Refactor Birdseye activity types as composable booleans (#23940)

* Add combined motion and object Birdseye mode

Add a motion_objects mode that keeps Birdseye active when motion is detected or a confirmed tracked object is present, including stationary objects.

Wire the mode through configuration, runtime commands, API schemas, documentation, and UI labels. Exclude false-positive trackers and add regression coverage for Birdseye activation and MQTT validation.

* Refactor Birdseye activity types as booleans

Replace combination-specific Birdseye modes with composable boolean activity types for motion, active objects, stationary objects, and continuous display.

Preserve legacy single-mode configuration and MQTT inputs, support canonical comma-separated MQTT combinations, and allow scalar YAML values to be replaced by nested settings through the config API.

* Preserve OpenVINO config translations

Regenerate the configuration translations with the OpenVINO detector schema available so the unrelated production detector labels remain intact.

* Preserve partial Birdseye mode overrides

Allow an empty activity selection with a canonical NONE MQTT state so partial camera and profile overrides can disable inherited flags without failing validation.

Add regression coverage for camera and profile inheritance, document the NONE contract, and keep the generated schema fixture scoped to Birdseye.

* Address Birdseye activity review feedback

Move scalar mode compatibility into the 0.18-1 config migration and reject empty activity selections instead of publishing a NONE state.

Pass activity signals through a frozen dataclass, preserve existing active-object tracker behavior, and require confirmed stationary objects. Revert the generic YAML mutation and cover migration, inheritance, MQTT, and activation regressions.

* Move Birdseye migration to 0.19

Use the 0.19-0 configuration revision for converting scalar Birdseye modes to composable activity flags, and update the migration regression coverage accordingly.

* Remove Birdseye migration test

Drop the dedicated config migration test as requested during review while retaining the 0.19-0 migration implementation.

Makefile

@@ -1,7 +1,7 @@
 default_target: local
 
 COMMIT_HASH := $(shell git log -1 --pretty=format:"%h"|tail -1)
-VERSION = 0.18.0
+VERSION = 0.19.0
 IMAGE_REPO ?= ghcr.io/blakeblackshear/frigate
 GITHUB_REF_NAME ?= $(shell git rev-parse --abbrev-ref HEAD)
 BOARDS= #Initialized empty

docker/main/build_ov_model.py

@@ -1,10 +1,14 @@
 """Convert the default SSDLite MobileNet v2 model to OpenVINO IR.
 
 Replaces the legacy openvino-dev Model Optimizer conversion. The TensorFlow
-frontend converts the Object Detection API frozen graph natively; the four TF
-outputs are then repacked into the single [1, 1, 100, 7] DetectionOutput-style
-tensor that Frigate's OpenVINO detector expects, and the input is flipped to
-BGR to match the legacy reverse_input_channels behavior.
+frontend translates the Object Detection API pre and post processors literally,
+producing per-class NonMaxSuppression, NonZero ops and map loops with data
+dependent shapes that the GPU plugin handles very badly. Both are cut out the
+way ssd_v2_support.json used to do it: the preprocessor is an identity at the
+native 300x300 input, and the postprocessor becomes a single fused
+DetectionOutput. The result is the [1, 1, 100, 7] tensor that Frigate's
+OpenVINO detector expects, with the input flipped to BGR to match the legacy
+reverse_input_channels behavior.
 """
 
 import numpy as np
@@ -12,31 +16,91 @@ import openvino as ov
 from openvino import opset8 as ops
 from openvino.preprocess import PrePostProcessor
 
+MODEL_DIR = "/models/ssdlite_mobilenet_v2_coco_2018_05_09"
+OUTPUT_PATH = "/models/ssdlite_mobilenet_v2.xml"
+INPUT_SHAPE = [1, 300, 300, 3]
+
+# faster_rcnn_box_coder divides the deltas by pipeline.config's y/x/height/width
+# scales of 10/10/5/5, which DetectionOutput expresses as per-prior variances.
+BOX_VARIANCES = np.float32([0.1, 0.1, 0.2, 0.2])
+
 model = ov.convert_model(
-    "/models/ssdlite_mobilenet_v2_coco_2018_05_09/frozen_inference_graph.pb",
-    input=[("image_tensor:0", [1, 300, 300, 3])],
+    f"{MODEL_DIR}/frozen_inference_graph.pb",
+    input=[("image_tensor:0", INPUT_SHAPE)],
 )
 
-# rows of (image_id, class_id, score, xmin, ymin, xmax, ymax)
-boxes = model.output("detection_boxes:0").get_node().input_value(0)
-classes = model.output("detection_classes:0").get_node().input_value(0)
-scores = model.output("detection_scores:0").get_node().input_value(0)
+nodes = {op.get_friendly_name(): op for op in model.get_ordered_ops()}
+parameter = model.get_parameters()[0]
 
-# (ymin,xmin,ymax,xmax) -> (xmin,ymin,xmax,ymax)
-boxes = ops.gather(boxes, [1, 0, 3, 2], 2)
-classes = ops.unsqueeze(classes, 2)
-scores = ops.unsqueeze(scores, 2)
-image_id = ops.multiply(scores, np.float32(0.0))
+preprocessor = nodes["Preprocessor/map/TensorArrayStack/TensorArrayGatherV3"]
+box_deltas = nodes["Postprocessor/Reshape_1"].output(0)
+class_scores = nodes["Postprocessor/convert_scores"].output(0)
+anchors_output = nodes["Postprocessor/Reshape"].output(0)
 
-detections = ops.concat([image_id, classes, scores, boxes], 2)
-detections = ops.unsqueeze(detections, 1)
+# The anchors only depend on the static input shape, so fold them into a
+# constant and drop the generator subgraph with the rest of the postprocessor.
+probe = ov.Core().compile_model(
+    ov.Model([anchors_output, preprocessor.output(0)], [parameter], "probe"), "CPU"
+)
+probe_input = np.random.default_rng(0).integers(0, 255, INPUT_SHAPE, dtype=np.uint8)
+anchors, resized = (out.copy() for out in probe([probe_input]).values())
+
+assert np.allclose(resized, probe_input, atol=1e-3), (
+    "preprocessor is not an identity at 300x300, it cannot be bypassed"
+)
+
+image = ops.convert(parameter, "f32")
+
+for consumer in list(preprocessor.output(0).get_target_inputs()):
+    consumer.replace_source_output(image.output(0))
+
+# (ymin, xmin, ymax, xmax) -> (xmin, ymin, xmax, ymax)
+priors = anchors[:, [1, 0, 3, 2]].astype(np.float32).reshape(-1)
+variances = np.tile(BOX_VARIANCES, len(anchors))
+proposals = ops.constant(np.stack([priors, variances])[np.newaxis])
+
+# (ty, tx, th, tw) -> (dx, dy, dw, dh) for the CENTER_SIZE decode
+box_logits = ops.reshape(ops.gather(box_deltas, [1, 0, 3, 2], 1), [1, -1], False)
+class_preds = ops.reshape(class_scores, [1, -1], False)
+
+detections = ops.detection_output(
+    box_logits,
+    class_preds,
+    proposals,
+    {
+        "background_label_id": 0,
+        "top_k": 100,
+        "keep_top_k": [100],
+        "nms_threshold": 0.6,
+        "confidence_threshold": 0.3,
+        "code_type": "caffe.PriorBoxParameter.CENTER_SIZE",
+        "share_location": True,
+        "variance_encoded_in_target": False,
+        "normalized": True,
+        "clip_before_nms": False,
+        "clip_after_nms": True,
+        "decrease_label_id": False,
+    },
+)
 detections.output(0).get_tensor().set_names({"detection_out"})
 
-model = ov.Model([detections], model.get_parameters(), "ssdlite_mobilenet_v2")
+model = ov.Model([detections], [parameter], "ssdlite_mobilenet_v2")
 
 ppp = PrePostProcessor(model)
 ppp.input().tensor().set_layout(ov.Layout("NHWC"))
 ppp.input().preprocess().reverse_channels()
 model = ppp.build()
 
-ov.save_model(model, "/models/ssdlite_mobilenet_v2.xml", compress_to_fp16=True)
+# Fail the build rather than silently ship the dynamically shaped graph again.
+op_types = [op.get_type_name() for op in model.get_ordered_ops()]
+assert op_types.count("DetectionOutput") == 1, "postprocessor was not fused"
+
+for dynamic_op in ("NonMaxSuppression", "NonZero", "Loop", "TensorIterator"):
+    assert dynamic_op not in op_types, f"{dynamic_op} left in the graph"
+
+output_shape = model.outputs[0].get_partial_shape()
+assert output_shape.is_static and list(output_shape) == [1, 1, 100, 7], (
+    f"unexpected detector output shape {output_shape}"
+)
+
+ov.save_model(model, OUTPUT_PATH, compress_to_fp16=True)

docs/docs/configuration/advanced/reference.md

@@ -251,11 +251,17 @@ birdseye:
   # Optional: Encoding quality of the mpeg1 feed (default: shown below)
   # 1 is the highest quality, and 31 is the lowest. Lower quality feeds utilize less CPU resources.
   quality: 8
-  # Optional: Mode of the view. Available options are: objects, motion, and continuous
-  #   objects - cameras are included if they have had a tracked object within the last 30 seconds
-  #   motion - cameras are included if motion was detected in the last 30 seconds
-  #   continuous - all cameras are included always
-  mode: objects
+  # Optional: Activity types that include cameras in Birdseye (default: shown below)
+  # Multiple activity types can be enabled at the same time.
+  mode:
+    # Optional: All cameras are included always (default: shown below)
+    continuous: False
+    # Optional: Cameras are included if motion was detected in the last 30 seconds (default: shown below)
+    motion: False
+    # Optional: Cameras are included if they have had an active tracked object within the last 30 seconds (default: shown below)
+    objects: True
+    # Optional: Cameras are included while they have a stationary tracked object (default: shown below)
+    stationary_objects: False
   # Optional: Threshold for camera activity to stop showing camera (default: shown below)
   inactivity_threshold: 30
   # Optional: Configure the birdseye layout

docs/docs/configuration/birdseye.md

@@ -18,13 +18,14 @@ Each camera tile in Birdseye is composed from the frames of the stream assigned
 
 ## Birdseye Behavior
 
-### Birdseye Modes
+### Birdseye Activity Types
 
-Birdseye offers different modes to customize which cameras show under which circumstances.
+Birdseye offers independent activity types that control when cameras are shown. Multiple activity types can be enabled together.
 
-- **continuous:** All cameras are always included
-- **motion:** Cameras that have detected motion within the last 30 seconds are included
-- **objects:** Cameras that have tracked an active object within the last 30 seconds are included
+- **continuous:** The camera is always included
+- **motion:** The camera is included when motion was detected within the last 30 seconds
+- **objects:** The camera is included when an active object was tracked within the last 30 seconds
+- **stationary_objects:** The camera is included while a stationary object is tracked
 
 ### Custom Birdseye Icon
 
@@ -39,27 +40,30 @@ To include a camera in Birdseye view only for specific circumstances, or exclude
 
 **Global settings:** Navigate to <NavPath path="Settings > System > Birdseye" /> to configure the default Birdseye behavior for all cameras.
 
-**Per-camera overrides:** Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> to override the mode or disable Birdseye for a specific camera.
+**Per-camera overrides:** Navigate to <NavPath path="Settings > Camera configuration > Birdseye" /> to override the activity types or disable Birdseye for a specific camera.
 
-| Field               | Description                                                   |
-| ------------------- | ------------------------------------------------------------- |
-| **Enable Birdseye** | Whether this camera appears in Birdseye view                  |
-| **Tracking mode**   | When to show the camera: `continuous`, `motion`, or `objects` |
+| Field                  | Description                                                |
+| ---------------------- | ---------------------------------------------------------- |
+| **Enable Birdseye**    | Whether this camera appears in Birdseye view               |
+| **Activity types**     | Conditions that determine when to show the camera          |
 
 </TabItem>
 <TabItem value="yaml">
 
-```yaml {8-10,12-14}
+```yaml {8-11,13-15}
 # Include all cameras by default in Birdseye view
 birdseye:
   enabled: True
-  mode: continuous
+  mode:
+    continuous: True
 
 cameras:
   front:
     # Only include the "front" camera in Birdseye view when objects are detected
     birdseye:
-      mode: objects
+      mode:
+        continuous: False
+        objects: True
   back:
     # Exclude the "back" camera from Birdseye view
     birdseye:

docs/docs/configuration/genai/config.md

@@ -6,6 +6,7 @@ title: Configuring Generative AI
 import ConfigTabs from "@site/src/components/ConfigTabs";
 import TabItem from "@theme/TabItem";
 import NavPath from "@site/src/components/NavPath";
+import FaqItem from "@site/src/components/FaqItem";
 
 ## Configuration
 
@@ -13,6 +14,18 @@ A Generative AI provider can be configured in the global config, which will make
 
 `genai` is a map of named providers. Each key under `genai` is a name you choose, and its value is that provider's settings:
 
+<ConfigTabs>
+<TabItem value="ui">
+
+1. Navigate to <NavPath path="Settings > Enrichments > Generative AI" />.
+   - Click **Add** and enter a **Provider name**. Any name of letters, numbers, hyphens, and underscores is accepted, but it cannot be changed from the UI after the provider is created.
+   - Set **Provider** to the service you are using (e.g., `ollama`)
+   - Set **Base URL**, **API key**, and **Model** as required by that provider
+   - Set **Roles** to the roles this provider should handle.
+
+</TabItem>
+<TabItem value="yaml">
+
 ```yaml
 genai:
   my_provider: # any name you like
@@ -25,6 +38,9 @@ genai:
       - chat
 ```
 
+</TabItem>
+</ConfigTabs>
+
 The examples on this page all use `my_provider`, but the name is arbitrary and is only used to reference the provider elsewhere in the config (for example, `semantic_search.model`).
 
 Each provider handles one or more **roles**: `chat`, `descriptions`, and `embeddings`. A provider handles all three by default, and each role may be assigned to exactly one provider. Define a single provider if you want it to do everything, or split the roles across several providers using the `roles` option.
@@ -43,15 +59,20 @@ Running Generative AI models on CPU is not recommended, as high inference times
 
 ### Recommended Local Models
 
-You must use a vision-capable model with Frigate. The following models are recommended for local deployment:
+You must use a vision-capable model with Frigate. The following models are recommended for local deployment of the `descriptions` and `chat` roles:
 
 | Model      | Notes                                                                                                                                                                |
 | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | `qwen3-vl` | Strong visual and situational understanding, enhanced ability to identify smaller objects and interactions with object.                                              |
-| `qwen3.5`  | Strong situational understanding, but missing DeepStack from qwen3-vl leading to worse performance for identifying objects in people's hand and other small details. |
-| `qwen3.6`  | Strong situational understanding, similar to qwen3-vl                                                                                                                |
+| `qwen3.6`  | Strong situational understanding, but missing DeepStack from qwen3-vl leading to worse performance for identifying objects in people's hand and other small details. |
 | `gemma4`   | Strong situational understanding, sometimes resorts to more vague terms like 'interacts' instead of assigning a specific action.                                     |
 
+The `embeddings` role needs a different kind of model. Text queries are matched against the stored image embeddings, so the model must be trained to place images and text into the same vector space. A chat or description model will still return vectors when asked, but those vectors are not trained for retrieval and text searches will return poor matches with no error to indicate why.
+
+| Model                | Notes                                                                                                                                                               |
+| -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Must be served by llama.cpp started with `--embeddings` and `--mmproj`. |
+
 :::info
 
 Each model is available in multiple parameter sizes (3b, 4b, 8b, etc.). Larger sizes are more capable of complex tasks and understanding of situations, but requires more memory and computational resources. It is recommended to try multiple models and experiment to see which performs best.
@@ -416,3 +437,82 @@ genai:
 
 </TabItem>
 </ConfigTabs>
+
+## FAQ
+
+<FaqItem id="how-do-i-debug-genai-issues" question="How do I debug GenAI issues?">
+
+Frigate's Generative AI features are configured and enabled separately. [Review descriptions and summaries](/configuration/genai/genai_review) live under `review.genai`, and [object descriptions](/configuration/genai/genai_objects) live under `objects.genai`. Configuring a provider on this page does not enable either feature, and enabling one does not enable the other. Decide which of the two is not working, then work through the steps below.
+
+1. Confirm a provider is available and holds the `descriptions` role.
+   - Review descriptions, review summaries, and object descriptions all use the provider that has the `descriptions` role assigned in <NavPath path="Settings > Enrichments > Generative AI > Roles" /> (`genai.<provider>.roles`).
+   - A provider is contacted the first time one of its roles is actually used. A provider holding the `embeddings` role for semantic search is initialized during startup, while a `descriptions` provider is not initialized until the first description is requested, which may be well after boot.
+   - In <NavPath path="Settings > Enrichments > Generative AI" />, use **Refresh models** next to the model field. It queries the provider for its model list and is a quick way to verify that the base URL, API key, and network path between Frigate and your provider are correct.
+
+2. Confirm the feature you expect is actually enabled.
+   - Object descriptions are disabled by default. Turn on <NavPath path="Settings > Global configuration > Objects > GenAI object config > Enable GenAI" /> (`objects.genai.enabled`), either globally or per camera. This is the most common reason custom prompts appear to be ignored while review summaries are still being generated.
+   - Review descriptions are disabled by default. Turn on <NavPath path="Settings > Global configuration > Review > GenAI config > Enable GenAI descriptions" /> (`review.genai.enabled`). Once enabled, alerts are described by default but detections are not, so a detection-only review item will never get a summary unless **Enable GenAI for detections** (`review.genai.detections`) is also on.
+
+3. If object descriptions are never requested, check the filters that skip generation.
+   - <NavPath path="Settings > Global configuration > Objects > GenAI object config > GenAI objects" /> (`objects.genai.objects`) limits generation to specific labels, and **Required zones** (`objects.genai.required_zones`) requires the object to have entered one of those zones. If either is set and does not match, Frigate skips the request silently.
+   - Thumbnails are only collected while an object is moving. Objects that go stationary early contribute fewer frames.
+   - **Use snapshots** (`objects.genai.use_snapshot`) requires snapshots to be enabled for the camera. If the snapshot cannot be read, Frigate logs `Cannot load snapshot for <id>, file not found` and no description is generated.
+   - **Send on end** (`objects.genai.send_triggers.tracked_object_end`) is on by default. If you have turned it off in favor of **Early GenAI trigger** (`objects.genai.send_triggers.after_significant_updates`), descriptions are only requested once that number of updates is reached.
+
+4. Enable debug logs to see exactly what Frigate is doing. Restart Frigate after this change. The next step also requires a restart, so turn both on at the same time to avoid restarting twice.
+
+   ```yaml
+   logger:
+     default: info
+     logs:
+       # highlight-start
+       frigate.genai: debug
+       frigate.data_processing.post.object_descriptions: debug
+       frigate.data_processing.post.review_descriptions: debug
+       # highlight-end
+   ```
+
+5. Save the exact images and prompts that were sent to your provider.
+   - Turn on **Save thumbnails** for the feature you are debugging (`review.genai.debug_save_thumbnails` or `objects.genai.debug_save_thumbnails`). Both features write to `/media/frigate/clips/genai-requests/`, and these files are admin-only.
+   - Review descriptions write `genai-requests/<review_id>/` containing the numbered frames that were sent, plus `prompt.txt` and `response.txt` with the exact prompt and the raw, unparsed model response.
+   - Review summary reports write `genai-requests/<start_ts>-<end_ts>/prompt.txt` and `response.txt`. No images are involved, since a report summarizes existing review descriptions.
+   - Object descriptions write `genai-requests/<event_id>/` containing the numbered thumbnails. The prompt for object descriptions is not written to a file, it is only visible in the debug logs from step 4.
+   - Look at the saved images before blaming the model. If the object is small, blurry, or out of frame, no prompt will fix the result. For object descriptions, consider turning on **Use snapshots** (`objects.genai.use_snapshot`) to send a higher quality image. For review items, consider setting **Review image source** (`review.genai.image_source`) to `recordings` for 480p frames instead of the lower resolution preview frames.
+
+<ConfigTabs>
+<TabItem value="ui">
+
+For review descriptions, navigate to <NavPath path="Settings > Global configuration > Review" /> and set **GenAI config > Save thumbnails** to on.
+
+For object descriptions, navigate to <NavPath path="Settings > Global configuration > Objects" />, expand **GenAI object config**, and set **Save thumbnails** to on.
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+review:
+  genai:
+    enabled: true
+    # highlight-next-line
+    debug_save_thumbnails: true
+
+objects:
+  genai:
+    enabled: true
+    # highlight-next-line
+    debug_save_thumbnails: true
+```
+
+</TabItem>
+</ConfigTabs>
+
+6. Verify the prompt is what you think it is.
+   - Object description prompts are the ones you control directly. A camera-level <NavPath path="Settings > Camera configuration > Objects > GenAI object config > Caption prompt" /> (`objects.genai.prompt`) overrides the global one, and an entry in **Object prompts** (`objects.genai.object_prompts`) for a label overrides both for that label. Only `{label}`, `{sub_label}`, and `{camera}` are substituted.
+   - Review description prompts are built by Frigate and request a structured JSON response, so they are not fully replaceable. The parts you control are <NavPath path="Settings > Global configuration > Review > GenAI config > Activity context prompt" /> (`review.genai.activity_context_prompt`) and **Additional concerns** (`review.genai.additional_concerns`). Keep the activity context prompt general, since overly specific rules will sway the model's threat level scoring.
+
+7. If descriptions are generated but the results are poor or inconsistent, look at the model and the context window.
+   - Empty fields, missing `shortSummary` values, or `Failed to parse review description` errors usually mean the model is not following the requested JSON schema. Smaller models struggle with structured output. Try a larger parameter size or one of the [recommended models](#recommended-local-models).
+   - Frigate calculates how many frames to send from the context size the provider reports. If your server reports a different value than it is actually running with, frames will be truncated or the request will fail. Pin the value by adding `context_size` under <NavPath path="Settings > Enrichments > Generative AI > Provider options" /> (`genai.<provider>.provider_options`), and for Ollama also confirm `options.num_ctx` there matches the context you have configured.
+   - Check **Review Description Speed** and **Object Description Speed** in <NavPath path="System metrics > Enrichments" />. If inference takes tens of seconds, requests will queue behind each other and descriptions will appear to stop. For Ollama, review `OLLAMA_NUM_PARALLEL`, `OLLAMA_MAX_QUEUE`, and `OLLAMA_MAX_LOADED_MODELS` so that concurrent requests from Frigate are handled the way you expect.
+
+</FaqItem>

docs/docs/configuration/genai/objects.md

@@ -113,3 +113,7 @@ Many providers also have a public facing chat interface for their models. Downlo
 - OpenAI - [ChatGPT](https://chatgpt.com)
 - Gemini - [Google AI Studio](https://aistudio.google.com)
 - Ollama - [Open WebUI](https://docs.openwebui.com/)
+
+## Troubleshooting
+
+If descriptions are not being generated, or the generated descriptions are not what you expect, see [How do I debug GenAI issues?](/configuration/genai/genai_config#how-do-i-debug-genai-issues).

docs/docs/configuration/genai/review_summaries.md

@@ -201,3 +201,7 @@ Along with individual review item summaries, Generative AI can also produce a si
 Review reports can be requested via the [API](/integrations/api/generate-review-summary-review-summarize-start-start-ts-end-end-ts-post) by sending a POST request to `/api/review/summarize/start/{start_ts}/end/{end_ts}` with Unix timestamps.
 
 For Home Assistant users, there is a built-in service (`frigate.review_summarize`) that makes it easy to request review reports as part of automations or scripts. This allows you to automatically generate daily summaries, vacation reports, or custom time period reports based on your specific needs.
+
+## Troubleshooting
+
+If summaries are not being generated, or the generated summaries are not what you expect, see [How do I debug GenAI issues?](/configuration/genai/genai_config#how-do-i-debug-genai-issues).

docs/docs/integrations/mqtt.md

@@ -539,20 +539,21 @@ Topic with current state of Birdseye for a camera. Published values are `ON` and
 
 ### `frigate/<camera_name>/birdseye_mode/set`
 
-Topic to set Birdseye mode for a camera. Birdseye offers different modes to customize under which circumstances the camera is shown.
+Topic to set the Birdseye activity types for a camera. Send one uppercase activity type or combine multiple types with commas, for example `MOTION,OBJECTS,STATIONARY_OBJECTS`.
 
-_Note: Changing the value from `CONTINUOUS` -> `MOTION | OBJECTS` will take up to 30 seconds for
+_Note: Changing the value from `CONTINUOUS` to non-continuous activity types will take up to 30 seconds for
 the camera to be removed from the view._
 
-| Command      | Description                                                       |
-| ------------ | ----------------------------------------------------------------- |
-| `CONTINUOUS` | Always included                                                   |
-| `MOTION`     | Show when detected motion within the last 30 seconds are included |
-| `OBJECTS`    | Shown if an active object tracked within the last 30 seconds      |
+| Command              | Description                                                      |
+| -------------------- | ---------------------------------------------------------------- |
+| `CONTINUOUS`         | Always included                                                  |
+| `MOTION`             | Shown if motion was detected within the last 30 seconds          |
+| `OBJECTS`            | Shown if an active object was tracked within the last 30 seconds |
+| `STATIONARY_OBJECTS` | Shown while a stationary object is tracked                       |
 
 ### `frigate/<camera_name>/birdseye_mode/state`
 
-Topic with current state of the Birdseye mode for a camera. Published values are `CONTINUOUS`, `MOTION`, `OBJECTS`.
+Topic with the current Birdseye activity types for a camera. Multiple enabled types are published as a comma-separated value in the order `OBJECTS`, `MOTION`, `STATIONARY_OBJECTS`, `CONTINUOUS`.
 
 ### `frigate/<camera_name>/notifications/set`
 

docs/docs/troubleshooting/common_errors.md

@@ -34,11 +34,15 @@ The detect FFmpeg process exited on its own. This message is only the notificati
 
 </FaqItem>
 
-<FaqItem id="non-monotonically-increasing-dts" question="Application provided invalid, non monotonically increasing dts to muxer">
+<FaqItem id="non-monotonically-increasing-dts" question="Non-monotonic DTS / non monotonically increasing dts to muxer / Queue input is backward in time">
 
-An FFmpeg message meaning the camera sent packets with out-of-order timestamps. Because recordings are copied without re-encoding, FFmpeg cannot fix them, and the segment muxer often splits early, producing one-second segments and a cache backlog. The usual cause is a camera "Smart Codec" / H.264+ / H.265+ mode or a camera clock that jumps.
+These are FFmpeg messages indicating the camera sent packets with out-of-order timestamps, either on the video or the audio stream. Timestamp jitter like this is common with WiFi cameras and restreamed or proxied sources; other causes are a camera "Smart Codec" / H.264+ / H.265+ mode or a camera clock that jumps. A sustained flood of these messages usually precedes the stream stalling and the watchdog restarting FFmpeg.
 
-See [Recordings: segments are only 1 second long](/troubleshooting/recordings#segments-are-only-1-second-long).
+In most cases, the fix is to improve the network, reduce system resource usage, or switch to non-WiFi cameras. In general, WiFi cameras are [not recommended](https://ipcamtalk.com/threads/multiple-cameras-high-bandwidth.77100/#post-861110).
+
+On the video stream, this can affect recordings: because they are copied without re-encoding, FFmpeg cannot fix the timestamps, and the segment muxer often splits early, producing one-second segments and a cache backlog. See [Recordings: segments are only 1 second long](/troubleshooting/recordings#segments-are-only-1-second-long).
+
+On the audio stream, the messages can come from the output's audio encoding. If the audio stream is the problem, it may help to have go2rtc transcode it by adding `#audio=aac` to the camera's go2rtc stream to produce clean timestamps for everything consuming the restream.
 
 </FaqItem>
 

docs/static/frigate-api.yaml

@@ -2872,6 +2872,44 @@ paths:
         - frigateUserAuth: []
       x-required-role: any
       description: '**Access:** Any authenticated user.'
+  /categorized_object_names:
+    get:
+      tags:
+        - App
+      summary: Get known object names by object type
+      description: |-
+        **Access:** Any authenticated user.
+
+        Returns the sub labels and attributes this install can attach,
+            grouped by object type. Unlike /sub_labels, which reflects what has already been
+            detected, this reads the config and model files, so it covers recognized face
+            names, named license plates, custom object classification categories, and the
+            detector attributes of tracked objects.
+      operationId: categorized_object_names_categorized_object_names_get
+      parameters:
+        - name: object_type
+          in: query
+          required: false
+          schema:
+            anyOf:
+              - type: string
+              - type: 'null'
+            title: Object Type
+      responses:
+        '200':
+          description: Successful Response
+          content:
+            application/json:
+              schema: {}
+        '422':
+          description: Validation Error
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/HTTPValidationError'
+      security:
+        - frigateUserAuth: []
+      x-required-role: any
   /audio_labels:
     get:
       tags:

frigate/api/app.py

@@ -31,7 +31,10 @@ from frigate.api.auth import (
     get_allowed_cameras_for_filter,
     require_role,
 )
-from frigate.api.config_util import swap_runtime_config
+from frigate.api.config_util import (
+    publish_camera_section_updates,
+    swap_runtime_config,
+)
 from frigate.api.defs.query.app_query_parameters import AppTimelineHourlyQueryParameters
 from frigate.api.defs.request.app_body import (
     AppConfigSetBody,
@@ -68,6 +71,7 @@ from frigate.util.config import (
     find_config_file,
     redact_credential,
 )
+from frigate.util.object_names import get_categorized_object_names
 from frigate.util.schema import get_config_schema
 from frigate.util.services import (
     get_nvidia_driver_info,
@@ -963,6 +967,17 @@ def config_set(request: Request, body: AppConfigSetBody):
                             body.update_topic, settings
                         )
 
+                        # a config/cameras/* topic publishes camera copies, a
+                        # global topic the global object. FrigateConfig.parse
+                        # folds some global sections down into every camera,
+                        # and workers read both objects, so any such section
+                        # needs its camera copies sent alongside the global
+                        # publish above.
+                        if body.update_topic == "config/birdseye":
+                            publish_camera_section_updates(
+                                request.app, config, CameraConfigUpdateEnum.birdseye
+                            )
+
             return JSONResponse(
                 content=(
                     {
@@ -1299,6 +1314,28 @@ def get_sub_labels(
     return JSONResponse(content=sub_labels)
 
 
+@router.get(
+    "/categorized_object_names",
+    dependencies=[Depends(allow_any_authenticated())],
+    summary="Get known object names by object type",
+    description="""Returns the sub labels and attributes this install can attach,
+    grouped by object type. Unlike /sub_labels, which reflects what has already been
+    detected, this reads the config and model files, so it covers recognized face
+    names, named license plates, custom object classification categories, and the
+    detector attributes of tracked objects.""",
+)
+def categorized_object_names(
+    request: Request,
+    object_type: str | None = None,
+    allowed_cameras: list[str] = Depends(get_allowed_cameras_for_filter),
+):
+    return JSONResponse(
+        content=get_categorized_object_names(
+            request.app.frigate_config, allowed_cameras, object_type
+        )
+    )
+
+
 @router.get("/audio_labels", dependencies=[Depends(allow_any_authenticated())])
 def get_audio_labels():
     labels = load_labels("/audio-labelmap.txt", prefill=521)

frigate/api/auth.py

@@ -83,6 +83,7 @@ def require_admin_by_default():
         "/nvinfo",
         "/labels",
         "/sub_labels",
+        "/categorized_object_names",
         "/plus/models",
         "/recognized_license_plates",
         "/timeline",

frigate/api/chat.py

@@ -50,6 +50,7 @@ from frigate.jobs.vlm_watch import (
     stop_vlm_watch_job,
 )
 from frigate.models import Event
+from frigate.util.object_names import get_categorized_object_names
 
 logger = logging.getLogger(__name__)
 
@@ -539,6 +540,11 @@ async def execute_tool(
     if tool_name == "search_objects":
         return await _execute_search_objects(request, arguments, allowed_cameras)
 
+    if tool_name == "get_categorized_object_names":
+        return JSONResponse(
+            content=_execute_get_categorized_object_names(request, allowed_cameras)
+        )
+
     if tool_name == "find_similar_objects":
         result = await _execute_find_similar_objects(
             request, arguments, allowed_cameras
@@ -717,6 +723,21 @@ async def _execute_set_camera_state(
     return {"success": True, "camera": camera, "feature": feature, "value": value}
 
