* Remove tracked object update resets

* Adjust face blur reduction

* Add space for config editor buttons

* Slight adjustment

* Fix double thats

* update icons

---------

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
This commit is contained in:
Nicolas Mowen
2025-06-19 09:20:33 -06:00
committed by GitHub
parent 42cae5d9ee
commit fe571dc217
7 changed files with 26 additions and 41 deletions

View File

@@ -108,21 +108,24 @@ class FaceRecognizer(ABC):
image, M, (output_width, output_height), flags=cv2.INTER_CUBIC
)
def get_blur_confidence_reduction(self, input: np.ndarray) -> tuple[float, float]:
def get_blur_confidence_reduction(self, input: np.ndarray) -> float:
"""Calculates the reduction in confidence based on the blur of the image."""
if not self.config.face_recognition.blur_confidence_filter:
return 0, 0.0
return 0.0
variance = cv2.Laplacian(input, cv2.CV_64F).var()
logger.debug(f"face detected with blurriness {variance}")
if variance < 80: # image is very blurry
return variance, 0.05
elif variance < 100: # image moderately blurry
return variance, 0.03
elif variance < 150: # image is slightly blurry
return variance, 0.01
if variance < 120: # image is very blurry
return 0.06
elif variance < 160: # image moderately blurry
return 0.04
elif variance < 200: # image is slightly blurry
return 0.02
elif variance < 250: # image is mostly clear
return 0.01
else:
return variance, 0.0
return 0.0
def similarity_to_confidence(
@@ -234,8 +237,7 @@ class FaceNetRecognizer(FaceRecognizer):
# face recognition is best run on grayscale images
# get blur factor before aligning face
variance, blur_reduction = self.get_blur_confidence_reduction(face_image)
logger.debug(f"face detected with blurriness {variance}")
blur_reduction = self.get_blur_confidence_reduction(face_image)
# align face and run recognition
img = self.align_face(face_image, face_image.shape[1], face_image.shape[0])
@@ -345,8 +347,7 @@ class ArcFaceRecognizer(FaceRecognizer):
# face recognition is best run on grayscale images
# get blur reduction before aligning face
variance, blur_reduction = self.get_blur_confidence_reduction(face_image)
logger.debug(f"face detected with blurriness {variance}")
blur_reduction = self.get_blur_confidence_reduction(face_image)
# align face and run recognition
img = self.align_face(face_image, face_image.shape[1], face_image.shape[0])

View File

@@ -1579,19 +1579,6 @@ class LicensePlateProcessingMixin:
if object_id in self.camera_current_cars.get(camera, []):
self.camera_current_cars[camera].remove(object_id)
if len(self.camera_current_cars[camera]) == 0:
self.requestor.send_data(
"tracked_object_update",
json.dumps(
{
"type": TrackedObjectUpdateTypesEnum.lpr,
"name": None,
"plate": None,
"camera": camera,
}
),
)
class CTCDecoder:
"""

View File

@@ -444,18 +444,6 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
if object_id in self.camera_current_people.get(camera, []):
self.camera_current_people[camera].remove(object_id)
if len(self.camera_current_people[camera]) == 0:
self.requestor.send_data(
"tracked_object_update",
json.dumps(
{
"type": TrackedObjectUpdateTypesEnum.face,
"name": None,
"camera": camera,
}
),
)
def weighted_average(
self, results_list: list[tuple[str, float, int]], max_weight: int = 4000
):