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Adjust blur confidence reduction

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This commit is contained in:
Nicolas Mowen 2025-06-02 13:08:59 -06:00
parent 3c3b0f620a
commit fa94dfad13
1 changed files with 16 additions and 16 deletions
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32
frigate/data_processing/common/face/model.py
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@ -108,21 +108,21 @@ class FaceRecognizer(ABC):
image, M, (output_width, output_height), flags=cv2.INTER_CUBIC image, M, (output_width, output_height), flags=cv2.INTER_CUBIC
) )
def get_blur_factor(self, input: np.ndarray) -> float: def get_blur_confidence_reduction(self, input: np.ndarray) -> tuple[float, float]:
"""Calculates the factor for the confidence based on the blur of the image.""" """Calculates the reduction in confidence based on the blur of the image."""
if not self.config.face_recognition.blur_confidence_filter: if not self.config.face_recognition.blur_confidence_filter:
return 1.0 return 1.0
variance = cv2.Laplacian(input, cv2.CV_64F).var() variance = cv2.Laplacian(input, cv2.CV_64F).var()
if variance < 60: # image is very blurry if variance < 80: # image is very blurry
return 0.96 return variance, 0.05
elif variance < 70: # image moderately blurry elif variance < 100: # image moderately blurry
return 0.98 return variance, 0.03
elif variance < 80: # image is slightly blurry elif variance < 150: # image is slightly blurry
return 0.99 return variance, 0.01
else: else:
return 1.0 return variance, 0.0
def similarity_to_confidence( def similarity_to_confidence(
@ -234,8 +234,8 @@ class FaceNetRecognizer(FaceRecognizer):
# face recognition is best run on grayscale images # face recognition is best run on grayscale images
# get blur factor before aligning face # get blur factor before aligning face
blur_factor = self.get_blur_factor(face_image) variance, blur_reduction = self.get_blur_confidence_reduction(face_image)
logger.debug(f"face detected with blurriness {blur_factor}") logger.debug(f"face detected with blurriness {variance}")
# align face and run recognition # align face and run recognition
img = self.align_face(face_image, face_image.shape[1], face_image.shape[0]) img = self.align_face(face_image, face_image.shape[1], face_image.shape[0])
@ -258,7 +258,7 @@ class FaceNetRecognizer(FaceRecognizer):
score = confidence score = confidence
label = name label = name
return label, round(score * blur_factor, 2) return label, round(score - blur_reduction, 2)
class ArcFaceRecognizer(FaceRecognizer): class ArcFaceRecognizer(FaceRecognizer):
@ -344,9 +344,9 @@ class ArcFaceRecognizer(FaceRecognizer):
# face recognition is best run on grayscale images # face recognition is best run on grayscale images
# get blur factor before aligning face # get blur reduction before aligning face
blur_factor = self.get_blur_factor(face_image) variance, blur_reduction = self.get_blur_confidence_reduction(face_image)
logger.debug(f"face detected with blurriness {blur_factor}") logger.debug(f"face detected with blurriness {variance}")
# align face and run recognition # align face and run recognition
img = self.align_face(face_image, face_image.shape[1], face_image.shape[0]) img = self.align_face(face_image, face_image.shape[1], face_image.shape[0])
@ -367,4 +367,4 @@ class ArcFaceRecognizer(FaceRecognizer):
score = confidence score = confidence
label = name label = name
return label, round(score * blur_factor, 2) return label, round(score - blur_reduction, 2)