Fix check for audio activity to keep a segemnt

frigate/util/classification.py

@@ -22,7 +22,6 @@ from frigate.const import (
 from frigate.log import redirect_output_to_logger
 from frigate.models import Event, Recordings, ReviewSegment
 from frigate.types import ModelStatusTypesEnum
-from frigate.util.downloader import ModelDownloader
 from frigate.util.file import get_event_thumbnail_bytes
 from frigate.util.image import get_image_from_recording
 from frigate.util.process import FrigateProcess
@@ -122,10 +121,6 @@ def get_dataset_image_count(model_name: str) -> int:
 
 class ClassificationTrainingProcess(FrigateProcess):
     def __init__(self, model_name: str) -> None:
-        self.BASE_WEIGHT_URL = os.environ.get(
-            "TF_KERAS_MOBILENET_V2_WEIGHTS_URL",
-            "",
-        )
         super().__init__(
             stop_event=None,
             priority=PROCESS_PRIORITY_LOW,
@@ -184,23 +179,11 @@ class ClassificationTrainingProcess(FrigateProcess):
                 )
                 return False
 
-            weights_path = "imagenet"
-            # Download MobileNetV2 weights if not present
-            if self.BASE_WEIGHT_URL:
-                weights_path = os.path.join(
-                    MODEL_CACHE_DIR, "MobileNet", "mobilenet_v2_weights.h5"
-                )
-                if not os.path.exists(weights_path):
-                    logger.info("Downloading MobileNet V2 weights file")
-                    ModelDownloader.download_from_url(
-                        self.BASE_WEIGHT_URL, weights_path
-                    )
-
             # Start with imagenet base model with 35% of channels in each layer
             base_model = MobileNetV2(
                 input_shape=(224, 224, 3),
                 include_top=False,
-                weights=weights_path,
+                weights="imagenet",
                 alpha=0.35,
             )
             base_model.trainable = False  # Freeze pre-trained layers
@@ -499,10 +482,6 @@ def _extract_keyframes(
     """
     Extract keyframes from recordings at specified timestamps and crop to specified regions.
 
-    This implementation batches work by running multiple ffmpeg snapshot commands
-    concurrently, which significantly reduces total runtime compared to
-    processing each timestamp serially.
-
     Args:
         ffmpeg_path: Path to ffmpeg binary
         timestamps: List of timestamp dicts from _select_balanced_timestamps
@@ -512,21 +491,15 @@ def _extract_keyframes(
     Returns:
         List of paths to successfully extracted and cropped keyframe images
     """
-    from concurrent.futures import ThreadPoolExecutor, as_completed
+    keyframe_paths = []
 
-    if not timestamps:
-        return []
-
-    # Limit the number of concurrent ffmpeg processes so we don't overload the host.
-    max_workers = min(5, len(timestamps))
-
-    def _process_timestamp(idx: int, ts_info: dict) -> tuple[int, str | None]:
+    for idx, ts_info in enumerate(timestamps):
         camera = ts_info["camera"]
         timestamp = ts_info["timestamp"]
 
         if camera not in camera_crops:
             logger.warning(f"No crop coordinates for camera {camera}")
-            return idx, None
+            continue
 
         norm_x1, norm_y1, norm_x2, norm_y2 = camera_crops[camera]
 
@@ -543,7 +516,7 @@ def _extract_keyframes(
                 .get()
             )
         except Exception:
-            return idx, None
+            continue
 
         relative_time = timestamp - recording.start_time
 
@@ -557,57 +530,38 @@ def _extract_keyframes(
                 height=None,
             )
 
-            if not image_data:
-                return idx, None
+            if image_data:
+                nparr = np.frombuffer(image_data, np.uint8)
+                img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
 
-            nparr = np.frombuffer(image_data, np.uint8)
-            img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+                if img is not None:
+                    height, width = img.shape[:2]
 
-            if img is None:
-                return idx, None
+                    x1 = int(norm_x1 * width)
+                    y1 = int(norm_y1 * height)
+                    x2 = int(norm_x2 * width)
+                    y2 = int(norm_y2 * height)
 
-            height, width = img.shape[:2]
+                    x1_clipped = max(0, min(x1, width))
+                    y1_clipped = max(0, min(y1, height))
+                    x2_clipped = max(0, min(x2, width))
+                    y2_clipped = max(0, min(y2, height))
 
-            x1 = int(norm_x1 * width)
-            y1 = int(norm_y1 * height)
-            x2 = int(norm_x2 * width)
-            y2 = int(norm_y2 * height)
+                    if x2_clipped > x1_clipped and y2_clipped > y1_clipped:
+                        cropped = img[y1_clipped:y2_clipped, x1_clipped:x2_clipped]
+                        resized = cv2.resize(cropped, (224, 224))
 
-            x1_clipped = max(0, min(x1, width))
-            y1_clipped = max(0, min(y1, height))
-            x2_clipped = max(0, min(x2, width))
-            y2_clipped = max(0, min(y2, height))
+                        output_path = os.path.join(output_dir, f"frame_{idx:04d}.jpg")
+                        cv2.imwrite(output_path, resized)
+                        keyframe_paths.append(output_path)
 
