dev/video11:/dev/video11 # For Raspberry Pi 4B
       - /dev/dri/renderD128:/dev/dri/renderD128 # AMD / Intel GPU, needs to be updated for your hardware
       - /dev/accel:/dev/accel # Intel NPU

docs/docs/guides/getting_started.md

@@ -202,7 +202,7 @@ services:
     ...
     devices:
       - /dev/bus/usb:/dev/bus/usb # passes the USB Coral, needs to be modified for other versions
-      - /dev/apex_0:/dev/apex_0 # passes a PCIe Coral, follow driver instructions here https://coral.ai/docs/m2/get-started/#2a-on-linux
+      - /dev/apex_0:/dev/apex_0 # passes a PCIe Coral, follow driver instructions here https://github.com/jnicolson/gasket-builder
     ...
 ```
 

docs/docs/troubleshooting/edgetpu.md

@@ -68,8 +68,7 @@ The USB Coral can become stuck and need to be restarted, this can happen for a n
 
 The most common reason for the PCIe Coral not being detected is that the driver has not been installed. This process varies based on what OS and kernel that is being run.
 
-- In most cases [the Coral docs](https://coral.ai/docs/m2/get-started/#2-install-the-pcie-driver-and-edge-tpu-runtime) show how to install the driver for the PCIe based Coral.
-- For some newer Linux distros (for example, Ubuntu 22.04+), https://github.com/jnicolson/gasket-builder can be used to build and install the latest version of the driver.
+- In most cases https://github.com/jnicolson/gasket-builder can be used to build and install the latest version of the driver.
 
 ## Attempting to load TPU as pci & Fatal Python error: Illegal instruction
 

frigate/api/app.py

@@ -37,7 +37,6 @@ from frigate.stats.prometheus import get_metrics, update_metrics
 from frigate.util.builtin import (
     clean_camera_user_pass,
     flatten_config_data,
-    get_tz_modifiers,
     process_config_query_string,
     update_yaml_file_bulk,
 )
@@ -48,6 +47,7 @@ from frigate.util.services import (
     restart_frigate,
     vainfo_hwaccel,
 )
+from frigate.util.time import get_tz_modifiers
 from frigate.version import VERSION
 
 logger = logging.getLogger(__name__)
@@ -403,12 +403,13 @@ def config_set(request: Request, body: AppConfigSetBody):
                     settings,
                 )
             else:
-                # Handle nested config updates (e.g., config/classification/custom/{name})
+                # Generic handling for global config updates
                 settings = config.get_nested_object(body.update_topic)
-                if settings:
-                    request.app.config_publisher.publisher.publish(
-                        body.update_topic, settings
-                    )
+
+                # Publish None for removal, actual config for add/update
+                request.app.config_publisher.publisher.publish(
+                    body.update_topic, settings
+                )
 
     return JSONResponse(
         content=(

frigate/api/classification.py

@@ -31,7 +31,7 @@ from frigate.api.defs.response.generic_response import GenericResponse
 from frigate.api.defs.tags import Tags
 from frigate.config import FrigateConfig
 from frigate.config.camera import DetectConfig
-from frigate.const import CLIPS_DIR, FACE_DIR
+from frigate.const import CLIPS_DIR, FACE_DIR, MODEL_CACHE_DIR
 from frigate.embeddings import EmbeddingsContext
 from frigate.models import Event
 from frigate.util.classification import (
@@ -828,9 +828,13 @@ def delete_classification_model(request: Request, name: str):
             status_code=404,
         )
 
-    # Delete the classification model's data directory
-    model_dir = os.path.join(CLIPS_DIR, sanitize_filename(name))
+    # Delete the classification model's data directory in clips
+    data_dir = os.path.join(CLIPS_DIR, sanitize_filename(name))
+    if os.path.exists(data_dir):
+        shutil.rmtree(data_dir)
 
+    # Delete the classification model's files in model_cache
+    model_dir = os.path.join(MODEL_CACHE_DIR, sanitize_filename(name))
     if os.path.exists(model_dir):
         shutil.rmtree(model_dir)
 

frigate/api/event.py

@@ -2,6 +2,7 @@
 
 import base64
 import datetime
+import json
 import logging
 import os
 import random
@@ -57,8 +58,8 @@ from frigate.const import CLIPS_DIR, TRIGGER_DIR
 from frigate.embeddings import EmbeddingsContext
 from frigate.models import Event, ReviewSegment, Timeline, Trigger
 from frigate.track.object_processing import TrackedObject
-from frigate.util.builtin import get_tz_modifiers
 from frigate.util.path import get_event_thumbnail_bytes
+from frigate.util.time import get_dst_transitions, get_tz_modifiers
 
 logger = logging.getLogger(__name__)
 
@@ -813,7 +814,6 @@ def events_summary(
     allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
 ):
     tz_name = params.timezone
-    hour_modifier, minute_modifier, seconds_offset = get_tz_modifiers(tz_name)
     has_clip = params.has_clip
     has_snapshot = params.has_snapshot
 
@@ -828,33 +828,91 @@ def events_summary(
     if len(clauses) == 0:
         clauses.append((True))
 
-    groups = (
+    time_range_query = (
         Event.select(
-            Event.camera,
-            Event.label,
-            Event.sub_label,
-            Event.data,
-            fn.strftime(
-                "%Y-%m-%d",
-                fn.datetime(
-                    Event.start_time, "unixepoch", hour_modifier, minute_modifier
-                ),
-            ).alias("day"),
-            Event.zones,
-            fn.COUNT(Event.id).alias("count"),
+            fn.MIN(Event.start_time).alias("min_time"),
+            fn.MAX(Event.start_time).alias("max_time"),
         )
         .where(reduce(operator.and_, clauses) & (Event.camera << allowed_cameras))
-        .group_by(
-            Event.camera,
-            Event.label,
-            Event.sub_label,
-            Event.data,
-            (Event.start_time + seconds_offset).cast("int") / (3600 * 24),
-            Event.zones,
-        )
+        .dicts()
+        .get()
     )
 
-    return JSONResponse(content=[e for e in groups.dicts()])
+    min_time = time_range_query.get("min_time")
+    max_time = time_range_query.get("max_time")
+
+    if min_time is None or max_time is None:
+        return JSONResponse(content=[])
+
+    dst_periods = get_dst_transitions(tz_name, min_time, max_time)
+
+    grouped: dict[tuple, dict] = {}
+
+    for period_start, period_end, period_offset in dst_periods:
+        hours_offset = int(period_offset / 60 / 60)
+        minutes_offset = int(period_offset / 60 - hours_offset * 60)
+        period_hour_modifier = f"{hours_offset} hour"
+        period_minute_modifier = f"{minutes_offset} minute"
+
+        period_groups = (
+            Event.select(
+                Event.camera,
+                Event.label,
+                Event.sub_label,
+                Event.data,
+                fn.strftime(
+                    "%Y-%m-%d",
+                    fn.datetime(
+                        Event.start_time,
+                        "unixepoch",
+                        period_hour_modifier,
+                        period_minute_modifier,
+                    ),
+                ).alias("day"),
+                Event.zones,
+                fn.COUNT(Event.id).alias("count"),
+            )
+            .where(
+                reduce(operator.and_, clauses)
+                & (Event.camera << allowed_cameras)
+                & (Event.start_time >= period_start)
+                & (Event.start_time <= period_end)
+            )
+            .group_by(
+                Event.camera,
+                Event.label,
+                Event.sub_label,
+                Event.data,
+                (Event.start_time + period_offset).cast("int") / (3600 * 24),
+                Event.zones,
+            )
+            .namedtuples()
+        )
+
+        for g in period_groups:
+            key = (
+                g.camera,
+                g.label,
+                g.sub_label,
+                json.dumps(g.data, sort_keys=True) if g.data is not None else None,
+                g.day,
+                json.dumps(g.zones, sort_keys=True) if g.zones is not None else None,
+            )
+
+            if key in grouped:
+                grouped[key]["count"] += int(g.count or 0)
+            else:
+                grouped[key] = {
+                    "camera": g.camera,
+                    "label": g.label,
+                    "sub_label": g.sub_label,
+                    "data": g.data,
+                    "day": g.day,
+                    "zones": g.zones,
+                    "count": int(g.count or 0),
+                }
+
+    return JSONResponse(content=list(grouped.values()))
 
 
 @router.get(

frigate/api/export.py

@@ -34,7 +34,7 @@ from frigate.record.export import (
     PlaybackSourceEnum,
     RecordingExporter,
 )
-from frigate.util.builtin import is_current_hour
+from frigate.util.time import is_current_hour
 
 logger = logging.getLogger(__name__)
 

frigate/api/media.py

@@ -44,9 +44,9 @@ from frigate.const import (
 )
 from frigate.models import Event, Previews, Recordings, Regions, ReviewSegment
 from frigate.track.object_processing import TrackedObjectProcessor
-from frigate.util.builtin import get_tz_modifiers
 from frigate.util.image import get_image_from_recording
 from frigate.util.path import get_event_thumbnail_bytes
+from frigate.util.time import get_dst_transitions
 
 logger = logging.getLogger(__name__)
 
@@ -424,7 +424,6 @@ def all_recordings_summary(
     allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
 ):
     """Returns true/false by day indicating if recordings exist"""
-    hour_modifier, minute_modifier, seconds_offset = get_tz_modifiers(params.timezone)
 
     cameras = params.cameras
     if cameras != "all":
@@ -432,41 +431,70 @@ def all_recordings_summary(
         filtered = requested.intersection(allowed_cameras)
         if not filtered:
             return JSONResponse(content={})
-        cameras = ",".join(filtered)
+        camera_list = list(filtered)
     else:
-        cameras = allowed_cameras
+        camera_list = allowed_cameras
 
-    query = (
+    time_range_query = (
         Recordings.select(
-            fn.strftime(
-                "%Y-%m-%d",
-                fn.datetime(
-                    Recordings.start_time + seconds_offset,
-                    "unixepoch",
-                    hour_modifier,
-                    minute_modifier,
-                ),
-            ).alias("day")
+            fn.MIN(Recordings.start_time).alias("min_time"),
+            fn.MAX(Recordings.start_time).alias("max_time"),
         )
-        .group_by(
-            fn.strftime(
-                "%Y-%m-%d",
