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Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
 dependabot[bot]andGitHub
|
a5b10c7e49 |
@@ -49,7 +49,7 @@ transformers == 4.45.*
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# Generative AI
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google-genai == 1.58.*
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ollama == 0.6.*
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openai == 1.65.*
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openai == 3.17.*
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# push notifications
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py-vapid == 1.9.4
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pywebpush == 2.0.*
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@@ -152,10 +152,9 @@ auth:
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models:
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# Optional: the camera environment this model is for (default: shown below)
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# Cameras select a model by setting detect -> scene to a matching value, and
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# the model with a scene of default is used by any camera that does not set one.
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# Any name made up of letters, numbers, _ and - is valid, such as thermal.
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# Models that use the same model file are combined into one model.
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- scene: default
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# a model with a scene of all is used by any camera that does not set one.
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# Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
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- scene: all
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# Required: hardware this model runs on, as <detector> or <detector>:<device>
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# See https://docs.frigate.video/configuration/object_detectors for the
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# detectors available and the devices each one accepts. All of a model's
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@@ -317,9 +316,9 @@ detect:
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# Optional: height of the frame for the input with the detect role (default: use native stream resolution)
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height: 720
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# Optional: the environment this camera looks at, which picks the model it runs on
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# (default: the model with a scene of default)
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# Must match the scene of a configured model
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scene: thermal
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# (default: the model with a scene of all)
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# Valid values are all, indoor, outdoor, indoor_thermal, outdoor_thermal
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scene: outdoor
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# Optional: desired fps for your camera for the input with the detect role (default: shown below)
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# NOTE: Recommended value of 5. Ideally, try and reduce your FPS on the camera.
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fps: 5
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@@ -571,8 +570,6 @@ notifications:
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enabled: False
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# Optional: Email for push service to reach out to
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# NOTE: This is required to use notifications
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# NOTE: Email can be specified with an environment variable or docker secrets that must begin with 'FRIGATE_'.
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# e.g. email: '{FRIGATE_NOTIFICATION_EMAIL}'
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email: "admin@example.com"
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# Optional: Cooldown time for notifications in seconds (default: shown below)
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cooldown: 0
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@@ -85,14 +85,6 @@ An optional config, `save_attempts`, can be set as a key under the model name. T
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</TabItem>
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</ConfigTabs>
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## Review items
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When a model's state changes while its camera has an active review item, the change is recorded on that review item. This includes changes in the few seconds before the item starts, such as a garage door opening just before the car is detected. State changes never create or extend review items on their own, and the first state reported after Frigate starts is not recorded as a change.
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Recorded changes appear in the review item's data as `classification_state_changes` (see the [`frigate/reviews`](/integrations/mqtt#frigatereviews) MQTT topic) and are passed to [GenAI review summaries](/configuration/genai/genai_review) as facts, so a description can note that a gate was opened during the activity.
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Change times are most accurate with `motion: true`. A model that only runs on an `interval` notices a change at its next run, so the change may be recorded late or attached to a later review item.
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## Training the model
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Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of three steps:
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@@ -201,8 +201,6 @@ Review items are sent to the model as a sequence of still frames. Some models fo
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The notes come from tracking data rather than from the images, so they describe activity the model may not have picked up on its own. In testing with a person carrying three waste bins to the curb one at a time, `gemma4` described a single trip on every attempt with `frames`, and consistently described multiple trips with `annotated_frames`. Models that already handle these sequences well, such as the `qwen3-vl` family, gain little and should stay on `frames`.
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Changes reported by [state classification](/configuration/custom_classification/state_classification#review-items) models during the review item are listed in the prompt in both modes. `annotated_frames` also notes each change before the frame where it happened.
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Annotated mode also caps the number of frames, since the notes already establish the order of events and extra near-duplicate frames tend to crowd out the middle of a clip. Longer review items are sampled more sparsely as a result, and typically use fewer tokens than `frames` mode for the same item.
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:::note
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@@ -103,36 +103,32 @@ Coral EdgeTPU and MemryX accelerators can only be opened by one process, so thos
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### Running more than one model
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Cameras can be split across models by scene, which is useful when some cameras benefit from a differently trained model, such as thermal cameras. Each model declares the `scene` it is for, and each camera picks one with `detect -> scene`:
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Cameras can be split across models by scene, which is useful when indoor and outdoor cameras benefit from differently trained models. Each model declares the `scene` it is for, and each camera picks one with `detect -> scene`:
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```yaml
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models:
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- scene: default
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path: plus://your-model
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- scene: outdoor
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path: plus://your-outdoor-model
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devices:
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- edgetpu:pci:0
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- scene: thermal
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path: /config/model_cache/thermal.onnx
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- scene: indoor
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path: /config/model_cache/indoor.onnx
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model_type: yolo-generic
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devices:
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- openvino:GPU
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cameras:
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driveway:
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...
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backyard_thermal:
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detect:
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scene: thermal
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scene: outdoor
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...
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hallway:
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detect:
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scene: indoor
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...
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```
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A scene is any name made up of letters, numbers, `_`, and `-`. The model with a scene of `default` is used by every camera that does not set one (or sets a scene that no model is configured for), and `default` is used when a model does not declare a scene. Changing a camera's scene requires a restart.
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:::warning
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Scenes are for running **different** models. Do not configure the same model under several scenes to dedicate a detector to specific cameras: every detector of a model already serves every camera using it, and splitting them only leaves some detectors idle while others fall behind. Frigate detects models that use the same model file, even under a different path or file name, combines them into one model with all of their hardware, and logs a warning.
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:::
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Available scenes are `all`, `indoor`, `outdoor`, `indoor_thermal`, and `outdoor_thermal`. A model with a scene of `all` is used by every camera that does not set one, and `all` is the default when a model does not declare a scene. Changing a camera's scene requires a restart.
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### Choosing a model size
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@@ -212,7 +212,6 @@ An `update` with the same ID will be published when:
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- The severity changes from `detection` to `alert`
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- Additional objects are detected
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- An object is recognized via face, lpr, etc.
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- A [state classification](/configuration/custom_classification/state_classification#review-items) model changes state
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When the review activity has ended a final `end` message is published.
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@@ -236,8 +235,7 @@ When the review activity has ended a final `end` message is published.
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"objects": ["person", "car"],
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"sub_labels": [],
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"zones": [],
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"audio": [],
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"classification_state_changes": []
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"audio": []
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}
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},
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"after": {
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@@ -256,16 +254,7 @@ When the review activity has ended a final `end` message is published.
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"objects": ["person", "car"],
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"sub_labels": ["Bob"],
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"zones": ["front_yard"],
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"audio": [],
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"classification_state_changes": [
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// verified changes of state classification models on this camera
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{
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"model": "front_gate",
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"from": "closed",
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"to": "open",
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"timestamp": 1718987131.52
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}
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]
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"audio": []
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}
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}
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}
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+3
-19
@@ -306,12 +306,9 @@ def config(request: Request):
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mode="json", warnings="none", exclude_none=True
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)
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is_admin = request.headers.get("remote-role") == "admin"
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# hide environment_vars and the notification email from non-admin users
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if not is_admin:
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# remove environment_vars for non-admin users
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if request.headers.get("remote-role") != "admin":
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config.pop("environment_vars", None)
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redact_credential(config["notifications"], "email")
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# redact mqtt credentials
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redact_credential(config["mqtt"], "password")
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@@ -368,15 +365,7 @@ def config(request: Request):
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camera_name
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)
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if base_sections:
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# copy so redaction below can't alter the profile manager's cache
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camera_dict["base_config"] = copy.deepcopy(base_sections)
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# cameras inherit the global notification email
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if not is_admin:
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redact_credential(camera_dict["notifications"], "email")
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redact_credential(
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camera_dict.get("base_config", {}).get("notifications", {}), "email"
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)
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camera_dict["base_config"] = base_sections
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# remove go2rtc stream passwords
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go2rtc: dict[str, Any] = config_obj.go2rtc.model_dump(
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@@ -404,11 +393,6 @@ def config(request: Request):
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model_dict["non_logo_attributes"] = model.non_logo_attributes
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model_dict["labelmap"] = model.merged_labelmap
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# report the configured reference rather than the resolved cache path,
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# so saving the config back doesn't lose the Frigate+ model
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if model.plus_id:
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model_dict["path"] = f"plus://{model.plus_id}"
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if not config["plus"]["enabled"]:
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continue
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@@ -51,7 +51,6 @@ def swap_runtime_config(app: FastAPI, config: FrigateConfig) -> None:
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if app.stats_emitter is not None:
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app.stats_emitter.config = config
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app.stats_emitter.hardware_stats.set_config(config)
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if app.dispatcher is not None:
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app.dispatcher.config = config
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@@ -63,6 +63,7 @@ from frigate.util.recording_coverage import (
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null_audio_glitches,
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plan_clip,
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resolve_coverage,
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stream_has_audio,
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)
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logger = logging.getLogger(__name__)
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@@ -680,10 +681,15 @@ async def _vod_response(
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end_ts,
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force_discontinuity,
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)
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intervals = resolve_coverage(camera_name, start_ts, end_ts)
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# rows contradicting their stream's audio composition are
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# truncated-shutdown glitches
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main_audio = stream_has_audio(intervals, main=True)
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sub_audio = stream_has_audio(intervals, main=False)
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spans = build_spans(
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null_audio_glitches(resolve_coverage(camera_name, start_ts, end_ts)),
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null_audio_glitches(intervals, main_audio, sub_audio),
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stream_preference,
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)
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+3
-2
@@ -49,6 +49,7 @@ from frigate.debug_replay import (
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DebugReplayManager,
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cleanup_replay_cameras,
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)
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from frigate.detectors.detector_config import SceneEnum
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from frigate.detectors.detector_types import api_types
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from frigate.detectors.device import build_detector_config, runner_names
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from frigate.embeddings import EmbeddingProcess, EmbeddingsContext
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@@ -107,7 +108,7 @@ class FrigateApp:
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self.metrics_manager = manager
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self.audio_process: mp.Process | None = None
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self.stop_event = stop_event
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self.detection_queues: dict[str, Queue] = {
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self.detection_queues: dict[SceneEnum, Queue] = {
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model.scene: mp.Queue() for model in config.models
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}
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self.detectors: dict[str, ObjectDetectProcess] = {}
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@@ -394,7 +395,7 @@ class FrigateApp:
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logger.error("Unable to prepare the %s runtime: %s", detector_type, err)
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def start_detectors(self) -> None:
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model_cameras: dict[str, list[str]] = {
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model_cameras: dict[SceneEnum, list[str]] = {
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model.scene: [] for model in self.config.models
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}
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@@ -15,6 +15,7 @@ from frigate.config.camera.updater import (
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CameraConfigUpdateSubscriber,
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)
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from frigate.const import REPLAY_CAMERA_PREFIX
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from frigate.detectors.detector_config import SceneEnum
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from frigate.models import Regions
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from frigate.object_detection.util import detection_frame_size
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from frigate.util.builtin import empty_and_close_queue
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@@ -30,7 +31,7 @@ class CameraMaintainer(threading.Thread):
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def __init__(
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self,
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config: FrigateConfig,
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detection_queues: dict[str, Queue],
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detection_queues: dict[SceneEnum, Queue],
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detected_frames_queue: Queue,
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camera_metrics: DictProxy,
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ptz_metrics: dict[str, PTZMetrics],
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@@ -12,7 +12,6 @@ class DetectionTypeEnum(str, Enum):
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video = "video"
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audio = "audio"
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lpr = "lpr"
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classification_state = "classification_state"
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class DetectionPublisher(Publisher):
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@@ -1,6 +1,6 @@
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from pydantic import Field, model_validator
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from frigate.detectors.detector_config import DEFAULT_SCENE, SCENE_PATTERN
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from frigate.detectors.detector_config import SceneEnum
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from ..base import FrigateBaseModel
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@@ -62,11 +62,10 @@ class DetectConfig(FrigateBaseModel):
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title="Detect width",
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description="Width (pixels) of frames used for the detect stream; leave empty to use the native stream resolution.",
|
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)
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scene: str = Field(
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default=DEFAULT_SCENE,
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pattern=SCENE_PATTERN,
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scene: SceneEnum = Field(
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default=SceneEnum.all,
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title="Detect scene",
|
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description="The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'default' run the model configured with a scene of 'default'.",
|
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description="The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'all' run the model configured with a scene of 'all'.",
|
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)
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fps: int = Field(
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default=5,
|
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|
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@@ -1,7 +1,6 @@
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from pydantic import Field
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|
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from ..base import FrigateBaseModel
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from ..env import EnvString
|
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|
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__all__ = ["NotificationConfig"]
|
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|
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@@ -12,7 +11,7 @@ class NotificationConfig(FrigateBaseModel):
|
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title="Enable notifications",
|
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description="Enable or disable notifications for all cameras; can be overridden per-camera.",
|
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)
|
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email: EnvString | None = Field(
|
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email: str | None = Field(
|
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default=None,
|
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title="Notification email",
|
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description="Email address used for push notifications or required by certain notification providers.",
|
||||
|
||||
+22
-103
@@ -19,7 +19,7 @@ from ruamel.yaml import YAML
|
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|
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from frigate.const import REGEX_JSON
|
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from frigate.detectors import ModelConfig
|
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from frigate.detectors.detector_config import DEFAULT_SCENE
|
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from frigate.detectors.detector_config import SceneEnum
|
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from frigate.detectors.device import DeviceParseError, DeviceSpec, parse_device
|
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from frigate.plus import PlusApi
|
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from frigate.util.builtin import (
|
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@@ -35,7 +35,6 @@ from frigate.util.config import (
|
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migrate_frigate_config,
|
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)
|
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from frigate.util.image import create_mask
|
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from frigate.util.runtime_deps import sha256_of
|
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from frigate.util.services import auto_detect_hwaccel
|
||||
|
||||
from .auth import AuthConfig
|
||||
@@ -537,7 +536,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
models: list[ModelConfig] = Field(
|
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default_factory=_default_models,
|
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title="Detection models",
|
||||
description="Object detection models and the hardware each one runs on. Cameras pick a model by matching their detect.scene against a model's scene, falling back to the 'default' model.",
|
||||
description="Object detection models and the hardware each one runs on. Cameras pick a model by matching their detect.scene against a model's scene.",
|
||||
)
|
||||
|
||||
# GenAI config (named provider configs: name -> GenAIConfig)
|
||||
@@ -652,9 +651,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
)
|
||||
|
||||
_plus_api: PlusApi
|
||||
_model_devices: dict[str, list[DeviceSpec]]
|
||||
# scene -> model, including the scenes of duplicate models folded into another
|
||||
_scene_models: dict[str, ModelConfig]
|
||||
_model_devices: dict[SceneEnum, list[DeviceSpec]]
|
||||
_camera_models: dict[str, ModelConfig]
|
||||
_all_attributes: list[str]
|
||||
_all_attribute_logos: list[str]
|
||||
@@ -689,7 +686,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
def primary_model(self) -> ModelConfig:
|
||||
"""The model used when no specific camera is in play."""
|
||||
for model in self.models:
|
||||
if model.scene == DEFAULT_SCENE:
|
||||
if model.scene == SceneEnum.all:
|
||||
return model
|
||||
|
||||
return self.models[0]
|
||||
@@ -711,7 +708,7 @@ class FrigateConfig(FrigateBaseModel):
|
||||
|
||||
if model is None:
|
||||
camera = self.cameras.get(camera_name)
|
||||
scene = camera.detect.scene if camera is not None else DEFAULT_SCENE
|
||||
scene = camera.detect.scene if camera is not None else SceneEnum.all
|
||||
model = self._resolve_camera_model(camera_name, scene)
|
||||
self._camera_models[camera_name] = model
|
||||
|
||||
@@ -771,14 +768,14 @@ class FrigateConfig(FrigateBaseModel):
|
||||
if not self.models:
|
||||
raise ValueError("At least one model must be configured under models")
|
||||
|
||||
model_devices: dict[str, list[DeviceSpec]] = {}
|
||||
model_devices: dict[SceneEnum, list[DeviceSpec]] = {}
|
||||
# device string -> the scene of the model that already claimed it
|
||||
claimed_devices: dict[str, str] = {}
|
||||
claimed_devices: dict[str, SceneEnum] = {}
|
||||
|
||||
for index, model in enumerate(self.models):
|
||||
scene = model.scene
|
||||
scene = model.scene.value
|
||||
|
||||
if scene in model_devices:
|
||||
if model.scene in model_devices:
|
||||
raise ValueError(
|
||||
f"Multiple models are configured with a scene of '{scene}'. Each model must use a different scene."
|
||||
)
|
||||
@@ -807,20 +804,17 @@ class FrigateConfig(FrigateBaseModel):
|
||||
other = claimed_devices[device.raw]
|
||||
where = (
|
||||
f"twice by model '{scene}'"
|
||||
if other == scene
|
||||
else f"by both the '{other}' and '{scene}' models"
|
||||
if other == model.scene
|
||||
else f"by both the '{other.value}' and '{scene}' models"
|
||||
)
|
||||
raise ValueError(
|
||||
f"Device '{device.raw}' is used {where}, but it can only run one detection process."
|
||||
)
|
||||
|
||||
claimed_devices[device.raw] = scene
|
||||
claimed_devices[device.raw] = model.scene
|
||||
|
||||
self.models[index] = self._load_model(model, devices[0].detector)
|
||||
model_devices[scene] = devices
|
||||
|
||||
self._scene_models = {model.scene: model for model in self.models}
|
||||
self._consolidate_duplicate_models(model_devices)
|
||||
model_devices[model.scene] = devices
|
||||
|
||||
attributes: set[str] = set()
|
||||
attribute_logos: set[str] = set()
|
||||
@@ -844,107 +838,36 @@ class FrigateConfig(FrigateBaseModel):
|
||||
}
|
||||
self._all_labels = labels
|
||||
|
||||
def _consolidate_duplicate_models(
|
||||
self, model_devices: dict[str, list[DeviceSpec]]
|
||||
) -> None:
|
||||
"""Fold models that load the same model file into a single model.
|
||||
|
||||
Separate scenes for one model only split the same work across separate
|
||||
detection queues, so each device serves fewer cameras and is slower
|
||||
overall than one shared model. The duplicate's devices are moved to the
|
||||
model it duplicates and its scene resolves to that model.
|
||||
|
||||
Args:
|
||||
model_devices: Scene to parsed devices, updated in place
|
||||
"""
|
||||
kept: list[ModelConfig] = []
|
||||
hashes: dict[str, str | None] = {}
|
||||
|
||||
def file_hash(path: str) -> str | None:
|
||||
if path not in hashes:
|
||||
hashes[path] = sha256_of(path) if os.path.isfile(path) else None
|
||||
|
||||
return hashes[path]
|
||||
|
||||
def same_model(a: ModelConfig, b: ModelConfig) -> bool:
|
||||
# a model's devices all share a detector, so folding across
|
||||
# detectors would produce an invalid model
|
||||
if model_devices[a.scene][0].detector != model_devices[b.scene][0].detector:
|
||||
return False
|
||||
|
||||
if not a.path or not b.path:
|
||||
return False
|
||||
|
||||
if os.path.realpath(a.path) == os.path.realpath(b.path):
|
||||
return True
|
||||
|
||||
a_hash = file_hash(a.path)
|
||||
return a_hash is not None and a_hash == file_hash(b.path)
|
||||
|
||||
for model in self.models:
|
||||
original = next((other for other in kept if same_model(other, model)), None)
|
||||
|
||||
if original is None:
|
||||
kept.append(model)
|
||||
continue
|
||||
|
||||
# keep the default model so cameras without a scene still find it
|
||||
if model.scene == DEFAULT_SCENE:
|
||||
kept[kept.index(original)] = model
|
||||
original, model = model, original
|
||||
|
||||
logger.warning(
|
||||
"Models '%s' and '%s' use the same model file, so they have been combined into the '%s' model. Defining one model under several scenes to assign detectors to specific cameras is slower and less efficient than letting every detector serve every camera. Remove the '%s' model and list its devices under the '%s' model instead",
|
||||
original.scene,
|
||||
model.scene,
|
||||
original.scene,
|
||||
model.scene,
|
||||
original.scene,
|
||||
)
|
||||
original.devices = [*original.devices, *model.devices]
|
||||
model_devices[original.scene] = [
|
||||
*model_devices[original.scene],
|
||||
*model_devices.pop(model.scene),
|
||||
]
|
||||
self._scene_models[model.scene] = original
|
||||
|
||||
# anything already folded into the duplicate follows it
|
||||
for scene, target in self._scene_models.items():
|
||||
if target is model:
|
||||
self._scene_models[scene] = original
|
||||
|
||||
self.models = kept
|
||||
|
||||
def _resolve_camera_model(self, name: str, scene: str) -> ModelConfig:
|
||||
def _resolve_camera_model(self, name: str, scene: SceneEnum) -> ModelConfig:
|
||||
"""Resolve which model a camera runs on.
|
||||
|
||||
A camera may name a scene no model is configured for, which is valid as
|
||||
long as a 'default' model is there to fall back to.
|
||||
long as an 'all' model is there to fall back to.
|
||||
|
||||
Args:
|
||||
name: Name of the camera
|
||||
scene: The camera's detect scene, which defaults to 'default'
|
||||
scene: The camera's detect scene, which defaults to 'all'
|
||||
|
||||
Returns:
|
||||
The model the camera runs on
|
||||
"""
|
||||
model = self._scene_models.get(scene)
|
||||
by_scene = {model.scene: model for model in self.models}
|
||||
model = by_scene.get(scene)
|
||||
|
||||
if model is not None:
|
||||
return model
|
||||
|
||||
default = self._scene_models.get(DEFAULT_SCENE)
|
||||
default = by_scene.get(SceneEnum.all)
|
||||
|
||||
if default is None:
|
||||
raise ValueError(
|
||||
f"Camera '{name}' has a detect scene of '{scene}', but no model is configured for that scene or for '{DEFAULT_SCENE}'."
|
||||
f"Camera '{name}' has a detect scene of '{scene.value}', but no model is configured for that scene or for 'all'."
|
||||
)
|
||||
|
||||
logger.warning(
|
||||
"Camera '%s' has a detect scene of '%s', but no model is configured for that scene, so the '%s' model is used",
|
||||
"Camera '%s' has a detect scene of '%s', but no model is configured for that scene, so the 'all' model is used",
|
||||
name,
|
||||
scene,
|
||||
DEFAULT_SCENE,
|
||||
scene.value,
|
||||
)
|
||||
return default
|
||||
|
||||
@@ -1075,10 +998,6 @@ class FrigateConfig(FrigateBaseModel):
|
||||
camera_model = self._resolve_camera_model(name, camera_config.detect.scene)
|
||||
self._camera_models[name] = camera_model
|
||||
|
||||
# point cameras at the model their duplicate scene was folded into
|
||||
if camera_config.detect.scene in self._scene_models:
|
||||
camera_config.detect.scene = camera_model.scene
|
||||
|
||||
if camera_config.ffmpeg.hwaccel_args == "auto":
|
||||
camera_config.ffmpeg.hwaccel_args = self.ffmpeg.hwaccel_args
|
||||
|
||||
|
||||
@@ -1,10 +1,10 @@
|
||||
"""Frame annotations derived from object tracking data.
|
||||
|
||||
Builds short notes describing what changed during a review item, keyed to the
|
||||
frames sampled from it. Everything here comes from data already recorded
|
||||
(each event's `path_data` trajectory, the timeline's stationary/active
|
||||
changes, and the review item's state classification changes), so the notes
|
||||
can be stated to the model as fact rather than as something it must perceive.
|
||||
frames sampled from it. Everything here comes from tracked object data already
|
||||
in the database (each event's `path_data` trajectory and the timeline's
|
||||
stationary/active changes), so the notes can be stated to the model as fact
|
||||
rather than as something it must perceive.
|
||||
"""
|
||||
|
||||
import logging
|
||||
@@ -95,15 +95,6 @@ def event_name(event: dict[str, Any]) -> str:
|
||||
return f"{article} {label}"
|
||||
|
||||
|
||||
def describe_classification_change(change: dict[str, Any]) -> str:
|
||||
"""Phrase a state classification change, e.g. 'front gate changed from
|
||||
closed to open'."""
|
||||
model = str(change["model"]).replace("_", " ")
|
||||
before = str(change["from"]).replace("_", " ")
|
||||
after = str(change["to"]).replace("_", " ")
|
||||
return f"{model} changed from {before} to {after}"
|
||||
|
||||
|
||||
def path_legs(points: list[Point]) -> list[Leg]:
|
||||
"""Split a trajectory into runs of travel in a consistent direction.
|
||||
|
||||
@@ -368,38 +359,25 @@ def get_state_changes(detection_ids: list[str]) -> list[dict[str, Any]]:
|
||||
def build_frame_captions(
|
||||
detection_ids: list[str],
|
||||
frame_times: list[float],
|
||||
classification_changes: Sequence[dict[str, Any]] = (),
|
||||
) -> list[str]:
|
||||
"""A caption for each sampled frame, in frame order.
|
||||
|
||||
Every frame gets its index and elapsed time so the model can tell them
|
||||
apart; frames where something changed also carry the tracker and state
|
||||
classification notes for that moment. Returns an empty list when there is
|
||||
nothing to say, which callers treat as a reason to fall back to sending
|
||||
plain frames.
|
||||
apart; frames where something changed also carry the tracker notes for
|
||||
that moment. Returns an empty list when there is nothing to say, which
|
||||
callers treat as a reason to fall back to sending plain frames.
|
||||
"""
|
||||
if not frame_times:
|
||||
return []
|
||||
|
||||
span_end = frame_times[-1]
|
||||
timeline: list[tuple[float, str]] = []
|
||||
events = get_tracked_events(detection_ids)
|
||||
|
||||
# audio and manual review items can have state changes but no tracked objects
|
||||
if events:
|
||||
timeline.extend(
|
||||
(timestamp, f"[tracker] {note}")
|
||||
for timestamp, note in build_timeline(
|
||||
events, span_end, get_state_changes(detection_ids)
|
||||
)
|
||||
)
|
||||
if not events:
|
||||
logger.debug("No tracked events found for review item, skipping annotations")
|
||||
return []
|
||||
|
||||
timeline.extend(
|
||||
(change["timestamp"], f"[state] {describe_classification_change(change)}")
|
||||
for change in classification_changes
|
||||
if change["timestamp"] <= span_end
|
||||
)
|
||||
buckets = annotations_by_frame(sorted(timeline, key=lambda m: m[0]), frame_times)
|
||||
timeline = build_timeline(events, frame_times[-1], get_state_changes(detection_ids))
|
||||
buckets = annotations_by_frame(timeline, frame_times)
|
||||
|
||||
if not buckets:
|
||||
return []
|
||||
@@ -410,7 +388,7 @@ def build_frame_captions(
|
||||
|
||||
for index, timestamp in enumerate(frame_times):
|
||||
lines = [f"Frame {index + 1} of {total} (+{timestamp - origin:.1f}s):"]
|
||||
lines.extend(buckets.get(index, []))
|
||||
lines.extend(f"[tracker] {note}" for note in buckets.get(index, []))
|
||||
captions.append("\n".join(lines))
|
||||
|
||||
return captions
|
||||
|
||||
@@ -40,7 +40,7 @@ from frigate.util.image import get_image_from_recording
|
||||
|
||||
from ..post.api import PostProcessorApi
|
||||
from ..types import DataProcessorMetrics
|
||||
from .review_annotations import build_frame_captions, describe_classification_change
|
||||
from .review_annotations import build_frame_captions
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -254,10 +254,6 @@ class ReviewDescriptionProcessor(PostProcessorApi):
|
||||
"start_time": r["start_time"],
|
||||
"end_time": r["end_time"],
|
||||
"metadata": r["data"]["metadata"],
|
||||
"state_changes": [
|
||||
describe_classification_change(change)
|
||||
for change in sorted_classification_state_changes(r["data"])
|
||||
],
|
||||
}
|
||||
for r in (
|
||||
ReviewSegment.select(
|
||||
@@ -302,9 +298,6 @@ class ReviewDescriptionProcessor(PostProcessorApi):
|
||||
primary_item["start_time"] = primary_seg["start_time"]
|
||||
primary_item["end_time"] = primary_seg["end_time"]
|
||||
|
||||
if primary_seg["state_changes"]:
|
||||
primary_item["state_changes"] = primary_seg["state_changes"]
|
||||
|
||||
# Find overlapping contextual items from other cameras
|
||||
primary_start = primary_seg["start_time"]
|
||||
primary_end = primary_seg["end_time"]
|
||||
@@ -325,25 +318,14 @@ class ReviewDescriptionProcessor(PostProcessorApi):
|
||||
seg_end = seg["end_time"]
|
||||
|
||||
if seg_start < primary_end and primary_start < seg_end:
|
||||
# Avoid duplicates if same camera has multiple overlapping
|
||||
# segments. One with state changes is kept as its own item
|
||||
# so each change stays within its item's time range.
|
||||
if (
|
||||
seg_camera in seen_contextual_cameras
|
||||
and not seg["state_changes"]
|
||||
):
|
||||
continue
|
||||
|
||||
contextual_item = copy.deepcopy(seg["metadata"])
|
||||
contextual_item["camera"] = seg_camera
|
||||
contextual_item["start_time"] = seg_start
|
||||
contextual_item["end_time"] = seg_end
|
||||
|
||||
if seg["state_changes"]:
|
||||
contextual_item["state_changes"] = seg["state_changes"]
|
||||
|
||||
contextual_items.append(contextual_item)
|
||||
seen_contextual_cameras.add(seg_camera)
|
||||
# Avoid duplicates if same camera has multiple overlapping segments
|
||||
if seg_camera not in seen_contextual_cameras:
|
||||
contextual_item = copy.deepcopy(seg["metadata"])
|
||||
contextual_item["camera"] = seg_camera
|
||||
contextual_item["start_time"] = seg_start
|
||||
contextual_item["end_time"] = seg_end
|
||||
contextual_items.append(contextual_item)
|
||||
seen_contextual_cameras.add(seg_camera)
|
||||
|
||||
# Add context array to primary item
|
||||
primary_item["context"] = contextual_items
|
||||
@@ -457,7 +439,6 @@ class ReviewDescriptionProcessor(PostProcessorApi):
|
||||
captions = build_frame_captions(
|
||||
final_data["data"].get("detections") or [],
|
||||
[timestamp for _, timestamp in frames],
|
||||
sorted_classification_state_changes(final_data["data"]),
|
||||
)
|
||||
|
||||
if not captions:
|
||||
@@ -707,39 +688,6 @@ def get_recording_buffer_extension(duration: float) -> float:
|
||||
return buffer_extension
|
||||
|
||||
|
||||
def sorted_classification_state_changes(
|
||||
review_data: dict[str, Any],
|
||||
) -> list[dict[str, Any]]:
|
||||
"""A review item's state classification changes in time order."""
|
||||
return sorted(
|
||||
review_data.get("classification_state_changes") or [],
|
||||
key=lambda change: change["timestamp"],
|
||||
)
|
||||
|
||||
|
||||
def format_classification_state_changes(
|
||||
changes: list[dict[str, Any]], start_time: float, end_time: float
|
||||
) -> list[str]:
|
||||
"""Phrase state classification changes with their timing in the activity.
|
||||
|
||||
Changes are attached while the review item is active, which runs past its
|
||||
end_time by the review cutoff, and a few seconds before its start.
|
||||
"""
|
||||
lines = []
|
||||
|
||||
for change in changes:
|
||||
if change["timestamp"] < start_time:
|
||||
when = "just before the activity started"
|
||||
elif change["timestamp"] > end_time:
|
||||
when = "after the activity ended"
|
||||
else:
|
||||
when = f"{round(change['timestamp'] - start_time)}s into the activity"
|
||||
|
||||
lines.append(f"{describe_classification_change(change)}, {when}")
|
||||
|
||||
return lines
|
||||
|
||||
|
||||
def run_analysis(
|
||||
requestor: InterProcessRequestor,
|
||||
genai_client: GenAIClient,
|
||||
@@ -795,13 +743,6 @@ def run_analysis(
|
||||
unified_objects.append(object_type)
|
||||
|
||||
analytics_data["unified_objects"] = unified_objects
|
||||
analytics_data["classification_state_changes"] = (
|
||||
format_classification_state_changes(
|
||||
sorted_classification_state_changes(final_data["data"]),
|
||||
final_data["start_time"],
|
||||
final_data["end_time"],
|
||||
)
|
||||
)
|
||||
|
||||
metadata = genai_client.generate_review_description(
|
||||
analytics_data,
|
||||
|
||||
@@ -91,23 +91,8 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
|
||||
self.tensor_input_details = self.interpreter.get_input_details()
|
||||
self.tensor_output_details = self.interpreter.get_output_details()
|
||||
self.labelmap = load_labels(labelmap_path, prefill=0, indexed=False)
|
||||
self._forget_unknown_states()
|
||||
self.classifications_per_second.start()
|
||||
|
||||
def _forget_unknown_states(self) -> None:
|
||||
"""Drop verified states that are not labels of the loaded model.
|
||||
|
||||
A retrained model can rename or remove labels. Keeping a state it can
|
||||
no longer produce would report its first verified state as a change
|
||||
from that obsolete label.
|
||||
"""
|
||||
labels = set(self.labelmap.values())
|
||||
self.state_history = {
|
||||
camera: history
|
||||
for camera, history in self.state_history.items()
|
||||
if history["current_state"] in labels
|
||||
}
|
||||
|
||||
def __update_metrics(self, duration: float) -> None:
|
||||
self.classifications_per_second.update()
|
||||
if self.inference_speed:
|
||||
@@ -149,20 +134,15 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
|
||||
# Don't save if state is stable (detected_state == current_state) AND score is 100%
|
||||
return False
|
||||
|
||||
def verify_state_change(
|
||||
self, camera: str, detected_state: str, timestamp: float
|
||||
) -> tuple[str | None, float] | None:
|
||||
def verify_state_change(self, camera: str, detected_state: str) -> str | None:
|
||||
"""
|
||||
Verify state change requires 3 consecutive identical states before publishing.
|
||||
Returns (previous state, time the new state was first seen) once verified,
|
||||
or None if verification not complete. The previous state is None for the
|
||||
first state verified on a camera.
|
||||
Returns state to publish or None if verification not complete.
