Full UI configuration (#22151)

* use react-jsonschema-form for UI config

* don't use properties wrapper when generating config i18n json

* configure for full i18n support

* section fields

* add descriptions to all fields for i18n

* motion i18n

* fix nullable fields

* sanitize internal fields

* add switches widgets and use friendly names

* fix nullable schema entries

* ensure update_topic is added to api calls

this needs further backend implementation to work correctly

* add global sections, camera config overrides, and reset button

* i18n

* add reset logic to global config view

* tweaks

* fix sections and live validation

* fix validation for schema objects that can be null

* generic and custom per-field validation

* improve generic error validation messages

* remove show advanced fields switch

* tweaks

* use shadcn theme

* fix array field template

* i18n tweaks

* remove collapsible around root section

* deep merge schema for advanced fields

* add array field item template and fix ffmpeg section

* add missing i18n keys

* tweaks

* comment out api call for testing

* add config groups as a separate i18n namespace

* add descriptions to all pydantic fields

* make titles more concise

* new titles as i18n

* update i18n config generation script to use json schema

* tweaks

* tweaks

* rebase

* clean up

* form tweaks

* add wildcards and fix object filter fields

* add field template for additionalproperties schema objects

* improve typing

* add section description from schema and clarify global vs camera level descriptions

* separate and consolidate global and camera i18n namespaces

* clean up now obsolete namespaces

* tweaks

* refactor sections and overrides

* add ability to render components before and after fields

* fix titles

* chore(sections): remove legacy single-section components replaced by template

* refactor configs to use individual files with a template

* fix review description

* apply hidden fields after ui schema

* move util

* remove unused i18n

* clean up error messages

* fix fast refresh

* add custom validation and use it for ffmpeg input roles

* update nav tree

* remove unused

* re-add override and modified indicators

* mark pending changes and add confirmation dialog for resets

* fix red unsaved dot

* tweaks

* add docs links, readonly keys, and restart required per field

* add special case and comments for global motion section

* add section form special cases

* combine review sections

* tweaks

* add audio labels endpoint

* add audio label switches and input to filter list

* fix type

* remove key from config when resetting to default/global

* don't show description for new key/val fields

* tweaks

* spacing tweaks

* add activity indicator and scrollbar tweaks

* add docs to filter fields

* wording changes

* fix global ffmpeg section

* add review classification zones to review form

* add backend endpoint and frontend widget for ffmpeg presets and manual args

* improve wording

* hide descriptions for additional properties arrays

* add warning log about incorrectly nested model config

* spacing and language tweaks

* fix i18n keys

* networking section docs and description

* small wording tweaks

* add layout grid field

* refactor with shared utilities

* field order

* add individual detectors to schema

add detector titles and descriptions (docstrings in pydantic are used for descriptions) and add i18n keys to globals

* clean up detectors section and i18n

* don't save model config back to yaml when saving detectors

* add full detectors config to api model dump

works around the way we use detector plugins so we can have the full detector config for the frontend

* add restart button to toast when restart is required

* add ui option to remove inner cards

* fix buttons

* section tweaks

* don't zoom into text on mobile

* make buttons sticky at bottom of sections

* small tweaks

* highlight label of changed fields

* add null to enum list when unwrapping

* refactor to shared utils and add save all button

* add undo all button

* add RJSF to dictionary

* consolidate utils

* preserve form data when changing cameras

* add mono fonts

* add popover to show what fields will be saved

* fix mobile menu not re-rendering with unsaved dots

* tweaks

* fix logger and env vars config section saving

use escaped periods in keys to retain them in the config file (eg "frigate.embeddings")

* add timezone widget

* role map field with validation

* fix validation for model section

* add another hidden field

* add footer message for required restart

* use rjsf for notifications view

* fix config saving

* add replace rules field

* default column layout and add field sizing

* clean up field template

* refactor profile settings to match rjsf forms

* tweaks

* refactor frigate+ view and make tweaks to sections

* show frigate+ model info in detection model settings when using a frigate+ model

