Merge 900f9f4ee8 into 2dcaeb6809

docker/main/install_deps.sh

@@ -87,43 +87,43 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
     # intel packages use zst compression so we need to update dpkg
     apt-get install -y dpkg
 
-    # use intel apt repo for libmfx1 (legacy QSV, pre-Gen12)
+    # use intel apt intel packages
     wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
     echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | tee /etc/apt/sources.list.d/intel-gpu-jammy.list
     apt-get -qq update
-
     # intel-media-va-driver-non-free is built from source in the
     # intel-media-driver Dockerfile stage for Battlemage (Xe2) support
     apt-get -qq install --no-install-recommends --no-install-suggests -y \
-        libmfx1
-    rm -f /usr/share/keyrings/intel-graphics.gpg
-    rm -f /etc/apt/sources.list.d/intel-gpu-jammy.list
+        libmfx1 libmfxgen1 libvpl2
 
-    # upgrade libva2, oneVPL runtime, and libvpl2 from trixie for Battlemage support
-    echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list
-    apt-get -qq update
-    apt-get -qq install -y -t trixie libva2 libva-drm2 libzstd1
-    apt-get -qq install -y -t trixie libmfx-gen1.2 libvpl2
-    rm -f /etc/apt/sources.list.d/trixie.list
-    apt-get -qq update
     apt-get -qq install -y ocl-icd-libopencl1
 
     # install libtbb12 for NPU support
     apt-get -qq install -y libtbb12
 
-    # install legacy and standard intel compute packages
+    rm -f /usr/share/keyrings/intel-graphics.gpg
+    rm -f /etc/apt/sources.list.d/intel-gpu-jammy.list
+
+    # install legacy and standard intel icd and level-zero-gpu
     # see https://github.com/intel/compute-runtime/blob/master/LEGACY_PLATFORMS.md for more info
+    # newer intel packages (gmmlib 22.9+, igc 2.32+) require libstdc++ >= 13.1 and libzstd >= 1.5.5
+    echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list
+    apt-get -qq update
+    apt-get -qq install -y -t trixie libstdc++6 libzstd1
+    rm -f /etc/apt/sources.list.d/trixie.list
+    apt-get -qq update
+
     # needed core package
     wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libigdgmm12_22.9.0_amd64.deb
     dpkg -i libigdgmm12_22.9.0_amd64.deb
     rm libigdgmm12_22.9.0_amd64.deb
 
-    # legacy compute-runtime packages
+    # legacy packages
     wget https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-opencl-icd-legacy1_24.35.30872.36_amd64.deb
     wget https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-level-zero-gpu-legacy1_1.5.30872.36_amd64.deb
     wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-opencl_1.0.17537.24_amd64.deb
     wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-core_1.0.17537.24_amd64.deb
-    # standard compute-runtime packages
+    # standard packages
     wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/intel-opencl-icd_26.14.37833.4-0_amd64.deb
     wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libze-intel-gpu1_26.14.37833.4-0_amd64.deb
     wget https://github.com/intel/intel-graphics-compiler/releases/download/v2.32.7/intel-igc-opencl-2_2.32.7+21184_amd64.deb
@@ -137,10 +137,6 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
     dpkg -i *.deb
     rm *.deb
     apt-get -qq install -f -y
-
-    # Battlemage uses the xe kernel driver, but the VA-API driver is still iHD.
-    # The oneVPL runtime may look for a driver named after the kernel module.
-    ln -sf /usr/lib/x86_64-linux-gnu/dri/iHD_drv_video.so /usr/lib/x86_64-linux-gnu/dri/xe_drv_video.so
 fi
 
 if [[ "${TARGETARCH}" == "arm64" ]]; then

docker/main/requirements-wheels.txt

@@ -11,7 +11,7 @@ joserfc == 1.2.*
 cryptography == 44.0.*
 pathvalidate == 3.3.*
 markupsafe == 3.0.*
-python-multipart == 0.0.26
+python-multipart == 0.0.20
 # Classification Model Training
 tensorflow == 2.19.* ; platform_machine == 'aarch64'
 tensorflow-cpu == 2.19.* ; platform_machine == 'x86_64'

docs/docs/integrations/third_party_extensions.md

@@ -39,10 +39,6 @@ This is a fork (with fixed errors and new features) of [original Double Take](ht
 
 [Frigate telegram](https://github.com/OldTyT/frigate-telegram) makes it possible to send events from Frigate to Telegram. Events are sent as a message with a text description, video, and thumbnail.
 