|
||||
"""
|
||||
if camera not in self.state_history:
|
||||
self.state_history[camera] = {
|
||||
"current_state": None,
|
||||
"pending_state": None,
|
||||
"pending_since": 0.0,
|
||||
"consecutive_count": 0,
|
||||
}
|
||||
|
||||
@@ -177,14 +157,12 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
|
||||
verification["consecutive_count"] += 1
|
||||
|
||||
if verification["consecutive_count"] >= 3:
|
||||
previous_state = verification["current_state"]
|
||||
verification["current_state"] = detected_state
|
||||
verification["pending_state"] = None
|
||||
verification["consecutive_count"] = 0
|
||||
return previous_state, verification["pending_since"]
|
||||
return detected_state
|
||||
else:
|
||||
verification["pending_state"] = detected_state
|
||||
verification["pending_since"] = timestamp
|
||||
verification["consecutive_count"] = 1
|
||||
logger.debug(
|
||||
f"New state '{detected_state}' detected for {camera}, need {3 - verification['consecutive_count']} more consecutive detections"
|
||||
@@ -362,19 +340,16 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
|
||||
)
|
||||
return
|
||||
|
||||
verified = self.verify_state_change(camera, detected_state, timestamp)
|
||||
verified_state = self.verify_state_change(camera, detected_state)
|
||||
|
||||
if verified is not None:
|
||||
previous_state, changed_at = verified
|
||||
if verified_state is not None:
|
||||
self._emit_result(
|
||||
{
|
||||
"type": "classification",
|
||||
"processor": "state",
|
||||
"model_name": self.model_config.name,
|
||||
"camera": camera,
|
||||
"state": detected_state,
|
||||
"previous_state": previous_state,
|
||||
"timestamp": changed_at,
|
||||
"state": verified_state,
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
@@ -47,17 +47,21 @@ class ModelTypeEnum(str, Enum):
|
||||
yologeneric = "yolo-generic"
|
||||
|
||||
|
||||
# the scene of the model used by cameras that don't name one
|
||||
DEFAULT_SCENE = "default"
|
||||
SCENE_PATTERN = r"^[A-Za-z0-9_-]+$"
|
||||
class SceneEnum(str, Enum):
|
||||
"""The camera environment a detection model is intended for."""
|
||||
|
||||
all = "all"
|
||||
indoor = "indoor"
|
||||
outdoor = "outdoor"
|
||||
indoor_thermal = "indoor_thermal"
|
||||
outdoor_thermal = "outdoor_thermal"
|
||||
|
||||
|
||||
class ModelConfig(BaseModel):
|
||||
scene: str = Field(
|
||||
default=DEFAULT_SCENE,
|
||||
pattern=SCENE_PATTERN,
|
||||
scene: SceneEnum = Field(
|
||||
default=SceneEnum.all,
|
||||
title="Model scene",
|
||||
description="A name for the camera environment this model is used for, such as 'thermal'. Cameras select a model by setting detect.scene to a matching value, and the 'default' model is used by any camera that does not set one.",
|
||||
description="The camera environment this model is used for. Cameras select a model by setting detect.scene to a matching value, and 'all' is used by any camera that does not set one.",
|
||||
)
|
||||
devices: list[str] = Field(
|
||||
default_factory=list,
|
||||
@@ -119,7 +123,6 @@ class ModelConfig(BaseModel):
|
||||
_all_attributes: list[str] = PrivateAttr()
|
||||
_all_attribute_logos: list[str] = PrivateAttr()
|
||||
_model_hash: str = PrivateAttr()
|
||||
_plus_id: str | None = PrivateAttr(default=None)
|
||||
|
||||
@property
|
||||
def merged_labelmap(self) -> dict[int, str]:
|
||||
@@ -145,11 +148,6 @@ class ModelConfig(BaseModel):
|
||||
def model_hash(self) -> str:
|
||||
return self._model_hash
|
||||
|
||||
@property
|
||||
def plus_id(self) -> str | None:
|
||||
"""The Frigate+ model id, once a plus:// path has been resolved."""
|
||||
return self._plus_id
|
||||
|
||||
def __init__(self, **config):
|
||||
super().__init__(**config)
|
||||
|
||||
@@ -180,7 +178,6 @@ class ModelConfig(BaseModel):
|
||||
os.makedirs(MODEL_CACHE_DIR, exist_ok=True)
|
||||
|
||||
model_id = self.path[7:]
|
||||
self._plus_id = model_id
|
||||
self.path = os.path.join(MODEL_CACHE_DIR, model_id)
|
||||
model_info_path = f"{self.path}.json"
|
||||
|
||||
|
||||
@@ -11,11 +11,7 @@ from typing import Any
|
||||
from peewee import DoesNotExist
|
||||
|
||||
from frigate.comms.config_updater import ConfigSubscriber
|
||||
from frigate.comms.detections_updater import (
|
||||
DetectionPublisher,
|
||||
DetectionSubscriber,
|
||||
DetectionTypeEnum,
|
||||
)
|
||||
from frigate.comms.detections_updater import DetectionSubscriber, DetectionTypeEnum
|
||||
from frigate.comms.embeddings_updater import (
|
||||
EmbeddingsRequestEnum,
|
||||
EmbeddingsResponder,
|
||||
@@ -172,7 +168,6 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
)
|
||||
self.review_subscriber = ReviewDataSubscriber("")
|
||||
self.detection_subscriber = DetectionSubscriber(DetectionTypeEnum.video.value)
|
||||
self.detection_publisher = DetectionPublisher(DetectionTypeEnum.all.value)
|
||||
self.embeddings_responder = EmbeddingsResponder()
|
||||
self.frame_manager = SharedMemoryFrameManager()
|
||||
|
||||
@@ -361,7 +356,6 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
self.event_end_subscriber.stop()
|
||||
self.recordings_subscriber.stop()
|
||||
self.detection_subscriber.stop()
|
||||
self.detection_publisher.stop()
|
||||
self.event_metadata_publisher.stop()
|
||||
self.event_metadata_subscriber.stop()
|
||||
self.embeddings_responder.stop()
|
||||
@@ -857,21 +851,6 @@ class EmbeddingMaintainer(threading.Thread):
|
||||
f"{result['camera']}/classification/{result['model_name']}",
|
||||
result["state"],
|
||||
)
|
||||
|
||||
# the first state verified after startup is not a change
|
||||
if result["previous_state"] is not None:
|
||||
self.detection_publisher.publish(
|
||||
(
|
||||
result["camera"],
|
||||
{
|
||||
"model": result["model_name"],
|
||||
"from": result["previous_state"],
|
||||
"to": result["state"],
|
||||
"timestamp": result["timestamp"],
|
||||
},
|
||||
),
|
||||
DetectionTypeEnum.classification_state.value,
|
||||
)
|
||||
elif result["processor"] == "object":
|
||||
object_id = result["object_id"]
|
||||
camera = result["camera"]
|
||||
|
||||
@@ -103,10 +103,11 @@ class LlamaCppClient(GenAIClient):
|
||||
_supports_reasoning: bool
|
||||
_image_token_cache: dict[tuple[int, int], int]
|
||||
_text_baseline_tokens: int | None
|
||||
_media_marker: str
|
||||
|
||||
@property
|
||||
def supports_embeddings(self) -> bool:
|
||||
"""llama.cpp exposes a /v1/embeddings endpoint for any loaded model."""
|
||||
"""llama.cpp exposes an /embeddings endpoint for any loaded model."""
|
||||
return True
|
||||
|
||||
def _auth_headers(self) -> dict | None:
|
||||
@@ -158,6 +159,7 @@ class LlamaCppClient(GenAIClient):
|
||||
self._supports_reasoning = False
|
||||
self._image_token_cache = {}
|
||||
self._text_baseline_tokens = None
|
||||
self._media_marker = "<__media__>"
|
||||
|
||||
base_url = (
|
||||
self.genai_config.base_url.rstrip("/")
|
||||
@@ -185,6 +187,7 @@ class LlamaCppClient(GenAIClient):
|
||||
self._supports_audio = info["supports_audio"]
|
||||
self._supports_tools = info["supports_tools"]
|
||||
self._supports_reasoning = info["supports_reasoning"]
|
||||
self._media_marker = info["media_marker"]
|
||||
|
||||
logger.info(
|
||||
"llama.cpp model '%s' initialized — context: %s, vision: %s, audio: %s, tools: %s, reasoning: %s",
|
||||
@@ -212,7 +215,9 @@ class LlamaCppClient(GenAIClient):
|
||||
`architecture.input_modalities` (text/image/audio) — the primary
|
||||
source. When proxied through llama-swap, the same entry carries
|
||||
`status.args` (server launch argv) and, for the loaded model,
|
||||
`meta.n_ctx`.
|
||||
`meta.n_ctx`. /props remains the only source for `media_marker`,
|
||||
which the server randomizes per startup unless LLAMA_MEDIA_MARKER
|
||||
is set.
|
||||
"""
|
||||
info: dict[str, Any] = {
|
||||
"context_size": None,
|
||||
@@ -220,6 +225,7 @@ class LlamaCppClient(GenAIClient):
|
||||
"supports_audio": False,
|
||||
"supports_tools": False,
|
||||
"supports_reasoning": False,
|
||||
"media_marker": "<__media__>",
|
||||
}
|
||||
|
||||
model_entry: dict[str, Any] | None = None
|
||||
@@ -308,8 +314,16 @@ class LlamaCppClient(GenAIClient):
|
||||
# in the Jinja chat template itself.
|
||||
chat_template = props.get("chat_template") or ""
|
||||
info["supports_reasoning"] = "enable_thinking" in chat_template
|
||||
|
||||
media_marker = props.get("media_marker")
|
||||
if isinstance(media_marker, str) and media_marker:
|
||||
info["media_marker"] = media_marker
|
||||
except Exception as e:
|
||||
logger.warning("Failed to query llama.cpp /props endpoint: %s", e)
|
||||
logger.warning(
|
||||
"Failed to query llama.cpp /props endpoint: %s. "
|
||||
"Image embeddings may fail if the server randomized its media marker.",
|
||||
e,
|
||||
)
|
||||
|
||||
return info
|
||||
|
||||
@@ -460,6 +474,9 @@ class LlamaCppClient(GenAIClient):
|
||||
def _transcribe_via_chat(self, audio: bytes, language: str | None) -> str | None:
|
||||
"""Transcribe through /v1/chat/completions, for servers without the
|
||||
transcriptions route.
|
||||
|
||||
The _media_marker / multimodal_data convention is an /embeddings-only
|
||||
protocol, so no marker-refresh retry is needed here.
|
||||
"""
|
||||
prompt = "Transcribe the speech in this audio verbatim. Respond with the transcript only, and with nothing at all if there is no speech."
|
||||
|
||||
@@ -777,16 +794,41 @@ class LlamaCppClient(GenAIClient):
|
||||
)
|
||||
return result if result else None
|
||||
|
||||
def _refresh_media_marker(self) -> bool:
|
||||
"""Re-fetch /props and update the cached media marker if it changed.
|
||||
|
||||
The server randomizes the marker per startup (unless LLAMA_MEDIA_MARKER
|
||||
is set), so a stale marker indicates a restart. Returns True iff the
|
||||
marker was updated to a new value — used to gate a one-shot retry of
|
||||
a failed embeddings request.
|
||||
"""
|
||||
if self.provider is None:
|
||||
return False
|
||||
try:
|
||||
props = self._fetch_llama_props(self.provider, self.genai_config.model)
|
||||
except Exception as e:
|
||||
logger.warning("Failed to refresh llama.cpp media marker: %s", e)
|
||||
return False
|
||||
|
||||
marker = props.get("media_marker")
|
||||
|
||||
if not isinstance(marker, str) or not marker or marker == self._media_marker:
|
||||
return False
|
||||
|
||||
logger.info("llama.cpp media marker changed (server restart); refreshed")
|
||||
self._media_marker = marker
|
||||
return True
|
||||
|
||||
def embed(
|
||||
self,
|
||||
texts: list[str] | None = None,
|
||||
images: list[bytes] | None = None,
|
||||
) -> list[np.ndarray]:
|
||||
"""Generate embeddings via llama.cpp /v1/embeddings endpoint.
|
||||
"""Generate embeddings via llama.cpp /embeddings endpoint.
|
||||
|
||||
Each text or image is one entry in `input`, using the chat-style
|
||||
content array from ggml-org/llama.cpp#29556. Server must be started
|
||||
with --embeddings, and --mmproj for image support.
|
||||
Supports batch requests. Uses content format with prompt_string and
|
||||
multimodal_data for images (PR #15108). Server must be started with
|
||||
--embeddings and --mmproj for multimodal support.
|
||||
"""
|
||||
if self.provider is None:
|
||||
logger.warning(
|
||||
@@ -801,42 +843,49 @@ class LlamaCppClient(GenAIClient):
|
||||
|
||||
EMBEDDING_DIM = 768
|
||||
|
||||
inputs: list[dict[str, Any]] = [
|
||||
{"content": [{"type": "text", "text": text}]} for text in texts
|
||||
]
|
||||
|
||||
encoded_images: list[str] = []
|
||||
for img in images:
|
||||
# llama.cpp uses STB which does not support WebP; convert to JPEG
|
||||
jpeg_bytes = _to_jpeg(img)
|
||||
to_encode = jpeg_bytes if jpeg_bytes is not None else img
|
||||
encoded = base64.b64encode(to_encode).decode("utf-8")
|
||||
# The trailing newline keeps tokenization identical to the older
|
||||
# "<__media__>\n" prompt_string format, so indexed vectors stay valid
|
||||
inputs.append(
|
||||
{
|
||||
"content": [
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {"url": f"data:image/jpeg;base64,{encoded}"},
|
||||
},
|
||||
{"type": "text", "text": "\n"},
|
||||
]
|
||||
}
|
||||
encoded_images.append(base64.b64encode(to_encode).decode("utf-8"))
|
||||
|
||||
def build_content() -> list[dict[str, Any]]:
|
||||
# prompt_string must contain the server's media marker placeholder
|
||||
# for each image. The marker is randomized per server startup.
|
||||
content: list[dict[str, Any]] = []
|
||||
for text in texts:
|
||||
content.append({"prompt_string": text})
|
||||
for encoded in encoded_images:
|
||||
content.append(
|
||||
{
|
||||
"prompt_string": f"{self._media_marker}\n",
|
||||
"multimodal_data": [encoded],
|
||||
}
|
||||
)
|
||||
return content
|
||||
|
||||
def post_embeddings() -> requests.Response:
|
||||
return self._post(
|
||||
f"{self.provider}/embeddings",
|
||||
json={"model": self.genai_config.model, "content": build_content()},
|
||||
timeout=self.timeout,
|
||||
)
|
||||
|
||||
try:
|
||||
response = self._post(
|
||||
f"{self.provider}/v1/embeddings",
|
||||
json={
|
||||
"model": self.genai_config.model,
|
||||
"input": inputs,
|
||||
"encoding_format": "float",
|
||||
},
|
||||
timeout=self.timeout,
|
||||
)
|
||||
response.raise_for_status()
|
||||
items = response.json().get("data")
|
||||
try:
|
||||
response = post_embeddings()
|
||||
response.raise_for_status()
|
||||
except requests.exceptions.RequestException:
|
||||
# The server may have restarted with a new media marker.
|
||||
# Refresh from /props; only retry if the marker actually changed.
|
||||
if not encoded_images or not self._refresh_media_marker():
|
||||
raise
|
||||
response = post_embeddings()
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
|
||||
items = result.get("data", result) if isinstance(result, dict) else result
|
||||
if not isinstance(items, list):
|
||||
logger.warning("llama.cpp embeddings returned unexpected format")
|
||||
return []
|
||||
@@ -847,7 +896,11 @@ class LlamaCppClient(GenAIClient):
|
||||
if emb is None:
|
||||
logger.warning("llama.cpp embeddings item missing embedding field")
|
||||
continue
|
||||
arr = np.array(emb, dtype=np.float32).flatten()
|
||||
arr = np.array(emb, dtype=np.float32)
|
||||
if arr.ndim > 1:
|
||||
# llama.cpp can return token-level embeddings; pool per item
|
||||
arr = arr.mean(axis=0)
|
||||
arr = arr.flatten()
|
||||
orig_dim = arr.size
|
||||
if orig_dim != EMBEDDING_DIM:
|
||||
if orig_dim > EMBEDDING_DIM:
|
||||
|
||||
@@ -104,21 +104,6 @@ def build_review_description_prompt(
|
||||
else:
|
||||
return "\n- (No objects detected)"
|
||||
|
||||
def get_state_changes_section() -> str:
|
||||
# empty when nothing changed so the prompt is otherwise unaffected
|
||||
changes = review_data.get("classification_state_changes")
|
||||
|
||||
if not changes:
|
||||
return ""
|
||||
|
||||
return (
|
||||
"\n\n## State Changes\n\n"
|
||||
"The camera's state classifiers watch fixed areas of the scene and "
|
||||
"reported these changes. They come from the classifiers rather than "
|
||||
"from the images, and they are reliable. Describe each one where it "
|
||||
"fits in the sequence of events.\n- " + "\n- ".join(changes)
|
||||
)
|
||||
|
||||
fields = get_review_field_guidelines(response_style)
|
||||
frame_guidance = f"\n{FRAME_ANNOTATION_GUIDANCE}" if frame_captions else ""
|
||||
|
||||
@@ -160,7 +145,7 @@ Respond with a JSON object matching the provided schema. Field-specific guidance
|
||||
- Camera: {review_data["camera"]}
|
||||
- Total frames: {len(thumbnails)} (Frame 1 = earliest, Frame {len(thumbnails)} = latest){frame_guidance}
|
||||
- Activity started at {review_data["start"]} and lasted {review_data["duration"]} seconds
|
||||
- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}{get_state_changes_section()}
|
||||
- Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}
|
||||
|
||||
## Objects in Scene
|
||||
|
||||
@@ -211,17 +196,6 @@ def build_review_summary_prompt(
|
||||
f" to "
|
||||
f"{datetime.datetime.fromtimestamp(end_ts).strftime('%B %d, %Y at %I:%M %p')}"
|
||||
)
|
||||
has_state_changes = any(
|
||||
"state_changes" in item
|
||||
for event in events
|
||||
for item in [event, *event.get("context", [])]
|
||||
)
|
||||
state_changes_format = (
|
||||
'\n- "state_changes" (only on some events): changes to monitored areas '
|
||||
"reported by the camera's state classifiers, which are reliable"
|
||||
if has_state_changes
|
||||
else ""
|
||||
)
|
||||
prompt = f"""
|
||||
You are a security officer writing a concise security report.
|
||||
|
||||
@@ -229,7 +203,7 @@ Time range: {time_range}
|
||||
|
||||
Input format: Each event is a JSON object with:
|
||||
- "title", "scene", "confidence", "potential_threat_level" (0-2), "other_concerns", "camera", "time", "start_time", "end_time"
|
||||
- "context": array of related events from other cameras that occurred during overlapping time periods{state_changes_format}
|
||||
- "context": array of related events from other cameras that occurred during overlapping time periods
|
||||
|
||||
**Note: Use the "scene" field for event descriptions in the report. Ignore any "shortSummary" field if present.**
|
||||
|
||||
|
||||
+22
-90
@@ -42,8 +42,6 @@ from frigate.util.ownership import chown_to_runtime
|
||||
from frigate.util.recording_coverage import (
|
||||
build_spans,
|
||||
known_video_codecs,
|
||||
null_audio_glitches,
|
||||
realized_timeline,
|
||||
resolve_coverage,
|
||||
stream_media_summary,
|
||||
)
|
||||
@@ -86,20 +84,10 @@ class StreamRun:
|
||||
|
||||
@dataclass
|
||||
class _ChapterWindow:
|
||||
"""A merged-timeline slice, shaped like the recording rows chapters read.
|
||||
|
||||
lead_in is the output time the slice's vod clip plays before start_time,
|
||||
from snapping its first frame back to a keyframe.
|
||||
"""
|
||||
"""A merged-timeline slice, shaped like the recording rows chapters read."""
|
||||
|
||||
start_time: float
|
||||
end_time: float
|
||||
lead_in: float = 0.0
|
||||
|
||||
|
||||
def _lead_in(recording: Any) -> float:
|
||||
"""Output seconds a chapter source plays before its first wall second."""
|
||||
return recording.lead_in if isinstance(recording, _ChapterWindow) else 0.0
|
||||
|
||||
|
||||
# Matches the setpts factor used in timelapse exports (e.g. setpts=0.04*PTS).
|
||||
@@ -388,18 +376,15 @@ class RecordingExporter(threading.Thread):
|
||||
def _resolve_coverage(self) -> tuple[list[list[Any]], set[str], bool]:
|
||||
"""Resolve the export range into the spans the VOD manifest will serve.
|
||||
|
||||
Delegates to the same coverage resolution and glitch nulling the
|
||||
manifest builder uses, so what we plan around and what nginx-vod
|
||||
emits agree by construction. Returns the spans (each [row, start,
|
||||
end, is_main]), the known video codecs, and whether audio survives
|
||||
the range.
|
||||
Delegates to the same coverage resolution the manifest builder
|
||||
uses, so what we plan around and what nginx-vod emits agree by
|
||||
construction. Returns the spans (each [row, start, end, is_main]),
|
||||
the known video codecs, and whether audio survives the range.
|
||||
Memoized: several stages of the export ask the same question, and
|
||||
the recordings backing a finished range do not change under us.
|
||||
"""
|
||||
if self._coverage is None:
|
||||
intervals = null_audio_glitches(
|
||||
resolve_coverage(self.camera, self.start_time, self.end_time)
|
||||
)
|
||||
intervals = resolve_coverage(self.camera, self.start_time, self.end_time)
|
||||
self._coverage = (
|
||||
build_spans(intervals, self.pinned_stream),
|
||||
known_video_codecs(intervals),
|
||||
@@ -448,57 +433,17 @@ class RecordingExporter(threading.Thread):
|
||||
# hand-off to stage around
|
||||
return True
|
||||
|
||||
_spans, codecs, keep_audio = self._resolve_coverage()
|
||||
runs = self._planned_stream_runs()
|
||||
spans, codecs, keep_audio = self._resolve_coverage()
|
||||
runs = self._stream_runs(spans)
|
||||
|
||||
# a range one stream covers end to end has nothing to hand off,
|
||||
# so it stays on the existing path however long it is
|
||||
if len(runs) < 2:
|
||||
return True
|
||||
|
||||
runs = [piece for run in runs for piece in self._split_long_run(run)]
|
||||
return self._stage_stream_runs(runs, codecs, keep_audio)
|
||||
|
||||
def _planned_stream_runs(self) -> list[StreamRun]:
|
||||
"""The runs a mixed range is staged as, one pinned vod playlist each."""
|
||||
runs = self._stream_runs(self._merged_spans())
|
||||
|
||||
if len(runs) < 2:
|
||||
return runs
|
||||
|
||||
return [piece for run in runs for piece in self._split_long_run(run)]
|
||||
|
||||
def _staged_chapter_windows(self) -> list[_ChapterWindow]:
|
||||
"""Chapter windows for the staged files as they were rendered.
|
||||
|
||||
Each staged run comes from its own pinned vod playlist, whose first
|
||||
clip snaps back to the preceding keyframe, so a staged file runs up
|
||||
to a GOP longer than its slice of the merged timeline. Planning each
|
||||
run the way its playlist does carries that lead-in into the chapter
|
||||
offsets instead of letting it accumulate at every hand-off.
|
||||
"""
|
||||
windows: list[_ChapterWindow] = []
|
||||
|
||||
for run in self._planned_stream_runs():
|
||||
intervals = null_audio_glitches(
|
||||
resolve_coverage(self.camera, run.start_time, run.end_time)
|
||||
)
|
||||
|
||||
for clip in realized_timeline(intervals, run.stream_type):
|
||||
# a skipped clip is absent from the playlist and the file
|
||||
if clip["duration"] <= 0:
|
||||
continue
|
||||
|
||||
span = clip["end_time"] - clip["start_time"]
|
||||
windows.append(
|
||||
_ChapterWindow(
|
||||
clip["start_time"],
|
||||
clip["end_time"],
|
||||
max(0.0, clip["duration"] / 1000 - span),
|
||||
)
|
||||
)
|
||||
|
||||
return windows
|
||||
|
||||
def _stream_runs(self, spans: list[list[Any]]) -> list[StreamRun]:
|
||||
"""Collapse the merged spans into contiguous runs of one stream type.
|
||||
|
||||
@@ -895,8 +840,6 @@ class RecordingExporter(threading.Thread):
|
||||
clipped_end = min(float(rec.end_time), float(self.end_time))
|
||||
if clipped_end <= clipped_start:
|
||||
continue
|
||||
# a staged window's keyframe lead-in plays before it
|
||||
output_offset += _lead_in(rec)
|
||||
windows.append((clipped_start, clipped_end, output_offset))
|
||||
output_offset += clipped_end - clipped_start
|
||||
|
||||
@@ -1044,13 +987,9 @@ class RecordingExporter(threading.Thread):
|
||||
if duration_ms <= 0:
|
||||
continue
|
||||
|
||||
# a staged window's keyframe lead-in opens its chapter, with
|
||||
# frames captured that long before the window
|
||||
lead_in = _lead_in(rec)
|
||||
duration_ms += int(round(lead_in * 1000))
|
||||
title = datetime.datetime.fromtimestamp(
|
||||
clipped_start - lead_in, tz=tz
|
||||
).isoformat(timespec="seconds")
|
||||
title = datetime.datetime.fromtimestamp(clipped_start, tz=tz).isoformat(
|
||||
timespec="seconds"
|
||||
)
|
||||
chapter_blocks.append(
|
||||
"[CHAPTER]\n"
|
||||
"TIMEBASE=1/1000\n"
|
||||
@@ -1189,12 +1128,12 @@ class RecordingExporter(threading.Thread):
|
||||
if self.staged_runs:
|
||||
# each run was already rendered to a temp file with a common
|
||||
# track timescale, so the concat demuxer has nothing left to
|
||||
# reconcile
|
||||
recordings = (
|
||||
self._staged_chapter_windows()
|
||||
if self.chapters not in (None, ChaptersEnum.none)
|
||||
else []
|
||||
)
|
||||
# reconcile and every chapter offset lines up with the merged
|
||||
# timeline the staged files reproduce
|
||||
recordings = [
|
||||
_ChapterWindow(span_start, span_end)
|
||||
for _row, span_start, span_end, _is_main in self._merged_spans()
|
||||
]
|
||||
playlist_lines: list[str] = [f"file '{path}'" for path in self.staged_runs]
|
||||
ffmpeg_input = (
|
||||
"-y -protocol_whitelist pipe,file -f concat -safe 0 -i /dev/stdin"
|
||||
@@ -1210,18 +1149,11 @@ class RecordingExporter(threading.Thread):
|
||||
# its own rows are the ones the chapters describe
|
||||
recordings = self._get_recordings_for_range(pin)
|
||||
else:
|
||||
# an unstaged auto range resolves to at most one stream run, and
|
||||
# its rows are the ones the chapters describe. Main rows the
|
||||
# manifest drops (glitches, slivers at the edges of a sub range)
|
||||
# must not stand in for it.
|
||||
runs = self._stream_runs(self._merged_spans())
|
||||
recordings = self._get_recordings_for_range(
|
||||
runs[0].stream_type if runs else STREAM_TYPE_MAIN
|
||||
)
|
||||
# never mix streams in one playlist; use main when available
|
||||
# and fall back to sub for expired-main history
|
||||
recordings = self._get_recordings_for_range(STREAM_TYPE_MAIN)
|
||||
|
||||
# never mix streams in one playlist; fall back to sub for
|
||||
# expired-main history
|
||||
if not recordings and not runs:
|
||||
if not recordings:
|
||||
recordings = self._get_recordings_for_range(STREAM_TYPE_SUB)
|
||||
|
||||
playlist_lines = []
|
||||
|
||||
@@ -490,17 +490,9 @@ class RecordingMaintainer(threading.Thread):
|
||||
)
|
||||
reviews = reviews_by_camera[camera]
|
||||
|
||||
# probes run concurrently, but each segment's start chains off the
|
||||
# previous segment's end, so starts resolve in segment order
|
||||
previous: asyncio.Event | None = None
|
||||
for recording in recordings:
|
||||
resolved = asyncio.Event()
|
||||
tasks.append(
|
||||
self._validate_in_order(
|
||||
camera, reviews, recording, previous, resolved
|
||||
)
|
||||
)
|
||||
previous = resolved
|
||||
tasks.extend(
|
||||
[self.validate_and_move_segment(camera, reviews, r) for r in recordings]
|
||||
)
|
||||
|
||||
# publish most recently available recording time and None if disabled
|
||||
if stream_type == STREAM_TYPE_MAIN:
|
||||
@@ -558,33 +550,12 @@ class RecordingMaintainer(threading.Thread):
|
||||
while info and info[0][0] < expire_before:
|
||||
info.pop(0)
|
||||
|
||||
async def _validate_in_order(
|
||||
self,
|
||||
camera: str,
|
||||
reviews: Any,
|
||||
recording: dict[str, Any],
|
||||
previous_start: asyncio.Event | None,
|
||||
start_resolved: asyncio.Event,
|
||||
) -> dict[str, Any] | None:
|
||||
"""Validate a segment, always releasing the next one in its stream."""
|
||||
try:
|
||||
return await self.validate_and_move_segment(
|
||||
camera, reviews, recording, previous_start, start_resolved
|
||||
)
|
||||
finally:
|
||||
start_resolved.set()
|
||||
|
||||
def drop_segment(self, cache_path: str) -> None:
|
||||
Path(cache_path).unlink(missing_ok=True)
|
||||
self.end_time_cache.pop(cache_path, None)
|
||||
|
||||
async def validate_and_move_segment(
|
||||
self,
|
||||
camera: str,
|
||||
reviews: Any,
|
||||
recording: dict[str, Any],
|
||||
previous_start: asyncio.Event | None = None,
|
||||
start_resolved: asyncio.Event | None = None,
|
||||
self, camera: str, reviews: Any, recording: dict[str, Any]
|
||||
) -> dict[str, Any] | None:
|
||||
cache_path: str = recording["cache_path"]
|
||||
start_time: datetime.datetime = recording["start_time"]
|
||||
@@ -646,9 +617,6 @@ class RecordingMaintainer(threading.Thread):
|
||||
async with self.probe_semaphore:
|
||||
keyframes = await get_keyframe_offsets(cache_path)
|
||||
|
||||
if previous_start is not None:
|
||||
await previous_start.wait()
|
||||
|
||||
start_time = self._resolve_segment_start(
|
||||
camera, stream_type, start_time, duration, cache_path
|
||||
)
|
||||
@@ -686,11 +654,6 @@ class RecordingMaintainer(threading.Thread):
|
||||
RecordingsDataTypeEnum.valid.value,
|
||||
)
|
||||
|
||||
# the start is settled, so the next segment of the stream can chain
|
||||
# off it while this one waits on retention and the move
|
||||
if start_resolved is not None:
|
||||
start_resolved.set()
|
||||
|
||||
record_config = self.config.cameras[camera].record
|
||||
|
||||
# sub's alerts/detections carry the retain mode directly, unlike
|
||||
@@ -1127,7 +1090,6 @@ class RecordingMaintainer(threading.Thread):
|
||||
elif (
|
||||
topic == DetectionTypeEnum.api.value
|
||||
or topic == DetectionTypeEnum.lpr.value
|
||||
or topic == DetectionTypeEnum.classification_state.value
|
||||
):
|
||||
continue
|
||||
|
||||
|
||||
@@ -40,10 +40,6 @@ logger = logging.getLogger(__name__)
|
||||
THUMB_HEIGHT = 180
|
||||
THUMB_WIDTH = 320
|
||||
|
||||
# seconds before a review item starts that a state classification change is
|
||||
# still attached to it, e.g. a garage door opening before the car is visible
|
||||
CLASSIFICATION_STATE_PRE_ROLL = 5
|
||||
|
||||
|
||||
class PendingReviewSegment:
|
||||
def __init__(
|
||||
@@ -65,7 +61,6 @@ class PendingReviewSegment:
|
||||
self.sub_labels = sub_labels
|
||||
self.zones = zones
|
||||
self.audio = audio
|
||||
self.classification_state_changes: list[dict[str, Any]] = []
|
||||
self.thumb_time: float | None = None
|
||||
self.last_alert_time: float | None = None
|
||||
self.last_detection_time: float = frame_time
|
||||
@@ -167,7 +162,6 @@ class PendingReviewSegment:
|
||||
"sub_labels": list(self.sub_labels.values()),
|
||||
"zones": self.zones,
|
||||
"audio": list(self.audio),
|
||||
"classification_state_changes": self.classification_state_changes,
|
||||
"thumb_time": self.thumb_time,
|
||||
"metadata": None,
|
||||
},
|
||||
@@ -299,9 +293,6 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
# manual events
|
||||
self.indefinite_events: dict[str, dict[str, Any]] = {}
|
||||
|
||||
# state classification changes seen while a camera had no review item
|
||||
self.recent_classification_state_changes: dict[str, list[dict[str, Any]]] = {}
|
||||
|
||||
# ensure dirs
|
||||
Path(os.path.join(CLIPS_DIR, "review")).mkdir(exist_ok=True)
|
||||
|
||||
@@ -383,43 +374,6 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
self.active_review_segments[segment.camera] = None
|
||||
return end_time
|
||||
|
||||
def _activate_segment(self, segment: PendingReviewSegment) -> None:
|
||||
"""Make a segment the camera's active one, attaching any state
|
||||
classification changes seen just before it started."""
|
||||
self.active_review_segments[segment.camera] = segment
|
||||
recent = self.recent_classification_state_changes.pop(segment.camera, [])
|
||||
segment.classification_state_changes.extend(
|
||||
c
|
||||
for c in recent
|
||||
if c["timestamp"] >= segment.start_time - CLASSIFICATION_STATE_PRE_ROLL
|
||||
)
|
||||
|
||||
def handle_classification_state_change(
|
||||
self, camera: str, change: dict[str, Any]
|
||||
) -> None:
|
||||
"""Attach a verified state classification change to the active segment.
|
||||
|
||||
State changes never start, extend, or upgrade a segment. A change seen
|
||||
with no active segment is held briefly for a segment starting right
|
||||
after it.
