def process(self, output_item):
""" Detect and move blurry face """
extractor = AlignerExtract()
for idx, detected_face in enumerate(output_item["detected_faces"]):
frame_name = detected_face["file_location"].parts[-1]
face = detected_face["face"]
logger.trace("Checking for blurriness. Frame: '%s', Face: %s", frame_name, idx)
aligned_landmarks = face.aligned_landmarks
resized_face = face.aligned_face
size = face.aligned["size"]
padding = int(size * 0.1875)
feature_mask = extractor.get_feature_mask(
aligned_landmarks / size,
size, padding)
feature_mask = cv2.blur( # pylint: disable=no-member
feature_mask, (10, 10))
isolated_face = cv2.multiply( # pylint: disable=no-member
feature_mask,
resized_face.astype(float)).astype(np.uint8)
blurry, focus_measure = self.is_blurry(isolated_face)
if blurry:
blur_folder = detected_face["file_location"].parts[:-1]
blur_folder = get_folder(Path(*blur_folder) / Path("blurry"))
detected_face["file_location"] = blur_folder / Path(frame_name)
logger.verbose("%s's focus measure of %s was below the blur threshold, "
"moving to 'blurry'", frame_name, "{0:.2f}".format(focus_measure))
def process(self, output_item):
""" Detect and move blurry face """
extractor = AlignerExtract()
for idx, detected_face in enumerate(output_item["detected_faces"]):
frame_name = detected_face["file_location"].parts[-1]
face = detected_face["face"]
logger.trace("Checking for blurriness. Frame: '%s', Face: %s",
frame_name, idx)
aligned_landmarks = face.aligned_landmarks
resized_face = face.aligned_face
size = face.aligned["size"]
padding = int(size * 0.1875)
feature_mask = extractor.get_feature_mask(aligned_landmarks / size,
size, padding)
feature_mask = cv2.blur(feature_mask, (10, 10))
isolated_face = cv2.multiply(feature_mask,
resized_face.astype(float)).astype(
np.uint8)
blurry, focus_measure = self.is_blurry(isolated_face)
if blurry:
blur_folder = detected_face["file_location"].parts[:-1]
blur_folder = get_folder(Path(*blur_folder) / Path("blurry"))
detected_face["file_location"] = blur_folder / Path(frame_name)
logger.verbose(
"%s's focus measure of %s was below the blur threshold, "
"moving to 'blurry'", frame_name,
"{0:.2f}".format(focus_measure))
def process(self, output_item):
""" Detect and move blurry face """
extractor = AlignerExtract()
for face in output_item["detected_faces"]:
aligned_landmarks = face.aligned_landmarks
resized_face = face.aligned_face
size = face.aligned["size"]
feature_mask = extractor.get_feature_mask(
aligned_landmarks / size,
size, 48)
feature_mask = cv2.blur( # pylint: disable=no-member
feature_mask, (10, 10))
isolated_face = cv2.multiply( # pylint: disable=no-member
feature_mask,
resized_face.astype(float)).astype(np.uint8)
blurry, focus_measure = is_blurry(isolated_face, self.blur_thresh)
if blurry:
blur_folder = output_item["output_file"].parts[:-1]
blur_folder = get_folder(Path(*blur_folder) / Path("blurry"))
frame_name = output_item["output_file"].parts[-1]
output_item["output_file"] = blur_folder / Path(frame_name)
if self.verbose:
print("{}'s focus measure of {} was below the blur "
"threshold, moving to \"blurry\"".format(
frame_name, focus_measure))