Fixes (#18117)

* face library i18n fixes

* face library i18n fixes

* add ability to use ctrl/cmd S to save in the config editor

* Use datetime as ID

* Update metrics inference speed to start with 0 ms

* fix android formatted thumbnail

* ensure role is comma separated and stripped correctly

* improve face library deletion

- add a confirmation dialog
- add ability to select all / delete faces in collections

* Implement lazy loading for video previews

* Force GPU for large embedding model

* GPU is required

* settings i18n fixes

* Don't delete train tab

* webpush debugging logs

* Fix incorrectly copying zones

* copy path data

* Ensure that cache dir exists for Frigate+

* face docs update

* Add description to upload image step to clarify the image

* Clean up

---------

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

docs/docs/configuration/face_recognition.md

@@ -34,7 +34,7 @@ All of these features run locally on your system.
 
 The `small` model is optimized for efficiency and runs on the CPU, most CPUs should run the model efficiently.
 
-The `large` model is optimized for accuracy, an integrated or discrete GPU is highly recommended. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation.
+The `large` model is optimized for accuracy, an integrated or discrete GPU is required. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation.
 
 ## Configuration
 
@@ -107,17 +107,17 @@ When choosing images to include in the face training set it is recommended to al
 
 ### Step 1 - Building a Strong Foundation
 
-When first enabling face recognition it is important to build a foundation of strong images. It is recommended to start by uploading 1-5 "portrait" photos for each person. It is important that the person's face in the photo is straight-on and not turned which will ensure a good starting point.
+When first enabling face recognition it is important to build a foundation of strong images. It is recommended to start by uploading 1-5 photos containing just this person's face. It is important that the person's face in the photo is front-facing and not turned, this will ensure a good starting point.
 
-Then it is recommended to use the `Face Library` tab in Frigate to select and train images for each person as they are detected. When building a strong foundation it is strongly recommended to only train on images that are straight-on. Ignore images from cameras that recognize faces from an angle.
+Then it is recommended to use the `Face Library` tab in Frigate to select and train images for each person as they are detected. When building a strong foundation it is strongly recommended to only train on images that are front-facing. Ignore images from cameras that recognize faces from an angle.
 
 Aim to strike a balance between the quality of images while also having a range of conditions (day / night, different weather conditions, different times of day, etc.) in order to have diversity in the images used for each person and not have over-fitting.
 
-Once a person starts to be consistently recognized correctly on images that are straight-on, it is time to move on to the next step.
+Once a person starts to be consistently recognized correctly on images that are front-facing, it is time to move on to the next step.
 
 ### Step 2 - Expanding The Dataset
 
-Once straight-on images are performing well, start choosing slightly off-angle images to include for training. It is important to still choose images where enough face detail is visible to recognize someone.
+Once front-facing images are performing well, start choosing slightly off-angle images to include for training. It is important to still choose images where enough face detail is visible to recognize someone.
 
 ## FAQ
 
@@ -156,3 +156,7 @@ Face recognition does not run on the recording stream, this would be suboptimal
 ### I get an unknown error when taking a photo directly with my iPhone
 
 By default iOS devices will use HEIC (High Efficiency Image Container) for images, but this format is not supported for uploads. Choosing `large` as the format instead of `original` will use JPG which will work correctly.
+
+## How can I delete the face database and start over?
+
+Frigate does not store anything in its database related to face recognition. You can simply delete all of your faces through the Frigate UI or remove the contents of the `/media/frigate/clips/faces` directory.

frigate/api/auth.py

@@ -268,7 +268,9 @@ def auth(request: Request):
 
         # if comma-separated with "admin", use "admin", else use default role
         success_response.headers["remote-role"] = (
-            "admin" if role and "admin" in role else proxy_config.default_role
+            "admin"
+            if role and "admin" in [r.strip() for r in role.split(",")]
+            else proxy_config.default_role
         )
 
         return success_response

frigate/api/classification.py

@@ -1,10 +1,9 @@
 """Object classification APIs."""
 
+import datetime
 import logging
 import os
-import random
 import shutil
-import string
 
 import cv2
 from fastapi import APIRouter, Depends, Request, UploadFile
@@ -120,8 +119,7 @@ def train_face(request: Request, name: str, body: dict = None):
         )
 
     sanitized_name = sanitize_filename(name)
-    rand_id = "".join(random.choices(string.ascii_lowercase + string.digits, k=6))
+    new_name = f"{sanitized_name}-{datetime.datetime.now().timestamp()}.webp"
-    new_name = f"{sanitized_name}-{rand_id}.webp"
     new_file_folder = os.path.join(FACE_DIR, f"{sanitized_name}")
 
     if not os.path.exists(new_file_folder):

frigate/api/media.py

@@ -909,7 +909,7 @@ def event_thumbnail(
         elif extension == "webp":
             quality_params = [int(cv2.IMWRITE_WEBP_QUALITY), 60]
 
-        _, img = cv2.imencode(f".{img}", thumbnail, quality_params)
+        _, img = cv2.imencode(f".{extension}", thumbnail, quality_params)
         thumbnail_bytes = img.tobytes()
 
     return Response(

frigate/comms/webpush.py

@@ -303,6 +303,9 @@ class WebPushClient(Communicator):  # type: ignore[misc]
             and len(payload["before"]["data"]["zones"])
             == len(payload["after"]["data"]["zones"])
         ):
+            logger.debug(
+                f"Skipping notification for {camera} - message is an update and important fields don't have an update"
+            )
             return
 
         self.last_camera_notification_time[camera] = current_time
@@ -325,6 +328,8 @@ class WebPushClient(Communicator):  # type: ignore[misc]
         direct_url = f"/review?id={reviewId}" if state == "end" else f"/#{camera}"
         ttl = 3600 if state == "end" else 0
 
