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/tags/v2.1.0.zip -O /tmp/mxaccl.zip
+wget https://github.com/memryx/mx_accl_frigate/archive/refs/heads/main.zip -O /tmp/mxaccl.zip
 unzip /tmp/mxaccl.zip -d /tmp
-mv /tmp/mx_accl_frigate-2.1.0 /opt/mx_accl_frigate
+mv /tmp/mx_accl_frigate-main /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.*
-rapidfuzz==3.12.*
+Levenshtein==0.26.*
 # HailoRT Wheels
 appdirs==1.4.*
 argcomplete==2.0.*

docker/memryx/user_installation.sh

@@ -24,13 +24,10 @@ 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 specific SDK 2.1 packages
+# Update and install memx-drivers
-echo "Installing MemryX SDK 2.1 packages..."
+echo "Installing memx-drivers..."
 sudo apt update
-sudo apt install -y memx-drivers=2.1.* memx-accl=2.1.* mxa-manager=2.1.*
+sudo apt install -y memx-drivers
-
-# 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
@@ -40,5 +37,11 @@ fi
 
 echo -e "\n\n\033[1;31mYOU MUST RESTART YOUR COMPUTER NOW\033[0m\n\n"
 
-echo "MemryX SDK 2.1 installation complete!"
+# 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 installation complete!"

frigate/api/event.py

@@ -2,7 +2,6 @@
 
 import base64
 import datetime
-import json
 import logging
 import os
 import random
@@ -59,7 +58,7 @@ from frigate.embeddings import EmbeddingsContext
 from frigate.models import Event, ReviewSegment, Timeline, Trigger
 from frigate.track.object_processing import TrackedObject
 from frigate.util.path import get_event_thumbnail_bytes
-from frigate.util.time import get_dst_transitions, get_tz_modifiers
+from frigate.util.time import get_tz_modifiers
 
 logger = logging.getLogger(__name__)
 
@@ -814,6 +813,7 @@ 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
 
@@ -828,91 +828,33 @@ def events_summary(
     if len(clauses) == 0:
         clauses.append((True))
 
-    time_range_query = (
+    groups = (
         Event.select(
-            fn.MIN(Event.start_time).alias("min_time"),
+            Event.camera,
-            fn.MAX(Event.start_time).alias("max_time"),
+            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"),
         )
         .where(reduce(operator.and_, clauses) & (Event.camera << allowed_cameras))
-        .dicts()
+        .group_by(
-        .get()
+            Event.camera,
+            Event.label,
+            Event.sub_label,
+            Event.data,
+            (Event.start_time + seconds_offset).cast("int") / (3600 * 24),
+            Event.zones,
+        )
     )
 
-    min_time = time_range_query.get("min_time")
+    return JSONResponse(content=[e for e in groups.dicts()])
-    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/media.py

@@ -46,7 +46,7 @@ from frigate.models import Event, Previews, Recordings, Regions, ReviewSegment
 from frigate.track.object_processing import TrackedObjectProcessor
 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
+from frigate.util.time import get_tz_modifiers
 
 logger = logging.getLogger(__name__)
 
@@ -424,6 +424,7 @@ 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":
@@ -431,70 +432,41 @@ def all_recordings_summary(
         filtered = requested.intersection(allowed_cameras)
         if not filtered:
             return JSONResponse(content={})
-        camera_list = list(filtered)
+        cameras = ",".join(filtered)
     else:
-        camera_list = allowed_cameras
+        cameras = allowed_cameras
 
-    time_range_query = (
+    query = (
         Recordings.select(
-            fn.MIN(Recordings.start_time).alias("min_time"),
+            fn.strftime(
-            fn.MAX(Recordings.start_time).alias("max_time"),
+                "%Y-%m-%d",
+                fn.datetime(
+                    Recordings.start_time + seconds_offset,
+                    "unixepoch",
+                    hour_modifier,
+                    minute_modifier,
+                ),
+            ).alias("day")
         )
-        .where(Recordings.camera << camera_list)
+        .group_by(
-        .dicts()
+            fn.strftime(
-        .get()
+                "%Y-%m-%d",
+                fn.datetime(
+                    Recordings.start_time + seconds_offset,
+                    "unixepoch",
+                    hour_modifier,
+                    minute_modifier,
+                ),
+            )
+        )
+        .order_by(Recordings.start_time.desc())
     )
 
-    min_time = time_range_query.get("min_time")
+    if params.cameras != "all":
-    max_time = time_range_query.get("max_time")
+        query = query.where(Recordings.camera << cameras.split(","))
 
