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Min face configuration option (#18284)
* Add option to specify minimum face attempts for an object * Set upper bound
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@ -65,6 +65,8 @@ Fine-tune face recognition with these optional parameters at the global level of
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- Default: `0.8`.
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- `recognition_threshold`: Recognition confidence score required to add the face to the object as a sub label.
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- Default: `0.9`.
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- `min_faces`: Min face attempts for the sub label to be applied to the person object.
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- Default: `1`
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- `save_attempts`: Number of images of recognized faces to save for training.
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- Default: `100`.
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- `blur_confidence_filter`: Enables a filter that calculates how blurry the face is and adjusts the confidence based on this.
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@ -559,6 +559,8 @@ face_recognition:
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recognition_threshold: 0.9
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# Optional: Min area of detected face box to consider running face recognition (default: shown below)
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min_area: 500
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# Optional: Min face attempts for the sub label to be applied to the person object (default: shown below)
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min_faces: 1
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# Optional: Number of images of recognized faces to save for training (default: shown below)
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save_attempts: 100
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# Optional: Apply a blur quality filter to adjust confidence based on the blur level of the image (default: shown below)
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@ -80,6 +80,12 @@ class FaceRecognitionConfig(FrigateBaseModel):
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min_area: int = Field(
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default=750, title="Min area of face box to consider running face recognition."
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)
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min_faces: int = Field(
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default=1,
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gt=0,
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le=6,
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title="Min face attempts for the sub label to be applied to the person object.",
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)
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save_attempts: int = Field(
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default=100, ge=0, title="Number of face attempts to save in the train tab."
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)
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@ -302,6 +302,9 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
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self.person_face_history[id]
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)
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if len(self.person_face_history[id]) < self.face_config.min_faces:
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weighted_sub_label = "unknown"
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self.requestor.send_data(
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"tracked_object_update",
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json.dumps(
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