 
+def _execute_get_categorized_object_names(
+    request: Request,
+    allowed_cameras: list[str],
+) -> dict[str, Any]:
+    names = get_categorized_object_names(request.app.frigate_config, allowed_cameras)
+
+    if not names:
+        return {
+            "names": {},
+            "message": "No names configured; search by label or semantic_query.",
+        }
+
+    return {"names": names}
+
+
 async def _execute_tool_internal(
     tool_name: str,
     arguments: dict[str, Any],
@@ -741,6 +762,8 @@ async def _execute_tool_internal(
         except (json.JSONDecodeError, AttributeError) as e:
             logger.warning(f"Failed to extract tool result: {e}")
             return {"error": "Failed to parse tool result"}
+    elif tool_name == "get_categorized_object_names":
+        return _execute_get_categorized_object_names(request, allowed_cameras)
     elif tool_name == "find_similar_objects":
         return await _execute_find_similar_objects(request, arguments, allowed_cameras)
     elif tool_name == "set_camera_state":
@@ -773,8 +796,8 @@ async def _execute_tool_internal(
     else:
         logger.error(
             "Tool call failed: unknown tool %r. Expected one of: search_objects, find_similar_objects, "
-            "get_live_context, start_camera_watch, stop_camera_watch, get_profile_status, get_recap. "
-            "Arguments received: %s",
+            "get_categorized_object_names, get_live_context, start_camera_watch, stop_camera_watch, "
+            "get_profile_status, get_recap. Arguments received: %s",
             tool_name,
             json.dumps(arguments),
         )

frigate/api/config_util.py

@@ -3,6 +3,30 @@
 from fastapi import FastAPI
 
 from frigate.config import FrigateConfig
+from frigate.config.camera.updater import (
+    CameraConfigUpdateEnum,
+    CameraConfigUpdateTopic,
+)
+
+
+def publish_camera_section_updates(
+    app: FastAPI, config: FrigateConfig, update_type: CameraConfigUpdateEnum
+) -> None:
+    """Broadcast every camera's re-resolved value for a global section.
+
+    Global sections are folded into each camera at parse time and the camera
+    copies are what workers read, so send them rather than leave a worker to
+    guess which cameras were inheriting.
+    """
+    for camera_name, camera_config in config.cameras.items():
+        settings = getattr(camera_config, update_type.name, None)
+
+        if settings is None:
+            continue
+
+        app.config_publisher.publish_update(
+            CameraConfigUpdateTopic(update_type, camera_name), settings
+        )
 
 
 def swap_runtime_config(app: FastAPI, config: FrigateConfig) -> None:
@@ -16,6 +40,10 @@ def swap_runtime_config(app: FastAPI, config: FrigateConfig) -> None:
     camera the user turned off would silently come back on.
     """
     app.frigate_config = config
+
+    if app.config_holder is not None:
+        app.config_holder.set(config)
+
     app.genai_manager.update_config(config)
 
     if app.profile_manager is not None:

frigate/api/fastapi_app.py

@@ -35,6 +35,7 @@ from frigate.comms.event_metadata_updater import (
 )
 from frigate.config import FrigateConfig
 from frigate.config.camera.updater import CameraConfigUpdatePublisher
+from frigate.config.holder import ConfigHolder
 from frigate.config.profile_manager import ProfileManager
 from frigate.debug_replay import DebugReplayManager, debug_replay_auto_stop_watchdog
 from frigate.embeddings import EmbeddingsContext
@@ -74,6 +75,7 @@ def create_fastapi_app(
     dispatcher: Dispatcher | None = None,
     profile_manager: ProfileManager | None = None,
     enforce_default_admin: bool = True,
+    config_holder: ConfigHolder | None = None,
 ):
     logger.info("Starting FastAPI app")
     app = FastAPI(
@@ -162,6 +164,7 @@ def create_fastapi_app(
     app.replay_manager = replay_manager
     app.dispatcher = dispatcher
     app.profile_manager = profile_manager
+    app.config_holder = config_holder
 
     if frigate_config.auth.enabled:
         secret = get_jwt_secret()

frigate/api/media.py

@@ -574,11 +574,11 @@ async def vod_ts(
             Recordings.start_time,
         )
         .where(
-            Recordings.start_time.between(start_ts, end_ts)
-            | Recordings.end_time.between(start_ts, end_ts)
-            | ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
+            Recordings.camera == camera_name,
+            Recordings.start_time >= start_ts - MAX_SEGMENT_DURATION,
+            Recordings.start_time <= end_ts,
+            Recordings.end_time >= start_ts,
         )
-        .where(Recordings.camera == camera_name)
         .order_by(Recordings.start_time.asc())
         .iterator()
     )

frigate/api/record.py

@@ -25,7 +25,7 @@ from frigate.api.defs.query.recordings_query_parameters import (
 )
 from frigate.api.defs.response.generic_response import GenericResponse
 from frigate.api.defs.tags import Tags
-from frigate.const import RECORD_DIR
+from frigate.const import MAX_SEGMENT_DURATION, RECORD_DIR
 from frigate.models import Event, Recordings
 from frigate.util.time import get_dst_transitions
 
@@ -243,6 +243,7 @@ async def recordings(
         )
         .where(
             Recordings.camera == camera_name,
+            Recordings.start_time >= after - MAX_SEGMENT_DURATION,
             Recordings.end_time >= after,
             Recordings.start_time <= before,
         )

frigate/app.py

@@ -30,6 +30,7 @@ from frigate.comms.ws import WebSocketClient
 from frigate.comms.zmq_proxy import ZmqProxy
 from frigate.config.camera.updater import CameraConfigUpdatePublisher
 from frigate.config.config import FrigateConfig
+from frigate.config.holder import ConfigHolder
 from frigate.config.profile_manager import ProfileManager
 from frigate.const import (
     CACHE_DIR,
@@ -122,7 +123,18 @@ class FrigateApp:
         self.processes: dict[str, int] = {}
         self.embeddings: EmbeddingsContext | None = None
         self.profile_manager: ProfileManager | None = None
-        self.config = config
+        self.config_holder = ConfigHolder(config)
+
+    @property
+    def config(self) -> FrigateConfig:
+        """The current config, not the one Frigate booted with.
+
+        Read through the holder so the deferred watchdog factories below build
+        a replacement process from the config as it is now. There is no setter
+        on purpose: a plain attribute would let a caller pin this back to a
+        single object and reintroduce the staleness.
+        """
+        return self.config_holder.config
 
     def ensure_dirs(self) -> None:
         dirs = [
@@ -645,6 +657,7 @@ class FrigateApp:
                     self.replay_manager,
                     self.dispatcher,
                     self.profile_manager,
+                    config_holder=self.config_holder,
                 ),
                 host="127.0.0.1",
                 port=5001,

frigate/comms/dispatcher.py

@@ -11,7 +11,7 @@ from frigate.camera.activity_manager import AudioActivityManager, CameraActivity
 from frigate.comms.base_communicator import Communicator
 from frigate.comms.runtime_state import RuntimeStatePersistence
 from frigate.comms.webpush import WebPushClient
-from frigate.config import BirdseyeModeEnum, FrigateConfig
+from frigate.config import BirdseyeModeConfig, FrigateConfig
 from frigate.config.camera.updater import (
     CameraConfigUpdateEnum,
     CameraConfigUpdatePublisher,
@@ -882,8 +882,9 @@ class Dispatcher:
     def _on_birdseye_mode_command(self, camera_name: str, payload: str) -> None:
         """Callback for birdseye mode topic."""
 
-        if payload not in ["CONTINUOUS", "MOTION", "OBJECTS"]:
-            logger.info(f"Invalid birdseye_mode command: {payload}")
+        mode = BirdseyeModeConfig.from_mqtt_payload(payload)
+        if mode is None:
+            logger.info("Invalid birdseye_mode command: %s", payload)
             return
 
         birdseye_settings = self.config.cameras[camera_name].birdseye
@@ -892,7 +893,7 @@ class Dispatcher:
             logger.info(f"Birdseye mode not enabled for {camera_name}")
             return
 
-        birdseye_settings.mode = BirdseyeModeEnum(payload.lower())
+        birdseye_settings.mode = mode
         logger.info(
             f"Setting birdseye mode for {camera_name} to {birdseye_settings.mode}"
         )
@@ -901,7 +902,9 @@ class Dispatcher:
             CameraConfigUpdateTopic(CameraConfigUpdateEnum.birdseye, camera_name),
             birdseye_settings,
         )
-        self.publish(f"{camera_name}/birdseye_mode/state", payload, retain=True)
+        self.publish(
+            f"{camera_name}/birdseye_mode/state", mode.to_mqtt_payload(), retain=True
+        )
 
     def _on_camera_notification_command(self, camera_name: str, payload: str) -> None:
         """Callback for camera level notifications topic."""

frigate/comms/mqtt.py

@@ -120,7 +120,7 @@ class MqttClient(Communicator):
             self.publish(
                 f"{camera_name}/birdseye_mode/state",
                 (
-                    camera.birdseye.mode.value.upper()
+                    camera.birdseye.mode.to_mqtt_payload()
                     if camera.birdseye.enabled
                     else "OFF"
                 ),

frigate/config/camera/birdseye.py

@@ -1,5 +1,3 @@
-from enum import Enum
-
 from pydantic import BaseModel, Field
 
 from ..base import FrigateBaseModel
@@ -8,22 +6,78 @@ __all__ = [
     "BirdseyeCameraConfig",
     "BirdseyeConfig",
     "BirdseyeLayoutConfig",
-    "BirdseyeModeEnum",
+    "BirdseyeModeConfig",
 ]
 
+BIRDSEYE_ACTIVITY_TYPES = (
+    "objects",
+    "motion",
+    "stationary_objects",
+    "continuous",
+)
 
-class BirdseyeModeEnum(str, Enum):
-    objects = "objects"
-    motion = "motion"
-    continuous = "continuous"
+
+class BirdseyeModeConfig(FrigateBaseModel):
+    continuous: bool = Field(
+        default=False,
+        title="Continuous",
+        description="Always include the camera in Birdseye.",
+    )
+    motion: bool = Field(
+        default=False,
+        title="Motion",
+        description="Include the camera in Birdseye when motion is detected.",
+    )
+    objects: bool = Field(
+        default=False,
+        title="Active objects",
+        description="Include the camera in Birdseye while an active object is tracked.",
+    )
+    stationary_objects: bool = Field(
+        default=False,
+        title="Stationary objects",
+        description="Include the camera in Birdseye while a stationary object is tracked.",
+    )
 
     @classmethod
-    def get_index(cls, type):
-        return list(cls).index(type)
+    def from_mqtt_payload(cls, payload: str) -> "BirdseyeModeConfig | None":
+        """Create mode options from an uppercase MQTT payload."""
+        raw_modes = payload.split(",")
+        if not raw_modes or any(not mode for mode in raw_modes):
+            return None
 
-    @classmethod
-    def get(cls, index):
-        return list(cls)[index]
+        modes = [mode.lower() for mode in raw_modes]
+        if any(
+            raw_mode != mode.upper() or mode not in BIRDSEYE_ACTIVITY_TYPES
+            for raw_mode, mode in zip(raw_modes, modes)
+        ):
+            return None
+
+        if len(modes) != len(set(modes)):
+            return None
+
+        return cls(**{mode: True for mode in modes})
+
+    def has_enabled_activity(self) -> bool:
+        """Return whether at least one activity type is enabled."""
+        return any(getattr(self, activity) for activity in BIRDSEYE_ACTIVITY_TYPES)
+
+    def to_mqtt_payload(self) -> str:
+        """Serialize enabled mode options for MQTT state topics."""
+        payload = ",".join(
+            activity.upper()
+            for activity in BIRDSEYE_ACTIVITY_TYPES
+            if getattr(self, activity)
+        )
+        if not payload:
+            raise ValueError("At least one Birdseye activity type must be enabled")
+
+        return payload
+
+
+def default_birdseye_mode() -> BirdseyeModeConfig:
+    """Return the default Birdseye mode configuration."""
+    return BirdseyeModeConfig(objects=True)
 
 
 class BirdseyeLayoutConfig(FrigateBaseModel):
@@ -47,10 +101,10 @@ class BirdseyeConfig(FrigateBaseModel):
         title="Enable Birdseye",
         description="Enable or disable the Birdseye view feature.",
     )
-    mode: BirdseyeModeEnum = Field(
-        default=BirdseyeModeEnum.objects,
-        title="Tracking mode",
-        description="Mode for including cameras in Birdseye: 'objects', 'motion', or 'continuous'.",
+    mode: BirdseyeModeConfig = Field(
+        default_factory=default_birdseye_mode,
+        title="Activity types",
+        description="Activity types that include cameras in Birdseye.",
     )
 
     restream: bool = Field(
@@ -102,10 +156,10 @@ class BirdseyeCameraConfig(BaseModel):
         title="Enable Birdseye",
         description="Enable or disable the Birdseye view feature.",
     )
-    mode: BirdseyeModeEnum = Field(
-        default=BirdseyeModeEnum.objects,
-        title="Tracking mode",
-        description="Mode for including cameras in Birdseye: 'objects', 'motion', or 'continuous'.",
+    mode: BirdseyeModeConfig = Field(
+        default_factory=default_birdseye_mode,
+        title="Activity types",
+        description="Activity types that include cameras in Birdseye.",
     )
 
     order: int = Field(

frigate/config/config.py

@@ -41,7 +41,7 @@ from .auth import AuthConfig
 from .base import FrigateBaseModel
 from .camera import CameraConfig, CameraLiveConfig
 from .camera.audio import AudioConfig, AudioFilterConfig
-from .camera.birdseye import BirdseyeConfig
+from .camera.birdseye import BirdseyeConfig, BirdseyeModeConfig
 from .camera.detect import DetectConfig
 from .camera.ffmpeg import FfmpegConfig
 from .camera.genai import GenAIConfig, GenAIRoleEnum
@@ -326,8 +326,20 @@ def verify_required_zones_exist(camera_config: CameraConfig) -> None:
 
 
 def verify_profile_overrides_match_base(camera_config: CameraConfig) -> None:
-    """Verify that profile zone and mask IDs reference entries defined on the base camera."""
+    """Verify profile overrides against the resolved base camera configuration."""
     for profile_name, profile in camera_config.profiles.items():
+        if profile.birdseye is not None:
+            overrides = profile.birdseye.mode.model_dump(exclude_unset=True)
+            base_mode = camera_config.birdseye.mode.model_dump()
+            resolved_mode = BirdseyeModeConfig.model_validate(
+                deep_merge(overrides, base_mode)
+            )
+            if not resolved_mode.has_enabled_activity():
+                raise ValueError(
+                    f"Camera '{camera_config.name}' profile '{profile_name}' must "
+                    "enable at least one Birdseye activity type"
+                )
+
         if profile.zones:
             for zone_name in profile.zones:
                 if zone_name not in camera_config.zones:
@@ -998,6 +1010,10 @@ class FrigateConfig(FrigateBaseModel):
             self.cameras[name] = camera_config
 
             verify_config_roles(camera_config)
+            if not camera_config.birdseye.mode.has_enabled_activity():
+                raise ValueError(
+                    f"Camera '{name}' must enable at least one Birdseye activity type"
+                )
             verify_valid_live_stream_names(self, camera_config)
             verify_recording_segments_setup_with_reasonable_time(camera_config)
             verify_zone_objects_are_tracked(camera_config)

frigate/config/holder.py

@@ -0,0 +1,34 @@
+"""Shared handle on the config object that is current for this instance."""
+
+from .config import FrigateConfig
+
+__all__ = ["ConfigHolder"]
+
+
+class ConfigHolder:
+    """Indirection for the most recently parsed config.
+
+    /api/config/set re-parses yaml into a brand new FrigateConfig instead of
+    mutating the old one, so any reference captured during startup goes stale
+    the first time a user saves. Anything that has to build something after
+    startup, most importantly the watchdog factories that rebuild a crashed
+    process, must read through a holder rather than close over a config
+    object, or the rebuilt process comes back with the config as it was at
+    boot and silently discards every change made since.
+
+    There is deliberately no setter on the read side: the swap runs in exactly
+    one place (frigate.api.config_util.swap_runtime_config) and everyone else
+    only reads.
+    """
+
+    def __init__(self, config: FrigateConfig) -> None:
+        self._config = config
+
+    @property
+    def config(self) -> FrigateConfig:
+        """The config as of the most recent successful save."""
+        return self._config
+
+    def set(self, config: FrigateConfig) -> None:
+        """Install a freshly parsed config as the current one."""
+        self._config = config

frigate/config/profile_manager.py

@@ -43,7 +43,9 @@ SECTION_STATE_TOPICS: dict[str, list[tuple[str, Callable[[Any], Any]]]] = {
         ("birdseye", lambda c: "ON" if c.birdseye.enabled else "OFF"),
         (
             "birdseye_mode",
-            lambda c: c.birdseye.mode.value.upper() if c.birdseye.enabled else "OFF",
+            lambda c: (
+                c.birdseye.mode.to_mqtt_payload() if c.birdseye.enabled else "OFF"
+            ),
         ),
     ],
     "detect": [("detect", lambda c: "ON" if c.detect.enabled else "OFF")],

frigate/detectors/plugins/openvino.py

@@ -226,12 +226,12 @@ class OvDetector(DetectionApi):
 
             conf_mask = (image_pred[:, 4] * class_conf.squeeze() >= 0.3).squeeze()
             # Detections ordered as (x1, y1, x2, y2, obj_conf, class_conf, class_pred)
-            detections = np.concatenate(
+            predictions = np.concatenate(
                 (image_pred[:, :5], class_conf, class_pred), axis=1
             )
-            detections = detections[conf_mask]
+            predictions = predictions[conf_mask]
 
-            ordered = detections[detections[:, 5].argsort()[::-1]][:20]
+            ordered = predictions[predictions[:, 5].argsort()[::-1]][:20]
 
             for i, object_detected in enumerate(ordered):
                 detections[i] = self.process_yolo(

frigate/genai/__init__.py

@@ -23,6 +23,7 @@ from frigate.genai.prompts import (
     build_review_summary_prompt,
 )
 from frigate.models import Event
+from frigate.util.builtin import has_non_finite_number
 
 logger = logging.getLogger(__name__)
 
@@ -164,6 +165,15 @@ class GenAIClient:
                 except json.JSONDecodeError as je:
                     logger.error("Failed to parse review description JSON: %s", je)
                     return None
+
+                # model_construct skips validation, so non-finite numbers that
+                # the validated path would have rejected have to be caught here
+                if has_non_finite_number(raw):
+                    logger.error(
+                        "Discarding review description containing non-finite numbers."
+                    )
+                    return None
+
                 # observations and confidence are required on the model; fill an empty default
                 # if the response omitted it so attribute access stays safe.
                 raw.setdefault("observations", [])

frigate/genai/prompts.py

@@ -262,6 +262,10 @@ def get_tool_definitions(
     `attribute` parameter is exposed for filtering by their labels. When the
     embeddings model only understands English (JinaV1), the `semantic_query`
     description instructs the model to write the query in English.
+
+    Descriptions here stay mechanical: which tool to reach for, and how the
+    filters relate to each other, is stated once in the system prompt so the
+    guidance is not paid for twice on every request.
     """
     search_objects_properties: dict[str, Any] = {
         "camera": {
@@ -270,26 +274,13 @@ def get_tool_definitions(
         },
         "label": {
             "type": "string",
-            "description": (
-                "Generic object class to filter by — one of the tracked detector "
-                "labels such as 'person', 'package', 'car', 'dog', 'bird'. Use "
-                "this for broad queries like 'show me all cars today'. Combine "
-                "with semantic_query when the user also describes appearance or "
-                "behavior (e.g. label='person', semantic_query='riding a lawn "
-                "mower')."
-            ),
+            "description": "Tracked object class to filter by.",
         },
         "sub_label": {
             "type": "string",
             "description": (
-                "Filter by a DISCRETE NAMED entity recognized in the detection. "
-                "Use this for: a known person's name ('John'), a delivery "
-                "company ('Amazon', 'UPS'), a recognized animal species or "
-                "breed ('blue jay', 'cardinal', 'golden retriever'), or a "
-                "license plate string. When filtering by a specific name, set "
-                "only sub_label and leave label unset. Do NOT use sub_label "
-                "for descriptions of appearance, clothing, or actions — those "
-                "belong in semantic_query."
+                "Name recognized in the detection: a person, delivery company, "
+                "animal species or breed, or license plate."
             ),
         },
         "after": {
@@ -313,20 +304,11 @@ def get_tool_definitions(
     }
 
     if attribute_classifications:
-        model_outline = "; ".join(
-            f"{m['name']} (applies to {', '.join(m['objects']) or 'any object'})"
-            for m in attribute_classifications
-        )
         search_objects_properties["attribute"] = {
             "type": "string",
             "description": (
-                "Filter by a classification attribute label produced by a "
-                "configured attribute classification model. Use this INSTEAD "
-                "of semantic_query when the user's request matches one of "
-                "these classifications. Configured models: "
-                f"{model_outline}. "
-                "Set the value to the attribute label that matches the user's "
-                "phrasing (case-sensitive)."
+                "Attribute label produced by a configured classification model "
+                "(case-sensitive)."
             ),
         }
 
@@ -334,29 +316,12 @@ def get_tool_definitions(
         search_objects_properties["semantic_query"] = {
             "type": "string",
             "description": (
-                "Optional natural-language description of a PHYSICAL "
-                "CHARACTERISTIC, APPEARANCE, or ACTIVITY the user mentioned, "
-                "used to semantically narrow results. Only set this when the "
-                "user describes something beyond what label and sub_label can "
-                "express on their own.\n"
-                "USE for descriptive phrases like: 'riding a lawn mower', "
-                "'wearing a red jacket', 'carrying a package', 'walking a "
-                "dog', 'on a bicycle', 'holding an umbrella'.\n"
-                "DO NOT USE for:\n"
-                "- specific named people, pets, or delivery companies → use sub_label\n"
-                "- animal species or breed names like 'blue jay', 'cardinal', "
-                "'golden retriever' → use sub_label\n"
-                "- license plate strings → use sub_label\n"
-                "- generic object queries like 'all cars today' or 'every "
-                "person' → use label alone with no semantic_query\n"
-                "When set, combine with label/time/camera/zone filters as "
-                "usual (e.g. label='person', semantic_query='riding a lawn "
-                "mower', after='2024-05-01T00:00:00Z')."
+                "Description of an appearance or activity, used to semantically "
+                "narrow results."
                 + (
-                    " The configured embeddings model only understands "
-                    "English, so always write semantic_query in English, "
-                    "translating the user's description if they phrased it "
-                    "in another language."
+                    " The configured embeddings model only understands English, so "
+                    "always write this in English, translating the user's "
+                    "description if they phrased it in another language."
                     if embeddings_language == "english"
                     else ""
                 )
@@ -364,26 +329,10 @@ def get_tool_definitions(
         }
 
     search_objects_description = (
-        "Search the historical record of detected objects in Frigate. "
-        "Use this ONLY for questions about the PAST — e.g. 'did anyone come by today?', "
-        "'when was the last car?', 'show me detections from yesterday'. "
-        "Do NOT use this for monitoring or alerting requests about future events — "
-        "use start_camera_watch instead for those. "
-        "An 'object' in Frigate represents a tracked detection (e.g., a person, package, car).\n\n"
-        "Choose filters based on what the user is asking for:\n"
-        "- Generic class query ('show me all cars today'): set `label` only.\n"
-        "- Specific NAMED entity (known person, delivery company, animal "
-        "species/breed like 'blue jay' or 'golden retriever', license "
-        "plate): set `sub_label` only and leave `label` unset.\n"
+        "Search the historical record of tracked detections. Use this ONLY for "
+        "questions about the PAST, e.g. 'did anyone come by today?', 'when was the "
+        "last car?'. For alerting on future events use start_camera_watch instead."
     )
-    if semantic_search_enabled:
-        search_objects_description += (
-            "- Physical CHARACTERISTIC, APPEARANCE, or ACTIVITY that is not a "
-            "discrete name ('person riding a lawn mower', 'someone in a red "
-            "jacket', 'person carrying a package'): set `semantic_query` with "
-            "the descriptive phrase, optionally alongside `label` for the "
-            "object class. Do NOT put descriptive phrases in sub_label."
-        )
 
     return [
         {
@@ -398,20 +347,30 @@ def get_tool_definitions(
                 "required": [],
             },
         },
+        {
+            "type": "function",
+            "function": {
+                "name": "get_categorized_object_names",
+                "description": (
+                    "Every name that can be attached as a sub_label, grouped by object "
+                    "type: recognized faces, named license plates, classification "
+                    "categories, and delivery logos. Takes no arguments and always "
+                    "returns the complete map."
+                ),
+                "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": [],
+                },
+            },
+        },
         {
             "type": "function",
             "function": {
                 "name": "find_similar_objects",
                 "description": (
-                    "Find tracked objects that are visually and semantically similar "
-                    "to a specific past event. Use this when the user references a "
-                    "particular object they have seen and wants to find other "
-                    "sightings of the same or similar one ('that green car', 'the "
-                    "person in the red jacket', 'the package that was delivered'). "
-                    "Prefer this over search_objects whenever the user's intent is "
-                    "'find more like this specific one.' Use search_objects first "
-                    "only if you need to locate the anchor event. Requires semantic "
-                    "search to be enabled."
+                    "Find tracked objects visually and semantically similar to a "
+                    "specific past event. Requires semantic search to be enabled."
                 ),
                 "parameters": {
                     "type": "object",
@@ -473,9 +432,8 @@ def get_tool_definitions(
             "function": {
                 "name": "set_camera_state",
                 "description": (
-                    "Change a camera's feature state (e.g., turn detection on/off, enable/disable recordings). "
-                    "Use camera='*' to apply to all cameras at once. "
-                    "Only call this tool when the user explicitly asks to change a camera setting. "
+                    "Change a camera's feature state, e.g. turn detection on or off. "
+                    "Only call this when the user explicitly asks to change a setting. "
                     "Requires admin privileges."
                 ),
                 "parameters": {
@@ -510,14 +468,14 @@ def get_tool_definitions(
                             ],
                             "description": (
                                 "The feature to change. Most features accept ON or OFF. "
-                                "birdseye_mode accepts CONTINUOUS, MOTION, or OBJECTS. "
+                                "birdseye_mode accepts CONTINUOUS, MOTION, OBJECTS, STATIONARY_OBJECTS, or a comma-separated combination. "
                                 "motion_contour_area and motion_threshold accept a number. "
                                 "profile accepts a profile name or 'none' to deactivate (requires camera='*')."
                             ),
                         },
                         "value": {
                             "type": "string",
-                            "description": "The value to set. ON or OFF for toggles, a number for thresholds, a profile name or 'none' for profile.",
+                            "description": "The value to set, as accepted by the chosen feature.",
                         },
                     },
                     "required": ["camera", "feature", "value"],
@@ -529,11 +487,9 @@ def get_tool_definitions(
             "function": {
                 "name": "get_live_context",
                 "description": (
-                    "Get the current live image and detection information for a single camera: objects being tracked, "
-                    "zones, timestamps. Use this to understand what is visible in the live view. "
-                    "Call this when answering questions about what is happening right now on a specific camera. "
-                    "Operates on one camera at a time; call the tool again for each additional camera. "
-                    "Wildcards and empty values are not accepted."
+                    "Current live image and detections (tracked objects, zones, "
+                    "timestamps) for one camera. Use this for questions about what is "
+                    "happening right now. Call it again for each additional camera."
                 ),
                 "parameters": {
                     "type": "object",
@@ -541,8 +497,8 @@ def get_tool_definitions(
                         "camera": {
                             "type": "string",
                             "description": (
-                                "Exact name of a single camera to get live context for. "
-                                "Wildcards (e.g. '*', 'all') and empty strings are not accepted."
+                                "Exact name of a single camera. Wildcards (e.g. '*', "
+                                "'all') and empty strings are not accepted."
                             ),
                         },
                     },
@@ -555,10 +511,9 @@ def get_tool_definitions(
             "function": {
                 "name": "start_camera_watch",
                 "description": (
-                    "Start a continuous VLM watch job that monitors a camera and sends a notification "
-                    "when a specified condition is met. Use this when the user wants to be alerted about "
-                    "a future event, e.g. 'tell me when guests arrive' or 'notify me when the package is picked up'. "
-                    "Only one watch job can run at a time. Returns a job ID."
+                    "Start a continuous watch job that monitors a camera and notifies "
+                    "the user when a condition is met, e.g. 'tell me when guests "
+                    "arrive'. Only one watch job can run at a time. Returns a job ID."
                 ),
                 "parameters": {
                     "type": "object",
@@ -598,10 +553,7 @@ def get_tool_definitions(
             "type": "function",
             "function": {
                 "name": "stop_camera_watch",
-                "description": (
-                    "Cancel the currently running VLM watch job. Use this when the user wants to "
-                    "stop a previously started watch, e.g. 'stop watching the front door'."
-                ),
+                "description": "Cancel the currently running watch job.",
                 "parameters": {
                     "type": "object",
                     "properties": {},
@@ -614,11 +566,9 @@ def get_tool_definitions(
             "function": {
                 "name": "get_profile_status",
                 "description": (
-                    "Get the current profile status including the active profile and "
-                    "timestamps of when each profile was last activated. Use this to "
-                    "determine time periods for recap requests — e.g. when the user asks "
-                    "'what happened while I was away?', call this first to find the relevant "
-                    "time window based on profile activation history."
+                    "Get the active profile and when each profile was last activated. "
+                    "Call this before get_recap to derive the time window for requests "
+                    "like 'what happened while I was away?'."
                 ),
                 "parameters": {
                     "type": "object",
@@ -632,11 +582,9 @@ def get_tool_definitions(
             "function": {
                 "name": "get_recap",
                 "description": (
-                    "Get a recap of all activity (alerts and detections) for a given time period. "
-                    "Use this after calling get_profile_status to retrieve what happened during "
-                    "a specific window — e.g. 'what happened while I was away?'. Returns a "
-                    "chronological list of activity with camera, objects, zones, and GenAI-generated "
-                    "descriptions when available. Summarize the results for the user."
+                    "Get all activity (alerts and detections) for a time period, as a "
+                    "chronological list with camera, objects, zones, and descriptions "
+                    "when available. Summarize the results for the user."
                 ),
                 "parameters": {
                     "type": "object",
@@ -723,14 +671,13 @@ def build_chat_system_prompt(
         )
         speed_units_section = f"\n\nReport object speeds to the user in {speed_unit}."
 
-    semantic_search_section = ""
+    filter_routing_section = (
+        "\n\nWhen routing a search_objects call, pick filters by the shape of the user's request:\n"
+        "- Generic class ('show me all cars today'): set `label` only.\n"
+        "- Specific named entity — a known person ('John'), delivery company ('Amazon'), animal species/breed ('blue jay', 'golden retriever'), or license plate: set `sub_label` only and leave `label` unset. Call get_categorized_object_names first and use the exact spelling it returns; a guessed spelling matches nothing. If the name is absent, say it is not configured rather than searching for it."
+    )
     if semantic_search_enabled:
-        semantic_search_section = (
-            "\n\nWhen routing a search_objects call, pick filters by the shape of the user's request:\n"
-            "- Generic class ('show me all cars today'): set `label` only.\n"
-            "- Specific named entity — a known person ('John'), delivery company ('Amazon'), animal species/breed ('blue jay', 'cardinal', 'golden retriever'), or license plate: set `sub_label` only and leave `label` unset.\n"
-            "- Physical characteristic, appearance, or activity that is NOT a discrete name ('find me people riding a lawn mower', 'someone in a red jacket', 'a person carrying a package'): set `semantic_query` with the descriptive phrase, optionally combined with `label` for the object class. Never put descriptive phrases in `sub_label`."
-        )
+        filter_routing_section += "\n- Physical characteristic, appearance, or activity that is NOT a discrete name ('riding a lawn mower', 'someone in a red jacket'): set `semantic_query` with the descriptive phrase, optionally combined with `label`. Never put descriptive phrases in `sub_label`."
 
     attribute_classification_section = ""
     if attribute_classifications:
@@ -739,9 +686,9 @@ def build_chat_system_prompt(
             for m in attribute_classifications
         )
         attribute_classification_section = (
-            "\n\nAttribute classification models are configured for the following object types:\n"
+            "\n\nConfigured attribute classification models:\n"
             f"{model_lines}\n"
-            "When the user's request matches one of these classifications, set the search_objects `attribute` field to the matching label rather than using `semantic_query`. Reserve `semantic_query` for descriptive phrases that fall outside the configured attribute labels."
+            "When the user's request matches one of these classifications, set the search_objects `attribute` field to the matching label (case-sensitive) rather than using `semantic_query`. Reserve `semantic_query` for descriptive phrases outside the configured attribute labels."
         )
 
     return f"""You are a helpful assistant for Frigate, a security camera NVR system. You help users answer questions about their cameras, detected objects, and events.
@@ -750,9 +697,6 @@ Current server local date and time: {current_date_str} at {current_time_str}
 
 Do not start your response with phrases like "I will check...", "Let me see...", or "Let me look...". Answer directly.
 
-Always present times to the user in the server's local timezone. When tool results include start_time_local and end_time_local, use those exact strings when listing or describing detection times—do not convert or invent timestamps. Do not use UTC or ISO format with Z for the user-facing answer unless the tool result only provides Unix timestamps without local time fields.
-When users ask about "today", "yesterday", "this week", etc., use the current date above as reference.
-When searching for objects or events, use ISO 8601 format for dates (e.g., {current_date_str}T00:00:00Z for the start of today).
-Always be accurate with time calculations based on the current date provided.
+Always present times in the server's local timezone. When tool results include start_time_local and end_time_local, quote those strings exactly; never convert or invent timestamps, and fall back to UTC or ISO format only when a result has no local time fields. Resolve relative dates like "today" or "this week" against the current date above, and pass dates to tools in ISO 8601 (e.g. {current_date_str}T00:00:00Z for the start of today).
 