-            if x2_clipped <= x1_clipped or y2_clipped <= y1_clipped:
-                return idx, None
-
-            cropped = img[y1_clipped:y2_clipped, x1_clipped:x2_clipped]
-            resized = cv2.resize(cropped, (224, 224))
-
-            output_path = os.path.join(output_dir, f"frame_{idx:04d}.jpg")
-            cv2.imwrite(output_path, resized)
-            return idx, output_path
         except Exception as e:
             logger.debug(
                 f"Failed to extract frame from {recording.path} at {relative_time}s: {e}"
             )
-            return idx, None
+            continue
 
-    keyframes_with_index: list[tuple[int, str]] = []
-
-    with ThreadPoolExecutor(max_workers=max_workers) as executor:
-        future_to_idx = {
-            executor.submit(_process_timestamp, idx, ts_info): idx
-            for idx, ts_info in enumerate(timestamps)
-        }
-
-        for future in as_completed(future_to_idx):
-            _, path = future.result()
-            if path:
-                keyframes_with_index.append((future_to_idx[future], path))
-
-    keyframes_with_index.sort(key=lambda item: item[0])
-    return [path for _, path in keyframes_with_index]
+    return keyframe_paths
 
 
 def _select_distinct_images(

web/src/App.tsx

@@ -14,7 +14,6 @@ import ProtectedRoute from "@/components/auth/ProtectedRoute";
 import { AuthProvider } from "@/context/auth-context";
 import useSWR from "swr";
 import { FrigateConfig } from "./types/frigateConfig";
-import ActivityIndicator from "@/components/indicators/activity-indicator";
 
 const Live = lazy(() => import("@/pages/Live"));
 const Events = lazy(() => import("@/pages/Events"));
@@ -51,13 +50,6 @@ function DefaultAppView() {
   const { data: config } = useSWR<FrigateConfig>("config", {
     revalidateOnFocus: false,
   });
-
-  // Compute required roles for main routes, ensuring we have config first
-  // to prevent race condition where custom roles are temporarily unavailable
-  const mainRouteRoles = config?.auth?.roles
-    ? Object.keys(config.auth.roles)
-    : undefined;
-
   return (
     <div className="size-full overflow-hidden">
       {isDesktop && <Sidebar />}
@@ -76,11 +68,13 @@ function DefaultAppView() {
           <Routes>
             <Route
               element={
-                mainRouteRoles ? (
-                  <ProtectedRoute requiredRoles={mainRouteRoles} />
-                ) : (
-                  <ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
-                )
+                <ProtectedRoute
+                  requiredRoles={
+                    config?.auth.roles
+                      ? Object.keys(config.auth.roles)
+                      : ["admin", "viewer"]
+                  }
+                />
               }
             >
               <Route index element={<Live />} />

web/src/components/overlay/ExportDialog.tsx

@@ -440,7 +440,6 @@ function CustomTimeSelector({
       <FaCalendarAlt />
       <div className="flex flex-wrap items-center">
         <Popover
-          modal={false}
           open={startOpen}
           onOpenChange={(open) => {
             if (!open) {
@@ -462,10 +461,7 @@ function CustomTimeSelector({
               {formattedStart}
             </Button>
           </PopoverTrigger>
-          <PopoverContent
-            disablePortal={isDesktop}
-            className="flex flex-col items-center"
-          >
+          <PopoverContent className="flex flex-col items-center">
             <TimezoneAwareCalendar
               timezone={config?.ui.timezone}
               selectedDay={new Date(startTime * 1000)}
@@ -510,7 +506,6 @@ function CustomTimeSelector({
         </Popover>
         <FaArrowRight className="size-4 text-primary" />
         <Popover
-          modal={false}
           open={endOpen}
           onOpenChange={(open) => {
             if (!open) {
@@ -532,10 +527,7 @@ function CustomTimeSelector({
               {formattedEnd}
             </Button>
           </PopoverTrigger>
-          <PopoverContent
-            disablePortal={isDesktop}
-            className="flex flex-col items-center"
-          >
+          <PopoverContent className="flex flex-col items-center">
             <TimezoneAwareCalendar
               timezone={config?.ui.timezone}
               selectedDay={new Date(endTime * 1000)}
@@ -553,7 +545,7 @@ function CustomTimeSelector({
             <SelectSeparator className="bg-secondary" />
             <input
               className="text-md mx-4 w-full border border-input bg-background p-1 text-secondary-foreground hover:bg-accent hover:text-accent-foreground dark:[color-scheme:dark]"
-              id="endTime"
+              id="startTime"
               type="time"
               value={endClock}
               step={isIOS ? "60" : "1"}

web/src/pages/Settings.tsx

@@ -438,7 +438,7 @@ export default function Settings() {
   return (
     <div className="flex h-full flex-col">
       <div className="flex items-center justify-between border-b border-secondary p-3">
-        <Heading as="h3" className="mb-0 min-h-9">
+        <Heading as="h3" className="mb-0">
           {t("menu.settings", { ns: "common" })}
         </Heading>
         {CAMERA_SELECT_BUTTON_PAGES.includes(page) && (