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Increase default number of faces shown
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@ -70,7 +70,7 @@ Fine-tune face recognition with these optional parameters at the global level of
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- `min_faces`: Min face recognitions 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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- Default: `200`.
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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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- Default: `True`.
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- `device`: Target a specific device to run the face recognition model on (multi-GPU installation).
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@ -630,7 +630,7 @@ face_recognition:
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# Optional: Min face recognitions 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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save_attempts: 200
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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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blur_confidence_filter: True
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# Optional: Set the model size used face recognition. (default: shown below)
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@ -197,7 +197,7 @@ class FaceRecognitionConfig(FrigateBaseModel):
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title="Min face recognitions 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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default=200, ge=0, title="Number of face attempts to save in the train tab."
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)
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blur_confidence_filter: bool = Field(
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default=True, title="Apply blur quality filter to face confidence."
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