-When a user refers to a specific object they have seen or describe with identifying details ("that green car", "the person in the red jacket", "a package left today"), prefer the find_similar_objects tool over search_objects. Use search_objects first only to locate the anchor event, then pass its id to find_similar_objects. For generic queries like "show me all cars today", keep using search_objects. If a user message begins with [attached_event:<id>], treat that event id as the anchor for any similarity or "tell me more" request in the same message and call find_similar_objects with that id.{semantic_search_section}{attribute_classification_section}{cameras_section}{speed_units_section}"""
+When the user refers to a specific object they have seen ("that green car", "the person in the red jacket", "a package left today"), prefer find_similar_objects over search_objects, using search_objects only to locate the anchor event and passing its id along. Keep search_objects for generic queries like "show me all cars today". If a user message begins with [attached_event:<id>], treat that id as the anchor for any similarity or "tell me more" request in the same message.{filter_routing_section}{attribute_classification_section}{cameras_section}{speed_units_section}"""

frigate/output/birdseye.py

@@ -9,6 +9,7 @@ import queue
 import subprocess as sp
 import threading
 import traceback
+from dataclasses import dataclass
 from multiprocessing.synchronize import Event as MpEvent
 from typing import Any
 
@@ -16,7 +17,7 @@ import cv2
 import numpy as np
 
 from frigate.comms.inter_process import InterProcessRequestor
-from frigate.config import BirdseyeModeEnum, FfmpegConfig, FrigateConfig
+from frigate.config import BirdseyeModeConfig, FfmpegConfig, FrigateConfig
 from frigate.const import BASE_DIR, BIRDSEYE_PIPE, INSTALL_DIR, UPDATE_BIRDSEYE_LAYOUT
 from frigate.output.ws_auth import ws_has_camera_access
 from frigate.util.image import (
@@ -28,6 +29,15 @@ from frigate.util.image import (
 logger = logging.getLogger(__name__)
 
 
+@dataclass(frozen=True, slots=True)
+class BirdseyeActivity:
+    """Activity signals used to decide whether a camera is shown in Birdseye."""
+
+    has_active_object: bool
+    has_stationary_object: bool
+    has_motion: bool
+
+
 def get_standard_aspect_ratio(width: int, height: int) -> tuple[int, int]:
     """Ensure that only standard aspect ratios are used."""
     # it is important that all ratios have the same scale
@@ -409,18 +419,16 @@ class BirdsEyeFrameManager:
         )
 
     def camera_active(
-        self, mode: Any, object_box_count: int, motion_box_count: int
+        self,
+        mode: BirdseyeModeConfig,
+        activity: BirdseyeActivity,
     ) -> bool:
-        if mode == BirdseyeModeEnum.continuous:
-            return True
-
-        if mode == BirdseyeModeEnum.motion and motion_box_count > 0:
-            return True
-
-        if mode == BirdseyeModeEnum.objects and object_box_count > 0:
-            return True
-
-        return False
+        return (
+            mode.continuous
+            or (mode.motion and activity.has_motion)
+            or (mode.objects and activity.has_active_object)
+            or (mode.stationary_objects and activity.has_stationary_object)
+        )
 
     def get_camera_coordinates(self) -> dict[str, dict[str, int]]:
         """Return the coordinates of each camera in the current layout."""
@@ -604,112 +612,92 @@ class BirdsEyeFrameManager:
     ) -> list[list[Any]] | None:
         """Calculate the optimal layout for 2+ cameras."""
 
-        def map_layout(
-            camera_layout: list[list[Any]], row_height: int
-        ) -> tuple[int, int, list[list[Any]] | None]:
-            """Map the calculated layout."""
-            candidate_layout = []
-            starting_x = 0
-            x = 0
-            max_width = 0
-            y = 0
+        def find_available_x(
+            current_x: int,
+            width: int,
+            reserved_ranges: list[tuple[int, int]],
+            max_width: int,
+        ) -> int | None:
+            """Find the first horizontal slot that does not collide with reservations."""
+            x = current_x
 
-            for row in camera_layout:
-                final_row = []
-                max_width = max(max_width, x)
-                x = starting_x
-                for cameras in row:
-                    camera_dims = self.cameras[cameras[0]]["dimensions"].copy()
-                    camera_aspect = cameras[1]
+            for reserved_start, reserved_end in sorted(reserved_ranges):
+                if x >= reserved_end:
+                    continue
 
-                    if camera_dims[1] > camera_dims[0]:
-                        scaled_height = int(row_height * 2)
-                        scaled_width = int(scaled_height * camera_aspect)
-                        starting_x = scaled_width
-                    else:
-                        scaled_height = row_height
-                        scaled_width = int(scaled_height * camera_aspect)
+                if x + width <= reserved_start:
+                    return x
 
-                    # layout is too large
-                    if (
-                        x + scaled_width > self.canvas.width
-                        or y + scaled_height > self.canvas.height
-                    ):
-                        return x + scaled_width, y + scaled_height, None
+                x = max(x, reserved_end)
 
-                    final_row.append((cameras[0], (x, y, scaled_width, scaled_height)))
-                    x += scaled_width
+            if x + width <= max_width:
+                return x
 
-                y += row_height
-                candidate_layout.append(final_row)
-
-            if max_width == 0:
-                max_width = x
-
-            return max_width, y, candidate_layout
-
-        canvas_aspect_x, canvas_aspect_y = self.canvas.get_aspect(coefficient)
-        camera_layout: list[list[Any]] = []
-        camera_layout.append([])
-        starting_x = 0
-        x = starting_x
-        y = 0
-        y_i = 0
-        max_y = 0
-        for camera in cameras_to_add:
-            camera_dims = self.cameras[camera]["dimensions"].copy()
-            camera_aspect_x, camera_aspect_y = self.canvas.get_camera_aspect(
-                camera, camera_dims[0], camera_dims[1]
-            )
-
-            if camera_dims[1] > camera_dims[0]:
-                portrait = True
-            else:
-                portrait = False
-
-            if (x + camera_aspect_x) <= canvas_aspect_x:
-                # insert if camera can fit on current row
-                camera_layout[y_i].append(
-                    (
-                        camera,
-                        camera_aspect_x / camera_aspect_y,
-                    )
-                )
-
-                if portrait:
-                    starting_x = camera_aspect_x
-                else:
-                    max_y = max(
-                        max_y,
-                        camera_aspect_y,
-                    )
-
-                x += camera_aspect_x
-            else:
-                # move on to the next row and insert
-                y += max_y
-                y_i += 1
-                camera_layout.append([])
-                x = starting_x
-
-                if x + camera_aspect_x > canvas_aspect_x:
-                    return None
-
-                camera_layout[y_i].append(
-                    (
-                        camera,
-                        camera_aspect_x / camera_aspect_y,
-                    )
-                )
-                x += camera_aspect_x
-
-        if y + max_y > canvas_aspect_y:
             return None
 
-        row_height = int(self.canvas.height / coefficient)
-        total_width, total_height, standard_candidate_layout = map_layout(
-            camera_layout, row_height
-        )
+        def map_layout(row_height: int) -> tuple[int, int, list[list[Any]] | None]:
+            """Lay out cameras row by row while reserving portrait spans for the next row."""
+            candidate_layout: list[list[Any]] = []
+            reserved_ranges: dict[int, list[tuple[int, int]]] = {}
+            current_row: list[Any] = []
+            row_index = 0
+            row_y = 0
+            row_x = 0
+            max_width = 0
+            max_height = 0
+
+            for camera in cameras_to_add:
+                camera_dims = self.cameras[camera]["dimensions"].copy()
+                camera_aspect_x, camera_aspect_y = self.canvas.get_camera_aspect(
+                    camera, camera_dims[0], camera_dims[1]
+                )
+                portrait = camera_dims[1] > camera_dims[0]
+                scaled_height = row_height * 2 if portrait else row_height
+                scaled_width = int(scaled_height * (camera_aspect_x / camera_aspect_y))
+
+                while True:
+                    x = find_available_x(
+                        row_x,
+                        scaled_width,
+                        reserved_ranges.get(row_index, []),
+                        self.canvas.width,
+                    )
+
+                    if x is not None and row_y + scaled_height <= self.canvas.height:
+                        current_row.append(
+                            (camera, (x, row_y, scaled_width, scaled_height))
+                        )
+                        row_x = x + scaled_width
+                        max_width = max(max_width, row_x)
+                        max_height = max(max_height, row_y + scaled_height)
+
+                        if portrait:
+                            reserved_ranges.setdefault(row_index + 1, []).append(
+                                (x, row_x)
+                            )
+
+                        break
+
+                    if current_row:
+                        candidate_layout.append(current_row)
+                        current_row = []
+
+                    row_index += 1
+                    row_y = row_index * row_height
+                    row_x = 0
+
+                    if row_y + scaled_height > self.canvas.height:
+                        overflow_width = max(max_width, scaled_width)
+                        overflow_height = row_y + scaled_height
+                        return overflow_width, overflow_height, None
+
+            if current_row:
+                candidate_layout.append(current_row)
+
+            return max_width, max_height, candidate_layout
+
+        row_height = max(1, int(self.canvas.height / coefficient))
+        total_width, total_height, standard_candidate_layout = map_layout(row_height)
 
         if not standard_candidate_layout:
             # if standard layout didn't work
@@ -718,9 +706,9 @@ class BirdsEyeFrameManager:
                 total_width / self.canvas.width,
                 total_height / self.canvas.height,
             )
-            row_height = int(row_height / scale_down_percent)
+            row_height = max(1, int(row_height / scale_down_percent))
             total_width, total_height, standard_candidate_layout = map_layout(
-                camera_layout, row_height
+                row_height
             )
 
             if not standard_candidate_layout:
@@ -734,8 +722,8 @@ class BirdsEyeFrameManager:
             1 / (total_width / self.canvas.width),
             1 / (total_height / self.canvas.height),
         )
-        row_height = int(row_height * scale_up_percent)
-        _, _, scaled_layout = map_layout(camera_layout, row_height)
+        row_height = max(1, int(row_height * scale_up_percent))
+        _, _, scaled_layout = map_layout(row_height)
 
         if scaled_layout:
             return scaled_layout
@@ -745,8 +733,7 @@ class BirdsEyeFrameManager:
     def update(
         self,
         camera: str,
-        object_count: int,
-        motion_count: int,
+        activity: BirdseyeActivity,
         frame_time: float,
         frame: np.ndarray,
     ) -> tuple[bool, bool]:
@@ -774,7 +761,10 @@ class BirdsEyeFrameManager:
         # update the last active frame for the camera
         self.cameras[camera]["current_frame"] = frame.copy()
         self.cameras[camera]["current_frame_time"] = frame_time
-        if self.camera_active(camera_config.birdseye.mode, object_count, motion_count):
+        if self.camera_active(
+            camera_config.birdseye.mode,
+            activity,
+        ):
             self.cameras[camera]["last_active_frame"] = frame_time
 
         now = datetime.datetime.now().timestamp()
@@ -882,10 +872,29 @@ class Birdseye:
         frame_time: float,
         frame: np.ndarray,
     ) -> None:
+        has_active_object = False
+        has_stationary_object = False
+        for tracked_object in current_tracked_objects:
+            if tracked_object["stationary"]:
+                if not tracked_object["false_positive"]:
+                    has_stationary_object = True
+            else:
+                # Preserve the existing objects activity behavior, which includes
+                # non-stationary trackers before they are confirmed.
+                has_active_object = True
+
+            if has_active_object and has_stationary_object:
+                break
+
+        activity = BirdseyeActivity(
+            has_active_object=has_active_object,
+            has_stationary_object=has_stationary_object,
+            has_motion=bool(motion_boxes),
+        )
+
         frame_changed, frame_layout_changed = self.birdseye_manager.update(
             camera,
-            len([o for o in current_tracked_objects if not o["stationary"]]),
-            len(motion_boxes),
+            activity,
             frame_time,
             frame,
         )

frigate/output/output.py

@@ -178,13 +178,10 @@ class OutputProcess(FrigateProcess):
             )
 
             if update_topic is not None and birdseye_config is not None:
-                previous_global_mode = self.config.birdseye.mode
+                # only the global-only fields are applied here; the per-camera
+                # enabled and mode arrive on config/cameras/<name>/birdseye,
+                # already resolved against yaml by the config parse
                 self.config.birdseye = birdseye_config
-
-                for camera_config in self.config.cameras.values():
-                    if camera_config.birdseye.mode == previous_global_mode:
-                        camera_config.birdseye.mode = birdseye_config.mode
-
                 logger.debug("Applied dynamic birdseye config update")
 
             # check if there is an updated config

frigate/test/http_api/test_http_config_set.py

@@ -13,6 +13,7 @@ from frigate.config.camera.updater import (
     CameraConfigUpdatePublisher,
     CameraConfigUpdateTopic,
 )
+from frigate.config.holder import ConfigHolder
 from frigate.models import Event, Recordings, ReviewSegment
 from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
 
@@ -373,6 +374,151 @@ class TestConfigSetWildcardPropagation(BaseTestHttp):
         finally:
             os.unlink(config_path)
 
+    @patch("frigate.api.app.find_config_file")
+    def test_global_birdseye_save_fans_out_resolved_camera_configs(
+        self, mock_find_config
+    ):
+        """A global birdseye save must also publish the per-camera values.
+
+        Global birdseye only seeds enabled and mode; the camera copies are what
+        the output process actually reads. Sending just the global object makes
+        a worker guess which cameras were inheriting, and the only available
+        guess (mode still equals the previous global) wrongly claims a camera
+        whose explicit yaml mode happens to match.
+        """
+        self.minimal_config["birdseye"] = {
+            "enabled": True,
+            "mode": {"motion": True},
+        }
+        # explicit override that matches the global value being replaced
+        self.minimal_config["cameras"]["front_door"]["birdseye"] = {
+            "mode": {
+                "continuous": False,
+                "motion": True,
+                "objects": False,
+                "stationary_objects": False,
+            }
+        }
+
+        config_path = self._write_config_file()
+        mock_find_config.return_value = config_path
+
+        try:
+            app, mock_publisher = self._create_app_with_publisher()
+            with AuthTestClient(app) as client:
+                resp = client.put(
+                    "/config/set",
+                    json={
+                        "config_data": {
+                            "birdseye": {
+                                "mode": {
+                                    "continuous": True,
+                                    "motion": False,
+                                    "objects": False,
+                                    "stationary_objects": False,
+                                }
+                            }
+                        },
+                        "update_topic": "config/birdseye",
+                        "requires_restart": 0,
+                    },
+                )
+
+                self.assertEqual(resp.status_code, 200)
+
+                # the global object still goes out on its own topic
+                mock_publisher.publisher.publish.assert_called_once()
+                topic, settings = mock_publisher.publisher.publish.call_args[0]
+                self.assertEqual(topic, "config/birdseye")
+                self.assertEqual(settings.mode.to_mqtt_payload(), "CONTINUOUS")
+
+                published = {
+                    call[0][0].camera: call[0][1]
+                    for call in mock_publisher.publish_update.call_args_list
+                }
+                self.assertEqual(set(published), {"front_door", "back_yard"})
+
+                for call in mock_publisher.publish_update.call_args_list:
+                    self.assertEqual(
+                        call[0][0].update_type, CameraConfigUpdateEnum.birdseye
+                    )
+
+                # the override survives, the inheriting camera follows global
+                self.assertEqual(
+                    published["front_door"].mode.to_mqtt_payload(), "MOTION"
+                )
+                self.assertEqual(
+                    published["back_yard"].mode.to_mqtt_payload(), "CONTINUOUS"
+                )
+        finally:
+            os.unlink(config_path)
+
+    @patch("frigate.api.app.find_config_file")
+    def test_save_updates_the_config_holder(self, mock_find_config):
+        """A save must move the holder onto the freshly parsed config.
+
+        FrigateApp reads the holder when the watchdog rebuilds a crashed
+        process; if the save leaves it on the boot config, that process comes
+        back having lost every change made since Frigate started.
+        """
+        from fastapi import Request
+
+        from frigate.api.auth import get_allowed_cameras_for_filter, get_current_user
+        from frigate.api.fastapi_app import create_fastapi_app
+
+        config_path = self._write_config_file()
+        mock_find_config.return_value = config_path
+
+        mock_publisher = Mock(spec=CameraConfigUpdatePublisher)
+        mock_publisher.publisher = MagicMock()
+        boot_config = FrigateConfig(**self.minimal_config)
+        holder = ConfigHolder(boot_config)
+
+        try:
+            app = create_fastapi_app(
+                boot_config,
+                self.db,
+                None,
+                None,
+                None,
+                None,
+                None,
+                None,
+                mock_publisher,
+                None,
+                enforce_default_admin=False,
+                config_holder=holder,
+            )
+
+            async def mock_get_current_user(request: Request):
+                return {"username": "admin", "role": "admin"}
+
+            async def mock_get_allowed_cameras_for_filter(request: Request):
+                return list(self.minimal_config.get("cameras", {}).keys())
+
+            app.dependency_overrides[get_current_user] = mock_get_current_user
+            app.dependency_overrides[get_allowed_cameras_for_filter] = (
+                mock_get_allowed_cameras_for_filter
+            )
+
+            with AuthTestClient(app) as client:
+                resp = client.put(
+                    "/config/set",
+                    json={
+                        "config_data": {"birdseye": {"inactivity_threshold": 5}},
+                        "update_topic": "config/birdseye",
+                        "requires_restart": 0,
+                    },
+                )
+
+                self.assertEqual(resp.status_code, 200)
+
+            self.assertIsNot(holder.config, boot_config)
+            self.assertIs(holder.config, app.frigate_config)
+            self.assertEqual(holder.config.birdseye.inactivity_threshold, 5)
+        finally:
+            os.unlink(config_path)
+
 
 if __name__ == "__main__":
     unittest.main()

frigate/test/http_api/test_http_media.py

@@ -1,15 +1,73 @@
 """Unit tests for recordings/media API endpoints."""
 
+from dataclasses import dataclass
 from datetime import UTC, datetime
+from unittest.mock import patch
 
 import pytz
 from fastapi import Request
 
 from frigate.api.auth import get_allowed_cameras_for_filter, get_current_user
+from frigate.const import MAX_SEGMENT_DURATION
 from frigate.models import Recordings
 from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
 
 
+@dataclass(frozen=True)
+class RangeCase:
+    """Expected behavior for one segment relative to the requested range.
+
+    Offsets are seconds from REQUEST_START; the request ends at +100 seconds.
+    """
+
+    name: str
+    start_offset: float
+    end_offset: float
+    included_in_recordings: bool
+    vod_clip_from_ms: int | None = None
+    vod_duration_ms: int | None = None
+
+
+REQUEST_START = 1000
+REQUEST_END = 1100
+RANGE_CASES = (
+    RangeCase("before", -MAX_SEGMENT_DURATION + 1, -1, False),
+    RangeCase("meets_start", -10, 0, True),
+    RangeCase(
+        "overlaps_start",
+        -MAX_SEGMENT_DURATION + 0.5,
+        0.25,
+        True,
+        vod_clip_from_ms=599500,
+        vod_duration_ms=250,
+    ),
+    RangeCase("starts_at_start", 0, 10, True, vod_duration_ms=10000),
+    RangeCase("inside", 20, 80, True, vod_duration_ms=60000),
+    RangeCase("ends_at_end", 90, 100, True, vod_duration_ms=10000),
+    RangeCase("matches_range", 0, 100, True, vod_duration_ms=100000),
+    RangeCase("starts_with_range", 0, 110, True, vod_duration_ms=100000),
+    RangeCase(
+        "covers_range",
+        -20,
+        120,
+        True,
+        vod_clip_from_ms=20000,
+        vod_duration_ms=100000,
+    ),
+    RangeCase(
+        "ends_with_range",
+        -10,
+        100,
+        True,
+        vod_clip_from_ms=10000,
+        vod_duration_ms=100000,
+    ),
+    RangeCase("overlaps_end", 95, 105, True, vod_duration_ms=5000),
+    RangeCase("starts_at_end", 100, 110, True),
+    RangeCase("after", 101, 110, False),
+)
+
+
 class TestHttpMedia(BaseTestHttp):
     """Test media API endpoints, particularly recordings with DST handling."""
 
@@ -44,6 +102,26 @@ class TestHttpMedia(BaseTestHttp):
         self.app.dependency_overrides.clear()
         super().tearDown()
 
+    def _assert_vod_response(
+        self,
+        response,
+        expected_clips: list[tuple[str, int | None, int]],
+    ) -> None:
+        """Assert VOD clip metadata and its derived duration fields."""
+        assert response.status_code == 200
+        vod = response.json()
+        assert [
+            (
+                clip["path"],
+                clip.get("clipFrom"),
+                clip["keyFrameDurations"][0],
+            )
+            for clip in vod["sequences"][0]["clips"]
+        ] == expected_clips
+        expected_durations = [clip[2] for clip in expected_clips]
+        assert vod["durations"] == expected_durations
+        assert vod["segment_duration"] == max(expected_durations)
+
     def test_recordings_summary_across_dst_spring_forward(self):
         """
         Test recordings summary across spring DST transition (spring forward).
@@ -404,6 +482,102 @@ class TestHttpMedia(BaseTestHttp):
             assert "2024-03-10" in summary
             assert summary["2024-03-10"] is True
 
+    def test_recordings_handles_all_range_relations(self):
+        """Recordings return every interval relation that touches the range."""
+        with AuthTestClient(self.app) as client:
+            for case in RANGE_CASES:
+                with self.subTest(case=case.name):
+                    Recordings.delete().execute()
+                    super().insert_mock_recording(
+                        case.name,
+                        REQUEST_START + case.start_offset,
+                        REQUEST_START + case.end_offset,
+                    )
+
+                    response = client.get(
+                        "/front_door/recordings",
+                        params={"after": REQUEST_START, "before": REQUEST_END},
+                    )
+
+                    assert response.status_code == 200
+                    expected_ids = [case.name] if case.included_in_recordings else []
+                    assert [
+                        recording["id"] for recording in response.json()
+                    ] == expected_ids
+
+    def test_vod_handles_all_range_relations(self):
+        """VOD clips every interval relation with positive playback duration."""
+        with (
+            AuthTestClient(self.app) as client,
+            patch(
+                "frigate.api.media.get_keyframe_before",
+                side_effect=lambda _path, offset: offset,
+            ),
+        ):
+            for case in RANGE_CASES:
+                with self.subTest(case=case.name):
+                    Recordings.delete().execute()
+                    super().insert_mock_recording(
+                        case.name,
+                        REQUEST_START + case.start_offset,
+                        REQUEST_START + case.end_offset,
+                    )
+
+                    response = client.get(
+                        f"/vod/front_door/start/{REQUEST_START}/end/{REQUEST_END}"
+                    )
+
+                    if case.vod_duration_ms is None:
+                        assert response.status_code == 404
+                        continue
+
+                    self._assert_vod_response(
+                        response,
+                        [
+                            (
+                                case.name,
+                                case.vod_clip_from_ms,
+                                case.vod_duration_ms,
+                            )
+                        ],
+                    )
+
+    def test_vod_handles_segment_ending_at_start_with_keyframe_fallbacks(self):
+        """VOD keeps a boundary segment when keyframe lookup extends it."""
+
+        def keyframe_before(path: str, offset: int) -> int | None:
+            return offset - 1000 if path == "previous_keyframe" else None
+
+        with (
+            AuthTestClient(self.app) as client,
+            patch(
+                "frigate.api.media.get_keyframe_before",
+                side_effect=keyframe_before,
+            ),
+        ):
+            super().insert_mock_recording(
+                "previous_keyframe",
+                REQUEST_START - 10,
+                REQUEST_START,
+            )
+            super().insert_mock_recording(
+                "missing_keyframe",
+                REQUEST_START - 5,
+                REQUEST_START,
+            )
+
+            response = client.get(
+                f"/vod/front_door/start/{REQUEST_START}/end/{REQUEST_END}"
+            )
+
+            self._assert_vod_response(
+                response,
+                [
+                    ("previous_keyframe", 9000, 1000),
+                    ("missing_keyframe", None, 5000),
+                ],
+            )
+
     def test_recordings_unavailable_reports_gap_between_recordings(self):
         """A gap between two recordings is reported as an unavailable segment."""
         with AuthTestClient(self.app) as client:

frigate/test/test_birdseye.py

@@ -1,13 +1,70 @@
-"""Test camera user and password cleanup."""
+"""Tests for Birdseye canvas sizing and layout behavior."""
 
 import multiprocessing as mp
 import unittest
+from unittest.mock import Mock
 
-from frigate.config import FrigateConfig
-from frigate.output.birdseye import BirdsEyeFrameManager, get_canvas_shape
+from frigate.config import BirdseyeModeConfig, FrigateConfig
+from frigate.output.birdseye import (
+    Birdseye,
+    BirdseyeActivity,
+    BirdsEyeFrameManager,
+    get_canvas_shape,
+)
 
 
 class TestBirdseye(unittest.TestCase):
+    def _build_manager(
+        self, camera_dimensions: dict[str, tuple[int, int]]
+    ) -> BirdsEyeFrameManager:
+        config = {
+            "mqtt": {"host": "mqtt"},
+            "birdseye": {"width": 1280, "height": 720},
+            "cameras": {},
+        }
+
+        for order, (camera, dimensions) in enumerate(
+            camera_dimensions.items(), start=1
+        ):
+            config["cameras"][camera] = {
+                "ffmpeg": {
+                    "inputs": [
+                        {
+                            "path": f"rtsp://10.0.0.1:554/{camera}",
+                            "roles": ["detect"],
+                        }
+                    ]
+                },
+                "detect": {
+                    "width": dimensions[0],
+                    "height": dimensions[1],
+                    "fps": 5,
+                },
+                "birdseye": {"order": order},
+            }
+
+        return BirdsEyeFrameManager(FrigateConfig(**config), mp.Event())
+
+    def _assert_no_overlaps(
+        self, layout: list[list[tuple[str, tuple[int, int, int, int]]]]
+    ):
+        rectangles = [position for row in layout for _, position in row]
+
+        for index, rect in enumerate(rectangles):
+            x1, y1, width1, height1 = rect
+            for other in rectangles[index + 1 :]:
+                x2, y2, width2, height2 = other
+                overlap = (
+                    x1 < x2 + width2
+                    and x2 < x1 + width1
+                    and y1 < y2 + height2
+                    and y2 < y1 + height1
+                )
+                self.assertFalse(
+                    overlap,
+                    msg=f"Overlapping rectangles found: {rect} and {other}",
+                )
+
     def test_16x9(self):
         """Test 16x9 aspect ratio works as expected for birdseye."""
         width = 1280
@@ -48,6 +105,212 @@ class TestBirdseye(unittest.TestCase):
         assert canvas_width == width  # width will be the same
         assert canvas_height != height
 
+    def test_portrait_camera_does_not_overlap_next_row(self):
+        """Portrait cameras should reserve their real horizontal position on the next row."""
+        manager = self._build_manager(
+            {
+                "cam_a": (1280, 720),
+                "cam_p": (360, 640),
+                "cam_b": (1280, 720),
+                "cam_c": (640, 480),
+            }
+        )
+
+        layout = manager.calculate_layout(["cam_a", "cam_p", "cam_b", "cam_c"], 3)
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+        cam_c = [
+            position for row in layout for camera, position in row if camera == "cam_c"
+        ][0]
+        self.assertEqual(cam_c[0], 0)
+
+    def test_portrait_reservation_only_applies_to_next_row(self):
+        """Portrait reservations should not push later rows after the span ends."""
+        manager = self._build_manager(
+            {
+                "cam_a": (1280, 720),
+                "cam_p": (360, 640),
+                "cam_b": (1280, 720),
+                "cam_c": (1280, 720),
+                "cam_d": (1280, 720),
+                "cam_e": (1280, 720),
+            }
+        )
+
+        layout = manager.calculate_layout(
+            ["cam_a", "cam_p", "cam_b", "cam_c", "cam_d", "cam_e"],
+            3,
+        )
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+        cam_e = [
+            position for row in layout for camera, position in row if camera == "cam_e"
+        ][0]
+        self.assertEqual(cam_e[0], 0)
+
+    def test_multiple_portraits_reserve_distinct_ranges(self):
+        """Multiple portrait cameras in one row should reserve separate spans below them."""
+        manager = self._build_manager(
+            {
+                "cam_a": (640, 480),
+                "cam_p1": (360, 640),
+                "cam_p2": (360, 640),
+                "cam_b": (640, 480),
+                "cam_c": (1280, 720),
+                "cam_d": (640, 480),
+            }
+        )
+
+        layout = manager.calculate_layout(
+            ["cam_a", "cam_p1", "cam_p2", "cam_b", "cam_c", "cam_d"],
+            4,
+        )
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+    def test_two_landscapes_then_portrait_then_two_landscapes(self):
+        """A portrait after two landscapes should reserve only its own tail span."""
+        manager = self._build_manager(
+            {
+                "cam_a": (1280, 720),
+                "cam_b": (1280, 720),
+                "cam_p": (360, 640),
+                "cam_c": (1280, 720),
+                "cam_d": (1280, 720),
+            }
+        )
+
+        layout = manager.calculate_layout(
+            ["cam_a", "cam_b", "cam_p", "cam_c", "cam_d"],
+            3,
+        )
+
+        self.assertIsNotNone(layout)
+        assert layout is not None
+        self._assert_no_overlaps(layout)
+
+        cam_c = [
+            position for row in layout for camera, position in row if camera == "cam_c"
+        ][0]
+        cam_d = [
+            position for row in layout for camera, position in row if camera == "cam_d"
+        ][0]
+        self.assertEqual(cam_c[0], 0)
+        self.assertEqual(cam_d[0], cam_c[0] + cam_c[2])
+
+
+class TestBirdseyeActivity(unittest.TestCase):
+    """Test which camera activity is included in each Birdseye mode."""
+
+    def setUp(self):
+        config = {
+            "mqtt": {"enabled": False},
+            "birdseye": {
+                "enabled": True,
+                "mode": {
+                    "motion": True,
+                    "objects": True,
+                    "stationary_objects": True,
+                },
+            },
+            "cameras": {
+                "front": {
+                    "ffmpeg": {
+                        "inputs": [
+                            {"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
+                        ]
+                    },
+                    "detect": {"height": 1080, "width": 1920, "fps": 5},
+                }
+            },
+        }
+        self.manager = BirdsEyeFrameManager(FrigateConfig(**config), mp.Event())
+
+    def test_existing_modes_keep_their_activity_rules(self):
+        continuous = BirdseyeModeConfig(continuous=True)
+        motion = BirdseyeModeConfig(motion=True)
+        objects = BirdseyeModeConfig(objects=True)
+
+        no_activity = BirdseyeActivity(False, False, False)
+        motion_activity = BirdseyeActivity(False, False, True)
+        stationary_activity = BirdseyeActivity(False, True, False)
+        active_object_activity = BirdseyeActivity(True, False, False)
+
+        assert self.manager.camera_active(continuous, no_activity)
+        assert self.manager.camera_active(motion, motion_activity)
+        assert not self.manager.camera_active(motion, stationary_activity)
+        assert self.manager.camera_active(objects, active_object_activity)
+        assert not self.manager.camera_active(objects, stationary_activity)
+
+    def test_modes_can_be_combined(self):
+        mode = BirdseyeModeConfig(motion=True, stationary_objects=True)
+
+        assert self.manager.camera_active(mode, BirdseyeActivity(False, False, True))
+        assert self.manager.camera_active(mode, BirdseyeActivity(False, True, False))
+        assert not self.manager.camera_active(
+            mode, BirdseyeActivity(False, False, False)
+        )
+
+    def test_stationary_objects_are_independent_from_active_objects(self):
+        stationary_objects = BirdseyeModeConfig(stationary_objects=True)
+
+        assert self.manager.camera_active(
+            stationary_objects, BirdseyeActivity(False, True, False)
+        )
+        assert not self.manager.camera_active(
+            stationary_objects, BirdseyeActivity(True, False, False)
+        )
+
+    def test_write_data_preserves_active_and_confirms_stationary_activity(self):
+        birdseye = Birdseye.__new__(Birdseye)
+        birdseye.birdseye_manager = Mock()
+        birdseye.birdseye_manager.update.return_value = (False, False)
+        birdseye._idle_interval = None
+        frame = Mock()
+
+        birdseye.write_data(
+            "front",
+            [
+                {"stationary": True, "false_positive": True},
+                {"stationary": False, "false_positive": True},
+                {"stationary": True, "false_positive": False},
+            ],
+            [[0, 0, 10, 10]],
+            1.0,
+            frame,
+        )
+
+        birdseye.birdseye_manager.update.assert_called_once_with(
+            "front", BirdseyeActivity(True, True, True), 1.0, frame
+        )
+
+    def test_stationary_false_positive_does_not_activate_birdseye(self):
+        birdseye = Birdseye.__new__(Birdseye)
+        birdseye.birdseye_manager = Mock()
+        birdseye.birdseye_manager.update.return_value = (False, False)
+        birdseye._idle_interval = None
+        frame = Mock()
+
+        birdseye.write_data(
+            "front",
+            [{"stationary": True, "false_positive": True}],
+            [],
+            1.0,
+            frame,
+        )
+
+        birdseye.birdseye_manager.update.assert_called_once_with(
+            "front", BirdseyeActivity(False, False, False), 1.0, frame
+        )
+
 
 class TestBirdseyeCameraOrder(unittest.TestCase):
     """Test that birdseye reacts to camera order changes without a restart."""
@@ -55,7 +318,7 @@ class TestBirdseyeCameraOrder(unittest.TestCase):
     def setUp(self):
         config = {
             "mqtt": {"enabled": False},
-            "birdseye": {"enabled": True, "mode": "continuous"},
+            "birdseye": {"enabled": True, "mode": {"continuous": True}},
             "cameras": {
                 camera: {
                     "ffmpeg": {

frigate/test/test_config.py

@@ -7,7 +7,7 @@ import numpy as np
 from pydantic import ValidationError
 from ruamel.yaml.constructor import DuplicateKeyError
 