+        logger.debug(f"Sending push notification for {camera}, review ID {reviewId}")
+
         for user in self.web_pushers:
             self.send_push_notification(
                 user=user,

frigate/data_processing/common/license_plate/mixin.py

@@ -25,7 +25,7 @@ from frigate.comms.event_metadata_updater import (
 from frigate.const import CLIPS_DIR
 from frigate.embeddings.onnx.lpr_embedding import LPR_EMBEDDING_SIZE
 from frigate.types import TrackedObjectUpdateTypesEnum
-from frigate.util.builtin import EventsPerSecond
+from frigate.util.builtin import EventsPerSecond, InferenceSpeed
 from frigate.util.image import area
 
 logger = logging.getLogger(__name__)
@@ -36,8 +36,10 @@ WRITE_DEBUG_IMAGES = False
 class LicensePlateProcessingMixin:
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
+        self.plate_rec_speed = InferenceSpeed(self.metrics.alpr_speed)
         self.plates_rec_second = EventsPerSecond()
         self.plates_rec_second.start()
+        self.plate_det_speed = InferenceSpeed(self.metrics.yolov9_lpr_speed)
         self.plates_det_second = EventsPerSecond()
         self.plates_det_second.start()
         self.event_metadata_publisher = EventMetadataPublisher()
@@ -1157,22 +1159,6 @@ class LicensePlateProcessingMixin:
         # 5. Return True if previous plate scores higher
         return prev_score > curr_score
 
-    def __update_yolov9_metrics(self, duration: float) -> None:
-        """
-        Update inference metrics.
-        """
-        self.metrics.yolov9_lpr_speed.value = (
-            self.metrics.yolov9_lpr_speed.value * 9 + duration
-        ) / 10
-
-    def __update_lpr_metrics(self, duration: float) -> None:
-        """
-        Update inference metrics.
-        """
-        self.metrics.alpr_speed.value = (
-            self.metrics.alpr_speed.value * 9 + duration
-        ) / 10
-
     def _generate_plate_event(self, camera: str, plate: str, plate_score: float) -> str:
         """Generate a unique ID for a plate event based on camera and text."""
         now = datetime.datetime.now().timestamp()
@@ -1228,7 +1214,7 @@ class LicensePlateProcessingMixin:
                 f"{camera}: YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
             )
             self.plates_det_second.update()
-            self.__update_yolov9_metrics(
+            self.plate_det_speed.update(
                 datetime.datetime.now().timestamp() - yolov9_start
             )
 
@@ -1319,7 +1305,7 @@ class LicensePlateProcessingMixin:
                     f"{camera}: YOLOv9 LPD inference time: {(datetime.datetime.now().timestamp() - yolov9_start) * 1000:.2f} ms"
                 )
                 self.plates_det_second.update()
-                self.__update_yolov9_metrics(
+                self.plate_det_speed.update(
                     datetime.datetime.now().timestamp() - yolov9_start
                 )
 
@@ -1433,7 +1419,7 @@ class LicensePlateProcessingMixin:
             camera, id, license_plate_frame
         )
         self.plates_rec_second.update()
-        self.__update_lpr_metrics(datetime.datetime.now().timestamp() - start)
+        self.plate_rec_speed.update(datetime.datetime.now().timestamp() - start)
 
         if license_plates:
             for plate, confidence, text_area in zip(license_plates, confidences, areas):

frigate/data_processing/real_time/face.py

@@ -5,9 +5,7 @@ import datetime
 import json
 import logging
 import os
-import random
 import shutil
-import string
 from typing import Optional
 
 import cv2
@@ -27,7 +25,7 @@ from frigate.data_processing.common.face.model import (
     FaceRecognizer,
 )
 from frigate.types import TrackedObjectUpdateTypesEnum
-from frigate.util.builtin import EventsPerSecond
+from frigate.util.builtin import EventsPerSecond, InferenceSpeed
 from frigate.util.image import area
 
 from ..types import DataProcessorMetrics
@@ -58,6 +56,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
         self.person_face_history: dict[str, list[tuple[str, float, int]]] = {}
         self.recognizer: FaceRecognizer | None = None
         self.faces_per_second = EventsPerSecond()
+        self.inference_speed = InferenceSpeed(self.metrics.face_rec_speed)
 
         download_path = os.path.join(MODEL_CACHE_DIR, "facedet")
         self.model_files = {
@@ -155,9 +154,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
     def __update_metrics(self, duration: float) -> None:
         self.faces_per_second.update()
-        self.metrics.face_rec_speed.value = (
+        self.inference_speed.update(duration)
-            self.metrics.face_rec_speed.value * 9 + duration
-        ) / 10
 
     def process_frame(self, obj_data: dict[str, any], frame: np.ndarray):
         """Look for faces in image."""
@@ -343,11 +340,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
             return {"success": True, "score": score, "face_name": sub_label}
         elif topic == EmbeddingsRequestEnum.register_face.value:
-            rand_id = "".join(
-                random.choices(string.ascii_lowercase + string.digits, k=6)
-            )
             label = request_data["face_name"]
-            id = f"{label}-{rand_id}"
 
             if request_data.get("cropped"):
                 thumbnail = request_data["image"]
@@ -376,7 +369,9 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
             # write face to library
             folder = os.path.join(FACE_DIR, label)
-            file = os.path.join(folder, f"{id}.webp")
+            file = os.path.join(
+                folder, f"{label}_{datetime.datetime.now().timestamp()}.webp"
+            )
             os.makedirs(folder, exist_ok=True)
 
             # save face image

frigate/data_processing/types.py

@@ -7,7 +7,9 @@ from multiprocessing.sharedctypes import Synchronized
 
 class DataProcessorMetrics:
     image_embeddings_speed: Synchronized
+    image_embeddings_eps: Synchronized
     text_embeddings_speed: Synchronized
+    text_embeddings_eps: Synchronized
     face_rec_speed: Synchronized
     face_rec_fps: Synchronized
     alpr_speed: Synchronized
@@ -16,15 +18,15 @@ class DataProcessorMetrics:
     yolov9_lpr_pps: Synchronized
 
     def __init__(self):
-        self.image_embeddings_speed = mp.Value("d", 0.01)
+        self.image_embeddings_speed = mp.Value("d", 0.0)
         self.image_embeddings_eps = mp.Value("d", 0.0)
-        self.text_embeddings_speed = mp.Value("d", 0.01)
+        self.text_embeddings_speed = mp.Value("d", 0.0)
         self.text_embeddings_eps = mp.Value("d", 0.0)
-        self.face_rec_speed = mp.Value("d", 0.01)
+        self.face_rec_speed = mp.Value("d", 0.0)
         self.face_rec_fps = mp.Value("d", 0.0)
-        self.alpr_speed = mp.Value("d", 0.01)
+        self.alpr_speed = mp.Value("d", 0.0)
         self.alpr_pps = mp.Value("d", 0.0)
-        self.yolov9_lpr_speed = mp.Value("d", 0.01)
+        self.yolov9_lpr_speed = mp.Value("d", 0.0)
         self.yolov9_lpr_pps = mp.Value("d", 0.0)
 