-                fn.datetime(
-                    Recordings.start_time + seconds_offset,
-                    "unixepoch",
-                    hour_modifier,
-                    minute_modifier,
-                ),
-            )
-        )
-        .order_by(Recordings.start_time.desc())
+        .where(Recordings.camera << camera_list)
+        .dicts()
+        .get()
     )
 
-    if params.cameras != "all":
-        query = query.where(Recordings.camera << cameras.split(","))
+    min_time = time_range_query.get("min_time")
+    max_time = time_range_query.get("max_time")
 
-    recording_days = query.namedtuples()
-    days = {day.day: True for day in recording_days}
+    if min_time is None or max_time is None:
+        return JSONResponse(content={})
+
+    dst_periods = get_dst_transitions(params.timezone, min_time, max_time)
+
+    days: dict[str, bool] = {}
+
+    for period_start, period_end, period_offset in dst_periods:
+        hours_offset = int(period_offset / 60 / 60)
+        minutes_offset = int(period_offset / 60 - hours_offset * 60)
+        period_hour_modifier = f"{hours_offset} hour"
+        period_minute_modifier = f"{minutes_offset} minute"
+
+        period_query = (
+            Recordings.select(
+                fn.strftime(
+                    "%Y-%m-%d",
+                    fn.datetime(
+                        Recordings.start_time,
+                        "unixepoch",
+                        period_hour_modifier,
+                        period_minute_modifier,
+                    ),
+                ).alias("day")
+            )
+            .where(
+                (Recordings.camera << camera_list)
+                & (Recordings.end_time >= period_start)
+                & (Recordings.start_time <= period_end)
+            )
+            .group_by(
+                fn.strftime(
+                    "%Y-%m-%d",
+                    fn.datetime(
+                        Recordings.start_time,
+                        "unixepoch",
+                        period_hour_modifier,
+                        period_minute_modifier,
+                    ),
+                )
+            )
+            .order_by(Recordings.start_time.desc())
+            .namedtuples()
+        )
+
+        for g in period_query:
+            days[g.day] = True
 
     return JSONResponse(content=days)
 
@@ -476,61 +504,103 @@ def all_recordings_summary(
 )
 async def recordings_summary(camera_name: str, timezone: str = "utc"):
     """Returns hourly summary for recordings of given camera"""
-    hour_modifier, minute_modifier, seconds_offset = get_tz_modifiers(timezone)
-    recording_groups = (
+
+    time_range_query = (
         Recordings.select(
-            fn.strftime(
-                "%Y-%m-%d %H",
-                fn.datetime(
-                    Recordings.start_time, "unixepoch", hour_modifier, minute_modifier
-                ),
-            ).alias("hour"),
-            fn.SUM(Recordings.duration).alias("duration"),
-            fn.SUM(Recordings.motion).alias("motion"),
-            fn.SUM(Recordings.objects).alias("objects"),
+            fn.MIN(Recordings.start_time).alias("min_time"),
+            fn.MAX(Recordings.start_time).alias("max_time"),
         )
         .where(Recordings.camera == camera_name)
-        .group_by((Recordings.start_time + seconds_offset).cast("int") / 3600)
-        .order_by(Recordings.start_time.desc())
-        .namedtuples()
+        .dicts()
+        .get()
     )
 
-    event_groups = (
-        Event.select(
-            fn.strftime(
-                "%Y-%m-%d %H",
-                fn.datetime(
-                    Event.start_time, "unixepoch", hour_modifier, minute_modifier
-                ),
-            ).alias("hour"),
-            fn.COUNT(Event.id).alias("count"),
+    min_time = time_range_query.get("min_time")
+    max_time = time_range_query.get("max_time")
+
+    days: dict[str, dict] = {}
+
+    if min_time is None or max_time is None:
+        return JSONResponse(content=list(days.values()))
+
+    dst_periods = get_dst_transitions(timezone, min_time, max_time)
+
+    for period_start, period_end, period_offset in dst_periods:
+        hours_offset = int(period_offset / 60 / 60)
+        minutes_offset = int(period_offset / 60 - hours_offset * 60)
+        period_hour_modifier = f"{hours_offset} hour"
+        period_minute_modifier = f"{minutes_offset} minute"
+
+        recording_groups = (
+            Recordings.select(
+                fn.strftime(
+                    "%Y-%m-%d %H",
+                    fn.datetime(
+                        Recordings.start_time,
+                        "unixepoch",
+                        period_hour_modifier,
+                        period_minute_modifier,
+                    ),
+                ).alias("hour"),
+                fn.SUM(Recordings.duration).alias("duration"),
+                fn.SUM(Recordings.motion).alias("motion"),
+                fn.SUM(Recordings.objects).alias("objects"),
+            )
+            .where(
+                (Recordings.camera == camera_name)
+                & (Recordings.end_time >= period_start)
+                & (Recordings.start_time <= period_end)
+            )
+            .group_by((Recordings.start_time + period_offset).cast("int") / 3600)
+            .order_by(Recordings.start_time.desc())
+            .namedtuples()
         )
-        .where(Event.camera == camera_name, Event.has_clip)
-        .group_by((Event.start_time + seconds_offset).cast("int") / 3600)
-        .namedtuples()
-    )
 
-    event_map = {g.hour: g.count for g in event_groups}
+        event_groups = (
+            Event.select(
+                fn.strftime(
+                    "%Y-%m-%d %H",
+                    fn.datetime(
+                        Event.start_time,
+                        "unixepoch",
+                        period_hour_modifier,
+                        period_minute_modifier,
+                    ),
+                ).alias("hour"),
+                fn.COUNT(Event.id).alias("count"),
+            )
+            .where(Event.camera == camera_name, Event.has_clip)
+            .where(
+                (Event.start_time >= period_start) & (Event.start_time <= period_end)
+            )
+            .group_by((Event.start_time + period_offset).cast("int") / 3600)
+            .namedtuples()
+        )
 
-    days = {}
+        event_map = {g.hour: g.count for g in event_groups}
 
-    for recording_group in recording_groups:
-        parts = recording_group.hour.split()
-        hour = parts[1]
-        day = parts[0]
-        events_count = event_map.get(recording_group.hour, 0)
-        hour_data = {
-            "hour": hour,
-            "events": events_count,
-            "motion": recording_group.motion,
-            "objects": recording_group.objects,
-            "duration": round(recording_group.duration),
-        }
-        if day not in days:
-            days[day] = {"events": events_count, "hours": [hour_data], "day": day}
-        else:
-            days[day]["events"] += events_count
-            days[day]["hours"].append(hour_data)
+        for recording_group in recording_groups:
+            parts = recording_group.hour.split()
+            hour = parts[1]
+            day = parts[0]
+            events_count = event_map.get(recording_group.hour, 0)
+            hour_data = {
+                "hour": hour,
+                "events": events_count,
+                "motion": recording_group.motion,
+                "objects": recording_group.objects,
+                "duration": round(recording_group.duration),
+            }
+            if day in days:
+                # merge counts if already present (edge-case at DST boundary)
+                days[day]["events"] += events_count or 0
+                days[day]["hours"].append(hour_data)
+            else:
+                days[day] = {
+                    "events": events_count or 0,
+                    "hours": [hour_data],
+                    "day": day,
+                }
 
     return JSONResponse(content=list(days.values()))
 

frigate/api/review.py

@@ -36,7 +36,7 @@ from frigate.config import FrigateConfig
 from frigate.embeddings import EmbeddingsContext
 from frigate.models import Recordings, ReviewSegment, UserReviewStatus
 from frigate.review.types import SeverityEnum
-from frigate.util.builtin import get_tz_modifiers
+from frigate.util.time import get_dst_transitions
 
 logger = logging.getLogger(__name__)
 
@@ -197,7 +197,6 @@ async def review_summary(
 
     user_id = current_user["username"]
 
-    hour_modifier, minute_modifier, seconds_offset = get_tz_modifiers(params.timezone)
     day_ago = (datetime.datetime.now() - datetime.timedelta(hours=24)).timestamp()
 
     cameras = params.cameras
@@ -329,89 +328,135 @@ async def review_summary(
             )
         clauses.append(reduce(operator.or_, label_clauses))
 
-    day_in_seconds = 60 * 60 * 24
-    last_month_query = (
+    # Find the time range of available data
+    time_range_query = (
         ReviewSegment.select(
-            fn.strftime(
-                "%Y-%m-%d",
-                fn.datetime(
-                    ReviewSegment.start_time,
-                    "unixepoch",
-                    hour_modifier,
-                    minute_modifier,
-                ),
-            ).alias("day"),
-            fn.SUM(
-                Case(
-                    None,
-                    [
-                        (
-                            (ReviewSegment.severity == SeverityEnum.alert)
-                            & (UserReviewStatus.has_been_reviewed == True),
-                            1,
-                        )
-                    ],
-                    0,
-                )
-            ).alias("reviewed_alert"),
-            fn.SUM(
-                Case(
-                    None,
-                    [
-                        (
-                            (ReviewSegment.severity == SeverityEnum.detection)
-                            & (UserReviewStatus.has_been_reviewed == True),
-                            1,
-                        )
-                    ],
-                    0,
-                )
-            ).alias("reviewed_detection"),
-            fn.SUM(
-                Case(
-                    None,
-                    [
-                        (
-                            (ReviewSegment.severity == SeverityEnum.alert),
-                            1,
-                        )
-                    ],
-                    0,
-                )
-            ).alias("total_alert"),
-            fn.SUM(