-from frigate.config import BirdseyeModeEnum, FrigateConfig
+from frigate.config import FrigateConfig
 from frigate.const import MODEL_CACHE_DIR
 from frigate.detectors import DetectorTypeEnum
 from frigate.util.builtin import deep_merge
@@ -170,7 +170,7 @@ class TestConfig(unittest.TestCase):
     def test_override_birdseye(self):
         config = {
             "mqtt": {"host": "mqtt"},
-            "birdseye": {"enabled": True, "mode": "continuous"},
+            "birdseye": {"enabled": True, "mode": {"continuous": True}},
             "cameras": {
                 "back": {
                     "ffmpeg": {
@@ -183,19 +183,30 @@ class TestConfig(unittest.TestCase):
                         "width": 1920,
                         "fps": 5,
                     },
-                    "birdseye": {"enabled": False, "mode": "motion"},
+                    "birdseye": {
+                        "enabled": False,
+                        "mode": {"continuous": False, "motion": True},
+                    },
                 }
             },
         }
 
         frigate_config = FrigateConfig(**config)
         assert not frigate_config.cameras["back"].birdseye.enabled
-        assert frigate_config.cameras["back"].birdseye.mode is BirdseyeModeEnum.motion
+        mode = frigate_config.cameras["back"].birdseye.mode
+        assert mode.motion
+        assert not mode.continuous
+        assert not mode.objects
+        assert not mode.stationary_objects
 
     def test_override_birdseye_non_inheritable(self):
         config = {
             "mqtt": {"host": "mqtt"},
-            "birdseye": {"enabled": True, "mode": "continuous", "height": 1920},
+            "birdseye": {
+                "enabled": True,
+                "mode": {"continuous": True},
+                "height": 1920,
+            },
             "cameras": {
                 "back": {
                     "ffmpeg": {
@@ -218,7 +229,7 @@ class TestConfig(unittest.TestCase):
     def test_inherit_birdseye(self):
         config = {
             "mqtt": {"host": "mqtt"},
-            "birdseye": {"enabled": True, "mode": "continuous"},
+            "birdseye": {"enabled": True, "mode": {"continuous": True}},
             "cameras": {
                 "back": {
                     "ffmpeg": {
@@ -237,9 +248,89 @@ class TestConfig(unittest.TestCase):
 
         frigate_config = FrigateConfig(**config)
         assert frigate_config.cameras["back"].birdseye.enabled
-        assert (
-            frigate_config.cameras["back"].birdseye.mode is BirdseyeModeEnum.continuous
-        )
+        mode = frigate_config.cameras["back"].birdseye.mode
+        assert mode.continuous
+        assert not mode.motion
+        assert not mode.objects
+        assert not mode.stationary_objects
+
+    def test_combine_birdseye_activity_types(self):
+        config = {
+            **self.minimal,
+            "birdseye": {
+                "mode": {
+                    "motion": True,
+                    "stationary_objects": True,
+                }
+            },
+        }
+
+        frigate_config = FrigateConfig(**config)
+        mode = frigate_config.cameras["back"].birdseye.mode
+        assert mode.motion
+        assert mode.stationary_objects
+        assert not mode.continuous
+        assert not mode.objects
+
+    def test_birdseye_requires_an_activity_type(self):
+        config = {
+            **self.minimal,
+            "birdseye": {
+                "mode": {
+                    "continuous": False,
+                    "motion": False,
+                    "objects": False,
+                    "stationary_objects": False,
+                }
+            },
+        }
+
+        with self.assertRaisesRegex(
+            ValidationError, "must enable at least one Birdseye activity type"
+        ):
+            FrigateConfig(**config)
+
+    def test_camera_can_disable_an_inherited_activity_type(self):
+        config = {
+            **self.minimal,
+            "birdseye": {"mode": {"motion": True, "objects": True}},
+        }
+        config["cameras"]["back"]["birdseye"] = {"mode": {"motion": False}}
+
+        frigate_config = FrigateConfig(**config)
+        mode = frigate_config.cameras["back"].birdseye.mode
+        assert not mode.motion
+        assert mode.objects
+
+    def test_profile_must_leave_an_activity_type_enabled(self):
+        config = {
+            **self.minimal,
+            "profiles": {"away": {"friendly_name": "Away"}},
+            "birdseye": {"mode": {"objects": True}},
+        }
+        config["cameras"]["back"]["profiles"] = {
+            "away": {"birdseye": {"mode": {"objects": False}}}
+        }
+
+        with self.assertRaisesRegex(
+            ValidationError, "must enable at least one Birdseye activity type"
+        ):
+            FrigateConfig(**config)
+
+    def test_camera_birdseye_activity_types_override_global_values(self):
+        config = {
+            **self.minimal,
+            "birdseye": {"mode": {"motion": True, "objects": True}},
+        }
+        config["cameras"]["back"]["birdseye"] = {
+            "mode": {"motion": False, "stationary_objects": True}
+        }
+
+        frigate_config = FrigateConfig(**config)
+        mode = frigate_config.cameras["back"].birdseye.mode
+        assert not mode.motion
+        assert mode.objects
+        assert mode.stationary_objects
 
     def test_override_tracked_objects(self):
         config = {

frigate/test/test_config_util.py

@@ -4,6 +4,7 @@ import unittest
 from unittest.mock import MagicMock
 
 from frigate.api.config_util import swap_runtime_config
+from frigate.config.holder import ConfigHolder
 
 
 class TestSwapRuntimeConfig(unittest.TestCase):
@@ -12,6 +13,7 @@ class TestSwapRuntimeConfig(unittest.TestCase):
     def _make_app(self) -> MagicMock:
         app = MagicMock()
         app.dispatcher.comms = [MagicMock(), MagicMock()]
+        app.config_holder = ConfigHolder(MagicMock(name="boot_config"))
         return app
 
     def test_rebinds_all_references(self) -> None:
@@ -37,11 +39,40 @@ class TestSwapRuntimeConfig(unittest.TestCase):
         # the swap rebuilds cameras from yaml, so overrides must be re-layered
         app.dispatcher.reapply_runtime_state_to_config.assert_called_once_with()
 
+    def test_updates_the_config_holder(self) -> None:
+        app = self._make_app()
+        holder = app.config_holder
+        config = MagicMock(name="new_config")
+
+        swap_runtime_config(app, config)
+
+        self.assertIs(holder.config, config)
+
+    def test_deferred_factory_builds_from_the_swapped_config(self) -> None:
+        """A watchdog-style factory must not rebuild from the boot config.
+
+        The factories in FrigateApp are lambdas evaluated when a process is
+        restarted, long after a user may have saved. Reading through the
+        holder is what keeps a rebuilt process from reverting every change
+        made since Frigate started.
+        """
+        app = self._make_app()
+        holder = app.config_holder
+        boot_config = holder.config
+        factory = lambda: holder.config  # noqa: E731
+        self.assertIs(factory(), boot_config)
+
+        config = MagicMock(name="new_config")
+        swap_runtime_config(app, config)
+
+        self.assertIs(factory(), config)
+
     def test_tolerates_missing_optional_collaborators(self) -> None:
         app = MagicMock()
         app.profile_manager = None
         app.stats_emitter = None
         app.dispatcher = None
+        app.config_holder = None
         config = MagicMock(name="new_config")
 
         # must not raise when the optional collaborators are absent

frigate/test/test_dispatcher_runtime_state.py

@@ -7,6 +7,7 @@ from unittest.mock import MagicMock, patch
 
 from frigate.comms.dispatcher import Dispatcher
 from frigate.comms.runtime_state import RuntimeStatePersistence
+from frigate.config import BirdseyeModeConfig
 
 
 def _make_camera_mock(
@@ -50,6 +51,58 @@ def _build_dispatcher(cameras: dict[str, MagicMock]) -> Dispatcher:
         return Dispatcher(config, config_updater, onvif, ptz_metrics, communicators)
 
 
+class TestBirdseyeModeCommands(unittest.TestCase):
+    """Verify Birdseye mode commands use the boolean mode contract."""
+
+    def setUp(self) -> None:
+        self.camera = _make_camera_mock()
+        self.camera.birdseye.enabled = True
+        self.dispatcher = _build_dispatcher({"front_door": self.camera})
+        self.dispatcher.publish = MagicMock()
+
+    def test_combined_modes_are_accepted(self) -> None:
+        self.dispatcher._on_birdseye_mode_command(
+            "front_door", "STATIONARY_OBJECTS,MOTION"
+        )
+
+        self.assertEqual(
+            self.camera.birdseye.mode,
+            BirdseyeModeConfig(motion=True, stationary_objects=True),
+        )
+        self.dispatcher.config_updater.publish_update.assert_called_once()
+        self.dispatcher.publish.assert_called_once_with(
+            "front_door/birdseye_mode/state",
+            "MOTION,STATIONARY_OBJECTS",
+            retain=True,
+        )
+
+    def test_single_activity_type_is_accepted(self) -> None:
+        self.dispatcher._on_birdseye_mode_command("front_door", "OBJECTS")
+
+        self.assertEqual(
+            self.camera.birdseye.mode,
+            BirdseyeModeConfig(objects=True),
+        )
+        self.dispatcher.publish.assert_called_once_with(
+            "front_door/birdseye_mode/state", "OBJECTS", retain=True
+        )
+
+    def test_unknown_mode_is_rejected(self) -> None:
+        for payload in (
+            "UNKNOWN",
+            "motion",
+            "MOTION_OBJECTS",
+            "NONE",
+            "NONE,MOTION",
+            "MOTION,MOTION",
+            "MOTION,",
+        ):
+            with self.subTest(payload=payload):
+                self.dispatcher._on_birdseye_mode_command("front_door", payload)
+
+        self.dispatcher.config_updater.publish_update.assert_not_called()
+
+
 class TestRestoreRuntimeState(unittest.TestCase):
     """Verify replay routes through handlers and tolerates missing entries."""
 

frigate/test/test_gpu_stats.py

@@ -1,7 +1,12 @@
 import unittest
+from io import StringIO
 from unittest.mock import MagicMock, patch
 
-from frigate.util.services import get_amd_gpu_stats, get_intel_gpu_stats
+from frigate.util.services import (
+    get_amd_gpu_stats,
+    get_intel_gpu_stats,
+    get_openvino_npu_stats,
+)
 
 
 class TestGpuStats(unittest.TestCase):
@@ -17,6 +22,88 @@ class TestGpuStats(unittest.TestCase):
         amd_stats = get_amd_gpu_stats()
         assert amd_stats == {"gpu": "4.17%", "mem": "60.37%"}
 
+    @patch("frigate.util.services.time.sleep")
+    @patch("frigate.util.services.time.time", side_effect=[0.0, 1.0])
+    @patch(
+        "frigate.util.services.os.readlink",
+        return_value="/sys/bus/pci/drivers/intel_vpu",
+    )
+    @patch(
+        "frigate.util.services.glob.glob",
+        return_value=["/sys/class/accel/accel0"],
+    )
+    @patch(
+        "builtins.open",
+        side_effect=[StringIO("1000"), StringIO("1250")],
+    )
+    def test_openvino_npu_stats_discovers_accel0(
+        self, open_file, glob, readlink, time, sleep
+    ):
+        assert get_openvino_npu_stats() == {"npu": "25.0", "mem": "-%"}
+
+        open_file.assert_any_call(
+            "/sys/class/accel/accel0/device/power/runtime_active_time"
+        )
+
+    @patch("frigate.util.services.time.sleep")
+    @patch("frigate.util.services.time.time", side_effect=[0.0, 1.0])
+    @patch(
+        "frigate.util.services.os.readlink",
+        side_effect=[
+            "/sys/bus/pci/drivers/other",
+            "/sys/bus/pci/drivers/intel_vpu",
+        ],
+    )
+    @patch(
+        "frigate.util.services.glob.glob",
+        return_value=[
+            "/sys/class/accel/accel0",
+            "/sys/class/accel/accel1",
+        ],
+    )
+    @patch(
+        "builtins.open",
+        side_effect=[StringIO("1000"), StringIO("1250")],
+    )
+    def test_openvino_npu_stats_skips_non_intel_accelerator(
+        self, open_file, glob, readlink, time, sleep
+    ):
+        assert get_openvino_npu_stats() == {"npu": "25.0", "mem": "-%"}
+
+        open_file.assert_any_call(
+            "/sys/class/accel/accel1/device/power/runtime_active_time"
+        )
+
+    @patch(
+        "frigate.util.services.os.readlink",
+        return_value="/sys/bus/pci/drivers/other",
+    )
+    @patch(
+        "frigate.util.services.glob.glob",
+        return_value=["/sys/class/accel/accel0"],
+    )
+    @patch("builtins.open")
+    def test_openvino_npu_stats_no_intel_accelerator(self, open_file, glob, readlink):
+        assert get_openvino_npu_stats() is None
+        open_file.assert_not_called()
+
+    @patch(
+        "frigate.util.services.os.readlink",
+        return_value="/sys/bus/pci/drivers/intel_vpu",
+    )
+    @patch(
+        "frigate.util.services.glob.glob",
+        return_value=["/sys/class/accel/accel0"],
+    )
+    @patch("builtins.open", side_effect=FileNotFoundError)
+    def test_openvino_npu_stats_runtime_counter_unavailable(
+        self, open_file, glob, readlink
+    ):
+        assert get_openvino_npu_stats() is None
+        open_file.assert_called_once_with(
+            "/sys/class/accel/accel0/device/power/runtime_active_time"
+        )
+
     @patch("frigate.stats.intel_gpu_info.intel_gpu_name_resolver.get_names")
     @patch("frigate.util.services.time.sleep")
     @patch("frigate.util.services.time.monotonic")

frigate/test/test_profiles.py

@@ -560,6 +560,25 @@ class TestProfileManager(unittest.TestCase):
         assert err is None
         assert self.config.cameras["front"].enabled is False
 
+    @patch.object(ProfileManager, "_persist_active_profile")
+    def test_profile_can_disable_inherited_birdseye_activity(self, mock_persist):
+        """A false-only mode override inherits the other base activity types."""
+        self.config.profiles["away"] = ProfileDefinitionConfig(friendly_name="Away")
+        base_mode = self.config.cameras["front"].birdseye.mode
+        base_mode.motion = True
+        base_mode.objects = True
+        self.config.cameras["front"].profiles["away"] = CameraProfileConfig(
+            birdseye={"mode": {"motion": False}}
+        )
+        self.manager = ProfileManager(self.config, self.mock_updater)
+
+        err = self.manager.activate_profile("away")
+
+        assert err is None
+        mode = self.config.cameras["front"].birdseye.mode
+        assert not mode.motion
+        assert mode.objects
+
     @patch.object(ProfileManager, "_persist_active_profile")
     def test_deactivate_restores_enabled(self, mock_persist):
         """Deactivating a profile restores the camera's base enabled state."""

frigate/util/builtin.py

@@ -472,6 +472,18 @@ def sanitize_float(value):
     return value
 
 
+def has_non_finite_number(value: Any) -> bool:
+    """Return True if any number in a parsed JSON value is NaN or infinite."""
+    if isinstance(value, float):
+        return not math.isfinite(value)
+    if isinstance(value, dict):
+        return any(has_non_finite_number(v) for v in value.values())
+    if isinstance(value, list):
+        return any(has_non_finite_number(v) for v in value)
+
+    return False
+
+
 def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float:
     return 1 - cosine_distance(a, b)
 

frigate/util/config.py

@@ -20,7 +20,7 @@ from frigate.util.services import get_video_properties
 
 logger = logging.getLogger(__name__)
 
-CURRENT_CONFIG_VERSION = "0.18-0"
+CURRENT_CONFIG_VERSION = "0.19-0"
 DEFAULT_CONFIG_FILE = os.path.join(CONFIG_DIR, "config.yml")
 
 
@@ -93,6 +93,7 @@ def migrate_frigate_config(config_file: str):
 
     logger.info("copying config as backup...")
     shutil.copy(config_file, os.path.join(CONFIG_DIR, "backup_config.yaml"))
+    new_config = config
 
     if previous_version < "0.14":
         logger.info(f"Migrating frigate config from {previous_version} to 0.14...")
@@ -147,6 +148,13 @@ def migrate_frigate_config(config_file: str):
             yaml.dump(new_config, f)
         previous_version = "0.18-0"
 
+    if previous_version < "0.19-0":
+        logger.info(f"Migrating frigate config from {previous_version} to 0.19-0...")
+        new_config = migrate_019_0(new_config)
+        with open(config_file, "w") as f:
+            yaml.dump(new_config, f)
+        previous_version = "0.19-0"
+
     logger.info("Finished frigate config migration...")
 
 
@@ -525,6 +533,21 @@ def _convert_legacy_mask_to_dict(
     return result
 
 
+def _migrate_birdseye_mode(birdseye: dict[str, Any] | None) -> None:
+    """Convert a scalar Birdseye mode to composable activity types."""
+    if not birdseye or not isinstance(birdseye.get("mode"), str):
+        return
+
+    legacy_mode = birdseye["mode"]
+    activity_types = ("continuous", "motion", "objects", "stationary_objects")
+    if legacy_mode not in activity_types:
+        return
+
+    birdseye["mode"] = {
+        activity_type: activity_type == legacy_mode for activity_type in activity_types
+    }
+
+
 def migrate_018_0(config: dict[str, dict[str, Any]]) -> dict[str, dict[str, Any]]:
     """Handle migrating frigate config to 0.18-0"""
     new_config = config.copy()
@@ -658,6 +681,26 @@ def migrate_018_0(config: dict[str, dict[str, Any]]) -> dict[str, dict[str, Any]
     return new_config
 
 
+def migrate_019_0(config: dict[str, dict[str, Any]]) -> dict[str, dict[str, Any]]:
+    """Handle migrating Frigate config to 0.19-0."""
+    new_config = config.copy()
+
+    _migrate_birdseye_mode(new_config.get("birdseye"))
+
+    for name, camera in new_config.get("cameras", {}).items():
+        camera_config: dict[str, dict[str, Any]] = camera.copy()
+        _migrate_birdseye_mode(camera_config.get("birdseye"))
+
+        for profile in camera_config.get("profiles", {}).values():
+            if isinstance(profile, dict):
+                _migrate_birdseye_mode(profile.get("birdseye"))
+
+        new_config["cameras"][name] = camera_config
+
+    new_config["version"] = "0.19-0"
+    return new_config
+
+
 def get_relative_coordinates(
     mask: str | list | None,
     frame_shape: tuple[int, int],

frigate/util/object_names.py

@@ -0,0 +1,209 @@
+"""Aggregation of the known sub label names an object can be tagged with."""
+
+import logging
+import os
+
+from pathvalidate import sanitize_filename
+
+from frigate.config import FrigateConfig
+from frigate.config.classification import ObjectClassificationType
+from frigate.const import CLIPS_DIR, FACE_DIR, MODEL_CACHE_DIR
+from frigate.util.builtin import load_labels
+
+logger = logging.getLogger(__name__)
+
+# subdirectory of FACE_DIR holding unassigned training images, not a face name
+FACE_TRAIN_DIR = "train"
+
+# category used by classification models for "no match", never attached to an object
+CLASSIFICATION_NONE_CATEGORY = "none"
+
+
+def get_categorized_object_names(
+    config: FrigateConfig,
+    allowed_cameras: list[str],
+    object_type: str | None = None,
+) -> dict[str, list[str]]:
+    """Collect every sub label name this install can attach, by object type.
+
+    Unlike the database-backed /sub_labels endpoint, this reads the config and
+    model files, so it also covers names that are configured but have not been
+    detected yet. Names come from the detector's logo attributes (limited to
+    objects the allowed cameras actually track), LPR known plate names,
+    registered face names, and custom object classification categories.
+
+    Structural attributes such as `face` and `license_plate` are excluded: they
+    describe a part of an object rather than naming it, and are never attached
+    as a sub label.
+
+    Args:
+        config: The running Frigate config
+        allowed_cameras: Cameras the requesting user may see
+        object_type: Optional object label to restrict the result to
+
+    Returns:
+        Mapping of object label to its known sub label names, sorted and
+        deduplicated. Object types with no known names are omitted.
+    """
+    tracked_objects = _get_tracked_objects(config, allowed_cameras)
+    names: dict[str, set[str]] = {}
+    logos = set(config.model.all_attribute_logos)
+
+    # 1. detector logo attributes, only for objects that are actually tracked
+    for label, label_attributes in config.model.attributes_map.items():
+        if label not in tracked_objects:
+            continue
+
+        label_logos = logos.intersection(label_attributes)
+
+        if label_logos:
+            names.setdefault(label, set()).update(label_logos)
+
+    # 2. LPR known plate names, for objects that can carry a plate
+    if config.lpr.known_plates and _lpr_enabled(config, allowed_cameras):
+        known_plates = set(config.lpr.known_plates)
+
+        for label in _objects_with_attribute(config, tracked_objects, "license_plate"):
+            names.setdefault(label, set()).update(known_plates)
+
+    # 3. registered face names, for objects that can carry a face
+    if _face_recognition_enabled(config, allowed_cameras):
+        face_names = _get_face_names()
+
+        if face_names:
+            for label in _objects_with_attribute(config, tracked_objects, "face"):
+                names.setdefault(label, set()).update(face_names)
+
+    # 4. custom object classification categories
+    for model_key, model_config in config.classification.custom.items():
+        if not model_config.enabled or model_config.object_config is None:
+            continue
+
+        if (
+            model_config.object_config.classification_type
+            != ObjectClassificationType.sub_label
+        ):
+            continue
+
+        categories = _get_classification_categories(model_key)
+
+        if not categories:
+            continue
+
+        for label in model_config.object_config.objects:
+            names.setdefault(label, set()).update(categories)
+
+    return {
+        label: sorted(label_names)
+        for label, label_names in sorted(names.items())
+        if label_names and (object_type is None or label == object_type)
+    }
+
+
+def _get_tracked_objects(config: FrigateConfig, allowed_cameras: list[str]) -> set[str]:
+    """Get the union of objects tracked by the cameras the user can see."""
+    tracked: set[str] = set()
+
+    for camera_name in allowed_cameras:
+        camera_config = config.cameras.get(camera_name)
+
+        if camera_config is None:
+            continue
+
+        tracked.update(camera_config.objects.track)
+
+    return tracked
+
+
+def _objects_with_attribute(
+    config: FrigateConfig, tracked_objects: set[str], attribute: str
+) -> set[str]:
+    """Get the tracked objects that a given attribute can be recognized on.
+
+    The attribute may also be tracked as an object in its own right, as
+    `license_plate` is on a dedicated LPR camera, in which case the name is
+    attached to that object directly.
+    """
+    objects = {
+        label
+        for label, label_attributes in config.model.attributes_map.items()
+        if attribute in label_attributes and label in tracked_objects
+    }
+
+    if attribute in tracked_objects:
+        objects.add(attribute)
+
+    return objects
+
+
+def _lpr_enabled(config: FrigateConfig, allowed_cameras: list[str]) -> bool:
+    return any(
+        config.cameras[camera_name].lpr.enabled
+        for camera_name in allowed_cameras
+        if camera_name in config.cameras
+    )
+
+
+def _face_recognition_enabled(
+    config: FrigateConfig, allowed_cameras: list[str]
+) -> bool:
+    return any(
+        config.cameras[camera_name].face_recognition.enabled
+        for camera_name in allowed_cameras
+        if camera_name in config.cameras
+    )
+
+
+def _get_face_names() -> set[str]:
+    """Get the names of every registered face collection."""
+    if not os.path.exists(FACE_DIR):
+        return set()
+
+    try:
+        entries = os.listdir(FACE_DIR)
+    except OSError:
+        logger.debug("Failed to read face directory %s", FACE_DIR)
+        return set()
+
+    return {
+        name
+        for name in entries
+        if name != FACE_TRAIN_DIR and os.path.isdir(os.path.join(FACE_DIR, name))
+    }
+
+
+def _get_classification_categories(model_key: str) -> set[str]:
+    """Get the categories a custom classification model can output.
+
+    The trained labelmap is authoritative, but it only exists once the model
+    has been trained, so fall back to the dataset directories that will become
+    the labelmap on the next training run.
+    """
+    safe_key = sanitize_filename(model_key)
+    categories: set[str] = set()
+    labelmap_path = os.path.join(MODEL_CACHE_DIR, safe_key, "labelmap.txt")
+
+    if os.path.exists(labelmap_path):
+        try:
+            labelmap = load_labels(labelmap_path, prefill=0, indexed=False)
+        except OSError:
+            logger.debug("Failed to read labelmap %s", labelmap_path)
+            labelmap = {}
+
+        categories.update(label for label in labelmap.values() if label)
+
+    dataset_dir = os.path.join(CLIPS_DIR, safe_key, "dataset")
+
+    if os.path.exists(dataset_dir):
+        try:
+            entries = os.listdir(dataset_dir)
+        except OSError:
+            logger.debug("Failed to read dataset directory %s", dataset_dir)
+            entries = []
+
+        categories.update(
+            name for name in entries if os.path.isdir(os.path.join(dataset_dir, name))
+        )
+
+    categories.discard(CLASSIFICATION_NONE_CATEGORY)
+    return categories

frigate/util/services.py

@@ -1,6 +1,7 @@
 """Utilities for services."""
 
 import asyncio
+import glob
 import json
 import logging
 import os
@@ -670,19 +671,33 @@ def get_intel_gpu_stats(
 
 def get_openvino_npu_stats() -> dict[str, str] | None:
     """Get NPU stats using openvino."""
-    NPU_RUNTIME_PATH = "/sys/devices/pci0000:00/0000:00:0b.0/power/runtime_active_time"
+    for accel_path in sorted(glob.glob("/sys/class/accel/accel*")):
+        try:
+            driver = os.path.basename(os.readlink(f"{accel_path}/device/driver"))
+        except OSError:
+            continue
+
+        if driver != "intel_vpu":
+            continue
+
+        try:
+            runtime_path = f"{accel_path}/device/power/runtime_active_time"
+            with open(runtime_path) as f:
+                initial_runtime = float(f.read().strip())
+            break
+        except (FileNotFoundError, PermissionError, ValueError):
+            continue
+    else:
+        return None
 
     try:
-        with open(NPU_RUNTIME_PATH) as f:
-            initial_runtime = float(f.read().strip())
-
         initial_time = time.time()
 
         # Sleep for 1 second to get an accurate reading
         time.sleep(1.0)
 
         # Read runtime value again
-        with open(NPU_RUNTIME_PATH) as f:
+        with open(runtime_path) as f:
             current_runtime = float(f.read().strip())
 
         current_time = time.time()

testing-scripts/face_dataset.py

@@ -36,8 +36,8 @@ from __future__ import annotations
 import argparse
 import os
 import sys
+from collections.abc import Iterable
 from dataclasses import dataclass
-from typing import Iterable
 
 import cv2
 import numpy as np
@@ -53,21 +53,31 @@ ARCFACE_INPUT_SIZE = 112
 # ---------------------------------------------------------------------------
 
 
+def _bgr_to_rgb(frame: np.ndarray) -> np.ndarray:
+    """Mirror BaseEmbedding._bgr_to_rgb."""
+    if isinstance(frame, np.ndarray) and frame.ndim == 3:
+        return np.ascontiguousarray(frame[:, :, ::-1])
+
+    return frame
+
+
 def _process_image_frigate(image: np.ndarray) -> Image.Image:
     """Mirror BaseEmbedding._process_image for an ndarray input.
 
-    NOTE: Frigate passes the output of `cv2.imread` (BGR) directly in. PIL's
-    `Image.fromarray` does NOT reorder channels, so the embedder effectively
-    receives a BGR-ordered tensor. We replicate that faithfully here. (Tested
-    — swapping to RGB produces near-identical embeddings; this model is
-    robust to channel order.)
+    `Image.fromarray` does not reorder channels, so whatever order it is
+    handed is what reaches the model. Callers swap to RGB first, exactly as
+    ArcfaceEmbedding._preprocess_inputs does.
     """
     return Image.fromarray(image)
 
 
 def arcface_preprocess(image_bgr: np.ndarray) -> np.ndarray:
-    """Mirror ArcfaceEmbedding._preprocess_inputs."""
-    pil = _process_image_frigate(image_bgr)
+    """Mirror ArcfaceEmbedding._preprocess_inputs.
+
+    Face crops arrive BGR from cv2 and #23712 added the swap to RGB before
+    embedding, so this script has to do it too.
+    """
+    pil = _process_image_frigate(_bgr_to_rgb(image_bgr))
 
     width, height = pil.size
     if width != ARCFACE_INPUT_SIZE or height != ARCFACE_INPUT_SIZE:
@@ -138,9 +148,7 @@ class LandmarkAligner:
         M[0, 2] += tX - eyesCenter[0]
         M[1, 2] += tY - eyesCenter[1]
 
-        aligned = cv2.warpAffine(
-            image, M, (out_w, out_h), flags=cv2.INTER_CUBIC
-        )
+        aligned = cv2.warpAffine(image, M, (out_w, out_h), flags=cv2.INTER_CUBIC)
         info = dict(
             angle=float(angle),
             eye_dist_px=dist,
@@ -433,9 +441,7 @@ def vector_outlier_test(
         if neg
         else np.array([])
     )
-    baseline_conf_neg = np.array(
-        [similarity_to_confidence(c) for c in baseline_neg]
-    )
+    baseline_conf_neg = np.array([similarity_to_confidence(c) for c in baseline_neg])
 
     print(
         f"\nBaseline (trim_mean only, {len(pos)} images):"
@@ -465,9 +471,7 @@ def vector_outlier_test(
         mean, keep = iterative_mean(all_embs, T)
         pos_sims = np.array([cosine(p.embedding, mean) for p in pos])
         neg_sims = (
-            np.array([cosine(n.embedding, mean) for n in neg])
-            if neg
-            else np.array([])
+            np.array([cosine(n.embedding, mean) for n in neg]) if neg else np.array([])
         )
         neg_conf = np.array([similarity_to_confidence(c) for c in neg_sims])
         margin = pos_sims.min() - (neg_sims.max() if len(neg_sims) else 0)
@@ -483,9 +487,7 @@ def vector_outlier_test(
     # Show which images get dropped at the shipped threshold + neighbors
     for T_show in (0.25, 0.30, 0.33):
         _, keep = iterative_mean(all_embs, T_show)
-        print(
-            f"\nAt T={T_show}, the {int((~keep).sum())} dropped positives are:"
-        )
+        print(f"\nAt T={T_show}, the {int((~keep).sum())} dropped positives are:")
         final_mean = stats.trim_mean(all_embs[keep], base_trim, axis=0)
         m_n = final_mean / (np.linalg.norm(final_mean) + 1e-9)
         for i, (p, k) in enumerate(zip(pos, keep)):
@@ -501,9 +503,7 @@ def vector_outlier_test(
                 )
 
 
-def degenerate_embedding_test(
-    pos: list[FaceSample], neg: list[FaceSample]
-) -> None:
+def degenerate_embedding_test(pos: list[FaceSample], neg: list[FaceSample]) -> None:
     """Detect whether negatives and low-quality positives share a degenerate
     'tiny/noisy face' region of the embedding space.
 
@@ -533,8 +533,7 @@ def degenerate_embedding_test(
         f"(how tightly negatives cluster together)"
     )
     print(
-        f"  pos<->pos mean cos : {np.nanmean(pp):.3f}   "
-        f"(how tightly positives cluster)"
+        f"  pos<->pos mean cos : {np.nanmean(pp):.3f}   (how tightly positives cluster)"
     )
     print(
         f"  pos<->neg mean cos : {pn.mean():.3f}   "
@@ -558,11 +557,7 @@ def degenerate_embedding_test(
         neg_scores = np.array([cosine(n.embedding, clean_mean) for n in neg])
         neg_confs = np.array([similarity_to_confidence(c) for c in neg_scores])
         pos_scores = np.array(
-            [
-                cosine(pos[i].embedding, clean_mean)
-                for i in range(len(pos))
-                if keep[i]
-            ]
+            [cosine(pos[i].embedding, clean_mean) for i in range(len(pos)) if keep[i]]
         )
         print(
             f"\n  mean_intra >= {thresh}: keeping {int(keep.sum())}/{len(pos)} positives"
@@ -585,9 +580,7 @@ def degenerate_embedding_test(
         )
 
 
-def contamination_analysis(
-    pos: list[FaceSample], neg: list[FaceSample]
-) -> None:
+def contamination_analysis(pos: list[FaceSample], neg: list[FaceSample]) -> None:
     """Check whether the positive collection contains a second identity.
 
