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Make detection threhsold configurable (#17136)
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@ -55,7 +55,13 @@ class FaceRecognitionConfig(FrigateBaseModel):
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gt=0.0,
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gt=0.0,
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le=1.0,
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le=1.0,
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)
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)
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threshold: float = Field(
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detection_threshold: float = Field(
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default=0.7,
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title="Minimum face detection score required to be considered a face.",
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gt=0.0,
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le=1.0,
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)
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recognition_threshold: float = Field(
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default=0.9,
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default=0.9,
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title="Minimum face distance score required to be considered a match.",
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title="Minimum face distance score required to be considered a match.",
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gt=0.0,
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gt=0.0,
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@ -88,7 +88,7 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
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os.path.join(MODEL_CACHE_DIR, "facedet/facedet.onnx"),
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os.path.join(MODEL_CACHE_DIR, "facedet/facedet.onnx"),
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config="",
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config="",
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input_size=(320, 320),
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input_size=(320, 320),
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score_threshold=0.8,
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score_threshold=self.face_config.detection_threshold,
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nms_threshold=0.3,
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nms_threshold=0.3,
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)
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)
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self.landmark_detector = cv2.face.createFacemarkLBF()
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self.landmark_detector = cv2.face.createFacemarkLBF()
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@ -367,9 +367,9 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
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os.makedirs(folder, exist_ok=True)
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os.makedirs(folder, exist_ok=True)
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cv2.imwrite(file, face_frame)
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cv2.imwrite(file, face_frame)
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if score < self.config.face_recognition.threshold:
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if score < self.config.face_recognition.recognition_threshold:
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logger.debug(
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logger.debug(
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f"Recognized face distance {score} is less than threshold {self.config.face_recognition.threshold}"
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f"Recognized face distance {score} is less than threshold {self.config.face_recognition.recognition_threshold}"
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)
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)
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self.__update_metrics(datetime.datetime.now().timestamp() - start)
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self.__update_metrics(datetime.datetime.now().timestamp() - start)
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return
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return
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