-                Case(
-                    None,
-                    [
-                        (
-                            (ReviewSegment.severity == SeverityEnum.detection),
-                            1,
-                        )
-                    ],
-                    0,
-                )
-            ).alias("total_detection"),
-        )
-        .left_outer_join(
-            UserReviewStatus,
-            on=(
-                (ReviewSegment.id == UserReviewStatus.review_segment)
-                & (UserReviewStatus.user_id == user_id)
-            ),
+            fn.MIN(ReviewSegment.start_time).alias("min_time"),
+            fn.MAX(ReviewSegment.start_time).alias("max_time"),
         )
         .where(reduce(operator.and_, clauses) if clauses else True)
-        .group_by(
-            (ReviewSegment.start_time + seconds_offset).cast("int") / day_in_seconds
-        )
-        .order_by(ReviewSegment.start_time.desc())
+        .dicts()
+        .get()
     )
 
+    min_time = time_range_query.get("min_time")
+    max_time = time_range_query.get("max_time")
+
     data = {
         "last24Hours": last_24_query,
     }
 
-    for e in last_month_query.dicts().iterator():
-        data[e["day"]] = e
+    # If no data, return early
+    if min_time is None or max_time is None:
+        return JSONResponse(content=data)
+
+    # Get DST transition periods
+    dst_periods = get_dst_transitions(params.timezone, min_time, max_time)
+
+    day_in_seconds = 60 * 60 * 24
+
+    # Query each DST period separately with the correct offset
+    for period_start, period_end, period_offset in dst_periods:
+        # Calculate hour/minute modifiers for this period
+        hours_offset = int(period_offset / 60 / 60)
+        minutes_offset = int(period_offset / 60 - hours_offset * 60)
+        period_hour_modifier = f"{hours_offset} hour"
+        period_minute_modifier = f"{minutes_offset} minute"
+
+        # Build clauses including time range for this period
+        period_clauses = clauses.copy()
+        period_clauses.append(
+            (ReviewSegment.start_time >= period_start)
+            & (ReviewSegment.start_time <= period_end)
+        )
+
+        period_query = (
+            ReviewSegment.select(
+                fn.strftime(
+                    "%Y-%m-%d",
+                    fn.datetime(
+                        ReviewSegment.start_time,
+                        "unixepoch",
+                        period_hour_modifier,
+                        period_minute_modifier,
+                    ),
+                ).alias("day"),
+                fn.SUM(
+                    Case(
+                        None,
+                        [
+                            (
+                                (ReviewSegment.severity == SeverityEnum.alert)
+                                & (UserReviewStatus.has_been_reviewed == True),
+                                1,
+                            )
+                        ],
+                        0,
+                    )
+                ).alias("reviewed_alert"),
+                fn.SUM(
+                    Case(
+                        None,
+                        [
+                            (
+                                (ReviewSegment.severity == SeverityEnum.detection)
+                                & (UserReviewStatus.has_been_reviewed == True),
+                                1,
+                            )
+                        ],
+                        0,
+                    )
+                ).alias("reviewed_detection"),
+                fn.SUM(
+                    Case(
+                        None,
+                        [
+                            (
+                                (ReviewSegment.severity == SeverityEnum.alert),
+                                1,
+                            )
+                        ],
+                        0,
+                    )
+                ).alias("total_alert"),
+                fn.SUM(
+                    Case(
+                        None,
+                        [
+                            (
+                                (ReviewSegment.severity == SeverityEnum.detection),
+                                1,
+                            )
+                        ],
+                        0,
+                    )
+                ).alias("total_detection"),
+            )
+            .left_outer_join(
+                UserReviewStatus,
+                on=(
+                    (ReviewSegment.id == UserReviewStatus.review_segment)
+                    & (UserReviewStatus.user_id == user_id)
+                ),
+            )
+            .where(reduce(operator.and_, period_clauses))
+            .group_by(
+                (ReviewSegment.start_time + period_offset).cast("int") / day_in_seconds
+            )
+            .order_by(ReviewSegment.start_time.desc())
+        )
+
+        # Merge results from this period
+        for e in period_query.dicts().iterator():
+            day_key = e["day"]
+            if day_key in data:
+                # Merge counts if day already exists (edge case at DST boundary)
+                data[day_key]["reviewed_alert"] += e["reviewed_alert"] or 0
+                data[day_key]["reviewed_detection"] += e["reviewed_detection"] or 0
+                data[day_key]["total_alert"] += e["total_alert"] or 0
+                data[day_key]["total_detection"] += e["total_detection"] or 0
+            else:
+                data[day_key] = e
 
     return JSONResponse(content=data)
 

frigate/data_processing/common/license_plate/mixin.py

@@ -14,8 +14,8 @@ from typing import Any, List, Optional, Tuple
 
 import cv2
 import numpy as np
-from Levenshtein import distance, jaro_winkler
 from pyclipper import ET_CLOSEDPOLYGON, JT_ROUND, PyclipperOffset
+from rapidfuzz.distance import JaroWinkler, Levenshtein
 from shapely.geometry import Polygon
 
 from frigate.comms.event_metadata_updater import (
@@ -1123,7 +1123,9 @@ class LicensePlateProcessingMixin:
         for i, plate in enumerate(plates):
             merged = False
             for j, cluster in enumerate(clusters):
-                sims = [jaro_winkler(plate["plate"], v["plate"]) for v in cluster]
+                sims = [
+                    JaroWinkler.similarity(plate["plate"], v["plate"]) for v in cluster
+                ]
                 if len(sims) > 0:
                     avg_sim = sum(sims) / len(sims)
                     if avg_sim >= self.cluster_threshold:
@@ -1500,7 +1502,7 @@ class LicensePlateProcessingMixin:
                     and current_time - data["last_seen"]
                     <= self.config.cameras[camera].lpr.expire_time
                 ):
-                    similarity = jaro_winkler(data["plate"], top_plate)
+                    similarity = JaroWinkler.similarity(data["plate"], top_plate)
                     if similarity >= self.similarity_threshold:
                         plate_id = existing_id
                         logger.debug(
@@ -1580,7 +1582,8 @@ class LicensePlateProcessingMixin:
                     for label, plates_list in self.lpr_config.known_plates.items()
                     if any(
                         re.match(f"^{plate}$", rep_plate)
-                        or distance(plate, rep_plate) <= self.lpr_config.match_distance
+                        or Levenshtein.distance(plate, rep_plate)
+                        <= self.lpr_config.match_distance
                         for plate in plates_list
                     )
                 ),

frigate/data_processing/real_time/face.py

@@ -166,6 +166,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
         camera = obj_data["camera"]
 
         if not self.config.cameras[camera].face_recognition.enabled:
+            logger.debug(f"Face recognition disabled for camera {camera}, skipping")
             return
 
         start = datetime.datetime.now().timestamp()
@@ -208,6 +209,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             person_box = obj_data.get("box")
 
             if not person_box:
+                logger.debug(f"No person box available for {id}")
                 return
 
             rgb = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
@@ -233,7 +235,8 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
             try:
                 face_frame = cv2.cvtColor(face_frame, cv2.COLOR_RGB2BGR)
-            except Exception:
+            except Exception as e:
+                logger.debug(f"Failed to convert face frame color for {id}: {e}")
                 return
         else:
             # don't run for object without attributes
@@ -251,6 +254,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
             # no faces detected in this frame
             if not face:
+                logger.debug(f"No face attributes found for {id}")
                 return
 
             face_box = face.get("box")
@@ -274,6 +278,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
         res = self.recognizer.classify(face_frame)
 
         if not res:
+            logger.debug(f"Face recognizer returned no result for {id}")
             self.__update_metrics(datetime.datetime.now().timestamp() - start)
             return
 
@@ -330,6 +335,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
     def handle_request(self, topic, request_data) -> dict[str, Any] | None:
         if topic == EmbeddingsRequestEnum.clear_face_classifier.value:
             self.recognizer.clear()
+            return {"success": True, "message": "Face classifier cleared."}
         elif topic == EmbeddingsRequestEnum.recognize_face.value:
             img = cv2.imdecode(
                 np.frombuffer(base64.b64decode(request_data["image"]), dtype=np.uint8),

frigate/embeddings/maintainer.py

@@ -158,11 +158,13 @@ class EmbeddingMaintainer(threading.Thread):
         self.realtime_processors: list[RealTimeProcessorApi] = []
 
         if self.config.face_recognition.enabled:
+            logger.debug("Face recognition enabled, initializing FaceRealTimeProcessor")
             self.realtime_processors.append(
                 FaceRealTimeProcessor(
                     self.config, self.requestor, self.event_metadata_publisher, metrics
                 )
             )
+            logger.debug("FaceRealTimeProcessor initialized successfully")
 
         if self.config.classification.bird.enabled:
             self.realtime_processors.append(
@@ -283,44 +285,65 @@ class EmbeddingMaintainer(threading.Thread):
         logger.info("Exiting embeddings maintenance...")