     Two signals:
@@ -617,10 +610,7 @@ def contamination_analysis(
         "\nPositives closer to a negative than to their own class avg"
         "\n(these are candidates for mislabeled images):"
     )
-    print(
-        f"\n{'max_neg':>7}  {'mean_neg':>8}  {'mean_intra':>10}  "
-        f"{'delta':>6}  name"
-    )
+    print(f"\n{'max_neg':>7}  {'mean_neg':>8}  {'mean_intra':>10}  {'delta':>6}  name")
     rows = list(zip(pos_names, max_to_neg, mean_to_neg, mean_intra))
     rows.sort(key=lambda r: -(r[1] - r[3]))
     for nm, mxn, mnn, mi in rows[:15]:
@@ -704,7 +694,9 @@ def main() -> int:
         formatter_class=argparse.RawDescriptionHelpFormatter,
         epilog=__doc__,
     )
-    ap.add_argument("--positive", required=True, help="Training folder for one identity")
+    ap.add_argument(
+        "--positive", required=True, help="Training folder for one identity"
+    )
     ap.add_argument(
         "--negative",
         default=None,

web/public/locales/ca/components/dialog.json

@@ -61,7 +61,8 @@
       "error": {
         "endTimeMustAfterStartTime": "L'hora de finalització ha de ser posterior a l'hora d'inici",
         "noVaildTimeSelected": "No s'ha seleccionat un rang de temps vàlid",
-        "failed": "No s'ha pogut inciar l'exportació: {{error}}"
+        "failed": "No s'ha pogut inciar l'exportació: {{error}}",
+        "noValidTimeSelected": "No s'ha seleccionat cap interval de temps vàlid"
       },
       "view": "Vista",
       "queued": "Exporta a la cua. Mostra el progrés a la pàgina d'exportacions.",

web/public/locales/ca/config/cameras.json

@@ -493,6 +493,9 @@
             "max_concurrent": {
                 "label": "Màxim d'exportacions concurrents",
                 "description": "Nombre màxim de treballs d'exportació a processar al mateix temps."
+            },
+            "chapters": {
+                "label": "Metadades de capítol per incrustar en els enregistraments exportats"
             }
         },
         "preview": {

web/public/locales/ca/config/global.json

@@ -380,6 +380,9 @@
             "max_concurrent": {
                 "label": "Màxim d'exportacions concurrents",
                 "description": "Nombre màxim de treballs d'exportació a processar al mateix temps."
+            },
+            "chapters": {
+                "label": "Metadades de capítol per incrustar en els enregistraments exportats"
             }
         },
         "preview": {
@@ -1917,7 +1920,7 @@
             },
             "model_type": {
                 "label": "Tipus de Model de detecció d'objecte",
-                "description": "Tipus d'arquitectura del model de detector (ssd, yolox, yolonas) usat per l'optimització d'alguns detectors."
+                "description": "Tipus d'arquitectura del model de detector (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) utilitzat per alguns detectors per a l'optimització"
             }
         },
         "model_path": {
@@ -1966,7 +1969,7 @@
         },
         "model_type": {
             "label": "Tipus de model de detecció d'objectes",
-            "description": "Tipus d'arquitectura del model de detector (ssd, yolox, yolonas) utilitzat per alguns detectors per a l'optimització."
+            "description": "Tipus d'arquitectura del model de detector (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) utilitzat per alguns detectors per a l'optimització."
         }
     },
     "genai": {

web/public/locales/ca/views/classificationModel.json

@@ -192,7 +192,20 @@
     "title": "Edita el model de classificació",
     "descriptionState": "Edita les classes per a aquest model de classificació d'estats. Els canvis requeriran tornar a entrenar el model.",
     "descriptionObject": "Edita el tipus d'objecte i el tipus de classificació per a aquest model de classificació d'objectes.",
-    "stateClassesInfo": "Nota: Canviar les classes d'estat requereix tornar a entrenar el model amb les classes actualitzades."
+    "stateClassesInfo": "S'ha actualitzat el model. Restringeix el model perquè els canvis de classe tinguin efecte.",
+    "enabled": "Habilitat",
+    "enabledDesc": "Executa aquest model. Quan està desactivat, deixa d'executar-se i ja no classifica.",
+    "saveAttempts": "Desa els intents",
+    "saveAttemptsDesc": "Nombre d'imatges de classificació que s'intenten mantenir per a les classificacions recents UI.",
+    "motion": "Executa en moviment",
+    "motionDesc": "Executa la classificació quan es detecta el moviment dins de l'escapçat configurat.",
+    "interval": "Interval",
+    "intervalDesc": "Segons entre les classificacions periòdiques. Deixeu-ho buit per a executar-se només en moviment.",
+    "intervalPlaceholder": "Sense interval",
+    "errors": {
+      "saveAttemptsInvalid": "Els intents de desar han de ser un nombre sencer de 0 o més",
+      "intervalInvalid": "L'interval ha de ser un nombre sencer més gran que 0"
+    }
   },
   "tooltip": {
     "trainingInProgress": "El model s'està entrenant actualment",
@@ -202,5 +215,6 @@
   },
   "none": "Cap",
   "reclassifyImageAs": "Reclassifica la imatge com a:",
-  "reclassifyImage": "Reclassifica la imatge"
+  "reclassifyImage": "Reclassifica la imatge",
+  "disabled": "Desactivat"
 }

web/public/locales/ca/views/explore.json

@@ -303,7 +303,7 @@
       },
       "offset": {
         "label": "Òfset d'Anotació",
-        "desc": "Aquestes dades provenen del flux de detecció de la càmera, però se superposen a les imatges del flux de gravació. És poc probable que els dos fluxos estiguin perfectament sincronitzats. Com a resultat, el quadre delimitador i les imatges no s'alinearan perfectament. Tanmateix, es pot utilitzar el camp <code>annotation_offset</code> per ajustar-ho.",
+        "desc": "Aquestes dades provenen del canal de detecció de la càmera, però estan sobreposades a les imatges del canal de registre. És poc probable que els dos corrents estiguin perfectament sincronitzats. Com a resultat, la caixa contenidora i les imatges no s'alinearan perfectament. Podeu utilitzar aquest paràmetre per a compensar les anotacions cap endavant o cap enrere en el temps per a alinear-les millor amb el metratge gravat.",
         "millisecondsToOffset": "Millisegons per l'òfset de detecció d'anotacions per. <em>Per defecte: 0</em>",
         "tips": "Reduïu el valor si la reproducció del vídeo es troba per davant dels quadres i els punts de ruta, i augmenteu-lo si es troba per darrere. Aquest valor pot ser negatiu.",
         "toast": {

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

@@ -698,7 +698,7 @@
         "title": "Crear un nou usuari",
         "confirmPassword": "Siusplau, confirma la contrasenya",
         "usernameOnlyInclude": "El nom d'usuari només pot contenir lletres, números, . o _",
-        "desc": "Afegeix un nou compte d'usuari i especifica un rol per accedir a àrees de la interfície de Frigate."
+        "desc": "Afegeix un compte d'usuari nou i especifica un rol per a l'accés a les àrees de la interfície d'usuari de Frigate."
       }
     },
     "title": "Usuaris",
@@ -1323,7 +1323,7 @@
       "details": {
         "edit": "Edita els detalls de la càmera",
         "title": "Edita els detalls de la càmera",
-        "description": "Actualitza el nom de visualització, l'URL extern i la visibilitat utilitzada per a aquesta càmera a tota la interfície d'usuari de la Fragata.",
+        "description": "Actualitza el nom de visualització, l'URL extern i la visibilitat utilitzada per a aquesta càmera a tota la interfície d'usuari de Frigate.",
         "friendlyNameLabel": "Nom a mostrar",
         "friendlyNameHelp": "Nom amistós que es mostra per a aquesta càmera a tota la interfície d'usuari de Frigate. Deixeu-ho en blanc per utilitzar l'ID de la càmera.",
         "webuiUrlLabel": "URL de la interfície web de la càmera",
@@ -1484,7 +1484,7 @@
         "successMulti_other": "Configuració copiada a {{count}} càmeres",
         "successMultiWithRestart_one": "Configuració copiada a la càmera {{count}}. Reinicia Frigate per aplicar tots els canvis.",
         "successMultiWithRestart_many": "Configuració copiada a {{count}} càmeres. Reinicia Frigate per aplicar tots els canvis.",
-        "successMultiWithRestart_other": "Configuració copiada a {{count}} càmeres. Reinicia la fragata per aplicar tots els canvis.",
+        "successMultiWithRestart_other": "Configuració copiada a {{count}} càmeres. Reinicia Frigate per aplicar tots els canvis.",
         "partialFailure": "{{successCount}} seccions aplicades; «{{failedSection}}» ha fallat: {{errorMessage}}",
         "partialFailureMulti": "S'ha copiat a {{successCount}} càmera(es); ha fallat {{failed}}: {{errorMessage}}",
         "newCameraPartialFailure": "S'ha creat la càmera {{cameraName}} però no s'han pogut copiar alguns paràmetres: {{errorMessage}}",
@@ -1641,7 +1641,14 @@
       "keyLabel": "Clau",
       "valueLabel": "Valor",
       "keyPlaceholder": "Nou valor",
-      "remove": "Elimina"
+      "remove": "Elimina",
+      "providerNameLabel": "Nom del proveïdor",
+      "providerNamePlaceholder": "p. ex., openai",
+      "variableNameLabel": "Nom de la variable",
+      "variableNamePlaceholder": ". ex., La_Meva_Variable",
+      "loggerNameLabel": "Nom del registrador",
+      "loggerNamePlaceholder": "p. ex., friagte.registre",
+      "keyPatternError": "Utilitza només lletres, números, guions i guions baixos (sense espais)"
     },
     "timezone": {
       "defaultOption": "Utilitza la zona horària del navegador"
@@ -2096,7 +2103,8 @@
       "autotrackingNoZones": "Autotraquejar requereix al menys una zona. Defineix una zona per aquesta cámera a Mascares/Zones, després usa'l com a requerit a la part inferior."
     },
     "ffmpeg": {
-      "hwaccelManualNotRecommended": "No es recomanen arguments manuals d'acceleració de maquinari. Tret que existeixi un requisit específic, seleccioneu el predefinit que coincideixi amb el vostre maquinari."
+      "hwaccelManualNotRecommended": "No es recomanen arguments manuals d'acceleració de maquinari. Tret que existeixi un requisit específic, seleccioneu el predefinit que coincideixi amb el vostre maquinari.",
+      "inputsMissingGo2rtcStream": "Una entrada a sota apunta a un restream go2rtc que ja no existeix. Seleccioneu un restream existent o introduïu manualment l'URL de la càmera, en cas contrari aquesta càmera no es connectarà."
     },
     "model": {
       "optimizedFor320": "Frigate està optimitzada per a un model 320x320, que és la millor opció per a la majoria de configuracions. Un model 640x640 és més lent i només ajuda en escenaris específics.",

web/public/locales/cs/audio.json

@@ -425,5 +425,23 @@
   "chop": "Sekání",
   "crack": "Prasknutí",
   "chink": "Cinknutí",
-  "field_recording": "Nahrávka z terénu"
+  "field_recording": "Nahrávka z terénu",
+  "change_ringing": "Změnit vyzvánění",
+  "liquid": "Tekutina",
+  "splash": "Šplouchnutí",
+  "squish": "Zmáčknout",
+  "drip": "Kapat",
+  "pour": "Lít",
+  "trickle": "Stékat",
+  "fill": "Naplnit",
+  "stir": "Míchat",
+  "boiling": "Vařící",
+  "sonar": "Sonar",
+  "arrow": "Šíp",
+  "electronic_tuner": "Elektronický Ladič",
+  "bang": "Rána",
+  "slap": "Plácnout",
+  "smash": "Rozmlátit",
+  "bouncing": "Odrážející",
+  "scratch": "Škrábat"
 }

web/public/locales/en/config/cameras.json

@@ -71,8 +71,24 @@
       "description": "Enable or disable the Birdseye view feature."
     },
     "mode": {
-      "label": "Tracking mode",
-      "description": "Mode for including cameras in Birdseye: 'objects', 'motion', or 'continuous'."
+      "label": "Activity types",
+      "description": "Activity types that include cameras in Birdseye.",
+      "continuous": {
+        "label": "Continuous",
+        "description": "Always include the camera in Birdseye."
+      },
+      "motion": {
+        "label": "Motion",
+        "description": "Include the camera in Birdseye when motion is detected."
+      },
+      "objects": {
+        "label": "Active objects",
+        "description": "Include the camera in Birdseye while an active object is tracked."
+      },
+      "stationary_objects": {
+        "label": "Stationary objects",
+        "description": "Include the camera in Birdseye while a stationary object is tracked."
+      }
     },
     "order": {
       "label": "Position",

web/public/locales/en/config/global.json

@@ -574,8 +574,24 @@
       "description": "Enable or disable the Birdseye view feature."
     },
     "mode": {
-      "label": "Tracking mode",
-      "description": "Mode for including cameras in Birdseye: 'objects', 'motion', or 'continuous'."
+      "label": "Activity types",
+      "description": "Activity types that include cameras in Birdseye.",
+      "continuous": {
+        "label": "Continuous",
+        "description": "Always include the camera in Birdseye."
+      },
+      "motion": {
+        "label": "Motion",
+        "description": "Include the camera in Birdseye when motion is detected."
+      },
+      "objects": {
+        "label": "Active objects",
+        "description": "Include the camera in Birdseye while an active object is tracked."
+      },
+      "stationary_objects": {
+        "label": "Stationary objects",
+        "description": "Include the camera in Birdseye while a stationary object is tracked."
+      }
     },
     "restream": {
       "label": "Restream RTSP",

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

@@ -1956,7 +1956,7 @@
       "noRecordRole": "No streams have the record role defined. Recording will not function."
     },
     "birdseye": {
-      "objectsModeDetectDisabled": "Birdseye is set to 'objects' mode, but object detection is disabled for this camera. The camera will not appear in Birdseye."
+      "objectTrackingDetectDisabled": "Birdseye includes tracked objects, but object detection is disabled for this camera. The camera will not appear in Birdseye."
     },
     "snapshots": {
       "detectDisabled": "Object detection is disabled. Snapshots are generated from tracked objects and will not be created."

web/public/locales/es/components/dialog.json

@@ -36,6 +36,9 @@
           "ask_a": "¿Es este objeto un <code>{{label}}</code>?",
           "ask_an": "¿Es este objeto un <code>{{label}}</code>?",
           "ask_full": "¿Es este objeto un <code>{{untranslatedLabel}}</code> ({{translatedLabel}})?"
+        },
+        "toast": {
+          "error": "Error al enviarlo a Frigate+. Por favor, comprueba tu conexión a internet y prueba de nuevo."
         }
       }
     },
@@ -68,7 +71,8 @@
       "error": {
         "failed": "No se pudo iniciar la exportación: {{error}}",
         "noVaildTimeSelected": "No se seleccionó un rango de tiempo válido",
-        "endTimeMustAfterStartTime": "La hora de finalización debe ser posterior a la hora de inicio"
+        "endTimeMustAfterStartTime": "La hora de finalización debe ser posterior a la hora de inicio",
+        "noValidTimeSelected": "Rango de tiempo seleccionado no valido"
       },
       "success": "Exportación iniciada con éxito. Ver el archivo en la página exportaciones.",
       "view": "Vista",

web/public/locales/et/audio.json

@@ -273,5 +273,69 @@
   "sailboat": "Purjekas",
   "soundtrack_music": "Filmimuusika",
   "jingle": "Kõlisemine/tilisemine",
-  "theme_music": "Tunnusmuusika"
+  "theme_music": "Tunnusmuusika",
+  "steel_guitar": "Steel Kitarr",
+  "tapping": "Koputamine",
+  "strum": "Klimberdus",
+  "drum_machine": "Trummimasin",
+  "drum": "Trumm",
+  "maraca": "Marakas",
+  "bowed_string_instrument": "Poogenkeelpill",
+  "singing_bowl": "Helikauss",
+  "wind_noise": "Tuulemüra",
+  "rustling_leaves": "Sahisevad lehed",
+  "waves": "Lained",
+  "steam": "Aur",
+  "ship": "Laev",
+  "motor_vehicle": "Mootorsõiduk",
+  "rowboat": "Sõudepaat",
+  "motorboat": "Mootorpaat",
+  "waterfall": "Kosk",
+  "ocean": "Ookean",
+  "rain_on_surface": "Vihm pinnal",
+  "stream": "Oja",
+  "fire": "Tuli",
+  "crackle": "Praksumine",
+  "car_alarm": "Auto alarm",
+  "truck": "Veoauto",
+  "police_car": "Politseiauto",
+  "ambulance": "Kiirabi",
+  "fire_engine": "Tuletõrjeauto",
+  "aircraft": "Lennuk",
+  "aircraft_engine": "Lennukimootor",
+  "jet_engine": "Reaktiivmootor",
+  "propeller": "Propeller",
+  "helicopter": "Helikopter",
+  "fixed-wing_aircraft": "Fikseeritud tiivaga õhusõiduk",
+  "train_horn": "Rongisignaal",
+  "railroad_car": "Kaubavagun",
+  "lawn_mower": "Muruniiduk",
+  "chainsaw": "mootorsaag",
+  "engine": "Mootor",
+  "knock": "Koputus",
+  "alarm": "Häire",
+  "siren": "Sireen",
+  "fire_alarm": "Tulekahjuhäire",
+  "telephone": "Telefon",
+  "telephone_bell_ringing": "Helisev telefon",
+  "ringtone": "Telefonihelin",
+  "smoke_detector": "Suitsuandur",
+  "foghorn": "Udupasun",
+  "whistle": "Vile",
+  "printer": "Printer",
+  "drill": "Puur",
+  "explosion": "Plahvatus",
+  "hammer": "Haamer",
+  "air_conditioning": "Õhukonditsioneer",
+  "gunshot": "Püssilask",
+  "glass": "Klaas",
+  "boom": "Pauk",
+  "fireworks": "Ilutulestik",
+  "static": "Staatiline",
+  "white_noise": "Valge müra",
+  "radio": "Raadio",
+  "television": "Televiisor",
+  "scream": "Karjumine",
+  "pour": "Valamine",
+  "drip": "Tilkumine"
 }

web/public/locales/et/components/dialog.json

@@ -37,6 +37,9 @@
           "ask_an": "Kas see objekt on <code>{{label}}</code>?",
           "ask_full": "Kas see objekt on <code>{{untranslatedLabel}}</code> ({{translatedLabel}})?",
           "label": "Kinnita see silt Frigate+ teenuse jaoks"
+        },
+        "toast": {
+          "error": "Frigate+ teenusesse saatmine ebaõnnestus. Palun kontrolli oma võrguühendust ja proovi uuesti."
         }
       },
       "submitToPlus": {
@@ -70,18 +73,79 @@
       "success": "Eksportimise käivitamine õnnestus. Faili leiad eksportimise lehelt.",
       "view": "Vaata",
       "error": {
-        "failed": "Eksportimise käivitamine ei õnnestunud: {{error}}",
+        "failed": "Eksportimise järjekorda lisamine ei õnnestunud: {{error}}",
         "endTimeMustAfterStartTime": "Ajavahemiku lõpp peab olema peale algust",
-        "noVaildTimeSelected": "Ühtegi kehtivat ajavahemikku pole valitud"
-      }
+        "noVaildTimeSelected": "Ühtegi kehtivat ajavahemikku pole valitud",
+        "noValidTimeSelected": "Ühtegi korrektset ajavahemikku pole valitud"
+      },
+      "queued": "Eksport on järjekorda lisatud. Vaata progressi eksportide lehelt.",
+      "batchSuccess_one": "Alustasin 1 ekspordiga. Avan juhtumi kohe.",
+      "batchSuccess_other": "Alustasin {{count}} ekspordiga. Avan juhtumi kohe.",
+      "batchPartial": "Alustasin {{successful}}/{{total}} ekspordiga. Ebaõnnestunud kaamerad: {{failedCameras}}",
+      "batchFailed": "{{total}} eksporti ebaõnnestus algatada. Ebaõnnestunud kaamerad: {{failedCameras}}",
+      "batchQueuedSuccess_one": "1 eksport järjekorda lisatud. Avan juhtumi kohe.",
+      "batchQueuedSuccess_other": "{{count}} eksporti järjekorda lisatud. Avan juhtumi kohe.",
+      "batchQueuedPartial": "{{successful}}/{{total}} ekspordist on järjekorda lisatud. Ebaõnnestunud kaamerad: {{failedCameras}}",
+      "batchQueueFailed": "{{total}} eksporti ebaõnnestus järjekorda lisada. Ebaõnnestunud kaamerad: {{failedCameras}}"
     },
     "fromTimeline": {
       "saveExport": "Salvesta eksporditud sisu",
-      "previewExport": "Eksporditud sisu eelvaade"
+      "previewExport": "Eksporditud sisu eelvaade",
+      "queueingExport": "Ekspordi järjekorda lisamine...",
+      "useThisRange": "Kasuta seda vahemikku"
     },
     "case": {
       "label": "Juhtum",
-      "placeholder": "Vali juhtum"
+      "placeholder": "Vali juhtum",
+      "newCaseOption": "Ava uus juhtum",
+      "newCaseNamePlaceholder": "Uue juhtumi nimi",
+      "newCaseDescriptionPlaceholder": "Juhtumi kirjeldus",
+      "nonAdminHelp": "Uus juhtum avatakse järnevatele eksportidele."
+    },
+    "queueing": "Ekspordi järjekorda lisamine...",
+    "tabs": {
+      "export": "Üksik kaamera",
+      "multiCamera": "Mitu kaamerat"
+    },
+    "multiCamera": {
+      "timeRange": "Ajavahemik",
+      "selectFromTimeline": "Vali ajajoonelt",
+      "cameraSelection": "Kaamerad",
+      "cameraSelectionHelp": "Selles ajavahemikus tuvastatud objektidega kaamerad on eelvalitud",
+      "searchOrSelectGroup": "Otsi või vali kaamera grupp...",
+      "selectAll": "Vali kõik kaamerad",
+      "clearSelection": "Tühista valik",
+      "selectWithActivity": "Jälgitud objektidega kaamerad",
+      "selectGroup": "Vali grupp",
+      "noMatchingCameras": "Ükski kaamera ei sobitunud otsinguga",
+      "selectedCount": "{{selected}} / {{total}} valitud",
+      "checkingActivity": "Kaamera aktiivsuse kontrollimine...",
+      "noCameras": "Ühtegi kaamerat pole saadaval",
+      "detectionCount_one": "1 jälgitav objekt",
+      "detectionCount_other": "{{count}} jälgitavat objekti",
+      "nameLabel": "Ekspordi nimi",
+      "namePlaceholder": "Valikuline baasnimi nendele eksportidele",
+      "queueingButton": "Ekspordi järjekorda lisamine...",
+      "exportButton_one": "Ekspordi 1 kaamera",
+      "exportButton_other": "Ekspordi {{count}} kaamerat"
+    },
+    "multi": {
+      "title_one": "Ekspordi 1 ülevaade",
+      "title_other": "Espordi {{count}} ülevaadet",
+      "description": "Ekspordi valitud ülevaated. Kõik ekspordid on grupeeritud ühte juhtumisse.",
+      "descriptionNoCase": "Ekspordi kõik valitud juhtumid.",
+      "caseNamePlaceholder": "Ülevaate eksport - {{date}}",
+      "exportButton_one": "Ekspordi 1 ülevaade",
+      "exportButton_other": "Ekspordi {{count}} ülevaadet",
+      "exportingButton": "Ekspordin...",
+      "toast": {
+        "started_one": "Alustasin 1 eksporti. Avan juhtumi kohe.",
+        "started_other": "Alustasin {{count}} ekspordiga. Avan juhtumi kohe.",
+        "startedNoCase_one": "Alustasin 1 ekspordiga.",
+        "startedNoCase_other": "Alustasin {{count}} ekspordiga.",
+        "partial": "Alustasin {{successful}}/{{total}} ekspordiga. Ebaõnnestusid: {{failedItems}}",
+        "failed": "{{total}} ekspordi algatamine ebaõnnestus. Ebaõnnestunud: {{failedItems}}"
+      }
     }
   },
   "streaming": {
@@ -114,6 +178,14 @@
         "success": "Selle ülevaadatava objektiga seotud videosisu on kustutatud.",
         "error": "Kustutamine ei õnnestunud: {{error}}"
       }
+    },
+    "shareTimestamp": {
+      "label": "Jaotise ajatempel",
+      "title": "Jaotise ajatempel",
+      "description": "Jaga praeguse esituskoha ajatempliga URL-i või vali kohandatud ajatempel. Arvesta, et see ei ole avalik jagamislink ja on kättesaadav ainult kasutajatele, kellel on ligipääs Frigate'ile ja sellele kaamerale.",
+      "custom": "Kohandatud ajatempel",
+      "button": "Jaga ajatempliga linki",
+      "shareTitle": "Frigate ülevaate ajatempel: {{camera}}"
     }
   },
   "imagePicker": {

web/public/locales/et/config/cameras.json

@@ -12,11 +12,20 @@
         "description": "Kasutusel"
     },
     "audio": {
-        "label": "Helisündmused"
+        "label": "Heli tuvastus",
+        "min_volume": {
+            "label": "Minimaalne helitase"
+        },
+        "filters": {
+            "label": "Audio filtrid"
+        }
     },
     "birdseye": {
         "mode": {
             "label": "Jälgimisrežiim"
+        },
+        "order": {
+            "label": "Positsioon"
         }
     },
     "label": "Kaameraseadistus",
@@ -25,7 +34,8 @@
             "threshold": {
                 "description": "Minimaalne sarnasuse punktiskoor (0-1), mis on vajalik selle päästiku käivitamiseks."
             }
-        }
+        },
+        "label": "Semantiline otsing"
     },
     "lpr": {
         "label": "Sõidukite numbrimärkide tuvastus",
@@ -34,6 +44,171 @@
     "review": {
         "genai": {
             "description": "Kontrollib generatiivse tehisaru kasutamist kirjelduste ja kokkuvõtete koostamiseks ülevaatamisele kuuluvate objektide jaoks."
+        },
+        "alerts": {
+            "enabled": {
+                "label": "Luba häired"
+            }
         }
+    },
+    "audio_transcription": {
+        "label": "Audio transkriptsioon",
+        "live_enabled": {
+            "label": "Reaalajas transkriptsioon"
+        },
+        "enabled": {
+            "label": "Luba heli üleskirjutamine tekstina"
+        }
+    },
+    "detect": {
+        "label": "Objekti tuvastus",
+        "enabled": {
+            "label": "Luba objektituvastus"
+        },
+        "height": {
+            "label": "Tuvastamise kõrgus"
+        },
+        "width": {
+            "label": "Tuvastamise laius"
+        },
+        "fps": {
+            "label": "Tuvastamise kaadrisagedus"
+        },
+        "stationary": {
+            "label": "Püsivate objektide sätted"
+        }
+    },
+    "face_recognition": {
+        "label": "Näotuvastus"
+    },
+    "ffmpeg": {
+        "path": {
+            "label": "FFmpeg asukoht"
+        },
+        "gpu": {
+            "label": "GPU indeks"
+        },
+        "inputs": {
+            "global_args": {
+                "label": "FFmpeg globaalsed argumendid"
+            }
+        }
+    },
+    "live": {
+        "label": "Reaalajas mahamängimine",
+        "height": {
+            "label": "Otseülekande kõrgus"
+        },
+        "quality": {
+            "label": "Otseülekande kvaliteet"
+        },
+        "streams": {
+            "label": "Otseülekande voo nimed"
+        }
+    },
+    "motion": {
+        "label": "Liikumistuvastus",
+        "frame_height": {
+            "label": "Kaadri kõrgus"
+        },
+        "enabled": {
+            "label": "Luba liikumistuvastus"
+        }
+    },
+    "objects": {
+        "label": "Objektid",
+        "filters": {
+            "min_area": {
+                "label": "Minimaalne objekti ala"
+            },
+            "max_area": {
+                "label": "Maksimaalne objekti ala"
+            }
+        },
+        "genai": {
+            "label": "GenAI objekti konfiguratsioon",
+            "required_zones": {
+                "label": "Nõutud tsoonid"
+            },
+            "debug_save_thumbnails": {
+                "label": "Salvesta pisipildid"
+            },
+            "enabled": {
+                "label": "Luba GenAI"
+            },
+            "use_snapshot": {
+                "label": "Kasuta hetktõmmiseid"
+            }
+        }
+    },
+    "mqtt": {
+        "label": "MQTT"
+    },
+    "notifications": {
+        "enabled": {
+            "label": "Luba teavitused"
+        },
+        "email": {
+            "label": "Teavituste email"
+        },
+        "label": "Teavitused"
+    },
+    "ui": {
+        "label": "Kaamera kasutajaliides"
+    },
+    "record": {
+        "label": "Salvestus",
+        "enabled": {
+            "label": "Luba salvestamine"
+        }
+    },
+    "snapshots": {
+        "enabled": {
+            "label": "Luba hetktõmmised"
+        }
+    },
+    "timestamp_style": {
+        "color": {
+            "red": {
+                "label": "Punane",
+                "description": "Punase komponent (0–255) ajatempli värvi jaoks."
+            },
+            "green": {
+                "label": "Roheline",
+                "description": "Rohelise komponent (0–255) ajatempli värvi jaoks."
+            },
+            "blue": {
+                "label": "Sinine",
+                "description": "Sinise komponent (0–255) ajatempli värvi jaoks."
+            },
+            "label": "Ajatempli värv",
+            "description": "Ajatempli teksti RGB värviväärtused (kõik väärtused 0–255)."
+        },
+        "thickness": {
+            "label": "Ajatempli paksus",
+            "description": "Ajatempli teksti joone paksus."
+        },
+        "effect": {
+            "label": "Ajatempli efekt",
+            "description": "Ajatempli teksti visuaalne efekt (puudub, ühtlane, vari)."
+        }
+    },
+    "onvif": {
+        "user": {
+            "label": "ONVIF kasutajanimi"
+        },
+        "password": {
+            "label": "ONVIF parool"
+        },
+        "port": {
+            "label": "ONVIF port"
+        },
+        "label": "ONVIF",
+        "host": {
+            "label": "ONVIF host"
+        }
+    },
+    "profiles": {
+        "label": "Profiilid"
     }
 }

web/public/locales/et/config/global.json

@@ -1,10 +1,31 @@
 {
     "audio": {
-        "label": "Helisündmused"
+        "label": "Heli tuvastus",
+        "min_volume": {
+            "label": "Minimaalne helitase"
+        },
+        "filters": {
+            "label": "Audio filtrid"
+        }
     },
     "birdseye": {
         "mode": {
             "label": "Jälgimisrežiim"
+        },
+        "order": {
+            "label": "Positsioon"
+        },
+        "height": {
+            "label": "Kõrgus"
+        },
+        "width": {
+            "label": "Laius"
+        },
+        "layout": {
+            "label": "Paigutus",
+            "scaling_factor": {
+                "label": "Skaleerimistegur"
+            }
         }
     },
     "version": {
@@ -22,6 +43,15 @@
             "threshold": {
                 "label": "Punktiskoori lävend",
                 "description": "Punktiskoori lävend, mida kasutatakse klassifitseerimise oleku muutmiseks."
+            },
+            "enabled": {
+                "label": "Luba mudel"
+            },
+            "name": {
+                "label": "Mudeli nimi"
+            },
+            "save_attempts": {
+                "label": "Salvestamiskatsed"
             }
         }
     },
@@ -30,11 +60,25 @@
             "threshold": {
                 "description": "Minimaalne sarnasuse punktiskoor (0-1), mis on vajalik selle päästiku käivitamiseks."
             }
+        },
+        "label": "Semantiline otsing",
+        "model_size": {
+            "label": "Mudeli suurus"
+        },
+        "device": {
+            "label": "Seade"
         }
     },
     "face_recognition": {
         "unknown_score": {
             "label": "Tundmatu punktiskoori lävend"
+        },
+        "label": "Näotuvastus",
+        "model_size": {
+            "label": "Mudeli suurus"
+        },
+        "device": {
+            "label": "Seade"
         }
     },
     "lpr": {
@@ -42,15 +86,393 @@
         "description": "Sõidukite numbrimärkide tuvastuse seadistus sisaldab tuvastuse lävendeid, vormindust ja teadaolevaid numbrimärke.",
         "enabled": {
             "description": "Lülita sõidukite numbrimärkide tuvastus kõikide kaamerate jaoks sisse; seda saad kaamerakohaselt ka sürjutada."
+        },
+        "model_size": {
+            "label": "Mudeli suurus"
+        },
+        "device": {
+            "label": "Seade"
         }
     },
     "genai": {
         "label": "Generatiivse tehisaru seadistus",
-        "description": "Seadistsued generatiivse tehisaru teenusepakkujate kasutamisel kirjelduste ja kokkuvõtete loomiseks ülevaatamisele kuuluvate objektide jaoks."
+        "description": "Seadistsued generatiivse tehisaru teenusepakkujate kasutamisel kirjelduste ja kokkuvõtete loomiseks ülevaatamisele kuuluvate objektide jaoks.",
+        "model": {
+            "label": "Mudel"
+        },
+        "roles": {
+            "label": "Rollid"
+        },
+        "api_key": {
+            "label": "API võti"
+        },
+        "base_url": {
+            "label": "Baas-URL"
+        }
     },
     "review": {
         "genai": {
             "description": "Kontrollib generatiivse tehisaru kasutamist kirjelduste ja kokkuvõtete koostamiseks ülevaatamisele kuuluvate objektide jaoks."
+        },
+        "alerts": {
+            "enabled": {
+                "label": "Luba häired",
+                "description": "Luba või keela kõigi kaamerate häirete genereerimine; seda saab kaamerati eraldi muuta."
+            }
         }
+    },
+    "audio_transcription": {
+        "label": "Audio transkriptsioon",
+        "live_enabled": {
+            "label": "Reaalajas transkriptsioon"
+        },
+        "enabled": {
+            "label": "Luba heli üleskirjutamine tekstina",
+            "description": "Luba või keela automaatne heli üleskirjutamine tektina kõigi kaamerate jaoks; seda saad kaamerati eraldi muuta."
+        },
+        "language": {
+            "label": "Üleskirjutuse keel",
+            "description": "Üleskirjutuse/tõlkimise jaoks kasutatav keelekood (näiteks „en” inglise keele puhul). Toetatud keelekoodid leiad lehelt https://whisper-api.com/docs/languages/."
+        },
+        "device": {
+            "label": "Üleskirjutusseade"
+        },
+        "model_size": {
+            "label": "Mudeli suurus"
+        }
+    },
+    "detect": {
+        "label": "Objekti tuvastus",
+        "enabled": {
+            "label": "Luba objektituvastus"
+        },
+        "height": {
+            "label": "Tuvastamise kõrgus"
+        },
+        "width": {
+            "label": "Tuvastamise laius"
+        },
+        "fps": {
+            "label": "Tuvastamise kaadrisagedus"
+        },
+        "stationary": {
+            "label": "Püsivate objektide sätted"
+        }
+    },
+    "ffmpeg": {
+        "path": {
+            "label": "FFmpeg asukoht"
+        },
+        "gpu": {
+            "label": "GPU indeks"
+        },
+        "inputs": {
+            "global_args": {
+                "label": "FFmpeg globaalsed argumendid"
+            }
+        },
+        "label": "FFmpeg"
+    },
+    "live": {
+        "label": "Reaalajas mahamängimine",
+        "height": {
+            "label": "Otseülekande kõrgus"
+        },
+        "quality": {
+            "label": "Otseülekande kvaliteet"
+        },
+        "streams": {
+            "label": "Otseülekande voo nimed"
+        }
+    },
+    "motion": {
+        "label": "Liikumistuvastus",
+        "frame_height": {
+            "label": "Kaadri kõrgus"
+        },
+        "enabled": {
+            "label": "Luba liikumistuvastus"
+        }
+    },
+    "objects": {
+        "label": "Objektid",
+        "filters": {
+            "min_area": {
+                "label": "Minimaalne objekti ala"
+            },
+            "max_area": {
+                "label": "Maksimaalne objekti ala"
+            }
+        },
+        "genai": {
+            "label": "GenAI objekti konfiguratsioon",
+            "required_zones": {
+                "label": "Nõutud tsoonid"
+            },
+            "debug_save_thumbnails": {
+                "label": "Salvesta pisipildid"
+            },
+            "enabled": {
+                "label": "Luba GenAI"
+            },
+            "use_snapshot": {
+                "label": "Kasuta hetktõmmiseid"
+            }
+        }
+    },
+    "auth": {
+        "reset_admin_password": {
+            "label": "Lähtesta administraatori parool"
+        },
+        "cookie_name": {
+            "label": "JWT küpsise nimi"
+        },
+        "enabled": {
+            "label": "Luba autentimine"
+        },
+        "label": "Autentimine",
+        "session_length": {
+            "label": "Sessiooni pikkus"
+        }
+    },
+    "database": {
+        "label": "Andmebaas"
+    },
+    "mqtt": {
+        "label": "MQTT",
+        "enabled": {
+            "label": "Luba MQTT"
+        },
+        "user": {
+            "label": "MQTT kasutajanimi"
+        },
+        "tls_ca_certs": {
+            "label": "TLS CA sertifikaat"
+        },
+        "tls_client_cert": {
+            "label": "Kliendi sertifikaat"
+        },
+        "host": {
+            "label": "MQTT host",
+            "description": "MQTT maakleri hostinimi või IP-aadress."
+        },
+        "port": {
+            "label": "MQTT port"
+        },
+        "client_id": {
+            "label": "Kliendi ID"
+        },
+        "stats_interval": {
+            "label": "Statistika intervall"
+        },
+        "tls_client_key": {
+            "label": "Kliendi võti"
+        },
+        "qos": {
+            "label": "MQTT QoS"
+        }
+    },
+    "go2rtc": {
+        "label": "go2rtc"
+    },
+    "notifications": {
+        "enabled": {
+            "label": "Luba teavitused"
+        },
+        "email": {
+            "label": "Teavituste email"
+        },
+        "label": "Teavitused"
+    },
+    "networking": {
+        "ipv6": {
+            "label": "IPv6 sätted",
+            "enabled": {
+                "label": "Luba IPv6"
+            }
+        },
+        "label": "Võrguühendus",
+        "listen": {
+            "internal": {
+                "label": "Sisemine port"
+            },
+            "external": {
+                "label": "Välimine port"
+            }
+        }
+    },
+    "proxy": {
+        "label": "Vaheserver",
+        "logout_url": {
+            "label": "Väljalogimise url"
+        },
+        "default_role": {
+            "label": "Vaikimisi roll"
+        }
+    },
+    "telemetry": {
+        "stats": {
+            "label": "Süsteemi statistika",
+            "amd_gpu_stats": {
+                "label": "AMD GPU statistika"
+            },
+            "intel_gpu_stats": {
+                "label": "Intel GPU statistika"
+            },
+            "intel_gpu_device": {
+                "label": "Intel GPU seade"
+            },
+            "network_bandwidth": {
+                "label": "Võrgu ribalaius"
+            }
+        },
+        "label": "Telemeetria",
+        "network_interfaces": {
+            "label": "Võrguliides"
+        },
+        "version_check": {
+            "label": "Versiooni kontroll",
+            "description": "Luba väljaminev ühendus, et kontrollida uuema Frigate versooni olemasolu."
+        }
+    },
+    "tls": {
+        "label": "TLS",
+        "enabled": {
+            "label": "Luba TLS"
+        }
+    },
+    "ui": {
+        "timezone": {
+            "label": "ajavöönd"
+        },
+        "label": "Kasutajaliides",
+        "description": "Kasutajaliidese eelistused nagu ajavöönd, aja ja kuupäeva formaat ning ühikud.",
+        "unit_system": {
+            "label": "Ühikute süsteem"
+        }
+    },
+    "detectors": {
+        "label": "Detektori riistvara",
+        "cpu": {
+            "label": "CPU"
+        },
+        "deepstack": {
+            "label": "DeepStack"
+        },
+        "edgetpu": {
+            "label": "EdgeTPU"
+        },
+        "onnx": {
+            "label": "ONNX",
+            "device": {
+                "label": "Seadme tüüp"
+            }
+        },
+        "rknn": {
+            "label": "RKNN"
+        },
+        "openvino": {
+            "label": "OpenVINO"
+        },
+        "tensorrt": {
+            "label": "TensorRT"
+        },
+        "teflon_tfl": {
+            "label": "Teflon"
+        },
+        "synaptics": {
+            "label": "Synaptics"
+        },
+        "memryx": {
+            "device": {
+                "label": "Seadme asukoht"
+            },
+            "label": "MemryX"
+        },
+        "hailo8l": {
+            "label": "Hailo-8/Hailo-8L"
+        },
+        "zmq": {
+            "label": "ZMQ IPC"
+        },
+        "axengine": {
+            "label": "AXEngine NPU"
+        },
+        "degirum": {
+            "label": "DeGirum"
+        }
+    },
+    "logger": {
+        "label": "Logimine"
+    },
+    "model": {
+        "label": "Tuvastusmudel"
+    },
+    "record": {
+        "label": "Salvestus",
+        "enabled": {
+            "label": "Luba salvestamine",
+            "description": "Luba või keela salvestamine kõigi kaamerate jaoks; seda saab kaamerati eraldi muuta."
+        }
+    },
+    "snapshots": {
+        "enabled": {
+            "label": "Luba hetktõmmised",
+            "description": "Luba või keela kõigi kaamerate hetktõmmiste salvestamine; seda saab kaamerati eraldi muuta."
+        }
+    },
+    "timestamp_style": {
+        "color": {
+            "red": {
+                "label": "Punane",
+                "description": "Punase komponent (0–255) ajatempli värvi jaoks."
+            },
+            "green": {
+                "label": "Roheline",
+                "description": "Rohelise komponent (0–255) ajatempli värvi jaoks."
+            },
+            "blue": {
+                "label": "Sinine",
+                "description": "Sinise komponent (0–255) ajatempli värvi jaoks."
+            },
+            "label": "Ajatempli värv",
+            "description": "Ajatempli teksti RGB värviväärtused (kõik väärtused 0–255)."
+        },
+        "thickness": {
+            "label": "Ajatempli paksus",
+            "description": "Ajatempli teksti joone paksus."
+        },
+        "effect": {
+            "label": "Ajatempli efekt",
+            "description": "Ajatempli teksti visuaalne efekt (puudub, ühtlane, vari)."
+        }
+    },
+    "onvif": {
+        "user": {
+            "label": "ONVIF kasutajanimi"
+        },
+        "password": {
+            "label": "ONVIF parool"
+        },
+        "port": {
+            "label": "ONVIF port"
+        },
+        "label": "ONVIF",
+        "host": {
+            "label": "ONVIF host"
+        }
+    },
+    "camera_mqtt": {
+        "quality": {
+            "label": "JPEG kvaliteet",
+            "description": "MQTT-sse saadetud piltide JPEG-kvaliteet (0–100)."
+        },
+        "enabled": {
+            "label": "Saada pilt"
+        },
+        "label": "MQTT"
+    },
+    "profiles": {
+        "label": "Profiilid"
     }
 }