-## [kiosk-monitor](https://github.com/extremeshok/kiosk-monitor)
-
-[kiosk-monitor](https://github.com/extremeshok/kiosk-monitor) is a Raspberry Pi watchdog that runs Chromium fullscreen on a Frigate dashboard (optionally with VLC on a second monitor for an RTSP camera stream), auto-restarts on frozen screens or unreachable URLs, and ships a Birdseye-aware Chromium helper that auto-sizes the grid to the display.
-
 ## [Periscope](https://github.com/maksz42/periscope)
 
 [Periscope](https://github.com/maksz42/periscope) is a lightweight Android app that turns old devices into live viewers for Frigate. It works on Android 2.2 and above, including Android TV. It supports authentication and HTTPS.

docs/docs/troubleshooting/faqs.md

@@ -111,16 +111,26 @@ TCP ensures that all data packets arrive in the correct order. This is crucial f
 
 You can still configure Frigate to use UDP by using ffmpeg input args or the preset `preset-rtsp-udp`. See the [ffmpeg presets](/configuration/ffmpeg_presets) documentation.
 
-### Frigate is slow to start up with a "probing detect stream" message in the logs
+### Frigate hangs on startup with a "probing detect stream" message in the logs
 
-When `detect.width` and `detect.height` are not set, Frigate probes each camera's detect stream on startup (and when saving the config) to auto-detect its resolution. For RTSP streams Frigate probes with ffprobe and automatically retries over TCP if UDP doesn't respond, with a 5 second timeout per attempt. A camera that cannot be reached over either transport will add up to ~10 seconds to startup before Frigate falls through with default dimensions, which may show up as width `0` and height `0` in Camera Probe Info under System Metrics.
+On startup, Frigate probes each camera's detect stream with OpenCV to auto-detect its resolution. OpenCV's FFmpeg backend may attempt RTSP over UDP during this probe regardless of the `-rtsp_transport tcp` in your `input_args` or preset. For cameras that do not respond to UDP (common on some Reolink models and others behind firewalls that block UDP), the probe can hang indefinitely and block Frigate from finishing startup, or it can return zeroed-out dimensions that show up as width `0` and height `0` in Camera Probe Info under System Metrics.
 
-To skip the probe entirely and make startup instant, set `detect.width` and `detect.height` explicitly in your camera config:
+There are two ways to avoid this:
 
-```yaml
-cameras:
-  my_camera:
-    detect:
-      width: 1280
-      height: 720
-```
+1. Set `detect.width` and `detect.height` explicitly in your camera config. When both are set, Frigate skips the auto-detect probe entirely:
+
+   ```yaml
+   cameras:
+     my_camera:
+       detect:
+         width: 1280
+         height: 720
+   ```
+
+2. Force OpenCV's FFmpeg backend to use TCP for RTSP by setting the environment variable on your Frigate container:
+
+   ```
+   OPENCV_FFMPEG_CAPTURE_OPTIONS=rtsp_transport;tcp
+   ```
+
+   This is a process-wide setting and applies to all cameras. If you have any cameras that require `preset-rtsp-udp`, use option 1 instead.

docs/package-lock.json

@@ -10897,9 +10897,9 @@
       "license": "MIT"
     },
     "node_modules/express/node_modules/path-to-regexp": {
-      "version": "0.1.13",
-      "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.13.tgz",
-      "integrity": "sha512-A/AGNMFN3c8bOlvV9RreMdrv7jsmF9XIfDeCd87+I8RNg6s78BhJxMu69NEMHBSJFxKidViTEdruRwEk/WIKqA==",
+      "version": "0.1.12",
+      "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.12.tgz",
+      "integrity": "sha512-RA1GjUVMnvYFxuqovrEqZoxxW5NUZqbwKtYz/Tt7nXerk0LbLblQmrsgdeOxV5SFHf0UDggjS/bSeOZwt1pmEQ==",
       "license": "MIT"
     },
     "node_modules/express/node_modules/range-parser": {

frigate/embeddings/maintainer.py

@@ -310,10 +310,6 @@ class EmbeddingMaintainer(threading.Thread):
             self._handle_custom_classification_update(topic, payload)
             return
 
-        if topic == "config/genai":
-            self.config.genai = payload
-            self.genai_manager.update_config(self.config)
-
         # Broadcast to all processors — each decides if the topic is relevant
         for processor in self.realtime_processors:
             processor.update_config(topic, payload)