* update restartRequired for all fields

* fix restart fields

* tweaks and add ability enable disabled cameras

more backend changes required

* require restart when enabling camera that is disabled in config

* disable save when form is invalid

* refactor ffmpeg section for readability

* change label

* clean up camera inputs fields

* misc tweaks to ffmpeg section

- add raw paths endpoint to ensure credentials get saved
- restart required tooltip

* maintenance settings tweaks

* don't mutate with lodash

* fix description re-rendering for nullable object fields

* hide reindex field

* update rjsf

* add frigate+ description to settings pane

* disable save all when any section is invalid

* show translated field name in validation error pane

* clean up

* remove unused

* fix genai merge

* fix genai

frigate/detectors/detector_config.py

@@ -45,30 +45,55 @@ class ModelTypeEnum(str, Enum):
 
 
 class ModelConfig(BaseModel):
-    path: Optional[str] = Field(None, title="Custom Object detection model path.")
+    path: Optional[str] = Field(
+        None,
+        title="Custom Object detection model path",
+        description="Path to a custom detection model file (or plus://<model_id> for Frigate+ models).",
+    )
     labelmap_path: Optional[str] = Field(
-        None, title="Label map for custom object detector."
+        None,
+        title="Label map for custom object detector",
+        description="Path to a labelmap file that maps numeric classes to string labels for the detector.",
+    )
+    width: int = Field(
+        default=320,
+        title="Object detection model input width",
+        description="Width of the model input tensor in pixels.",
+    )
+    height: int = Field(
+        default=320,
+        title="Object detection model input height",
+        description="Height of the model input tensor in pixels.",
     )
-    width: int = Field(default=320, title="Object detection model input width.")
-    height: int = Field(default=320, title="Object detection model input height.")
     labelmap: Dict[int, str] = Field(
-        default_factory=dict, title="Labelmap customization."
+        default_factory=dict,
+        title="Labelmap customization",
+        description="Overrides or remapping entries to merge into the standard labelmap.",
     )
     attributes_map: Dict[str, list[str]] = Field(
         default=DEFAULT_ATTRIBUTE_LABEL_MAP,
-        title="Map of object labels to their attribute labels.",
+        title="Map of object labels to their attribute labels",
+        description="Mapping from object labels to attribute labels used to attach metadata (for example 'car' -> ['license_plate']).",
     )
     input_tensor: InputTensorEnum = Field(
-        default=InputTensorEnum.nhwc, title="Model Input Tensor Shape"
+        default=InputTensorEnum.nhwc,
+        title="Model Input Tensor Shape",
+        description="Tensor format expected by the model: 'nhwc' or 'nchw'.",
     )
     input_pixel_format: PixelFormatEnum = Field(
-        default=PixelFormatEnum.rgb, title="Model Input Pixel Color Format"
+        default=PixelFormatEnum.rgb,
+        title="Model Input Pixel Color Format",
+        description="Pixel colorspace expected by the model: 'rgb', 'bgr', or 'yuv'.",
     )
     input_dtype: InputDTypeEnum = Field(
-        default=InputDTypeEnum.int, title="Model Input D Type"
+        default=InputDTypeEnum.int,
+        title="Model Input D Type",
+        description="Data type of the model input tensor (for example 'float32').",
     )
     model_type: ModelTypeEnum = Field(
-        default=ModelTypeEnum.ssd, title="Object Detection Model Type"
+        default=ModelTypeEnum.ssd,
+        title="Object Detection Model Type",
+        description="Detector model architecture type (ssd, yolox, yolonas) used by some detectors for optimization.",
     )
     _merged_labelmap: Optional[Dict[int, str]] = PrivateAttr()
     _colormap: Dict[int, Tuple[int, int, int]] = PrivateAttr()
@@ -210,12 +235,20 @@ class ModelConfig(BaseModel):
 
 class BaseDetectorConfig(BaseModel):
     # the type field must be defined in all subclasses
-    type: str = Field(default="cpu", title="Detector Type")
+    type: str = Field(
+        default="cpu",
+        title="Detector Type",
+        description="Type of detector to use for object detection (for example 'cpu', 'edgetpu', 'openvino').",
+    )
     model: Optional[ModelConfig] = Field(
-        default=None, title="Detector specific model configuration."
+        default=None,
+        title="Detector specific model configuration",
+        description="Detector-specific model configuration options (path, input size, etc.).",
     )
     model_path: Optional[str] = Field(
-        default=None, title="Detector specific model path."
+        default=None,
+        title="Detector specific model path",
+        description="File path to the detector model binary if required by the chosen detector.",
     )
     model_config = ConfigDict(
         extra="allow", arbitrary_types_allowed=True, protected_namespaces=()