web/public/locales/et/views/chat.json

@@ -6,5 +6,67 @@
     "error": "Midagi läks valesti. Palun proovi uuesti.",
     "processing": "Töötlen…",
     "toolsUsed": "Kasutatud: {{tools}}",
-    "similarity_score": "Sarnasus"
+    "similarity_score": "Sarnasus",
+    "showTools": "Näita tööriistu ({{count}})",
+    "hideTools": "Peida tööriistad",
+    "call": "Kutse",
+    "result": "Tulemus",
+    "arguments": "Argumendid:",
+    "response": "Vastus:",
+    "send": "Saada",
+    "new_chat": "Uus vestlus",
+    "settings": {
+        "title": "Vestluse sätted",
+        "show_stats": {
+            "title": "Näita statistikat",
+            "always": "Alati",
+            "desc": "Kuva vastuste genereerimise kiirus ja konteksti suurus.",
+            "while_generating": "Genereerimise ajal"
+        },
+        "auto_scroll": {
+            "title": "Automaatne kerimine",
+            "desc": "Jälgi uusi sõnumeid kohe, kui need saabuvad."
+        }
+    },
+    "stats": {
+        "context": "{{tokens}} tokenit",
+        "tokens_per_second": "{{rate}} t/s"
+    },
+    "starting_requests_prompts": {
+        "recap": "Mis juhtus kui ma olin ära?",
+        "watch_camera": "Jälgi ust ja anna mulle teada kui keegi tuleb",
+        "show_camera_status": "Milline on minu kaamerate praegune seis?",
+        "show_recent_events": "Näita mulle viimase tunni viimaseid sündmusi"
+    },
+    "starting_requests": {
+        "show_camera_status": "Näita kaamera olekut",
+        "show_recent_events": "Kuva hiljutised sündmused",
+        "recap": "Mis juhtus kui ma olin ära?",
+        "watch_camera": "Jälgi kaamerat aktiivsuse osas"
+    },
+    "suggested_requests": "Proovi küsida:",
+    "semantic_search_required": "Sarnaste objektide leidmiseks peab olema lubatud semantiline otsing.",
+    "no_similar_objects_found": "Sarnaseid objekte ei leitud.",
+    "quick_reply_when_else": "Millal seda veel nähti?",
+    "quick_reply_find_similar_text": "Leia sarnaseid vaatepilte.",
+    "quick_reply_tell_me_more_text": "Räägi mulle sellest lähemalt.",
+    "quick_reply_when_else_text": "Millal seda veel nähtud on?",
+    "attach_event_aria": "Lisa sündmus {{eventId}}",
+    "attachment_picker_paste_label": "Või kleebi sündmuse ID",
+    "attachment_picker_attach": "Lisa",
+    "attachment_picker_placeholder": "Lisa sündmus",
+    "quick_reply_find_similar": "Leia sarnaseid vaatlusi",
+    "quick_reply_tell_me_more": "Räägi mulle sellest lähemalt",
+    "attachment_chip_remove": "Eemalda manus",
+    "attachment_chip_label": "{{label}} kaameras {{camera}}",
+    "open_in_explore": "Ava uurimisvaates",
+    "anchor": "Viide",
+    "reasoning": {
+        "active": "Otsin põhjendust…",
+        "show": "Näita põhjendust",
+        "hide": "Peida põhjendus"
+    },
+    "thinking": {
+        "toggle": "Näita mõtlemise olekut või peida see"
+    }
 }

web/public/locales/et/views/classificationModel.json

@@ -43,5 +43,8 @@
   },
   "tooltip": {
     "trainingInProgress": "Mudel on parasjagu õppimas"
+  },
+  "train": {
+    "titleShort": "Hiljutised"
   }
 }

web/public/locales/et/views/explore.json

@@ -5,7 +5,8 @@
   "noTrackedObjects": "Ühtegi jälgitavat objekti ei leidunud",
   "itemMenu": {
     "findSimilar": {
-      "aria": "Otsi sarnaseid jälgitavaid objekte"
+      "aria": "Otsi sarnaseid jälgitavaid objekte",
+      "label": "Leia sarnane"
     },
     "downloadSnapshot": {
       "label": "Laadi hetkvõte alla",
@@ -14,6 +15,14 @@
     "downloadCleanSnapshot": {
       "label": "Laadi puhas hetkvõte alla",
       "aria": "Laadi puhas hetkvõte alla"
+    },
+    "viewTrackingDetails": {
+      "label": "Vaata jälgimise üksikasju",
+      "aria": "Näita jälgimise üksikasju"
+    },
+    "downloadVideo": {
+      "label": "Laadi video alla",
+      "aria": "Laadi video alla"
     }
   },
   "trackingDetails": {
@@ -21,11 +30,22 @@
       "showAllZones": {
         "title": "Näita kõiki tsoone",
         "desc": "Kui objekt on sisenenud tsooni, siis alati näida tsooni märgistust."
+      },
+      "title": "Annotatsioonide seaded",
+      "offset": {
+        "desc": "Need andmed pärinevad teie kaamera tuvastusvoost, kuid on salvestusvoo piltide peal. On ebatõenäoline, et need kaks voogu on ideaalselt sünkroonis. Seetõttu ei joondu piirav kast ja kaader ideaalselt. Selle säte abil saad annotatsioone ajas edasi või tagasi nihutada, et need salvestatud kaadriga paremini joonduks.",
+        "millisecondsToOffset": "Millisekundid annotatsioonide tuvastuse nihutamiseks. <em>Vaikimisi: 0</em>",
+        "tips": "Vähendage väärtust, kui video taasesitus on kastidest ja teekonnapunktidest ees, ning suurendage väärtust, kui video taasesitus on neist maas. See väärtus võib olla negatiivne.",
+        "toast": {
+          "success": "Kaamera '{{camera}}' annotatsiooni nihe on konfiguratsioonifaili salvestatud."
+        },
+        "label": "Annotatsiooni nihe"
       }
     },
     "lifecycleItemDesc": {
       "attribute": {
-        "other": "{{label}} on tuvastatud kui {{attribute}}"
+        "other": "{{label}} on tuvastatud kui {{attribute}}",
+        "faceOrLicense_plate": "{{attribute}} tuvastatud objektil {{label}}"
       },
       "stationary": "{{label}} jäi paigale",
       "active": "{{label}} muutus aktiivseks",
@@ -37,7 +57,8 @@
         "area": "Ala",
         "score": "Punktiskoor",
         "computedScore": "Arvutatud punktiskoor",
-        "topScore": "Suuremad punktiskoorid"
+        "topScore": "Suuremad punktiskoorid",
+        "toggleAdvancedScores": "Täpsemate tulemuste sisse-/väljalülitamine"
       },
       "external": "{{label}} on tuvastatud",
       "heard": "{{label}} on kuuldud",
@@ -50,7 +71,11 @@
       "previous": "Eelmine slaid",
       "next": "Järgmine slaid"
     },
-    "count": "{{first}} / {{second}}"
+    "count": "{{first}} / {{second}}",
+    "adjustAnnotationSettings": "Korrigeeri annotatsioonide seadeid",
+    "scrollViewTips": "Klõpsake selle objekti elutsükli oluliste hetkede vaatamiseks.",
+    "autoTrackingTips": "Piirdekastide asukohad on automaatselt jälgivate kaamerate puhul ebatäpsed.",
+    "trackedPoint": "Jälgitav punkt"
   },
   "documentTitle": "Avasta - Frigate",
   "generativeAI": "Generatiivne tehisaru",
@@ -64,7 +89,22 @@
       },
       "startingUp": "Käivitun…",
       "estimatedTime": "Hinnanguliselt jäänud aega:",
-      "finishingShortly": "Lõpetan õige pea"
+      "finishingShortly": "Lõpetan õige pea",
+      "context": "Avastamist saab kasutada pärast seda, kui jälgitavate objektide manustamine on uuesti indekseerimise lõpetanud."
+    },
+    "title": "Avastamine pole saadaval",
+    "downloadingModels": {
+      "context": "Frigate laadib alla semantilise otsingu funktsiooni toetamiseks vajalikke manustamismudeleid. See võib võtta mitu minutit, olenevalt teie võrguühenduse kiirusest.",
+      "setup": {
+        "visionModel": "Nägemismudel",
+        "visionModelFeatureExtractor": "Nägemismudeli tunnuste eraldaja",
+        "textModel": "Tekstimudel",
+        "textTokenizer": "Teksti tokenisaator"
+      },
+      "tips": {
+        "context": "Pärast mudelite allalaadimist tuleks oma jälgitavate objektide manused uuesti indekseerida."
+      },
+      "error": "Tekkis viga. Kontrollige Frigate'i logisid."
     }
   },
   "type": {
@@ -107,8 +147,52 @@
     },
     "recognizedLicensePlate": "Tuvastatud sõiduki numbrimärk",
     "description": {
-      "aiTips": "Frigate ei küsi sinu generatiivse tehisaru teenusepakkujalt kirjeldust enne, kui jälgitava objekti elutsükkel on lõppenud."
+      "aiTips": "Frigate ei küsi sinu generatiivse tehisaru teenusepakkujalt kirjeldust enne, kui jälgitava objekti elutsükkel on lõppenud.",
+      "label": "Kirjeldus",
+      "placeholder": "Jälgitava objekti kirjeldus"
+    },
+    "label": "Silt",
+    "editSubLabel": {
+      "title": "Muuda alamsilti",
+      "desc": "Sisesta sildile '{{label}}' uus alamsilt",
+      "descNoLabel": "Sisesta sellele jälgitavale objektile uus alamsilt"
+    },
+    "camera": "Kaamera",
+    "zones": "Tsoonid",
+    "title": {
+      "label": "Pealkiri"
+    },
+    "button": {
+      "findSimilar": "Leia sarnane",
+      "regenerate": {
+        "title": "Taasloomine",
+        "label": "Jälgitava objekti kirjelduse uuesti genereerimine"
+      }
+    },
+    "topScore": {
+      "label": "Parim punktiskoor",
+      "info": "Kõrgeim skoor on jälgitava objekti kõrgeim mediaanskoor, seega võib see erineda otsingutulemuste pisipildil kuvatavast skoorist."
+    },
+    "objects": "Objektid",
+    "tips": {
+      "descriptionSaved": "Kirjeldus salvestati edukalt",
+      "saveDescriptionFailed": "Kirjelduse uuendamine ebaõnnestus: {{errorMessage}}"
+    },
+    "attributes": "Klassifikatsiooni atribuudid",
+    "estimatedSpeed": "Hinnanguline kiirus",
+    "editAttributes": {
+      "title": "Atribuutide muutmine",
+      "desc": "Valige selle sildi '{{label}}' jaoks klassifikatsiooniatribuudid"
     }
   },
-  "trackedObjectDetails": "Jälgitava objekti üksikasjad"
+  "trackedObjectDetails": "Jälgitava objekti üksikasjad",
+  "aiAnalysis": {
+    "title": "Tehisintellekti analüüs"
+  },
+  "concerns": {
+    "label": "Mured"
+  },
+  "objectLifecycle": {
+    "noImageFound": "Selle jälgitava objekti kohta ei leitud pilti."
+  }
 }

web/public/locales/et/views/exports.json

@@ -16,12 +16,15 @@
     "downloadVideo": "Laadi video alla",
     "editName": "Muuda nime",
     "deleteExport": "Kustuta eksporditud sisu",
-    "assignToCase": "Lisa juhtumile"
+    "assignToCase": "Lisa juhtumile",
+    "removeFromCase": "Eemalda juhtumist"
   },
   "toast": {
     "error": {
       "renameExportFailed": "Eksporditud sisu nime muutmine ei õnnestunud: {{errorMessage}}",
-      "assignCaseFailed": "Juhtumiga seose uuendamine ei õnnestunud: {{errorMessage}}"
+      "assignCaseFailed": "Juhtumiga seose uuendamine ei õnnestunud: {{errorMessage}}",
+      "caseSaveFailed": "Juhtumi salvestamine ei õnnestunud: {{errorMessage}}",
+      "caseDeleteFailed": "Juhtumi kustutamine ei õnnestunud: {{errorMessage}}"
     }
   },
   "headings": {
@@ -35,5 +38,44 @@
     "nameLabel": "Juhtumi nimi",
     "descriptionLabel": "Kirjeldus",
     "description": "Vali olemasolev juhtum või lisa uus."
+  },
+  "toolbar": {
+    "newCase": "Uus juhtum",
+    "addExport": "Lisa eksportimiseks",
+    "editCase": "Muuda juhtumit",
+    "deleteCase": "Kustuta juhtum"
+  },
+  "deleteCase": {
+    "label": "Kustuta juhtum",
+    "desc": "Kas oled kindel, et soovid „{{caseName}}“ juhtumi kustutada?"
+  },
+  "caseCard": {
+    "emptyCase": "Eksportimise veel pole"
+  },
+  "jobCard": {
+    "defaultName": "Eksportimine kaamerast „{{camera}}“",
+    "queued": "Lisatud järjekorda",
+    "running": "Töös",
+    "preparing": "Ettevalmistamisel",
+    "copying": "Kopeerimisel",
+    "encoding": "Kodeerimisel",
+    "encodingRetry": "Kodeerimisel (uuesti)",
+    "finalizing": "Lõpetamisel"
+  },
+  "caseView": {
+    "noDescription": "Kirjeldust pole",
+    "createdAt": "Loodud {{value}}",
+    "exportCount_one": "1 eksportimine",
+    "exportCount_other": "{{count}} eksportimist",
+    "cameraCount_one": "1 kaamera",
+    "cameraCount_other": "{{count}} kaamerat",
+    "showMore": "Näita rohkem",
+    "showLess": "Näita vähem",
+    "emptyTitle": "See juhtum on tühi"
+  },
+  "caseEditor": {
+    "namePlaceholder": "Juhtumi nimi",
+    "editTitle": "Muuda juhtumit",
+    "createTitle": "Lisa juhtum"
   }
 }

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

@@ -1,6 +1,11 @@
 {
   "button": {
-    "uploadImage": "Laadi pilt üles"
+    "uploadImage": "Laadi pilt üles",
+    "deleteFaceAttempts": "Kustuta näod",
+    "addFace": "Lisa nägu",
+    "renameFace": "Nimeta nägu ümber",
+    "deleteFace": "Kustuta nägu",
+    "reprocessFace": "Käivita näotuvastus uuesti"
   },
   "collections": "Kogumikud",
   "description": {
@@ -11,28 +16,41 @@
   },
   "documentTitle": "Näoteek - Frigate",
   "createFaceLibrary": {
-    "new": "Lisa uus nägu"
+    "new": "Lisa uus nägu",
+    "nextSteps": "Tugeva tuvastusaluse loomiseks:<li>Kasuta vahekaarti \"Hiljutised tuvastused\", et valida pilte ja treenida isikutuvastust.</li><li>Parima tulemuse saavutamiseks keskendu otsepiltidele; väldi nurga all olevaid nägusid treenimiseks.</li></ul>"
   },
   "deleteFaceLibrary": {
-    "title": "Kustuta nimi"
+    "title": "Kustuta nimi",
+    "desc": "Kas oled kindel, et soovid isiku '{{name}}' kollektsiooni kustutada? See kustutab jäädavalt kõik seotud näod."
   },
   "toast": {
     "error": {
       "addFaceLibraryFailed": "Näo sidumine nimega ei õnnestunud: {{errorMessage}}",
-      "updateFaceScoreFailed": "Näo punktiskoori uuendamine ei õnnestunud: {{errorMessage}}"
+      "updateFaceScoreFailed": "Näo punktiskoori uuendamine ei õnnestunud: {{errorMessage}}",
+      "uploadingImageFailed": "Pildi üleslaadimine ebaõnnestus: {{errorMessage}}",
+      "deleteFaceFailed": "Kustutamine ebaõnnestus: {{errorMessage}}",
+      "deleteNameFailed": "Nime kustutamine ebaõnnestus: {{errorMessage}}",
+      "renameFaceFailed": "Näo ümbernimetamine ebaõnnestus: {{errorMessage}}",
+      "trainFailed": "Treenimine ebaõnnestus: {{errorMessage}}",
+      "reclassifyFailed": "Näo ümberklassifitseerimine ebaõnnestus: {{errorMessage}}"
     },
     "success": {
-      "addFaceLibrary": "Lisamine Näoteeki õnnestus: {{name}}!",
+      "addFaceLibrary": "Lisamine nägude kogusse õnnestus: {{name}}!",
       "deletedFace_one": "{{count}} näo kustutamine õnnestus.",
       "deletedFace_other": "{{count}} näo kustutamine õnnestus.",
       "deletedName_one": "{{count}} näo kustutamine õnnestus.",
       "deletedName_other": "{{count}} näo kustutamine õnnestus.",
-      "updatedFaceScore": "Näo punktiskoori uuendamine õnnestus: {{name}} ({{score}})."
+      "updatedFaceScore": "Näo punktiskoori uuendamine õnnestus: {{name}} ({{score}}).",
+      "uploadedImage": "Pildi üleslaadimine õnnestus.",
+      "renamedFace": "Näo ümbernimetamine õnnestus, uus nimi on {{name}}",
+      "trainedFace": "Edukalt treenitud nägu.",
+      "reclassifiedFace": "Näo ümberklassifitseerimine õnnestus."
     }
   },
   "deleteFaceAttempts": {
     "desc_one": "Kas oled kindel, et soovid kustutada {{count}} näo? Seda tegevust ei saa tagasi pöörata.",
-    "desc_other": "Kas oled kindel, et soovid kustutada {{count}} nägu? Seda tegevust ei saa tagasi pöörata."
+    "desc_other": "Kas oled kindel, et soovid kustutada {{count}} nägu? Seda tegevust ei saa tagasi pöörata.",
+    "title": "Kustuta näod"
   },
   "details": {
     "timestamp": "Ajatampel",
@@ -42,5 +60,40 @@
   "uploadFaceImage": {
     "title": "Laadi näopilt üles",
     "desc": "Laadi üles pilt, et otsida sellelt nägusid ja lisada see {{pageToggle}}'i jaoks"
-  }
+  },
+  "steps": {
+    "faceName": "Lisa näole nimi",
+    "uploadFace": "Lae näopilt üles",
+    "nextSteps": "Järgmised sammud",
+    "description": {
+      "uploadFace": "Laadi üles pilt isikust '{{name}}', mis näitab tema nägu eestvaates. Ainult nägu ei pea pildilt välja lõikama."
+    }
+  },
+  "train": {
+    "title": "Hiljutised tuvastamised",
+    "titleShort": "Hiljutised",
+    "aria": "Vali hiljutised tuvastamised",
+    "empty": "Hiljutisi näotuvastuse katseid pole",
+    "emptyNoLibrary": {
+      "title": "Laadi üles nägu",
+      "description": "Näotuvastuse toimimiseks peate lisama vähemalt ühe näo kogusse."
+    }
+  },
+  "renameFace": {
+    "title": "Nimeta nägu ümber",
+    "desc": "Sisesta uus nimi isiku '{{name}}' jaoks"
+  },
+  "imageEntry": {
+    "validation": {
+      "selectImage": "Palun vali pildifail."
+    },
+    "dropActive": "Lohista pilt siia…",
+    "dropInstructions": "Lohistage või kleepige pilt siia või klõpsake valimiseks",
+    "maxSize": "Maksimum suurus: {{size}}MB"
+  },
+  "nofaces": "Nägusid pole saadaval",
+  "trainFaceAs": "Treeni nägu kui:",
+  "trainFace": "Treeni nägu",
+  "reclassifyFaceAs": "Liigita nägu ümber järgmiselt:",
+  "reclassifyFace": "Näo ümberklassifitseerimine"
 }

web/public/locales/et/views/motionSearch.json

@@ -1,4 +1,78 @@
 {
     "documentTitle": "Liikumise tuvastus - Frigate",
-    "title": "Liikumise otsing"
+    "title": "Liikumise otsing",
+    "cancelSearch": "Tühista",
+    "startSearch": "Alusta otsingut",
+    "selectCamera": "Liikumisotsingut laaditakse",
+    "description": "Joonesta hulknurk, et määratleda huvipakkuv piirkond, ja määra ajavahemik, mille jooksul otsida liikumise muutusi selles piirkonnas.",
+    "searchStarted": "Otsing alustatud",
+    "searchCancelled": "Otsing tühistatud",
+    "searching": "Otsing on pooleli.",
+    "searchComplete": "Otsing lõpetatud",
+    "noResultsYet": "Käivita otsing valitud piirkonnas liikumise muutuste leidmiseks",
+    "noChangesFound": "Valitud piirkonnas ei tuvastatud pikslimuutusi",
+    "results": "Tulemused",
+    "polygonControls": {
+        "drawMode": "Joonista",
+        "moveMode": "Liiguta",
+        "reset": "Lähtesta hulknurk",
+        "undo": "Tühista viimane punkt",
+        "points_one": "{{count}} punkt",
+        "points_other": "{{count}} punkti"
+    },
+    "newSearch": "Uus otsing",
+    "clearResults": "Tühista tulemused",
+    "clearROI": "Tühista hulknurk",
+    "dialog": {
+        "cameraLabel": "Kaamera",
+        "title": "Liikumisotsing",
+        "previewAlt": "Kaamera '{{camera}}' eelvaade"
+    },
+    "timeRange": {
+        "title": "Otsinguvahemik",
+        "start": "Algusaeg",
+        "end": "Lõppaeg"
+    },
+    "settings": {
+        "title": "Otsinguseaded",
+        "parallelMode": "Paralleelrežiim",
+        "parallelModeDesc": "Skanni mitut salvestusvahemikku korraga (kiirem; kasutab rohkem dekodeerimisressursse)",
+        "threshold": "Tundlikkuse lävi",
+        "thresholdDesc": "Väiksemad väärtused tuvastavad väiksemaid muutusi (1–255)",
+        "minArea": "Minimaalne muutusala",
+        "minAreaDesc": "Ühe liikuva piirkonna minimaalne suurus protsentides huvipakkuvast piirkonnast",
+        "maxResults": "Maksimaalselt tulemusi",
+        "maxResultsDesc": "Peata pärast nii paljude ajatemplite sobivust"
+    },
+    "errors": {
+        "noCamera": "Palun vali kaamera",
+        "noROI": "Palun joonistage huvipakkuv piirkond",
+        "noTimeRange": "Palun valige ajavahemik",
+        "invalidTimeRange": "Lõppaeg peab olema pärast algusaega",
+        "searchFailed": "Otsing ebaõnnestus: {{message}}",
+        "polygonTooSmall": "Hulknurgal peab olema vähemalt 3 punkti",
+        "unknown": "Tundmatu viga"
+    },
+    "changePercentage": "{{percentage}}% muutus",
+    "metrics": {
+        "title": "Otsingumõõdikud",
+        "segmentsScanned": "Skannitud segmente",
+        "segmentsProcessed": "Töödeldud",
+        "segmentsSkippedInactive": "Vahele jäetud (tegevust pole)",
+        "segmentsSkippedHeatmap": "Vahele jäetud (kattuvaid piirkondi pole)",
+        "fallbackFullRange": "Varurežiimis täisulatusega skaneerimine",
+        "framesDecoded": "Kaadreid dekodeeritud",
+        "wallTime": "Otsingu aeg",
+        "seconds": "{{seconds}}s",
+        "minutesSeconds": "{{minutes}}m {{seconds}}s",
+        "segmentErrors": "Segmendi vead",
+        "scanSummary": "{{segments}} segmenti · {{time}}"
+    },
+    "jumpToTime": "Hüppa sellele ajale",
+    "framesProcessed": "{{count}} kaadrit töödeldud",
+    "changesFound_one": "Tuvastatud {{count}} liikumine",
+    "changesFound_other": "Tuvastatud {{count}} liikumist",
+    "motionHeatmapLabel": "Liikumise soojakaart",
+    "showSegmentHeatmap": "Soojakaart",
+    "scanning": "Skannimine {{time}}"
 }

web/public/locales/et/views/replay.json

@@ -12,7 +12,48 @@
         "selectFromTimeline": "Vali",
         "starting": "Käivitan kordust…",
         "startLabel": "Algus",
-        "endLabel": "Lõpp"
+        "endLabel": "Lõpp",
+        "title": "Alusta silumise taasesitust",
+        "description": "Looge ajutine taasesituskaamera, mis kordab ajaloolist salvestist objektide tuvastamise ja jälgimise probleemide silumiseks. Taasesituskaameral on sama tuvastusseadistus mis lähtekaameral. Valige algusaeg.",
+        "toast": {
+            "error": "Silumise taasesitus ebaõnnestus: {{error}}",
+            "alreadyActive": "Kordusseanss on juba aktiivne",
+            "stopError": "Silumise taasesituse peatamine ebaõnnestus: {{error}}",
+            "goToReplay": "Mine kordusesse"
+        }
     },
-    "title": "Kordus veaotsinguks"
+    "title": "Kordus veaotsinguks",
+    "websocket_messages": "Sõnumid",
+    "description": "Mängi kaamera salvestisi veaotsinguks. Objektide loend näitab tuvastatud objektide ajalist viivitust ja vahekaart „Sõnumid” näitab Fregati sisemiste sõnumite voogu taasesituse materjalist.",
+    "page": {
+        "noSession": "Aktiivset silumis- ja taasesitusseanssi pole",
+        "noSessionDesc": "Alusta silumissalvestise taasesitust ajaloo vaates, klõpsates tööriistaribal nupul \"Toimingud\" ja valides silumissalvestise taasesituse.",
+        "goToRecordings": "Mine ajaloo vaatesse",
+        "preparingClip": "Klipi ettevalmistamine…",
+        "preparingClipDesc": "Frigate koondab valitud ajavahemiku salvestisi. Pikemate vahemike puhul võib see võtta kauem.",
+        "startingCamera": "Silumise taasesituse käivitamine…",
+        "startError": {
+            "title": "Silumise taasesituse käivitamine ebaõnnestus",
+            "back": "Tagasi ajaloo vaatesse"
+        },
+        "sourceCamera": "Lähtekaamera",
+        "replayCamera": "Taasesituse kaamera",
+        "initializingReplay": "Silumise taasesituse initsialiseerimine...",
+        "stoppingReplay": "Silumise taasesituse peatamine...",
+        "stopReplay": "Peata kordusesitus",
+        "confirmStop": {
+            "title": "Peata silumise kordusesitus?",
+            "description": "See peatab seansi ja kustutab kõik ajutised andmed. Kas oled kindel?",
+            "confirm": "Peata kordusesitus",
+            "cancel": "Tühista"
+        },
+        "activity": "Toimingud",
+        "objects": "Objekti loend",
+        "audioDetections": "Audio tuvastused",
+        "noActivity": "Ühtegi tegevust ei tuvastatud",
+        "activeTracking": "Aktiivne jälgimine",
+        "noActiveTracking": "Aktiivset jälgimist pole",
+        "configuration": "Seaded",
+        "configurationDesc": "Peenhäälesta liikumistuvastuse ja objektide jälgimise sätteid silumis- ja taasesituskaamera jaoks. Frigate'i konfiguratsiooni faili muudatusi ei salvestata."
+    }
 }