 

frigate/detectors/detector_config.py

@@ -126,6 +126,9 @@ class ModelConfig(BaseModel):
         if not self.path or not self.path.startswith("plus://"):
             return
 
+        # ensure that model cache dir exists
+        os.makedirs(MODEL_CACHE_DIR, exist_ok=True)
+
         model_id = self.path[7:]
         self.path = os.path.join(MODEL_CACHE_DIR, model_id)
         model_info_path = f"{self.path}.json"

frigate/embeddings/__init__.py

@@ -235,7 +235,7 @@ class EmbeddingsContext:
             if os.path.isfile(file_path):
                 os.unlink(file_path)
 
-        if len(os.listdir(folder)) == 0:
+        if face != "train" and len(os.listdir(folder)) == 0:
             os.rmdir(folder)
 
         self.requestor.send_data(

frigate/embeddings/embeddings.py

@@ -21,7 +21,7 @@ from frigate.data_processing.types import DataProcessorMetrics
 from frigate.db.sqlitevecq import SqliteVecQueueDatabase
 from frigate.models import Event
 from frigate.types import ModelStatusTypesEnum
-from frigate.util.builtin import EventsPerSecond, serialize
+from frigate.util.builtin import EventsPerSecond, InferenceSpeed, serialize
 from frigate.util.path import get_event_thumbnail_bytes
 
 from .onnx.jina_v1_embedding import JinaV1ImageEmbedding, JinaV1TextEmbedding
@@ -75,8 +75,10 @@ class Embeddings:
         self.metrics = metrics
         self.requestor = InterProcessRequestor()
 
+        self.image_inference_speed = InferenceSpeed(self.metrics.image_embeddings_speed)
         self.image_eps = EventsPerSecond()
         self.image_eps.start()
+        self.text_inference_speed = InferenceSpeed(self.metrics.text_embeddings_speed)
         self.text_eps = EventsPerSecond()
         self.text_eps.start()
 
@@ -183,10 +185,7 @@ class Embeddings:
                 (event_id, serialize(embedding)),
             )
 
-        duration = datetime.datetime.now().timestamp() - start
+        self.image_inference_speed.update(datetime.datetime.now().timestamp() - start)
-        self.metrics.image_embeddings_speed.value = (
-            self.metrics.image_embeddings_speed.value * 9 + duration
-        ) / 10
         self.image_eps.update()
 
         return embedding
@@ -220,9 +219,7 @@ class Embeddings:
             )
 
         duration = datetime.datetime.now().timestamp() - start
-        self.metrics.text_embeddings_speed.value = (
+        self.text_inference_speed.update(duration / len(ids))
-            self.metrics.text_embeddings_speed.value * 9 + (duration / len(ids))
-        ) / 10
 
         return embeddings
 
@@ -241,10 +238,7 @@ class Embeddings:
                 (event_id, serialize(embedding)),
             )
 
-        duration = datetime.datetime.now().timestamp() - start
+        self.text_inference_speed.update(datetime.datetime.now().timestamp() - start)
-        self.metrics.text_embeddings_speed.value = (
-            self.metrics.text_embeddings_speed.value * 9 + duration
-        ) / 10
         self.text_eps.update()
 
         return embedding
@@ -276,10 +270,7 @@ class Embeddings:
                 items,
             )
 
-        duration = datetime.datetime.now().timestamp() - start
+        self.text_inference_speed.update(datetime.datetime.now().timestamp() - start)
-        self.metrics.text_embeddings_speed.value = (
-            self.metrics.text_embeddings_speed.value * 9 + (duration / len(ids))
-        ) / 10
 
         return embeddings
 

frigate/embeddings/onnx/face_embedding.py

@@ -23,10 +23,7 @@ FACENET_INPUT_SIZE = 160
 
 
 class FaceNetEmbedding(BaseEmbedding):
-    def __init__(
+    def __init__(self):
-        self,
-        device: str = "AUTO",
-    ):
         super().__init__(
             model_name="facedet",
             model_file="facenet.tflite",
@@ -34,7 +31,6 @@ class FaceNetEmbedding(BaseEmbedding):
                 "facenet.tflite": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/facenet.tflite",
             },
         )
-        self.device = device
         self.download_path = os.path.join(MODEL_CACHE_DIR, self.model_name)
         self.tokenizer = None
         self.feature_extractor = None
@@ -113,10 +109,7 @@ class FaceNetEmbedding(BaseEmbedding):
 
 
 class ArcfaceEmbedding(BaseEmbedding):
-    def __init__(
+    def __init__(self):
-        self,
-        device: str = "AUTO",
-    ):
         super().__init__(
             model_name="facedet",
             model_file="arcface.onnx",
@@ -124,7 +117,6 @@ class ArcfaceEmbedding(BaseEmbedding):
                 "arcface.onnx": "https://github.com/NickM-27/facenet-onnx/releases/download/v1.0/arcface.onnx",
             },
         )
-        self.device = device
         self.download_path = os.path.join(MODEL_CACHE_DIR, self.model_name)
         self.tokenizer = None
         self.feature_extractor = None
@@ -154,7 +146,7 @@ class ArcfaceEmbedding(BaseEmbedding):
 
             self.runner = ONNXModelRunner(
                 os.path.join(self.download_path, self.model_file),
-                self.device,
+                "GPU",
             )
 
     def _preprocess_inputs(self, raw_inputs):

frigate/review/maintainer.py

@@ -1,5 +1,6 @@
 """Maintain review segments in db."""
 