|
||||
"""
|
||||
segment = self.active_review_segments.get(camera)
|
||||
|
||||
if segment is None:
|
||||
cutoff = change["timestamp"] - CLASSIFICATION_STATE_PRE_ROLL
|
||||
self.recent_classification_state_changes[camera] = [
|
||||
c
|
||||
for c in self.recent_classification_state_changes.get(camera, [])
|
||||
if c["timestamp"] >= cutoff
|
||||
] + [change]
|
||||
return
|
||||
|
||||
prev_data = segment.get_data(False)
|
||||
segment.classification_state_changes.append(change)
|
||||
self._publish_segment_update(
|
||||
segment, self.config.cameras[camera], None, [], prev_data
|
||||
)
|
||||
|
||||
def forcibly_end_segment(self, camera: str) -> Any:
|
||||
"""Forcibly end the pending segment for a camera."""
|
||||
segment = self.active_review_segments.get(camera)
|
||||
@@ -468,7 +422,6 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
"""Close out a deleted camera's segment so a reused name cannot inherit it."""
|
||||
self.forcibly_end_segment(camera)
|
||||
self.indefinite_events.pop(camera, None)
|
||||
self.recent_classification_state_changes.pop(camera, None)
|
||||
|
||||
def update_existing_segment(
|
||||
self,
|
||||
@@ -626,7 +579,7 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
audio=set(),
|
||||
zones=list(new_zones),
|
||||
)
|
||||
self._activate_segment(new_segment)
|
||||
self.active_review_segments[segment.camera] = new_segment
|
||||
self._publish_segment_start(new_segment)
|
||||
new_segment.last_detection_time = last_detection_time
|
||||
elif segment.severity == SeverityEnum.detection and frame_time > (
|
||||
@@ -686,7 +639,7 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
audio=set(),
|
||||
zones=zones,
|
||||
)
|
||||
self._activate_segment(new_segment)
|
||||
self.active_review_segments[camera] = new_segment
|
||||
|
||||
try:
|
||||
yuv_frame = self.frame_manager.get(
|
||||
@@ -760,10 +713,6 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
|
||||
if camera not in self.indefinite_events:
|
||||
self.indefinite_events[camera] = {}
|
||||
elif topic == DetectionTypeEnum.classification_state.value:
|
||||
(camera, classification_change) = data
|
||||
else:
|
||||
continue
|
||||
|
||||
if camera not in self.config.cameras:
|
||||
continue
|
||||
@@ -774,10 +723,6 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
):
|
||||
continue
|
||||
|
||||
if topic == DetectionTypeEnum.classification_state:
|
||||
self.handle_classification_state_change(camera, classification_change)
|
||||
continue
|
||||
|
||||
current_segment = self.active_review_segments.get(camera)
|
||||
|
||||
# Check if the current segment should be processed based on enabled settings
|
||||
@@ -919,16 +864,14 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
severity = SeverityEnum.detection
|
||||
|
||||
if severity:
|
||||
self._activate_segment(
|
||||
PendingReviewSegment(
|
||||
camera,
|
||||
frame_time,
|
||||
severity,
|
||||
{},
|
||||
{},
|
||||
[],
|
||||
detections,
|
||||
)
|
||||
self.active_review_segments[camera] = PendingReviewSegment(
|
||||
camera,
|
||||
frame_time,
|
||||
severity,
|
||||
{},
|
||||
{},
|
||||
[],
|
||||
detections,
|
||||
)
|
||||
elif topic == DetectionTypeEnum.api:
|
||||
severity = self.get_manual_event_severity(
|
||||
@@ -945,7 +888,7 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
[],
|
||||
set(),
|
||||
)
|
||||
self._activate_segment(api_segment)
|
||||
self.active_review_segments[camera] = api_segment
|
||||
|
||||
if manual_info["state"] == ManualEventState.start:
|
||||
self.indefinite_events[camera][manual_info["event_id"]] = (
|
||||
@@ -972,7 +915,7 @@ class ReviewSegmentMaintainer(threading.Thread):
|
||||
[],
|
||||
set(),
|
||||
)
|
||||
self._activate_segment(lpr_segment)
|
||||
self.active_review_segments[camera] = lpr_segment
|
||||
|
||||
if manual_info["state"] == ManualEventState.start:
|
||||
self.indefinite_events[camera][manual_info["event_id"]] = (
|
||||
|
||||
@@ -256,17 +256,6 @@ class HardwareStats:
|
||||
)
|
||||
self.update_config()
|
||||
|
||||
def set_config(self, config: FrigateConfig) -> None:
|
||||
"""Follow a runtime config swap and recalculate the monitored hardware.
|
||||
|
||||
The camera update subscriber has to follow too, or later camera updates
|
||||
would land on the discarded config.
|
||||
"""
|
||||
self.config = config
|
||||
self._config_subscriber.config = config
|
||||
self._config_subscriber.camera_configs = config.cameras
|
||||
self.update_config()
|
||||
|
||||
def update_config(self) -> None:
|
||||
"""Recalculate all hardware that needs to be monitored from the config."""
|
||||
names = self._scan_ffmpeg() | self._scan_detectors() | self._scan_enrichments()
|
||||
|
||||
@@ -111,18 +111,15 @@ def get_detector_stats(
|
||||
) -> dict[str, dict[str, Any]]:
|
||||
"""Get stats for all detectors, including temperatures based on detector type."""
|
||||
detector_stats: dict[str, dict[str, Any]] = {}
|
||||
# detector type -> device -> index into that type's temperatures
|
||||
device_indices: dict[str, dict[str, int]] = {}
|
||||
detector_type_indices: dict[str, int] = {}
|
||||
|
||||
for name, detector in stats_tracking["detectors"].items():
|
||||
pid = detector.detect_process.pid if detector.detect_process else None
|
||||
detector_type = detector.detector_config.type
|
||||
|
||||
# temperatures are per physical unit, so a repeated device
|
||||
# ("hailo:PCIe#2", see runner_names) shares its unit's reading
|
||||
device = name.partition("#")[0]
|
||||
type_devices = device_indices.setdefault(detector_type, {})
|
||||
current_index = type_devices.setdefault(device, len(type_devices))
|
||||
# Keep track of the index for each detector type to match temperatures correctly
|
||||
current_index = detector_type_indices.get(detector_type, 0)
|
||||
detector_type_indices[detector_type] = current_index + 1
|
||||
|
||||
detector_stat = {
|
||||
"inference_speed": round(detector.avg_inference_speed.value * 1000, 2), # type: ignore[attr-defined]
|
||||
|
||||
@@ -1,11 +1,8 @@
|
||||
import json
|
||||
import os
|
||||
from unittest.mock import Mock, patch
|
||||
|
||||
import frigate.genai
|
||||
from frigate.config import GenAIProviderEnum
|
||||
from frigate.config.env import FRIGATE_ENV_VARS
|
||||
from frigate.const import MODEL_CACHE_DIR, REDACTED_CREDENTIAL_SENTINEL
|
||||
from frigate.const import REDACTED_CREDENTIAL_SENTINEL
|
||||
from frigate.genai import GenAIClient
|
||||
from frigate.models import Event, Recordings, ReviewSegment
|
||||
from frigate.stats.emitter import StatsEmitter
|
||||
@@ -93,68 +90,6 @@ class TestHttpApp(BaseTestHttp):
|
||||
mqtt = response.json()["mqtt"]
|
||||
assert mqtt["password"] == REDACTED_CREDENTIAL_SENTINEL
|
||||
|
||||
def test_config_response_hides_notification_email_from_viewers(self):
|
||||
self.minimal_config["notifications"] = {"email": "{FRIGATE_TEST_EMAIL}"}
|
||||
|
||||
with patch.dict(FRIGATE_ENV_VARS, {"FRIGATE_TEST_EMAIL": "me@example.com"}):
|
||||
app = super().create_app()
|
||||
|
||||
assert app.frigate_config.notifications.email == "me@example.com"
|
||||
|
||||
with AuthTestClient(app) as client:
|
||||
response = client.get(
|
||||
"/config",
|
||||
headers={"remote-user": "viewer", "remote-role": "viewer"},
|
||||
)
|
||||
assert response.status_code == 200
|
||||
config = response.json()
|
||||
assert config["notifications"]["email"] == REDACTED_CREDENTIAL_SENTINEL
|
||||
assert (
|
||||
config["cameras"]["front_door"]["notifications"]["email"]
|
||||
== REDACTED_CREDENTIAL_SENTINEL
|
||||
)
|
||||
|
||||
response = client.get("/config")
|
||||
assert response.json()["notifications"]["email"] == "me@example.com"
|
||||
|
||||
def test_config_response_keeps_plus_model_reference(self):
|
||||
model_id = "test_plus_reference"
|
||||
model_path = os.path.join(MODEL_CACHE_DIR, model_id)
|
||||
os.makedirs(MODEL_CACHE_DIR, exist_ok=True)
|
||||
|
||||
with open(model_path, "w") as f:
|
||||
f.write("model")
|
||||
|
||||
with open(f"{model_path}.json", "w") as f:
|
||||
json.dump(
|
||||
{
|
||||
"id": model_id,
|
||||
"type": "ssd",
|
||||
"supportedDetectors": ["cpu"],
|
||||
"width": 320,
|
||||
"height": 320,
|
||||
"inputShape": "nhwc",
|
||||
"pixelFormat": "rgb",
|
||||
"labelMap": {"0": "person"},
|
||||
},
|
||||
f,
|
||||
)
|
||||
|
||||
self.addCleanup(os.remove, model_path)
|
||||
self.addCleanup(os.remove, f"{model_path}.json")
|
||||
self.minimal_config["models"] = [
|
||||
{"path": f"plus://{model_id}", "devices": ["cpu"]}
|
||||
]
|
||||
app = super().create_app()
|
||||
|
||||
with AuthTestClient(app) as client:
|
||||
response = client.get("/config")
|
||||
assert response.status_code == 200
|
||||
assert response.json()["models"][0]["path"] == f"plus://{model_id}"
|
||||
|
||||
# detection still loads the resolved cache file
|
||||
assert app.frigate_config.models[0].path == model_path
|
||||
|
||||
####################################################################################################################
|
||||
################################### POST /genai/probe Endpoint ##################################################
|
||||
####################################################################################################################
|
||||
|
||||
@@ -9,6 +9,7 @@ from frigate.config.camera.updater import (
|
||||
CameraConfigUpdateSubscriber,
|
||||
)
|
||||
from frigate.const import SUB_CACHE_TAG
|
||||
from frigate.detectors.detector_config import SceneEnum
|
||||
|
||||
|
||||
def _build_scene_frigate_config(scene: str | None) -> FrigateConfig:
|
||||
@@ -118,7 +119,7 @@ class TestRecordUpdateRecreatesFfmpegCmds(unittest.TestCase):
|
||||
subscriber = CameraConfigUpdateSubscriber(
|
||||
config, {}, [CameraConfigUpdateEnum.add, CameraConfigUpdateEnum.remove]
|
||||
)
|
||||
assert config.model_for_camera("front_door").scene == "outdoor"
|
||||
assert config.model_for_camera("front_door").scene == SceneEnum.outdoor
|
||||
|
||||
subscriber.subscriber.check_for_update.side_effect = [
|
||||
("config/cameras/front_door/remove", config.cameras["front_door"]),
|
||||
@@ -135,7 +136,7 @@ class TestRecordUpdateRecreatesFfmpegCmds(unittest.TestCase):
|
||||
]
|
||||
subscriber.check_for_updates()
|
||||
|
||||
assert config.model_for_camera("front_door").scene == "default"
|
||||
assert config.model_for_camera("front_door").scene == SceneEnum.all
|
||||
|
||||
def test_unchanged_record_update_keeps_existing_cmds(self):
|
||||
camera_config = _build_camera_config(sub_enabled=False)
|
||||
|
||||
@@ -179,16 +179,12 @@ class TestReviewMaintainerRemoval(unittest.TestCase):
|
||||
maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
|
||||
maintainer.active_review_segments = {"deleted_cam": MagicMock()}
|
||||
maintainer.indefinite_events = {"deleted_cam": {"1234.5-abcdef": 1.0}}
|
||||
maintainer.recent_classification_state_changes = {
|
||||
"deleted_cam": [{"model": "gate", "from": "a", "to": "b", "timestamp": 1.0}]
|
||||
}
|
||||
maintainer.forcibly_end_segment = MagicMock()
|
||||
|
||||
maintainer._handle_camera_removed("deleted_cam")
|
||||
|
||||
maintainer.forcibly_end_segment.assert_called_once_with("deleted_cam")
|
||||
self.assertNotIn("deleted_cam", maintainer.indefinite_events)
|
||||
self.assertNotIn("deleted_cam", maintainer.recent_classification_state_changes)
|
||||
|
||||
|
||||
class TestAutotrackerMoveQueue(unittest.TestCase):
|
||||
|
||||
+7
-125
@@ -1,6 +1,5 @@
|
||||
import json
|
||||
import os
|
||||
import tempfile
|
||||
import unittest
|
||||
from copy import deepcopy
|
||||
from unittest.mock import patch
|
||||
@@ -12,6 +11,7 @@ from ruamel.yaml.constructor import DuplicateKeyError
|
||||
from frigate.config import BirdseyeModeEnum, FrigateConfig, RetainModeEnum
|
||||
from frigate.const import MODEL_CACHE_DIR
|
||||
from frigate.detectors import DetectorTypeEnum
|
||||
from frigate.detectors.detector_config import SceneEnum
|
||||
from frigate.detectors.device import build_detector_config, runner_names
|
||||
from frigate.util.builtin import deep_merge
|
||||
|
||||
@@ -68,7 +68,7 @@ class TestConfig(unittest.TestCase):
|
||||
def test_config_class(self):
|
||||
frigate_config = FrigateConfig(**self.minimal)
|
||||
model = frigate_config.primary_model
|
||||
assert model.scene == "default"
|
||||
assert model.scene == SceneEnum.all
|
||||
assert model.width == 320
|
||||
assert frigate_config.devices_for_model(model)[0].detector == (
|
||||
DetectorTypeEnum.cpu
|
||||
@@ -140,8 +140,8 @@ class TestConfig(unittest.TestCase):
|
||||
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert frigate_config.model_for_camera("back").scene == "outdoor"
|
||||
assert frigate_config.model_for_camera("front").scene == "indoor"
|
||||
assert frigate_config.model_for_camera("back").scene == SceneEnum.outdoor
|
||||
assert frigate_config.model_for_camera("front").scene == SceneEnum.indoor
|
||||
assert frigate_config.model_for_camera("back").width == 320
|
||||
assert frigate_config.model_for_camera("front").width == 300
|
||||
|
||||
@@ -177,7 +177,7 @@ class TestConfig(unittest.TestCase):
|
||||
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert frigate_config.model_for_camera("back").scene == "default"
|
||||
assert frigate_config.model_for_camera("back").scene == SceneEnum.all
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_model_for_camera_resolves_camera_added_after_parse(self, mock_labels):
|
||||
@@ -205,7 +205,7 @@ class TestConfig(unittest.TestCase):
|
||||
new_config = FrigateConfig(**(deep_merge(deepcopy(config), added)))
|
||||
frigate_config.cameras["new_cam"] = new_config.cameras["new_cam"]
|
||||
|
||||
assert frigate_config.model_for_camera("new_cam").scene == "outdoor"
|
||||
assert frigate_config.model_for_camera("new_cam").scene == SceneEnum.outdoor
|
||||
assert frigate_config.model_for_camera("new_cam").width == 416
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
@@ -221,7 +221,7 @@ class TestConfig(unittest.TestCase):
|
||||
frigate_config = FrigateConfig(**(deep_merge(deepcopy(config), self.minimal)))
|
||||
|
||||
# a caller racing a runtime remove may still name the popped camera
|
||||
assert frigate_config.model_for_camera("removed").scene == "default"
|
||||
assert frigate_config.model_for_camera("removed").scene == SceneEnum.all
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_camera_scene_without_a_model_or_a_default(self, mock_labels):
|
||||
@@ -256,124 +256,6 @@ class TestConfig(unittest.TestCase):
|
||||
with self.assertRaises(ValidationError):
|
||||
FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_scene_names_are_not_a_fixed_list(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
config = {
|
||||
"models": [
|
||||
{"devices": ["cpu"]},
|
||||
{"scene": "garage_thermal", "devices": ["openvino:CPU"]},
|
||||
],
|
||||
"cameras": {"back": {"detect": {"scene": "garage_thermal"}}},
|
||||
}
|
||||
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert frigate_config.model_for_camera("back").scene == "garage_thermal"
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_scene_names_must_be_simple_identifiers(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
config = {"models": [{"scene": "front yard", "devices": ["cpu"]}]}
|
||||
|
||||
with self.assertRaises(ValidationError):
|
||||
FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
def _two_scene_config(self, default_path: str, outdoor_path: str) -> dict:
|
||||
return {
|
||||
"models": [
|
||||
{"path": default_path, "devices": ["openvino:CPU"]},
|
||||
{"scene": "outdoor", "path": outdoor_path, "devices": ["openvino:GPU"]},
|
||||
],
|
||||
"cameras": {"back": {"detect": {"scene": "outdoor"}}},
|
||||
}
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_models_with_the_same_path_are_combined(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
config = self._two_scene_config("/etc/hosts", "/etc/hosts")
|
||||
|
||||
with self.assertLogs("frigate.config.config", level="WARNING") as logs:
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert len(frigate_config.models) == 1
|
||||
model = frigate_config.primary_model
|
||||
assert model.devices == ["openvino:CPU", "openvino:GPU"]
|
||||
assert [d.raw for d in frigate_config.devices_for_model(model)] == [
|
||||
"openvino:CPU",
|
||||
"openvino:GPU",
|
||||
]
|
||||
assert frigate_config.model_for_camera("back") is model
|
||||
assert frigate_config.cameras["back"].detect.scene == "default"
|
||||
assert any("same model file" in line for line in logs.output)
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_models_with_the_same_file_contents_are_combined(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
|
||||
with tempfile.TemporaryDirectory() as temp_dir:
|
||||
first = os.path.join(temp_dir, "model.onnx")
|
||||
copy = os.path.join(temp_dir, "renamed.onnx")
|
||||
|
||||
for path in (first, copy):
|
||||
with open(path, "wb") as f:
|
||||
f.write(b"same weights")
|
||||
|
||||
config = self._two_scene_config(first, copy)
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert len(frigate_config.models) == 1
|
||||
assert frigate_config.model_for_camera("back").scene == "default"
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_models_with_different_files_are_kept_apart(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
|
||||
with tempfile.TemporaryDirectory() as temp_dir:
|
||||
first = os.path.join(temp_dir, "model.onnx")
|
||||
other = os.path.join(temp_dir, "thermal.onnx")
|
||||
|
||||
for path, contents in ((first, b"visible"), (other, b"thermal")):
|
||||
with open(path, "wb") as f:
|
||||
f.write(contents)
|
||||
|
||||
config = self._two_scene_config(first, other)
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert len(frigate_config.models) == 2
|
||||
assert frigate_config.model_for_camera("back").scene == "outdoor"
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_combined_models_keep_the_default_model(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
config = {
|
||||
"models": [
|
||||
{"scene": "outdoor", "path": "/etc/hosts", "devices": ["openvino:GPU"]},
|
||||
{"path": "/etc/hosts", "devices": ["openvino:CPU"]},
|
||||
],
|
||||
"cameras": {"back": {"detect": {"scene": "outdoor"}}},
|
||||
}
|
||||
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert [model.scene for model in frigate_config.models] == ["default"]
|
||||
assert frigate_config.primary_model.devices == ["openvino:CPU", "openvino:GPU"]
|
||||
assert frigate_config.model_for_camera("back").scene == "default"
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_models_on_different_detectors_are_kept_apart(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
config = {
|
||||
"models": [
|
||||
{"path": "/etc/hosts", "devices": ["openvino:CPU"]},
|
||||
{"scene": "outdoor", "path": "/etc/hosts", "devices": ["onnx"]},
|
||||
],
|
||||
}
|
||||
|
||||
frigate_config = FrigateConfig(**(deep_merge(config, self.minimal)))
|
||||
|
||||
assert len(frigate_config.models) == 2
|
||||
|
||||
@patch("frigate.detectors.detector_config.load_labels")
|
||||
def test_model_devices_must_share_a_detector(self, mock_labels):
|
||||
mock_labels.return_value = {}
|
||||
|
||||
@@ -20,7 +20,7 @@ class TestMigrateModels(unittest.TestCase):
|
||||
def test_single_cpu_detector(self):
|
||||
migrated = migrate_models({"detectors": {"cpu": {"type": "cpu"}}})
|
||||
|
||||
self.assertEqual(migrated["models"], [{"scene": "default", "devices": ["cpu"]}])
|
||||
self.assertEqual(migrated["models"], [{"scene": "all", "devices": ["cpu"]}])
|
||||
self.assertNotIn("detectors", migrated)
|
||||
|
||||
def test_model_settings_are_carried_over(self):
|
||||
@@ -35,7 +35,7 @@ class TestMigrateModels(unittest.TestCase):
|
||||
migrated["models"],
|
||||
[
|
||||
{
|
||||
"scene": "default",
|
||||
"scene": "all",
|
||||
"path": "plus://abc",
|
||||
"width": 320,
|
||||
"devices": ["edgetpu:pci:0"],
|
||||
@@ -262,7 +262,7 @@ class TestMigrateConfigFile(unittest.TestCase):
|
||||
"mqtt:\n"
|
||||
" enabled: false\n"
|
||||
"models:\n"
|
||||
" - scene: default\n"
|
||||
" - scene: all\n"
|
||||
" devices:\n"
|
||||
" - openvino:GPU\n"
|
||||
"cameras: {}\n"
|
||||
@@ -270,7 +270,7 @@ class TestMigrateConfigFile(unittest.TestCase):
|
||||
)
|
||||
|
||||
self.assertEqual(
|
||||
migrated["models"], [{"scene": "default", "devices": ["openvino:GPU"]}]
|
||||
migrated["models"], [{"scene": "all", "devices": ["openvino:GPU"]}]
|
||||
)
|
||||
self.assertFalse(
|
||||
os.path.exists(os.path.join(self.temp_dir.name, "backup_config.yaml"))
|
||||
@@ -298,7 +298,7 @@ class TestMigrateConfigFile(unittest.TestCase):
|
||||
"mqtt:\n"
|
||||
" enabled: false\n"
|
||||
"models:\n"
|
||||
" - scene: default\n"
|
||||
" - scene: all\n"
|
||||
" devices:\n"
|
||||
" - hailo8l:PCIe\n"
|
||||
"cameras: {}\n"
|
||||
|
||||
@@ -26,7 +26,6 @@ class TestSwapRuntimeConfig(unittest.TestCase):
|
||||
app.genai_manager.update_config.assert_called_once_with(config)
|
||||
app.profile_manager.update_config.assert_called_once_with(config)
|
||||
self.assertIs(app.stats_emitter.config, config)
|
||||
app.stats_emitter.hardware_stats.set_config.assert_called_once_with(config)
|
||||
self.assertIs(app.dispatcher.config, config)
|
||||
for comm in app.dispatcher.comms:
|
||||
self.assertIs(comm.config, config)
|
||||
|
||||
@@ -1,39 +0,0 @@
|
||||
"""Tests for per-detector stats."""
|
||||
|
||||
import unittest
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
from frigate.stats.util import get_detector_stats
|
||||
|
||||
|
||||
def _detector(detector_type: str) -> MagicMock:
|
||||
detector = MagicMock()
|
||||
detector.detector_config.type = detector_type
|
||||
detector.avg_inference_speed.value = 0.01
|
||||
detector.detection_start.value = 0.0
|
||||
detector.detect_process.pid = 1
|
||||
return detector
|
||||
|
||||
|
||||
class TestDetectorTemperatures(unittest.TestCase):
|
||||
def test_repeated_device_shares_its_unit_temperature(self):
|
||||
stats_tracking = {
|
||||
"detectors": {
|
||||
"hailo:PCIe": _detector("hailo8l"),
|
||||
"hailo:PCIe#2": _detector("hailo8l"),
|
||||
"hailo:PCIe:1": _detector("hailo8l"),
|
||||
}
|
||||
}
|
||||
|
||||
with patch(
|
||||
"frigate.stats.util.get_hardware_temperatures", return_value=[50.0, 60.0]
|
||||
):
|
||||
stats = get_detector_stats(stats_tracking)
|
||||
|
||||
self.assertEqual(stats["hailo:PCIe"]["temperature"], 50.0)
|
||||
self.assertEqual(stats["hailo:PCIe#2"]["temperature"], 50.0)
|
||||
self.assertEqual(stats["hailo:PCIe:1"]["temperature"], 60.0)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -543,56 +543,6 @@ class TestPinnedStream(unittest.TestCase):
|
||||
self.assertFalse(any("/vod/front/main/" in token for token in cmd))
|
||||
|
||||
|
||||
class TestExportTimelineAlignment(unittest.TestCase):
|
||||
def test_unstaged_auto_reads_the_stream_it_serves(self) -> None:
|
||||
# a sub-only range whose main rows are glitches the manifest drops
|
||||
exporter = _make_exporter([_span("/s1.mp4", 1_000, 1_040, False)], {"h264"})
|
||||
streams: list[str] = []
|
||||
|
||||
def rows(stream: str) -> list:
|
||||
streams.append(stream)
|
||||
return [_FakeRow(f"/{stream}.mp4")]
|
||||
|
||||
exporter._get_recordings_for_range = rows # type: ignore[method-assign]
|
||||
exporter.get_record_export_command("/exports/out.mp4")
|
||||
|
||||
self.assertEqual(streams, ["sub"])
|
||||
|
||||
def test_staged_chapters_carry_keyframe_lead_in(self) -> None:
|
||||
exporter = _make_exporter(
|
||||
[
|
||||
_span("/m1.mp4", 1_000, 1_020, True),
|
||||
_span("/s1.mp4", 1_020, 1_040, False),
|
||||
],
|
||||
{"h264"},
|
||||
)
|
||||
exporter.config.ui.timezone = None
|
||||
|
||||
# each run's vod clip snaps 1.5s back to a keyframe
|
||||
def timeline(_intervals: list, stream: str) -> list[dict]:
|
||||
start, end = (1_000, 1_020) if stream == "main" else (1_020, 1_040)
|
||||
return [
|
||||
{
|
||||
"start_time": start,
|
||||
"end_time": end,
|
||||
"duration": (end - start + 1.5) * 1000,
|
||||
}
|
||||
]
|
||||
|
||||
with (
|
||||
patch("frigate.record.export.resolve_coverage", return_value=[]),
|
||||
patch("frigate.record.export.realized_timeline", side_effect=timeline),
|
||||
):
|
||||
windows = exporter._staged_chapter_windows()
|
||||
|
||||
path = exporter._build_recording_segment_chapter_metadata_file(windows)
|
||||
self.addCleanup(os.remove, path)
|
||||
content = Path(path).read_text()
|
||||
|
||||
self.assertIn("START=0\nEND=21500", content)
|
||||
self.assertIn("START=21500\nEND=43000", content)
|
||||
|
||||
|
||||
class TestStagedFileCleanup(unittest.TestCase):
|
||||
"""A staged path must be tracked before ffmpeg can write to it."""
|
||||
|
||||
|
||||
@@ -7,7 +7,6 @@ from frigate.genai.prompts import (
|
||||
REVIEW_DESCRIPTION_FIELD_GUIDELINES,
|
||||
REVIEW_RESPONSE_STYLES,
|
||||
build_review_description_prompt,
|
||||
build_review_summary_prompt,
|
||||
get_review_field_guidelines,
|
||||
)
|
||||
|
||||
@@ -84,49 +83,5 @@ class TestReviewResponseStyle(unittest.TestCase):
|
||||
)
|
||||
|
||||
|
||||
class TestClassificationStateChanges(unittest.TestCase):
|
||||
def _build_prompt(self, **extra) -> str:
|
||||
review_data = {
|
||||
"camera": "Front Door",
|
||||
"start": "Monday, 09:30 AM",
|
||||
"duration": 25,
|
||||
"zones": [],
|
||||
"unified_objects": ["person"],
|
||||
**extra,
|
||||
}
|
||||
return build_review_description_prompt(
|
||||
review_data, [b"fake-image"], [], None, "activity context"
|
||||
)
|
||||
|
||||
def test_no_changes_leaves_prompt_unchanged(self):
|
||||
self.assertEqual(
|
||||
self._build_prompt(classification_state_changes=[]),
|
||||
self._build_prompt(),
|
||||
)
|
||||
self.assertNotIn("## State Changes", self._build_prompt())
|
||||
|
||||
def test_changes_are_listed_before_objects(self):
|
||||
change = "front gate changed from closed to open, 12s into the activity"
|
||||
prompt = self._build_prompt(classification_state_changes=[change])
|
||||
self.assertIn(f"\n- {change}\n\n## Objects in Scene", prompt)
|
||||
self.assertLess(
|
||||
prompt.index("## Sequence Details"), prompt.index("## State Changes")
|
||||
)
|
||||
|
||||
def test_summary_describes_state_changes_only_when_present(self):
|
||||
event = {"title": "Person at door", "camera": "Front Door", "context": []}
|
||||
without = build_review_summary_prompt(0, 3600, [event], None)
|
||||
self.assertNotIn('"state_changes"', without)
|
||||
|
||||
context_event = {
|
||||
**event,
|
||||
"context": [
|
||||
{"camera": "Driveway", "state_changes": ["gate changed from a to b"]}
|
||||
],
|
||||
}
|
||||
with_changes = build_review_summary_prompt(0, 3600, [context_event], None)
|
||||
self.assertIn('- "state_changes"', with_changes)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
||||
@@ -19,8 +19,6 @@ import unittest
|
||||
from types import SimpleNamespace
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import requests
|
||||
|
||||
from frigate.config import GenAIConfig, GenAIProviderEnum
|
||||
from frigate.genai import PROVIDERS, load_providers
|
||||
|
||||
@@ -568,6 +566,7 @@ class TestLlamaCppProvider(unittest.TestCase):
|
||||
"supports_audio": False,
|
||||
"supports_tools": False,
|
||||
"supports_reasoning": False,
|
||||
"media_marker": "<__media__>",
|
||||
}
|
||||
cls = PROVIDERS[GenAIProviderEnum.llamacpp]
|
||||
with patch.object(cls, "_get_model_info", return_value=info):
|
||||
@@ -590,62 +589,6 @@ class TestLlamaCppProvider(unittest.TestCase):
|
||||
with patch.object(client, "_fetch_models_data", return_value=models_data):
|
||||
self.assertEqual(client.list_models(), ["g4", "gemma", "qwen3-asr"])
|
||||
|
||||
@staticmethod
|
||||
def _embeddings_response(vectors):
|
||||
response = MagicMock()
|
||||
response.status_code = 200
|
||||
response.json.return_value = {
|
||||
"object": "list",
|
||||
"data": [
|
||||
{"object": "embedding", "index": i, "embedding": v}
|
||||
for i, v in enumerate(vectors)
|
||||
],
|
||||
}
|
||||
return response
|
||||
|
||||
def test_embed_posts_content_arrays_to_v1_embeddings(self):
|
||||
client = self._client()
|
||||
response = self._embeddings_response([[0.1] * 768, [0.2] * 768])
|
||||
|
||||
with patch.object(client, "_post", return_value=response) as post:
|
||||
result = client.embed(texts=["a person"], images=[b"not an image"])
|
||||
|
||||
url = post.call_args.args[0]
|
||||
payload = post.call_args.kwargs["json"]
|
||||
self.assertEqual(url, "http://localhost:9999/v1/embeddings")
|
||||
self.assertEqual(payload["model"], "m")
|
||||
self.assertEqual(payload["encoding_format"], "float")
|
||||
self.assertEqual(
|
||||
payload["input"][0], {"content": [{"type": "text", "text": "a person"}]}
|
||||
)
|
||||
image_parts = payload["input"][1]["content"]
|
||||
self.assertEqual(image_parts[0]["type"], "image_url")
|
||||
self.assertEqual(
|
||||
image_parts[0]["image_url"]["url"],
|
||||
"data:image/jpeg;base64," + base64.b64encode(b"not an image").decode(),
|
||||
)
|
||||
self.assertEqual(image_parts[1], {"type": "text", "text": "\n"})
|
||||
self.assertEqual(len(result), 2)
|
||||
self.assertAlmostEqual(float(result[1][0]), 0.2, places=5)
|
||||
|
||||
def test_embed_normalizes_dimension(self):
|
||||
client = self._client()
|
||||
response = self._embeddings_response([[1.0] * 1024, [1.0] * 512])
|
||||
|
||||
with patch.object(client, "_post", return_value=response):
|
||||
result = client.embed(texts=["long", "short"])
|
||||
|
||||
self.assertEqual([r.shape for r in result], [(768,), (768,)])
|
||||
self.assertEqual(float(result[1][-1]), 0.0)
|
||||
|
||||
def test_embed_request_error_returns_empty(self):
|
||||
client = self._client()
|
||||
response = MagicMock()
|
||||
response.raise_for_status.side_effect = requests.exceptions.HTTPError("400")
|
||||
|
||||
with patch.object(client, "_post", return_value=response):
|
||||
self.assertEqual(client.embed(texts=["a"]), [])
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# transcribe role
|
||||
@@ -819,6 +762,7 @@ class TestLlamaCppTranscribe(unittest.TestCase):
|
||||
"supports_audio": supports_audio,
|
||||
"supports_tools": False,
|
||||
"supports_reasoning": False,
|
||||
"media_marker": "<__media__>",
|
||||
}
|
||||
cls = PROVIDERS[GenAIProviderEnum.llamacpp]
|
||||
with patch.object(cls, "_get_model_info", return_value=info):
|
||||
|
||||
@@ -288,17 +288,6 @@ class TestUpdateConfig(HardwareStatsTestCase):
|
||||
|
||||
self.assertEqual(set(stats._monitored), {"rockchip"})
|
||||
|
||||
def test_follows_a_runtime_config_swap(self):
|
||||
stats = self.make_stats(self.make_config())
|
||||
self.assertEqual(set(stats._monitored), set())
|
||||
|
||||
swapped = self.make_config("preset-rk-h264")
|
||||
stats.set_config(swapped)
|
||||
|
||||
self.assertEqual(set(stats._monitored), {"rockchip"})
|
||||
self.assertIs(self.subscriber.return_value.config, swapped)
|
||||
self.assertIs(self.subscriber.return_value.camera_configs, swapped.cameras)
|
||||
|
||||
|
||||
class TestUpdateStats(HardwareStatsTestCase):
|
||||
def run_stats(self, stats: HardwareStats) -> dict:
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import datetime
|
||||
import sys
|
||||
import unittest
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
# Mock complex imports before importing maintainer, saving originals so we can
|
||||
# restore them after import and avoid polluting sys.modules for other tests.
|
||||
@@ -48,11 +48,8 @@ class TestMaintainer(unittest.IsolatedAsyncioTestCase):
|
||||
"frigate.record.maintainer.psutil.process_iter", return_value=[]
|
||||
):
|
||||
with patch("frigate.record.maintainer.logger.warning") as warn:
|
||||
# Mock validate_and_move_segment to avoid further logic.
|
||||
# The requestor is real when another test imported the
|
||||
# maintainer first, and it would block on a reply.
|
||||
maintainer.validate_and_move_segment = AsyncMock()
|
||||
maintainer.requestor = MagicMock()
|
||||
# Mock validate_and_move_segment to avoid further logic
|
||||
maintainer.validate_and_move_segment = MagicMock()
|
||||
|
||||
try:
|
||||
await maintainer.move_files()
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
"""Tests for sub stream cache segment handling in the recording maintainer."""