-    if min_time is None or max_time is None:
+    recording_days = query.namedtuples()
-        return JSONResponse(content={})
+    days = {day.day: True for day in recording_days}
-
-    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)
 
@@ -504,103 +476,61 @@ 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)
-    time_range_query = (
+    recording_groups = (
         Recordings.select(
-            fn.MIN(Recordings.start_time).alias("min_time"),
+            fn.strftime(
-            fn.MAX(Recordings.start_time).alias("max_time"),
+                "%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"),
         )
         .where(Recordings.camera == camera_name)
-        .dicts()
+        .group_by((Recordings.start_time + seconds_offset).cast("int") / 3600)
-        .get()
+        .order_by(Recordings.start_time.desc())
+        .namedtuples()
     )
 
-    min_time = time_range_query.get("min_time")
+    event_groups = (
-    max_time = time_range_query.get("max_time")
+        Event.select(
-
+            fn.strftime(
-    days: dict[str, dict] = {}
+                "%Y-%m-%d %H",
-
+                fn.datetime(
-    if min_time is None or max_time is None:
+                    Event.start_time, "unixepoch", hour_modifier, minute_modifier
-        return JSONResponse(content=list(days.values()))
+                ),
-
+            ).alias("hour"),
-    dst_periods = get_dst_transitions(timezone, min_time, max_time)
+            fn.COUNT(Event.id).alias("count"),
-
-    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_groups = (
+    event_map = {g.hour: g.count for g in 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()
-        )
 
-        event_map = {g.hour: g.count for g in event_groups}
+    days = {}
 
-        for recording_group in recording_groups:
+    for recording_group in recording_groups:
-            parts = recording_group.hour.split()
+        parts = recording_group.hour.split()
-            hour = parts[1]
+        hour = parts[1]
-            day = parts[0]
+        day = parts[0]
-            events_count = event_map.get(recording_group.hour, 0)
+        events_count = event_map.get(recording_group.hour, 0)
-            hour_data = {
+        hour_data = {
-                "hour": hour,
+            "hour": hour,
-                "events": events_count,
+            "events": events_count,
-                "motion": recording_group.motion,
+            "motion": recording_group.motion,
-                "objects": recording_group.objects,
+            "objects": recording_group.objects,
-                "duration": round(recording_group.duration),
+            "duration": round(recording_group.duration),
-            }
+        }
-            if day in days:
+        if day not in days:
-                # merge counts if already present (edge-case at DST boundary)
+            days[day] = {"events": events_count, "hours": [hour_data], "day": day}
-                days[day]["events"] += events_count or 0
+        else:
-                days[day]["hours"].append(hour_data)
+            days[day]["events"] += events_count
-            else:
+            days[day]["hours"].append(hour_data)
-                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.time import get_dst_transitions
+from frigate.util.time import get_dst_transitions, get_tz_modifiers
 
 logger = logging.getLogger(__name__)
 
@@ -197,6 +197,7 @@ 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

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 (
@@ -1123,9 +1123,7 @@ class LicensePlateProcessingMixin:
         for i, plate in enumerate(plates):
             merged = False
             for j, cluster in enumerate(clusters):
-                sims = [
+                sims = [jaro_winkler(plate["plate"], v["plate"]) for v in cluster]
-                    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:
@@ -1502,7 +1500,7 @@ class LicensePlateProcessingMixin:
                     and current_time - data["last_seen"]
                     <= self.config.cameras[camera].lpr.expire_time
                 ):
-                    similarity = JaroWinkler.similarity(data["plate"], top_plate)
+                    similarity = jaro_winkler(data["plate"], top_plate)
                     if similarity >= self.similarity_threshold:
                         plate_id = existing_id
                         logger.debug(
@@ -1582,8 +1580,7 @@ class LicensePlateProcessingMixin:
                     for label, plates_list in self.lpr_config.known_plates.items()
                     if any(
                         re.match(f"^{plate}$", rep_plate)
-                        or Levenshtein.distance(plate, rep_plate)
+                        or distance(plate, rep_plate) <= self.lpr_config.match_distance
-                        <= self.lpr_config.match_distance
                         for plate in plates_list
                     )
                 ),

frigate/embeddings/maintainer.py

@@ -397,14 +397,7 @@ 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:
@@ -414,9 +407,6 @@ 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
@@ -425,7 +415,6 @@ 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:
@@ -434,11 +423,7 @@ 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

@@ -9,7 +9,6 @@ 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,
@@ -378,15 +377,6 @@ 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)

web/src/components/card/ClassificationCard.tsx

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

web/src/pages/FaceLibrary.tsx

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

web/src/views/classification/ModelTrainingView.tsx

@@ -961,7 +961,6 @@ 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);