+import copy
 import json
 import logging
 import os
@@ -119,21 +120,23 @@ class PendingReviewSegment:
             )
 
     def get_data(self, ended: bool) -> dict:
-        return {
+        return copy.deepcopy(
-            ReviewSegment.id.name: self.id,
+            {
-            ReviewSegment.camera.name: self.camera,
+                ReviewSegment.id.name: self.id,
-            ReviewSegment.start_time.name: self.start_time,
+                ReviewSegment.camera.name: self.camera,
-            ReviewSegment.end_time.name: self.last_update if ended else None,
+                ReviewSegment.start_time.name: self.start_time,
-            ReviewSegment.severity.name: self.severity.value,
+                ReviewSegment.end_time.name: self.last_update if ended else None,
-            ReviewSegment.thumb_path.name: self.frame_path,
+                ReviewSegment.severity.name: self.severity.value,
-            ReviewSegment.data.name: {
+                ReviewSegment.thumb_path.name: self.frame_path,
-                "detections": list(set(self.detections.keys())),
+                ReviewSegment.data.name: {
-                "objects": list(set(self.detections.values())),
+                    "detections": list(set(self.detections.keys())),
-                "sub_labels": list(self.sub_labels.values()),
+                    "objects": list(set(self.detections.values())),
-                "zones": self.zones,
+                    "sub_labels": list(self.sub_labels.values()),
-                "audio": list(self.audio),
+                    "zones": self.zones,
-            },
+                    "audio": list(self.audio),
-        }.copy()
+                },
+            }
+        )
 
 
 class ReviewSegmentMaintainer(threading.Thread):

frigate/track/tracked_object.py

@@ -154,7 +154,7 @@ class TrackedObject:
                         "attributes": obj_data["attributes"],
                         "current_estimated_speed": self.current_estimated_speed,
                         "velocity_angle": self.velocity_angle,
-                        "path_data": self.path_data,
+                        "path_data": self.path_data.copy(),
                         "recognized_license_plate": obj_data.get(
                             "recognized_license_plate"
                         ),
@@ -378,7 +378,7 @@ class TrackedObject:
             "current_estimated_speed": self.current_estimated_speed,
             "average_estimated_speed": self.average_estimated_speed,
             "velocity_angle": self.velocity_angle,
-            "path_data": self.path_data,
+            "path_data": self.path_data.copy(),
             "recognized_license_plate": self.obj_data.get("recognized_license_plate"),
         }
 

frigate/util/builtin.py

@@ -11,6 +11,7 @@ import shlex
 import struct
 import urllib.parse
 from collections.abc import Mapping
+from multiprocessing.sharedctypes import Synchronized
 from pathlib import Path
 from typing import Any, Optional, Tuple, Union
 from zoneinfo import ZoneInfoNotFoundError
@@ -26,16 +27,16 @@ logger = logging.getLogger(__name__)
 
 
 class EventsPerSecond:
-    def __init__(self, max_events=1000, last_n_seconds=10):
+    def __init__(self, max_events=1000, last_n_seconds=10) -> None:
         self._start = None
         self._max_events = max_events
         self._last_n_seconds = last_n_seconds
         self._timestamps = []
 
-    def start(self):
+    def start(self) -> None:
         self._start = datetime.datetime.now().timestamp()
 
-    def update(self):
+    def update(self) -> None:
         now = datetime.datetime.now().timestamp()
         if self._start is None:
             self._start = now
@@ -45,7 +46,7 @@ class EventsPerSecond:
             self._timestamps = self._timestamps[(1 - self._max_events) :]
         self.expire_timestamps(now)
 
-    def eps(self):
+    def eps(self) -> float:
         now = datetime.datetime.now().timestamp()
         if self._start is None:
             self._start = now
@@ -58,12 +59,29 @@ class EventsPerSecond:
         return len(self._timestamps) / seconds
 
     # remove aged out timestamps
-    def expire_timestamps(self, now):
+    def expire_timestamps(self, now: float) -> None:
         threshold = now - self._last_n_seconds
         while self._timestamps and self._timestamps[0] < threshold:
             del self._timestamps[0]
 
 
+class InferenceSpeed:
+    def __init__(self, metric: Synchronized) -> None:
+        self.__metric = metric
+        self.__initialized = False
+
+    def update(self, inference_time: float) -> None:
+        if not self.__initialized:
+            self.__metric.value = inference_time
+            self.__initialized = True
+            return
+
+        self.__metric.value = (self.__metric.value * 9 + inference_time) / 10
+
+    def current(self) -> float:
+        return self.__metric.value
+
+
 def deep_merge(dct1: dict, dct2: dict, override=False, merge_lists=False) -> dict:
     """
     :param dct1: First dict to merge

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

@@ -8,14 +8,16 @@
     "subLabelScore": "Sub Label Score",
     "scoreInfo": "The sub label score is the weighted score for all of the recognized face confidences, so this may differ from the score shown on the snapshot.",
     "face": "Face Details",
-    "faceDesc": "Details for the face and associated object",
+    "faceDesc": "Details of the tracked object that generated this face",
-    "timestamp": "Timestamp"
+    "timestamp": "Timestamp",
+    "unknown": "Unknown"
   },
   "documentTitle": "Face Library - Frigate",
   "uploadFaceImage": {
     "title": "Upload Face Image",
     "desc": "Upload an image to scan for faces and include for {{pageToggle}}"
   },
+  "collections": "Collections",
   "createFaceLibrary": {
     "title": "Create Collection",
     "desc": "Create a new collection",
@@ -25,7 +27,10 @@
   "steps": {
     "faceName": "Enter Face Name",
     "uploadFace": "Upload Face Image",
-    "nextSteps": "Next Steps"
+    "nextSteps": "Next Steps",
+    "description": {
+      "uploadFace": "Upload an image of {{name}} that shows their face from a front-facing angle. The image does not need to be cropped to just their face."
+    }
   },
   "train": {
     "title": "Train",
@@ -38,12 +43,17 @@
     "title": "Delete Name",
     "desc": "Are you sure you want to delete the collection {{name}}? This will permanently delete all associated faces."
   },
+  "deleteFaceAttempts": {
+    "title": "Delete Faces",
+    "desc_one": "Are you sure you want to delete {{count}} face? This action cannot be undone.",
+    "desc_other": "Are you sure you want to delete {{count}} faces? This action cannot be undone."
+  },
   "renameFace": {
     "title": "Rename Face",
     "desc": "Enter a new name for {{name}}"
   },
   "button": {
-    "deleteFaceAttempts": "Delete Face Attempts",
+    "deleteFaceAttempts": "Delete Faces",
     "addFace": "Add Face",
     "renameFace": "Rename Face",
     "deleteFace": "Delete Face",

