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3762ac9cbe
* 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>
47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
from typing import Dict, List, Optional
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from pydantic import Field
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from .base import FrigateBaseModel
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__all__ = [
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"FaceRecognitionConfig",
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"SemanticSearchConfig",
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"LicensePlateRecognitionConfig",
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]
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class SemanticSearchConfig(FrigateBaseModel):
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enabled: bool = Field(default=False, title="Enable semantic search.")
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reindex: Optional[bool] = Field(
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default=False, title="Reindex all detections on startup."
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)
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model_size: str = Field(
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default="small", title="The size of the embeddings model used."
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)
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class FaceRecognitionConfig(FrigateBaseModel):
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enabled: bool = Field(default=False, title="Enable face recognition.")
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threshold: float = Field(
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default=0.9, title="Face similarity score required to be considered a match."
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)
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min_area: int = Field(
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default=500, title="Min area of face box to consider running face recognition."
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)
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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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threshold: float = Field(
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default=0.9,
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title="License plate confidence score required to be added to the object as a sub label.",
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)
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min_area: int = Field(
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default=500,
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title="Min area of license plate to consider running license plate recognition.",
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)
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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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)
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