frigate/detectors/plugins/cpu_tfl.py

@@ -1,6 +1,6 @@
 import logging
 
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -21,8 +21,18 @@ DETECTOR_KEY = "cpu"
 
 
 class CpuDetectorConfig(BaseDetectorConfig):
+    """CPU TFLite detector that runs TensorFlow Lite models on the host CPU without hardware acceleration. Not recommended."""
+
+    model_config = ConfigDict(
+        title="CPU",
+    )
+
     type: Literal[DETECTOR_KEY]
-    num_threads: int = Field(default=3, title="Number of detection threads")
+    num_threads: int = Field(
+        default=3,
+        title="Number of detection threads",
+        description="The number of threads used for CPU-based inference.",
+    )
 
 
 class CpuTfl(DetectionApi):

frigate/detectors/plugins/deepstack.py

@@ -4,7 +4,7 @@ import logging
 import numpy as np
 import requests
 from PIL import Image
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -16,12 +16,28 @@ DETECTOR_KEY = "deepstack"
 
 
 class DeepstackDetectorConfig(BaseDetectorConfig):
+    """DeepStack/CodeProject.AI detector that sends images to a remote DeepStack HTTP API for inference. Not recommended."""
+
+    model_config = ConfigDict(
+        title="DeepStack",
+    )
+
     type: Literal[DETECTOR_KEY]
     api_url: str = Field(
-        default="http://localhost:80/v1/vision/detection", title="DeepStack API URL"
+        default="http://localhost:80/v1/vision/detection",
+        title="DeepStack API URL",
+        description="The URL of the DeepStack API.",
+    )
+    api_timeout: float = Field(
+        default=0.1,
+        title="DeepStack API timeout (in seconds)",
+        description="Maximum time allowed for a DeepStack API request.",
+    )
+    api_key: str = Field(
+        default="",
+        title="DeepStack API key (if required)",
+        description="Optional API key for authenticated DeepStack services.",
     )
-    api_timeout: float = Field(default=0.1, title="DeepStack API timeout (in seconds)")
-    api_key: str = Field(default="", title="DeepStack API key (if required)")
 
 
 class DeepStack(DetectionApi):

frigate/detectors/plugins/degirum.py

@@ -2,7 +2,7 @@ import logging
 import queue
 
 import numpy as np
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -14,10 +14,28 @@ DETECTOR_KEY = "degirum"
 
 ### DETECTOR CONFIG ###
 class DGDetectorConfig(BaseDetectorConfig):
+    """DeGirum detector for running models via DeGirum cloud or local inference services."""
+
+    model_config = ConfigDict(
+        title="DeGirum",
+    )
+
     type: Literal[DETECTOR_KEY]
-    location: str = Field(default=None, title="Inference Location")
-    zoo: str = Field(default=None, title="Model Zoo")
-    token: str = Field(default=None, title="DeGirum Cloud Token")
+    location: str = Field(
+        default=None,
+        title="Inference Location",
+        description="Location of the DeGirim inference engine (e.g. '@cloud', '127.0.0.1').",
+    )
+    zoo: str = Field(
+        default=None,
+        title="Model Zoo",
+        description="Path or URL to the DeGirum model zoo.",
+    )
+    token: str = Field(
+        default=None,
+        title="DeGirum Cloud Token",
+        description="Token for DeGirum Cloud access.",
+    )
 