frigate/genai/ollama.py

@@ -113,15 +113,6 @@ class OllamaClient(GenAIClient):
                 schema = response_format.get("json_schema", {}).get("schema")
                 if schema:
                     ollama_options["format"] = self._clean_schema_for_ollama(schema)
-            logger.debug(
-                "Ollama generate request: model=%s, prompt_len=%s, image_count=%s, "
-                "has_format=%s, options=%s",
-                self.genai_config.model,
-                len(prompt),
-                len(images) if images else 0,
-                "format" in ollama_options,
-                {k: v for k, v in ollama_options.items() if k != "format"},
-            )
             result = self.provider.generate(
                 self.genai_config.model,
                 prompt,
@@ -129,24 +120,9 @@ class OllamaClient(GenAIClient):
                 **ollama_options,
             )
             logger.debug(
-                "Ollama generate response: done=%s, done_reason=%s, eval_count=%s, "
-                "prompt_eval_count=%s, response_len=%s",
-                result.get("done"),
-                result.get("done_reason"),
-                result.get("eval_count"),
-                result.get("prompt_eval_count"),
-                len(result.get("response", "") or ""),
+                f"Ollama tokens used: eval_count={result.get('eval_count')}, prompt_eval_count={result.get('prompt_eval_count')}"
             )
-            response_text = str(result["response"]).strip()
-            if not response_text:
-                logger.warning(
-                    "Ollama returned a blank response for model %s (done_reason=%s, "
-                    "eval_count=%s). Check model output, ensure thinking is disabled.",
-                    self.genai_config.model,
-                    result.get("done_reason"),
-                    result.get("eval_count"),
-                )
-            return response_text
+            return str(result["response"]).strip()
         except (
             TimeoutException,
             ResponseError,

frigate/genai/openai.py

@@ -80,23 +80,7 @@ class OpenAIClient(GenAIClient):
                 and hasattr(result, "choices")
                 and len(result.choices) > 0
             ):
-                message = result.choices[0].message
-                content = message.content
-
-                if not content:
-                    # When reasoning is enabled for some OpenAI backends the actual response
-                    # is incorrectly placed in reasoning_content instead of content.
-                    # This is buggy/incorrect behavior — reasoning should not be
-                    # enabled for these models.
-                    reasoning_content = getattr(message, "reasoning_content", None)
-                    if reasoning_content:
-                        logger.warning(
-                            "Response content was empty but reasoning_content was provided; "
-                            "reasoning appears to be enabled and should be disabled for this model."
-                        )
-                        content = reasoning_content
-
-                return str(content.strip()) if content else None
+                return str(result.choices[0].message.content.strip())
             return None
         except (TimeoutException, Exception) as e:
             logger.warning("OpenAI returned an error: %s", str(e))

frigate/util/classification.py

@@ -24,12 +24,8 @@ from frigate.log import redirect_output_to_logger, suppress_stderr_during
 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, load_event_snapshot_image
-from frigate.util.image import (
-    calculate_region,
-    get_image_from_recording,
-    relative_box_to_absolute,
-)
+from frigate.util.file import get_event_thumbnail_bytes
+from frigate.util.image import get_image_from_recording
 from frigate.util.process import FrigateProcess
 
 BATCH_SIZE = 16
@@ -717,7 +713,7 @@ def collect_object_classification_examples(
     This function:
     1. Queries events for the specified label
     2. Selects 100 balanced events across different cameras and times
-    3. Crops each event's clean snapshot around the object bounding box
+    3. Retrieves thumbnails for selected events (with 33% center crop applied)
     4. Selects 24 most visually distinct thumbnails
     5. Saves to dataset directory
 
@@ -836,106 +832,66 @@ def _select_balanced_events(
 
 def _extract_event_thumbnails(events: list[Event], output_dir: str) -> list[str]:
     """
-    Extract a training image for each event.
-
-    Preferred path: load the full-frame clean snapshot and crop around the
-    stored bounding box with the same calculate_region(..., max(w, h), 1.0)
-    call the live ObjectClassificationProcessor uses, so wizard examples
-    are framed like inference-time inputs.
-
-    Fallback: if no clean snapshot exists (snapshots disabled, or only a
-    legacy annotated JPG is on disk), center-crop the stored thumbnail
-    using a step ladder sized from the box/region area ratio.
+    Extract thumbnails from events and save to disk.
 
     Args:
         events: List of Event objects
-        output_dir: Directory to save crops
+        output_dir: Directory to save thumbnails
 
     Returns:
-        List of paths to successfully extracted images
+        List of paths to successfully extracted thumbnail images
     """
-    image_paths = []
+    thumbnail_paths = []
 
     for idx, event in enumerate(events):
         try:
-            img = _load_event_classification_crop(event)
-            if img is None:
-                continue
+            thumbnail_bytes = get_event_thumbnail_bytes(event)
 