 
     def _check_classification_config_updates(self) -> None:
-        """Check for classification config updates and add new processors."""
+        """Check for classification config updates and add/remove processors."""
         topic, model_config = self.classification_config_subscriber.check_for_update()
 
-        if topic and model_config:
+        if topic:
             model_name = topic.split("/")[-1]
-            self.config.classification.custom[model_name] = model_config
 
-            # Check if processor already exists
-            for processor in self.realtime_processors:
-                if isinstance(
-                    processor,
-                    (
-                        CustomStateClassificationProcessor,
-                        CustomObjectClassificationProcessor,
-                    ),
-                ):
-                    if processor.model_config.name == model_name:
-                        logger.debug(
-                            f"Classification processor for model {model_name} already exists, skipping"
+            if model_config is None:
+                self.realtime_processors = [
+                    processor
+                    for processor in self.realtime_processors
+                    if not (
+                        isinstance(
+                            processor,
+                            (
+                                CustomStateClassificationProcessor,
+                                CustomObjectClassificationProcessor,
+                            ),
                         )
-                        return
+                        and processor.model_config.name == model_name
+                    )
+                ]
 
-            if model_config.state_config is not None:
-                processor = CustomStateClassificationProcessor(
-                    self.config, model_config, self.requestor, self.metrics
+                logger.info(
+                    f"Successfully removed classification processor for model: {model_name}"
                 )
             else:
-                processor = CustomObjectClassificationProcessor(
-                    self.config,
-                    model_config,
-                    self.event_metadata_publisher,
-                    self.metrics,
-                )
+                self.config.classification.custom[model_name] = model_config
 
-            self.realtime_processors.append(processor)
-            logger.info(
-                f"Added classification processor for model: {model_name} (type: {type(processor).__name__})"
-            )
+                # Check if processor already exists
+                for processor in self.realtime_processors:
+                    if isinstance(
+                        processor,
+                        (
+                            CustomStateClassificationProcessor,
+                            CustomObjectClassificationProcessor,
+                        ),
+                    ):
+                        if processor.model_config.name == model_name:
+                            logger.debug(
+                                f"Classification processor for model {model_name} already exists, skipping"
+                            )
+                            return
+
+                if model_config.state_config is not None:
+                    processor = CustomStateClassificationProcessor(
+                        self.config, model_config, self.requestor, self.metrics
+                    )
+                else:
+                    processor = CustomObjectClassificationProcessor(
+                        self.config,
+                        model_config,
+                        self.event_metadata_publisher,
+                        self.metrics,
+                    )
+
+                self.realtime_processors.append(processor)
+                logger.info(
+                    f"Added classification processor for model: {model_name} (type: {type(processor).__name__})"
+                )
 
     def _process_requests(self) -> None:
         """Process embeddings requests"""
@@ -374,7 +397,14 @@ class EmbeddingMaintainer(threading.Thread):
 
         source_type, _, camera, frame_name, data = update
 
+        logger.debug(
+            f"Received update - source_type: {source_type}, camera: {camera}, data label: {data.get('label') if data else 'None'}"
+        )
+
         if not camera or source_type != EventTypeEnum.tracked_object:
+            logger.debug(
+                f"Skipping update - camera: {camera}, source_type: {source_type}"
+            )
             return
 
         if self.config.semantic_search.enabled:
@@ -384,6 +414,9 @@ class EmbeddingMaintainer(threading.Thread):
 
         # no need to process updated objects if no processors are active
         if len(self.realtime_processors) == 0 and len(self.post_processors) == 0:
+            logger.debug(
+                f"No processors active - realtime: {len(self.realtime_processors)}, post: {len(self.post_processors)}"
+            )
             return
 
         # Create our own thumbnail based on the bounding box and the frame time
@@ -392,6 +425,7 @@ class EmbeddingMaintainer(threading.Thread):
                 frame_name, camera_config.frame_shape_yuv
             )
         except FileNotFoundError:
+            logger.debug(f"Frame {frame_name} not found for camera {camera}")
             pass
 
         if yuv_frame is None:
@@ -400,7 +434,11 @@ class EmbeddingMaintainer(threading.Thread):
             )
             return
 
+        logger.debug(
+            f"Processing {len(self.realtime_processors)} realtime processors for object {data.get('id')} (label: {data.get('label')})"
+        )
         for processor in self.realtime_processors:
+            logger.debug(f"Calling process_frame on {processor.__class__.__name__}")
             processor.process_frame(data, yuv_frame)
 
         for processor in self.post_processors:

frigate/object_detection/base.py

@@ -9,6 +9,7 @@ from multiprocessing import Queue, Value
 from multiprocessing.synchronize import Event as MpEvent
 
 import numpy as np
+import zmq
 
 from frigate.comms.object_detector_signaler import (
     ObjectDetectorPublisher,
@@ -377,6 +378,15 @@ class RemoteObjectDetector:
         if self.stop_event.is_set():
             return detections
 
+        # Drain any stale detection results from the ZMQ buffer before making a new request
+        # This prevents reading detection results from a previous request
+        # NOTE: This should never happen, but can in some rare cases
+        while True:
+            try:
+                self.detector_subscriber.socket.recv_string(flags=zmq.NOBLOCK)
+            except zmq.Again:
+                break
+
         # copy input to shared memory
         self.np_shm[:] = tensor_input[:]
         self.detection_queue.put(self.name)

frigate/record/cleanup.py

@@ -14,7 +14,8 @@ from frigate.config import CameraConfig, FrigateConfig, RetainModeEnum
 from frigate.const import CACHE_DIR, CLIPS_DIR, MAX_WAL_SIZE, RECORD_DIR
 from frigate.models import Previews, Recordings, ReviewSegment, UserReviewStatus
 from frigate.record.util import remove_empty_directories, sync_recordings
-from frigate.util.builtin import clear_and_unlink, get_tomorrow_at_time
+from frigate.util.builtin import clear_and_unlink
+from frigate.util.time import get_tomorrow_at_time
 
 logger = logging.getLogger(__name__)
 

frigate/record/export.py

@@ -28,7 +28,7 @@ from frigate.ffmpeg_presets import (
     parse_preset_hardware_acceleration_encode,
 )
 from frigate.models import Export, Previews, Recordings
-from frigate.util.builtin import is_current_hour
+from frigate.util.time import is_current_hour
 
 logger = logging.getLogger(__name__)
 

frigate/util/builtin.py

@@ -15,12 +15,9 @@ from collections.abc import Mapping
 from multiprocessing.sharedctypes import Synchronized
 from pathlib import Path
 from typing import Any, Dict, Optional, Tuple, Union
-from zoneinfo import ZoneInfoNotFoundError
 
 import numpy as np
-import pytz
 from ruamel.yaml import YAML
-from tzlocal import get_localzone
 
 from frigate.const import REGEX_HTTP_CAMERA_USER_PASS, REGEX_RTSP_CAMERA_USER_PASS
 
@@ -157,17 +154,6 @@ def load_labels(path: Optional[str], encoding="utf-8", prefill=91):
         return labels
 
 
-def get_tz_modifiers(tz_name: str) -> Tuple[str, str, float]:
-    seconds_offset = (
-        datetime.datetime.now(pytz.timezone(tz_name)).utcoffset().total_seconds()
-    )
-    hours_offset = int(seconds_offset / 60 / 60)
-    minutes_offset = int(seconds_offset / 60 - hours_offset * 60)
-    hour_modifier = f"{hours_offset} hour"
-    minute_modifier = f"{minutes_offset} minute"
-    return hour_modifier, minute_modifier, seconds_offset
-
-
 def to_relative_box(
     width: int, height: int, box: Tuple[int, int, int, int]
 ) -> Tuple[int | float, int | float, int | float, int | float]:
@@ -298,34 +284,6 @@ def find_by_key(dictionary, target_key):
     return None
 
 
-def get_tomorrow_at_time(hour: int) -> datetime.datetime:
-    """Returns the datetime of the following day at 2am."""
-    try:
-        tomorrow = datetime.datetime.now(get_localzone()) + datetime.timedelta(days=1)
-    except ZoneInfoNotFoundError:
-        tomorrow = datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(
-            days=1
-        )
-        logger.warning(
-            "Using utc for maintenance due to missing or incorrect timezone set"
-        )
-
-    return tomorrow.replace(hour=hour, minute=0, second=0).astimezone(
-        datetime.timezone.utc
-    )
-
-
-def is_current_hour(timestamp: int) -> bool:
-    """Returns if timestamp is in the current UTC hour."""
-    start_of_next_hour = (
-        datetime.datetime.now(datetime.timezone.utc).replace(
-            minute=0, second=0, microsecond=0
-        )
-        + datetime.timedelta(hours=1)
-    ).timestamp()
-    return timestamp < start_of_next_hour
-
-
 def clear_and_unlink(file: Path, missing_ok: bool = True) -> None:
     """clear file then unlink to avoid space retained by file descriptors."""
     if not missing_ok and not file.exists():

frigate/util/time.py

@@ -0,0 +1,100 @@
+"""Time utilities."""