|
||||
|
||||
import asyncio
|
||||
import datetime
|
||||
import os
|
||||
import tempfile
|
||||
@@ -533,59 +532,6 @@ class TestSegmentStartChaining(unittest.IsolatedAsyncioTestCase):
|
||||
self.assertAlmostEqual(calls[1].args[2].timestamp(), self.T0 + 10.4, places=3)
|
||||
self.assertAlmostEqual(calls[1].args[3].timestamp(), self.T0 + 20.8, places=3)
|
||||
|
||||
async def test_out_of_order_probes_chain_in_segment_order(self):
|
||||
maintainer = _build_chaining_maintainer(self.T0)
|
||||
|
||||
async def probe(_ffmpeg, cache_path, get_duration=False):
|
||||
# the earlier segment's probe finishes last
|
||||
if "chain0" in cache_path:
|
||||
await asyncio.sleep(0.05)
|
||||
|
||||
return {"has_valid_video": True, "duration": 10.4}
|
||||
|
||||
recordings = [
|
||||
{
|
||||
"start_time": datetime.datetime.fromtimestamp(
|
||||
self.T0 + offset, tz=datetime.UTC
|
||||
),
|
||||
"cache_path": f"/tmp/cache/test_cam@chain{offset}.mp4",
|
||||
"stream_type": "main",
|
||||
}
|
||||
for offset in (0, 10)
|
||||
]
|
||||
first_resolved = asyncio.Event()
|
||||
|
||||
with (
|
||||
patch("frigate.record.maintainer.get_video_properties", probe),
|
||||
patch(
|
||||
"frigate.record.maintainer.get_keyframe_offsets",
|
||||
AsyncMock(return_value=[0]),
|
||||
),
|
||||
patch(
|
||||
"frigate.record.maintainer.os.path.getmtime",
|
||||
MagicMock(side_effect=OSError("missing")),
|
||||
),
|
||||
):
|
||||
await asyncio.gather(
|
||||
maintainer._validate_in_order(
|
||||
"test_cam", [], recordings[0], None, first_resolved
|
||||
),
|
||||
maintainer._validate_in_order(
|
||||
"test_cam", [], recordings[1], first_resolved, asyncio.Event()
|
||||
),
|
||||
)
|
||||
|
||||
starts = sorted(
|
||||
call.args[2].timestamp() for call in maintainer.move_segment.await_args_list
|
||||
)
|
||||
self.assertEqual(starts[0], self.T0)
|
||||
self.assertAlmostEqual(starts[1], self.T0 + 10.4, places=3)
|
||||
self.assertAlmostEqual(
|
||||
maintainer.last_segment_end[("test_cam", "main")],
|
||||
self.T0 + 20.8,
|
||||
places=3,
|
||||
)
|
||||
|
||||
async def test_genuine_gap_is_not_snapped(self):
|
||||
maintainer = _build_chaining_maintainer(self.T0)
|
||||
|
||||
|
||||
@@ -1,13 +1,10 @@
|
||||
"""Tests for tracker-derived review frame annotations."""
|
||||
|
||||
import unittest
|
||||
from unittest.mock import patch
|
||||
|
||||
from frigate.data_processing.post.review_annotations import (
|
||||
annotations_by_frame,
|
||||
build_frame_captions,
|
||||
build_timeline,
|
||||
describe_classification_change,
|
||||
describe_heading,
|
||||
describe_position,
|
||||
event_name,
|
||||
@@ -315,75 +312,5 @@ class TestFrameBucketing(unittest.TestCase):
|
||||
self.assertEqual(annotations_by_frame([(1.0, "x")], []), {})
|
||||
|
||||
|
||||
class TestClassificationChangeCaptions(unittest.TestCase):
|
||||
def setUp(self):
|
||||
person = track(
|
||||
"1789481994.684479-lpyc2z",
|
||||
"person",
|
||||
0.0,
|
||||
straight_path((0.9, 0.6), (0.4, 0.3), 10, 0.0),
|
||||
)
|
||||
patcher = patch(
|
||||
"frigate.data_processing.post.review_annotations.get_tracked_events",
|
||||
return_value=[person],
|
||||
)
|
||||
patcher.start()
|
||||
self.addCleanup(patcher.stop)
|
||||
patcher = patch(
|
||||
"frigate.data_processing.post.review_annotations.get_state_changes",
|
||||
return_value=[],
|
||||
)
|
||||
patcher.start()
|
||||
self.addCleanup(patcher.stop)
|
||||
|
||||
def test_change_is_phrased_without_underscores(self):
|
||||
self.assertEqual(
|
||||
describe_classification_change(
|
||||
{"model": "trash_day", "from": "no_bins", "to": "bins_at_curb"}
|
||||
),
|
||||
"trash day changed from no bins to bins at curb",
|
||||
)
|
||||
|
||||
def test_change_is_noted_before_the_frame_it_precedes(self):
|
||||
change = {"model": "front_gate", "from": "closed", "to": "open"}
|
||||
captions = build_frame_captions(
|
||||
["1789481994.684479-lpyc2z"],
|
||||
[0.0, 10.0, 20.0],
|
||||
[{**change, "timestamp": 12.0}],
|
||||
)
|
||||
self.assertEqual(
|
||||
captions[2],
|
||||
"Frame 3 of 3 (+20.0s):\n[state] front gate changed from closed to open",
|
||||
)
|
||||
self.assertTrue(captions[0].splitlines()[1].startswith("[tracker] "))
|
||||
|
||||
def test_change_is_noted_without_tracked_objects(self):
|
||||
with patch(
|
||||
"frigate.data_processing.post.review_annotations.get_tracked_events",
|
||||
return_value=[],
|
||||
):
|
||||
captions = build_frame_captions(
|
||||
[],
|
||||
[0.0, 10.0],
|
||||
[{"model": "gate", "from": "a", "to": "b", "timestamp": 5.0}],
|
||||
)
|
||||
|
||||
self.assertEqual(
|
||||
captions,
|
||||
[
|
||||
"Frame 1 of 2 (+0.0s):",
|
||||
"Frame 2 of 2 (+10.0s):\n[state] gate changed from a to b",
|
||||
],
|
||||
)
|
||||
|
||||
def test_change_after_the_last_frame_is_dropped(self):
|
||||
captions = build_frame_captions(
|
||||
["1789481994.684479-lpyc2z"],
|
||||
[0.0, 10.0, 20.0],
|
||||
[{"model": "gate", "from": "a", "to": "b", "timestamp": 25.0}],
|
||||
)
|
||||
self.assertFalse(any("[state]" in caption for caption in captions))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
||||
@@ -1,258 +0,0 @@
|
||||
"""Tests for attaching state classification changes to review items."""
|
||||
|
||||
import unittest
|
||||
from unittest.mock import MagicMock, patch
|
||||
|
||||
from frigate.comms.embeddings_updater import EmbeddingsRequestEnum
|
||||
from frigate.config import FrigateConfig
|
||||
from frigate.data_processing.post.review_descriptions import (
|
||||
ReviewDescriptionProcessor,
|
||||
format_classification_state_changes,
|
||||
)
|
||||
from frigate.data_processing.real_time.custom_classification import (
|
||||
CustomStateClassificationProcessor,
|
||||
)
|
||||
from frigate.models import ReviewSegment
|
||||
from frigate.review.maintainer import (
|
||||
CLASSIFICATION_STATE_PRE_ROLL,
|
||||
PendingReviewSegment,
|
||||
ReviewSegmentMaintainer,
|
||||
)
|
||||
from frigate.review.types import SeverityEnum
|
||||
|
||||
CONFIG = """
|
||||
mqtt:
|
||||
enabled: False
|
||||
cameras:
|
||||
front_door:
|
||||
ffmpeg:
|
||||
inputs:
|
||||
- path: rtsp://10.0.0.1:554/video
|
||||
roles:
|
||||
- detect
|
||||
detect:
|
||||
width: 1920
|
||||
height: 1080
|
||||
fps: 5
|
||||
"""
|
||||
|
||||
|
||||
def gate_change(timestamp: float, before: str = "closed", after: str = "open"):
|
||||
return {"model": "front_gate", "from": before, "to": after, "timestamp": timestamp}
|
||||
|
||||
|
||||
class TestVerifyStateChange(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.processor = CustomStateClassificationProcessor.__new__(
|
||||
CustomStateClassificationProcessor
|
||||
)
|
||||
self.processor.state_history = {}
|
||||
|
||||
def verify(self, state: str, timestamp: float):
|
||||
return self.processor.verify_state_change("front_door", state, timestamp)
|
||||
|
||||
def test_first_verified_state_has_no_previous_state(self):
|
||||
self.assertIsNone(self.verify("closed", 1.0))
|
||||
self.assertIsNone(self.verify("closed", 2.0))
|
||||
self.assertEqual(self.verify("closed", 3.0), (None, 1.0))
|
||||
|
||||
def test_change_reports_previous_state_and_first_sighting(self):
|
||||
for timestamp in (1.0, 2.0, 3.0):
|
||||
self.verify("closed", timestamp)
|
||||
|
||||
self.assertIsNone(self.verify("open", 10.0))
|
||||
self.assertIsNone(self.verify("open", 11.0))
|
||||
self.assertEqual(self.verify("open", 12.0), ("closed", 10.0))
|
||||
|
||||
def test_interrupted_verification_restarts_the_first_sighting(self):
|
||||
for timestamp in (1.0, 2.0, 3.0):
|
||||
self.verify("closed", timestamp)
|
||||
|
||||
self.verify("open", 10.0)
|
||||
self.verify("closed", 11.0)
|
||||
self.verify("open", 20.0)
|
||||
self.verify("open", 21.0)
|
||||
self.assertEqual(self.verify("open", 22.0), ("closed", 20.0))
|
||||
|
||||
def test_reload_forgets_states_the_model_no_longer_has(self):
|
||||
for timestamp in (1.0, 2.0, 3.0):
|
||||
self.verify("closed", timestamp)
|
||||
|
||||
self.processor.state_history["back_door"] = {"current_state": "open"}
|
||||
self.processor.labelmap = {0: "open", 1: "shut"}
|
||||
self.processor._forget_unknown_states()
|
||||
|
||||
self.assertEqual(list(self.processor.state_history), ["back_door"])
|
||||
self.assertIsNone(self.verify("shut", 10.0))
|
||||
self.assertIsNone(self.verify("shut", 11.0))
|
||||
self.assertEqual(self.verify("shut", 12.0), (None, 10.0))
|
||||
|
||||
|
||||
class TestReviewSegmentAttachment(unittest.TestCase):
|
||||
def setUp(self):
|
||||
self.maintainer = ReviewSegmentMaintainer.__new__(ReviewSegmentMaintainer)
|
||||
self.maintainer.config = FrigateConfig.parse_yaml(CONFIG)
|
||||
self.maintainer.active_review_segments = {}
|
||||
self.maintainer.recent_classification_state_changes = {}
|
||||
self.maintainer._publish_segment_update = MagicMock()
|
||||
|
||||
def segment(self, start_time: float) -> PendingReviewSegment:
|
||||
return PendingReviewSegment(
|
||||
"front_door",
|
||||
start_time,
|
||||
SeverityEnum.alert,
|
||||
{"1.0-abcdef": "person"},
|
||||
{},
|
||||
[],
|
||||
set(),
|
||||
)
|
||||
|
||||
def test_change_during_segment_is_attached_and_published(self):
|
||||
segment = self.segment(100.0)
|
||||
self.maintainer.active_review_segments["front_door"] = segment
|
||||
|
||||
self.maintainer.handle_classification_state_change(
|
||||
"front_door", gate_change(110.0)
|
||||
)
|
||||
|
||||
self.assertEqual(segment.classification_state_changes, [gate_change(110.0)])
|
||||
self.maintainer._publish_segment_update.assert_called_once()
|
||||
prev_data = self.maintainer._publish_segment_update.call_args.args[4]
|
||||
self.assertEqual(prev_data["data"]["classification_state_changes"], [])
|
||||
self.assertEqual(
|
||||
segment.get_data(False)["data"]["classification_state_changes"],
|
||||
[gate_change(110.0)],
|
||||
)
|
||||
|
||||
def test_change_never_starts_a_segment(self):
|
||||
self.maintainer.handle_classification_state_change(
|
||||
"front_door", gate_change(110.0)
|
||||
)
|
||||
|
||||
self.assertIsNone(self.maintainer.active_review_segments.get("front_door"))
|
||||
self.maintainer._publish_segment_update.assert_not_called()
|
||||
|
||||
def test_change_just_before_a_segment_is_attached_when_it_starts(self):
|
||||
self.maintainer.handle_classification_state_change(
|
||||
"front_door", gate_change(98.0)
|
||||
)
|
||||
segment = self.segment(100.0)
|
||||
|
||||
self.maintainer._activate_segment(segment)
|
||||
|
||||
self.assertIs(self.maintainer.active_review_segments["front_door"], segment)
|
||||
self.assertEqual(segment.classification_state_changes, [gate_change(98.0)])
|
||||
self.assertNotIn(
|
||||
"front_door", self.maintainer.recent_classification_state_changes
|
||||
)
|
||||
|
||||
def test_change_long_before_a_segment_is_not_attached(self):
|
||||
self.maintainer.handle_classification_state_change(
|
||||
"front_door", gate_change(100.0 - CLASSIFICATION_STATE_PRE_ROLL - 1)
|
||||
)
|
||||
segment = self.segment(100.0)
|
||||
|
||||
self.maintainer._activate_segment(segment)
|
||||
|
||||
self.assertEqual(segment.classification_state_changes, [])
|
||||
|
||||
def test_held_changes_are_pruned(self):
|
||||
self.maintainer.handle_classification_state_change(
|
||||
"front_door", gate_change(10.0)
|
||||
)
|
||||
self.maintainer.handle_classification_state_change(
|
||||
"front_door", gate_change(50.0, "open", "closed")
|
||||
)
|
||||
|
||||
self.assertEqual(
|
||||
self.maintainer.recent_classification_state_changes["front_door"],
|
||||
[gate_change(50.0, "open", "closed")],
|
||||
)
|
||||
|
||||
|
||||
class TestChangeTiming(unittest.TestCase):
|
||||
def test_changes_are_placed_relative_to_the_activity(self):
|
||||
lines = format_classification_state_changes(
|
||||
[
|
||||
gate_change(98.0),
|
||||
gate_change(112.4, "open", "closed"),
|
||||
gate_change(140.0),
|
||||
],
|
||||
start_time=100.0,
|
||||
end_time=130.0,
|
||||
)
|
||||
|
||||
self.assertEqual(
|
||||
lines,
|
||||
[
|
||||
"front gate changed from closed to open, "
|
||||
"just before the activity started",
|
||||
"front gate changed from open to closed, 12s into the activity",
|
||||
"front gate changed from closed to open, after the activity ended",
|
||||
],
|
||||
)
|
||||
|
||||
|
||||
class TestSummaryContext(unittest.TestCase):
|
||||
def row(self, camera, start, end, threat, changes=()):
|
||||
return {
|
||||
"camera": camera,
|
||||
"start_time": start,
|
||||
"end_time": end,
|
||||
"data": {
|
||||
"metadata": {"title": camera, "potential_threat_level": threat},
|
||||
"classification_state_changes": list(changes),
|
||||
},
|
||||
}
|
||||
|
||||
def summarize(self, rows):
|
||||
processor = ReviewDescriptionProcessor.__new__(ReviewDescriptionProcessor)
|
||||
processor.config = FrigateConfig.parse_yaml(CONFIG)
|
||||
processor.genai_manager = MagicMock()
|
||||
client = processor.genai_manager.description_client
|
||||
|
||||
with patch.object(ReviewSegment, "select") as select:
|
||||
query = select.return_value.where.return_value.order_by.return_value
|
||||
query.dicts.return_value.iterator.return_value = iter(rows)
|
||||
processor.handle_request(
|
||||
EmbeddingsRequestEnum.summarize_review.value,
|
||||
{"start_ts": 0, "end_ts": 100},
|
||||
)
|
||||
|
||||
return client.generate_review_summary.call_args.args[2]
|
||||
|
||||
def test_context_state_changes_stay_with_their_review(self):
|
||||
events = self.summarize(
|
||||
[
|
||||
self.row("front_door", 10, 60, 1),
|
||||
self.row("driveway", 15, 25, 0, [gate_change(20.0)]),
|
||||
self.row("driveway", 30, 40, 0, [gate_change(35.0, "open", "closed")]),
|
||||
]
|
||||
)
|
||||
|
||||
self.assertEqual(
|
||||
[
|
||||
(item["start_time"], item["end_time"], item["state_changes"])
|
||||
for item in events[0]["context"]
|
||||
],
|
||||
[
|
||||
(15, 25, ["front gate changed from closed to open"]),
|
||||
(30, 40, ["front gate changed from open to closed"]),
|
||||
],
|
||||
)
|
||||
|
||||
def test_later_context_review_without_changes_is_deduplicated(self):
|
||||
events = self.summarize(
|
||||
[
|
||||
self.row("front_door", 10, 60, 1),
|
||||
self.row("driveway", 15, 25, 0, [gate_change(20.0)]),
|
||||
self.row("driveway", 30, 40, 0),
|
||||
]
|
||||
)
|
||||
|
||||
self.assertEqual(len(events[0]["context"]), 1)
|
||||
self.assertEqual(events[0]["context"][0]["start_time"], 15)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@@ -978,7 +978,7 @@ def migrate_models(config: dict[str, dict[str, Any]]) -> dict[str, dict[str, Any
|
||||
", ".join(sorted(detector_types)),
|
||||
)
|
||||
|
||||
entry: dict[str, Any] = {"scene": "default", **model}
|
||||
entry: dict[str, Any] = {"scene": "all", **model}
|
||||
|
||||
if model_path:
|
||||
entry["path"] = model_path
|
||||
|
||||
@@ -14,10 +14,6 @@ from frigate.util.file import FileLock
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# (connect, read) seconds. The read timeout bounds each socket read rather than
|
||||
# the whole download, so large models still finish.
|
||||
DOWNLOAD_TIMEOUT = (15, 60)
|
||||
|
||||
# target path -> first line of the last download error for it; every existing
|
||||
# download function swallows its exceptions, so this is how the downloader
|
||||
# thread learns why a file is still missing
|
||||
@@ -128,9 +124,7 @@ class ModelDownloader:
|
||||
logger.info(f"Downloading model file from: {url}")
|
||||
|
||||
try:
|
||||
with requests.get(
|
||||
url, stream=True, allow_redirects=True, timeout=DOWNLOAD_TIMEOUT
|
||||
) as r:
|
||||
with requests.get(url, stream=True, allow_redirects=True) as r:
|
||||
r.raise_for_status()
|
||||
with open(temporary_filename, "wb") as f:
|
||||
for chunk in r.iter_content(chunk_size=8192):
|
||||
|
||||
@@ -213,19 +213,17 @@ def stream_has_audio(intervals: list[CoverageInterval], main: bool) -> bool:
|
||||
)
|
||||
|
||||
|
||||
def null_audio_glitches(intervals: list[CoverageInterval]) -> list[CoverageInterval]:
|
||||
def null_audio_glitches(
|
||||
intervals: list[CoverageInterval], main_audio: bool, sub_audio: bool
|
||||
) -> list[CoverageInterval]:
|
||||
"""Treat video-only glitch rows on audio-bearing streams as no recording.
|
||||
|
||||
nginx-vod requires every clip in a sequence to carry the same track
|
||||
count, so a truncated video-only segment (a backend restart can flush
|
||||
a sub-second file before any audio packet landed) poisons every
|
||||
manifest that includes it. Nulling the row turns the glitch into a
|
||||
hole the span builder skips like any recording gap. Every consumer of
|
||||
a window's coverage (the vod manifest, its realized timelines, and
|
||||
exports) goes through here, so they all agree on which rows exist.
|
||||
hole the span builder skips like any recording gap.
|
||||
"""
|
||||
main_audio = stream_has_audio(intervals, main=True)
|
||||
sub_audio = stream_has_audio(intervals, main=False)
|
||||
result: list[CoverageInterval] = []
|
||||
for interval in intervals:
|
||||
main = interval.main
|
||||
@@ -451,7 +449,9 @@ def realized_timelines(
|
||||
assembles each variant's realized spans. Keyframe snapping reads the
|
||||
per-row index stored at record time, so no file is touched.
|
||||
"""
|
||||
nulled = null_audio_glitches(intervals)
|
||||
main_audio = stream_has_audio(intervals, main=True)
|
||||
sub_audio = stream_has_audio(intervals, main=False)
|
||||
nulled = null_audio_glitches(intervals, main_audio, sub_audio)
|
||||
|
||||
return {
|
||||
"auto": realized_timeline(nulled, None),
|
||||
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -1,204 +0,0 @@
|
||||
/**
|
||||
* Helpers for the live dashboard's draggable grid layout: reading and seeding
|
||||
* the persisted layout, and measuring rendered tiles.
|
||||
*
|
||||
* DraggableGridLayout persists through useUserPersistence, which namespaces
|
||||
* keys by username, and every write is an async idb put. A test that seeds the
|
||||
* bare key, or seeds before the app's own first write has landed, silently
|
||||
* asserts against a key the app never reads. persistedLayoutKey() closes both
|
||||
* holes, so prefer it over building the key by hand.
|
||||
*
|
||||
* Geometry has its own trap: the grid first lays out against window.innerWidth,
|
||||
* then reflows narrower once useResizeObserver reports the real container.
|
||||
* Tiles measured in separate round-trips can straddle that reflow and disagree
|
||||
* on scale, so cameraBoxes() takes every measurement in one evaluate.
|
||||
*
|
||||
* Used by live-grid-aspect-modes.spec.ts and masonry-live-grid.spec.ts.
|
||||
*/
|
||||
|
||||
import { expect, type Page } from "@playwright/test";
|
||||
|
||||
export type LayoutItem = {
|
||||
i: string;
|
||||
x: number;
|
||||
y: number;
|
||||
w: number;
|
||||
h: number;
|
||||
};
|
||||
|
||||
export type PersistedLayout = {
|
||||
version: number;
|
||||
naturalAspect: boolean;
|
||||
layout: LayoutItem[];
|
||||
};
|
||||
|
||||
function layoutKeySuffix(group: string): string {
|
||||
return `${group}-draggable-layout`;
|
||||
}
|
||||
|
||||
/**
|
||||
* The key the app has actually written an envelope to, or undefined while its
|
||||
* first write is still in flight.
|
||||
*/
|
||||
function findWrittenKey(
|
||||
page: Page,
|
||||
group: string,
|
||||
): Promise<string | undefined> {
|
||||
return page.evaluate(
|
||||
(suffix) =>
|
||||
new Promise<string | undefined>((resolve) => {
|
||||
const open = indexedDB.open("keyval-store");
|
||||
open.onsuccess = () => {
|
||||
const store = open.result
|
||||
.transaction("keyval", "readonly")
|
||||
.objectStore("keyval");
|
||||
// getAllKeys and getAll both return in key order, so the indexes align
|
||||
const keys = store.getAllKeys();
|
||||
const values = store.getAll();
|
||||
keys.transaction.oncomplete = () => {
|
||||
open.result.close();
|
||||
const names = keys.result as string[];
|
||||
const stored = values.result as { version?: number }[];
|
||||
const match = names.findIndex(
|
||||
(name, index) =>
|
||||
(name === suffix || name.startsWith(`${suffix}:`)) &&
|
||||
typeof stored[index]?.version === "number",
|
||||
);
|
||||
resolve(match === -1 ? undefined : names[match]);
|
||||
};
|
||||
};
|
||||
open.onerror = () => resolve(undefined);
|
||||
}),
|
||||
layoutKeySuffix(group),
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Wait for the grid to persist its own layout, then return the key it used.
|
||||
* Waiting for that write is what makes a later seed meaningful: it proves the
|
||||
* key is live, and it rules out the app overwriting the seed a moment later.
|
||||
*/
|
||||
export async function persistedLayoutKey(
|
||||
page: Page,
|
||||
group: string,
|
||||
): Promise<string> {
|
||||
let key: string | undefined;
|
||||
|
||||
await expect
|
||||
.poll(async () => (key = await findWrittenKey(page, group)), {
|
||||
timeout: 10_000,
|
||||
message: `grid never persisted a layout for group "${group}"`,
|
||||
})
|
||||
.not.toBeUndefined();
|
||||
|
||||
return key!;
|
||||
}
|
||||
|
||||
/** Overwrite the stored layout, resolving only once the put has committed. */
|
||||
export function seedLayout(
|
||||
page: Page,
|
||||
key: string,
|
||||
value: unknown,
|
||||
): Promise<void> {
|
||||
return page.evaluate(
|
||||
([key, value]) =>
|
||||
new Promise<void>((resolve, reject) => {
|
||||
const open = indexedDB.open("keyval-store");
|
||||
open.onupgradeneeded = () => open.result.createObjectStore("keyval");
|
||||
open.onsuccess = () => {
|
||||
const tx = open.result.transaction("keyval", "readwrite");
|
||||
tx.objectStore("keyval").put(value, key as string);
|
||||
tx.oncomplete = () => {
|
||||
open.result.close();
|
||||
resolve();
|
||||
};
|
||||
tx.onerror = () => reject(tx.error);
|
||||
};
|
||||
open.onerror = () => reject(open.error);
|
||||
}),
|
||||
[key, value] as const,
|
||||
);
|
||||
}
|
||||
|
||||
/** Read the stored layout back. Undefined until the app writes it. */
|
||||
export function readLayout(
|
||||
page: Page,
|
||||
key: string,
|
||||
): Promise<PersistedLayout | undefined> {
|
||||
return page.evaluate(
|
||||
(target) =>
|
||||
new Promise((resolve) => {
|
||||
const open = indexedDB.open("keyval-store");
|
||||
open.onsuccess = () => {
|
||||
const tx = open.result.transaction("keyval", "readonly");
|
||||
const request = tx.objectStore("keyval").get(target);
|
||||
tx.oncomplete = () => {
|
||||
open.result.close();
|
||||
resolve(request.result);
|
||||
};
|
||||
};
|
||||
open.onerror = () => resolve(undefined);
|
||||
}),
|
||||
key,
|
||||
) as Promise<PersistedLayout | undefined>;
|
||||
}
|
||||
|
||||
export type Box = { w: number; h: number; x: number; y: number };
|
||||
|
||||
/** The card is the player root; the cell is the grid slot it sits in. */
|
||||
export type BoxTarget = "card" | "cell";
|
||||
|
||||
/** One atomic snapshot, or null while any tile is missing or unlaid out. */
|
||||
function snapshotBoxes(
|
||||
page: Page,
|
||||
cameras: readonly string[],
|
||||
target: BoxTarget,
|
||||
): Promise<Record<string, Box> | null> {
|
||||
return page.evaluate(
|
||||
({ cams, target }) => {
|
||||
const boxes: Record<string, Box> = {};
|
||||
|
||||
for (const cam of cams) {
|
||||
const card = document.querySelector(`[data-camera='${cam}']`);
|
||||
const el = target === "cell" ? card?.closest(".p-1") : card;
|
||||
|
||||
if (!el) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const r = el.getBoundingClientRect();
|
||||
|
||||
// a re-rendering tile can briefly report no box at all
|
||||
if (!r.width || !r.height) {
|
||||
return null;
|
||||
}
|
||||
|
||||
boxes[cam] = { w: r.width, h: r.height, x: r.x, y: r.y };
|
||||
}
|
||||
|
||||
return boxes;
|
||||
},
|
||||
{ cams: cameras as readonly string[], target },
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Measure the given cameras' tiles together, once they have all rendered.
|
||||
* Measuring in one evaluate is what keeps the numbers mutually comparable.
|
||||
*/
|
||||
export async function cameraBoxes<T extends string>(
|
||||
page: Page,
|
||||
cameras: readonly T[],
|
||||
target: BoxTarget = "cell",
|
||||
): Promise<Record<T, Box>> {
|
||||
let boxes: Record<string, Box> | null = null;
|
||||
|
||||
await expect
|
||||
.poll(async () => (boxes = await snapshotBoxes(page, cameras, target)), {
|
||||
timeout: 10_000,
|
||||
message: `${target}s never rendered for ${cameras.join(", ")}`,
|
||||
})
|
||||
.not.toBeNull();
|
||||
|
||||
return boxes as unknown as Record<T, Box>;
|
||||
}
|
||||
@@ -45,11 +45,6 @@ export class LivePage extends BasePage {
|
||||
);
|
||||
}
|
||||
|
||||
/** Edit-layout toggle on the draggable grid (desktop, custom groups). */
|
||||
get editLayoutButton(): Locator {
|
||||
return this.page.getByTestId("toggle-edit-layout");
|
||||
}
|
||||
|
||||
/** Open the right-click context menu on a camera card (desktop only). */
|
||||
async openContextMenuOn(cameraName: string): Promise<Locator> {
|
||||
await this.cameraCard(cameraName).first().click({ button: "right" });
|
||||
|
||||
@@ -1,185 +0,0 @@
|
||||
/**
|
||||
* Live grid aspect modes.
|
||||
*
|
||||
* Bucketed mode (the default) snaps every camera to a wide, landscape or tall
|
||||
* tile, and converts layouts saved by pre-masonry versions instead of
|
||||
* discarding them. Natural mode sizes each tile to its own camera.
|
||||
*/
|
||||
|
||||
import { test, expect } from "../fixtures/frigate-test";
|
||||
import { LivePage } from "../pages/live.page";
|
||||
import {
|
||||
cameraBoxes,
|
||||
persistedLayoutKey,
|
||||
readLayout,
|
||||
seedLayout,
|
||||
type LayoutItem,
|
||||
} from "../helpers/grid-layout";
|
||||
|
||||
const GROUP = "outdoor";
|
||||
const GRID_COLS = 96;
|
||||
|
||||
test.describe("Live grid aspect modes @critical", () => {
|
||||
test.skip(
|
||||
({ frigateApp }) => frigateApp.isMobile,
|
||||
"Draggable grid is desktop-only",
|
||||
);
|
||||
|
||||
test("an ultra-wide camera gets a 32:9 tile in bucketed mode @mobile", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.installDefaults({
|
||||
config: {
|
||||
cameras: { backyard: { detect: { width: 2560, height: 720 } } },
|
||||
},
|
||||
});
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
const { backyard: wide, front_door: normal } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
["backyard", "front_door"] as const,
|
||||
);
|
||||
|
||||
expect(wide.w / wide.h).toBeCloseTo(32 / 9, 1);
|
||||
expect(wide.w / normal.w).toBeCloseTo(2, 1);
|
||||
expect(wide.h).toBeCloseTo(normal.h, 0);
|
||||
});
|
||||
|
||||
test("a letterboxed still image rounds its own corners", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// A portrait camera pillarboxes inside its 8:9 bucket, so the card's
|
||||
// overflow-hidden clip never reaches the picture's corners. The image has
|
||||
// to carry the radius itself or it renders with square edges on the tile.
|
||||
await frigateApp.installDefaults({
|
||||
config: {
|
||||
cameras: { backyard: { detect: { width: 720, height: 1280 } } },
|
||||
},
|
||||
});
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
const radii = await frigateApp.page.evaluate(() => {
|
||||
const card = document.querySelector("[data-camera='backyard']");
|
||||
const img = card?.querySelector("img");
|
||||
return {
|
||||
card: card ? getComputedStyle(card).borderTopLeftRadius : null,
|
||||
img: img ? getComputedStyle(img).borderTopLeftRadius : null,
|
||||
};
|
||||
});
|
||||
|
||||
expect(radii.card).not.toBe("0px");
|
||||
expect(radii.img).toBe(radii.card);
|
||||
});
|
||||
|
||||
test("a pre-masonry layout is converted, keeping resized tiles", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// 0.17/0.18 shape: bare array on a 12-column grid, 4x4 standard tiles.
|
||||
// backyard was manually resized to 8x8 and sits beside front_door's column,
|
||||
// front_door is a standard tile on the row below.
|
||||
const key = await persistedLayoutKey(frigateApp.page, GROUP);
|
||||
await seedLayout(frigateApp.page, key, [
|
||||
{ i: "backyard", x: 4, y: 0, w: 8, h: 8, moved: false, static: false },
|
||||
{ i: "front_door", x: 0, y: 8, w: 4, h: 4, moved: false, static: false },
|
||||
]);
|
||||
await frigateApp.page.reload();
|
||||
await frigateApp.page.waitForSelector("#pageRoot", { timeout: 10_000 });
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// The conversion is written back on first load, replacing the legacy array
|
||||
// with an envelope. Poll for it: that write is an async idb put.
|
||||
await expect
|
||||
.poll(async () => (await readLayout(frigateApp.page, key))?.version, {
|
||||
timeout: 10_000,
|
||||
})
|
||||
.toBe(2);
|
||||
|
||||
const stored = (await readLayout(frigateApp.page, key))!;
|
||||
expect(stored).toMatchObject({ version: 2, naturalAspect: false });
|
||||
|
||||
// x and w scale 8x (12 -> 96 columns), y and h scale 18x (4 -> 72 rows per
|
||||
// standard tile), so the manual resize survives instead of snapping back.