-            resized = cv2.resize(img, (224, 224))
-            output_path = os.path.join(output_dir, f"thumbnail_{idx:04d}.jpg")
-            cv2.imwrite(output_path, resized)
-            image_paths.append(output_path)
+            if thumbnail_bytes:
+                nparr = np.frombuffer(thumbnail_bytes, np.uint8)
+                img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+
+                if img is not None:
+                    height, width = img.shape[:2]
+
+                    crop_size = 1.0
+                    if event.data and "box" in event.data and "region" in event.data:
+                        box = event.data["box"]
+                        region = event.data["region"]
+
+                        if len(box) == 4 and len(region) == 4:
+                            box_w, box_h = box[2], box[3]
+                            region_w, region_h = region[2], region[3]
+
+                            box_area = (box_w * box_h) / (region_w * region_h)
+
+                            if box_area < 0.05:
+                                crop_size = 0.4
+                            elif box_area < 0.10:
+                                crop_size = 0.5
+                            elif box_area < 0.20:
+                                crop_size = 0.65
+                            elif box_area < 0.35:
+                                crop_size = 0.80
+                            else:
+                                crop_size = 0.95
+
+                    crop_width = int(width * crop_size)
+                    crop_height = int(height * crop_size)
+
+                    x1 = (width - crop_width) // 2
+                    y1 = (height - crop_height) // 2
+                    x2 = x1 + crop_width
+                    y2 = y1 + crop_height
+
+                    cropped = img[y1:y2, x1:x2]
+                    resized = cv2.resize(cropped, (224, 224))
+                    output_path = os.path.join(output_dir, f"thumbnail_{idx:04d}.jpg")
+                    cv2.imwrite(output_path, resized)
+                    thumbnail_paths.append(output_path)
 
         except Exception as e:
-            logger.debug(f"Failed to extract image for event {event.id}: {e}")
+            logger.debug(f"Failed to extract thumbnail for event {event.id}: {e}")
             continue
 
-    return image_paths
-
-
-def _load_event_classification_crop(event: Event) -> np.ndarray | None:
-    """Prefer a snapshot-based object crop; fall back to a center-cropped thumbnail."""
-    if event.data and "box" in event.data:
-        snapshot, _ = load_event_snapshot_image(event, clean_only=True)
-        if snapshot is not None:
-            abs_box = relative_box_to_absolute(snapshot.shape, event.data["box"])
-            if abs_box is not None:
-                xmin, ymin, xmax, ymax = abs_box
-                box_w = xmax - xmin
-                box_h = ymax - ymin
-                if box_w > 0 and box_h > 0:
-                    x1, y1, x2, y2 = calculate_region(
-                        snapshot.shape,
-                        xmin,
-                        ymin,
-                        xmax,
-                        ymax,
-                        max(box_w, box_h),
-                        1.0,
-                    )
-                    cropped = snapshot[y1:y2, x1:x2]
-                    if cropped.size > 0:
-                        return cropped
-
-    thumbnail_bytes = get_event_thumbnail_bytes(event)
-    if not thumbnail_bytes:
-        return None
-
-    nparr = np.frombuffer(thumbnail_bytes, np.uint8)
-    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    if img is None or img.size == 0:
-        return None
-
-    height, width = img.shape[:2]
-    crop_size = 1.0
-
-    if event.data and "box" in event.data and "region" in event.data:
-        box = event.data["box"]
-        region = event.data["region"]
-
-        if len(box) == 4 and len(region) == 4:
-            box_w, box_h = box[2], box[3]
-            region_w, region_h = region[2], region[3]
-            box_area = (box_w * box_h) / (region_w * region_h)
-
-            if box_area < 0.05:
-                crop_size = 0.4
-            elif box_area < 0.10:
-                crop_size = 0.5
-            elif box_area < 0.20:
-                crop_size = 0.65
-            elif box_area < 0.35:
-                crop_size = 0.80
-            else:
-                crop_size = 0.95
-
-    crop_width = int(width * crop_size)
-    crop_height = int(height * crop_size)
-    x1 = (width - crop_width) // 2
-    y1 = (height - crop_height) // 2
-    cropped = img[y1 : y1 + crop_height, x1 : x1 + crop_width]
-    if cropped.size == 0:
-        return None
-
-    return cropped
+    return thumbnail_paths

frigate/util/services.py

@@ -711,44 +711,23 @@ def ffprobe_stream(ffmpeg, path: str, detailed: bool = False) -> sp.CompletedPro
     else:
         format_entries = None
 
-    def run(rtsp_transport: Optional[str] = None) -> sp.CompletedProcess:
-        cmd = [ffmpeg.ffprobe_path]
-        if rtsp_transport:
-            cmd += ["-rtsp_transport", rtsp_transport]
-        cmd += [
-            "-timeout",
-            "1000000",
-            "-print_format",
-            "json",
-            "-show_entries",
-            f"stream={stream_entries}",
-        ]
-        if detailed and format_entries:
-            cmd.extend(["-show_entries", f"format={format_entries}"])
-        cmd.extend(["-loglevel", "error", clean_path])
-        try:
-            return sp.run(cmd, capture_output=True, timeout=6)
-        except sp.TimeoutExpired as e:
-            logger.info(
-                "ffprobe timed out while probing %s (transport=%s)",
-                clean_camera_user_pass(path),
-                rtsp_transport or "default",
-            )
-            return sp.CompletedProcess(
-                args=cmd,
-                returncode=1,
-                stdout=e.stdout or b"",
-                stderr=(e.stderr or b"") + b"\nffprobe timed out",
-            )
+    ffprobe_cmd = [
+        ffmpeg.ffprobe_path,
+        "-timeout",
+        "1000000",
+        "-print_format",
+        "json",
+        "-show_entries",
+        f"stream={stream_entries}",
+    ]
 