+
+import datetime
+import logging
+from typing import Tuple
+from zoneinfo import ZoneInfoNotFoundError
+
+import pytz
+from tzlocal import get_localzone
+
+logger = logging.getLogger(__name__)
+
+
+def get_tz_modifiers(tz_name: str) -> Tuple[str, str, float]:
+    seconds_offset = (
+        datetime.datetime.now(pytz.timezone(tz_name)).utcoffset().total_seconds()
+    )
+    hours_offset = int(seconds_offset / 60 / 60)
+    minutes_offset = int(seconds_offset / 60 - hours_offset * 60)
+    hour_modifier = f"{hours_offset} hour"
+    minute_modifier = f"{minutes_offset} minute"
+    return hour_modifier, minute_modifier, seconds_offset
+
+
+def get_tomorrow_at_time(hour: int) -> datetime.datetime:
+    """Returns the datetime of the following day at 2am."""
+    try:
+        tomorrow = datetime.datetime.now(get_localzone()) + datetime.timedelta(days=1)
+    except ZoneInfoNotFoundError:
+        tomorrow = datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(
+            days=1
+        )
+        logger.warning(
+            "Using utc for maintenance due to missing or incorrect timezone set"
+        )
+
+    return tomorrow.replace(hour=hour, minute=0, second=0).astimezone(
+        datetime.timezone.utc
+    )
+
+
+def is_current_hour(timestamp: int) -> bool:
+    """Returns if timestamp is in the current UTC hour."""
+    start_of_next_hour = (
+        datetime.datetime.now(datetime.timezone.utc).replace(
+            minute=0, second=0, microsecond=0
+        )
+        + datetime.timedelta(hours=1)
+    ).timestamp()
+    return timestamp < start_of_next_hour
+
+
+def get_dst_transitions(
+    tz_name: str, start_time: float, end_time: float
+) -> list[tuple[float, float]]:
+    """
+    Find DST transition points and return time periods with consistent offsets.
+
+    Args:
+        tz_name: Timezone name (e.g., 'America/New_York')
+        start_time: Start timestamp (UTC)
+        end_time: End timestamp (UTC)
+
+    Returns:
+        List of (period_start, period_end, seconds_offset) tuples representing
+        continuous periods with the same UTC offset
+    """
+    try:
+        tz = pytz.timezone(tz_name)
+    except pytz.UnknownTimeZoneError:
+        # If timezone is invalid, return single period with no offset
+        return [(start_time, end_time, 0)]
+
+    periods = []
+    current = start_time
+
+    # Get initial offset
+    dt = datetime.datetime.utcfromtimestamp(current).replace(tzinfo=pytz.UTC)
+    local_dt = dt.astimezone(tz)
+    prev_offset = local_dt.utcoffset().total_seconds()
+    period_start = start_time
+
+    # Check each day for offset changes
+    while current <= end_time:
+        dt = datetime.datetime.utcfromtimestamp(current).replace(tzinfo=pytz.UTC)
+        local_dt = dt.astimezone(tz)
+        current_offset = local_dt.utcoffset().total_seconds()
+
+        if current_offset != prev_offset:
+            # Found a transition - close previous period
+            periods.append((period_start, current, prev_offset))
+            period_start = current
+            prev_offset = current_offset
+
+        current += 86400  # Check daily
+
+    # Add final period
+    periods.append((period_start, end_time, prev_offset))
+
+    return periods

frigate/video.py

@@ -34,7 +34,7 @@ from frigate.ptz.autotrack import ptz_moving_at_frame_time
 from frigate.track import ObjectTracker
 from frigate.track.norfair_tracker import NorfairTracker
 from frigate.track.tracked_object import TrackedObjectAttribute
-from frigate.util.builtin import EventsPerSecond, get_tomorrow_at_time
+from frigate.util.builtin import EventsPerSecond
 from frigate.util.image import (
     FrameManager,
     SharedMemoryFrameManager,
@@ -53,6 +53,7 @@ from frigate.util.object import (
     reduce_detections,
 )
 from frigate.util.process import FrigateProcess
+from frigate.util.time import get_tomorrow_at_time
 
 logger = logging.getLogger(__name__)
 

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

@@ -271,6 +271,8 @@
       "disconnectStream": "Disconnect",
       "estimatedBandwidth": "Estimated Bandwidth",
       "roles": "Roles",
+      "ffmpegModule": "Use stream compatibility mode",
+      "ffmpegModuleDescription": "If the stream does not load after several attempts, try enabling this. When enabled, Frigate will use the ffmpeg module with go2rtc. This may provide better compatibility with some camera streams.",
       "none": "None",
       "error": "Error",
       "streamValidated": "Stream {{number}} validated successfully",

web/src/components/card/ClassificationCard.tsx

@@ -181,6 +181,7 @@ type GroupedClassificationCardProps = {
   selectedItems: string[];
   i18nLibrary: string;
   objectType: string;
+  noClassificationLabel?: string;
   onClick: (data: ClassificationItemData | undefined) => void;
   children?: (data: ClassificationItemData) => React.ReactNode;
 };
@@ -190,6 +191,7 @@ export function GroupedClassificationCard({
   threshold,
   selectedItems,
   i18nLibrary,
+  noClassificationLabel = "details.none",
   onClick,
   children,
 }: GroupedClassificationCardProps) {
@@ -222,10 +224,14 @@ export function GroupedClassificationCard({
     const bestTyped: ClassificationItemData = best;
     return {
       ...bestTyped,
-      name: event ? (event.sub_label ?? t("details.unknown")) : bestTyped.name,
+      name: event
+        ? event.sub_label && event.sub_label !== "none"
+          ? event.sub_label
+          : t(noClassificationLabel)
+        : bestTyped.name,
       score: event?.data?.sub_label_score || bestTyped.score,
     };
-  }, [group, event, t]);
+  }, [group, event, noClassificationLabel, t]);
 
   const bestScoreStatus = useMemo(() => {
     if (!bestItem?.score || !threshold) {
@@ -311,8 +317,10 @@ export function GroupedClassificationCard({
                     isMobile && "px-2",
                   )}
                 >
-                  {event?.sub_label ? event.sub_label : t("details.unknown")}
-                  {event?.sub_label && (
+                  {event?.sub_label && event.sub_label !== "none"
+                    ? event.sub_label
+                    : t(noClassificationLabel)}
+                  {event?.sub_label && event.sub_label !== "none" && (
                     <div
                       className={cn(
                         "",

web/src/components/classification/wizard/Step3ChooseExamples.tsx

@@ -317,6 +317,21 @@ export default function Step3ChooseExamples({
     return unclassifiedImages.length === 0;
   }, [unclassifiedImages]);
 
+  const handleBack = useCallback(() => {
+    if (currentClassIndex > 0) {
+      const previousClass = allClasses[currentClassIndex - 1];
+      setCurrentClassIndex((prev) => prev - 1);
+
+      // Restore selections for the previous class
+      const previousSelections = Object.entries(imageClassifications)
+        .filter(([_, className]) => className === previousClass)
+        .map(([imageName, _]) => imageName);
+      setSelectedImages(new Set(previousSelections));
+    } else {
+      onBack();
+    }
+  }, [currentClassIndex, allClasses, imageClassifications, onBack]);
+
   return (
     <div className="flex flex-col gap-6">
       {isTraining ? (
@@ -420,7 +435,7 @@ export default function Step3ChooseExamples({
 
       {!isTraining && (
         <div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
-          <Button type="button" onClick={onBack} className="sm:flex-1">
+          <Button type="button" onClick={handleBack} className="sm:flex-1">
             {t("button.back", { ns: "common" })}
           </Button>
           <Button

web/src/components/filter/SearchFilterGroup.tsx

@@ -348,6 +348,26 @@ export function GeneralFilterContent({
   onClose,
 }: GeneralFilterContentProps) {
   const { t } = useTranslation(["components/filter"]);
+  const { data: config } = useSWR<FrigateConfig>("config", {
+    revalidateOnFocus: false,
+  });
+
+  const allAudioListenLabels = useMemo<string[]>(() => {
+    if (!config) {
+      return [];
+    }
+
+    const labels = new Set<string>();
+    Object.values(config.cameras).forEach((camera) => {
+      if (camera?.audio?.enabled) {
+        camera.audio.listen.forEach((label) => {
+          labels.add(label);
+        });
+      }
+    });
+    return [...labels].sort();
+  }, [config]);
+
   return (
     <>
       <div className="overflow-x-hidden">
@@ -373,7 +393,10 @@ export function GeneralFilterContent({
           {allLabels.map((item) => (
             <FilterSwitch
               key={item}
-              label={getTranslatedLabel(item)}
+              label={getTranslatedLabel(
+                item,
+                allAudioListenLabels.includes(item) ? "audio" : "object",
+              )}
               isChecked={currentLabels?.includes(item) ?? false}
               onCheckedChange={(isChecked) => {
                 if (isChecked) {

web/src/components/overlay/ObjectTrackOverlay.tsx

@@ -58,6 +58,47 @@ export default function ObjectTrackOverlay({
 
   const effectiveCurrentTime = currentTime - annotationOffset / 1000;
 
+  const {
+    pathStroke,
+    pointRadius,
+    pointStroke,
+    zoneStroke,
+    boxStroke,
+    highlightRadius,
+  } = useMemo(() => {
+    const BASE_WIDTH = 1280;
+    const BASE_HEIGHT = 720;