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

@@ -7,7 +7,28 @@
       "connectionSettings": "Ühenduse seadistused",
       "port": "Port",
       "username": "Kasutajanimi",
-      "usernamePlaceholder": "Valikuline"
+      "usernamePlaceholder": "Valikuline",
+      "cameraName": "Kaamera nimi",
+      "cameraNamePlaceholder": "näiteks: eesmine_uks või Hoovi ülevaade",
+      "host": "Host/IP-aadress",
+      "cameraBrand": "Kaamera bränd",
+      "selectBrand": "Vali URL malli jaoks kaamera bränd",
+      "customUrl": "Kohandatud voo URL",
+      "brandInformation": "Brändi teave",
+      "brandUrlFormat": "Kaamerate puhul, mille RTSP URL-i vorming on järgmine: {{exampleUrl}}",
+      "selectTransport": "Valige transpordiprotokoll",
+      "description": "Sisestage oma kaamera andmed ja valige, kas soovite kaamerat tuvastada või valida tootja käsitsi.",
+      "onvifPort": "ONVIF port",
+      "probeMode": "Tuvasta kaamera",
+      "manualMode": "Manuaalne valik",
+      "errors": {
+        "nameRequired": "Kaamera nimi on kohustuslik",
+        "nameLength": "Kaamera nimi peab olema kuni 64 tähemärki pikk",
+        "invalidCharacters": "Kaamera nimi sisaldab sobimatuid märke",
+        "nameExists": "Kaamera nimi on juba olemas",
+        "brandOrCustomUrlRequired": "Valige kas kaamera bränd koos hosti/IP-aadressiga või valige „Muu” kohandatud URL-iga"
+      },
+      "detectionMethod": "Vootuvastus meetod"
     },
     "step3": {
       "streamUrlPlaceholder": "rtsp://kasutajanimi:salasõna@host:port/asukoht",
@@ -17,17 +38,37 @@
       "roles": "Rollid",
       "roleLabels": {
         "record": "Salvestamine",
-        "audio": "Heliriba"
+        "audio": "Heliriba",
+        "detect": "Objektituvastus"
       },
       "connected": "Ühendatud",
-      "featuresTitle": "Funktsionaalsused"
+      "featuresTitle": "Funktsionaalsused",
+      "selectStream": "Vali voog",
+      "selectQuality": "Valige kvaliteet",
+      "notConnected": "Pole ühendatud",
+      "testFailedTitle": "Test ebaõnnestus",
+      "testStream": "Testi ühendust",
+      "testSuccess": "Voo test edukas!",
+      "testFailed": "Voo test ebaõnnestus",
+      "selectResolution": "Vali resolutsioon",
+      "noStreamFound": "Voogu ei leitud",
+      "addAnotherStream": "Lisa järgmine voog",
+      "streamTitle": "Voog {{number}}",
+      "streamUrl": "Voo URL",
+      "addStream": "Lisa voog",
+      "description": "Seadista voogedastusrolle ja lisa oma kaamerale täiendavaid vooge.",
+      "streamsTitle": "Kaamera vood"
     },
     "steps": {
-      "probeOrSnapshot": "Võta proov või tee hetkvõte"
+      "probeOrSnapshot": "Võta proov või tee hetkvõte",
+      "nameAndConnection": "Nimi ja ühendus",
+      "streamConfiguration": "Voo seaded",
+      "validationAndTesting": "Valideerimine ja testimine"
     },
     "step2": {
       "testing": {
-        "fetchingSnapshot": "Laadin kaamera hetkvõtet alla..."
+        "fetchingSnapshot": "Laadin kaamera hetkvõtet alla...",
+        "probingMetadata": "Tuvastan kaamera metaandmeid..."
       },
       "retry": "Proovi uuesti",
       "manufacturer": "Tootja",
@@ -37,7 +78,30 @@
       "presets": "Eelseadistused",
       "useCandidate": "Kasuta",
       "uriCopy": "Kopeeri",
-      "connected": "Ühendatud"
+      "connected": "Ühendatud",
+      "testSuccess": "Ühenduse test õnnestus!",
+      "testFailed": "Ühenduse test ebaõnnestus. Palun kontrollige sisestatud andmeid ja proovige uuesti.",
+      "testFailedTitle": "Test ebaõnnestus",
+      "streamDetails": "Voo üksikasjad",
+      "probing": "Tuvastan kaamerat...",
+      "ptzSupport": "PTZ tugi",
+      "testConnection": "Testi ühendust",
+      "toggleUriView": "Klõpsake täieliku URI vaate sisse/välja lülitamiseks",
+      "notConnected": "Pole ühendatud",
+      "errors": {
+        "hostRequired": "Hosti/IP-aadress on kohustuslik"
+      },
+      "candidateStreamTitle": "Kandidaat {{number}}",
+      "probeSuccessful": "Tuvastamine õnnestus",
+      "probeError": "Tuvastamise viga",
+      "probeNoSuccess": "Tuvastamine ebaõnnestus",
+      "deviceInfo": "Seadme info",
+      "autotrackingSupport": "Automaatse jälgimise tugi",
+      "uriCopied": "URI kopeeriti lõikelauale",
+      "rtspCandidates": "RTSP kandidaadid",
+      "probingDevice": "Tuvastan seadet...",
+      "description": "Tuvasta kaamera vooge või seadista käsitsi seaded vastavalt valitud tuvastusmeetodile.",
+      "probeFailed": "Kaamera tuvastamine ebaõnnestus: {{error}}"
     },
     "testResultLabels": {
       "resolution": "Resolutsioon",
@@ -56,7 +120,17 @@
       "roles": "Rollid",
       "none": "Määramata",
       "error": "Viga"
-    }
+    },
+    "commonErrors": {
+      "noUrl": "Palun sisestage kehtiv voogesituse URL",
+      "testFailed": "Voo test ebaõnnestus: {{error}}"
+    },
+    "save": {
+      "success": "Uue kaamera '{{cameraName}}' salvestamine õnnestus.",
+      "failure": "Viga kaamera '{{cameraName}}' salvestamisel."
+    },
+    "title": "Lisa kaamera",
+    "description": "Uue kaamera lisamiseks oma Frigate paigaldisesse järgige alltoodud samme."
   },
   "users": {
     "updatePassword": "Lähtesta salasõna",
@@ -172,24 +246,32 @@
   },
   "documentTitle": {
     "default": "Seadistused - Frigate",
-    "authentication": "Autentimise seadistused - Frigate",
-    "cameraReview": "Kaamerate kordusvaatuste seadistused - Frigate",
-    "general": "Profiili seadistused - Frigate",
-    "frigatePlus": "Frigate+ seadistused - Frigate",
-    "notifications": "Teavituste seadistused - Frigate",
+    "authentication": "Autentimise seaded - Frigate",
+    "cameraReview": "Kaamerate kordusvaatuste seaded - Frigate",
+    "general": "Profiili seaded - Frigate",
+    "frigatePlus": "Frigate+ seaded - Frigate",
+    "notifications": "Teavituste seaded - Frigate",
     "cameraManagement": "Kaamerate haldus - Frigate",
     "masksAndZones": "Maskide ja tsoonide haldus - Frigate",
-    "object": "Silumine ja veaotsing - Frigate"
+    "object": "Silumine ja veaotsing - Frigate",
+    "enrichments": "Rikastamise seaded - Frigate",
+    "motionTuner": "Liikumise häälestaja – Frigate",
+    "globalConfig": "Globaalsed seaded – Frigate",
+    "cameraConfig": "Kaamera seaded - Frigate",
+    "detectorsAndModel": "Detektorid ja mudel – Frigate",
+    "maintenance": "Hooldus – Frigate",
+    "profiles": "Profiilid - Frigate"
   },
   "general": {
-    "title": "Profiili seadistused",
+    "title": "Kasutajaliidese seadistused",
     "cameraGroupStreaming": {
       "clearAll": "Kustuta kõik voogedastuse seadistused"
     },
     "liveDashboard": {
       "title": "Töölaud reaalajas",
       "automaticLiveView": {
-        "label": "Automaatne otseülekande vaade"
+        "label": "Automaatne otseülekande vaade",
+        "desc": "Aktiveerib automaatselt kaamera reaalajas vaate, kui tuvastatakse tegevus. Selle valiku keelamisel uuendatakse kaamerapilti töölaual ainult üks kord minutis."
       }
     },
     "calendar": {
@@ -335,7 +417,7 @@
   },
   "menu": {
     "ui": "Kasutajaliides",
-    "cameraManagement": "Haldus",
+    "cameraManagement": "Kaamera haldus",
     "masksAndZones": "Maskid ja tsoonid",
     "triggers": "Päästikud",
     "debug": "Silumine ja veaotsing",
@@ -373,7 +455,37 @@
     "systemMqtt": "MQTT",
     "systemGo2rtcStreams": "go2rtc voogedastus",
     "integrationSemanticSearch": "Semantiline otsing",
-    "integrationGenerativeAi": "Generatiivne tehisaru"
+    "integrationGenerativeAi": "Generatiivne tehisaru",
+    "general": "Üldine",
+    "globalConfig": "Globaalsed seaded",
+    "system": "Süsteem",
+    "integrations": "Integratsioonid",
+    "cameras": "Kaamera seaded",
+    "integrationFaceRecognition": "Nöotuvastus",
+    "cameraDetect": "Objektituvastus",
+    "cameraFfmpeg": "Vood (FFmpeg)",
+    "cameraRecording": "Salvestus",
+    "cameraSnapshots": "Hetktõmmised",
+    "cameraMotion": "Liikumistuvastus",
+    "cameraObjects": "Objektid",
+    "cameraConfigReview": "Ülevaade",
+    "cameraAudioEvents": "audiotuvastus",
+    "cameraAudioTranscription": "Audio transkriptsioon",
+    "cameraNotifications": "Teated",
+    "cameraLivePlayback": "Otseülekanne",
+    "integrationAudioTranscription": "Audio transkriptsioon",
+    "integrationObjectClassification": "Objektide klassifitseerimine",
+    "cameraFaceRecognition": "Näotuvastus",
+    "cameraMqttConfig": "MQTT",
+    "cameraOnvif": "ONVIF",
+    "cameraUi": "Kaamera kasutajaliides",
+    "cameraTimestampStyle": "Ajatempli stiil",
+    "cameraMqtt": "Kaamera MQTT",
+    "maintenance": "Hooldus",
+    "mediaSync": "Meedia sünkroonimine",
+    "regionGrid": "Regioonide ruudustik",
+    "enrichments": "Andmete rikastamine",
+    "motionTuner": "Liikumistuvastuse seadistaja"
   },
   "dialog": {
     "unsavedChanges": {
@@ -389,7 +501,11 @@
     "semanticSearch": {
       "reindexNow": {
         "confirmButton": "Indekseeri uuesti",
-        "label": "Indekseeri uuesti kohe"
+        "label": "Indekseeri kohe uuesti",
+        "alreadyInProgress": "Ümberindekseerimine on juba käimas.",
+        "error": "Uuesti indekseerimise alustamine ebaõnnestus: {{errorMessage}}",
+        "success": "Ümberindekseerimine algas edukalt.",
+        "confirmTitle": "Kinnita uuesti indekseerimine"
       },
       "modelSize": {
         "small": {
@@ -397,7 +513,9 @@
         },
         "large": {
           "title": "suur"
-        }
+        },
+        "label": "Mudeli suurus",
+        "desc": "Semantilise otsingu manustamiseks kasutatava mudeli suurus."
       },
       "title": "Semantiline otsing"
     },
@@ -408,14 +526,23 @@
         },
         "large": {
           "title": "suur"
-        }
-      }
+        },
+        "label": "Mudeli suurus",
+        "desc": "Näotuvastuseks kasutatava mudeli suurus."
+      },
+      "title": "Näotuvastus"
     },
     "birdClassification": {
       "title": "Lindude klassifikatsioon"
     },
     "licensePlateRecognition": {
       "title": "Sõidukite numbrimärkide tuvastus"
+    },
+    "title": "Andmerikastuse seaded",
+    "restart_required": "Taaskäivitamine on vajalik (Andmerikastuse seadeid on muudetud)",
+    "toast": {
+      "success": "Andmerikastamise seaded on salvestatud. Muudatuste rakendamiseks taaskäivitage Frigate.",
+      "error": "Seadete muudatuste salvestamine ebaõnnestus: {{errorMessage}}"
     }
   },
   "cameraReview": {
@@ -497,5 +624,31 @@
     "lpr": {
       "vehicleNotTracked": "Sõidukite numbrimärkide tuvastus eeldab, et auto või mootorratas on jälgitav. Lülita menüüst Objektid sell kaamera jaoks sisse valikud „auto“ või „mootorratas“."
     }
+  },
+  "button": {
+    "overriddenGlobal": "Ülekirjutatud (Globaalne)",
+    "overriddenGlobalTooltip": "Käesolev kaamera kirjutab selles jaotises üle globaalsed seaded",
+    "overriddenGlobalHeading_one": "See kaamera sürjutab {{count}} üldise seadistuse välja:",
+    "overriddenGlobalHeading_other": "See kaamera sürjutab {{count}} üldise seadistuse välja:"
+  },
+  "saveAllPreview": {
+    "title": "Salvestatavad muudatused",
+    "triggerLabel": "Vaadake üle ootel olevad muudatused",
+    "empty": "Ootel muudatusi pole.",
+    "scope": {
+      "label": "Ulatus",
+      "global": "Globaalne",
+      "camera": "Kaamera: {{cameraName}}"
+    },
+    "profile": {
+      "label": "Profiil"
+    },
+    "field": {
+      "label": "Väli"
+    },
+    "value": {
+      "label": "Uus väärtus",
+      "reset": "Lähtesta"
+    }
   }
 }

web/public/locales/et/views/system.json

@@ -2,7 +2,14 @@
   "documentTitle": {
     "general": "Üldine statistika - Frigate",
     "cameras": "Kaamerate statistika - Frigate",
-    "storage": "Andmeruumi statistika - Frigate"
+    "storage": "Andmeruumi statistika - Frigate",
+    "logs": {
+      "frigate": "Frigate logid - Frigate",
+      "go2rtc": "Go2RTC logid - Frigate",
+      "nginx": "Nginx logid - Frigate",
+      "websocket": "Sõnumite logid - Frigate"
+    },
+    "enrichments": "Rikastus statistika - Frigate"
   },
   "logs": {
     "download": {
@@ -16,11 +23,29 @@
     "websocket": {
       "filter": {
         "cameras_count_one": "{{count}} kaamera",
-        "cameras_count_other": "{{count}} kaamerat"
+        "cameras_count_other": "{{count}} kaamerat",
+        "camera": "Kaamera",
+        "all_cameras": "Kõik kaamerad",
+        "events": "Sündmused",
+        "reviews": "Ülevaated",
+        "system": "Süsteem",
+        "topics": "Teemad",
+        "all": "Kõik teemad",
+        "face_recognition": "Näotuvastus",
+        "classification": "Klassifikatsioon",
+        "camera_activity": "Kaamera aktiivsus",
+        "lpr": "Numbrimärgituvastus"
       },
       "empty": "Ühtegi sõnumit pole veel hõivatud",
       "count_one": "{{count}} sõnum",
-      "count_other": "{{count}} sõnumit"
+      "count_other": "{{count}} sõnumit",
+      "pause": "Peata",
+      "resume": "Jätka",
+      "label": "Sõnumid",
+      "clear": "Tühista",
+      "expanded": {
+        "payload": "Last"
+      }
     },
     "type": {
       "label": "Tüüp",
@@ -36,5 +61,170 @@
       }
     }
   },
-  "title": "Süsteem"
+  "title": "Süsteem",
+  "enrichments": {
+    "embeddings": {
+      "object_description_events_per_second": "Objekti kirjeldus",
+      "face_recognition": "Näotuvastus",
+      "plate_recognition": "Numbrimärgi tuvastus",
+      "object_description": "Objekti kirjeldus",
+      "review_description_events_per_second": "Ülevaate kirjeldus",
+      "review_description": "Ülevaate kirjeldus",
+      "yolov9_plate_detection": "YOLOv9 numbrimärgi tuvastus",
+      "yolov9_plate_detection_speed": "YOLOv9 numbrimärgi tuvastuskiirus",
+      "plate_recognition_speed": "Numbrimärgituvastuse kiirus",
+      "face_recognition_speed": "Näotuvastuse kiirus"
+    },
+    "title": "Andmerikastused"
+  },
+  "cameras": {
+    "connectionQuality": {
+      "reconnectsLastHour": "Uuesti ühendumisi (viimase tunni jooksul)",
+      "stallsLastHour": "Seiskumisi (viimase tunni jooksul)",
+      "title": "Ühenduse kvaliteet",
+      "excellent": "Suurepärane",
+      "fair": "Rahuldav",
+      "poor": "Kehv",
+      "unusable": "Mittekasutatav",
+      "fps": "Kaadrisagedus",
+      "expectedFps": "Eeldatav kaadrisagedus (FPS)"
+    },
+    "label": {
+      "camera": "kaamera",
+      "detect": "tuvasta",
+      "skipped": "vahele jäetud",
+      "ffmpeg": "FFmpeg",
+      "cameraFfmpeg": "{{camName}} FFmpeg",
+      "cameraGpu": "{{camName}} GPU",
+      "cameraDetect": "{{camName}} tuvastus",
+      "overallFramesPerSecond": "kaadreid sekundis kokku",
+      "overallDetectionsPerSecond": "kogutuvastusi sekundis",
+      "overallSkippedDetectionsPerSecond": "vahelejäänud tuvastusi sekundis kokku",
+      "cameraFramesPerSecond": "{{camName}} kaadreid sekundis",
+      "cameraDetectionsPerSecond": "{{camName}} tuvastusi sekundis",
+      "cameraSkippedDetectionsPerSecond": "{{camName}} vahelejäänud tuvastusi sekundis",
+      "capture": "jäädvustamine"
+    },
+    "noCameras": {
+      "title": "Ühtegi kaamerat ei leitud"
+    },
+    "framesAndDetections": "Kaadreid / Tuvastusi",
+    "info": {
+      "keyframes": {
+        "recordDisabled": "Selle kaamera salvestamine on välja lülitatud.",
+        "segmentLength": "Salvestuse segmendi pikkus:",
+        "recordStream": "Salvestusvoog:",
+        "keyframeCount": "Vaadeldud võtmekaadrid:",
+        "observedDuration": "Vaadeldud kestus:"
+      },
+      "audio": "Audio:",
+      "error": "Viga: {{error}}",
+      "codec": "Koodek:",
+      "resolution": "Resolutsioon:",
+      "video": "Video:",
+      "aspectRatio": "kuvasuhe",
+      "unknown": "Tundmatu",
+      "fetching": "Kaameraandmete toomine",
+      "stream": "Voog {{idx}}",
+      "streamDataFromFFPROBE": "Vooandmed saadakse <code>ffprobe</code> abil.",
+      "fps": "Kaadrisagedus (FPS):"
+    },
+    "title": "Kaamerad",
+    "overview": "Ülevaade"
+  },
+  "lastRefreshed": "Viimati uuendatud: ",
+  "stats": {
+    "healthy": "Süsteem on töökorras",
+    "detectIsSlow": "{{detect}} on aeglane ({{speed}} ms)",
+    "detectIsVerySlow": "{{detect}} on väga aeglane ({{speed}} ms)",
+    "cameraIsOffline": "{{camera}} on ühenduseta"
+  },
+  "storage": {
+    "cameraStorage": {
+      "camera": "Kaamera",
+      "unused": {
+        "title": "Kasutamata",
+        "tips": "See väärtus ei pruugi Frigate'i jaoks saadaolevat vaba ruumi täpselt kajastada, kui teie draivil on lisaks Frigate'i salvestistele ka muid faile. Frigate ei jälgi salvestusruumi kasutamist väljaspool oma salvestisi."
+      },
+      "bandwidth": "Ribalaius",
+      "storageUsed": "Salvestusmaht",
+      "percentageOfTotalUsed": "protsent kogusummast",
+      "unusedStorageInformation": "Kasutamata salvestusmahu info",
+      "title": "Kaamera salvestusmaht"
+    },
+    "title": "Säilitus",
+    "overview": "Ülevaade",
+    "recordings": {
+      "title": "Salvestused",
+      "earliestRecording": "Varaseim saadaolev salvestis:"
+    },
+    "shm": {
+      "title": "SHM (jagatud mälu) eraldus",
+      "frameLifetime": {
+        "title": "Kaadri eluiga"
+      }
+    }
+  },
+  "metrics": "Süsteemi mõõdikud",
+  "general": {
+    "title": "Üldine",
+    "hardwareInfo": {
+      "gpuUsage": "GPU kasutus",
+      "gpuMemory": "GPU mälu",
+      "gpuInfo": {
+        "vainfoOutput": {
+          "title": "Vainfo väljund",
+          "processOutput": "Protsessi väljund:",
+          "processError": "Protsessi viga:",
+          "returnCode": "Tagastuskood: {{code}}"
+        },
+        "closeInfo": {
+          "label": "Sulge GPU info"
+        },
+        "copyInfo": {
+          "label": "Kopeeri GPU info"
+        },
+        "nvidiaSMIOutput": {
+          "title": "Nvidia SMI väljund",
+          "name": "Nimi: {{name}}",
+          "driver": "Draiver: {{driver}}",
+          "cudaComputerCapability": "CUDA arvutusvõimekus: {{cuda_compute}}",
+          "vbios": "VBios info: {{vbios}}"
+        },
+        "toast": {
+          "success": "GPU info kopeeriti lõikelauale"
+        }
+      },
+      "gpuDecoder": "GPU dekooder",
+      "gpuTemperature": "GPU temperatuur",
+      "gpuEncoder": "GPU kodeerija",
+      "gpuCompute": "GPU arvutus / kodeerimine",
+      "title": "Riistvara info",
+      "npuUsage": "NPU kasutus",
+      "npuMemory": "NPU mälu",
+      "npuTemperature": "NPU temperatuur",
+      "intelGpuWarning": {
+        "title": "Inteli GPU statistika hoiatus",
+        "message": "GPU statistika pole saadaval"
+      }
+    },
+    "otherProcesses": {
+      "series": {
+        "go2rtc": "go2rtc",
+        "recording": "salvestus",
+        "review_segment": "Segmendi ülevaade",
+        "audio_detector": "audio detektor"
+      },
+      "processCpuUsage": "Protsessi CPU kasutus",
+      "processMemoryUsage": "Protsessi mälukasutus"
+    },
+    "detector": {
+      "title": "Detektorid",
+      "memoryUsage": "Detektori mälukasutus",
+      "cpuUsage": "Detektori CPU kasutus",
+      "temperature": "Detektori temperatuur",
+      "inferenceSpeed": "Detektori järelduskiirus",
+      "cpuUsageInformation": "Protsessori võimsus, mida kasutatakse tuvastusmudelite sisend- ja väljundandmete ettevalmistamisel. See väärtus ei mõõda järelduste kasutamist isegi siis, kui kasutatakse graafikaprotsessorit või kiirendit."
+    }
+  }
 }

web/public/locales/fi/views/search.json

@@ -26,7 +26,8 @@
       "max_speed": "Maksimi nopeus",
       "recognized_license_plate": "Tunnistettu rekisterikilpi",
       "has_clip": "Leike löytyy",
-      "has_snapshot": "Tilannekuva löytyy"
+      "has_snapshot": "Tilannekuva löytyy",
+      "attributes": "Muuttujat"
     },
     "searchType": {
       "thumbnail": "Kuvake",

web/public/locales/fr/audio.json

@@ -16,7 +16,7 @@
   "whoop": "Cri strident",
   "sigh": "Soupir",
   "singing": "Chant",
-  "choir": "Chorale",
+  "choir": "Chœur",
   "yodeling": "Yodel",
   "chant": "Chant",
   "mantra": "Mantra",
@@ -33,7 +33,7 @@
   "snoring": "Ronflement",
   "gasp": "Souffle coupé",
   "pant": "halètement",
-  "snort": "Ébrouement",
+  "snort": "Reniflement",
   "camera": "Caméra",
   "cough": "Toux",
   "groan": "Gémissement",
@@ -104,7 +104,7 @@
   "toothbrush": "Brosse à dents",
   "sink": "Évier",
   "scissors": "Ciseaux",
-  "humming": "Bourdonnement",
+  "humming": "Fredonnement",
   "shuffle": "Pas traînants",
   "footsteps": "Bruits de pas",
   "hiccup": "Hoquet",

web/public/locales/fr/components/dialog.json

@@ -67,7 +67,8 @@
       "error": {
         "failed": "Échec du démarrage de l'exportation : {{error}}",
         "endTimeMustAfterStartTime": "L'heure de fin doit être postérieure à l'heure de début.",
-        "noVaildTimeSelected": "La plage horaire sélectionnée n'est pas valide."
+        "noVaildTimeSelected": "La plage horaire sélectionnée n'est pas valide.",
+        "noValidTimeSelected": "Interval de temps invalide"
       },
       "success": "Exportation démarrée avec succès. Consultez le fichier sur la page des exportations.",
       "view": "Vue",
@@ -88,7 +89,9 @@
     "export": "Exporter",
     "fromTimeline": {
       "saveExport": "Enregistrer l'exportation",
-      "previewExport": "Aperçu de l'exportation"
+      "previewExport": "Aperçu de l'exportation",
+      "queueingExport": "Traitement de l'export...",
+      "useThisRange": "Utiliser cet interval"
     },
     "case": {
       "label": "Dossier",
@@ -195,6 +198,10 @@
       "markAsReviewed": "Marquer comme traité",
       "deleteNow": "Supprimer maintenant",
       "markAsUnreviewed": "Marquer comme non traité"
+    },
+    "shareTimestamp": {
+      "label": "Partager cette date",
+      "title": "Partager cette date"
     }
   },
   "imagePicker": {

web/public/locales/gl/audio.json

@@ -8,12 +8,59 @@
   "sigh": "Suspiro",
   "singing": "Cantando",
   "motorcycle": "Motocicleta",
-  "bus": "Bus",
+  "bus": "Autobús",
   "train": "Tren",
-  "boat": "Bote",
+  "boat": "Barco",
   "bird": "Paxaro",
   "cat": "Gato",
-  "bellow": "Abaixo",
-  "whoop": "Ei carballeira",
-  "whispering": "Murmurando"
+  "bellow": "Bramido",
+  "whoop": "Berro de alegría",
+  "whispering": "Susurro",
+  "laughter": "Risa",
+  "choir": "Coro",
+  "chant": "Canto",
+  "child_singing": "Neno Cantando",
+  "rapping": "Rapeando",
+  "horse": "Cabalo",
+  "pig": "Porco",
+  "goat": "Cabra",
+  "sheep": "Ovella",
+  "wild_animals": "Animais salvaxes",
+  "crow": "Corvo",
+  "dogs": "Cans",
+  "snicker": "Risa abafada",
+  "yodeling": "Iolando",
+  "humming": "Tarareo",
+  "groan": "Xemido",
+  "grunt": "Gruñido",
+  "synthetic_singing": "Canto Sintético",
+  "whistling": "Asubío",
+  "breathing": "Respiración",
+  "wheeze": "Sibilancia",
+  "snoring": "Ronquido",
+  "gasp": "Inspiración brusca",
+  "pant": "Respiración axitada",
+  "snort": "Bufido",
+  "cough": "Tose",
+  "throat_clearing": "Carraspeo",
+  "sneeze": "Espirro",
+  "sniff": "Cheirada",
+  "run": "Correr",
+  "shuffle": "Arrastre de pés",
+  "footsteps": "Pasos",
+  "hands": "Mans",
+  "dog": "Can",
+  "fart": "Peido",
+  "applause": "Aplauso",
+  "chatter": "Parloteo",
+  "crowd": "Multitude",
+  "children_playing": "Nenos Xogando",
+  "animal": "Animal",
+  "pets": "Mascotas",
+  "bark": "Ladrido",
+  "yip": "Gañido",
+  "howl": "Ouveo",
+  "clapping": "Aplausos",
+  "heartbeat": "Latexo do corazón",
+  "heart_murmur": "Sopro cardíaco"
 }

web/public/locales/gl/common.json

@@ -10,5 +10,8 @@
     "untilRestart": "Ata o reinicio",
     "ago": "Fai {{timeAgo}}"
   },
-  "readTheDocumentation": "Ler a documentación"
+  "readTheDocumentation": "Ler a documentación",
+  "button": {
+    "save": "Gardar"
+  }
 }

web/public/locales/gl/objects.json

@@ -3,9 +3,9 @@
   "bicycle": "Bicicleta",
   "airplane": "Avión",
   "motorcycle": "Motocicleta",
-  "bus": "Bus",
+  "bus": "Autobús",
   "train": "Tren",
-  "boat": "Bote",
+  "boat": "Barco",
   "traffic_light": "Luces de tráfico",
   "fire_hydrant": "Boca de incendio",
   "street_sign": "Sinal de tráfico",
@@ -14,5 +14,11 @@
   "bench": "Banco",
   "bird": "Paxaro",
   "cat": "Gato",
-  "car": "Coche"
+  "car": "Coche",
+  "horse": "Cabalo",
+  "goat": "Cabra",
+  "sheep": "Ovella",
+  "dog": "Can",
+  "animal": "Animal",
+  "bark": "Ladrido"
 }

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

@@ -1,6 +1,6 @@
 {
   "description": {
-    "addFace": "Navegar para engadir unha nova colección á Libraría de Caras.",
+    "addFace": "Engade unha nova colección á Biblioteca de rostros subindo a túa primeira imaxe.",
     "placeholder": "Introduce un nome para esta colección",
     "invalidName": "Nome non válido. Os nomes só poden incluír letras, números, espazos, apóstrofes, guións baixos e guións."
   },

web/public/locales/gl/views/search.json

@@ -2,7 +2,7 @@
   "search": "Pesquisar",
   "savedSearches": "Pesquisas gardadas",
   "button": {
-    "save": "Gardar pesquisa",
+    "save": "Gardar procura",
     "filterActive": "Filtros activos",
     "clear": "Borrar pesquisa"
   },