-    result = run()
+    # Add format entries for detailed mode
+    if detailed and format_entries:
+        ffprobe_cmd.extend(["-show_entries", f"format={format_entries}"])
 
-    # For RTSP: retry with explicit TCP transport if the first attempt failed
-    # (default UDP may be blocked)
-    if result.returncode != 0 and clean_path.startswith("rtsp://"):
-        result = run(rtsp_transport="tcp")
+    ffprobe_cmd.extend(["-loglevel", "error", clean_path])
 
-    return result
+    return sp.run(ffprobe_cmd, capture_output=True)
 
 
 def vainfo_hwaccel(device_name: Optional[str] = None) -> sp.CompletedProcess:
@@ -828,15 +807,10 @@ async def get_video_properties(
 ) -> dict[str, Any]:
     async def probe_with_ffprobe(
         url: str,
-        rtsp_transport: Optional[str] = None,
     ) -> tuple[bool, int, int, Optional[str], float]:
         """Fallback using ffprobe: returns (valid, width, height, codec, duration)."""
-        cmd = [ffmpeg.ffprobe_path]
-        if rtsp_transport:
-            cmd += ["-rtsp_transport", rtsp_transport]
-        cmd += [
-            "-rw_timeout",
-            "5000000",
+        cmd = [
+            ffmpeg.ffprobe_path,
             "-v",
             "quiet",
             "-print_format",
@@ -845,23 +819,11 @@ async def get_video_properties(
             "-show_streams",
             url,
         ]
-        proc = None
         try:
             proc = await asyncio.create_subprocess_exec(
                 *cmd, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
             )
-            try:
-                stdout, _ = await asyncio.wait_for(proc.communicate(), timeout=6)
-            except asyncio.TimeoutError:
-                logger.info(
-                    "ffprobe timed out while probing %s (transport=%s)",
-                    clean_camera_user_pass(url),
-                    rtsp_transport or "default",
-                )
-                proc.kill()
-                await proc.wait()
-                return False, 0, 0, None, -1
-
+            stdout, _ = await proc.communicate()
             if proc.returncode != 0:
                 return False, 0, 0, None, -1
 
@@ -910,26 +872,12 @@ async def get_video_properties(
         cap.release()
         return valid, width, height, fourcc, duration
 
-    is_rtsp = url.startswith("rtsp://")
+    # try cv2 first
+    has_video, width, height, fourcc, duration = probe_with_cv2(url)
 
-    if is_rtsp:
-        # skip cv2 for RTSP: its FFmpeg backend has a hardcoded ~30s internal
-        # timeout that cannot be shortened per-call, and ffprobe bounded by
-        # -rw_timeout handles RTSP probing reliably
+    # fallback to ffprobe if needed
+    if not has_video or (get_duration and duration < 0):
         has_video, width, height, fourcc, duration = await probe_with_ffprobe(url)
-    else:
-        # try cv2 first for local files, HTTP, RTMP
-        has_video, width, height, fourcc, duration = probe_with_cv2(url)
-
-        # fallback to ffprobe if needed
-        if not has_video or (get_duration and duration < 0):
-            has_video, width, height, fourcc, duration = await probe_with_ffprobe(url)
-
-    # last resort for RTSP: try TCP transport, since default UDP may be blocked
-    if (not has_video or (get_duration and duration < 0)) and is_rtsp:
-        has_video, width, height, fourcc, duration = await probe_with_ffprobe(
-            url, rtsp_transport="tcp"
-        )
 
     result: dict[str, Any] = {"has_valid_video": has_video}
     if has_video:

web/package-lock.json

@@ -54,7 +54,7 @@
         "immer": "^10.1.1",
         "js-yaml": "^4.1.1",
         "konva": "^10.2.3",
-        "lodash": "^4.18.1",
+        "lodash": "^4.17.23",
         "lucide-react": "^0.577.0",
         "monaco-yaml": "^5.4.1",
         "next-themes": "^0.4.6",
@@ -9636,15 +9636,15 @@
       }
     },
     "node_modules/lodash": {
-      "version": "4.18.1",
-      "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.18.1.tgz",
-      "integrity": "sha512-dMInicTPVE8d1e5otfwmmjlxkZoUpiVLwyeTdUsi/Caj/gfzzblBcCE5sRHV/AsjuCmxWrte2TNGSYuCeCq+0Q==",
+      "version": "4.17.23",
+      "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.23.tgz",
+      "integrity": "sha512-LgVTMpQtIopCi79SJeDiP0TfWi5CNEc/L/aRdTh3yIvmZXTnheWpKjSZhnvMl8iXbC1tFg9gdHHDMLoV7CnG+w==",
       "license": "MIT"
     },
     "node_modules/lodash-es": {
-      "version": "4.18.1",
-      "resolved": "https://registry.npmjs.org/lodash-es/-/lodash-es-4.18.1.tgz",
-      "integrity": "sha512-J8xewKD/Gk22OZbhpOVSwcs60zhd95ESDwezOFuA3/099925PdHJ7OFHNTGtajL3AlZkykD32HykiMo+BIBI8A==",
+      "version": "4.17.23",
+      "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.23.tgz",
+      "integrity": "sha512-LgVTMpQtIopCi79SJeDiP0TfWi5CNEc/L/aRdTh3yIvmZXTnheWpKjSZhnvMl8iXbC1tFg9gdHHDMLoV7CnG+w==",
       "license": "MIT"
     },
     "node_modules/lodash.merge": {

