mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-06 04:52:13 -07:00
fix
This commit is contained in:
iperov
parent
da7cf225db
commit
bf831331e6
1 changed files with 66 additions and 59 deletions
|
|
@ -141,66 +141,73 @@ class ExtractSubprocessor(Subprocessor):
|
|||
if self.debug_dir is not None:
|
||||
debug_output_file = str( Path(self.debug_dir) / (filename_path.stem+'.jpg') )
|
||||
debug_image = image.copy()
|
||||
|
||||
face_idx = 0
|
||||
for face in faces:
|
||||
rect = np.array(face[0])
|
||||
image_landmarks = face[1]
|
||||
if image_landmarks is None:
|
||||
continue
|
||||
image_landmarks = np.array(image_landmarks)
|
||||
|
||||
if self.face_type == FaceType.MARK_ONLY:
|
||||
face_image = image
|
||||
face_image_landmarks = image_landmarks
|
||||
else:
|
||||
image_to_face_mat = LandmarksProcessor.get_transform_mat (image_landmarks, self.image_size, self.face_type)
|
||||
face_image = cv2.warpAffine(image, image_to_face_mat, (self.image_size, self.image_size), cv2.INTER_LANCZOS4)
|
||||
face_image_landmarks = LandmarksProcessor.transform_points (image_landmarks, image_to_face_mat)
|
||||
|
||||
landmarks_bbox = LandmarksProcessor.transform_points ( [ (0,0), (0,self.image_size-1), (self.image_size-1, self.image_size-1), (self.image_size-1,0) ], image_to_face_mat, True)
|
||||
|
||||
rect_area = mathlib.polygon_area(np.array(rect[[0,2,2,0]]), np.array(rect[[1,1,3,3]]))
|
||||
landmarks_area = mathlib.polygon_area(landmarks_bbox[:,0], landmarks_bbox[:,1] )
|
||||
|
||||
if landmarks_area > 4*rect_area: #get rid of faces which umeyama-landmark-area > 4*detector-rect-area
|
||||
continue
|
||||
|
||||
if self.debug_dir is not None:
|
||||
LandmarksProcessor.draw_rect_landmarks (debug_image, rect, image_landmarks, self.image_size, self.face_type, transparent_mask=True)
|
||||
|
||||
output_file = '{}_{}{}'.format(str(self.output_path / filename_path.stem), str(face_idx), '.jpg')
|
||||
face_idx += 1
|
||||
|
||||
landmarks=face_image_landmarks.tolist()
|
||||
source_filename = filename_path.name
|
||||
source_landmarks = image_landmarks.tolist()
|
||||
source_rect = rect
|
||||
if src_dflimg is not None:
|
||||
#if extracting from dflimg copy it in order not to lose quality
|
||||
output_file = str(self.output_path / filename_path.name)
|
||||
if str(filename_path) != str(output_file):
|
||||
shutil.copy ( str(filename_path), str(output_file) )
|
||||
|
||||
#and transfer data
|
||||
source_filename = src_dflimg.get_source_filename()
|
||||
mat = src_dflimg.get_image_to_face_mat()
|
||||
if mat is not None:
|
||||
image_to_face_mat = mat
|
||||
source_landmarks = LandmarksProcessor.transform_points (landmarks, image_to_face_mat, True)
|
||||
else:
|
||||
cv2_imwrite(output_file, face_image, [int(cv2.IMWRITE_JPEG_QUALITY), 85] )
|
||||
|
||||
DFLJPG.embed_data(output_file, face_type=FaceType.toString(self.face_type),
|
||||
landmarks=landmarks,
|
||||
source_filename=source_filename,
|
||||
source_rect=source_rect,
|
||||
source_landmarks=source_landmarks,
|
||||
image_to_face_mat=image_to_face_mat
|
||||
)
|
||||
|
||||
|
||||
if src_dflimg is not None and len(faces) != 1:
|
||||
#if re-extracting from dflimg and more than 1 or zero faces detected - dont process and just copy it
