def process_single_face(self, idx, face, filename, image):
""" Perform processing on found faces """
output_file = self.output_dir / Path(
filename).stem if self.export_face else None
self.faces.draw_landmarks_on_face(face, image)
resized_face, t_mat = self.faces.extractor.extract(
image, face, 256, self.faces.align_eyes)
blurry_file = self.faces.detect_blurry_faces(face, t_mat, resized_face,
filename)
output_file = blurry_file if blurry_file else output_file
if self.export_face:
filename = "{}_{}{}".format(str(output_file), str(idx),
Path(filename).suffix)
Utils.cv2_read_write('write', filename, resized_face)
return {
"r": face.r,
"x": face.x,
"w": face.w,
"y": face.y,
"h": face.h,
"landmarksXY": face.landmarksAsXY()
}
def process_single_face(self, idx, face, filename, image):
""" Perform processing on found faces """
output_file = self.output_dir / Path(
filename).stem if self.export_face else None
self.faces.draw_landmarks_on_face(face, image)
resized_face, t_mat = self.faces.extractor.extract(
image,
face,
256,
self.faces.align_eyes)
blurry_file = self.faces.detect_blurry_faces(face,
t_mat,
resized_face,
filename)
output_file = blurry_file if blurry_file else output_file
if self.export_face:
filename = "{}_{}{}".format(str(output_file),
str(idx),
Path(filename).suffix)
Utils.cv2_read_write('write', filename, resized_face)
return {"r": face.r,
"x": face.x,
"w": face.w,
"y": face.y,
"h": face.h,
"landmarksXY": face.landmarks_as_xy()}
def convert(self, converter, item):
""" Apply the conversion transferring faces onto frames """
try:
filename, image, faces = item
skip = self.opts.check_skipframe(filename)
if not skip:
for idx, face in faces:
# --- Changes ---
if self.write_image_mask:
image, image_mask = self.convert_one_face(
converter, (filename, image, idx, face),
return_image_mask=self.write_image_mask)
# --- Changes ---
image = self.convert_one_face(
converter, (filename, image, idx, face))
if skip != "discard":
filename = str(self.output_dir / Path(filename).name)
Utils.cv2_read_write('write', filename, image)
# --- Changes ---
if self.write_image_mask:
# Writes image into a mask folder, be careful with that if
# you write multiple images
os.makedirs(self.write_image_mask, exist_ok=True)
Utils.cv2_read_write(
'write',
os.path.join(self.write_image_mask,
filename.split('/')[-1]), image_mask)
# --- Changes ---
except Exception as err:
print("Failed to convert image: {}. "
"Reason: {}".format(filename, err))
def convert(self, converter, item):
""" Apply the conversion transferring faces onto frames """
try:
filename, image, faces = item
skip = self.opts.check_skipframe(filename)
if not skip:
for idx, face in faces:
image = self.convert_one_face(converter, (filename, image, idx, face))
if skip != "discard":
filename = str(self.output_dir / Path(filename).name)
Utils.cv2_read_write('write', filename, image)
except Exception as err:
print("Failed to convert image: {}. Reason: {}".format(filename, err))
def convert(self, converter, item):
""" Apply the conversion transferring faces onto frames """
try:
filename, image, faces = item
skip = self.opts.check_skipframe(filename)
if not skip:
for idx, face in faces:
image = self.convert_one_face(converter, (filename, image, idx, face))
if skip != "discard":
filename = str(self.output_dir / Path(filename).name)
Utils.cv2_read_write('write', filename, image)
except Exception as err:
print("Failed to convert image: {}. Reason: {}".format(filename, err))
def process_single_image(self, filename):
""" Detect faces in an image. Rotate the image the specified amount
until at least one face is found, or until image rotations are
depleted.
Once at least one face has been detected, pass to process_single_face
to process the individual faces """
retval = filename, list()
try:
image = Utils.cv2_read_write('read', filename)
for angle in self.images.rotation_angles:
image = Utils.rotate_image_by_angle(image, angle)
faces = self.faces.get_faces(image, angle)
process_faces = [(idx, face) for idx, face in faces]
if process_faces and angle != 0 and self.args.verbose:
print("found face(s) by rotating image {} degrees".format(
angle))
if process_faces:
break
final_faces = [
self.process_single_face(idx, face, filename, image)
for idx, face in process_faces
]
retval = filename, final_faces
except Exception as err:
if self.args.verbose:
print("Failed to extract from image: {}. Reason: {}".format(
filename, err))
return retval
def process_single_image(self, filename):
""" Detect faces in an image. Rotate the image the specified amount
until at least one face is found, or until image rotations are
depleted.
Once at least one face has been detected, pass to
process_single_face to process the individual faces """
retval = filename, list()
try:
image = Utils.cv2_read_write('read', filename)
for angle in self.images.rotation_angles:
currentimage = Utils.rotate_image_by_angle(image, angle)
faces = self.faces.get_faces(currentimage, angle)
process_faces = [(idx, face) for idx, face in faces]
if process_faces and angle != 0 and self.args.verbose:
print("found face(s) by rotating image {} degrees".format(angle))
if process_faces:
break
final_faces = [self.process_single_face(idx, face, filename, currentimage)
for idx, face in process_faces]
retval = filename, final_faces
except Exception as err:
if self.args.verbose:
print("Failed to extract from image: {}. Reason: {}".format(filename, err))
return retval
def prepare_images(self):
""" Prepare the images for conversion """
filename = ""
for filename in tqdm(self.images.input_images, file=sys.stdout):
if not self.check_alignments(filename):
continue
image = Utils.cv2_read_write('read', filename)
faces = self.faces.get_faces_alignments(filename, image)
if not faces:
continue
yield filename, image, faces
def prepare_images(self):
""" Prepare the images for conversion """
filename = ""
for filename in tqdm(self.images.input_images, file=sys.stdout):
if not self.check_alignments(filename):
continue
image = Utils.cv2_read_write('read', filename)
faces = self.faces.get_faces_alignments(filename, image)
if not faces:
continue
yield filename, image, faces