web/package.json

@@ -68,7 +68,7 @@
     "immer": "^10.1.1",
     "js-yaml": "^4.1.1",
     "konva": "^10.2.3",
-    "lodash": "^4.18.1",
+    "lodash": "^4.17.23",
     "lucide-react": "^0.577.0",
     "monaco-yaml": "^5.4.1",
     "next-themes": "^0.4.6",

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

@@ -415,7 +415,6 @@
         "audioCodecGood": "Audio codec is {{codec}}.",
         "resolutionHigh": "A resolution of {{resolution}} may cause increased resource usage.",
         "resolutionLow": "A resolution of {{resolution}} may be too low for reliable detection of small objects.",
-        "resolutionUnknown": "The resolution of this stream could not be probed. You should manually set the detect resolution in Settings or your config.",
         "noAudioWarning": "No audio detected for this stream, recordings will not have audio.",
         "audioCodecRecordError": "The AAC audio codec is required to support audio in recordings.",
         "audioCodecRequired": "An audio stream is required to support audio detection.",

web/src/components/card/AnimatedEventCard.tsx

@@ -17,9 +17,6 @@ import { useUserPersistence } from "@/hooks/use-user-persistence";
 import { Skeleton } from "../ui/skeleton";
 import { Button } from "../ui/button";
 import { FaCircleCheck } from "react-icons/fa6";
-import { FaExclamationTriangle } from "react-icons/fa";
-import { MdOutlinePersonSearch } from "react-icons/md";
-import { ThreatLevel } from "@/types/review";
 import { cn } from "@/lib/utils";
 import { useTranslation } from "react-i18next";
 import { getTranslatedLabel } from "@/utils/i18n";
@@ -130,11 +127,6 @@ export function AnimatedEventCard({
     true,
   );
 
-  const threatLevel = useMemo<ThreatLevel>(
-    () => (event.data.metadata?.potential_threat_level ?? 0) as ThreatLevel,
-    [event],
-  );
-
   const aspectRatio = useMemo(() => {
     if (
       !config ||
@@ -160,15 +152,7 @@ export function AnimatedEventCard({
           <Tooltip>
             <TooltipTrigger asChild>
               <Button
-                className={cn(
-                  "absolute left-2 top-1 z-40 transition-opacity",
-                  threatLevel === ThreatLevel.SECURITY_CONCERN &&
-                    "pointer-events-auto bg-severity_alert opacity-100 hover:bg-severity_alert",
-                  threatLevel === ThreatLevel.NEEDS_REVIEW &&
-                    "pointer-events-auto bg-severity_detection opacity-100 hover:bg-severity_detection",
-                  threatLevel === ThreatLevel.NORMAL &&
-                    "pointer-events-none bg-gray-500 bg-gradient-to-br from-gray-400 to-gray-500 opacity-0 group-hover:pointer-events-auto group-hover:opacity-100",
-                )}
+                className="pointer-events-none absolute left-2 top-1 z-40 bg-gray-500 bg-gradient-to-br from-gray-400 to-gray-500 opacity-0 transition-opacity group-hover:pointer-events-auto group-hover:opacity-100"
                 size="xs"
                 aria-label={t("markAsReviewed")}
                 onClick={async () => {
@@ -176,13 +160,7 @@ export function AnimatedEventCard({
                   updateEvents();
                 }}
               >
-                {threatLevel === ThreatLevel.SECURITY_CONCERN ? (
-                  <FaExclamationTriangle className="size-3 text-white" />
-                ) : threatLevel === ThreatLevel.NEEDS_REVIEW ? (
-                  <MdOutlinePersonSearch className="size-3 text-white" />
-                ) : (
-                  <FaCircleCheck className="size-3 text-white" />
-                )}
+                <FaCircleCheck className="size-3 text-white" />
               </Button>
             </TooltipTrigger>
             <TooltipContent>{t("markAsReviewed")}</TooltipContent>

