License plate recognition (ALPR) backend (#14564)

* Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * Update version * Face recognition backend (#14495) * Add basic config and face recognition table * Reconfigure updates processing to handle face * Crop frame to face box * Implement face embedding calculation * Get matching face embeddings * Add support face recognition based on existing faces * Use arcface face embeddings instead of generic embeddings model * Add apis for managing faces * Implement face uploading API * Build out more APIs * Add min area config * Handle larger images * Add more debug logs * fix calculation * Reduce timeout * Small tweaks * Use webp images * Use facenet model * Improve face recognition (#14537) * Increase requirements for face to be set * Manage faces properly * Add basic docs * Simplify * Separate out face recognition frome semantic search * Update docs * Formatting * Fix access (#14540) * Face detection (#14544) * Add support for face detection * Add support for detecting faces during registration * Set body size to be larger * Undo * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * initial foundation for alpr with paddleocr * config * config * lpr maintainer * clean up * clean up * fix processing * don't process for stationary cars * fix order * fixes * check for known plates * improved length and character by character confidence * model fixes and small tweaks * docs * placeholder for non frigate+ model lp detection --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2026-08-03 09:38:15 +03:00 · 2025-02-08 12:47:01 -06:00
parent 594a4e0ba3
commit c4ce7f9800
10 changed files with 1151 additions and 9 deletions
@@ -57,7 +57,11 @@ from .logger import LoggerConfig
 from .mqtt import MqttConfig
 from .notification import NotificationConfig
 from .proxy import ProxyConfig
-from .semantic_search import FaceRecognitionConfig, SemanticSearchConfig
+from .semantic_search import (
+    FaceRecognitionConfig,
+    LicensePlateRecognitionConfig,
+    SemanticSearchConfig,
+)
 from .telemetry import TelemetryConfig
 from .tls import TlsConfig
 from .ui import UIConfig
@@ -333,6 +337,10 @@ class FrigateConfig(FrigateBaseModel):
    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
@@ -1,10 +1,14 @@
-from typing import Optional
+from typing import Dict, List, Optional

 from pydantic import Field

 from .base import FrigateBaseModel

-__all__ = ["FaceRecognitionConfig", "SemanticSearchConfig"]
+__all__ = [
+    "FaceRecognitionConfig",
+    "SemanticSearchConfig",
+    "LicensePlateRecognitionConfig",
+]


 class SemanticSearchConfig(FrigateBaseModel):
@@ -25,3 +29,18 @@ class FaceRecognitionConfig(FrigateBaseModel):
    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.")
+    threshold: float = Field(
+        default=0.9,
+        title="License plate confidence score required to be added to the object as a sub label.",
+    )
+    min_area: int = Field(
+        default=500,
+        title="Min area of license plate to consider running license plate recognition.",
+    )
+    known_plates: Optional[Dict[str, List[str]]] = Field(
+        default={}, title="Known plates to track."
+    )