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

@@ -84,6 +84,7 @@
   },
   "classification": {
     "title": "Classification Settings",
+    "unsavedChanges": "Unsaved Classification settings changes",
     "birdClassification": {
       "title": "Bird Classification",
       "desc": "Bird classification identifies known birds using a quantized Tensorflow model. When a known bird is recognized, its common name will be added as a sub_label. This information is included in the UI, filters, as well as in notifications."
@@ -168,11 +169,12 @@
         "notSelectDetections": "All {{detectionsLabels}} objects detected in {{zone}} on {{cameraName}} not categorized as Alerts will be shown as Detections regardless of which zone they are in.",
         "regardlessOfZoneObjectDetectionsTips": "All {{detectionsLabels}} objects not categorized on {{cameraName}} will be shown as Detections regardless of which zone they are in."
       },
+      "unsavedChanges": "Unsaved Review Classification settings for {{camera}}",
       "selectAlertsZones": "Select zones for Alerts",
       "selectDetectionsZones": "Select zones for Detections",
       "limitDetections": "Limit detections to specific zones",
       "toast": {
-        "success": "Review classification configuration has been saved. Restart Frigate to apply changes."
+        "success": "Review Classification configuration has been saved. Restart Frigate to apply changes."
       }
     }
   },
@@ -338,6 +340,7 @@
   },
   "motionDetectionTuner": {
     "title": "Motion Detection Tuner",
+    "unsavedChanges": "Unsaved Motion Tuner changes ({{camera}})",
     "desc": {
       "title": "Frigate uses motion detection as a first line check to see if there is anything happening in the frame worth checking with object detection.",
       "documentation": "Read the Motion Tuning Guide"
@@ -527,6 +530,8 @@
     "registerDevice": "Register This Device",
     "unregisterDevice": "Unregister This Device",
     "sendTestNotification": "Send a test notification",
+    "unsavedRegistrations": "Unsaved Notification registrations",
+    "unsavedChanges": "Unsaved Notification changes",
     "active": "Notifications Active",
     "suspended": "Notifications suspended {{time}}",
     "suspendTime": {
@@ -587,6 +592,7 @@
       "loadingAvailableModels": "Loading available models…",
       "modelSelect": "Your available models on Frigate+ can be selected here. Note that only models compatible with your current detector configuration can be selected."
     },
+    "unsavedChanges": "Unsaved Frigate+ settings changes",
     "restart_required": "Restart required (Frigate+ model changed)",
     "toast": {
       "success": "Frigate+ settings have been saved. Restart Frigate to apply changes.",

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

@@ -128,13 +128,18 @@ export default function CreateFaceWizardDialog({
           </TextEntry>
         )}
         {step == 1 && (
-          <ImageEntry onSave={onUploadImage}>
+          <>
-            <div className="flex justify-end py-2">
+            <div className="px-8 py-2 text-center text-sm text-secondary-foreground">
-              <Button variant="select" type="submit">
+              {t("steps.description.uploadFace", { name })}
-                {t("button.next", { ns: "common" })}
-              </Button>
             </div>
-          </ImageEntry>
+            <ImageEntry onSave={onUploadImage}>
+              <div className="flex justify-end py-2">
+                <Button variant="select" type="submit">
+                  {t("button.next", { ns: "common" })}
+                </Button>
+              </div>
+            </ImageEntry>
+          </>
         )}
         {step == 2 && (
           <div className="mt-2">

web/src/components/player/PreviewPlayer.tsx

@@ -23,6 +23,7 @@ import {
 import { useTranslation } from "react-i18next";
 
 type PreviewPlayerProps = {
+  previewRef?: (ref: HTMLDivElement | null) => void;
   className?: string;
   camera: string;
   timeRange: TimeRange;
@@ -30,16 +31,19 @@ type PreviewPlayerProps = {
   startTime?: number;
   isScrubbing: boolean;
   forceAspect?: number;
+  isVisible?: boolean;
   onControllerReady: (controller: PreviewController) => void;
   onClick?: () => void;
 };
 export default function PreviewPlayer({
+  previewRef,
   className,
   camera,
   timeRange,
   cameraPreviews,
   startTime,
   isScrubbing,
+  isVisible = true,
   onControllerReady,
   onClick,
 }: PreviewPlayerProps) {
@@ -54,6 +58,7 @@ export default function PreviewPlayer({
   if (currentPreview) {
     return (
       <PreviewVideoPlayer
+        visibilityRef={previewRef}
         className={className}
         camera={camera}
         timeRange={timeRange}
@@ -61,6 +66,7 @@ export default function PreviewPlayer({
         initialPreview={currentPreview}
         startTime={startTime}
         isScrubbing={isScrubbing}
+        isVisible={isVisible}
         currentHourFrame={currentHourFrame}
         onControllerReady={onControllerReady}
         onClick={onClick}
@@ -110,6 +116,7 @@ export abstract class PreviewController {
 }
 
 type PreviewVideoPlayerProps = {
+  visibilityRef?: (ref: HTMLDivElement | null) => void;
   className?: string;
   camera: string;
   timeRange: TimeRange;
@@ -117,12 +124,14 @@ type PreviewVideoPlayerProps = {
   initialPreview?: Preview;
   startTime?: number;
   isScrubbing: boolean;
+  isVisible: boolean;
   currentHourFrame?: string;
   onControllerReady: (controller: PreviewVideoController) => void;
   onClick?: () => void;
   setCurrentHourFrame: (src: string | undefined) => void;
 };
 function PreviewVideoPlayer({
+  visibilityRef,
   className,
   camera,
   timeRange,
@@ -130,6 +139,7 @@ function PreviewVideoPlayer({
   initialPreview,
   startTime,
   isScrubbing,
+  isVisible,
   currentHourFrame,
   onControllerReady,
   onClick,
@@ -267,11 +277,13 @@ function PreviewVideoPlayer({
 