|
||||
expect(
|
||||
stored.layout.find((i: LayoutItem) => i.i === "backyard"),
|
||||
).toMatchObject({
|
||||
x: 32,
|
||||
y: 0,
|
||||
w: 64,
|
||||
h: 144,
|
||||
});
|
||||
expect(
|
||||
stored.layout.find((i: LayoutItem) => i.i === "front_door"),
|
||||
).toMatchObject({
|
||||
x: 0,
|
||||
y: 144,
|
||||
w: 32,
|
||||
h: 72,
|
||||
});
|
||||
|
||||
// arrangement on screen: backyard indented, front_door below it
|
||||
const { backyard, front_door: frontDoor } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
["backyard", "front_door"] as const,
|
||||
);
|
||||
expect(backyard.x).toBeGreaterThan(frontDoor.x + frontDoor.w / 2);
|
||||
expect(frontDoor.y).toBeGreaterThan(backyard.y + backyard.h / 2);
|
||||
});
|
||||
|
||||
test("conversion is a pure scale, so odd sizes and positions survive", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// The old grid exposed all four resize corners with no aspect constraint,
|
||||
// so a stored tile can be any size. These two are adjacent and non-standard.
|
||||
const key = await persistedLayoutKey(frigateApp.page, GROUP);
|
||||
await seedLayout(frigateApp.page, key, [
|
||||
{ i: "front_door", x: 0, y: 3, w: 5, h: 5 },
|
||||
{ i: "backyard", x: 5, y: 3, w: 7, h: 5 },
|
||||
]);
|
||||
await frigateApp.page.reload();
|
||||
await frigateApp.page.waitForSelector("#pageRoot", { timeout: 10_000 });
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
await expect
|
||||
.poll(async () => (await readLayout(frigateApp.page, key))?.version, {
|
||||
timeout: 10_000,
|
||||
})
|
||||
.toBe(2);
|
||||
|
||||
const stored = (await readLayout(frigateApp.page, key))!;
|
||||
const frontDoor = stored.layout.find(
|
||||
(i: LayoutItem) => i.i === "front_door",
|
||||
)!;
|
||||
const backyard = stored.layout.find((i: LayoutItem) => i.i === "backyard")!;
|
||||
|
||||
expect(frontDoor).toMatchObject({ x: 0, y: 54, w: 40, h: 90 });
|
||||
expect(backyard).toMatchObject({ x: 40, y: 54, w: 56, h: 90 });
|
||||
|
||||
// still adjacent, still inside the grid, still not overlapping
|
||||
expect(frontDoor.x + frontDoor.w).toBe(backyard.x);
|
||||
expect(backyard.x + backyard.w).toBe(GRID_COLS);
|
||||
});
|
||||
});
|
||||
@@ -1,298 +0,0 @@
|
||||
/**
|
||||
* Masonry live grid -- custom-group draggable layout.
|
||||
*
|
||||
* Verifies natural-aspect tile sizing and that a saved layout the current
|
||||
* version cannot read is regenerated cleanly. The grid renders only for a
|
||||
* custom camera group (here: "outdoor") on desktop; mobile keeps the static
|
||||
* grid, which the @mobile block below guards.
|
||||
*/
|
||||
|
||||
import { test, expect } from "../fixtures/frigate-test";
|
||||
import { LivePage } from "../pages/live.page";
|
||||
import {
|
||||
cameraBoxes,
|
||||
persistedLayoutKey,
|
||||
readLayout,
|
||||
seedLayout,
|
||||
} from "../helpers/grid-layout";
|
||||
|
||||
const GROUP = "outdoor"; // custom group: front_door + backyard
|
||||
|
||||
test.describe("Masonry live grid @critical", () => {
|
||||
test.skip(
|
||||
({ frigateApp }) => frigateApp.isMobile,
|
||||
"Draggable masonry grid is desktop-only",
|
||||
);
|
||||
|
||||
test("custom group renders its cameras in the draggable grid", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible();
|
||||
});
|
||||
|
||||
test("tiles render at their camera's natural aspect ratio", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// backyard is 9:16, which bucketed mode would snap to an 8:9 tile
|
||||
await frigateApp.installDefaults({
|
||||
config: {
|
||||
cameras: { backyard: { detect: { width: 720, height: 1280 } } },
|
||||
},
|
||||
});
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
await seedLayout(frigateApp.page, "naturalAspectLayout:admin", true);
|
||||
await frigateApp.page.reload();
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
const { front_door: landscape, backyard: portrait } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
["front_door", "backyard"] as const,
|
||||
"card",
|
||||
);
|
||||
|
||||
expect(landscape.w / landscape.h).toBeCloseTo(16 / 9, 1);
|
||||
expect(portrait.w / portrait.h).toBeCloseTo(9 / 16, 1);
|
||||
});
|
||||
|
||||
test("dragging a tile does not shove other tiles far away", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
await live.editLayoutButton.click();
|
||||
|
||||
const cameras = ["front_door", "backyard"] as const;
|
||||
const { front_door: fixedBefore, backyard: draggedBox } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
cameras,
|
||||
"card",
|
||||
);
|
||||
|
||||
// Drag backyard onto front_door's position (a deliberate collision). With
|
||||
// free-placement + prevent-collision, front_door must NOT be shoved down.
|
||||
const from = {
|
||||
x: draggedBox.x + draggedBox.w / 2,
|
||||
y: draggedBox.y + draggedBox.h / 2,
|
||||
};
|
||||
const to = {
|
||||
x: fixedBefore.x + fixedBefore.w / 2,
|
||||
y: fixedBefore.y + fixedBefore.h / 2,
|
||||
};
|
||||
await frigateApp.page.mouse.move(from.x, from.y);
|
||||
await frigateApp.page.mouse.down();
|
||||
await frigateApp.page.mouse.move(to.x, to.y, { steps: 15 });
|
||||
await frigateApp.page.mouse.up();
|
||||
|
||||
const { front_door: fixedAfter } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
cameras,
|
||||
"card",
|
||||
);
|
||||
// Allow a few px of snap; a collision-push would move it a whole tile down.
|
||||
expect(Math.abs(fixedAfter.y - fixedBefore.y)).toBeLessThan(40);
|
||||
});
|
||||
|
||||
test("resizing a top-row tile preserves its aspect ratio (no pillarboxing)", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// A lone top tile has room to grow sideways, which is what exposed the bug:
|
||||
// a top-edge handle let width grow while height stayed clamped at y=0.
|
||||
await frigateApp.installDefaults({
|
||||
config: { camera_groups: { outdoor: { cameras: ["front_door"] } } },
|
||||
});
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
await live.editLayoutButton.click();
|
||||
|
||||
const tile = frigateApp.page.locator(".react-grid-item", {
|
||||
has: frigateApp.page.locator("[data-camera='front_door']"),
|
||||
});
|
||||
const only = ["front_door"] as const;
|
||||
const { front_door: before } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
only,
|
||||
"card",
|
||||
);
|
||||
const aspect = before.w / before.h;
|
||||
|
||||
// Regression: if a top-edge handle is exposed, dragging it up/out must NOT
|
||||
// distort the aspect (the old bug grew width while height stayed clamped).
|
||||
const ne = tile.locator(".react-resizable-handle-ne");
|
||||
if (await ne.count()) {
|
||||
await ne.dragTo(tile, {
|
||||
force: true,
|
||||
targetPosition: { x: 1000, y: -160 },
|
||||
});
|
||||
const { front_door: afterNe } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
only,
|
||||
"card",
|
||||
);
|
||||
// It must actually resize (not a silent no-op) AND keep its aspect.
|
||||
expect(afterNe.w).toBeGreaterThan(before.w);
|
||||
expect(Math.abs(afterNe.w / afterNe.h - aspect)).toBeLessThan(0.2);
|
||||
}
|
||||
|
||||
// Positive: growing from the bottom-right corner resizes and keeps aspect.
|
||||
const se = tile.locator(".react-resizable-handle-se");
|
||||
await se.dragTo(tile, { force: true, targetPosition: { x: 1000, y: 520 } });
|
||||
const { front_door: grown } = await cameraBoxes(
|
||||
frigateApp.page,
|
||||
only,
|
||||
"card",
|
||||
);
|
||||
expect(grown.w).toBeGreaterThan(before.w);
|
||||
expect(Math.abs(grown.w / grown.h - aspect)).toBeLessThan(0.2);
|
||||
});
|
||||
|
||||
test("the grid keeps its measured width after a back navigation", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// The grid sizes itself from window.innerWidth until its container is
|
||||
// measured. On a warm back navigation nothing re-renders after that
|
||||
// container mounts, so an observer that never attaches leaves every tile
|
||||
// sized against the full window: the layout widens by the sidebar's width
|
||||
// and the rightmost column clips on a full row.
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// total width the tiles span; tracks the width the grid laid out against
|
||||
const span = () =>
|
||||
frigateApp.page.evaluate(() => {
|
||||
const tiles = [...document.querySelectorAll(".react-grid-item")];
|
||||
|
||||
if (!tiles.length) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const rects = tiles.map((tile) => tile.getBoundingClientRect());
|
||||
return +(
|
||||
Math.max(...rects.map((r) => r.right)) -
|
||||
Math.min(...rects.map((r) => r.left))
|
||||
).toFixed(1);
|
||||
});
|
||||
|
||||
let fresh: number | null = null;
|
||||
await expect
|
||||
.poll(async () => (fresh = await span()), { timeout: 10_000 })
|
||||
.not.toBeNull();
|
||||
|
||||
await live.cameraCard("front_door").first().click();
|
||||
await expect(frigateApp.page).toHaveURL(/#front_door/);
|
||||
|
||||
await frigateApp.page.goBack();
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// the layout must settle back to the measured width, not window.innerWidth
|
||||
await expect
|
||||
.poll(span, { timeout: 10_000 })
|
||||
.toBeLessThanOrEqual(fresh! + 2);
|
||||
});
|
||||
|
||||
test("a camera added to a saved layout fills an open column", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// one tall tile in the first column; backyard is missing from the layout
|
||||
const key = await persistedLayoutKey(frigateApp.page, GROUP);
|
||||
await seedLayout(frigateApp.page, key, {
|
||||
version: 2,
|
||||
naturalAspect: false,
|
||||
layout: [{ i: "front_door", x: 0, y: 0, w: 32, h: 400 }],
|
||||
});
|
||||
await frigateApp.page.reload();
|
||||
|
||||
await expect
|
||||
.poll(async () => {
|
||||
const stored = await readLayout(frigateApp.page, key);
|
||||
return stored?.layout.find((item) => item.i === "backyard");
|
||||
})
|
||||
.toMatchObject({ x: 32, y: 0 });
|
||||
});
|
||||
|
||||
test("saved layout from an unreadable version regenerates without error", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, true);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
|
||||
// A bare array is converted rather than discarded (covered in
|
||||
// live-grid-aspect-modes), so use a version the current grid cannot read.
|
||||
const key = await persistedLayoutKey(frigateApp.page, GROUP);
|
||||
await seedLayout(frigateApp.page, key, {
|
||||
version: 1,
|
||||
naturalAspect: false,
|
||||
layout: [{ i: "front_door", x: 0, y: 0, w: 4, h: 3 }],
|
||||
});
|
||||
|
||||
await frigateApp.page.reload();
|
||||
await frigateApp.page.waitForSelector("#pageRoot", { timeout: 10_000 });
|
||||
|
||||
// Grid regenerated; both cameras still render and the error collector
|
||||
// (frigate-test fixture) catches any crash.
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible();
|
||||
|
||||
// The app must have replaced the value it could not read. Without this the
|
||||
// test would still pass against a key the app never touches.
|
||||
await expect
|
||||
.poll(async () => (await readLayout(frigateApp.page, key))?.version, {
|
||||
timeout: 10_000,
|
||||
})
|
||||
.toBeGreaterThan(1);
|
||||
});
|
||||
});
|
||||
|
||||
test.describe("Masonry live grid on mobile @critical @mobile", () => {
|
||||
test("custom group keeps the static grid, with no draggable layout", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
test.skip(!frigateApp.isMobile, "Mobile-only");
|
||||
|
||||
await frigateApp.goto(`/?group=${GROUP}`);
|
||||
const live = new LivePage(frigateApp.page, false);
|
||||
await expect(live.cameraCard("front_door").first()).toBeVisible({
|
||||
timeout: 10_000,
|
||||
});
|
||||
await expect(live.cameraCard("backyard").first()).toBeVisible();
|
||||
|
||||
// isMobileOnly routes around DraggableGridLayout entirely, so neither the
|
||||
// grid items nor the edit-layout toggle may appear.
|
||||
await expect(frigateApp.page.locator(".react-grid-item")).toHaveCount(0);
|
||||
await expect(live.editLayoutButton).toHaveCount(0);
|
||||
});
|
||||
});
|
||||
@@ -1,135 +0,0 @@
|
||||
/**
|
||||
* Camera detect scene tests -- MEDIUM tier.
|
||||
*
|
||||
* Scenes are free-form names declared by the configured models, so a camera
|
||||
* only needs to pick one when there is a choice to make. The choices are the
|
||||
* scenes of the configured models, plus a saved scene that no model uses.
|
||||
*/
|
||||
|
||||
import { readFileSync } from "node:fs";
|
||||
import { resolve, dirname } from "node:path";
|
||||
import { fileURLToPath } from "node:url";
|
||||
import { test, expect } from "../../fixtures/frigate-test";
|
||||
import type { Page } from "@playwright/test";
|
||||
import { configFactory } from "../../fixtures/mock-data/config";
|
||||
|
||||
const __dirname = dirname(fileURLToPath(import.meta.url));
|
||||
const CONFIG_SCHEMA = JSON.parse(
|
||||
readFileSync(
|
||||
resolve(__dirname, "../../fixtures/mock-data/config-schema.json"),
|
||||
"utf-8",
|
||||
),
|
||||
);
|
||||
|
||||
const SETTINGS_URL = "/settings?page=cameraDetect&camera=front_door";
|
||||
|
||||
async function installRoutes(
|
||||
page: Page,
|
||||
models: { scene: string; devices: string[] }[],
|
||||
cameraScene?: string,
|
||||
) {
|
||||
const config = configFactory({
|
||||
models,
|
||||
...(cameraScene
|
||||
? { cameras: { front_door: { detect: { scene: cameraScene } } } }
|
||||
: {}),
|
||||
} as never);
|
||||
|
||||
await page.route("**/api/config/schema.json", (route) =>
|
||||
route.fulfill({ json: CONFIG_SCHEMA }),
|
||||
);
|
||||
await page.route("**/api/config", (route) =>
|
||||
route.request().method() === "GET"
|
||||
? route.fulfill({ json: config })
|
||||
: route.fulfill({ json: { success: true } }),
|
||||
);
|
||||
await page.route("**/api/config/raw_paths", (route) =>
|
||||
route.fulfill({ json: {} }),
|
||||
);
|
||||
}
|
||||
|
||||
test.describe("camera detect scene @medium", () => {
|
||||
test("is hidden when there is only one model", async ({ frigateApp }) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
]);
|
||||
await frigateApp.goto(SETTINGS_URL);
|
||||
|
||||
const root = frigateApp.page.locator("#pageRoot");
|
||||
await expect(root).toContainText("Detect FPS");
|
||||
await expect(root).not.toContainText("Detect scene");
|
||||
});
|
||||
|
||||
test("offers the default and configured model scenes", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
{ scene: "thermal", devices: ["openvino:GPU.0"] },
|
||||
]);
|
||||
await frigateApp.goto(SETTINGS_URL);
|
||||
|
||||
const root = frigateApp.page.locator("#pageRoot");
|
||||
await expect(root).toContainText("Detect scene");
|
||||
|
||||
await frigateApp.page.locator("#root_scene").click();
|
||||
const options = frigateApp.page.getByRole("option");
|
||||
await expect(options).toHaveText(["Default", "thermal"]);
|
||||
});
|
||||
|
||||
test("a saved scene no model uses stays editable", async ({ frigateApp }) => {
|
||||
// the camera falls back to the default model, but its saved scene would
|
||||
// silently take effect if a model for it were added later
|
||||
await installRoutes(
|
||||
frigateApp.page,
|
||||
[{ scene: "default", devices: ["cpu"] }],
|
||||
"garage",
|
||||
);
|
||||
await frigateApp.goto(SETTINGS_URL);
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"Detect scene",
|
||||
);
|
||||
|
||||
await frigateApp.page.locator("#root_scene").click();
|
||||
await expect(frigateApp.page.getByRole("option")).toHaveText([
|
||||
"Default",
|
||||
"garage",
|
||||
]);
|
||||
});
|
||||
|
||||
test("default is only offered when a default model exists", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(
|
||||
frigateApp.page,
|
||||
[
|
||||
{ scene: "thermal", devices: ["cpu"] },
|
||||
{ scene: "visible", devices: ["openvino:GPU.0"] },
|
||||
],
|
||||
"thermal",
|
||||
);
|
||||
await frigateApp.goto(SETTINGS_URL);
|
||||
|
||||
await frigateApp.page.locator("#root_scene").click();
|
||||
await expect(frigateApp.page.getByRole("option")).toHaveText([
|
||||
"thermal",
|
||||
"visible",
|
||||
]);
|
||||
});
|
||||
|
||||
test("one model every camera selects needs no choice", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(
|
||||
frigateApp.page,
|
||||
[{ scene: "thermal", devices: ["cpu"] }],
|
||||
"thermal",
|
||||
);
|
||||
await frigateApp.goto(SETTINGS_URL);
|
||||
|
||||
const root = frigateApp.page.locator("#pageRoot");
|
||||
await expect(root).toContainText("Detect FPS");
|
||||
await expect(root).not.toContainText("Detect scene");
|
||||
});
|
||||
});
|
||||
@@ -129,19 +129,19 @@ const openPage = async (frigateApp: {
|
||||
test.describe("Detection models settings @high", () => {
|
||||
test("renders a card per configured model", async ({ frigateApp }) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
{ scene: "all", devices: ["cpu"] },
|
||||
{ scene: "outdoor", devices: ["edgetpu:pci:0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
const root = frigateApp.page.locator("#pageRoot");
|
||||
await expect(root).toContainText("Default");
|
||||
await expect(root).toContainText("outdoor");
|
||||
await expect(root).toContainText("All cameras");
|
||||
await expect(root).toContainText("Outdoor");
|
||||
});
|
||||
|
||||
test("unlimited hardware offers a detector count", async ({ frigateApp }) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0"] },
|
||||
{ scene: "all", devices: ["openvino:GPU.0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -169,7 +169,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0", "openvino:GPU.0"] },
|
||||
{ scene: "all", devices: ["openvino:GPU.0", "openvino:GPU.0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -190,7 +190,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["edgetpu:pci:0"] },
|
||||
{ scene: "all", devices: ["edgetpu:pci:0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -206,7 +206,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["edgetpu:pci:0"] },
|
||||
{ scene: "all", devices: ["edgetpu:pci:0"] },
|
||||
{ scene: "outdoor", devices: ["edgetpu:pci:1"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
@@ -217,158 +217,23 @@ test.describe("Detection models settings @high", () => {
|
||||
).toBeDisabled();
|
||||
});
|
||||
|
||||
test("shareable hardware another model uses can still be picked", async ({
|
||||
test("adding a model appends a card with an unused scene", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0"] },
|
||||
{ scene: "outdoor", devices: ["openvino:GPU.1"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await expect(
|
||||
frigateApp.page.locator("#models-0-openvino\\:GPU\\.1").first(),
|
||||
).toBeEnabled();
|
||||
await expect(frigateApp.page.locator("#pageRoot")).not.toContainText(
|
||||
"used by outdoor",
|
||||
);
|
||||
});
|
||||
|
||||
test("adding a model appends a card with a scene to name", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
]);
|
||||
await installRoutes(frigateApp.page, [{ scene: "all", devices: ["cpu"] }]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await frigateApp.page.getByRole("button", { name: "Add model" }).click();
|
||||
|
||||
// the new card's scene starts empty, and a scene is required to save
|
||||
const scene = frigateApp.page.locator("#models-1-scene");
|
||||
await expect(scene).toHaveValue("");
|
||||
await expect(
|
||||
frigateApp.page.getByRole("button", { name: /^Save$/ }),
|
||||
).toBeDisabled();
|
||||
|
||||
// the card keeps focus while its scene is typed
|
||||
await scene.fill("thermal");
|
||||
await expect(scene).toHaveValue("thermal");
|
||||
await expect(scene).toBeFocused();
|
||||
});
|
||||
|
||||
test("one model file cannot be split across scenes", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{
|
||||
scene: "default",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "/config/model_cache/yolo.onnx",
|
||||
},
|
||||
{
|
||||
scene: "driveway",
|
||||
devices: ["openvino:GPU.1"],
|
||||
path: "/config/model_cache/other.onnx",
|
||||
},
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await frigateApp.page
|
||||
.locator("#root_1_path")
|
||||
.fill("/config/model_cache/yolo.onnx");
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"The Default and driveway models use the same model file",
|
||||
);
|
||||
await expect(
|
||||
frigateApp.page.getByRole("button", { name: /^Save$/ }),
|
||||
).toBeDisabled();
|
||||
});
|
||||
|
||||
test("two models without a path share the detector's default model", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
{ scene: "driveway", devices: ["cpu"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"The Default and driveway models use the same model file",
|
||||
);
|
||||
});
|
||||
|
||||
test("another spelling of the same path is the same model", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{
|
||||
scene: "default",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "/config/model_cache/yolo.onnx",
|
||||
},
|
||||
{
|
||||
scene: "driveway",
|
||||
devices: ["openvino:GPU.1"],
|
||||
path: "/config//model_cache/./tmp/../yolo.onnx",
|
||||
},
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"The Default and driveway models use the same model file",
|
||||
);
|
||||
});
|
||||
|
||||
test("one model file may run on different detectors", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{
|
||||
scene: "default",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "/config/model_cache/yolo.onnx",
|
||||
},
|
||||
{
|
||||
scene: "driveway",
|
||||
devices: ["onnx"],
|
||||
path: "/config/model_cache/yolo.onnx",
|
||||
},
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"driveway",
|
||||
);
|
||||
await expect(frigateApp.page.locator("#pageRoot")).not.toContainText(
|
||||
"models use the same model file",
|
||||
);
|
||||
});
|
||||
|
||||
test("two models cannot share a scene", async ({ frigateApp }) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
{ scene: "thermal", devices: ["edgetpu:pci:0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await frigateApp.page.locator("#models-1-scene").fill("default");
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"Each model must use a different scene",
|
||||
);
|
||||
await expect(
|
||||
frigateApp.page.getByRole("button", { name: /^Save$/ }),
|
||||
).toBeDisabled();
|
||||
// "all" is taken, so the new card takes the next available scene
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText("Indoor");
|
||||
});
|
||||
|
||||
test("hardware is summarized rather than listed device by device", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0", "openvino:GPU.0"] },
|
||||
{ scene: "all", devices: ["openvino:GPU.0", "openvino:GPU.0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -383,13 +248,15 @@ test.describe("Detection models settings @high", () => {
|
||||
test("a saved Frigate+ model opens on the Frigate+ tab", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// the backend resolves plus:// to a cache path before serving the config
|
||||
// back, so the plus metadata is the only signal the model is a Plus one
|
||||
await installRoutes(
|
||||
frigateApp.page,
|
||||
[
|
||||
{
|
||||
scene: "default",
|
||||
scene: "all",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "plus://abc123",
|
||||
path: "/config/model_cache/abc123",
|
||||
plus: PLUS_MODEL,
|
||||
},
|
||||
],
|
||||
@@ -412,7 +279,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp.page,
|
||||
[
|
||||
{
|
||||
scene: "default",
|
||||
scene: "all",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "/config/custom.onnx",
|
||||
},
|
||||
@@ -435,65 +302,6 @@ test.describe("Detection models settings @high", () => {
|
||||
expect(saves.at(-1)?.config_data?.models?.[0].path).toBe("plus://abc123");
|
||||
});
|
||||
|
||||
test("saving a Frigate+ model keeps its reference without the Frigate+ fields", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// the backend fills these in from the Frigate+ model info when it loads
|
||||
const saves = await installRoutes(
|
||||
frigateApp.page,
|
||||
[
|
||||
{
|
||||
scene: "default",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "plus://abc123",
|
||||
plus: PLUS_MODEL,
|
||||
width: 320,
|
||||
height: 320,
|
||||
input_tensor: "nchw",
|
||||
input_dtype: "float",
|
||||
model_type: "yolo-generic",
|
||||
},
|
||||
],
|
||||
true,
|
||||
);
|
||||
await openPage(frigateApp);
|
||||
|
||||
await frigateApp.page.locator("#models-0-openvino\\:GPU\\.1").click();
|
||||
await frigateApp.page.getByRole("button", { name: /^Save$/ }).click();
|
||||
await expect.poll(() => saves.length).toBeGreaterThan(0);
|
||||
|
||||
const model = saves.at(-1)?.config_data?.models?.[0];
|
||||
expect(model?.path).toBe("plus://abc123");
|
||||
expect(model?.devices).toEqual(["openvino:GPU.0", "openvino:GPU.1"]);
|
||||
expect(model).not.toHaveProperty("width");
|
||||
expect(model).not.toHaveProperty("input_tensor");
|
||||
expect(model).not.toHaveProperty("model_type");
|
||||
// a leftover dtype from a custom model must not override the int default
|
||||
expect(model).not.toHaveProperty("input_dtype");
|
||||
});
|
||||
|
||||
test("a Frigate+ model only shows its path without a Frigate+ API key", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{
|
||||
scene: "default",
|
||||
devices: ["openvino:GPU.0"],
|
||||
path: "plus://abc123",
|
||||
width: 320,
|
||||
height: 320,
|
||||
},
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
const root = frigateApp.page.locator("#pageRoot");
|
||||
await expect(root).toContainText("Custom object detector model path");
|
||||
await expect(root).not.toContainText("Object detection model input width");
|
||||
await expect(root).not.toContainText(
|
||||
"Label map for custom object detector",
|
||||
);
|
||||
});
|
||||
|
||||
test("a Frigate+ Hailo model is listed by the device it was built for", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
@@ -501,13 +309,7 @@ test.describe("Detection models settings @high", () => {
|
||||
// says nothing; which device it was built for is what the user picks on
|
||||
await installRoutes(
|
||||
frigateApp.page,
|
||||
[
|
||||
{
|
||||
scene: "default",
|
||||
devices: ["hailo:PCIe"],
|
||||
path: "/config/custom.hef",
|
||||
},
|
||||
],
|
||||
[{ scene: "all", devices: ["hailo:PCIe"], path: "/config/custom.hef" }],
|
||||
true,
|
||||
HAILO_PLUS_MODELS,
|
||||
true,
|
||||
@@ -537,7 +339,7 @@ test.describe("Detection models settings @high", () => {
|
||||
// that must not read as an edit.
|
||||
await installRoutes(frigateApp.page, [
|
||||
{
|
||||
scene: "default",
|
||||
scene: "all",
|
||||
devices: ["openvino:GPU.0", "openvino:GPU.0"],
|
||||
path: "/config/model_cache/abc123",
|
||||
width: 320,
|
||||
@@ -562,14 +364,12 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0"] },
|
||||
{ scene: "all", devices: ["openvino:GPU.0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
const root = frigateApp.page.locator("#pageRoot");
|
||||
await expect(root).toContainText(
|
||||
"A name for the cameras this model is for",
|
||||
);
|
||||
await expect(root).toContainText("The environment this model is for");
|
||||
await expect(root).toContainText(
|
||||
"The hardware this model runs its detection on",
|
||||
);
|
||||
@@ -580,7 +380,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["edgetpu:pci:0"] },
|
||||
{ scene: "all", devices: ["edgetpu:pci:0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -591,10 +391,10 @@ test.describe("Detection models settings @high", () => {
|
||||
});
|
||||
|
||||
test("removing the default model blocks saving", async ({ frigateApp }) => {
|
||||
// a camera that names no scene runs the default model, so deleting it would
|
||||
// a camera that names no scene runs the "all" model, so deleting it would
|
||||
// leave those cameras with nothing to fall back to
|
||||
await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["cpu"] },
|
||||
{ scene: "all", devices: ["cpu"] },
|
||||
{ scene: "outdoor", devices: ["edgetpu:pci:0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
@@ -605,7 +405,7 @@ test.describe("Detection models settings @high", () => {
|
||||
.click();
|
||||
|
||||
await expect(frigateApp.page.locator("#pageRoot")).toContainText(
|
||||
"One model must use the default scene",
|
||||
"One model must use a scene of 'All cameras'",
|
||||
);
|
||||
await expect(
|
||||
frigateApp.page.getByRole("button", { name: /^Save$/ }),
|
||||
@@ -616,7 +416,7 @@ test.describe("Detection models settings @high", () => {
|
||||
// shareable hardware can report several addressable units; every one of
|
||||
// them must be reachable, not just the first
|
||||
const saves = await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0"] },
|
||||
{ scene: "all", devices: ["openvino:GPU.0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -634,7 +434,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
const saves = await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["openvino:GPU.0", "openvino:GPU.1"] },
|
||||
{ scene: "all", devices: ["openvino:GPU.0", "openvino:GPU.1"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
@@ -657,7 +457,7 @@ test.describe("Detection models settings @high", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
const saves = await installRoutes(frigateApp.page, [
|
||||
{ scene: "default", devices: ["edgetpu:pci:0"] },
|
||||
{ scene: "all", devices: ["edgetpu:pci:0"] },
|
||||
]);
|
||||
await openPage(frigateApp);
|
||||
|
||||
|
||||
@@ -13,26 +13,7 @@ import type { Page } from "@playwright/test";
|
||||
const OUTDOOR_LAYOUT_KEY = "outdoor-draggable-layout:admin";
|
||||
const STREAMING_KEY = "streaming-settings:admin";
|
||||
|
||||
// the shape DraggableGridLayout writes
|
||||
const OUTDOOR_LAYOUT = {
|
||||
version: 2,
|
||||
naturalAspect: false,
|
||||
layout: [
|
||||
{ i: "front_door", x: 0, y: 0, w: 32, h: 72 },
|
||||
{ i: "backyard", x: 32, y: 0, w: 32, h: 72 },
|
||||
],
|
||||
};
|
||||
|
||||
const NATURAL_OUTDOOR_LAYOUT = {
|
||||
version: 2,
|
||||
naturalAspect: true,
|
||||
layout: [
|
||||
{ i: "front_door", x: 0, y: 0, w: 32, h: 72 },
|
||||
{ i: "backyard", x: 32, y: 0, w: 24, h: 96 },
|
||||
],
|
||||
};
|
||||
|
||||
const LEGACY_OUTDOOR_LAYOUT = [
|
||||
const OUTDOOR_LAYOUT = [
|
||||
{ i: "front_door", x: 0, y: 0, w: 6, h: 4 },
|
||||
{ i: "backyard", x: 6, y: 0, w: 6, h: 4 },
|
||||
];
|
||||
@@ -178,160 +159,6 @@ test.describe("UI settings import/export @medium", () => {
|
||||
expect(payload.sections.preferences.playbackRate).toBe(2);
|
||||
});
|
||||
|
||||
test("exports only layouts built for the current tile sizing mode", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
// a group not opened since the mode changed still holds a layout from
|
||||
// the other mode, which would import into a mode that cannot show it
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
|
||||
await writeIdb(frigateApp.page, {
|
||||
[OUTDOOR_LAYOUT_KEY]: OUTDOOR_LAYOUT,
|
||||
"default-draggable-layout:admin": NATURAL_OUTDOOR_LAYOUT,
|
||||
"naturalAspectLayout:admin": true,
|
||||
});
|
||||
|
||||
const downloadPromise = frigateApp.page.waitForEvent("download");
|
||||
await frigateApp.page
|
||||
.getByRole("button", { name: "Export Settings" })
|
||||
.click();
|
||||
const download = await downloadPromise;
|
||||
const payload = JSON.parse(readFileSync((await download.path())!, "utf-8"));
|
||||
|
||||
expect(payload.sections.layouts).toEqual({
|
||||
default: NATURAL_OUTDOOR_LAYOUT,
|
||||
});
|
||||
});
|
||||
|
||||
test("toggling tile sizing mode clears stored layouts", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
test.skip(frigateApp.isMobile, "The setting is hidden on phones");
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
await writeIdb(frigateApp.page, { [OUTDOOR_LAYOUT_KEY]: OUTDOOR_LAYOUT });
|
||||
|
||||
await frigateApp.page.locator("#natural-aspect-desktop").click();
|
||||
await frigateApp.page
|
||||
.getByRole("alertdialog")
|
||||
.getByRole("button", { name: "Enable" })
|
||||
.click();
|
||||
|
||||
await expect
|
||||
.poll(() => readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY))
|
||||
.toBeNull();
|
||||
expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
|
||||
true,
|
||||
);
|
||||
});
|
||||
|
||||
test("round-trips a layout left unconverted by an upgrade", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
|
||||
// DraggableGridLayout rewrites a pre-0.19 layout only when that group's
|
||||
// dashboard is opened, so exporting first carries the bare array into the
|
||||
// file. Import must accept it back rather than rejecting the whole file.
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
|
||||
await writeIdb(frigateApp.page, {
|
||||
[OUTDOOR_LAYOUT_KEY]: LEGACY_OUTDOOR_LAYOUT,
|
||||
"playbackRate:admin": 2,
|
||||
});
|
||||
|
||||
const downloadPromise = frigateApp.page.waitForEvent("download");
|
||||
await frigateApp.page
|
||||
.getByRole("button", { name: "Export Settings" })
|
||||
.click();
|
||||
const download = await downloadPromise;
|
||||
const contents = readFileSync((await download.path())!, "utf-8");
|
||||
|
||||
expect(JSON.parse(contents).sections.layouts.outdoor).toEqual(
|
||||
LEGACY_OUTDOOR_LAYOUT,
|
||||
);
|
||||
|
||||
await clearIdb(frigateApp.page);
|
||||
await chooseImportText(frigateApp.page, contents);
|
||||
await confirmImport(frigateApp.page);
|
||||
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
|
||||
LEGACY_OUTDOOR_LAYOUT,
|
||||
);
|
||||
// the rest of the file must survive alongside it
|
||||
expect(await readIdb(frigateApp.page, "playbackRate:admin")).toBe(2);
|
||||
});
|
||||
|
||||
test("legacy layouts import turns natural aspect off so they display", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
|
||||
// Bare-array layouts only render in bucketed mode; with natural aspect on
|
||||
// they would be discarded and regenerated on the next dashboard visit. The
|
||||
// import applies the mode the layouts were built for, and the file's own
|
||||
// naturalAspectLayout preference must not override that.