+    const BASE_PATH_STROKE = 5;
+    const BASE_POINT_RADIUS = 7;
+    const BASE_POINT_STROKE = 3;
+    const BASE_ZONE_STROKE = 5;
+    const BASE_BOX_STROKE = 5;
+    const BASE_HIGHLIGHT_RADIUS = 5;
+
+    const scale = Math.sqrt(
+      (videoWidth * videoHeight) / (BASE_WIDTH * BASE_HEIGHT),
+    );
+
+    const pathStroke = Math.max(1, Math.round(BASE_PATH_STROKE * scale));
+    const pointRadius = Math.max(2, Math.round(BASE_POINT_RADIUS * scale));
+    const pointStroke = Math.max(1, Math.round(BASE_POINT_STROKE * scale));
+    const zoneStroke = Math.max(1, Math.round(BASE_ZONE_STROKE * scale));
+    const boxStroke = Math.max(1, Math.round(BASE_BOX_STROKE * scale));
+    const highlightRadius = Math.max(
+      2,
+      Math.round(BASE_HIGHLIGHT_RADIUS * scale),
+    );
+
+    return {
+      pathStroke,
+      pointRadius,
+      pointStroke,
+      zoneStroke,
+      boxStroke,
+      highlightRadius,
+    };
+  }, [videoWidth, videoHeight]);
+
   // Fetch all event data in a single request (CSV ids)
   const { data: eventsData } = useSWR<Event[]>(
     selectedObjectIds.length > 0
@@ -198,16 +239,21 @@ export default function ObjectTrackOverlay({
                 b.timestamp - a.timestamp,
             )[0]?.data?.zones || [];
 
-        // bounding box (with tolerance for browsers with seek precision by-design issues)
-        const boxCandidates = timelineData?.filter(
-          (event: TrackingDetailsSequence) =>
-            event.timestamp <= effectiveCurrentTime + TOLERANCE &&
-            event.data.box,
-        );
-        const currentBox = boxCandidates?.sort(
-          (a: TrackingDetailsSequence, b: TrackingDetailsSequence) =>
-            b.timestamp - a.timestamp,
-        )[0]?.data?.box;
+        // bounding box - only show if there's a timeline event at/near the current time with a box
+        // Search all timeline events (not just those before current time) to find one matching the seek position
+        const nearbyTimelineEvent = timelineData
+          ?.filter((event: TrackingDetailsSequence) => event.data.box)
+          .sort(
+            (a: TrackingDetailsSequence, b: TrackingDetailsSequence) =>
+              Math.abs(a.timestamp - effectiveCurrentTime) -
+              Math.abs(b.timestamp - effectiveCurrentTime),
+          )
+          .find(
+            (event: TrackingDetailsSequence) =>
+              Math.abs(event.timestamp - effectiveCurrentTime) <= TOLERANCE,
+          );
+
+        const currentBox = nearbyTimelineEvent?.data?.box;
 
         return {
           objectId,
@@ -333,7 +379,7 @@ export default function ObjectTrackOverlay({
           points={zone.points}
           fill={zone.fill}
           stroke={zone.stroke}
-          strokeWidth="5"
+          strokeWidth={zoneStroke}
           opacity="0.7"
         />
       ))}
@@ -353,7 +399,7 @@ export default function ObjectTrackOverlay({
                 d={generateStraightPath(absolutePositions)}
                 fill="none"
                 stroke={objData.color}
-                strokeWidth="5"
+                strokeWidth={pathStroke}
                 strokeLinecap="round"
                 strokeLinejoin="round"
               />
@@ -365,13 +411,13 @@ export default function ObjectTrackOverlay({
                   <circle
                     cx={pos.x}
                     cy={pos.y}
-                    r="7"
+                    r={pointRadius}
                     fill={getPointColor(
                       objData.color,
                       pos.lifecycle_item?.class_type,
                     )}
                     stroke="white"
-                    strokeWidth="3"
+                    strokeWidth={pointStroke}
                     style={{ cursor: onSeekToTime ? "pointer" : "default" }}
                     onClick={() => handlePointClick(pos.timestamp)}
                   />
@@ -400,7 +446,7 @@ export default function ObjectTrackOverlay({
                   height={objData.currentBox[3] * videoHeight}
                   fill="none"
                   stroke={objData.color}
-                  strokeWidth="5"
+                  strokeWidth={boxStroke}
                   opacity="0.9"
                 />
                 <circle
@@ -412,10 +458,10 @@ export default function ObjectTrackOverlay({
                     (objData.currentBox[1] + objData.currentBox[3]) *
                     videoHeight
                   }
-                  r="5"
+                  r={highlightRadius}
                   fill="rgb(255, 255, 0)" // yellow highlight
                   stroke={objData.color}
-                  strokeWidth="5"
+                  strokeWidth={boxStroke}
                   opacity="1"
                 />
               </g>

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

@@ -8,7 +8,7 @@ import Heading from "@/components/ui/heading";
 import { FrigateConfig } from "@/types/frigateConfig";
 import { formatUnixTimestampToDateTime } from "@/utils/dateUtil";
 import { getIconForLabel } from "@/utils/iconUtil";
-import { LuCircle, LuSettings } from "react-icons/lu";
+import { LuCircle, LuFolderX, LuSettings } from "react-icons/lu";
 import { cn } from "@/lib/utils";
 import {
   Tooltip,
@@ -37,9 +37,12 @@ import { HiDotsHorizontal } from "react-icons/hi";
 import axios from "axios";
 import { toast } from "sonner";
 import { useDetailStream } from "@/context/detail-stream-context";
-import { isDesktop, isIOS } from "react-device-detect";
+import { isDesktop, isIOS, isMobileOnly, isSafari } from "react-device-detect";
 import Chip from "@/components/indicators/Chip";
 import { FaDownload, FaHistory } from "react-icons/fa";
+import { useApiHost } from "@/api";
+import ImageLoadingIndicator from "@/components/indicators/ImageLoadingIndicator";
+import ObjectTrackOverlay from "../ObjectTrackOverlay";
 
 type TrackingDetailsProps = {
   className?: string;
@@ -56,9 +59,19 @@ export function TrackingDetails({
   const videoRef = useRef<HTMLVideoElement | null>(null);
   const { t } = useTranslation(["views/explore"]);
   const navigate = useNavigate();
+  const apiHost = useApiHost();
+  const imgRef = useRef<HTMLImageElement | null>(null);
+  const [imgLoaded, setImgLoaded] = useState(false);
+  const [displaySource, _setDisplaySource] = useState<"video" | "image">(
+    "video",
+  );
   const { setSelectedObjectIds, annotationOffset, setAnnotationOffset } =
     useDetailStream();
 
+  // manualOverride holds a record-stream timestamp explicitly chosen by the
+  // user (eg, clicking a lifecycle row). When null we display `currentTime`.
+  const [manualOverride, setManualOverride] = useState<number | null>(null);
+
   // event.start_time is detect time, convert to record, then subtract padding
   const [currentTime, setCurrentTime] = useState(
     (event.start_time ?? 0) + annotationOffset / 1000 - REVIEW_PADDING,
@@ -73,9 +86,13 @@ export function TrackingDetails({
 
   const { data: config } = useSWR<FrigateConfig>("config");
 
+  // Use manualOverride (set when seeking in image mode) if present so
+  // lifecycle rows and overlays follow image-mode seeks. Otherwise fall
+  // back to currentTime used for video mode.
   const effectiveTime = useMemo(() => {
-    return currentTime - annotationOffset / 1000;
-  }, [currentTime, annotationOffset]);
+    const displayedRecordTime = manualOverride ?? currentTime;
+    return displayedRecordTime - annotationOffset / 1000;
+  }, [manualOverride, currentTime, annotationOffset]);
 
   const containerRef = useRef<HTMLDivElement | null>(null);
   const [_selectedZone, setSelectedZone] = useState("");
@@ -118,20 +135,30 @@ export function TrackingDetails({
 
   const handleLifecycleClick = useCallback(
     (item: TrackingDetailsSequence) => {
-      if (!videoRef.current) return;
+      if (!videoRef.current && !imgRef.current) return;
 
       // Convert lifecycle timestamp (detect stream) to record stream time
       const targetTimeRecord = item.timestamp + annotationOffset / 1000;
 
-      // Convert to video-relative time for seeking
+      if (displaySource === "image") {
+        // For image mode: set a manual override timestamp and update
+        // currentTime so overlays render correctly.
+        setManualOverride(targetTimeRecord);
+        setCurrentTime(targetTimeRecord);
+        return;
+      }
+
+      // For video mode: convert to video-relative time and seek player
       const eventStartRecord =
         (event.start_time ?? 0) + annotationOffset / 1000;
       const videoStartTime = eventStartRecord - REVIEW_PADDING;
       const relativeTime = targetTimeRecord - videoStartTime;
 
-      videoRef.current.currentTime = relativeTime;
+      if (videoRef.current) {
+        videoRef.current.currentTime = relativeTime;
+      }
     },
-    [event.start_time, annotationOffset],
+    [event.start_time, annotationOffset, displaySource],
   );
 
   const formattedStart = config
@@ -172,11 +199,20 @@ export function TrackingDetails({
   }, [eventSequence]);
 
   useEffect(() => {
-    if (seekToTimestamp === null || !videoRef.current) return;
+    if (seekToTimestamp === null) return;
+
+    if (displaySource === "image") {
+      // For image mode, set the manual override so the snapshot updates to
+      // the exact record timestamp.