 
 ### ACTUAL DETECTOR  ###

frigate/detectors/plugins/edgetpu_tfl.py

@@ -4,7 +4,7 @@ import os
 
 import cv2
 import numpy as np
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -21,8 +21,18 @@ DETECTOR_KEY = "edgetpu"
 
 
 class EdgeTpuDetectorConfig(BaseDetectorConfig):
+    """EdgeTPU detector that runs TensorFlow Lite models compiled for Coral EdgeTPU using the EdgeTPU delegate."""
+
+    model_config = ConfigDict(
+        title="EdgeTPU",
+    )
+
     type: Literal[DETECTOR_KEY]
-    device: str = Field(default=None, title="Device Type")
+    device: str = Field(
+        default=None,
+        title="Device Type",
+        description="The device to use for EdgeTPU inference (e.g. 'usb', 'pci').",
+    )
 
 
 class EdgeTpuTfl(DetectionApi):

frigate/detectors/plugins/hailo8l.py

@@ -8,7 +8,7 @@ from typing import Dict, List, Optional, Tuple
 
 import cv2
 import numpy as np
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.const import MODEL_CACHE_DIR
@@ -410,5 +410,15 @@ class HailoDetector(DetectionApi):
 
 # ----------------- HailoDetectorConfig Class ----------------- #
 class HailoDetectorConfig(BaseDetectorConfig):
+    """Hailo-8/Hailo-8L detector using HEF models and the HailoRT SDK for inference on Hailo hardware."""
+
+    model_config = ConfigDict(
+        title="Hailo-8/Hailo-8L",
+    )
+
     type: Literal[DETECTOR_KEY]
-    device: str = Field(default="PCIe", title="Device Type")
+    device: str = Field(
+        default="PCIe",
+        title="Device Type",
+        description="The device to use for Hailo inference (e.g. 'PCIe', 'M.2').",
+    )

frigate/detectors/plugins/memryx.py

@@ -8,7 +8,7 @@ from queue import Queue
 
 import cv2
 import numpy as np
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -30,8 +30,18 @@ class ModelConfig(BaseModel):
 
 
 class MemryXDetectorConfig(BaseDetectorConfig):
+    """MemryX MX3 detector that runs compiled DFP models on MemryX accelerators."""
+
+    model_config = ConfigDict(
+        title="MemryX",
+    )
+
     type: Literal[DETECTOR_KEY]
-    device: str = Field(default="PCIe", title="Device Path")
+    device: str = Field(
+        default="PCIe",
+        title="Device Path",
+        description="The device to use for MemryX inference (e.g. 'PCIe').",
+    )
 
 
 class MemryXDetector(DetectionApi):

frigate/detectors/plugins/onnx.py

@@ -1,7 +1,7 @@
 import logging
 
 import numpy as np
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -23,8 +23,18 @@ DETECTOR_KEY = "onnx"
 
 
 class ONNXDetectorConfig(BaseDetectorConfig):
+    """ONNX detector for running ONNX models; will use available acceleration backends (CUDA/ROCm/OpenVINO) when available."""
+
+    model_config = ConfigDict(
+        title="ONNX",
+    )
+
     type: Literal[DETECTOR_KEY]
-    device: str = Field(default="AUTO", title="Device Type")
+    device: str = Field(
+        default="AUTO",
+        title="Device Type",
+        description="The device to use for ONNX inference (e.g. 'AUTO', 'CPU', 'GPU').",
+    )
 
 
 class ONNXDetector(DetectionApi):

frigate/detectors/plugins/openvino.py

@@ -2,7 +2,7 @@ import logging
 
 import numpy as np
 import openvino as ov
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -20,8 +20,18 @@ DETECTOR_KEY = "openvino"
 
 
 class OvDetectorConfig(BaseDetectorConfig):
+    """OpenVINO detector for AMD and Intel CPUs, Intel GPUs and Intel VPU hardware."""
+
+    model_config = ConfigDict(
+        title="OpenVINO",
+    )
+
     type: Literal[DETECTOR_KEY]
-    device: str = Field(default=None, title="Device Type")
+    device: str = Field(
+        default=None,
+        title="Device Type",
+        description="The device to use for OpenVINO inference (e.g. 'CPU', 'GPU', 'NPU').",
+    )
 
 
 class OvDetector(DetectionApi):

frigate/detectors/plugins/rknn.py

@@ -6,7 +6,7 @@ from typing import Literal
 
 import cv2
 import numpy as np
-from pydantic import Field
+from pydantic import ConfigDict, Field
 
 from frigate.const import MODEL_CACHE_DIR, SUPPORTED_RK_SOCS
 from frigate.detectors.detection_api import DetectionApi
@@ -29,8 +29,20 @@ model_cache_dir = os.path.join(MODEL_CACHE_DIR, "rknn_cache/")
 
