mirror of
https://github.com/iperov/DeepFaceLab.git
synced 2025-07-10 15:23:32 -07:00
removing trailing spaces
This commit is contained in:
iperov
parent
fa4e579b95
commit
a3df04999c
61 changed files with 2110 additions and 2103 deletions
|
|
@ -36,7 +36,7 @@ landmarks_68_pt = { "mouth": (48,68),
|
|||
"left_eye": (42, 48),
|
||||
"nose": (27, 36), # missed one point
|
||||
"jaw": (0, 17) }
|
||||
|
||||
|
||||
|
||||
landmarks_68_3D = np.array( [
|
||||
[-73.393523 , -29.801432 , 47.667532 ],
|
||||
|
|
@ -107,20 +107,20 @@ landmarks_68_3D = np.array( [
|
|||
[8.449166 , 30.596216 , -20.671489 ],
|
||||
[0.205322 , 31.408738 , -21.903670 ],
|
||||
[-7.198266 , 30.844876 , -20.328022 ] ], dtype=np.float32)
|
||||
|
||||
|
||||
def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
|
||||
if not isinstance(image_landmarks, np.ndarray):
|
||||
image_landmarks = np.array (image_landmarks)
|
||||
|
||||
image_landmarks = np.array (image_landmarks)
|
||||
|
||||
if face_type == FaceType.AVATAR:
|
||||
centroid = np.mean (image_landmarks, axis=0)
|
||||
|
||||
|
||||
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
|
||||
a, c = mat[0,0], mat[1,0]
|
||||
scale = math.sqrt((a * a) + (c * c))
|
||||
|
||||
|
||||
padding = (output_size / 64) * 32
|
||||
|
||||
|
||||
mat = np.eye ( 2,3 )
|
||||
mat[0,2] = -centroid[0]
|
||||
mat[1,2] = -centroid[1]
|
||||
|
|
@ -135,15 +135,15 @@ def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
|
|||
padding = (output_size / 64) * 24
|
||||
else:
|
||||
raise ValueError ('wrong face_type: ', face_type)
|
||||
|
||||
|
||||
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
|
||||
mat = mat * (output_size - 2 * padding)
|
||||
mat[:,2] += padding
|
||||
mat[:,2] += padding
|
||||
mat *= (1 / scale)
|
||||
mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 )
|
||||
|
||||
|
||||
return mat
|
||||
|
||||
|
||||
def transform_points(points, mat, invert=False):
|
||||
if invert:
|
||||
mat = cv2.invertAffineTransform (mat)
|
||||
|
|
@ -151,68 +151,68 @@ def transform_points(points, mat, invert=False):
|
|||
points = cv2.transform(points, mat, points.shape)
|
||||
points = np.squeeze(points)
|
||||
return points
|
||||
|
||||
|
||||
def get_image_hull_mask (image_shape, image_landmarks):
|
||||
|
||||
|
||||
def get_image_hull_mask (image_shape, image_landmarks):
|
||||
if len(image_landmarks) != 68:
|
||||
raise Exception('get_image_hull_mask works only with 68 landmarks')
|
||||
|
||||
|
||||
hull_mask = np.zeros(image_shape[0:2]+(1,),dtype=np.float32)
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[0:9],
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[0:9],
|
||||
image_landmarks[17:18]))) , (1,) )
|
||||
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[8:17],
|
||||
np.concatenate ( (image_landmarks[8:17],
|
||||
image_landmarks[26:27]))) , (1,) )
|
||||
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[17:20],
|
||||
np.concatenate ( (image_landmarks[17:20],
|
||||
image_landmarks[8:9]))) , (1,) )
|
||||
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[24:27],
|
||||
np.concatenate ( (image_landmarks[24:27],
|
||||
image_landmarks[8:9]))) , (1,) )
|
||||
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[19:25],
|
||||
np.concatenate ( (image_landmarks[19:25],
|
||||
image_landmarks[8:9],
|
||||
))) , (1,) )
|
||||
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[17:22],
|
||||
np.concatenate ( (image_landmarks[17:22],
|
||||
image_landmarks[27:28],
|
||||
image_landmarks[31:36],
|
||||
image_landmarks[8:9]
|
||||
))) , (1,) )
|
||||
|
||||
))) , (1,) )
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
|
||||
np.concatenate ( (image_landmarks[22:27],
|
||||
np.concatenate ( (image_landmarks[22:27],
|
||||
image_landmarks[27:28],
|
||||
image_landmarks[31:36],
|
||||
image_landmarks[8:9]
|
||||
))) , (1,) )
|
||||
|
||||
))) , (1,) )
|
||||
|
||||
#nose
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull(image_landmarks[27:36]), (1,) )
|
||||
|
||||
|
||||
return hull_mask
|
||||
|
||||
def get_image_eye_mask (image_shape, image_landmarks):
|
||||
def get_image_eye_mask (image_shape, image_landmarks):
|
||||