+      setManualOverride(seekToTimestamp);
+      setSeekToTimestamp(null);
+      return;
+    }
 
     // seekToTimestamp is a record stream timestamp
     // event.start_time is detect stream time, convert to record
     // The video clip starts at (eventStartRecord - REVIEW_PADDING)
+    if (!videoRef.current) return;
     const eventStartRecord = event.start_time + annotationOffset / 1000;
     const videoStartTime = eventStartRecord - REVIEW_PADDING;
     const relativeTime = seekToTimestamp - videoStartTime;
@@ -184,7 +220,14 @@ export function TrackingDetails({
       videoRef.current.currentTime = relativeTime;
     }
     setSeekToTimestamp(null);
-  }, [seekToTimestamp, event.start_time, annotationOffset]);
+  }, [
+    seekToTimestamp,
+    event.start_time,
+    annotationOffset,
+    apiHost,
+    event.camera,
+    displaySource,
+  ]);
 
   const isWithinEventRange =
     effectiveTime !== undefined &&
@@ -287,6 +330,27 @@ export function TrackingDetails({
     [event.start_time, annotationOffset],
   );
 
+  const [src, setSrc] = useState(
+    `${apiHost}api/${event.camera}/recordings/${currentTime + REVIEW_PADDING}/snapshot.jpg?height=500`,
+  );
+  const [hasError, setHasError] = useState(false);
+
+  // Derive the record timestamp to display: manualOverride if present,
+  // otherwise use currentTime.
+  const displayedRecordTime = manualOverride ?? currentTime;
+
+  useEffect(() => {
+    if (displayedRecordTime) {
+      const newSrc = `${apiHost}api/${event.camera}/recordings/${displayedRecordTime}/snapshot.jpg?height=500`;
+      setSrc(newSrc);
+    }
+    setImgLoaded(false);
+    setHasError(false);
+
+    // we know that these deps are correct
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [displayedRecordTime]);
+
   if (!config) {
     return <ActivityIndicator />;
   }
@@ -304,9 +368,10 @@ export function TrackingDetails({
 
       <div
         className={cn(
-          "flex w-full items-center justify-center",
+          "flex items-center justify-center",
           isDesktop && "overflow-hidden",
           cameraAspect === "tall" ? "max-h-[50dvh] lg:max-h-[70dvh]" : "w-full",
+          cameraAspect === "tall" && isMobileOnly && "w-full",
           cameraAspect !== "tall" && isDesktop && "flex-[3]",
         )}
         style={{ aspectRatio: aspectRatio }}
@@ -318,21 +383,75 @@ export function TrackingDetails({
             cameraAspect === "tall" ? "h-full" : "w-full",
           )}
         >
-          <HlsVideoPlayer
-            videoRef={videoRef}
-            containerRef={containerRef}
-            visible={true}
-            currentSource={videoSource}
-            hotKeys={false}
-            supportsFullscreen={false}
-            fullscreen={false}
-            frigateControls={true}
-            onTimeUpdate={handleTimeUpdate}
-            onSeekToTime={handleSeekToTime}
-            isDetailMode={true}
-            camera={event.camera}
-            currentTimeOverride={currentTime}
-          />
+          {displaySource == "video" && (
+            <HlsVideoPlayer
+              videoRef={videoRef}
+              containerRef={containerRef}
+              visible={true}
+              currentSource={videoSource}
+              hotKeys={false}
+              supportsFullscreen={false}
+              fullscreen={false}
+              frigateControls={true}
+              onTimeUpdate={handleTimeUpdate}
+              onSeekToTime={handleSeekToTime}
+              isDetailMode={true}
+              camera={event.camera}
+              currentTimeOverride={currentTime}
+            />
+          )}
+          {displaySource == "image" && (
+            <>
+              <ImageLoadingIndicator
+                className="absolute inset-0"
+                imgLoaded={imgLoaded}
+              />
+              {hasError && (
+                <div className="relative aspect-video">
+                  <div className="flex flex-col items-center justify-center p-20 text-center">
+                    <LuFolderX className="size-16" />
+                    {t("objectLifecycle.noImageFound")}
+                  </div>
+                </div>
+              )}
+              <div
+                className={cn("relative", imgLoaded ? "visible" : "invisible")}
+              >
+                <div className="absolute z-50 size-full">
+                  <ObjectTrackOverlay
+                    key={`overlay-${displayedRecordTime}`}
+                    camera={event.camera}
+                    showBoundingBoxes={true}
+                    currentTime={displayedRecordTime}
+                    videoWidth={imgRef?.current?.naturalWidth ?? 0}
+                    videoHeight={imgRef?.current?.naturalHeight ?? 0}
+                    className="absolute inset-0 z-10"
+                    onSeekToTime={handleSeekToTime}
+                  />
+                </div>
+                <img
+                  key={event.id}
+                  ref={imgRef}
+                  className={cn(
+                    "max-h-[50dvh] max-w-full select-none rounded-lg object-contain",
+                  )}
+                  loading={isSafari ? "eager" : "lazy"}
+                  style={
+                    isIOS
+                      ? {
+                          WebkitUserSelect: "none",
+                          WebkitTouchCallout: "none",
+                        }
+                      : undefined
+                  }
+                  draggable={false}
+                  src={src}
+                  onLoad={() => setImgLoaded(true)}
+                  onError={() => setHasError(true)}
+                />
+              </div>
+            </>
+          )}
           <div
             className={cn(
               "absolute top-2 z-[5] flex items-center gap-2",

web/src/components/settings/CameraWizardDialog.tsx

@@ -174,9 +174,7 @@ export default function CameraWizardDialog({
             ...(friendlyName && { friendly_name: friendlyName }),
             ffmpeg: {
               inputs: wizardData.streams.map((stream, index) => {
-                const isRestreamed =
-                  wizardData.restreamIds?.includes(stream.id) ?? false;
-                if (isRestreamed) {
+                if (stream.restream) {
                   const go2rtcStreamName =
                     wizardData.streams!.length === 1
                       ? finalCameraName
@@ -234,7 +232,11 @@ export default function CameraWizardDialog({
                   wizardData.streams!.length === 1
                     ? finalCameraName
                     : `${finalCameraName}_${index + 1}`;
-                go2rtcStreams[streamName] = [stream.url];
+
+                const streamUrl = stream.useFfmpeg
+                  ? `ffmpeg:${stream.url}`
+                  : stream.url;
+                go2rtcStreams[streamName] = [streamUrl];
               });
 
               if (Object.keys(go2rtcStreams).length > 0) {

web/src/components/settings/wizard/Step1NameCamera.tsx

@@ -608,6 +608,12 @@ export default function Step1NameCamera({
         </div>
       )}
 
+      {isTesting && (
+        <div className="flex items-center gap-2 text-sm text-muted-foreground">
+          <ActivityIndicator className="size-4" />
+          {testStatus}
+        </div>
+      )}
       <div className="flex flex-col gap-3 pt-3 sm:flex-row sm:justify-end sm:gap-4">
         <Button
           type="button"
@@ -635,10 +641,7 @@ export default function Step1NameCamera({
             variant="select"
             className="flex items-center justify-center gap-2 sm:flex-1"
           >
-            {isTesting && <ActivityIndicator className="size-4" />}
-            {isTesting && testStatus
-              ? testStatus
-              : t("cameraWizard.step1.testConnection")}
+            {t("cameraWizard.step1.testConnection")}
           </Button>
         )}
       </div>

web/src/components/settings/wizard/Step2StreamConfig.tsx

@@ -201,16 +201,12 @@ export default function Step2StreamConfig({
 
   const setRestream = useCallback(
     (streamId: string) => {
-      const currentIds = wizardData.restreamIds || [];
-      const isSelected = currentIds.includes(streamId);
-      const newIds = isSelected
-        ? currentIds.filter((id) => id !== streamId)
-        : [...currentIds, streamId];
-      onUpdate({
-        restreamIds: newIds,
-      });
+      const stream = streams.find((s) => s.id === streamId);
+      if (!stream) return;
+
+      updateStream(streamId, { restream: !stream.restream });
     },
-    [wizardData.restreamIds, onUpdate],
+    [streams, updateStream],
   );
 
   const hasDetectRole = streams.some((s) => s.roles.includes("detect"));
@@ -435,9 +431,7 @@ export default function Step2StreamConfig({
                       {t("cameraWizard.step2.go2rtc")}
                     </span>
                     <Switch
-                      checked={(wizardData.restreamIds || []).includes(
-                        stream.id,
-                      )}
+                      checked={stream.restream || false}
                       onCheckedChange={() => setRestream(stream.id)}
                     />
                   </div>

web/src/components/settings/wizard/Step3Validation.tsx

@@ -1,7 +1,13 @@
 import { Button } from "@/components/ui/button";
 import { Badge } from "@/components/ui/badge";
+import { Switch } from "@/components/ui/switch";
+import {
+  Popover,
+  PopoverContent,
+  PopoverTrigger,
+} from "@/components/ui/popover";
 import { useTranslation } from "react-i18next";
-import { LuRotateCcw } from "react-icons/lu";
+import { LuRotateCcw, LuInfo } from "react-icons/lu";
 import { useState, useCallback, useMemo, useEffect } from "react";
 import ActivityIndicator from "@/components/indicators/activity-indicator";