   return (
     <div
+      ref={visibilityRef}
       className={cn(
         "relative flex w-full justify-center overflow-hidden rounded-lg bg-black md:rounded-2xl",
         onClick && "cursor-pointer",
         className,
       )}
+      data-camera={camera}
       onClick={onClick}
     >
       <img
@@ -286,45 +298,48 @@ function PreviewVideoPlayer({
           previewRef.current?.load();
         }}
       />
-      <video
+      {isVisible && (
-        ref={previewRef}
+        <video
-        className={`absolute size-full ${currentHourFrame ? "invisible" : "visible"}`}
+          ref={previewRef}
-        preload="auto"
+          className={`absolute size-full ${currentHourFrame ? "invisible" : "visible"}`}
-        autoPlay
+          preload="auto"
-        playsInline
+          autoPlay
-        muted
+          playsInline
-        disableRemotePlayback
+          muted
-        onSeeked={onPreviewSeeked}
+          disableRemotePlayback
-        onLoadedData={() => {
+          onSeeked={onPreviewSeeked}
-          if (firstLoad) {
+          onLoadedData={() => {
-            setFirstLoad(false);
+            if (firstLoad) {
-          }
+              setFirstLoad(false);
-
-          if (controller) {
-            controller.previewReady();
-          } else {
-            previewRef.current?.pause();
-          }
-
-          if (previewRef.current) {
-            setVideoSize([
-              previewRef.current.videoWidth,
-              previewRef.current.videoHeight,
-            ]);
-
-            if (startTime && currentPreview) {
-              previewRef.current.currentTime = startTime - currentPreview.start;
             }
-          }
+
-        }}
+            if (controller) {
-      >
+              controller.previewReady();
-        {currentPreview != undefined && (
+            } else {
-          <source
+              previewRef.current?.pause();
-            src={`${baseUrl}${currentPreview.src.substring(1)}`}
+            }
-            type={currentPreview.type}
+
-          />
+            if (previewRef.current) {
-        )}
+              setVideoSize([
-      </video>
+                previewRef.current.videoWidth,
+                previewRef.current.videoHeight,
+              ]);
+
+              if (startTime && currentPreview) {
+                previewRef.current.currentTime =
+                  startTime - currentPreview.start;
+              }
+            }
+          }}
+        >
+          {currentPreview != undefined && (
+            <source
+              src={`${baseUrl}${currentPreview.src.substring(1)}`}
+              type={currentPreview.type}
+            />
+          )}
+        </video>
+      )}
       {cameraPreviews && !currentPreview && (
         <div className="absolute inset-0 flex items-center justify-center rounded-lg bg-background_alt text-primary dark:bg-black md:rounded-2xl">
           {t("noPreviewFoundFor", { camera: camera.replaceAll("_", " ") })}

web/src/pages/ConfigEditor.tsx

@@ -143,6 +143,12 @@ function ConfigEditor() {
         scrollBeyondLastLine: false,
         theme: (systemTheme || theme) == "dark" ? "vs-dark" : "vs-light",
       });
+      editorRef.current?.addCommand(
+        monaco.KeyMod.CtrlCmd | monaco.KeyCode.KeyS,
+        () => {
+          onHandleSaveConfig("saveonly");
+        },
+      );
     } else if (editorRef.current) {
       editorRef.current.setModel(modelRef.current);
     }
@@ -158,7 +164,7 @@ function ConfigEditor() {
       }
       schemaConfiguredRef.current = false;
     };
-  }, [config, apiHost, systemTheme, theme]);
+  }, [config, apiHost, systemTheme, theme, onHandleSaveConfig]);
 
   // monitoring state
 

web/src/pages/FaceLibrary.tsx

@@ -6,7 +6,17 @@ import CreateFaceWizardDialog from "@/components/overlay/detail/FaceCreateWizard
 import TextEntryDialog from "@/components/overlay/dialog/TextEntryDialog";
 import UploadImageDialog from "@/components/overlay/dialog/UploadImageDialog";
 import FaceSelectionDialog from "@/components/overlay/FaceSelectionDialog";
-import { Button } from "@/components/ui/button";
+import { Button, buttonVariants } from "@/components/ui/button";
+import {
+  AlertDialog,
+  AlertDialogAction,
+  AlertDialogCancel,
+  AlertDialogContent,
+  AlertDialogDescription,
+  AlertDialogFooter,
+  AlertDialogHeader,
+  AlertDialogTitle,
+} from "@/components/ui/alert-dialog";
 import {
   Dialog,
   DialogContent,
@@ -44,7 +54,7 @@ import { TooltipPortal } from "@radix-ui/react-tooltip";
 import axios from "axios";
 import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { isDesktop, isMobile } from "react-device-detect";
-import { useTranslation } from "react-i18next";
+import { Trans, useTranslation } from "react-i18next";
 import {
   LuFolderCheck,
   LuImagePlus,
@@ -165,6 +175,11 @@ export default function FaceLibrary() {
     [selectedFaces, setSelectedFaces],
   );
 
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState<{
+    name: string;
+    ids: string[];
+  } | null>(null);
+
   const onDelete = useCallback(
     (name: string, ids: string[], isName: boolean = false) => {
       axios
@@ -191,7 +206,7 @@ export default function FaceLibrary() {
 
             if (faceImages.length == 1) {
               // face has been deleted
-              setPageToggle("");
+              setPageToggle("train");
             }
 
             refreshFaces();
@@ -244,29 +259,32 @@ export default function FaceLibrary() {
 
   // keyboard
 
-  useKeyboardListener(
+  useKeyboardListener(["a", "Escape"], (key, modifiers) => {
-    page === "train" ? ["a", "Escape"] : [],
+    if (modifiers.repeat || !modifiers.down) {
-    (key, modifiers) => {
+      return;
-      if (modifiers.repeat || !modifiers.down) {
+    }
-        return;
-      }
 
-      switch (key) {
+    switch (key) {
-        case "a":
+      case "a":
-          if (modifiers.ctrl) {
+        if (modifiers.ctrl) {
-            if (selectedFaces.length) {
+          if (selectedFaces.length) {
-              setSelectedFaces([]);
+            setSelectedFaces([]);
-            } else {
+          } else {
-              setSelectedFaces([...trainImages]);
+            setSelectedFaces([
-            }
+              ...(pageToggle === "train" ? trainImages : faceImages),
+            ]);
           }
-          break;
+        }
-        case "Escape":
+        break;
-          setSelectedFaces([]);
+      case "Escape":
-          break;
+        setSelectedFaces([]);
-      }
+        break;
-    },
+    }
-  );
+  });
+
+  useEffect(() => {
+    setSelectedFaces([]);
+  }, [pageToggle]);
 
   if (!config) {
     return <ActivityIndicator />;
@@ -276,6 +294,41 @@ export default function FaceLibrary() {
     <div className="flex size-full flex-col p-2">
       <Toaster />
 
