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config updates
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@ -61,22 +61,35 @@ class FaceRecognitionConfig(FrigateBaseModel):
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class LicensePlateRecognitionConfig(FrigateBaseModel):
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class LicensePlateRecognitionConfig(FrigateBaseModel):
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enabled: bool = Field(default=False, title="Enable license plate recognition.")
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enabled: bool = Field(default=False, title="Enable license plate recognition.")
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threshold: float = Field(
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detection_threshold: float = Field(
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default=0.9,
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default=0.7,
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title="License plate confidence score required to be added to the object as a sub label.",
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title="License plate object confidence score required to begin running recognition.",
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gt=0.0,
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le=1.0,
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)
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)
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min_area: int = Field(
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min_area: int = Field(
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default=1000,
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default=1000,
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title="Minimum area of license plate to consider running license plate recognition.",
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title="Minimum area of license plate to begin running recognition.",
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)
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recognition_threshold: float = Field(
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default=0.9,
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title="Recognition confidence score required to add the plate to the object as a sub label.",
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gt=0.0,
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le=1.0,
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)
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)
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min_plate_length: int = Field(
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min_plate_length: int = Field(
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default=4,
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default=4,
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title="Minimum number of characters a license plate must have to be added to the object as a sub label.",
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title="Minimum number of characters a license plate must have to be added to the object as a sub label.",
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)
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)
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format: Optional[str] = Field(
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default=None,
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title="Regular expression for the expected format of license plate.",
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)
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match_distance: int = Field(
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match_distance: int = Field(
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default=1,
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default=1,
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title="Allow this number of missing/incorrect characters to still cause a detected plate to match a known plate.",
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title="Allow this number of missing/incorrect characters to still cause a detected plate to match a known plate.",
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ge=0,
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)
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)
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known_plates: Optional[Dict[str, List[str]]] = Field(
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known_plates: Optional[Dict[str, List[str]]] = Field(
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default={}, title="Known plates to track."
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default={}, title="Known plates to track (strings or regular expressions)."
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)
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)
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