web/src/components/config-form/sectionExtras/CameraReviewClassification.tsx

@@ -218,7 +218,7 @@ export default function CameraReviewClassification({
                 <Label
                   className={cn(
                     "flex flex-row items-center text-base",
-                    alertsZonesModified && "text-unsaved",
+                    alertsZonesModified && "text-danger",
                   )}
                 >
                   <Trans ns="views/settings">cameraReview.review.alerts</Trans>
@@ -286,7 +286,7 @@ export default function CameraReviewClassification({
                 <Label
                   className={cn(
                     "flex flex-row items-center text-base",
-                    detectionsZonesModified && "text-unsaved",
+                    detectionsZonesModified && "text-danger",
                   )}
                 >
                   <Trans ns="views/settings">

web/src/components/config-form/sections/BaseSection.tsx

@@ -1012,7 +1012,7 @@ export function ConfigSection({
         >
           {hasChanges && (
             <div className="flex items-center gap-2">
-              <span className="text-sm text-unsaved">
+              <span className="text-sm text-danger">
                 {t("unsavedChanges", {
                   ns: "views/settings",
                   defaultValue: "You have unsaved changes",
@@ -1299,7 +1299,7 @@ export function ConfigSection({
                 {hasChanges && (
                   <Badge
                     variant="secondary"
-                    className="cursor-default bg-unsaved text-xs text-black hover:bg-unsaved"
+                    className="cursor-default bg-danger text-xs text-white hover:bg-danger"
                   >
                     {t("button.modified", {
                       ns: "common",

web/src/components/config-form/theme/fields/KnownPlatesField.tsx

@@ -154,7 +154,7 @@ export function KnownPlatesField(props: FieldProps) {
             <div className="flex items-center justify-between">
               <div>
                 <CardTitle
-                  className={cn("text-sm", isModified && "text-unsaved")}
+                  className={cn("text-sm", isModified && "text-danger")}
                 >
                   {title}
                 </CardTitle>

web/src/components/config-form/theme/fields/ReplaceRulesField.tsx

@@ -142,7 +142,7 @@ export function ReplaceRulesField(props: FieldProps) {
             <div className="flex items-center justify-between">
               <div>
                 <CardTitle
-                  className={cn("text-sm", isModified && "text-unsaved")}
+                  className={cn("text-sm", isModified && "text-danger")}
                 >
                   {title}
                 </CardTitle>

web/src/components/config-form/theme/templates/FieldTemplate.tsx

@@ -497,7 +497,7 @@ export function FieldTemplate(props: FieldTemplateProps) {
         htmlFor={id}
         className={cn(
           "text-sm font-medium",
-          isModified && "text-unsaved",
+          isModified && "text-danger",
           hasFieldErrors && "text-destructive",
         )}
       >
@@ -516,7 +516,7 @@ export function FieldTemplate(props: FieldTemplateProps) {
     return (
       <Label
         htmlFor={id}
-        className={cn("text-sm font-medium", isModified && "text-unsaved")}
+        className={cn("text-sm font-medium", isModified && "text-danger")}
       >
         {finalLabel}
         {required && <span className="ml-1 text-destructive">*</span>}
@@ -535,7 +535,7 @@ export function FieldTemplate(props: FieldTemplateProps) {
         htmlFor={id}
         className={cn(
           "text-sm font-medium",
-          isModified && "text-unsaved",
+          isModified && "text-danger",
           hasFieldErrors && "text-destructive",
         )}
       >

web/src/components/config-form/theme/templates/ObjectFieldTemplate.tsx

@@ -467,7 +467,7 @@ export function ObjectFieldTemplate(props: ObjectFieldTemplateProps) {
                 <CardTitle
                   className={cn(
                     "flex items-center text-sm",
-                    hasModifiedDescendants && "text-unsaved",
+                    hasModifiedDescendants && "text-danger",
                   )}
                 >
                   {inferredLabel}

web/src/components/settings/wizard/Step4Validation.tsx

@@ -607,38 +607,23 @@ function StreamIssues({
       }
     }
 
-    if (stream.roles.includes("detect") && stream.testResult) {
-      const probedResolution = stream.testResult.resolution;
-      let probedWidth = 0;
-      let probedHeight = 0;
-      if (probedResolution) {
-        const [w, h] = probedResolution.split("x").map(Number);
-        if (!isNaN(w) && !isNaN(h)) {
-          probedWidth = w;
-          probedHeight = h;
-        }
-      }
-
-      if (probedWidth <= 0 || probedHeight <= 0) {
-        result.push({
-          type: "error",
-          message: t("cameraWizard.step4.issues.resolutionUnknown"),
-        });
-      } else {
-        const minDimension = Math.min(probedWidth, probedHeight);
-        const maxDimension = Math.max(probedWidth, probedHeight);
+    if (stream.roles.includes("detect") && stream.resolution) {
+      const [width, height] = stream.resolution.split("x").map(Number);
+      if (!isNaN(width) && !isNaN(height) && width > 0 && height > 0) {
+        const minDimension = Math.min(width, height);
+        const maxDimension = Math.max(width, height);
         if (minDimension > 1080) {
           result.push({
             type: "warning",
             message: t("cameraWizard.step4.issues.resolutionHigh", {
-              resolution: probedResolution,
+              resolution: stream.resolution,
             }),
           });
         } else if (maxDimension < 640) {
           result.push({
             type: "error",
             message: t("cameraWizard.step4.issues.resolutionLow", {
-              resolution: probedResolution,
+              resolution: stream.resolution,
             }),
           });
         }