+      <AlertDialog
+        open={!!deleteDialogOpen}
+        onOpenChange={() => setDeleteDialogOpen(null)}
+      >
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>{t("deleteFaceAttempts.title")}</AlertDialogTitle>
+          </AlertDialogHeader>
+          <AlertDialogDescription>
+            <Trans
+              ns="views/faceLibrary"
+              values={{ count: deleteDialogOpen?.ids.length }}
+            >
+              deleteFaceAttempts.desc
+            </Trans>
+          </AlertDialogDescription>
+          <AlertDialogFooter>
+            <AlertDialogCancel>
+              {t("button.cancel", { ns: "common" })}
+            </AlertDialogCancel>
+            <AlertDialogAction
+              className={buttonVariants({ variant: "destructive" })}
+              onClick={() => {
+                if (deleteDialogOpen) {
+                  onDelete(deleteDialogOpen.name, deleteDialogOpen.ids);
+                  setDeleteDialogOpen(null);
+                }
+              }}
+            >
+              {t("button.delete", { ns: "common" })}
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
+
       <UploadImageDialog
         open={upload}
         title={t("uploadFaceImage.title")}
@@ -314,7 +367,9 @@ export default function FaceLibrary() {
             </div>
             <Button
               className="flex gap-2"
-              onClick={() => onDelete("train", selectedFaces)}
+              onClick={() =>
+                setDeleteDialogOpen({ name: pageToggle, ids: selectedFaces })
+              }
             >
               <LuTrash2 className="size-7 rounded-md p-1 text-secondary-foreground" />
               {isDesktop && t("button.deleteFaceAttempts")}
@@ -335,7 +390,13 @@ export default function FaceLibrary() {
           </div>
         )}
       </div>
-      {pageToggle &&
+      {pageToggle && faceImages.length === 0 && pageToggle !== "train" ? (
+        <div className="absolute left-1/2 top-1/2 flex -translate-x-1/2 -translate-y-1/2 flex-col items-center justify-center text-center">
+          <LuFolderCheck className="size-16" />
+          No faces available
+        </div>
+      ) : (
+        pageToggle &&
         (pageToggle == "train" ? (
           <TrainingGrid
             config={config}
@@ -349,9 +410,12 @@ export default function FaceLibrary() {
           <FaceGrid
             faceImages={faceImages}
             pageToggle={pageToggle}
+            selectedFaces={selectedFaces}
+            onClickFaces={onClickFaces}
             onDelete={onDelete}
           />
-        ))}
+        ))
+      )}
     </div>
   );
 }
@@ -443,7 +507,7 @@ function LibrarySelector({
       <DropdownMenu>
         <DropdownMenuTrigger asChild>
           <Button className="flex justify-between smart-capitalize">
-            {pageToggle || t("selectFace")}
+            {pageToggle == "train" ? t("train.title") : pageToggle}
             <span className="ml-2 text-primary-variant">
               ({(pageToggle && faceData?.[pageToggle]?.length) || 0})
             </span>
@@ -467,7 +531,7 @@ function LibrarySelector({
             <>
               <DropdownMenuSeparator />
               <div className="mb-1 ml-1.5 text-xs text-secondary-foreground">
-                Collections
+                {t("collections")}
               </div>
             </>
           )}
@@ -644,7 +708,7 @@ function TrainingGrid({
           <div className="flex flex-col gap-1.5">
             <div className="text-sm text-primary/40">{t("details.person")}</div>
             <div className="text-sm smart-capitalize">
-              {selectedEvent?.sub_label ?? "Unknown"}
+              {selectedEvent?.sub_label ?? t("details.unknown")}
             </div>
           </div>
           {selectedEvent?.data.sub_label_score && (
@@ -793,7 +857,7 @@ function FaceAttemptGroup({
           Person
           {event?.sub_label
             ? `: ${event.sub_label} (${Math.round((event.data.sub_label_score || 0) * 100)}%)`
-            : ": Unknown"}
+            : ": " + t("details.unknown")}
         </div>
         {event && (
           <Tooltip>
@@ -968,7 +1032,9 @@ function FaceAttempt({
         <div className="select-none p-2">
           <div className="flex w-full flex-row items-center justify-between gap-2">
             <div className="flex flex-col items-start text-xs text-primary-variant">
-              <div className="smart-capitalize">{data.name}</div>
+              <div className="smart-capitalize">
+                {data.name == "unknown" ? t("details.unknown") : data.name}
+              </div>
               <div
                 className={cn(
                   "",
@@ -1007,16 +1073,36 @@ function FaceAttempt({
 type FaceGridProps = {
   faceImages: string[];
   pageToggle: string;
+  selectedFaces: string[];
+  onClickFaces: (images: string[], ctrl: boolean) => void;
   onDelete: (name: string, ids: string[]) => void;
 };
-function FaceGrid({ faceImages, pageToggle, onDelete }: FaceGridProps) {
+function FaceGrid({
-  const sortedFaces = useMemo(() => faceImages.sort().reverse(), [faceImages]);
+  faceImages,
+  pageToggle,
+  selectedFaces,
+  onClickFaces,
+  onDelete,
+}: FaceGridProps) {
+  const sortedFaces = useMemo(
+    () => (faceImages || []).sort().reverse(),
+    [faceImages],
+  );
+
+  if (sortedFaces.length === 0) {
+    return (
+      <div className="absolute left-1/2 top-1/2 flex -translate-x-1/2 -translate-y-1/2 flex-col items-center justify-center text-center">
+        <LuFolderCheck className="size-16" />
+        No faces available
+      </div>
+    );
+  }
 
   return (
     <div
       className={cn(
-        "scrollbar-container gap-2 overflow-y-scroll",
+        "scrollbar-container gap-2 overflow-y-scroll p-1",
-        isDesktop ? "flex flex-wrap" : "grid grid-cols-2",
+        isDesktop ? "flex flex-wrap" : "grid grid-cols-2 md:grid-cols-4",
       )}
     >
       {sortedFaces.map((image: string) => (
@@ -1024,6 +1110,8 @@ function FaceGrid({ faceImages, pageToggle, onDelete }: FaceGridProps) {
           key={image}
           name={pageToggle}
           image={image}
+          selected={selectedFaces.includes(image)}
+          onClickFaces={onClickFaces}
           onDelete={onDelete}
         />
       ))}
@@ -1034,22 +1122,44 @@ function FaceGrid({ faceImages, pageToggle, onDelete }: FaceGridProps) {
 type FaceImageProps = {
   name: string;
   image: string;
+  selected: boolean;
+  onClickFaces: (images: string[], ctrl: boolean) => void;
   onDelete: (name: string, ids: string[]) => void;
 };
-function FaceImage({ name, image, onDelete }: FaceImageProps) {
+function FaceImage({
+  name,
+  image,
+  selected,
+  onClickFaces,
+  onDelete,
+}: FaceImageProps) {
   const { t } = useTranslation(["views/faceLibrary"]);
 