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

@@ -3,7 +3,7 @@
     "default": "Preferencias - Frigate",
     "authentication": "Configuracións de Autenticación - Frigate",
     "camera": "Configuracións da Cámara - Frigate",
-    "general": "Configuracións xerais - Frigate",
+    "general": "Configuracións UI - Frigate",
     "notifications": "Configuración de Notificacións - Frigate",
     "enrichments": "Configuración complementarias - Frigate",
     "masksAndZones": "Editor de máscaras e zonas - Frigate"

web/public/locales/hu/audio.json

@@ -433,5 +433,22 @@
   "trickle": "Csörgedezés",
   "gush": "Folyás",
   "stir": "Kavarás",
-  "thump": "Puffanás"
+  "thump": "Puffanás",
+  "arrow": "Nyíl",
+  "bouncing": "Pattog",
+  "vibration": "Vibrálás",
+  "inside": "Belül",
+  "outside": "Kívül",
+  "mains_hum": "Hálózati zaj",
+  "distortion": "Torzulás",
+  "throbbing": "Lüktetés",
+  "flap": "Csapkodás",
+  "scratch": "Kapar",
+  "scrape": "Karcolás",
+  "rub": "Dörzsölés",
+  "roll": "Gördül",
+  "crushing": "Összenyom",
+  "crumpling": "Gyűrődés",
+  "beep": "Sípolás",
+  "clang": "Csengés"
 }

web/public/locales/id/components/dialog.json

@@ -24,6 +24,9 @@
         },
         "state": {
           "submitted": "Terkirim"
+        },
+        "toast": {
+          "error": "Gagal submit ke Frigate+. Harap periksa koneksi jaringan Anda dan coba lagi."
         }
       }
     },
@@ -57,7 +60,8 @@
       "view": "Melihat",
       "batchSuccess_other": "{{count}} Ekspor dimulai. Membuka kasusnya sekarang.",
       "batchPartial": "Ekspor berhasil dimulai sebanyak {{successful}} dari total {{total}} ekspor. Kamera yang gagal: {{failedCameras}}",
-      "batchFailed": "Gagal memulai ekspor sebanyak {{total}}. Kamera yang gagal: {{failedCameras}}"
+      "batchFailed": "Gagal memulai ekspor sebanyak {{total}}. Kamera yang gagal: {{failedCameras}}",
+      "batchQueuedPartial": "Antrian ekspor berhasil sebanyak {{successful}} dari total {{total}} ekspor. Kamera yang gagal: {{failedCameras}}"
     },
     "case": {
       "newCaseOption": "Membuat Kasus Baru",
@@ -87,7 +91,9 @@
       "selectGroup": "Pilih grup",
       "noMatchingCameras": "Tidak ada kamera yang sesuai dengan pencarian Anda",
       "selectedCount": "{{terpilih}} / {{total}} terpilih",
-      "namePlaceholder": "Nama dasar opsional untuk ekspor ini"
+      "namePlaceholder": "Nama dasar opsional untuk ekspor ini",
+      "searchOrSelectGroup": "Cari, atau pilih grup kamera...",
+      "selectAll": "Pilih semua kamera"
     },
     "multi": {
       "title_other": "Ekspor {{count}} Ulasan",

web/public/locales/ja/components/camera.json

@@ -67,7 +67,10 @@
           "desc": "このオプションは、ライブストリームに色のアーティファクトが表示され、画像右側に斜めの線が出る場合にのみ有効にしてください。"
         }
       }
-    }
+    },
+    "showAll": "全てのカメラグループを表示",
+    "showLess": "表示を縮小",
+    "editGroups": "カメラグループを編集"
   },
   "debug": {
     "options": {

web/public/locales/ja/components/dialog.json

@@ -24,6 +24,9 @@
         },
         "state": {
           "submitted": "送信済み"
+        },
+        "toast": {
+          "error": "Frigate+への送信に失敗しました。ネットワーク接続を確認して、もう一度お試しください。"
         }
       }
     },
@@ -56,7 +59,8 @@
       "error": {
         "failed": "エクスポートキューの開始に失敗しました: {{error}}",
         "endTimeMustAfterStartTime": "終了時間は開始時間より後である必要があります",
-        "noVaildTimeSelected": "有効な時間範囲が選択されていません"
+        "noVaildTimeSelected": "有効な時間範囲が選択されていません",
+        "noValidTimeSelected": "有効な時間範囲が選択されていません"
       },
       "view": "表示",
       "queued": "エクスポートがキューに追加されました。進捗状況はエクスポートページで確認できます。",
@@ -85,7 +89,14 @@
       "detectionCount_other": "{{count}} 追跡対象",
       "nameLabel": "エクスポート名",
       "namePlaceholder": "これらのエクスポート用オプションのベース名",
-      "exportButton_other": "{{count}} 台のカメラをエクスポート"
+      "exportButton_other": "{{count}} 台のカメラをエクスポート",
+      "searchOrSelectGroup": "検索するか、カメラグループを選択してください...",
+      "selectAll": "全てのカメラを選択",
+      "clearSelection": "選択を解除",
+      "selectWithActivity": "追跡対象のあるカメラ",
+      "selectGroup": "グループを選択",
+      "noMatchingCameras": "検索条件に一致するカメラはありません",
+      "selectedCount": "{{selected}} / {{total}} 個が選択されました"
     },
     "case": {
       "newCaseOption": "新しいケースを作成",

web/public/locales/ja/config/cameras.json

@@ -33,7 +33,7 @@
         },
         "listen": {
             "label": "リスニングタイプ",
-            "description": "検知対象の音声イベントの種類一覧（例：吠え声、火災報知器、悲鳴、会話、叫び声）。"
+            "description": "検出対象の音声イベントの種類の一覧（例：吠え声、火災報知器、会話、叫び声）。"
         },
         "enabled_in_config": {
             "label": "元の音声状態",
@@ -192,11 +192,11 @@
         "description": "このカメラの通知を有効化・制御する設定。"
     },
     "ffmpeg": {
-        "label": "FFmpeg",
-        "description": "FFmpeg の設定。バイナリパス、引数、ハードウェアアクセラレーション、ロール別の出力引数を含みます。",
+        "label": "ストリーム（FFmpeg）",
+        "description": "カメラストリームの入力およびFFmpegのオプション（バイナリパス、引数、ハードウェアアクセラレーション、ロールごとの出力引数など）。",
         "path": {
             "label": "FFmpeg パス",
-            "description": "使用する FFmpeg バイナリのパス、またはバージョンエイリアス（「5.0」または「7.0」）。"
+            "description": "使用する FFmpeg バイナリへのパス、またはバージョンのエイリアス（「7.0」または「8.0」）。"
         },
         "global_args": {
             "label": "FFmpeg グローバル引数",
@@ -512,6 +512,9 @@
             "max_concurrent": {
                 "label": "同時エクスポート数の上限",
                 "description": "同時に処理するエクスポートジョブの最大数。"
+            },
+            "chapters": {
+                "label": "エクスポートされた録画に埋め込むチャプターメタデータ"
             }
         },
         "preview": {
@@ -866,6 +869,10 @@
         "dashboard": {
             "label": "UI に表示",
             "description": "このカメラを Frigate UI 全体に表示するかを切り替えます。無効化した場合、再表示するには設定ファイルを手動編集する必要があります。"
+        },
+        "review": {
+            "label": "再生画面に表示",
+            "description": "このカメラを再生画面（再生ページおよびそのカメラフィルター、モーション再生、履歴表示）に表示するかどうかを切り替えます。"
         }
     },
     "webui_url": {

web/public/locales/ja/config/global.json

@@ -31,7 +31,7 @@
         },
         "listen": {
             "label": "リスニングタイプ",
-            "description": "検知対象の音声イベントの種類一覧（例：吠え声、火災報知器、悲鳴、会話、叫び声）。"
+            "description": "検出対象の音声イベントの種類の一覧（例：吠え声、火災報知器、会話、叫び声）。"
         },
         "enabled_in_config": {
             "label": "元の音声状態",
@@ -715,7 +715,7 @@
         "description": "FFmpeg の設定。バイナリパス、引数、ハードウェアアクセラレーション、ロール別の出力引数を含みます。",
         "path": {
             "label": "FFmpeg パス",
-            "description": "使用する FFmpeg バイナリのパス、またはバージョンエイリアス（「5.0」または「7.0」）。"
+            "description": "使用する FFmpeg バイナリへのパス、またはバージョンのエイリアス（「7.0」または「8.0」）。"
         },
         "global_args": {
             "label": "FFmpeg グローバル引数",
@@ -1067,6 +1067,9 @@
             "max_concurrent": {
                 "label": "同時エクスポート数の上限",
                 "description": "同時に処理するエクスポートジョブの最大数。"
+            },
+            "chapters": {
+                "label": "エクスポートされた録画に埋め込むチャプターメタデータ"
             }
         },
         "preview": {
@@ -1554,6 +1557,10 @@
         "dashboard": {
             "label": "UI に表示",
             "description": "このカメラを Frigate UI 全体に表示するかを切り替えます。無効化した場合、再表示するには設定ファイルを手動編集する必要があります。"
+        },
+        "review": {
+            "label": "再生画面に表示",
+            "description": "このカメラを再生画面（再生ページおよびそのカメラフィルター、モーション再生、履歴表示）に表示するかどうかを切り替えます。"
         }
     },
     "onvif": {

web/public/locales/ja/views/classificationModel.json

@@ -147,7 +147,20 @@
     "title": "分類モデルを編集",
     "descriptionState": "この状態分類モデルのクラスを編集します。変更を反映するにはモデルの再学習が必要です。",
     "descriptionObject": "このオブジェクト分類モデルのオブジェクトタイプおよび分類タイプを編集します。",
-    "stateClassesInfo": "注意: 状態クラスを変更すると、更新後のクラスでモデルを再学習する必要があります。"
+    "stateClassesInfo": "モデルが更新されました。変更を反映させるには、モデルの再学習を行ってください。",
+    "enabled": "有効",
+    "enabledDesc": "このモデルを実行します。無効にすると実行が停止し、分類が行われなくなります。",
+    "saveAttempts": "試行回数の保存",
+    "saveAttemptsDesc": "「最近の分類」UIに保持する分類試行画像の数です。",
+    "motion": "動き検知時に実行",
+    "motionDesc": "設定されたクロップ範囲内で動きが検知された際に、分類を実行します。",
+    "interval": "間隔",
+    "intervalDesc": "定期的な分類実行の間隔（秒）。空欄のままにすると、動きが検知された時のみ実行されます。",
+    "intervalPlaceholder": "間隔なし",
+    "errors": {
+      "saveAttemptsInvalid": "セーブ回数は0以上の整数でなければなりません",
+      "intervalInvalid": "「間隔」は0より大きい整数である必要があります"
+    }
   },
   "deleteDatasetImages": {
     "title": "データセット画像を削除",
@@ -187,5 +200,6 @@
     }
   },
   "reclassifyImageAs": "画像を次として再分類:",
-  "reclassifyImage": "画像を再分類"
+  "reclassifyImage": "画像を再分類",
+  "disabled": "無効"
 }

web/public/locales/ja/views/explore.json

@@ -301,7 +301,7 @@
         "toast": {
           "success": "{{camera}} のアノテーションオフセットが設定ファイルに保存されました。"
         },
-        "desc": "このデータはカメラの detect ストリーム から取得されていますが、表示される画像自体は record ストリーム のものです。そのため、2 つのストリームが完全に同期している可能性は低く、バウンディングボックスと実際の映像が正確に一致しない場合があります。この設定を使用すると、注釈（アノテーション）を 時間的に前後へオフセット することができ、録画映像との位置合わせをより正確に行えます。",
+        "desc": "このデータはカメラの「検出」フィードから取得されますが、「録画」フィードの画像に重ねて表示されます。2つのストリームが完全に同期している可能性は低いため、バウンディングボックスと映像が完全に一致しない場合があります。この設定を使用すると注釈を時間軸上で前後にずらすことができ、録画された映像との位置合わせをより正確に行うことができます。",
         "tips": "映像の再生がバウンディングボックスや軌跡ポイントより先行している場合は値を小さくし、遅れている場合は値を大きくしてください。この値は負の値も指定できます。"
       }
     },

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

@@ -69,7 +69,7 @@
     "integrationObjectClassification": "オブジェクト分類",
     "integrationAudioTranscription": "音声文字起こし",
     "cameraDetect": "物体検知",
-    "cameraFfmpeg": "FFmpeg",
+    "cameraFfmpeg": "ストリーム（FFmpeg）",
     "cameraRecording": "録画",
     "cameraSnapshots": "スナップショット",
     "cameraMotion": "モーション検知",
@@ -662,7 +662,7 @@
       },
       "createUser": {
         "title": "新規ユーザーを作成",
-        "desc": "新しいユーザーアカウントを追加し、Frigate UI へのアクセスロールを指定します。",
+        "desc": "新しいユーザーアカウントを追加し、Frigate UIの各エリアへのアクセス権限となる役割を指定します。",
         "usernameOnlyInclude": "ユーザー名に使用できるのは英数字、.、_ のみです",
         "confirmPassword": "パスワードを確認してください"
       },
@@ -1292,12 +1292,16 @@
       "details": {
         "edit": "カメラ詳細を編集",
         "title": "カメラ詳細を編集",
-        "description": "このカメラの表示名と外部 URL を更新します。Frigate UI 全体で使用されます。",
+        "description": "Frigate UI 全体で、このカメラに使用されている表示名、外部 URL、および公開設定を更新します。",
         "friendlyNameLabel": "表示名",
         "friendlyNameHelp": "Frigate UI 全体でこのカメラに表示される名前です。空欄にするとカメラ ID が使用されます。",
         "webuiUrlLabel": "カメラ Web UI の URL",
         "webuiUrlHelp": "デバッグビューからカメラの Web UI に直接アクセスするための URL です。空欄にするとリンクが無効になります。",
-        "webuiUrlInvalid": "有効な URL を入力してください (例: https://example.com)。"
+        "webuiUrlInvalid": "有効な URL を入力してください (例: https://example.com)。",
+        "dashboardLabel": "ライブダッシュボードに表示",
+        "dashboardHelp": "このカメラをライブダッシュボードに表示します。",
+        "reviewLabel": "レビューに表示",
+        "reviewHelp": "このカメラを、カメラフィルター、モーションレビュー、履歴ビューを含め、レビューに表示します。"
       }
     },
     "cameraConfig": {
@@ -1633,7 +1637,14 @@
       "keyLabel": "キー",
       "valueLabel": "値",
       "keyPlaceholder": "新しいキー",
-      "remove": "削除"
+      "remove": "削除",
+      "providerNameLabel": "プロバイダー名",
+      "providerNamePlaceholder": "例：openai",
+      "variableNameLabel": "変数名",
+      "variableNamePlaceholder": "例：MY_VARIABLE",
+      "loggerNameLabel": "ロガー名",
+      "loggerNamePlaceholder": "例：frigate.record",
+      "keyPatternError": "英字、数字、ハイフン、アンダースコアのみを使用してください（スペースは使用不可）"
     },
     "knownPlates": {
       "namePlaceholder": "例: 妻の車",
@@ -1685,7 +1696,17 @@
       }
     },
     "cameraInputs": {
-      "itemTitle": "ストリーム {{index}}"
+      "itemTitle": "ストリーム {{index}}",
+      "sourceMode": {
+        "restream": "リストリーム (go2rtc)",
+        "manual": "手動入力パス",
+        "go2rtcStreamLabel": "go2rtc ストリーム",
+        "go2rtcStreamPlaceholder": "go2rtc ストリームを選択",
+        "noGo2rtcStreams": "設定済みの go2rtc ストリームはありません",
+        "go2rtcStreamSearch": "ストリームを検索中...",
+        "availableStreams": "利用可能なストリーム",
+        "noMatchingStreams": "一致するストリームはありません"
+      }
     },
     "restartRequiredField": "再起動が必要",
     "restartRequiredFooter": "設定が変更されました - 再起動が必要です",
@@ -2054,7 +2075,11 @@
       "fpsGreaterThanFive": "検知 FPS を 5 より高く設定することは推奨されません。値を大きくしてもパフォーマンス上の問題を引き起こすだけで、メリットはありません。",
       "disabled": "物体検知が無効化されています。スナップショット、レビュー項目、顔認識、ナンバープレート認識、生成AI などのエンリッチメントは機能しません。",
       "resolutionShouldBeMultipleOfFour": "最良の結果を得るため、検知の幅と高さは 4 の倍数にしてください。他の偶数値でも動作しますが、検知ストリームに視覚的なノイズや軽微な歪みが生じる可能性があります。",
-      "aspectRatioMismatch": "入力した幅と高さは現在の検知解像度のアスペクト比と一致していません。映像が引き伸ばされたり歪んだりする可能性があります。"
+      "aspectRatioMismatch": "入力した幅と高さは現在の検知解像度のアスペクト比と一致していません。映像が引き伸ばされたり歪んだりする可能性があります。",
+      "maxFramesSet": "最大フレーム数を設定するとデフォルトの動作が上書きされ、静止物体の追跡が無効になります。これが必要な状況はごく稀ですので使用には注意が必要です。",
+      "squareResolution": "正方形の検出解像度は一般的ではありません。検出の幅と高さは、物体検出モデルの寸法ではなく、カメラのアスペクト比（例：16:9）に合わせる必要があります。アスペクト比が一致しないと、画像が引き伸ばされ、検出精度が低下する可能性があります。",
+      "resolutionHigh": "この検出解像度は推奨値よりも高く、検出精度が向上しないままリソース使用量が増加する可能性があります。ほとんどのカメラでは、1080p以下の検出解像度を推奨します。",
+      "globalResolutionMultipleCameras": "複数のカメラを設定する際は、グローバルな検出解像度が設定されます。すべてのカメラで解像度とアスペクト比が同一でない限り、各カメラのネイティブアスペクト比に合わせて、カメラごとに検出幅と検出高さを定義する必要があります。"
     },
     "objects": {
       "genaiNoDescriptionsProvider": "説明を生成するには「descriptions」ロールを持つ生成AIプロバイダを設定する必要があります。"
@@ -2087,6 +2112,13 @@
     },
     "onvif": {
       "autotrackingNoZones": "オートトラッキング機能を使用するには、少なくとも1つのゾーンが必要です。「マスク / ゾーン」でこのカメラ用のゾーンを定義し、以下でそれを必須ゾーンとして設定してください。"
+    },
+    "model": {
+      "optimizedFor320": "Frigateは320x320のモデルに最適化されており、これはほとんどのセットアップにおいて最適な選択です。640x640のモデルは処理速度が遅く、特定のシナリオでのみ有効です。",
+      "inputDimensionsNotDetectResolution": "モデルの入力幅と高さはオブジェクト検出モデルの入力寸法であり、カメラの検出解像度ではありません。これらは使用しているモデルの寸法と一致している必要があります。通常、320x320や640x640のような正方形のサイズになります。"
+    },
+    "ffmpeg": {
+      "hwaccelManualNotRecommended": "手動でのハードウェアアクセラレーション引数の指定は推奨されません。特定の要件がない限り、お使いのハードウェアに合ったプリセットを選択してください。"
     }
   }
 }

web/public/locales/ja/views/system.json

@@ -174,6 +174,21 @@
       "error": "エラー: {{error}}",
       "tips": {
         "title": "カメラプローブ情報"
+      },
+      "keyframes": {
+        "title": "キーフレームの分析",
+        "analyzing": "キーフレームを分析中... 残り {{seconds}} 秒",
+        "stillAnalyzing": "キーフレームの分析を継続中...",
+        "recordStream": "録画ストリーム：",
+        "keyframeCount": "検出されたキーフレーム：",
+        "observedDuration": "検出された再生時間：",
+        "gap": "キーフレームの間隔（最小／平均／最大）：",
+        "segmentLength": "録画セグメントの長さ：",
+        "ok": "キーフレーム間隔は約 {{seconds}} 秒で、録画および再生に適しています。",
+        "warning": "キーフレームがまばら、または変動的（最長間隔 ~{{seconds}}秒）で、スマートコーデック（H.264+/H.265+）である可能性が高いです。これは推奨されません。",
+        "error": "キーフレーム間隔（約{{seconds}}秒）が録画セグメントの長さ（{{segmentTime}}秒）を超えています。一部のセグメントにキーフレームが含まれない場合があり、再生に支障をきたす可能性があります。カメラでスマート/+コーデックを無効にするか、キーフレーム間隔を短縮してください。",
+        "unknown": "キーフレーム間隔を特定できませんでした。",
+        "recordDisabled": "このカメラでは録画が無効になっています。"
       }
     },
     "framesAndDetections": "フレーム / 検知",

web/public/locales/lv/audio.json

@@ -68,8 +68,8 @@
   "choir": "Koris",
   "yodeling": "Jodelēšana",
   "mantra": "Mantra",
-  "rapping": "Repot",
-  "whistling": "Svilpot",
+  "rapping": "Repošana",
+  "whistling": "Svilpošana",
   "sniff": "Ošņāt",
   "hands": "Rokas",
   "animal": "Dzīvnieks",
@@ -122,5 +122,17 @@
   "fireworks": "Uguņošana",
   "glass": "Stikls",
   "white_noise": "Baltais troksnis",
-  "radio": "Radio"
+  "radio": "Radio",
+  "chant": "Piedziedājums",
+  "synthetic_singing": "Sintētiskā dziedāšana",
+  "groan": "Vaidēšana",
+  "grunt": "Rukšķēšana",
+  "breathing": "Elpošana",
+  "wheeze": "Gārgšana",
+  "snoring": "Krākšana",
+  "gasp": "Elsošana",
+  "pant": "Elšana",
+  "snort": "Šņaukt",
+  "cough": "Klepus",
+  "throat_clearing": "Kakla tīrīšana"
 }

web/public/locales/nb-NO/components/dialog.json

@@ -64,7 +64,8 @@
       "error": {
         "failed": "Kunne ikke legge eksport i kø: {{error}}",
         "noVaildTimeSelected": "Ingen gyldig tidsperiode valgt",
-        "endTimeMustAfterStartTime": "Sluttid må være etter starttid"
+        "endTimeMustAfterStartTime": "Sluttid må være etter starttid",
+        "noValidTimeSelected": "Ingen gyldig tidsperiode valgt"
       },
       "view": "Vis",
       "queued": "Eksport lagt i kø. Se fremdrift på eksportsiden.",

web/public/locales/nb-NO/config/global.json

@@ -330,7 +330,7 @@
             },
             "model_type": {
                 "label": "Type objektdeteksjonsmodell",
-                "description": "Arkitekturtype for detektormodellen (ssd, yolox, yolonas) brukt av enkelte detektorer for optimalisering."
+                "description": "Arkitekturtype for detektormodellen (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) brukt av enkelte detektorer for optimalisering."
             }
         },
         "model_path": {
@@ -503,7 +503,7 @@
         },
         "model_type": {
             "label": "Type objektdeteksjonsmodell",
-            "description": "Arkitekturtype for detektormodellen (ssd, yolox, yolonas) brukt av enkelte detektorer for optimalisering."
+            "description": "Arkitekturtype for detektormodellen (ssd, yolox, yolonas, yolo-generic, rfdetr, dfine) brukt av enkelte detektorer for optimalisering."
         }
     },
     "genai": {

web/public/locales/nb-NO/views/classificationModel.json

@@ -188,7 +188,7 @@
     "title": "Rediger klassifiseringsmodell",
     "descriptionState": "Rediger klassene for denne tilstandsklassifiseringsmodellen. Endringer vil kreve at modellen trenes på nytt.",
     "descriptionObject": "Rediger objekttypen og klassifiseringstypen for denne objektklassifiseringsmodellen.",
-    "stateClassesInfo": "Merk: Endring av tilstandsklasser krever at modellen trenes på nytt med de oppdaterte klassene."
+    "stateClassesInfo": "Modellen ble oppdatert. Tren modellen på nytt for at endringene i klassene skal bli iverksatt."
   },
   "none": "Ingen",
   "reclassifyImageAs": "Reklassifiser bilde som:",

web/public/locales/nb-NO/views/settings.json

@@ -1722,7 +1722,10 @@
       "remove": "Fjern",
       "keyPlaceholder": "Ny nøkkel",
       "keyLabel": "Nøkkel",
-      "valueLabel": "Verdi"
+      "valueLabel": "Verdi",
+      "providerNamePlaceholder": "f.eks. openai",
+      "variableNameLabel": "Variabelnavn",
+      "variableNamePlaceholder": "f.eks MIN_VARIABEL"
     },
     "roleMap": {
       "remove": "Fjern",

web/public/locales/nl/components/dialog.json

@@ -34,6 +34,9 @@
           "label": "Bevestig dit label voor Frigate Plus",
           "ask_a": "Is dit object een <code>{{label}}</code>?",
           "ask_full": "Is dit object een <code>{{untranslatedLabel}}</code> ({{translatedLabel}})?"
+        },
+        "toast": {
+          "error": "Gefaald bij Frigate+ in te dienen. Controleer je netwerkverbinding en probeer opnieuw."
         }
       }
     },
@@ -104,7 +107,14 @@
       "namePlaceholder": "Optionele basisnaam voor deze exporten",
       "queueingButton": "Exporten in wachtrij plaatsen...",
       "exportButton_one": "Export 1 Camera",
-      "exportButton_other": "{{count}} camera's exporteren"
+      "exportButton_other": "{{count}} camera's exporteren",
+      "searchOrSelectGroup": "Zoek of selecteer een cameragroep...",
+      "selectAll": "Selecteer alle camera's",
+      "clearSelection": "Wis selectie",
+      "selectWithActivity": "Camera's met gevolgde objecten",
+      "selectGroup": "Selecteer groep",
+      "noMatchingCameras": "Geen camera's komen overeen met je zoekopdracht",
+      "selectedCount": "{{selected}} / {{total}} geselecteerd"
     },
     "multi": {
       "title_one": "Review 1 exporteren",

web/public/locales/pl/components/dialog.json

@@ -36,6 +36,9 @@
           "ask_an": "Czy ten obiekt to <code>{{label}}</code>?",
           "ask_full": "Czy ten obiekt to <code>{{untranslatedLabel}}</code> ({{translatedLabel}})?",
           "label": "Potwierdź tę etykietę dla Frigate Plus"
+        },
+        "toast": {
+          "error": "Nie udało się przesłać do Frigate+. Sprawdź połączenie sieciowe i spróbuj ponownie."
         }
       }
     },
@@ -70,7 +73,8 @@
       "error": {
         "failed": "Nie udało się zakolejkować eksportu: {{error}}",
         "endTimeMustAfterStartTime": "Czas zakończenia musi być późniejszy niż czas rozpoczęcia",
-        "noVaildTimeSelected": "Nie wybrano prawidłowego zakresu czasu"
+        "noVaildTimeSelected": "Nie wybrano prawidłowego zakresu czasu",
+        "noValidTimeSelected": "Nie wybrano prawidłowego zakresu czasu"
       },
       "view": "Widok",
       "queued": "Eksport dodany do kolejki. Postęp można sprawdzić na stronie eksportów.",

web/public/locales/pl/config/cameras.json

@@ -192,7 +192,7 @@
         },
         "listen": {
             "label": "Typy nasłuchu",
-            "description": "Lista typów zdarzeń audio do wykrywania (na przykład: szczekanie, alarm pożarowy, krzyk, mowa, wrzask)."
+            "description": "Lista typów zdarzeń audio do wykrywania (na przykład: szczekanie, alarm pożarowy, mowa, krzyk)."
         },
         "filters": {
             "label": "Filtry audio",
@@ -322,7 +322,8 @@
             },
             "record": {
                 "description": "Domyślne argumenty wyjściowe dla strumieni z rolą zapisu."
-            }
+            },
+            "description": "Domyślne argumenty wyjściowe używane dla różnych ról FFmpeg, takich jak wykrywanie i nagrywanie."
         },
         "retry_interval": {
             "label": "Czas ponownej próby FFmpeg",
@@ -335,6 +336,13 @@
         "gpu": {
             "label": "Indeks GPU",
             "description": "Domyślny indeks karty graficznej używany do akceleracji sprzętowej, jeśli jest dostępna."
+        },
+        "description": "Wejścia strumienia kamery i opcje FFmpeg, w tym ścieżka do pliku binarnego, args, hwaccel oraz argumenty wyjściowe dla poszczególnych ról.",
+        "path": {
+            "description": "Ścieżka do pliku binarnego FFmpeg lub alias wersji („7.0” lub „8.0”)."
+        },
+        "global_args": {
+            "label": "Argumenty globalne FFmpeg"
         }
     }
 }

web/public/locales/pl/config/global.json

@@ -14,7 +14,7 @@
         },
         "listen": {
             "label": "Typy nasłuchu",
-            "description": "Lista typów zdarzeń audio do wykrywania (na przykład: szczekanie, alarm pożarowy, krzyk, mowa, wrzask)."
+            "description": "Lista typów zdarzeń audio do wykrywania (na przykład: szczekanie, alarm pożarowy, mowa, krzyk)."
         },
         "filters": {
             "label": "Filtry audio",
@@ -165,7 +165,8 @@
             },
             "record": {
                 "description": "Domyślne argumenty wyjściowe dla strumieni z rolą zapisu."
-            }
+            },
+            "description": "Domyślne argumenty wyjściowe używane dla różnych ról FFmpeg, takich jak wykrywanie i nagrywanie."
         },
         "retry_interval": {
             "label": "Czas ponownej próby FFmpeg",
@@ -178,6 +179,12 @@
         "gpu": {
             "label": "Indeks GPU",
             "description": "Domyślny indeks karty graficznej używany do akceleracji sprzętowej, jeśli jest dostępna."
+        },
+        "path": {
+            "description": "Ścieżka do pliku binarnego FFmpeg lub alias wersji („7.0” lub „8.0”)."
+        },
+        "global_args": {
+            "label": "Argumenty globalne FFmpeg"
         }
     }
 }

web/public/locales/pt-BR/components/dialog.json

@@ -19,8 +19,8 @@
         "question": {
           "label": "Confirmar esse rótulo para Frigate Plus",
           "ask_a": "Este objeto é um <code>{{label}}</code>?",
-          "ask_an": "Este objeto é um<code>{{label}}</code>?",
-          "ask_full": "Este objeto é um<code>{{untranslatedLabel}}</code> ({{translatedLabel}})?"
+          "ask_an": "Este objeto é um <code>{{label}}</code>?",
+          "ask_full": "Este objeto é um <code>{{untranslatedLabel}}</code> ({{translatedLabel}})?"
         },
         "state": {
           "submitted": "Enviado"
@@ -71,7 +71,10 @@
       "batchQueueFailed": "Falha ao enfileirar {{total}} exportações. Câmeras com falha: {{failedCameras}}",
       "batchPartial": "Iniciadas {{successful}} de {{total}} exportações. Câmeras com falha: {{failedCameras}}",
       "batchFailed": "Falha ao iniciar {{total}} exportações. Câmeras com falha: {{failedCameras}}",
-      "queued": "Exportação na fila. Acompanhe o progresso na página de exportações."
+      "queued": "Exportação na fila. Acompanhe o progresso na página de exportações.",
+      "batchSuccess_one": "1 exportação iniciada. Abrindo o caso agora.",
+      "batchSuccess_many": "{{count}} exportações iniciadas. Abrindo o caso agora.",
+      "batchSuccess_other": "{{count}} exportações iniciadas. Abrindo o caso agora."
     },
     "fromTimeline": {
       "saveExport": "Salvar Exportação",
@@ -132,7 +135,10 @@
         "started_many": "Iniciadas {{count}} exportações. Abrindo o caso agora.",
         "started_other": "",
         "failed": "Falha ao iniciar {{total}} exportações. Falhas: {{failedItems}}",
-        "partial": "Iniciadas {{successful}} de {{total}} exportações. Falhas: {{failedItems}}"
+        "partial": "Iniciadas {{successful}} de {{total}} exportações. Falhas: {{failedItems}}",
+        "startedNoCase_one": "1 exportação iniciada.",
+        "startedNoCase_many": "{{count}} exportações iniciadas.",
+        "startedNoCase_other": "{{count}} exportações iniciadas."
       }
     }
   },

web/public/locales/pt-BR/config/cameras.json

@@ -215,7 +215,8 @@
         "label": "Birdseye",
         "description": "Configurações para a visualização composta \"Birdseye\", que combina múltiplas transmissões de câmera em um único layout.",
         "enabled": {
-            "label": "Ativar Birdseye"
+            "label": "Ativar Birdseye",
+            "description": "Habilita ou desabilita a função Birdseye."
         }
     },
     "live": {
@@ -401,7 +402,9 @@
         "enhancement": {
             "label": "Nível de aprimoramento",
             "description": "Nível de aprimoramento (0-10) a ser aplicado aos recortes da placa antes do OCR; valores mais altos nem sempre melhoram os resultados, e níveis acima de 5 podem funcionar apenas com placas noturnas, devendo ser utilizados com cautela."
-        }
+        },
+        "label": "Reconhecimento de placa veicular",
+        "description": "Configurações de reconhecimento de placa veicular, incluindo limites de detecção, formatação e placas conhecidas."
     },
     "record": {
         "label": "Gravação",
@@ -539,6 +542,18 @@
             "enabled": {
                 "label": "Ativar detecções",
                 "description": "Ative ou desative eventos de detecção para esta câmera."
+            },
+            "labels": {
+                "label": "Rótulos de detecção",
+                "description": "Lista de rótulos de objetos que são considerados eventos de detecção."
+            },
+            "required_zones": {
+                "label": "Zonas requeridas",
+                "description": "Zonas em que um objeto deve entrar para ser considerado detectado. Deixe em branco para permitir qualquer zona."
+            },
+            "cutoff_time": {
+                "label": "Tempo limite de detecção",
+                "description": "Segundos a esperar após o fim da atividade antes de encerrar a detecção."
             }
         }
     }

web/public/locales/pt-BR/config/global.json

@@ -239,7 +239,8 @@
         "label": "Birdseye",
         "description": "Configurações para a visualização composta \"Birdseye\", que combina múltiplas transmissões de câmera em um único layout.",
         "enabled": {
-            "label": "Ativar Birdseye"
+            "label": "Ativar Birdseye",
+            "description": "Habilita ou desabilita a função Birdseye."
         }
     },
     "live": {
@@ -420,7 +421,9 @@
         "enhancement": {
             "label": "Nível de aprimoramento",
             "description": "Nível de aprimoramento (0-10) a ser aplicado aos recortes da placa antes do OCR; valores mais altos nem sempre melhoram os resultados, e níveis acima de 5 podem funcionar apenas com placas noturnas, devendo ser utilizados com cautela."
-        }
+        },
+        "label": "Reconhecimento de placa veicular",
+        "description": "Configurações de reconhecimento de placa veicular, incluindo limites de detecção, formatação e placas conhecidas."
     },
     "record": {
         "label": "Gravação",
@@ -553,6 +556,18 @@
             "description": "Configurações que definem para quais objetos rastreados são geradas detecções (sem gerar alerta) e como essas detecções são retidas.",
             "enabled": {
                 "label": "Ativar detecções"
+            },
+            "labels": {
+                "label": "Rótulos de detecção",
+                "description": "Lista de rótulos de objetos que são considerados eventos de detecção."
+            },
+            "required_zones": {
+                "label": "Zonas requeridas",
+                "description": "Zonas em que um objeto deve entrar para ser considerado detectado. Deixe em branco para permitir qualquer zona."
+            },
+            "cutoff_time": {
+                "label": "Tempo limite de detecção",
+                "description": "Segundos a esperar após o fim da atividade antes de encerrar a detecção."
             }
         }
     }

web/public/locales/pt-BR/views/classificationModel.json

@@ -12,12 +12,12 @@
   },
   "toast": {
     "success": {
-      "deletedCategory_one": "Classe Apagada",
-      "deletedCategory_many": "Classes apagadas",
-      "deletedCategory_other": "",
-      "deletedImage_one": "Imagen Apagada",
-      "deletedImage_many": "Imagens Apagadas",
-      "deletedImage_other": "",
+      "deletedCategory_one": "{{count}} classe removida",
+      "deletedCategory_many": "{{count}} classes removidas",
+      "deletedCategory_other": "{{count}} classes removidas",
+      "deletedImage_one": "{{count}} imagem removida",
+      "deletedImage_many": "{{count}} imagens removidas",
+      "deletedImage_other": "{{count}} imagens removidas",
       "categorizedImage": "Imagem Classificada com Sucesso",
       "trainedModel": "Modelo treinado com sucesso.",
       "trainingModel": "Treinamento do modelo iniciado com sucesso.",

web/public/locales/pt-BR/views/settings.json

@@ -296,7 +296,7 @@
       }
     },
     "motionMaskLabel": "Máscara de Movimento {{number}}",
-    "objectMaskLabel": "Máscara de Objeto {{number}} ({{label}})",
+    "objectMaskLabel": "Máscara de Objeto {{number}}",
     "form": {
       "zoneName": {
         "error": {
@@ -437,7 +437,7 @@
       "add": "Nova Máscara de Movimento",
       "edit": "Editar Máscara de Movimento",
       "context": {
-        "title": "Máscaras de movimento são usadas para prevenir tipos de movimento não desejados de ativarem uma detecção (exemplo: galhos de árvores, timestamps de câmeras). Máscaras de movimento devem ser usadas <em> com moderação </em>. Excesso de mascaramento tornará o rastreamento de objetos mais difícil.",
+        "title": "Máscaras de movimento são usadas para prevenir tipos de movimento não desejados de ativarem uma detecção (exemplo: galhos de árvores, timestamps de câmeras). Máscaras de movimento devem ser usadas <em>com moderação</em>. Excesso de mascaramento tornará o rastreamento de objetos mais difícil.",
         "documentation": "Leia a documentação"
       },
       "point_one": "{{count}} ponto",
@@ -723,7 +723,7 @@
       "title": "Configuração de Captura de Imagem",
       "desc": "Envios ao Frigate+ requerem tanto a captura de imagem normais quanto a captura de imagem <code>clean_copy</code> estarem habilitadas na sua configuração.",
       "documentation": "Leia a documentação",
-      "cleanCopyWarning": "Algumas câmeras possuem captura de imagem habilitada porém têm a cópia limpa desabilitada. Você precisa habilitar a <code>clean_copy</code> nas suas configurações de captura de imagem para poder submeter imagems dessa câmera ao Frigate+.",
+      "cleanCopyWarning": "Algumas câmeras estão com os snapshots desativados",
       "table": {
         "camera": "Câmera",
         "snapshots": "Capturas de Imagem",