 
 class RknnDetectorConfig(BaseDetectorConfig):
+    """RKNN detector for Rockchip NPUs; runs compiled RKNN models on Rockchip hardware."""
+
+    model_config = ConfigDict(
+        title="RKNN",
+    )
+
     type: Literal[DETECTOR_KEY]
-    num_cores: int = Field(default=0, ge=0, le=3, title="Number of NPU cores to use.")
+    num_cores: int = Field(
+        default=0,
+        ge=0,
+        le=3,
+        title="Number of NPU cores to use.",
+        description="The number of NPU cores to use (0 for auto).",
+    )
 
 
 class Rknn(DetectionApi):

frigate/detectors/plugins/synaptics.py

@@ -2,6 +2,7 @@ import logging
 import os
 
 import numpy as np
+from pydantic import ConfigDict
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -27,6 +28,12 @@ DETECTOR_KEY = "synaptics"
 
 
 class SynapDetectorConfig(BaseDetectorConfig):
+    """Synaptics NPU detector for models in .synap format using the Synap SDK on Synaptics hardware."""
+
+    model_config = ConfigDict(
+        title="Synaptics",
+    )
+
     type: Literal[DETECTOR_KEY]
 
 

frigate/detectors/plugins/teflon_tfl.py

@@ -1,5 +1,6 @@
 import logging
 
+from pydantic import ConfigDict
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -18,6 +19,12 @@ DETECTOR_KEY = "teflon_tfl"
 
 
 class TeflonDetectorConfig(BaseDetectorConfig):
+    """Teflon delegate detector for TFLite using Mesa Teflon delegate library to accelerate inference on supported GPUs."""
+
+    model_config = ConfigDict(
+        title="Teflon",
+    )
+
     type: Literal[DETECTOR_KEY]
 
 

frigate/detectors/plugins/tensorrt.py

@@ -14,7 +14,7 @@ try:
 except ModuleNotFoundError:
     TRT_SUPPORT = False
 
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -46,8 +46,16 @@ if TRT_SUPPORT:
 
 
 class TensorRTDetectorConfig(BaseDetectorConfig):
+    """TensorRT detector for Nvidia Jetson devices using serialized TensorRT engines for accelerated inference."""
+
+    model_config = ConfigDict(
+        title="TensorRT",
+    )
+
     type: Literal[DETECTOR_KEY]
-    device: int = Field(default=0, title="GPU Device Index")
+    device: int = Field(
+        default=0, title="GPU Device Index", description="The GPU device index to use."
+    )
 
 
 class HostDeviceMem(object):

frigate/detectors/plugins/zmq_ipc.py

@@ -5,7 +5,7 @@ from typing import Any, List
 
 import numpy as np
 import zmq
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from typing_extensions import Literal
 
 from frigate.detectors.detection_api import DetectionApi
@@ -17,14 +17,28 @@ DETECTOR_KEY = "zmq"
 
 
 class ZmqDetectorConfig(BaseDetectorConfig):
+    """ZMQ IPC detector that offloads inference to an external process via a ZeroMQ IPC endpoint."""
+
+    model_config = ConfigDict(
+        title="ZMQ IPC",
+    )
+
     type: Literal[DETECTOR_KEY]
     endpoint: str = Field(
-        default="ipc:///tmp/cache/zmq_detector", title="ZMQ IPC endpoint"
+        default="ipc:///tmp/cache/zmq_detector",
+        title="ZMQ IPC endpoint",
+        description="The ZMQ endpoint to connect to.",
     )
     request_timeout_ms: int = Field(
-        default=200, title="ZMQ request timeout in milliseconds"
+        default=200,
+        title="ZMQ request timeout in milliseconds",
+        description="Timeout for ZMQ requests in milliseconds.",
+    )
+    linger_ms: int = Field(
+        default=0,
+        title="ZMQ socket linger in milliseconds",
+        description="Socket linger period in milliseconds.",
     )
-    linger_ms: int = Field(default=0, title="ZMQ socket linger in milliseconds")
 
 
 class ZmqIpcDetector(DetectionApi):