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
await writeIdb(frigateApp.page, { "naturalAspectLayout:admin": true });
|
||||
|
||||
await chooseImportFile(
|
||||
frigateApp.page,
|
||||
importPayload({
|
||||
sections: {
|
||||
layouts: { outdoor: LEGACY_OUTDOOR_LAYOUT },
|
||||
streaming: {},
|
||||
preferences: { naturalAspectLayout: true },
|
||||
},
|
||||
}),
|
||||
);
|
||||
|
||||
const note = frigateApp.page.getByText(/standard tile sizing/);
|
||||
await expect(note).toBeVisible();
|
||||
|
||||
// the note is about the layouts section, so it follows its switch
|
||||
await frigateApp.page.getByText("Camera group layouts (1 group)").click();
|
||||
await expect(note).toBeHidden();
|
||||
await frigateApp.page.getByText("Camera group layouts (1 group)").click();
|
||||
await expect(note).toBeVisible();
|
||||
|
||||
await confirmImport(frigateApp.page);
|
||||
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
|
||||
LEGACY_OUTDOOR_LAYOUT,
|
||||
);
|
||||
expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
|
||||
false,
|
||||
);
|
||||
});
|
||||
|
||||
test("natural aspect layouts import turns the setting on", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
|
||||
await chooseImportFile(
|
||||
frigateApp.page,
|
||||
importPayload({
|
||||
sections: {
|
||||
layouts: { outdoor: NATURAL_OUTDOOR_LAYOUT },
|
||||
streaming: {},
|
||||
preferences: {},
|
||||
},
|
||||
}),
|
||||
);
|
||||
|
||||
await expect(
|
||||
frigateApp.page.getByText(/camera aspect ratio tile sizing/),
|
||||
).toBeVisible();
|
||||
|
||||
await confirmImport(frigateApp.page);
|
||||
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
|
||||
NATURAL_OUTDOOR_LAYOUT,
|
||||
);
|
||||
expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
|
||||
true,
|
||||
);
|
||||
});
|
||||
|
||||
test("omits settings that were never stored", async ({ frigateApp }) => {
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
|
||||
@@ -363,15 +190,12 @@ test.describe("UI settings import/export @medium", () => {
|
||||
await expect(
|
||||
frigateApp.page.getByText("UI preferences (2 settings)"),
|
||||
).toBeVisible();
|
||||
// patio is layout-only, so its warning follows the layouts section
|
||||
await expect(frigateApp.page.getByText(/patio/)).toBeVisible({
|
||||
visible: !frigateApp.isMobile,
|
||||
});
|
||||
await expect(frigateApp.page.getByText(/patio/)).toBeVisible();
|
||||
|
||||
await confirmImport(frigateApp.page);
|
||||
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
|
||||
frigateApp.isMobile ? null : OUTDOOR_LAYOUT,
|
||||
OUTDOOR_LAYOUT,
|
||||
);
|
||||
expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual(
|
||||
STREAMING_SETTINGS,
|
||||
@@ -382,7 +206,6 @@ test.describe("UI settings import/export @medium", () => {
|
||||
test("hides the unknown-group warning when layouts are switched off", async ({
|
||||
frigateApp,
|
||||
}) => {
|
||||
test.skip(frigateApp.isMobile, "Layout import is desktop and tablet only");
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
|
||||
// patio is a layout-only group absent from this server, so the warning
|
||||
@@ -412,39 +235,7 @@ test.describe("UI settings import/export @medium", () => {
|
||||
|
||||
expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual({});
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
|
||||
frigateApp.isMobile ? null : OUTDOOR_LAYOUT,
|
||||
);
|
||||
});
|
||||
|
||||
test("phones refuse layouts and say why @mobile", async ({ frigateApp }) => {
|
||||
test.skip(!frigateApp.isMobile, "Phone-only");
|
||||
|
||||
await frigateApp.goto("/settings?page=uiSettings");
|
||||
await writeIdb(frigateApp.page, { "naturalAspectLayout:admin": false });
|
||||
|
||||
await chooseImportFile(frigateApp.page, importPayload());
|
||||
|
||||
await expect(
|
||||
frigateApp.page.getByText(/aren't imported on phones/),
|
||||
).toBeVisible();
|
||||
|
||||
// the section is still listed, but cannot be switched on
|
||||
await expect(
|
||||
frigateApp.page.getByText("Camera group layouts (2 groups)"),
|
||||
).toBeVisible();
|
||||
await expect(
|
||||
frigateApp.page.locator('[id="Camera group layouts (2 groups)"]'),
|
||||
).toBeDisabled();
|
||||
|
||||
await confirmImport(frigateApp.page);
|
||||
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toBeNull();
|
||||
expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual(
|
||||
STREAMING_SETTINGS,
|
||||
);
|
||||
// a layouts import is what flips this, so it must stay put
|
||||
expect(await readIdb(frigateApp.page, "naturalAspectLayout:admin")).toBe(
|
||||
false,
|
||||
OUTDOOR_LAYOUT,
|
||||
);
|
||||
});
|
||||
|
||||
@@ -534,7 +325,7 @@ test.describe("UI settings import/export @medium", () => {
|
||||
await confirmImport(frigateApp.page);
|
||||
|
||||
expect(await readIdb(frigateApp.page, OUTDOOR_LAYOUT_KEY)).toEqual(
|
||||
frigateApp.isMobile ? null : OUTDOOR_LAYOUT,
|
||||
OUTDOOR_LAYOUT,
|
||||
);
|
||||
expect(await readIdb(frigateApp.page, STREAMING_KEY)).toEqual(
|
||||
STREAMING_SETTINGS,
|
||||
|
||||
@@ -483,7 +483,7 @@ test.describe("System — Health hardware pane @medium", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.installDefaults({
|
||||
config: { models: [{ scene: "default", devices: ["openvino:GPU"] }] },
|
||||
config: { models: [{ scene: "all", devices: ["openvino:GPU"] }] },
|
||||
stats: {
|
||||
...QUIET_STATS,
|
||||
detectors: { "openvino:GPU": { inference_speed: 12.3 } },
|
||||
@@ -500,7 +500,7 @@ test.describe("System — Health hardware pane @medium", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.installDefaults({
|
||||
config: { models: [{ scene: "default", devices: ["hailo"] }] },
|
||||
config: { models: [{ scene: "all", devices: ["hailo"] }] },
|
||||
stats: QUIET_STATS,
|
||||
});
|
||||
await frigateApp.goto("/system#health");
|
||||
@@ -516,7 +516,7 @@ test.describe("System — Health hardware pane @medium", () => {
|
||||
frigateApp,
|
||||
}) => {
|
||||
await frigateApp.installDefaults({
|
||||
config: { models: [{ scene: "default", devices: ["openvino:AUTO"] }] },
|
||||
config: { models: [{ scene: "all", devices: ["openvino:AUTO"] }] },
|
||||
stats: {
|
||||
...QUIET_STATS,
|
||||
detectors: { "openvino:AUTO": { inference_speed: 12 } },
|
||||
@@ -536,7 +536,7 @@ test.describe("System — Health hardware pane @medium", () => {
|
||||
}) => {
|
||||
// the default image runs onnx on the CPU and the probe reports nothing
|
||||
await frigateApp.installDefaults({
|
||||
config: { models: [{ scene: "default", devices: ["onnx"] }] },
|
||||
config: { models: [{ scene: "all", devices: ["onnx"] }] },
|
||||
stats: { ...QUIET_STATS, detectors: { onnx: { inference_speed: 40 } } },
|
||||
});
|
||||
await frigateApp.goto("/system#health");
|
||||
@@ -549,7 +549,7 @@ test.describe("System — Health hardware pane @medium", () => {
|
||||
|
||||
test("detection row warns on slow inference", async ({ frigateApp }) => {
|
||||
await frigateApp.installDefaults({
|
||||
config: { models: [{ scene: "default", devices: ["openvino:GPU"] }] },
|
||||
config: { models: [{ scene: "all", devices: ["openvino:GPU"] }] },
|
||||
stats: {
|
||||
...QUIET_STATS,
|
||||
detectors: { "openvino:GPU": { inference_speed: 60 } },
|
||||
|
||||
@@ -1223,6 +1223,7 @@
|
||||
"desc": "Frigate можа сам адпраўляць push-апавяшчэнні на вашу прыладу, калі працуе ў браўзеры або ўсталяваны як PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Апавяшчэнні недаступныя",
|
||||
"desc": "Вэб-push-апавяшчэнні патрабуюць бяспечнага кантэксту (<code>https://…</code>). Гэта абмежаванне браўзера. Каб карыстацца апавяшчэннямі, адкрывайце Frigate па бяспечным пратаколе.",
|
||||
"descPwa": "У iOS вэб-push-апавяшчэнні даступныя, толькі калі Frigate дададзены на хатні экран. Адкрыйце меню <strong>Абагуліць</strong>, выберыце <strong>На хатні экран</strong>, а потым адкрыйце Frigate праз новы значок, каб зарэгістраваць гэту прыладу для апавяшчэнняў."
|
||||
},
|
||||
@@ -1330,6 +1331,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "Трыгеры",
|
||||
"semanticSearch": {
|
||||
"title": "Семантычны пошук адключаны",
|
||||
"desc": "Каб карыстацца трыгерамі, трэба ўключыць семантычны пошук."
|
||||
},
|
||||
"management": {
|
||||
|
||||
@@ -236,6 +236,8 @@
|
||||
},
|
||||
"lastRefreshed": "Апошняе абнаўленне: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} моцна нагружае CPU праз FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} моцна нагружае CPU дэтэктаваннем ({{detectAvg}}%)",
|
||||
"healthy": "Сістэма спраўная",
|
||||
"reindexingEmbeddings": "Пераіндэксацыя ўбудаванняў (гатова {{processed}}%)",
|
||||
"cameraIsOffline": "{{camera}} па-за сеткай",
|
||||
@@ -279,12 +281,20 @@
|
||||
"notices": {
|
||||
"title": "Заўвагі",
|
||||
"empty": "Ваша ўсталёўка Frigate у парадку",
|
||||
"dismiss": "Схаваць",
|
||||
"openSettings": "Адкрыць налады",
|
||||
"openLink": "Адкрыць спасылку",
|
||||
"noMatches": "Няма заўваг, якія адпавядаюць фільтру",
|
||||
"dismissedTitle": "Схаваныя",
|
||||
"noneDismissed": "Няма схаваных заўваг",
|
||||
"clearDismissed": "Ачысціць схаваныя",
|
||||
"clearDismissedTitle": "Ачысціць схаваныя заўвагі?",
|
||||
"clearDismissedDesc": "Усе схаваныя заўвагі будуць выдалены. Праверкі канфігурацыі і плыняў пакажуцца адразу, а іншыя заўвагі вернуцца пры наступным узнікненні.",
|
||||
"firstSeen_one": "Упершыню {{time}}",
|
||||
"firstSeen_other": "Упершыню {{time}} · {{count}} разу",
|
||||
"dismissedAt": "Схавана {{time}}",
|
||||
"filter": {
|
||||
"showDismissed": "Паказаць схаваныя",
|
||||
"severity": "Узровень важнасці",
|
||||
"error": "Памылка",
|
||||
"warning": "Папярэджанне",
|
||||
|
||||
@@ -1037,6 +1037,7 @@
|
||||
"desc": "Frigate može nativno slati obavijesti na vaš uređaj kada radi u pregledaču ili je instalirana kao PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Obavijesti nedostupne",
|
||||
"desc": "Web obavijesti zahtijevaju sigurni kontekst (<code>https://…</code>). Ovo je ograničenje pregledača. Pristupite Frigate sigurno da biste koristili obavijesti."
|
||||
},
|
||||
"globalSettings": {
|
||||
@@ -1134,6 +1135,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "Pokretači",
|
||||
"semanticSearch": {
|
||||
"title": "Semantička pretraga je onemogućena",
|
||||
"desc": "Semantička pretraga mora biti omogućena da biste koristili izazivače."
|
||||
},
|
||||
"management": {
|
||||
|
||||
@@ -211,6 +211,8 @@
|
||||
},
|
||||
"lastRefreshed": "Posljednje ažuriranje: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} ima visoku upotrebu CPU za FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} ima visoku upotrebu CPU za detekciju ({{detectAvg}}%)",
|
||||
"healthy": "Sistem je zdrav",
|
||||
"reindexingEmbeddings": "Ponovno indeksiranje ugrađenih vjerodajnica ({{processed}}% završeno)",
|
||||
"cameraIsOffline": "{{camera}} je offline",
|
||||
|
||||
@@ -119,9 +119,6 @@
|
||||
"liveFallbackTimeout": {
|
||||
"label": "Temps d'espera per a la reserva del jugador en directe",
|
||||
"desc": "Quan el flux en viu d'alta qualitat d'una càmera no està disponible, torneu al mode d'amplada de banda baixa després d'aquests molts segons. Per defecte: 3."
|
||||
},
|
||||
"naturalAspectLayout": {
|
||||
"label": "Utilitza relació natural d'aspecte"
|
||||
}
|
||||
},
|
||||
"storedLayouts": {
|
||||
@@ -458,8 +455,9 @@
|
||||
},
|
||||
"title": "Notificacions",
|
||||
"notificationUnavailable": {
|
||||
"desc": "Les notificacions push web requereixen un context segur (https://…). Aquesta és una limitació del navegador. Accedeix a Frigate de manera segura per utilitzar les notificacions.",
|
||||
"descPwa": "A iOS, les notificacions push web només estàn disponibles quan Frigate està instalat a la pantalla principal. Obre el menú Compartir, selecciona Afegir a la pantalla, i obre Frigate des del nou icona per registrar les notificacions en aquest dispositiu."
|
||||
"title": "Notificacions no disponibles",
|
||||
"desc": "Les notificacions push web requereixen un context segur (<code>https://…</code>). Aquesta és una limitació del navegador. Accedeix a Frigate de manera segura per utilitzar les notificacions.",
|
||||
"descPwa": "A iOS, les notificacions push web només estàn disponibles quan Frigate està instalat a la pantalla principal. Obre el menú <strong>Compartir</strong> , selecciona <strong>Afegir a la pantalla</strong>, i obre Frigate des del nou icona per registrar les notificacions en aquest dispositiu."
|
||||
},
|
||||
"unsavedChanges": "Canvis de notificació no desats",
|
||||
"globalSettings": {
|
||||
@@ -883,7 +881,8 @@
|
||||
},
|
||||
"addTrigger": "Afegir disaprador",
|
||||
"semanticSearch": {
|
||||
"desc": "La cerca semàntica ha d'estar activada per a utilitzar els activadors."
|
||||
"desc": "La cerca semàntica ha d'estar activada per a utilitzar els activadors.",
|
||||
"title": "La cerca semàntica està desactivada"
|
||||
},
|
||||
"wizard": {
|
||||
"title": "Crea un activador",
|
||||
@@ -1545,9 +1544,7 @@
|
||||
"preset-record-generic-audio-aac": "Enregistra (Genèric + Àudio a AAC)",
|
||||
"preset-record-mjpeg": "Registre - Càmeres MJPEG",
|
||||
"preset-record-jpeg": "Registre - Càmeres JPEG",
|
||||
"preset-record-ubiquiti": "Registre - Càmeres Ubiquiti",
|
||||
"preset-apple-silicon-h265": "Apple Silicon (H.265)",
|
||||
"preset-apple-silicon-h264": "Apple Silicon (H.264)"
|
||||
"preset-record-ubiquiti": "Registre - Càmeres Ubiquiti"
|
||||
},
|
||||
"sameAsRecord": "Igual que els arguments de sortida del registre"
|
||||
},
|
||||
|
||||
@@ -239,15 +239,15 @@
|
||||
"reindexingEmbeddings": "Reindexant vectors ({{processed}}% completat)",
|
||||
"healthy": "El sistema és saludable",
|
||||
"cameraIsOffline": "{{camera}} està fora de línia",
|
||||
"ffmpegHighCpuUsage": "{{camera}} te un ús elevat de CPU per FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} te un ús elevat de CPU per la detecció ({{detectAvg}}%)",
|
||||
"detectIsVerySlow": "{{detect}} és molt lent ({{speed}} ms)",
|
||||
"detectIsSlow": "{{detect}} és lent ({{speed}} ms)",
|
||||
"debugReplayActive": "La sessió de repetició de depuració està activa",
|
||||
"cameraSkippedDetections": "{{camera}} està ometent la detecció en {{pct}}% de fotogrames",
|
||||
"systemNotices_one": "{{count}} avís del sistema",
|
||||
"systemNotices_other": "{{count}} avisos del sistema",
|
||||
"retentionUnmet": "Els enregistraments s'estan suprimint abans que acabi el seu període de retenció a l'espai lliure",
|
||||
"moreMessages_other": "+{{count}}",
|
||||
"moreMessages_one": "+{{count}}"
|
||||
"retentionUnmet": "Els enregistraments s'estan suprimint abans que acabi el seu període de retenció a l'espai lliure"
|
||||
},
|
||||
"enrichments": {
|
||||
"title": "Anàlisi avançada",
|
||||
@@ -281,17 +281,24 @@
|
||||
"notices": {
|
||||
"title": "Avís",
|
||||
"empty": "La instal·lació de Frigate és saludable",
|
||||
"dismiss": "Descarta",
|
||||
"openSettings": "Obre la configuració",
|
||||
"openLink": "Obre l'enllaç",
|
||||
"noMatches": "No hi ha avisos que coincideixin amb el filtre",
|
||||
"dismissedTitle": "Descartat",
|
||||
"noneDismissed": "No hi ha avisos descartats",
|
||||
"clearDismissed": "Neteja descartada",
|
||||
"clearDismissedTitle": "Voleu netejar els avisos descartats?",
|
||||
"clearDismissedDesc": "S'elimina cada avís acomiadat. Les comprovacions de configuració i flux es mostren de nou immediatament, i altres avisos tornen la propera vegada que succeeixin.",
|
||||
"firstSeen_one": "{{time}} vist per primera vegada",
|
||||
"firstSeen_other": "{{time}} · {{count}} vegades",
|
||||
"dismissedAt": "S'ha suprimit {{time}}",
|
||||
"filter": {
|
||||
"showDismissed": "Mostra descartat",
|
||||
"severity": "Severitat",
|
||||
"warning": "Avís",
|
||||
"error": "Error",
|
||||
"info": "Info",
|
||||
"showHidden": "Mostra els ocults"
|
||||
"info": "Info"
|
||||
},
|
||||
"kinds": {
|
||||
"detector_stuck": "S'ha reiniciat el detector {{detector}} després que deixés de respondre",
|
||||
@@ -300,27 +307,12 @@
|
||||
"shm_too_low": "L'assignació /dev/shm ({{total}} MB) s'hauria d'augmentar a com a mínim {{min}} MB",
|
||||
"failed_login_one": "Error en l'intent d'inici de sessió de {{user}}",
|
||||
"failed_login_other": "Intents d'inici de sessió fallits per {{user}}",
|
||||
"update_available": "Frigate {{version}} està disponible",
|
||||
"ffmpeg_high_cpu": "L'ús de la CPU FFmpeg és alt ({{cpu}}% mitjana)",
|
||||
"detect_high_cpu": "L'ús de la CPU de detecció és alt ({{cpu}}% mitjana)"
|
||||
"update_available": "Frigate {{version}} està disponible"
|
||||
},
|
||||
"streamPrefix": "Flux {{index}}: {{message}}",
|
||||
"streamPrefixRestream": "Flux {{index}} (via go2rtc): {{message}}",
|
||||
"streamProbeFailed": "No s'ha pogut provar el flux {{index}}: {{error}}",
|
||||
"cameraProbeFailed": "No s'han pogut explorar els fluxos: {{error}}",
|
||||
"acknowledge": "Agraïment",
|
||||
"acknowledgeHint": "Amaga fins que això torni a passar",
|
||||
"mute": "Silenciar",
|
||||
"muteHint": "No ho mostris mai més",
|
||||
"unmute": "No silenciis",
|
||||
"showAgain": "Torna a mostrar",
|
||||
"hiddenTitle": "Ocultar",
|
||||
"noneHidden": "No hi ha avisos ocults",
|
||||
"showAll": "Mostra-ho tot de nou",
|
||||
"showAllTitle": "Voleu mostrar tots els avisos ocults?",
|
||||
"showAllDesc": "Cada avís reconegut i silenciat torna a la llista d'avisos, incloent-hi les comprovacions de configuració i flux.",
|
||||
"acknowledgedAt": "Reconegut {{time}}",
|
||||
"mutedAt": "Mutat {{time}}"
|
||||
"cameraProbeFailed": "No s'han pogut explorar els fluxos: {{error}}"
|
||||
},
|
||||
"hardware": {
|
||||
"title": "Maquinari",
|
||||
|
||||
@@ -374,6 +374,7 @@
|
||||
"desc": "Frigate může nativně odesílat push notifikace do vašeho zařízení, pokud běží v prohlížeči nebo je nainstalován jako PWA (progresivní webová aplikace)."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Notifikace Nedostupné",
|
||||
"desc": "Webové push notifikace vyžadují zabezpečený kontext (<code>https://…</code>). Jedná se o omezení prohlížeče. Pro použití notifikací přistupujte k Frigate přes zabezpečené připojení."
|
||||
},
|
||||
"cameras": {
|
||||
|
||||
@@ -50,7 +50,9 @@
|
||||
"healthy": "Systém je zdravý",
|
||||
"reindexingEmbeddings": "Přeindexování vektorů ({{processed}} % dokončeno)",
|
||||
"detectIsSlow": "{{detect}} je pomalé ({{speed}} ms)",
|
||||
"detectIsVerySlow": "{{detect}} je velmi pomalé ({{speed}} ms)"
|
||||
"detectIsVerySlow": "{{detect}} je velmi pomalé ({{speed}} ms)",
|
||||
"detectHighCpuUsage": "{{camera}} má vysoké využití CPU detekcemi ({{detectAvg}} %)",
|
||||
"ffmpegHighCpuUsage": "{{camera}} má vyské využití CPU FFmpegem ({{ffmpegAvg}}%)"
|
||||
},
|
||||
"enrichments": {
|
||||
"embeddings": {
|
||||
|
||||
@@ -346,71 +346,5 @@
|
||||
"bluegrass": "Bluegrass",
|
||||
"folk_music": "Folkemusik",
|
||||
"echo": "Ekko",
|
||||
"pulse": "Puls",
|
||||
"funk": "Funk",
|
||||
"middle_eastern_music": "Mellemøstlig musik",
|
||||
"carnatic_music": "Karnatisk musik",
|
||||
"music_of_bollywood": "Bollywood musik",
|
||||
"dental_drill's_drill": "Tandlægebor",
|
||||
"medium_engine": "Mellemstor motor",
|
||||
"heavy_engine": "Kraftig motor",
|
||||
"engine_knocking": "Motorbanken",
|
||||
"engine_starting": "Motor, der starter",
|
||||
"idling": "Tomgang",
|
||||
"accelerating": "Acceleration",
|
||||
"ding-dong": "Ding-dong",
|
||||
"sliding_door": "Skydedør",
|
||||
"tap": "let bank",
|
||||
"cupboard_open_or_close": "Skab åbnes eller lukkes",
|
||||
"drawer_open_or_close": "Skuffe åbnes eller lukkes",
|
||||
"chopping": "Hugning",
|
||||
"frying": "Stegning",
|
||||
"microwave_oven": "Mikrobølgeovn",
|
||||
"water_tap": "Vandhane",
|
||||
"toilet_flush": "Toiletskylning",
|
||||
"electric_toothbrush": "Elektrisk tandbørste",
|
||||
"vacuum_cleaner": "Støvsuger",
|
||||
"keys_jangling": "Nøgleraslen",
|
||||
"electric_shaver": "Elektrisk barbermaskine",
|
||||
"shuffling_cards": "Kortblanding",
|
||||
"typing": "Skrivning (på tastatur)",
|
||||
"computer_keyboard": "Computertastatur",
|
||||
"writing": "Skrivning",
|
||||
"telephone_bell_ringing": "Telefonringen",
|
||||
"telephone_dialing": "Telefonopkald",
|
||||
"dial_tone": "Summetone",
|
||||
"busy_signal": "Optaget-signal",
|
||||
"alarm_clock": "Vækkeur",
|
||||
"civil_defense_siren": "Luftsirene",
|
||||
"buzzer": "Summer",
|
||||
"smoke_detector": "Røgalarm",
|
||||
"fire_alarm": "Brandalarm",
|
||||
"steam_whistle": "Dampfløjte",
|
||||
"mechanisms": "Mekanismer",
|
||||
"ratchet": "Skralde",
|
||||
"tick": "Tik",
|
||||
"tick-tock": "Tik-tak",
|
||||
"gears": "Tandhjul",
|
||||
"pulleys": "Trisser",
|
||||
"sewing_machine": "Symaskine",
|
||||
"mechanical_fan": "Mekanisk blæser",
|
||||
"air_conditioning": "Air Condition",
|
||||
"cash_register": "Kasseapparat",
|
||||
"single-lens_reflex_camera": "Spejlreflekskamera",
|
||||
"jackhammer": "Trykkluftbor",
|
||||
"sawing": "Savning",
|
||||
"filing": "Filning",
|
||||
"sanding": "Slibning",
|
||||
"power_tool": "Elværktøj",
|
||||
"gunshot": "Skud",
|
||||
"machine_gun": "Maskingevær",
|
||||
"fusillade": "Salve",
|
||||
"artillery_fire": "Artilleriild",
|
||||
"cap_gun": "Knaldpistol",
|
||||
"firecracker": "Kanonslag",
|
||||
"burst": "Sprang",
|
||||
"eruption": "Udbrud",
|
||||
"boom": "Bum",
|
||||
"wood": "Træ",
|
||||
"chop": "Hugge"
|
||||
"pulse": "Puls"
|
||||
}
|
||||
|
||||
@@ -580,6 +580,7 @@
|
||||
},
|
||||
"title": "Benachrichtigungen",
|
||||
"notificationUnavailable": {
|
||||
"title": "Benachrichtigungen nicht verfügbar",
|
||||
"desc": "Web Push Benachrichtigungen erfordern einen sicheren Kontext (<code>https://…</code>). Das ist eine Vorgabe des Browsers. Greife auf Frigate gesichert zu um Benachrichtigungen zu nutzen.",
|
||||
"descPwa": "Unter iOS sind Web-Push-Benachrichtigungen nur verfügbar, wenn Frigate auf Ihrem Startbildschirm installiert ist. Öffnen Sie das Menü <strong>Teilen</strong>, wählen Sie <strong>Zum Startbildschirm hinzufügen</strong> und öffnen Sie Frigate über das neue Symbol, um dieses Gerät für Benachrichtigungen zu registrieren."
|
||||
},
|
||||
@@ -838,6 +839,7 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"title": "Semantische Suche ist deaktiviert",
|
||||
"desc": "Semantische Suche muss aktiviert sein um Auslöser nutzen zu können."
|
||||
},
|
||||
"wizard": {
|
||||
|
||||
@@ -254,6 +254,8 @@
|
||||
},
|
||||
"stats": {
|
||||
"healthy": "Das System läuft problemlos",
|
||||
"ffmpegHighCpuUsage": "{{camera}} hat eine hohe FFmpeg CPU Auslastung ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} hat eine hohe CPU Auslastung bei der Erkennung ({{detectAvg}}%)",
|
||||
"reindexingEmbeddings": "Neuindizierung von Einbettungen ({{processed}}% erledigt)",
|
||||
"detectIsSlow": "{{detect}} ist langsam ({{speed}} ms)",
|
||||
"detectIsVerySlow": "{{detect}} ist sehr langsam ({{speed}} ms)",
|
||||
|
||||
@@ -131,7 +131,6 @@
|
||||
"close": "Close",
|
||||
"expand": "Expand",
|
||||
"collapse": "Collapse",
|
||||
"clear": "Clear",
|
||||
"copy": "Copy",
|
||||
"copiedToClipboard": "Copied to clipboard",
|
||||
"back": "Back",
|
||||
|
||||
@@ -100,7 +100,7 @@
|
||||
},
|
||||
"scene": {
|
||||
"label": "Detect scene",
|
||||
"description": "The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'default' run the model configured with a scene of 'default'."
|
||||
"description": "The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'all' run the model configured with a scene of 'all'."
|
||||
},
|
||||
"fps": {
|
||||
"label": "Detect FPS",
|
||||
|
||||
@@ -277,10 +277,10 @@
|
||||
},
|
||||
"models": {
|
||||
"label": "Detection models",
|
||||
"description": "Object detection models and the hardware each one runs on. Cameras pick a model by matching their detect.scene against a model's scene, falling back to the 'default' model.",
|
||||
"description": "Object detection models and the hardware each one runs on. Cameras pick a model by matching their detect.scene against a model's scene.",
|
||||
"scene": {
|
||||
"label": "Model scene",
|
||||
"description": "A name for the camera environment this model is used for, such as 'thermal'. Cameras select a model by setting detect.scene to a matching value, and the 'default' model is used by any camera that does not set one."
|
||||
"description": "The camera environment this model is used for. Cameras select a model by setting detect.scene to a matching value, and 'all' is used by any camera that does not set one."
|
||||
},
|
||||
"devices": {
|
||||
"label": "Detection hardware",
|
||||
@@ -468,7 +468,7 @@
|
||||
},
|
||||
"scene": {
|
||||
"label": "Detect scene",
|
||||
"description": "The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'default' run the model configured with a scene of 'default'."
|
||||
"description": "The environment this camera looks at, used to pick which of the configured models runs on it. Cameras left on 'all' run the model configured with a scene of 'all'."
|
||||
},
|
||||
"fps": {
|
||||
"label": "Detect FPS",
|
||||
|
||||
@@ -33,8 +33,6 @@
|
||||
"dimensionMustBeEven": "Must be an even number."
|
||||
},
|
||||
"models": {
|
||||
"defaultRequired": "One model must use the default scene. Without it, any camera that does not choose a scene has no model to fall back to.",
|
||||
"sceneDuplicate": "Each model must use a different scene.",
|
||||
"sameModel": "The {{scene}} and {{other}} models use the same model file. Running one model under several scenes only splits the detection work across separate detectors, which is slower than one model with all of the hardware listed under it."
|
||||
"defaultRequired": "One model must use a scene of 'All cameras'. Without it, any camera that does not choose a scene has no model to fall back to."
|
||||
}
|
||||
}
|
||||
|
||||
@@ -167,11 +167,6 @@
|
||||
"label": "Always Show Camera Names",
|
||||
"desc": "Always show the camera names in a chip in the multi-camera live view dashboard."
|
||||
},
|
||||
"naturalAspectLayout": {
|
||||
"label": "Use Natural Aspect Ratios",
|
||||
"desc": "On camera group live view dashboards, size each tile to its camera's own natural aspect ratio. When disabled, cameras are snapped to a standard wide, landscape, or tall tile shape.",
|
||||
"descNote": "Toggling this setting on or off will clear the stored layout for all camera group live dashboards. Manual reconfiguration will be required."
|
||||
},
|
||||
"liveFallbackTimeout": {
|
||||
"label": "Live Player Fallback Timeout",
|
||||
"desc": "When a camera's high quality live stream is unavailable, fall back to low bandwidth mode after this many seconds. Default: 3."
|
||||
@@ -180,14 +175,12 @@
|
||||
"storedLayouts": {
|
||||
"title": "Stored Layouts",
|
||||
"desc": "The layout of cameras in a camera group can be dragged/resized. The positions are stored in your browser's local storage.",
|
||||
"clearAll": "Clear All Layouts",
|
||||
"clearConfirm": "This will clear the stored layout for every camera group in this browser. This cannot be undone."
|
||||
"clearAll": "Clear All Layouts"
|
||||
},
|
||||
"cameraGroupStreaming": {
|
||||
"title": "Camera Group Streaming Settings",
|
||||
"desc": "Streaming settings for each camera group are stored in your browser's local storage.",
|
||||
"clearAll": "Clear All Streaming Settings",
|
||||
"clearConfirm": "This will clear the streaming settings for every camera group in this browser. This cannot be undone."
|
||||
"clearAll": "Clear All Streaming Settings"
|
||||
},
|
||||
"backupRestore": {
|
||||
"title": "Backup & Restore",
|
||||
@@ -202,9 +195,6 @@
|
||||
"desc": "Choose what to apply from this file. Frigate will reload when the import finishes.",
|
||||
"exportedFrom": "Exported {{date}} from Frigate config version {{version}}",
|
||||
"layouts_one": "Camera group layouts ({{count}} group)",
|
||||
"layoutsPhone": "Camera group layouts aren't imported on phones, which always use the standard grid.",
|
||||
"layoutsModeOn": "These layouts use camera aspect ratio tile sizing, so importing them will also turn on \"Use Natural Aspect Ratios\".",
|
||||
"layoutsModeOff": "These layouts use standard tile sizing, so importing them will also turn off \"Use Natural Aspect Ratios\".",
|
||||
"layouts_other": "Camera group layouts ({{count}} groups)",
|
||||
"streaming_one": "Streaming settings ({{count}} camera)",
|
||||
"streaming_other": "Streaming settings ({{count}} cameras)",
|
||||
@@ -1986,7 +1976,7 @@
|
||||
"fpsGreaterThanFive": "Setting the detect FPS higher than 5 is not recommended. Higher values may cause performance issues and will not provide any benefit.",
|
||||
"disabled": "Object detection is disabled. Snapshots, review items, and enrichments such as face recognition, license plate recognition, and Generative AI will not function.",
|
||||
"runtimeDisabled": "Object detection is enabled in your config, but it is currently turned off for this camera. Snapshots, review items, and enrichments such as face recognition, license plate recognition, and Generative AI will not function until it is turned back on from the camera's live view, or until the active profile stops disabling it.",
|
||||
"sceneWithoutModel": "No detection model is configured for this scene, so this camera falls back to the Default model. Add a model for this scene to give the camera its own.",
|
||||
"sceneWithoutModel": "No detection model is configured for this scene, so this camera falls back to the model with a scene of 'All cameras'. Add a model for this scene to give the camera its own.",
|
||||
"resolutionShouldBeMultipleOfFour": "For best results, detect width and height should be multiples of 4. Other even values may produce visual artifacts or slight distortion in the detect stream.",
|
||||
"aspectRatioMismatch": "The width and height you've entered don't match the aspect ratio of your current detect resolution. This may produce a stretched or distorted image.",
|
||||
"maxFramesSet": "Setting max frames overrides default behavior and disables stationary object tracking. There are very few situations where this is needed, use with caution.",
|
||||
@@ -2036,17 +2026,20 @@
|
||||
},
|
||||
"detectionModels": {
|
||||
"title": "Detection models",
|
||||
"description": "Configure the object detection models and the hardware each one runs on. Add a model for a scene only when some cameras need a differently trained model, such as thermal cameras. Cameras choose a model by their scene in the camera's detect settings.",
|
||||
"description": "Configure the object detection models and the hardware each one runs on. Cameras choose a model by their scene in the camera's detect settings.",
|
||||
"addModel": "Add model",
|
||||
"cameras_one": "{{count}} camera",
|
||||
"cameras_other": "{{count}} cameras",
|
||||
"scene": {
|
||||
"label": "Scene",
|
||||
"placeholder": "thermal",
|
||||
"description": "A name for the cameras this model is for. Cameras pick a model by setting the same scene in their detect settings, and the Default model is used by any camera that does not set one. Use scenes to run different models, not to split one model across hardware, since models that use the same model file are combined."
