def extract_one_face(self, alignment, image):
""" Extract one face from image """
logger.trace("Extracting one face: (frame: '%s', alignment: %s)",
self.current_frame, alignment)
face = DetectedFace()
face.from_alignment(alignment, image=image)
face.load_aligned(image, size=self.size, align_eyes=self.align_eyes)
return face
def extract_one_face(self, alignment, image):
""" Extract one face from image """
logger.trace("Extracting one face: (frame: '%s', alignment: %s)",
self.current_frame, alignment)
face = DetectedFace()
face.from_alignment(alignment, image=image)
face.load_aligned(image, size=self.size, align_eyes=self.align_eyes)
return face
def extract_one_face(self, alignment, image):
""" Extract one face from image """
face = DetectedFace()
face.from_alignment(alignment, image=image)
face.load_aligned(image,
size=self.size,
padding=self.padding,
align_eyes=self.align_eyes)
return face
def transform_landmarks(self, alignments):
""" For each face transform landmarks and return """
landmarks = dict()
for _, faces, _, _ in alignments.yield_faces():
for face in faces:
detected_face = DetectedFace()
detected_face.from_alignment(face)
detected_face.load_aligned(None, size=self.size, align_eyes=False)
landmarks[detected_face.hash] = detected_face.aligned_landmarks
return landmarks
def align_face(self, faces, align_eyes, size, filename):
""" Align the detected face and add the destination file path """
final_faces = list()
image = faces["image"]
landmarks = faces["landmarks"]
detected_faces = faces["detected_faces"]
for idx, face in enumerate(detected_faces):
detected_face = DetectedFace()
detected_face.from_dlib_rect(face, image)
detected_face.landmarksXY = landmarks[idx]
detected_face.load_aligned(image, size=size, align_eyes=align_eyes)
final_faces.append({"file_location": self.output_dir / Path(filename).stem,
"face": detected_face})
faces["detected_faces"] = final_faces
def align_face(self, faces, align_eyes, size, filename):
""" Align the detected face and add the destination file path """
final_faces = list()
image = faces["image"]
landmarks = faces["landmarks"]
detected_faces = faces["detected_faces"]
for idx, face in enumerate(detected_faces):
detected_face = DetectedFace()
detected_face.from_bounding_box(face, image)
detected_face.landmarksXY = landmarks[idx]
detected_face.load_aligned(image, size=size, align_eyes=align_eyes)
final_faces.append({"file_location": self.output_dir / Path(filename).stem,
"face": detected_face})
faces["detected_faces"] = final_faces
def load_aligned_face(self):
""" Align the faces for vgg_face input """
for filename, face in self.filters.items():
logger.debug("Loading aligned face: '%s'", filename)
bounding_box = face["detected_faces"][0]
image = face["image"]
landmarks = face["landmarks"][0]
detected_face = DetectedFace()
detected_face.from_bounding_box_dict(bounding_box, image)
detected_face.landmarksXY = landmarks
detected_face.load_aligned(image, size=224)
face["face"] = detected_face.aligned_face
del face["image"]
logger.debug("Loaded aligned face: ('%s', shape: %s)", filename,
face["face"].shape)
def align_face(faces, align_eyes, size, padding=48):
""" Align the detected face """
final_faces = list()
image = faces["image"]
landmarks = faces["landmarks"]
detected_faces = faces["detected_faces"]
for idx, face in enumerate(detected_faces):
detected_face = DetectedFace()
detected_face.from_dlib_rect(face, image)
detected_face.landmarksXY = landmarks[idx]
detected_face.frame_dims = image.shape[:2]
detected_face.load_aligned(image,
size=size,
padding=padding,
align_eyes=align_eyes)
final_faces.append(detected_face)
faces["detected_faces"] = final_faces