 import axios from "axios";
@@ -216,7 +222,6 @@ export default function Step3Validation({
       brandTemplate: wizardData.brandTemplate,
       customUrl: wizardData.customUrl,
       streams: wizardData.streams,
-      restreamIds: wizardData.restreamIds,
     };
 
     onSave(configData);
@@ -322,6 +327,51 @@ export default function Step3Validation({
                     </div>
                   )}
 
+                  {result?.success && (
+                    <div className="mb-3 flex items-center justify-between">
+                      <div className="flex items-center gap-2">
+                        <span className="text-sm">
+                          {t("cameraWizard.step3.ffmpegModule")}
+                        </span>
+                        <Popover>
+                          <PopoverTrigger asChild>
+                            <Button
+                              variant="ghost"
+                              size="sm"
+                              className="h-4 w-4 p-0"
+                            >
+                              <LuInfo className="size-3" />
+                            </Button>
+                          </PopoverTrigger>
+                          <PopoverContent className="pointer-events-auto w-80 text-xs">
+                            <div className="space-y-2">
+                              <div className="font-medium">
+                                {t("cameraWizard.step3.ffmpegModule")}
+                              </div>
+                              <div className="text-muted-foreground">
+                                {t(
+                                  "cameraWizard.step3.ffmpegModuleDescription",
+                                )}
+                              </div>
+                            </div>
+                          </PopoverContent>
+                        </Popover>
+                      </div>
+                      <Switch
+                        checked={stream.useFfmpeg || false}
+                        onCheckedChange={(checked) => {
+                          onUpdate({
+                            streams: streams.map((s) =>
+                              s.id === stream.id
+                                ? { ...s, useFfmpeg: checked }
+                                : s,
+                            ),
+                          });
+                        }}
+                      />
+                    </div>
+                  )}
+
                   <div className="mb-2 flex flex-col justify-between gap-1 md:flex-row md:items-center">
                     <span className="break-all text-sm text-muted-foreground">
                       {stream.url}
@@ -491,8 +541,7 @@ function StreamIssues({
 
     // Restreaming check
     if (stream.roles.includes("record")) {
-      const restreamIds = wizardData.restreamIds || [];
-      if (restreamIds.includes(stream.id)) {
+      if (stream.restream) {
         result.push({
           type: "warning",
           message: t("cameraWizard.step3.issues.restreamingWarning"),
@@ -660,9 +709,10 @@ function StreamPreview({ stream, onBandwidthUpdate }: StreamPreviewProps) {
 
   useEffect(() => {
     // Register stream with go2rtc
+    const streamUrl = stream.useFfmpeg ? `ffmpeg:${stream.url}` : stream.url;
     axios
       .put(`go2rtc/streams/${streamId}`, null, {
-        params: { src: stream.url },
+        params: { src: streamUrl },
       })
       .then(() => {
         // Add small delay to allow go2rtc api to run and initialize the stream
@@ -680,7 +730,7 @@ function StreamPreview({ stream, onBandwidthUpdate }: StreamPreviewProps) {
         // do nothing on cleanup errors - go2rtc won't consume the streams
       });
     };
-  }, [stream.url, streamId]);
+  }, [stream.url, stream.useFfmpeg, streamId]);
 
   const resolution = stream.testResult?.resolution;
   let aspectRatio = "16/9";

web/src/pages/FaceLibrary.tsx

@@ -845,6 +845,7 @@ function FaceAttemptGroup({
       selectedItems={selectedFaces}
       i18nLibrary="views/faceLibrary"
       objectType="person"
+      noClassificationLabel="details.unknown"
       onClick={(data) => {
         if (data) {
           onClickFaces([data.filename], true);

web/src/types/cameraWizard.ts

@@ -85,6 +85,8 @@ export type StreamConfig = {
   quality?: string;
   testResult?: TestResult;
   userTested?: boolean;
+  useFfmpeg?: boolean;
+  restream?: boolean;
 };
 
 export type TestResult = {
@@ -105,7 +107,6 @@ export type WizardFormData = {
   brandTemplate?: CameraBrand;
   customUrl?: string;
   streams?: StreamConfig[];
-  restreamIds?: string[];
 };
 
 // API Response Types
@@ -146,6 +147,7 @@ export type CameraConfigData = {
         inputs: {
           path: string;
           roles: string[];
+          input_args?: string;
         }[];
       };
       live?: {

web/src/views/classification/ModelSelectionView.tsx

@@ -10,7 +10,7 @@ import {
   CustomClassificationModelConfig,
   FrigateConfig,
 } from "@/types/frigateConfig";
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import { useCallback, useEffect, useMemo, useState } from "react";
 import { useTranslation } from "react-i18next";
 import { FaFolderPlus } from "react-icons/fa";
 import { MdModelTraining } from "react-icons/md";
@@ -21,7 +21,6 @@ import Heading from "@/components/ui/heading";
 import { useOverlayState } from "@/hooks/use-overlay-state";
 import axios from "axios";
 import { toast } from "sonner";
-import useKeyboardListener from "@/hooks/use-keyboard-listener";
 import {
   DropdownMenu,
   DropdownMenuContent,
@@ -212,42 +211,44 @@ function ModelCard({ config, onClick, onDelete }: ModelCardProps) {
   }>(`classification/${config.name}/dataset`, { revalidateOnFocus: false });
 
   const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
-  const bypassDialogRef = useRef(false);
-
-  useKeyboardListener(["Shift"], (_, modifiers) => {
-    bypassDialogRef.current = modifiers.shift;
-    return false;
-  });
 
   const handleDelete = useCallback(async () => {
-    await axios
-      .delete(`classification/${config.name}`)
-      .then((resp) => {
-        if (resp.status == 200) {
-          toast.success(t("toast.success.deletedModel", { count: 1 }), {
-            position: "top-center",
-          });
-          onDelete();
-        }
-      })
-      .catch((error) => {
-        const errorMessage =
-          error.response?.data?.message ||
-          error.response?.data?.detail ||
-          "Unknown error";
-        toast.error(t("toast.error.deleteModelFailed", { errorMessage }), {
-          position: "top-center",
-        });
+    try {
+      await axios.delete(`classification/${config.name}`);
+      await axios.put("/config/set", {
+        requires_restart: 0,
+        update_topic: `config/classification/custom/${config.name}`,
+        config_data: {
+          classification: {
+            custom: {
+              [config.name]: "",
+            },
+          },
+        },
       });
+
+      toast.success(t("toast.success.deletedModel", { count: 1 }), {
+        position: "top-center",
+      });
+      onDelete();
+    } catch (err) {
+      const error = err as {
+        response?: { data?: { message?: string; detail?: string } };
+      };
+      const errorMessage =
+        error.response?.data?.message ||
+        error.response?.data?.detail ||
+        "Unknown error";
+      toast.error(t("toast.error.deleteModelFailed", { errorMessage }), {
+        position: "top-center",
+      });
+    }
   }, [config, onDelete, t]);
 
-  const handleDeleteClick = useCallback(() => {
-    if (bypassDialogRef.current) {
-      handleDelete();
-    } else {
-      setDeleteDialogOpen(true);
-    }
-  }, [handleDelete]);
+  const handleDeleteClick = useCallback((e: React.MouseEvent) => {
+    e.stopPropagation();
+    setDeleteDialogOpen(true);
+  }, []);
 
   const coverImage = useMemo(() => {
     if (!dataset) {
@@ -304,7 +305,7 @@ function ModelCard({ config, onClick, onDelete }: ModelCardProps) {
           className="size-full"
           src={`${baseUrl}clips/${config.name}/dataset/${coverImage?.name}/${coverImage?.img}`}
         />
-        <ImageShadowOverlay />
+        <ImageShadowOverlay lowerClassName="h-[30%] z-0" />
         <div className="absolute bottom-2 left-3 text-lg text-white smart-capitalize">
           {config.name}
         </div>
@@ -315,14 +316,13 @@ function ModelCard({ config, onClick, onDelete }: ModelCardProps) {
                 <FiMoreVertical className="size-5 text-white" />
               </BlurredIconButton>
             </DropdownMenuTrigger>
-            <DropdownMenuContent align="end">
+            <DropdownMenuContent
+              align="end"
+              onClick={(e) => e.stopPropagation()}
+            >
               <DropdownMenuItem onClick={handleDeleteClick}>
                 <LuTrash2 className="mr-2 size-4" />
-                <span>
-                  {bypassDialogRef.current
-                    ? t("button.deleteNow", { ns: "common" })
-                    : t("button.delete", { ns: "common" })}
-                </span>
+                <span>{t("button.delete", { ns: "common" })}</span>
               </DropdownMenuItem>
             </DropdownMenuContent>
           </DropdownMenu>

web/src/views/classification/ModelTrainingView.tsx

@@ -961,6 +961,7 @@ function ObjectTrainGrid({
                 selectedItems={selectedImages}
                 i18nLibrary="views/classificationModel"
                 objectType={model.object_config?.objects?.at(0) ?? "Object"}
+                noClassificationLabel="details.none"
                 onClick={(data) => {
                   if (data) {
                     onClickImages([data.filename], true);