   return (
-    <div className="relative flex flex-col rounded-lg">
+    <div
+      className={cn(
+        "flex cursor-pointer flex-col gap-2 rounded-lg bg-card outline outline-[3px]",
+        selected
+          ? "shadow-selected outline-selected"
+          : "outline-transparent duration-500",
+      )}
+      onClick={(e) => {
+        e.stopPropagation();
+        onClickFaces([image], e.ctrlKey || e.metaKey);
+      }}
+    >
       <div
         className={cn(
-          "w-full overflow-hidden rounded-t-lg *:text-card-foreground",
+          "w-full overflow-hidden p-2 *:text-card-foreground",
           isMobile && "flex justify-center",
         )}
       >
-        <img className="h-40" src={`${baseUrl}clips/faces/${name}/${image}`} />
+        <img
+          className="h-40 rounded-lg"
+          src={`${baseUrl}clips/faces/${name}/${image}`}
+        />
       </div>
-      <div className="rounded-b-lg bg-card p-2">
+      <div className="rounded-b-lg bg-card p-3">
         <div className="flex w-full flex-row items-center justify-between gap-2">
           <div className="flex flex-col items-start text-xs text-primary-variant">
             <div className="smart-capitalize">{name}</div>
@@ -1059,7 +1169,10 @@ function FaceImage({ name, image, onDelete }: FaceImageProps) {
               <TooltipTrigger>
                 <LuTrash2
                   className="size-5 cursor-pointer text-primary-variant hover:text-primary"
-                  onClick={() => onDelete(name, [image])}
+                  onClick={(e) => {
+                    e.stopPropagation();
+                    onDelete(name, [image]);
+                  }}
                 />
               </TooltipTrigger>
               <TooltipContent>{t("button.deleteFaceAttempts")}</TooltipContent>

web/src/views/recording/RecordingView.tsx

@@ -385,6 +385,55 @@ export function RecordingView({
     // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [previewRowRef.current?.scrollWidth, previewRowRef.current?.scrollHeight]);
 
+  // visibility listener for lazy loading
+
+  const [visiblePreviews, setVisiblePreviews] = useState<string[]>([]);
+  const visiblePreviewObserver = useRef<IntersectionObserver | null>(null);
+  useEffect(() => {
+    const visibleCameras = new Set<string>();
+    visiblePreviewObserver.current = new IntersectionObserver(
+      (entries) => {
+        entries.forEach((entry) => {
+          const camera = (entry.target as HTMLElement).dataset.camera;
+
+          if (!camera) {
+            return;
+          }
+
+          if (entry.isIntersecting) {
+            visibleCameras.add(camera);
+          } else {
+            visibleCameras.delete(camera);
+          }
+
+          setVisiblePreviews([...visibleCameras]);
+        });
+      },
+      { threshold: 0.1 },
+    );
+
+    return () => {
+      visiblePreviewObserver.current?.disconnect();
+    };
+  }, []);
+
+  const previewRef = useCallback(
+    (node: HTMLElement | null) => {
+      if (!visiblePreviewObserver.current) {
+        return;
+      }
+
+      try {
+        if (node) visiblePreviewObserver.current.observe(node);
+      } catch (e) {
+        // no op
+      }
+    },
+    // we need to listen on the value of the ref
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+    [visiblePreviewObserver.current],
+  );
+
   return (
     <div ref={contentRef} className="flex size-full flex-col pt-2">
       <Toaster closeButton={true} />
@@ -631,12 +680,14 @@ export function RecordingView({
                       }}
                     >
                       <PreviewPlayer
+                        previewRef={previewRef}
                         className="size-full"
                         camera={cam}
                         timeRange={currentTimeRange}
                         cameraPreviews={allPreviews ?? []}
                         startTime={startTime}
                         isScrubbing={scrubbing}
+                        isVisible={visiblePreviews.includes(cam)}
                         onControllerReady={(controller) => {
                           previewRefs.current[cam] = controller;
                           controller.scrubToTimestamp(startTime);

web/src/views/settings/CameraSettingsView.tsx

@@ -230,7 +230,9 @@ export default function CameraSettingsView({
     if (changedValue) {
       addMessage(
         "camera_settings",
-        `Unsaved review classification settings for ${capitalizeFirstLetter(selectedCamera)}`,
+        t("camera.reviewClassification.unsavedChanges", {
+          camera: selectedCamera,
+        }),
         undefined,
         `review_classification_settings_${selectedCamera}`,
       );

web/src/views/settings/ClassificationSettingsView.tsx

@@ -220,7 +220,7 @@ export default function ClassificationSettingsView({
     if (changedValue) {
       addMessage(
         "search_settings",
-        `Unsaved Classification settings changes`,
+        t("classification.unsavedChanges"),
         undefined,
         "search_settings",
       );

web/src/views/settings/FrigatePlusSettingsView.tsx

@@ -176,7 +176,7 @@ export default function FrigatePlusSettingsView({
     if (changedValue) {
       addMessage(
         "plus_settings",
-        `Unsaved Frigate+ settings changes`,
+        t("frigatePlus.unsavedChanges"),
         undefined,
         "plus_settings",
       );

web/src/views/settings/MotionTunerView.tsx

@@ -167,7 +167,7 @@ export default function MotionTunerView({
     if (changedValue) {
       addMessage(
         "motion_tuner",
-        `Unsaved motion tuner changes (${selectedCamera})`,
+        t("motionDetectionTuner.unsavedChanges", { camera: selectedCamera }),
         undefined,
         `motion_tuner_${selectedCamera}`,
       );

web/src/views/settings/NotificationsSettingsView.tsx

@@ -105,7 +105,7 @@ export default function NotificationView({
     if (changedValue) {
       addMessage(
         "notification_settings",
-        `Unsaved notification settings`,
+        t("notification.unsavedChanges"),
         undefined,
         `notification_settings`,
       );
@@ -128,7 +128,7 @@ export default function NotificationView({
       if (registration) {
         addMessage(
           "notification_settings",
-          "Unsaved Notification Registrations",
+          t("notification.unsavedRegistrations"),
           undefined,
           "registration",
         );