|
||||
print("src_dflimg is not None and len(faces) != 1", str(filename_path) )
|
||||
output_file = str(self.output_path / filename_path.name)
|
||||
if str(filename_path) != str(output_file):
|
||||
shutil.copy ( str(filename_path), str(output_file) )
|
||||
result.append (output_file)
|
||||
|
||||
else:
|
||||
face_idx = 0
|
||||
for face in faces:
|
||||
rect = np.array(face[0])
|
||||
image_landmarks = face[1]
|
||||
if image_landmarks is None:
|
||||
continue
|
||||
image_landmarks = np.array(image_landmarks)
|
||||
|
||||
if self.face_type == FaceType.MARK_ONLY:
|
||||
face_image = image
|
||||
face_image_landmarks = image_landmarks
|
||||
else:
|
||||
image_to_face_mat = LandmarksProcessor.get_transform_mat (image_landmarks, self.image_size, self.face_type)
|
||||
face_image = cv2.warpAffine(image, image_to_face_mat, (self.image_size, self.image_size), cv2.INTER_LANCZOS4)
|
||||
face_image_landmarks = LandmarksProcessor.transform_points (image_landmarks, image_to_face_mat)
|
||||
|
||||
landmarks_bbox = LandmarksProcessor.transform_points ( [ (0,0), (0,self.image_size-1), (self.image_size-1, self.image_size-1), (self.image_size-1,0) ], image_to_face_mat, True)
|
||||
|
||||
rect_area = mathlib.polygon_area(np.array(rect[[0,2,2,0]]), np.array(rect[[1,1,3,3]]))
|
||||
landmarks_area = mathlib.polygon_area(landmarks_bbox[:,0], landmarks_bbox[:,1] )
|
||||
|
||||
if landmarks_area > 4*rect_area: #get rid of faces which umeyama-landmark-area > 4*detector-rect-area
|
||||
continue
|
||||
|
||||
if self.debug_dir is not None:
|
||||
LandmarksProcessor.draw_rect_landmarks (debug_image, rect, image_landmarks, self.image_size, self.face_type, transparent_mask=True)
|
||||
|
||||
landmarks=face_image_landmarks.tolist()
|
||||
source_filename = filename_path.name
|
||||
source_landmarks = image_landmarks.tolist()
|
||||
source_rect = rect
|
||||
if src_dflimg is not None:
|
||||
#if extracting from dflimg copy it in order not to lose quality
|
||||
output_file = str(self.output_path / filename_path.name)
|
||||
if str(filename_path) != str(output_file):
|
||||
shutil.copy ( str(filename_path), str(output_file) )
|
||||
|
||||
#and transfer data
|
||||
source_filename = src_dflimg.get_source_filename()
|
||||
mat = src_dflimg.get_image_to_face_mat()
|
||||
if mat is not None:
|
||||
image_to_face_mat = mat
|
||||
source_landmarks = LandmarksProcessor.transform_points (landmarks, image_to_face_mat, True)
|
||||
else:
|
||||
output_file = '{}_{}{}'.format(str(self.output_path / filename_path.stem), str(face_idx), '.jpg')
|
||||
cv2_imwrite(output_file, face_image, [int(cv2.IMWRITE_JPEG_QUALITY), 85] )
|
||||
|
||||
DFLJPG.embed_data(output_file, face_type=FaceType.toString(self.face_type),
|
||||
landmarks=landmarks,
|
||||
source_filename=source_filename,
|
||||
source_rect=source_rect,
|
||||
source_landmarks=source_landmarks,
|
||||
image_to_face_mat=image_to_face_mat
|
||||
)
|
||||
|
||||
result.append (output_file)
|
||||
face_idx += 1
|
||||
|
||||
if self.debug_dir is not None:
|
||||
cv2_imwrite(debug_output_file, debug_image, [int(cv2.IMWRITE_JPEG_QUALITY), 50] )
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue