Add per-camera face and lpr configs (#17235)

* Add per-camera face and lpr configs

* Formatting

* Cleanup

docs/docs/configuration/reference.md

@@ -543,12 +543,23 @@ semantic_search:
   model_size: "small"
 
 # Optional: Configuration for face recognition capability
+# NOTE: Can (enabled, min_area) be overridden at the camera level
 face_recognition:
   # Optional: Enable semantic search (default: shown below)
   enabled: False
-  # Optional: Set the model size used for embeddings. (default: shown below)
-  # NOTE: small model runs on CPU and large model runs on GPU
-  model_size: "small"
+  # Optional: Minimum face distance score required to save the attempt (default: shown below)
+  min_score: 0.8
+  # Optional: Minimum face detection score required to detect a face (default: shown below)
+  # NOTE: This only applies when not running a Frigate+ model
+  detection_threshold: 0.7
+  # Optional: Minimum face distance score required to be considered a match (default: shown below)
+  recognition_threshold: 0.9
+  # Optional: Min area of detected face box to consider running face recognition (default: shown below)
+  min_area: 500
+  # Optional: Save images of recognized faces for training (default: shown below)
+  save_attempts: True
+  # Optional: Apply a blur quality filter to adjust confidence based on the blur level of the image (default: shown below)
+  blur_confidence_filter: True
 
 # Optional: Configuration for license plate recognition capability
 lpr:

frigate/config/camera/camera.py

@@ -17,6 +17,10 @@ from frigate.util.builtin import (
 )
 
 from ..base import FrigateBaseModel
+from ..classification import (
+    CameraFaceRecognitionConfig,
+    CameraLicensePlateRecognitionConfig,
+)
 from .audio import AudioConfig
 from .birdseye import BirdseyeCameraConfig
 from .detect import DetectConfig
@@ -52,6 +56,9 @@ class CameraConfig(FrigateBaseModel):
     detect: DetectConfig = Field(
         default_factory=DetectConfig, title="Object detection configuration."
     )
+    face_recognition: CameraFaceRecognitionConfig = Field(
+        default_factory=CameraFaceRecognitionConfig, title="Face recognition config."
+    )
     ffmpeg: CameraFfmpegConfig = Field(title="FFmpeg configuration for the camera.")
     genai: GenAICameraConfig = Field(
         default_factory=GenAICameraConfig, title="Generative AI configuration."
@@ -59,6 +66,9 @@ class CameraConfig(FrigateBaseModel):
     live: CameraLiveConfig = Field(
         default_factory=CameraLiveConfig, title="Live playback settings."
     )
+    lpr: CameraLicensePlateRecognitionConfig = Field(
+        default_factory=CameraLicensePlateRecognitionConfig, title="LPR config."
+    )
     motion: Optional[MotionConfig] = Field(
         None, title="Motion detection configuration."
     )

frigate/config/classification.py

@@ -6,6 +6,8 @@ from pydantic import Field
 from .base import FrigateBaseModel
 
 __all__ = [
+    "CameraFaceRecognitionConfig",
+    "CameraLicensePlateRecognitionConfig",
     "FaceRecognitionConfig",
     "SemanticSearchConfig",
     "LicensePlateRecognitionConfig",
@@ -78,6 +80,13 @@ class FaceRecognitionConfig(FrigateBaseModel):
     )
 
 
+class CameraFaceRecognitionConfig(FrigateBaseModel):
+    enabled: bool = Field(default=False, title="Enable face recognition.")
+    min_area: int = Field(
+        default=500, title="Min area of face box to consider running face recognition."
+    )
+
+
 class LicensePlateRecognitionConfig(FrigateBaseModel):
     enabled: bool = Field(default=False, title="Enable license plate recognition.")
     detection_threshold: float = Field(
@@ -112,3 +121,11 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
     known_plates: Optional[Dict[str, List[str]]] = Field(
         default={}, title="Known plates to track (strings or regular expressions)."
     )
+
+
+class CameraLicensePlateRecognitionConfig(FrigateBaseModel):
+    enabled: bool = Field(default=False, title="Enable license plate recognition.")
+    min_area: int = Field(
+        default=1000,
+        title="Minimum area of license plate to begin running recognition.",
+    )

frigate/config/config.py

@@ -331,19 +331,6 @@ class FrigateConfig(FrigateBaseModel):
         default_factory=TelemetryConfig, title="Telemetry configuration."
     )
     tls: TlsConfig = Field(default_factory=TlsConfig, title="TLS configuration.")
-    classification: ClassificationConfig = Field(
-        default_factory=ClassificationConfig, title="Object classification config."
-    )
-    semantic_search: SemanticSearchConfig = Field(
-        default_factory=SemanticSearchConfig, title="Semantic search configuration."
-    )
-    face_recognition: FaceRecognitionConfig = Field(
-        default_factory=FaceRecognitionConfig, title="Face recognition config."
-    )
-    lpr: LicensePlateRecognitionConfig = Field(
-        default_factory=LicensePlateRecognitionConfig,
-        title="License Plate recognition config.",
-    )
     ui: UIConfig = Field(default_factory=UIConfig, title="UI configuration.")
 
     # Detector config
@@ -395,6 +382,21 @@ class FrigateConfig(FrigateBaseModel):
         title="Global timestamp style configuration.",
     )
 
+    # Classification Config
+    classification: ClassificationConfig = Field(
+        default_factory=ClassificationConfig, title="Object classification config."
+    )
+    semantic_search: SemanticSearchConfig = Field(
+        default_factory=SemanticSearchConfig, title="Semantic search configuration."
+    )
+    face_recognition: FaceRecognitionConfig = Field(
+        default_factory=FaceRecognitionConfig, title="Face recognition config."
+    )
+    lpr: LicensePlateRecognitionConfig = Field(
+        default_factory=LicensePlateRecognitionConfig,
+        title="License Plate recognition config.",
+    )
+
     camera_groups: Dict[str, CameraGroupConfig] = Field(
         default_factory=dict, title="Camera group configuration"
     )

frigate/data_processing/real_time/face.py

@@ -288,6 +288,9 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
 
     def process_frame(self, obj_data: dict[str, any], frame: np.ndarray):
         """Look for faces in image."""
+        if not self.config.cameras[obj_data["camera"]].face_recognition.enabled:
+            return
+
         start = datetime.datetime.now().timestamp()
         id = obj_data["id"]
 
@@ -348,7 +351,11 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             face_box = face.get("box")
 
             # check that face is valid
-            if not face_box or area(face_box) < self.config.face_recognition.min_area:
+            if (
+                not face_box
+                or area(face_box)
+                < self.config.cameras[obj_data["camera"]].face_recognition.min_area
+            ):
                 logger.debug(f"Invalid face box {face}")
                 return