|
||||
"description": "The environment this model is for. Cameras pick a model by setting the same scene in their detect settings, and the model with a scene of all is used by any camera that does not set one."
|
||||
},
|
||||
"scenes": {
|
||||
"default": "Default"
|
||||
"all": "All cameras",
|
||||
"indoor": "Indoor",
|
||||
"outdoor": "Outdoor",
|
||||
"indoor_thermal": "Indoor thermal",
|
||||
"outdoor_thermal": "Outdoor thermal"
|
||||
},
|
||||
"hardware": {
|
||||
"label": "Hardware",
|
||||
@@ -2060,7 +2053,7 @@
|
||||
"unrecognized": "This model is configured for hardware that was not found on this system: {{devices}}",
|
||||
"description": "The hardware this model runs its detection on.",
|
||||
"detectorCountDescription": "How many detection processes to run on this hardware. More detectors keep up with more cameras, at the cost of extra device memory.",
|
||||
"unitsDescription": "Each unit runs its own detection process. A unit that can't be shared, such as a Coral, can only be used by one model."
|
||||
"unitsDescription": "Each unit runs its own detection process. A unit already used by another model can not be selected."
|
||||
},
|
||||
"tabs": {
|
||||
"plus": "Frigate+",
|
||||
|
||||
@@ -137,15 +137,6 @@
|
||||
"partial": "Se iniciaron {{successful}} de {{total}} exportaciones. Fallidas: {{failedItems}}",
|
||||
"failed": "No se pudieron iniciar {{total}} exportaciones. Fallidas: {{failedItems}}"
|
||||
}
|
||||
},
|
||||
"stream": {
|
||||
"label": "Calidad",
|
||||
"auto": "Auto",
|
||||
"main": "Original",
|
||||
"sub": "Bajo",
|
||||
"autoDesc": "Usa el stream princial y vuelve a la calidad baja del sub-stream si la principal no está disponible.",
|
||||
"mainDesc": "Exporta sólo la calidad original del stream principal. Los tiempos dónde el stream principal no esté disponible estarán faltantes.",
|
||||
"subDesc": "Exporta sólo la calidad inferior del sub-stream. Los tiempos dónde el sub-steam no está disponible faltarán."
|
||||
}
|
||||
},
|
||||
"streaming": {
|
||||
@@ -191,8 +182,7 @@
|
||||
"export": "Exportar",
|
||||
"markAsReviewed": "Marcar como revisado",
|
||||
"deleteNow": "Eliminar ahora",
|
||||
"markAsUnreviewed": "Marcar como no revisado",
|
||||
"generateDescription": "Generar descripción"
|
||||
"markAsUnreviewed": "Marcar como no revisado"
|
||||
},
|
||||
"shareTimestamp": {
|
||||
"description": "Comparta una URL con marca de tiempo de la posición actual del reproductor o elija una marca de tiempo personalizada. Tenga en cuenta que esta no es una URL pública para compartir y solo es accesible para los usuarios que tienen acceso a Frigate y a esta cámara.",
|
||||
@@ -201,11 +191,6 @@
|
||||
"custom": "Marca de tiempo personalizada",
|
||||
"button": "Compartir URL de la marca de tiempo",
|
||||
"shareTitle": "Marca de tiempo de revisión de Frigate: {{camera}}"
|
||||
},
|
||||
"genaiDescription": {
|
||||
"toast": {
|
||||
"error": "Falló al pedir descripción: {{error}}"
|
||||
}
|
||||
}
|
||||
},
|
||||
"imagePicker": {
|
||||
|
||||
@@ -35,25 +35,10 @@
|
||||
"submittedFrigatePlus": "Fotograma enviado correctamente a Frigate+"
|
||||
},
|
||||
"error": {
|
||||
"submitFrigatePlusFailed": "Error al enviar el fotograma a Frigate+",
|
||||
"playRecordingsFailed": "Falló al reproducir grabaciones(error{{code}}:{{message}})"
|
||||
"submitFrigatePlusFailed": "Error al enviar el fotograma a Frigate+"
|
||||
}
|
||||
},
|
||||
"livePlayerRequiredIOSVersion": "Se requiere iOS 17.1 o superior para este tipo de transmisión en vivo.",
|
||||
"noRecordingsFoundForThisTime": "No se encontraron grabaciones para este momento",
|
||||
"cameraOff": "La cámara está apagada",
|
||||
"quality": {
|
||||
"auto": "Auto",
|
||||
"autoLow": "Reproduciendo con baja calidad (ancho de banda limitado)",
|
||||
"autoLowCodec": "Reproduciendo con baja calidad (Este navegador no soporta la calidad original)",
|
||||
"autoLowSaveData": "Reproduciendo con baja calidad (ahorro de datos)",
|
||||
"main": "Original",
|
||||
"sub": "Baja",
|
||||
"notSupportedBrowser": "No soportado por este navegador",
|
||||
"label": "Calidad",
|
||||
"noAudio": "Sin audio",
|
||||
"audioRate": "{{rate}}kHz audio",
|
||||
"audioCodecRate": "{{codec}}{{rate}}kHz",
|
||||
"noRecordings": "Sin grabaciones en este rango de tiempo"
|
||||
}
|
||||
"cameraOff": "La cámara está apagada"
|
||||
}
|
||||
|
||||
@@ -496,9 +496,6 @@
|
||||
"annotation_offset": {
|
||||
"label": "Desplazamiento de anotaciones",
|
||||
"description": "Milisegundos para desplazar las anotaciones de detección y alinear mejor los cuadros delimitadores de la línea de tiempo con las grabaciones; puede ser positivo o negativo."
|
||||
},
|
||||
"scene": {
|
||||
"label": "Detectar escena"
|
||||
}
|
||||
},
|
||||
"record": {
|
||||
@@ -602,19 +599,6 @@
|
||||
"enabled_in_config": {
|
||||
"label": "Estado de grabación original",
|
||||
"description": "Indica si la grabación estaba habilitada en la configuración estática original."
|
||||
},
|
||||
"sub": {
|
||||
"continuous": {
|
||||
"days": {
|
||||
"label": "Días de retención",
|
||||
"description": "Días a retener las grabaciones."
|
||||
}
|
||||
},
|
||||
"motion": {
|
||||
"days": {
|
||||
"label": "Días de retención"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"ui": {
|
||||
@@ -751,9 +735,6 @@
|
||||
"order": {
|
||||
"label": "Posición",
|
||||
"description": "Posición numérica que controla el orden de la cámara en el diseño de Birdseye."
|
||||
},
|
||||
"modes": {
|
||||
"label": "Tipos de actividad"
|
||||
}
|
||||
},
|
||||
"ffmpeg": {
|
||||
|
||||
@@ -711,9 +711,6 @@
|
||||
"annotation_offset": {
|
||||
"label": "Desplazamiento de anotaciones",
|
||||
"description": "Milisegundos para desplazar las anotaciones de detección y alinear mejor los cuadros delimitadores de la línea de tiempo con las grabaciones; puede ser positivo o negativo."
|
||||
},
|
||||
"scene": {
|
||||
"label": "Detectar escena"
|
||||
}
|
||||
},
|
||||
"record": {
|
||||
@@ -817,20 +814,7 @@
|
||||
"label": "Estado de grabación original",
|
||||
"description": "Indica si la grabación estaba habilitada en la configuración estática original."
|
||||
},
|
||||
"description": "Ajustes de grabación y retención aplicados a las cámaras salvo que se sobrescriban por cámara.",
|
||||
"sub": {
|
||||
"continuous": {
|
||||
"days": {
|
||||
"label": "Días de retención",
|
||||
"description": "Días a retener las grabaciones."
|
||||
}
|
||||
},
|
||||
"motion": {
|
||||
"days": {
|
||||
"label": "Días de retención"
|
||||
}
|
||||
}
|
||||
}
|
||||
"description": "Ajustes de grabación y retención aplicados a las cámaras salvo que se sobrescriban por cámara."
|
||||
},
|
||||
"camera_ui": {
|
||||
"dashboard": {
|
||||
@@ -1054,9 +1038,6 @@
|
||||
"idle_heartbeat_fps": {
|
||||
"label": "FPS de latido en reposo",
|
||||
"description": "Fotogramas por segundo para reenviar el último fotograma compuesto de Birdseye en reposo; establécelo en 0 para deshabilitarlo."
|
||||
},
|
||||
"modes": {
|
||||
"label": "Tipos de actividad"
|
||||
}
|
||||
},
|
||||
"ffmpeg": {
|
||||
|
||||
@@ -578,6 +578,7 @@
|
||||
"desc": "Frigate puede enviar notificaciones push a tu dispositivo de forma nativa cuando se ejecuta en el navegador o está instalado como una PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Notificaciones no disponibles",
|
||||
"desc": "Las notificaciones push web requieren un contexto seguro (<code>https://…</code>). Esto es una limitación del navegador. Accede a Frigate de forma segura para usar las notificaciones.",
|
||||
"descPwa": "En iOS, las notificaciones push web solo están disponibles cuando Frigate está instalado en la pantalla de inicio. Abre el menú <strong>Compartir</strong>, selecciona <strong>Añadir a la pantalla de inicio</strong> y, a continuación, abre Frigate desde el nuevo icono para registrar este dispositivo para las notificaciones."
|
||||
},
|
||||
@@ -829,6 +830,7 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"title": "Búsqueda semántica desactivada",
|
||||
"desc": "Búsqueda semántica debe estar activada para usar Disparadores."
|
||||
},
|
||||
"toast": {
|
||||
|
||||
@@ -254,6 +254,8 @@
|
||||
"averageInf": "Tiempo promedio de inferencia"
|
||||
},
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} tiene un uso elevado de CPU por FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} tiene un uso elevado de CPU por detección ({{detectAvg}}%)",
|
||||
"healthy": "El sistema está saludable",
|
||||
"reindexingEmbeddings": "Reindexando empotrados ({{processed}}% completado)",
|
||||
"detectIsSlow": "{{detect}} es lento ({{speed}} ms)",
|
||||
|
||||
@@ -21,12 +21,7 @@
|
||||
"lowBandwidthMode": "Väikese ribalaiusega režiim",
|
||||
"twoWayTalk": {
|
||||
"enable": "Lülita kahepoolne kõneside sisse",
|
||||
"disable": "Lülita kahepoolne kõneside välja",
|
||||
"requiresWebRTC": "Kahepoolne suhtlus eeldab WebRTC kasutamist, aga see poel saadaval",
|
||||
"error": {
|
||||
"microphone": "Kahepoolsel suhtlusel puudub ligipääs sinu mikrofonile",
|
||||
"refused": "Kahepoolse suhtluse käivitamine ei õnnestunud. Lisateavet leiad veebibrauseri konsoolist."
|
||||
}
|
||||
"disable": "Lülita kahepoolne kõneside välja"
|
||||
},
|
||||
"cameraAudio": {
|
||||
"enable": "Lülita kaamera heli sisse",
|
||||
@@ -117,36 +112,10 @@
|
||||
"title": "Voogedastus",
|
||||
"lowBandwidth": {
|
||||
"resetStream": "Lähtesta voogedastus",
|
||||
"tips": "Reaalaja pilt on puhverdamise või voogedastuse vigade tõttu madala ribalaiusega režiimis.",
|
||||
"force": {
|
||||
"label": "Kasuta sundkorras väikese ribalaiusega režiimi",
|
||||
"desc": "Valitud voogedastuse asemel esita sisu alati Frigate'i sisseehitatud väikese ribalaiusega voogedastusena. Toimib igasuguste ühendustega, aga pildikvaliteet on kehvem ning heliriba pole kasutusel."
|
||||
}
|
||||
"tips": "Reaalaja pilt on puhverdamise või voogedastuse vigade tõttu madala ribalaiusega režiimis."
|
||||
},
|
||||
"debug": {
|
||||
"picker": "Voogedastuse osa valik pole silumisrežiimis saadaval. Silumisvaade kasutab alati voogedastust, millele on määratud tuvastamisroll.",
|
||||
"technology": "Voogedastuse tehnoloogia valik pole silumisrežiimis saadaval."
|
||||
},
|
||||
"mode": "Voogedastuse tehnoloogia",
|
||||
"technology": {
|
||||
"description": "Vali eelistatud voogedastuse tehnoloogia. Taasesituse ja võrguvigade puhul võib Frigate tagavaravariandina kasutada väikese ribalaiusega režiimi.",
|
||||
"name": {
|
||||
"mse": "MSE",
|
||||
"webrtc": "WebRTC",
|
||||
"jsmpeg": "JSMpeg"
|
||||
},
|
||||
"tips": {
|
||||
"mse": "Soovitatud vaikimisi väärtus, millel on lai ühilduvus ja sujuv taasesitus",
|
||||
"webrtc": "Vajab täiendavat seadistust ja pole igas seadmes toetatud"
|
||||
},
|
||||
"unavailable": {
|
||||
"browser": "Sinu veebibrauseris puudub WebRTC tugi.",
|
||||
"not-configured": "WebRTC pole seadistatud. Seadista go2rtc webrtc kandidaadid või ice_server teenused.",
|
||||
"unreachable": "WebRTC ühendamine ei õnnestunud. Kontrolli, et port 8555 on kättesaadav ja STUN/TURN-serveri seadistus on õige.",
|
||||
"video-codec": "Selles veebibrauseris puudub WebRTC jaoks antud voogedastuse videokoodeki tugi.",
|
||||
"audio-codec": "WebRTC ei toeta selle voogedastuse helikoodekit. Kodeeri go2rtc abil opus või G.711 vormingusse.",
|
||||
"checking": "Kontrollin WebRTC saadavust…"
|
||||
}
|
||||
"picker": "Voogedastuse osa valik pole silumisrežiimis saadaval. Silumisvaade kasutab alati voogedastust, millele on määratud tuvastamisroll."
|
||||
}
|
||||
},
|
||||
"notifications": "Teavitused",
|
||||
|
||||
@@ -1102,6 +1102,7 @@
|
||||
"desc": "Frigate میتواند بهصورت بومی وقتی در مرورگر اجرا میشود یا بهعنوان PWA نصب شده است، اعلانهای پوش را به دستگاه شما ارسال کند."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "اعلانها در دسترس نیستند",
|
||||
"desc": "اعلانهای پوش وب نیاز به یک بستر امن دارند ( <code>https://… </code>). این محدودیت مرورگر است. برای استفاده از اعلانها، بهصورت امن به Frigate دسترسی پیدا کنید.",
|
||||
"descPwa": "در iOS، اعلانهای وب پوش فقط زمانی در دسترس هستند که فریگیت روی صفحه اصلی شما نصب شده باشد. منوی <strong>اشتراکگذاری</strong> را باز کنید، <strong>افزودن به صفحه اصلی</strong> را انتخاب کنید، سپس فریگیت را از آیکون جدید باز کنید تا این دستگاه برای اعلانها ثبت شود."
|
||||
},
|
||||
@@ -1209,6 +1210,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "تریگرها",
|
||||
"semanticSearch": {
|
||||
"title": "جستجوی معنایی غیرفعال است",
|
||||
"desc": "برای استفاده از تریگرها باید جستجوی معنایی فعال باشد."
|
||||
},
|
||||
"management": {
|
||||
|
||||
@@ -226,6 +226,8 @@
|
||||
}
|
||||
},
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} استفادهٔ CPU بالایی برای FFmpeg دارد ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} استفادهٔ CPU بالایی برای تشخیص دارد ({{detectAvg}}%)",
|
||||
"reindexingEmbeddings": "بازتولید نمایهٔ embeddingها ({{processed}}% تکمیل شده)",
|
||||
"cameraIsOffline": "{{camera}} آفلاین است",
|
||||
"detectIsVerySlow": "{{detect}} بسیار کند است ({{speed}} ms)",
|
||||
|
||||
@@ -181,6 +181,7 @@
|
||||
"desc": "Frigate peut envoyer nativement des notifications push à votre appareil lorsqu'il est exécuté dans le navigateur ou installé en tant que PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Notifications indisponibles",
|
||||
"desc": "Les notifications push Web nécessitent un contexte sécurisé (<code>https://…</code>). Il s'agit d'une limitation du navigateur. Accédez à Frigate en toute sécurité pour utiliser les notifications."
|
||||
},
|
||||
"globalSettings": {
|
||||
@@ -796,6 +797,7 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"title": "La recherche sémantique est désactivée",
|
||||
"desc": "La recherche sémantique doit être activée pour utiliser les déclencheurs."
|
||||
},
|
||||
"wizard": {
|
||||
|
||||
@@ -227,6 +227,8 @@
|
||||
},
|
||||
"lastRefreshed": "Dernier rafraichissement : ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} a un taux élevé d'utilisation processeur par FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} : charge CPU détection élevée ({{detectAvg}}%)",
|
||||
"healthy": "Le système est sain",
|
||||
"reindexingEmbeddings": "Réindexation des embeddings ({{processed}} % terminée)",
|
||||
"cameraIsOffline": "{{camera}} est hors ligne",
|
||||
|
||||
@@ -531,6 +531,7 @@
|
||||
"desc": "Frigate יכולה לשלוח התראות דחיפה באופן טבעי למכשיר שלך כאשר הוא פועל בדפדפן או מותקן כ-PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "התראות לא זמינות",
|
||||
"desc": "התראות דחיפה באינטרנט דורשות קישור מאובטח (<code>https://…</code>). זוהי מגבלה של הדפדפן. יש לגשת ל-Frigate בצורה מאובטחת כדי להשתמש בהתראות."
|
||||
},
|
||||
"globalSettings": {
|
||||
@@ -948,6 +949,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "טריגרים",
|
||||
"semanticSearch": {
|
||||
"title": "חיפוש סמנטי מושבת",
|
||||
"desc": "כדי להשתמש בטריגרים, יש להפעיל חיפוש סמנטי."
|
||||
},
|
||||
"management": {
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
{
|
||||
"lastRefreshed": "רענון אחרון: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "ל-{{camera}} יש צריכת מעבד גבוהה של FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "ל-{{camera}} יש צריכת CPU גבוהה ({{detectAvg}}%)",
|
||||
"healthy": "המערכת פועלת בצורה תקינה",
|
||||
"reindexingEmbeddings": "אינדקס מחדש של ההטמעות ({{processed}}% הושלם)",
|
||||
"cameraIsOffline": "{{camera}} לא זמינה",
|
||||
|
||||
@@ -855,6 +855,7 @@
|
||||
"desc": "Frigate može nativno slati push obavijesti na vaš uređaj kada je pokrenut u pregledniku ili instaliran kao PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Obavijesti nisu dostupne",
|
||||
"desc": "Web push obavijesti zahtijevaju siguran kontekst (<code>https://...</code>). Ovo je ograničenje preglednika. Pristupite Frigateu sigurno kako biste koristili obavijesti."
|
||||
},
|
||||
"globalSettings": {
|
||||
@@ -945,6 +946,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "Okidači",
|
||||
"semanticSearch": {
|
||||
"title": "Semantičko pretraživanje je onemogućeno",
|
||||
"desc": "Semantičko pretraživanje mora biti omogućeno za korištenje okidača."
|
||||
},
|
||||
"management": {
|
||||
|
||||
@@ -164,6 +164,8 @@
|
||||
},
|
||||
"lastRefreshed": "Zadnje osvježavanje: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} ima visoku upotrebu CPU-a za FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} ima visoku upotrebu CPU-a za detekciju ({{detectAvg}}%)",
|
||||
"healthy": "Sustav je zdrav",
|
||||
"reindexingEmbeddings": "Reindeksiranje embeddings ({{processed}}% završeno)",
|
||||
"cameraIsOffline": "{{camera}} je offline",
|
||||
|
||||
@@ -210,6 +210,7 @@
|
||||
}
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Értesítés elérhetetlen",
|
||||
"desc": "A webes push értesítésekhez biztonságos környezet (<code>https://…</code>) szükséges. Ez egy böngészői korlátozás. A értesítések használatához férjen hozzá biztonságosan a Frigate-hez."
|
||||
},
|
||||
"sendTestNotification": "Teszt értesítés küldése",
|
||||
@@ -710,6 +711,7 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"title": "Szemantikus keresés le van tiltva",
|
||||
"desc": "A Triggerek használatához engedélyezni kell a szemantikus keresést."
|
||||
},
|
||||
"wizard": {
|
||||
|
||||
@@ -201,7 +201,9 @@
|
||||
"healthy": "A rendszer egészséges",
|
||||
"cameraIsOffline": "{{camera}} nem elérhető",
|
||||
"detectIsSlow": "{{detect}} lassú ({{speed}} ms)",
|
||||
"reindexingEmbeddings": "Beágyazások újra indexelése ({{processed}}% kész)"
|
||||
"reindexingEmbeddings": "Beágyazások újra indexelése ({{processed}}% kész)",
|
||||
"ffmpegHighCpuUsage": "{{camera}}-nak/-nek magas FFmpeg CPU felhasználása ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "A(z) {{camera}} kameránál magas az észlelési CPU-használat ({{detectAvg}}%)"
|
||||
},
|
||||
"lastRefreshed": "Utoljára frissítve: "
|
||||
}
|
||||
|
||||
@@ -6,12 +6,7 @@
|
||||
"lowBandwidthMode": "Mode bandwidth rendah",
|
||||
"twoWayTalk": {
|
||||
"enable": "Aktifkan Audio Dua Arah",
|
||||
"disable": "Nonaktifkan Audio Dua Arah",
|
||||
"requiresWebRTC": "Percakapan dua arah memerlukan WebRTC, yang tidak tersedia",
|
||||
"error": {
|
||||
"microphone": "Percakapan dua arah tidak dapat mengakses mikrofon Anda",
|
||||
"refused": "Percakapan dua arah gagal dimulai. Lihat konsol browser untuk detail."
|
||||
}
|
||||
"disable": "Nonaktifkan Audio Dua Arah"
|
||||
},
|
||||
"cameraAudio": {
|
||||
"enable": "Aktifkan Audio Kamera",
|
||||
@@ -136,8 +131,7 @@
|
||||
"unavailable": "Audio tidak tersedia untuk stream ini"
|
||||
},
|
||||
"debug": {
|
||||
"picker": "Pemilihan stream tidak tersedia dalam mode debug. Tampilan debug selalu menggunakan stream yang ditetapkan ke peran detect.",
|
||||
"technology": "Pemilihan teknologi streaming tidak tersedia dalam mode debug."
|
||||
"picker": "Pemilihan stream tidak tersedia dalam mode debug. Tampilan debug selalu menggunakan stream yang ditetapkan ke peran detect."
|
||||
},
|
||||
"twoWayTalk": {
|
||||
"tips": "Perangkat Anda harus mendukung fitur ini dan WebRTC harus dikonfigurasi untuk audio dua arah.",
|
||||
@@ -146,36 +140,11 @@
|
||||
},
|
||||
"lowBandwidth": {
|
||||
"tips": "Tampilan live berada dalam mode bandwidth rendah karena buffering atau kesalahan stream.",
|
||||
"resetStream": "Atur ulang stream",
|
||||
"force": {
|
||||
"label": "Paksa mode bandwidth rendah",
|
||||
"desc": "Selalu putar feed bandwidth rendah bawaan Frigate, bukan stream yang dipilih. Berfungsi pada semua koneksi, tetapi kualitasnya lebih rendah dan tanpa audio."
|
||||
}
|
||||
"resetStream": "Atur ulang stream"
|
||||
},
|
||||
"playInBackground": {
|
||||
"label": "Putar di latar belakang",
|
||||
"tips": "Aktifkan opsi ini untuk melanjutkan streaming saat pemutar disembunyikan."
|
||||
},
|
||||
"mode": "Teknologi Streaming",
|
||||
"technology": {
|
||||
"description": "Pilih teknologi streaming yang Anda inginkan. Frigate mungkin tetap beralih ke mode bandwidth rendah jika terjadi kesalahan pemutaran atau jaringan.",
|
||||
"name": {
|
||||
"mse": "MSE",
|
||||
"webrtc": "WebRTC",
|
||||
"jsmpeg": "JSMpeg"
|
||||
},
|
||||
"tips": {
|
||||
"mse": "Default yang direkomendasikan, kompatibilitas luas dan pemutaran lancar",
|
||||
"webrtc": "Memerlukan pengaturan tambahan dan tidak didukung pada setiap perangkat"
|
||||
},
|
||||
"unavailable": {
|
||||
"browser": "Browser Anda tidak mendukung WebRTC.",
|
||||
"not-configured": "WebRTC belum dikonfigurasi. Atur candidates WebRTC go2rtc atau ice_servers.",
|
||||
"unreachable": "WebRTC tidak dapat terhubung. Pastikan port 8555 dapat dijangkau dan server STUN/TURN telah dikonfigurasi dengan benar.",
|
||||
"video-codec": "Codec video stream ini tidak didukung oleh WebRTC pada browser ini.",
|
||||
"audio-codec": "Codec audio stream ini tidak didukung oleh WebRTC. Lakukan transcoding ke Opus atau G.711 menggunakan go2rtc.",
|
||||
"checking": "Memeriksa ketersediaan WebRTC…"
|
||||
}
|
||||
}
|
||||
},
|
||||
"cameraSettings": {
|
||||
@@ -185,8 +154,7 @@
|
||||
"snapshots": "Snapshot",
|
||||
"audioDetection": "Deteksi Audio",
|
||||
"transcription": "Transkripsi Audio",
|
||||
"autotracking": "Pelacakan Otomatis",
|
||||
"camera": "Kamera"
|
||||
"autotracking": "Pelacakan Otomatis"
|
||||
},
|
||||
"history": {
|
||||
"label": "Tampilkan rekaman historis"
|
||||
@@ -223,9 +191,5 @@
|
||||
"description": "Grup kamera ini tidak memiliki kamera yang ditetapkan atau diaktifkan.",
|
||||
"buttonText": "Kelola Grup"
|
||||
}
|
||||
},
|
||||
"camera": {
|
||||
"turnOn": "Nyalakan Kamera",
|
||||
"turnOff": "Matikan Kamera"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -58,7 +58,7 @@
|
||||
"systemTelemetry": "Telemetri",
|
||||
"systemBirdseye": "Birdseye",
|
||||
"systemFfmpeg": "FFmpeg",
|
||||
"systemDetectorsAndModel": "Model deteksi",
|
||||
"systemDetectorsAndModel": "Detektor dan model",
|
||||
"systemMqtt": "MQTT",
|
||||
"systemGo2rtcStreams": "Stream go2rtc",
|
||||
"integrationSemanticSearch": "Pencarian semantik",
|
||||
@@ -68,7 +68,7 @@
|
||||
"integrationObjectClassification": "Klasifikasi objek",
|
||||
"integrationAudioTranscription": "Transkripsi audio",
|
||||
"cameraDetect": "Deteksi objek",
|
||||
"cameraFfmpeg": "Stream (FFmpeg)",
|
||||
"cameraFfmpeg": "FFmpeg",
|
||||
"cameraRecording": "Perekaman",
|
||||
"cameraSnapshots": "Cuplikan",
|
||||
"cameraMotion": "Deteksi gerakan",
|
||||
@@ -150,48 +150,17 @@
|
||||
"toast": {
|
||||
"success": {
|
||||
"clearStoredLayout": "Tata letak tersimpan untuk {{cameraName}} telah dihapus",
|
||||
"clearStreamingSettings": "Pengaturan streaming untuk semua grup kamera telah dihapus.",
|
||||
"exportUiSettings": "Pengaturan diekspor",
|
||||
"importUiSettings": "Pengaturan diimpor"
|
||||
"clearStreamingSettings": "Pengaturan streaming untuk semua grup kamera telah dihapus."
|
||||
},
|
||||
"error": {
|
||||
"clearStoredLayoutFailed": "Gagal menghapus tata letak tersimpan: {{errorMessage}}",
|
||||
"clearStreamingSettingsFailed": "Gagal menghapus pengaturan streaming: {{errorMessage}}",
|
||||
"exportUiSettingsFailed": "Gagal mengekspor pengaturan",
|
||||
"importNothingToApply": "Gagal mengimpor pengaturan: file tidak berisi pengaturan",
|
||||
"importInvalidJson": "Gagal mengimpor pengaturan: file bukan JSON yang valid",
|
||||
"importWrongType": "Gagal mengimpor pengaturan: file bukan ekspor pengaturan Frigate",
|
||||
"importUnsupportedVersion": "Gagal mengimpor pengaturan: file memerlukan versi Frigate yang lebih baru",
|
||||
"importInvalidSchema": "Gagal mengimpor pengaturan: file tidak valid",
|
||||
"importUiSettingsFailed": "Gagal mengimpor pengaturan"
|
||||
}
|
||||
},
|
||||
"backupRestore": {
|
||||
"title": "Pencadangan & Pemulihan",
|
||||
"transfer": {
|
||||
"label": "File Pengaturan Perangkat",
|
||||
"desc": "Tata letak grup kamera, pengaturan streaming, dan preferensi UI disimpan di browser Anda. Ekspor ke file untuk mencadangkannya atau memindahkannya ke perangkat lain.",
|
||||
"export": "Ekspor Pengaturan",
|
||||
"import": "Impor Pengaturan"
|
||||
},
|
||||
"importDialog": {
|
||||
"title": "Impor Pengaturan",
|
||||
"desc": "Pilih yang akan diterapkan dari file ini. Frigate akan dimuat ulang setelah impor selesai.",
|
||||
"exportedFrom": "Diekspor pada {{date}} dari konfigurasi Frigate versi {{version}}",
|
||||
"layouts_other": "Tata letak grup kamera ({{count}} grup)",
|
||||
"streaming_other": "Pengaturan streaming ({{count}} kamera)",
|
||||
"preferences_other": "Preferensi UI ({{count}} pengaturan)",
|
||||
"unknownGroups_other": "Grup kamera {{groups}} tidak ada di server ini. Pengaturannya akan disimpan tetapi tidak digunakan.",
|
||||
"unknownCameras_other": "Kamera {{cameras}} tidak ada di server ini. Pengaturan streamingnya akan diabaikan.",
|
||||
"confirm": "Impor"
|
||||
"clearStreamingSettingsFailed": "Gagal menghapus pengaturan streaming: {{errorMessage}}"
|
||||
}
|
||||
}
|
||||
},
|
||||
"configMessages": {
|
||||
"audioTranscription": {
|
||||
"audioDetectionDisabled": "Deteksi audio tidak diaktifkan untuk kamera ini. Transkripsi audio memerlukan deteksi audio yang aktif.",
|
||||
"audioDetectionRuntimeDisabled": "Deteksi audio diaktifkan dalam konfigurasi Anda, tetapi saat ini dinonaktifkan untuk kamera ini, sehingga transkripsi audio tidak akan berjalan. Aktifkan kembali dari tampilan langsung kamera, atau periksa apakah profil aktif menonaktifkannya.",
|
||||
"genaiProviderSelected": "Penyedia GenAI dipilih, sehingga pengaturan perangkat dan ukuran model diabaikan."
|
||||
"audioDetectionDisabled": "Deteksi audio tidak diaktifkan untuk kamera ini. Transkripsi audio memerlukan deteksi audio yang aktif."
|
||||
},
|
||||
"detect": {
|
||||
"fpsGreaterThanFive": "Mengatur FPS deteksi lebih dari 5 tidak direkomendasikan. Nilai yang lebih tinggi dapat menyebabkan masalah performa dan tidak akan memberikan manfaat apa pun.",
|
||||
@@ -201,9 +170,7 @@
|
||||
"maxFramesSet": "Menetapkan frame maksimum akan menimpa perilaku default dan menonaktifkan pelacakan objek diam. Hanya sedikit situasi yang memerlukan ini, gunakan dengan hati-hati.",
|
||||
"squareResolution": "Resolusi deteksi berbentuk persegi tidak lazim. Lebar dan tinggi deteksi harus sesuai dengan rasio aspek kamera Anda, misalnya 16:9, bukan dimensi model deteksi objek. Rasio aspek yang tidak sesuai dapat meregangkan gambar dan mengurangi akurasi deteksi.",
|
||||
"resolutionHigh": "Resolusi deteksi ini lebih tinggi daripada yang direkomendasikan dan dapat meningkatkan penggunaan sumber daya tanpa meningkatkan akurasi deteksi. Resolusi deteksi 1080p atau lebih rendah direkomendasikan untuk sebagian besar kamera.",
|
||||
"globalResolutionMultipleCameras": "Resolusi deteksi global ditetapkan saat beberapa kamera dikonfigurasi. Kecuali semua kamera memiliki resolusi dan rasio aspek yang sama, lebar dan tinggi deteksi sebaiknya ditentukan per kamera agar sesuai dengan rasio aspek asli masing-masing kamera.",
|
||||
"runtimeDisabled": "Deteksi objek diaktifkan dalam konfigurasi Anda, tetapi saat ini dinonaktifkan untuk kamera ini. Snapshot, item tinjauan, dan pengayaan seperti pengenalan wajah, pengenalan pelat nomor, serta Generative AI tidak akan berfungsi hingga fitur tersebut diaktifkan kembali dari tampilan langsung kamera, atau hingga profil aktif berhenti menonaktifkannya.",
|
||||
"sceneWithoutModel": "Tidak ada model deteksi yang dikonfigurasi untuk scene ini, sehingga kamera ini menggunakan model dengan scene “All cameras” sebagai cadangan. Tambahkan model untuk scene ini agar kamera memiliki modelnya sendiri."