web/src/pages/Settings.tsx

@@ -1435,7 +1435,7 @@ export default function Settings() {
                 />
               )}
               {showUnsavedDot && (
-                <span className="inline-block size-2 rounded-full bg-unsaved" />
+                <span className="inline-block size-2 rounded-full bg-danger" />
               )}
             </div>
           )}
@@ -1516,7 +1516,7 @@ export default function Settings() {
               <div className="sticky bottom-0 z-50 mt-2 bg-background p-4">
                 <div className="flex flex-col items-center gap-2">
                   <div className="flex items-center gap-2">
-                    <span className="text-sm text-unsaved">
+                    <span className="text-sm text-danger">
                       {t("unsavedChanges", {
                         ns: "views/settings",
                         defaultValue: "You have unsaved changes",

web/src/utils/profileColors.ts

@@ -79,11 +79,11 @@ const PROFILE_COLORS: ProfileColor[] = [
     bgMuted: "bg-green-400/20",
   },
   {
-    bg: "bg-fuchsia-500",
-    text: "text-fuchsia-500",
-    dot: "bg-fuchsia-500",
-    border: "border-fuchsia-500",
-    bgMuted: "bg-fuchsia-500/20",
+    bg: "bg-amber-400",
+    text: "text-amber-400",
+    dot: "bg-amber-400",
+    border: "border-amber-400",
+    bgMuted: "bg-amber-400/20",
   },
   {
     bg: "bg-slate-400",
@@ -93,11 +93,11 @@ const PROFILE_COLORS: ProfileColor[] = [
     bgMuted: "bg-slate-400/20",
   },
   {
-    bg: "bg-stone-500",
-    text: "text-stone-500",
-    dot: "bg-stone-500",
-    border: "border-stone-500",
-    bgMuted: "bg-stone-500/20",
+    bg: "bg-orange-300",
+    text: "text-orange-300",
+    dot: "bg-orange-300",
+    border: "border-orange-300",
+    bgMuted: "bg-orange-300/20",
   },
   {
     bg: "bg-blue-300",

web/src/views/live/LiveCameraView.tsx

@@ -389,7 +389,7 @@ export default function LiveCameraView({
     return "mse";
   }, [lowBandwidth, mic, webRTC, isRestreamed]);
 
-  useKeyboardListener(["m", "Escape"], (key, modifiers) => {
+  useKeyboardListener(["m"], (key, modifiers) => {
     if (!modifiers.down) {
       return true;
     }
@@ -407,12 +407,6 @@ export default function LiveCameraView({
           return true;
         }
         break;
-      case "Escape":
-        if (!fullscreen) {
-          navigate(-1);
-          return true;
-        }
-        break;
     }
 
     return false;

web/src/views/settings/Go2RtcStreamsSettingsView.tsx

@@ -380,9 +380,7 @@ export default function Go2RtcStreamsSettingsView({
         >
           {hasChanges && (
             <div className="flex items-center gap-2">
-              <span className="text-sm text-unsaved">
-                {t("unsavedChanges")}
-              </span>
+              <span className="text-sm text-danger">{t("unsavedChanges")}</span>
             </div>
           )}
           <div className="flex w-full items-center gap-2 md:w-auto">

web/src/views/settings/SingleSectionPage.tsx

@@ -212,7 +212,7 @@ export function SingleSectionPage({
             {sectionStatus.hasChanges && (
               <Badge
                 variant="secondary"
-                className="cursor-default bg-unsaved text-xs text-black hover:bg-unsaved"
+                className="cursor-default bg-danger text-xs text-white hover:bg-danger"
               >
                 {t("button.modified", {
                   ns: "common",
@@ -250,7 +250,7 @@ export function SingleSectionPage({
           {sectionStatus.hasChanges && (
             <Badge
               variant="secondary"
-              className="cursor-default bg-unsaved text-xs text-black hover:bg-unsaved"
+              className="cursor-default bg-danger text-xs text-white hover:bg-danger"
             >
               {t("button.modified", { ns: "common", defaultValue: "Modified" })}
             </Badge>

web/tailwind.config.cjs

@@ -65,7 +65,6 @@ module.exports = {
         ring: "hsl(var(--ring))",
         danger: "#ef4444",
         success: "#22c55e",
-        unsaved: "#f59e0b",
         background: "hsl(var(--background))",
         background_alt: "hsl(var(--background-alt))",
         foreground: "hsl(var(--foreground))",