|
||||
"globalResolutionMultipleCameras": "Resolusi deteksi global ditetapkan saat beberapa kamera dikonfigurasi. Kecuali semua kamera memiliki resolusi dan rasio aspek yang sama, lebar dan tinggi deteksi sebaiknya ditentukan per kamera agar sesuai dengan rasio aspek asli masing-masing kamera."
|
||||
},
|
||||
"faceRecognition": {
|
||||
"globalDisabled": "Pengayaan pengenalan wajah harus diaktifkan agar fitur pengenalan wajah berfungsi pada kamera ini.",
|
||||
@@ -212,17 +179,14 @@
|
||||
},
|
||||
"lpr": {
|
||||
"globalDisabled": "Pengayaan pengenalan pelat nomor harus diaktifkan agar fitur LPR berfungsi pada kamera ini.",
|
||||
"vehicleNotTracked": "Pengenalan pelat nomor memerlukan kendaraan untuk dilacak. Aktifkan “car” atau jenis kendaraan lain pada Objects untuk kamera ini.",
|
||||
"vehicleNotTracked": "Pengenalan pelat nomor memerlukan 'car' atau 'motorcycle' untuk dilacak. Aktifkan 'car' atau 'motorcycle' di Objek untuk kamera ini.",
|
||||
"modelSizeLarge": "Model 'large' dioptimalkan untuk pelat nomor multi-baris. Model 'small' memberikan performa lebih baik daripada 'large' dan sebaiknya digunakan kecuali wilayah Anda menggunakan format pelat multi-baris."
|
||||
},
|
||||
"review": {
|
||||
"recordDisabled": "Perekaman dinonaktifkan, item tinjauan tidak akan dibuat.",
|
||||
"detectDisabled": "Deteksi objek dinonaktifkan. Item tinjauan memerlukan objek yang terdeteksi untuk mengategorikan alert dan deteksi.",
|
||||
"allNonAlertDetections": "Semua aktivitas non-alert akan disertakan sebagai deteksi.",
|
||||
"genaiImageSourceRecordingsRecordDisabled": "Sumber gambar disetel ke 'rekaman', tetapi perekaman dinonaktifkan. Frigate akan kembali ke gambar pratinjau.",
|
||||
"recordRuntimeDisabled": "Perekaman diaktifkan dalam konfigurasi Anda, tetapi saat ini dinonaktifkan untuk kamera ini, sehingga item tinjauan tidak akan dibuat. Aktifkan kembali dari tampilan langsung kamera, atau periksa apakah profil aktif menonaktifkannya.",
|
||||
"detectRuntimeDisabled": "Deteksi objek diaktifkan dalam konfigurasi Anda, tetapi saat ini dinonaktifkan untuk kamera ini. Item tinjauan memerlukan objek yang terdeteksi untuk mengategorikan peringatan dan deteksi. Aktifkan kembali dari tampilan langsung kamera, atau periksa apakah profil aktif menonaktifkannya.",
|
||||
"genaiImageSourceRecordingsRecordRuntimeDisabled": "Sumber gambar diatur ke “recordings”, tetapi perekaman saat ini dinonaktifkan untuk kamera ini meskipun konfigurasi Anda mengaktifkannya. Frigate akan menggunakan gambar pratinjau sebagai pengganti."
|
||||
"genaiImageSourceRecordingsRecordDisabled": "Sumber gambar disetel ke 'rekaman', tetapi perekaman dinonaktifkan. Frigate akan kembali ke gambar pratinjau."
|
||||
},
|
||||
"audio": {
|
||||
"noAudioRole": "Tidak ada stream yang memiliki peran audio yang didefinisikan. Anda harus mengaktifkan peran audio agar deteksi audio berfungsi."
|
||||
@@ -231,30 +195,16 @@
|
||||
"genaiNoDescriptionsProvider": "Anda harus mengonfigurasi penyedia GenAI dengan peran 'deskripsi' agar deskripsi dapat dibuat."
|
||||
},
|
||||
"record": {
|
||||
"noRecordRole": "Tidak ada stream yang memiliki peran record yang didefinisikan. Perekaman tidak akan berfungsi.",
|
||||
"noRecordSubRole": "Tidak ada stream yang memiliki peran record_sub. Perekaman sub stream tidak akan berfungsi."
|
||||
"noRecordRole": "Tidak ada stream yang memiliki peran record yang didefinisikan. Perekaman tidak akan berfungsi."
|
||||
},
|
||||
"snapshots": {
|
||||
"detectDisabled": "Deteksi objek dinonaktifkan. Cuplikan dihasilkan dari objek yang terlacak dan tidak akan dibuat.",
|
||||
"detectRuntimeDisabled": "Deteksi objek diaktifkan dalam konfigurasi Anda, tetapi saat ini dinonaktifkan untuk kamera ini, sehingga snapshot tidak akan dibuat. Aktifkan kembali dari tampilan langsung kamera, atau periksa apakah profil aktif menonaktifkannya."
|
||||
"detectDisabled": "Deteksi objek dinonaktifkan. Cuplikan dihasilkan dari objek yang terlacak dan tidak akan dibuat."
|
||||
},
|
||||
"semanticSearch": {
|
||||
"jinav2SmallModelSize": "Ukuran 'small' dengan model Jina V2 memiliki RAM tinggi dan biaya inferensi. Model 'large' dengan GPU diskrit direkomendasikan."
|
||||
},
|
||||
"onvif": {
|
||||
"autotrackingNoZones": "Pelacakan otomatis memerlukan setidaknya satu zona. Tentukan zona untuk kamera ini di Masker / Zona, lalu tetapkan sebagai zona wajib di bawah."
|
||||
},
|
||||
"model": {
|
||||
"optimizedFor320": "Frigate dioptimalkan untuk model 320x320, yang merupakan pilihan terbaik untuk sebagian besar konfigurasi. Model 640x640 lebih lambat dan hanya membantu dalam skenario tertentu.",
|
||||
"inputDimensionsNotDetectResolution": "Lebar dan tinggi input model adalah dimensi input model deteksi objek, bukan resolusi deteksi kamera Anda. Nilainya harus sesuai dengan dimensi model yang digunakan—biasanya ukuran persegi seperti 320x320 atau 640x640."
|
||||
},
|
||||
"ffmpeg": {
|
||||
"hwaccelManualNotRecommended": "Argumen akselerasi perangkat keras manual tidak direkomendasikan. Kecuali terdapat kebutuhan khusus, pilih preset yang sesuai dengan perangkat keras Anda.",
|
||||
"inputsMissingGo2rtcStream": "Input di bawah ini mengarah ke restream go2rtc yang sudah tidak ada. Pilih restream yang tersedia atau masukkan URL kamera secara manual; jika tidak, kamera ini akan gagal terhubung."
|
||||
},
|
||||
"birdseye": {
|
||||
"objectTrackingDetectDisabled": "Birdseye mencakup objek yang dilacak, tetapi deteksi objek dinonaktifkan untuk kamera ini. Kamera tidak akan muncul di Birdseye.",
|
||||
"objectTrackingDetectRuntimeDisabled": "Birdseye mencakup objek yang dilacak, tetapi deteksi objek saat ini dinonaktifkan untuk kamera ini meskipun konfigurasi Anda mengaktifkannya. Kamera tidak akan muncul di Birdseye hingga deteksi objek diaktifkan kembali dari tampilan langsung kamera, atau hingga profil aktif berhenti menonaktifkannya."
|
||||
}
|
||||
},
|
||||
"button": {
|
||||
@@ -272,10 +222,7 @@
|
||||
"heading_other": "Bagian global ini memiliki bidang yang ditimpa di {{count}} kamera.",
|
||||
"othersField_other": "{{count}} lainnya",
|
||||
"profilePrefix": "Profil {{profile}}: {{fields}}"
|
||||
},
|
||||
"overriddenLive": "Ditimpa (Langsung)",
|
||||
"overriddenLiveTooltip": "Kamera ini berjalan dengan nilai yang berbeda dari nilai yang tersimpan dalam konfigurasi Anda, yang ditampilkan di sini. Tampilan langsung, MQTT, atau profil aktif dapat mengubahnya saat Frigate berjalan.",
|
||||
"overriddenLiveValue": "Nilai yang berjalan: {{value}}"
|
||||
}
|
||||
},
|
||||
"menuDot": {
|
||||
"overrideGlobal": "Bagian ini menimpa konfigurasi global",
|
||||
@@ -460,7 +407,7 @@
|
||||
}
|
||||
},
|
||||
"step3": {
|
||||
"description": "Konfigurasikan fitur, peran stream, dan tambahkan stream tambahan untuk kamera Anda.",
|
||||
"description": "Konfigurasikan peran stream dan tambahkan stream tambahan untuk kamera Anda.",
|
||||
"streamsTitle": "Stream Kamera",
|
||||
"addStream": "Tambah Stream",
|
||||
"addAnotherStream": "Tambah Stream Lain",
|
||||
@@ -494,26 +441,11 @@
|
||||
"title": "Peran Stream",
|
||||
"detect": "Umpan utama untuk deteksi objek.",
|
||||
"record": "Menyimpan segmen umpan video berdasarkan pengaturan konfigurasi.",
|
||||
"audio": "Umpan untuk deteksi berbasis audio.",
|
||||
"record_sub": "Rekaman berkualitas lebih rendah untuk pemutaran adaptif dan retensi lebih lama (biasanya sub stream kamera)."
|
||||
"audio": "Umpan untuk deteksi berbasis audio."
|
||||
},
|
||||
"featuresPopover": {
|
||||
"title": "Fitur Stream",
|
||||
"description": "Gunakan restreaming go2rtc untuk mengurangi koneksi ke kamera Anda."
|
||||
},
|
||||
"appleCompatibility": {
|
||||
"title": "Tingkatkan pemutaran pada perangkat Apple",
|
||||
"description": "Aktifkan jika Anda menonton rekaman melalui Safari atau perangkat iPhone, iPad, atau Mac."
|
||||
},
|
||||
"ptz": {
|
||||
"title": "Aktifkan Kontrol PTZ",
|
||||
"detectedNote": "Dukungan PTZ telah terdeteksi melalui ONVIF. Jika ini adalah kamera PTZ, mengaktifkan opsi ini memungkinkan Anda mengendalikan fungsi pan/tilt/zoom kamera dari UI.",
|
||||
"connectionDetails": "Detail koneksi ONVIF",
|
||||
"host": "Host ONVIF",
|
||||
"port": "Port ONVIF",
|
||||
"username": "Nama Pengguna ONVIF",
|
||||
"password": "Kata Sandi ONVIF",
|
||||
"hostRequiredWarning": "Host dan port ONVIF diperlukan saat kontrol PTZ diaktifkan."
|
||||
}
|
||||
},
|
||||
"step4": {
|
||||
@@ -574,7 +506,7 @@
|
||||
"deleteCameraDialog": {
|
||||
"title": "Hapus Kamera",
|
||||
"description": "Menghapus kamera akan menghapus secara permanen semua rekaman, objek terlacak, dan konfigurasi untuk kamera tersebut. Semua stream go2rtc yang terkait dengan kamera ini mungkin masih perlu dihapus secara manual.",
|
||||
"selectPlaceholder": "Pilih kamera…",
|
||||
"selectPlaceholder": "Pilih kamera...",
|
||||
"confirmTitle": "Apakah Anda yakin?",
|
||||
"confirmWarning": "Menghapus <strong>{{cameraName}}</strong> tidak dapat dibatalkan.",
|
||||
"deleteExports": "Juga hapus ekspor untuk kamera ini",
|
||||
@@ -610,7 +542,7 @@
|
||||
"webuiUrlHelp": "URL untuk membuka web UI kamera langsung dari tampilan Debug. Biarkan kosong untuk menonaktifkan tautan.",
|
||||
"webuiUrlInvalid": "Harus berupa URL yang valid (misalnya, https://example.com).",
|
||||
"dashboardLabel": "Tampilkan di dasbor Live",
|
||||
"dashboardHelp": "Tampilkan kamera ini pada dasbor tampilan langsung Semua Kamera secara default. Kamera tetap tersedia di semua tempat lain, termasuk grup kamera.",
|
||||
"dashboardHelp": "Tampilkan kamera ini di dasbor Live.",
|
||||
"reviewLabel": "Tampilkan di Review",
|
||||
"reviewHelp": "Tampilkan kamera ini di Review, termasuk filter kamera, review gerakan, dan tampilan riwayat."
|
||||
}
|
||||
@@ -1157,7 +1089,7 @@
|
||||
},
|
||||
"createUser": {
|
||||
"title": "Buat Pengguna Baru",
|
||||
"desc": "Tambahkan akun pengguna baru dan tentukan peran untuk akses ke area UI Frigate.",
|
||||
"desc": "Tambahkan akun pengguna baru dan tentukan perannya untuk akses ke area UI Frigate.",
|
||||
"usernameOnlyInclude": "Nama pengguna hanya boleh berisi huruf, angka, . atau _",
|
||||
"confirmPassword": "Harap konfirmasi kata sandi Anda"
|
||||
},
|
||||
@@ -1260,8 +1192,9 @@
|
||||
"desc": "Frigate dapat secara native mengirim notifikasi push ke perangkat Anda saat berjalan di browser atau diinstal sebagai PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"desc": "Notifikasi push web memerlukan konteks aman ([https://…](https://…)). Ini merupakan batasan browser. Akses Frigate secara aman untuk menggunakan notifikasi.",
|
||||
"descPwa": "Di iOS, notifikasi push web hanya tersedia jika Frigate dipasang ke Layar Utama. Buka menu Bagikan, pilih Tambahkan ke Layar Utama, lalu buka Frigate dari ikon baru untuk mendaftarkan perangkat ini untuk notifikasi."
|
||||
"title": "Notifikasi Tidak Tersedia",
|
||||
"desc": "Notifikasi push web memerlukan konteks aman (<code>https://…</code>). Ini adalah batasan browser. Akses Frigate secara aman untuk menggunakan notifikasi.",
|
||||
"descPwa": "Di iOS, notifikasi push web hanya tersedia jika Frigate dipasang ke Layar Utama Anda. Buka menu <strong>Bagikan</strong>, pilih <strong>Tambahkan ke Layar Utama</strong>, lalu buka Frigate dari ikon baru tersebut untuk mendaftarkan perangkat ini agar menerima notifikasi."
|
||||
},
|
||||
"globalSettings": {
|
||||
"title": "Pengaturan Global",
|
||||
@@ -1367,6 +1300,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "Pemicu",
|
||||
"semanticSearch": {
|
||||
"title": "Pencarian Semantik dinonaktifkan",
|
||||
"desc": "Pencarian Semantik harus diaktifkan untuk menggunakan Pemicu."
|
||||
},
|
||||
"management": {
|
||||
@@ -1524,9 +1458,7 @@
|
||||
"orphansDeleted": "File Yatim Piatu Dihapus",
|
||||
"aborted": "Dibatalkan. Penghapusan akan melebihi ambang keamanan.",
|
||||
"error": "Kesalahan",
|
||||
"totals": "Total",
|
||||
"spaceToReclaim": "Ruang yang Dapat Diklaim Kembali",
|
||||
"spaceReclaimed": "Ruang Berhasil Diklaim Kembali"
|
||||
"totals": "Total"
|
||||
},
|
||||
"event_snapshots": "Cuplikan Objek Terlacak",
|
||||
"event_thumbnails": "Thumbnail Objek Terlacak",
|
||||
@@ -1568,23 +1500,11 @@
|
||||
"keyLabel": "Kunci",
|
||||
"valueLabel": "Nilai",
|
||||
"keyPlaceholder": "Kunci baru",
|
||||
"remove": "Hapus",
|
||||
"providerNameLabel": "Nama penyedia",
|
||||
"providerNamePlaceholder": "mis., openai",
|
||||
"variableNameLabel": "Nama variabel",
|
||||
"variableNamePlaceholder": "mis., MY_VARIABLE",
|
||||
"loggerNameLabel": "Nama logger",
|
||||
"loggerNamePlaceholder": "mis., frigate.record",
|
||||
"keyPatternError": "Gunakan hanya huruf, angka, tanda hubung, dan garis bawah (tanpa spasi)"
|
||||
"remove": "Hapus"
|
||||
},
|
||||
"knownPlates": {
|
||||
"namePlaceholder": "mis., Mobil Istri",
|
||||
"platePlaceholder": "Nomor pelat atau regex",
|
||||
"assignedTo": "Ditugaskan kepada {{name}}",
|
||||
"detected": "Pelat nomor terdeteksi",
|
||||
"noneDetected": "Belum ada pelat nomor yang terdeteksi",
|
||||
"search": "Cari atau masukkan pelat nomor",
|
||||
"useCustom": "Gunakan \"{{value}}\""
|
||||
"platePlaceholder": "Nomor pelat atau regex"
|
||||
},
|
||||
"timezone": {
|
||||
"defaultOption": "Gunakan zona waktu browser"
|
||||
@@ -1629,21 +1549,10 @@
|
||||
"preset-record-mjpeg": "Rekam - Kamera MJPEG",
|
||||
"preset-record-jpeg": "Rekam - Kamera JPEG",
|
||||
"preset-record-ubiquiti": "Rekam - Kamera Ubiquiti"
|
||||
},
|
||||
"sameAsRecord": "Sama seperti argumen keluaran rekaman"
|
||||
}
|
||||
},
|
||||
"cameraInputs": {
|
||||
"itemTitle": "Stream {{index}}",
|
||||
"sourceMode": {
|
||||
"restream": "Restream (go2rtc)",
|
||||
"manual": "Jalur input manual",
|
||||
"go2rtcStreamLabel": "Stream go2rtc",
|
||||
"go2rtcStreamPlaceholder": "Pilih stream go2rtc",
|
||||
"noGo2rtcStreams": "Tidak ada stream go2rtc yang dikonfigurasi",
|
||||
"go2rtcStreamSearch": "Cari stream...",
|
||||
"availableStreams": "Stream yang tersedia",
|
||||
"noMatchingStreams": "Tidak ada stream yang sesuai"
|
||||
}
|
||||
"itemTitle": "Stream {{index}}"
|
||||
},
|
||||
"restartRequiredField": "Perlu mulai ulang",
|
||||
"restartRequiredFooter": "Konfigurasi berubah - Perlu mulai ulang",
|
||||
@@ -1715,18 +1624,14 @@
|
||||
"options": {
|
||||
"detect": "Deteksi",
|
||||
"record": "Rekam",
|
||||
"audio": "Audio",
|
||||
"record_sub": "Rekam (Sub Stream)"
|
||||
},
|
||||
"roleInUse": "Sudah ditetapkan ke stream lain",
|
||||
"recordSubConflict": "Sebuah stream tidak dapat memiliki peran record dan record_sub sekaligus"
|
||||
"audio": "Audio"
|
||||
}
|
||||
},
|
||||
"genaiRoles": {
|
||||
"options": {
|
||||
"embeddings": "Embedding",
|
||||
"descriptions": "Deskripsi",
|
||||
"chat": "Chat",
|
||||
"transcribe": "Transkripsi"
|
||||
"chat": "Chat"
|
||||
}
|
||||
},
|
||||
"semanticSearchModel": {
|
||||
@@ -1784,26 +1689,7 @@
|
||||
},
|
||||
"defaultRole": {
|
||||
"admin": "Admin",
|
||||
"viewer": "Penampil",
|
||||
"none": "Tidak ada (tolak akses)"
|
||||
},
|
||||
"birdseyeModes": {
|
||||
"summary": "{{count}} dipilih",
|
||||
"options": {
|
||||
"continuous": "Kontinu",
|
||||
"motion": "Gerakan",
|
||||
"all_objects": "Semua objek",
|
||||
"alerts": "Peringatan",
|
||||
"detections": "Deteksi"
|
||||
}
|
||||
},
|
||||
"audioTranscriptionModel": {
|
||||
"placeholder": "Pilih model…",
|
||||
"builtIn": "Model Bawaan",
|
||||
"genaiProviders": "Penyedia GenAI"
|
||||
},
|
||||
"audioTranscriptionModelSize": {
|
||||
"notApplicable": "Tidak berlaku untuk penyedia GenAI"
|
||||
"viewer": "Penampil"
|
||||
}
|
||||
},
|
||||
"globalConfig": {
|
||||
@@ -1970,10 +1856,6 @@
|
||||
"imageSource": {
|
||||
"recordings": "Rekaman",
|
||||
"previews": "Pratinjau"
|
||||
},
|
||||
"frameMode": {
|
||||
"frames": "Frame",
|
||||
"annotated_frames": "Frame beranotasi"
|
||||
}
|
||||
},
|
||||
"logger": {
|
||||
@@ -1999,42 +1881,5 @@
|
||||
"modelSize": {
|
||||
"small": "Kecil",
|
||||
"large": "Besar"
|
||||
},
|
||||
"detectionModels": {
|
||||
"title": "Model deteksi",
|
||||
"description": "Konfigurasikan model deteksi objek dan perangkat keras yang digunakan oleh setiap model. Kamera memilih model berdasarkan scene dalam pengaturan deteksi kamera.",
|
||||
"addModel": "Tambahkan model",
|
||||
"cameras_other": "{{count}} kamera",
|
||||
"scene": {
|
||||
"label": "Scene",
|
||||
"description": "Lingkungan yang menjadi tujuan model ini. Kamera memilih model dengan menetapkan scene yang sama dalam pengaturan deteksinya, sedangkan model dengan scene “all” digunakan oleh setiap kamera yang tidak menetapkan scene."
|
||||
},
|
||||
"scenes": {
|
||||
"all": "Semua kamera",
|
||||
"indoor": "Dalam ruangan",
|
||||
"outdoor": "Luar ruangan",
|
||||
"indoor_thermal": "Termal dalam ruangan",
|
||||
"outdoor_thermal": "Termal luar ruangan"
|
||||
},
|
||||
"hardware": {
|
||||
"label": "Perangkat keras",
|
||||
"placeholder": "Pilih perangkat keras",
|
||||
"loading": "Mencari perangkat keras deteksi...",
|
||||
"none": "Tidak ada perangkat keras yang dipilih",
|
||||
"claimedBy": "digunakan oleh {{scene}}",
|
||||
"detectorCount": "Detektor",
|
||||
"countRecommended_other": "Direkomendasikan untuk {{count}} kamera",
|
||||
"unrecognized": "Model ini dikonfigurasi untuk perangkat keras yang tidak ditemukan pada sistem ini: {{devices}}",
|
||||
"description": "Perangkat keras tempat model ini menjalankan proses deteksi.",
|
||||
"detectorCountDescription": "Jumlah proses deteksi yang dijalankan pada perangkat keras ini. Lebih banyak detektor dapat menangani lebih banyak kamera, dengan konsekuensi penggunaan memori perangkat tambahan.",
|
||||
"unitsDescription": "Setiap unit menjalankan proses deteksinya sendiri. Unit yang sudah digunakan oleh model lain tidak dapat dipilih."
|
||||
},
|
||||
"tabs": {
|
||||
"plus": "Frigate+",
|
||||
"custom": "Model Kustom"
|
||||
},
|
||||
"plusModel": {
|
||||
"noModelSelected": "Pilih model Frigate+"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -214,6 +214,8 @@
|
||||
},
|
||||
"lastRefreshed": "Terakhir diperbarui: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} memiliki penggunaan CPU FFmpeg yang tinggi ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} memiliki penggunaan CPU deteksi yang tinggi ({{detectAvg}}%)",
|
||||
"healthy": "Sistem sehat",
|
||||
"reindexingEmbeddings": "Mengindeks ulang embedding ({{processed}}% selesai)",
|
||||
"cameraIsOffline": "{{camera}} sedang offline",
|
||||
|
||||
@@ -661,6 +661,7 @@
|
||||
"registerDevice": "Registra questo dispositivo",
|
||||
"notificationUnavailable": {
|
||||
"desc": "Le notifiche push web richiedono un contesto sicuro (<code>https://...</code>). Questa è una limitazione del browser. Accedi a Frigate in modo sicuro per utilizzare le notifiche.",
|
||||
"title": "Notifiche non disponibili",
|
||||
"descPwa": "Su iOS, le notifiche push web sono disponibili solo se Frigate è installato sulla schermata Home. Apri il menu <strong>Condividi</strong>, scegli <strong>Aggiungi alla schermata Home</strong>, quindi apri Frigate dalla nuova icona per registrare questo dispositivo per le notifiche."
|
||||
},
|
||||
"deviceSpecific": "Impostazioni specifiche del dispositivo",
|
||||
@@ -841,6 +842,7 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"title": "La ricerca semantica è disabilitata",
|
||||
"desc": "Per utilizzare gli attivatori, è necessario abilitare la ricerca semantica."
|
||||
},
|
||||
"wizard": {
|
||||
|
||||
@@ -222,6 +222,8 @@
|
||||
}
|
||||
},
|
||||
"stats": {
|
||||
"detectHighCpuUsage": "{{camera}} ha un utilizzo elevato della CPU con il rilevamento ({{detectAvg}}%)",
|
||||
"ffmpegHighCpuUsage": "{{camera}} ha un elevato utilizzo della CPU con FFmpeg ({{ffmpegAvg}}%)",
|
||||
"healthy": "Il sistema è integro",
|
||||
"reindexingEmbeddings": "Reindicizzazione degli incorporamenti (completata al {{processed}}%)",
|
||||
"cameraIsOffline": "{{camera}} è disconnessa",
|
||||
|
||||
@@ -691,6 +691,7 @@
|
||||
"desc": "Frigate はブラウザで実行中、または PWA としてインストールされている場合に、端末へネイティブのプッシュ通知を送信できます。"
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "通知は利用できません",
|
||||
"desc": "Web プッシュ通知にはセキュアコンテキスト（<code>https://…</code>）が必要です。これはブラウザの制限です。通知を利用するには、セキュアに Frigate へアクセスしてください。",
|
||||
"descPwa": "iOSでは、Frigateをホーム画面に追加した場合にのみ、Webプッシュ通知を利用できます。<strong>共有</strong>メニューを開き、<strong>ホーム画面に追加</strong>を選択してから、新しいアイコンからFrigateを起動し、このデバイスを通知対象として登録してください。"
|
||||
},
|
||||
@@ -895,7 +896,8 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"desc": "トリガーを使用するにはセマンティック検索を有効にする必要があります。"
|
||||
"desc": "トリガーを使用するにはセマンティック検索を有効にする必要があります。",
|
||||
"title": "セマンティック検索が無効です"
|
||||
},
|
||||
"wizard": {
|
||||
"title": "トリガーを作成",
|
||||
|
||||
@@ -227,6 +227,8 @@
|
||||
},
|
||||
"lastRefreshed": "最終更新: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} の FFmpeg の CPU 使用率が高い（{{ffmpegAvg}}%）",
|
||||
"detectHighCpuUsage": "{{camera}} の検知の CPU 使用率が高い（{{detectAvg}}%）",
|
||||
"healthy": "システムは正常です",
|
||||
"reindexingEmbeddings": "埋め込みを再インデックス中（{{processed}}% 完了）",
|
||||
"cameraIsOffline": "{{camera}} はオフラインです",
|
||||
|
||||
@@ -1143,6 +1143,7 @@
|
||||
"desc": "Frigate អាចផ្ញើការជូនដំណឹង Push ទៅឧបករណ៍របស់អ្នកដោយផ្ទាល់ នៅពេលដែលវាកំពុងដំណើរការក្នុងកម្មវិធីរុករក ឬបានដំឡើងជា PWA។"
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "ការជូនដំណឹងមិនអាចប្រើបាន",
|
||||
"desc": "ការជូនដំណឹង Push លើវេប ត្រូវការបរិយាកាសសុវត្ថិភាព (<code>https://…</code>)។ នេះគឺជាការកំណត់របស់កម្មវិធីរុករក។ ចូលប្រើ Frigate ដោយសុវត្ថិភាព ដើម្បីប្រើការជូនដំណឹង។",
|
||||
"descPwa": "នៅលើ iOS ការជូនដំណឹង Push លើវេប អាចប្រើបានតែនៅពេលដែល Frigate ត្រូវបានដំឡើងទៅកាន់អេក្រង់ដើមរបស់អ្នក។ បើកម៉ឺនុយ <strong>ចែករំលែក</strong> ជ្រើសរើស <strong>បន្ថែមទៅអេក្រង់ដើម</strong> បន្ទាប់មកបើក Frigate ពីរូបតំណាងថ្មី ដើម្បីចុះឈ្មោះឧបករណ៍នេះសម្រាប់ការជូនដំណឹង។"
|
||||
},
|
||||
@@ -1250,6 +1251,7 @@
|
||||
"triggers": {
|
||||
"documentTitle": "កេះ",
|
||||
"semanticSearch": {
|
||||
"title": "ការស្វែងរកតាមអត្ថន័យត្រូវបានបិទ",
|
||||
"desc": "ការស្វែងរកតាមអត្ថន័យត្រូវតែបើក ដើម្បីប្រើកេះ។"
|
||||
},
|
||||
"management": {
|
||||
|
||||
@@ -67,6 +67,7 @@
|
||||
},
|
||||
"documentTitle": "트리거",
|
||||
"semanticSearch": {
|
||||
"title": "시맨틱 검색이 비활성화됨",
|
||||
"desc": "트리거 기능을 사용하려면 시맨틱 검색이 활성화되어 있어야 합니다."
|
||||
},
|
||||
"management": {
|
||||
@@ -1307,6 +1308,7 @@
|
||||
"desc": "Frigate이 브라우저에서 실행 중이거나 PWA로 설치된 경우 기기로 푸시 알림을 기본 전송할 수 있습니다."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "알림을 사용할 수 없음",
|
||||
"desc": "웹 푸시 알림을 사용하려면 보안 컨텍스트(<code>https://…</code>)가 필요합니다. 이는 브라우저 자체의 제한 사항입니다. 알림을 사용하려면 Frigate에 보안 연결로 접속하세요.",
|
||||
"descPwa": "iOS의 경우 Frigate이 홈 화면에 추가되어 있어야만 웹 푸시 알림을 사용할 수 있습니다. <strong>공유</strong> 메뉴를 열고 <strong>홈 화면에 추가</strong>를 선택한 다음, 새로 생성된 아이콘으로 Frigate을 실행하여 기기를 알림에 등록하세요."
|
||||
},
|
||||
|
||||
@@ -236,6 +236,8 @@
|
||||
},
|
||||
"lastRefreshed": "마지막 갱신: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} 카메라의 FFmpeg CPU 사용량이 높습니다 ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} 카메라의 감지(detect) CPU 사용량이 높습니다 ({{detectAvg}}%)",
|
||||
"healthy": "시스템 상태가 양호합니다",
|
||||
"reindexingEmbeddings": "임베딩 재색인 중 ({{processed}}% 완료)",
|
||||
"cameraIsOffline": "{{camera}} 카메라가 오프라인 상태입니다",
|
||||
@@ -279,12 +281,20 @@
|
||||
"notices": {
|
||||
"title": "알림",
|
||||
"empty": "Frigate 이 잘 설치되어있습니다",
|
||||
"dismiss": "무시",
|
||||
"openSettings": "설정 열기",
|
||||
"openLink": "링크 열기",
|
||||
"noMatches": "필터에 맞는 알림이 없습니다",
|
||||
"dismissedTitle": "무시됨",
|
||||
"noneDismissed": "무시된 알림 없음",
|
||||
"clearDismissed": "무시됨 지우기",
|
||||
"clearDismissedTitle": "무시된 알림을 지울까요?",
|
||||
"clearDismissedDesc": "무시된 모든 알림이 삭제됩니다. 설정 및 스트림 점검 항목은 즉시 다시 표시되며, 기타 알림은 다음에 다시 발생할 때 표시됩니다.",
|
||||
"firstSeen_one": "최초 감지: {{time}}",
|
||||
"firstSeen_other": "최초 감지: {{time}} · {{count}}회",
|
||||
"dismissedAt": "무시됨: {{time}}",
|
||||
"filter": {
|
||||
"showDismissed": "무시된 항목 표시",
|
||||
"severity": "심각도",
|
||||
"error": "오류",
|
||||
"warning": "경고",
|
||||
|
||||
@@ -605,6 +605,7 @@
|
||||
}
|
||||
},
|
||||
"semanticSearch": {
|
||||
"title": "Semantic Paieška išjungta",
|
||||
"desc": "Norint naudoti Trigerius Semantic Paieška privalo būti įjungta."
|
||||
}
|
||||
},
|
||||
@@ -615,6 +616,7 @@
|
||||
"desc": "Frigate praneįimai sukurti veikti su push pranešimais į įrenginį kai naršoma per naršyklę arba įdiegta kaip PWA."
|
||||
},
|
||||
"notificationUnavailable": {
|
||||
"title": "Pranešimai Negalimi",
|
||||
"desc": "Web push pranešimai reikalauja saugios aplinkos (<code>https://...</code>). Tai yra naršyklės apribojimai. Atsidarykit Frigate saugiu kanalu kad galėtumėte naudotis pranešimais."
|
||||
},
|
||||
"globalSettings": {
|
||||
|
||||
@@ -227,6 +227,8 @@
|
||||
},
|
||||
"lastRefreshed": "Paskutinį kartą atnaujinta: ",
|
||||
"stats": {
|
||||
"ffmpegHighCpuUsage": "{{camera}} turi aukštą CPU suvartojimą FFmpeg ({{ffmpegAvg}}%)",
|
||||
"detectHighCpuUsage": "{{camera}} turi auktšą CPU vartojimą aptikimams ({{detectAvg}}%)",
|
||||
"healthy": "Sistemos būklė sveika",
|
||||
"reindexingEmbeddings": "Įterpinių reideksavimas ({{processed}}% baigtas)",
|
||||
"cameraIsOffline": "{{camera}} yra nepasiekiama",
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user