if len(image_landmarks) != 68:
|
||||
raise Exception('get_image_eye_mask works only with 68 landmarks')
|
||||
|
||||
|
||||
hull_mask = np.zeros(image_shape[0:2]+(1,),dtype=np.float32)
|
||||
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull( image_landmarks[36:42]), (1,) )
|
||||
cv2.fillConvexPoly( hull_mask, cv2.convexHull( image_landmarks[42:48]), (1,) )
|
||||
|
||||
|
||||
return hull_mask
|
||||
|
||||
def get_image_hull_mask_3D (image_shape, image_landmarks):
|
||||
|
||||
def get_image_hull_mask_3D (image_shape, image_landmarks):
|
||||
result = get_image_hull_mask(image_shape, image_landmarks)
|
||||
|
||||
|
||||
return np.repeat ( result, (3,), -1 )
|
||||
|
||||
def blur_image_hull_mask (hull_mask):
|
||||
|
|
@ -224,7 +224,7 @@ def blur_image_hull_mask (hull_mask):
|
|||
leny = maxy - miny;
|
||||
masky = int(minx+(lenx//2))
|
||||
maskx = int(miny+(leny//2))
|
||||
lowest_len = min (lenx, leny)
|
||||
lowest_len = min (lenx, leny)
|
||||
ero = int( lowest_len * 0.085 )
|
||||
blur = int( lowest_len * 0.10 )
|
||||
|
||||
|
|
@ -233,10 +233,10 @@ def blur_image_hull_mask (hull_mask):
|
|||
hull_mask = np.expand_dims (hull_mask,-1)
|
||||
|
||||
return hull_mask
|
||||
|
||||
def get_blurred_image_hull_mask(image_shape, image_landmarks):
|
||||
|
||||
def get_blurred_image_hull_mask(image_shape, image_landmarks):
|
||||
return blur_image_hull_mask ( get_image_hull_mask(image_shape, image_landmarks) )
|
||||
|
||||
|
||||
mirror_idxs = [
|
||||
[0,16],
|
||||
[1,15],
|
||||
|
|
@ -246,23 +246,23 @@ mirror_idxs = [
|
|||
[5,11],
|
||||
[6,10],
|
||||
[7,9],
|
||||
|
||||
|
||||
[17,26],
|
||||
[18,25],
|
||||
[19,24],
|
||||
[20,23],
|
||||
[21,22],
|
||||
|
||||
[21,22],
|
||||
|
||||
[36,45],
|
||||
[37,44],
|
||||
[38,43],
|
||||
[39,42],
|
||||
[40,47],
|
||||
[41,46],
|
||||
|
||||
[41,46],
|
||||
|
||||
[31,35],
|
||||
[32,34],
|
||||
|
||||
|
||||
[50,52],
|
||||
[49,53],
|
||||
[48,54],
|
||||
|
|
@ -271,28 +271,28 @@ mirror_idxs = [
|
|||
[67,65],
|
||||
[60,64],
|
||||
[61,63] ]
|
||||
|
||||
def mirror_landmarks (landmarks, val):
|
||||
|
||||
def mirror_landmarks (landmarks, val):
|
||||
result = landmarks.copy()
|
||||
|
||||
|
||||
for idx in mirror_idxs:
|
||||
result [ idx ] = result [ idx[::-1] ]
|
||||
|
||||
result[:,0] = val - result[:,0] - 1
|
||||
return result
|
||||
|
||||
|
||||
def draw_landmarks (image, image_landmarks, color=(0,255,0), transparent_mask=False):
|
||||
if len(image_landmarks) != 68:
|
||||
raise Exception('get_image_eye_mask works only with 68 landmarks')
|
||||
|
||||
jaw = image_landmarks[slice(*landmarks_68_pt["jaw"])]
|
||||
raise Exception('get_image_eye_mask works only with 68 landmarks')
|
||||
|
||||
jaw = image_landmarks[slice(*landmarks_68_pt["jaw"])]
|
||||
right_eyebrow = image_landmarks[slice(*landmarks_68_pt["right_eyebrow"])]
|
||||
left_eyebrow = image_landmarks[slice(*landmarks_68_pt["left_eyebrow"])]
|
||||
mouth = image_landmarks[slice(*landmarks_68_pt["mouth"])]
|
||||
right_eye = image_landmarks[slice(*landmarks_68_pt["right_eye"])]
|
||||
left_eye = image_landmarks[slice(*landmarks_68_pt["left_eye"])]
|
||||
nose = image_landmarks[slice(*landmarks_68_pt["nose"])]
|
||||
|
||||
mouth = image_landmarks[slice(*landmarks_68_pt["mouth"])]
|
||||
right_eye = image_landmarks[slice(*landmarks_68_pt["right_eye"])]
|
||||
left_eye = image_landmarks[slice(*landmarks_68_pt["left_eye"])]
|
||||
nose = image_landmarks[slice(*landmarks_68_pt["nose"])]
|
||||
|
||||
# open shapes
|
||||
cv2.polylines(image, tuple(np.array([v]) for v in ( right_eyebrow, jaw, left_eyebrow, np.concatenate((nose, [nose[-6]])) )),
|
||||
False, color, lineType=cv2.LINE_AA)
|
||||
|
|
@ -303,9 +303,9 @@ def draw_landmarks (image, image_landmarks, color=(0,255,0), transparent_mask=Fa
|
|||
for x, y in np.concatenate((right_eyebrow, left_eyebrow, mouth, right_eye, left_eye, nose), axis=0):
|
||||
cv2.circle(image, (x, y), 1, color, 1, lineType=cv2.LINE_AA)
|
||||
# jaw big circles
|
||||
for x, y in jaw:
|
||||
for x, y in jaw:
|
||||
cv2.circle(image, (x, y), 2, color, lineType=cv2.LINE_AA)
|
||||
|
||||
|
||||
if transparent_mask:
|
||||
mask = get_image_hull_mask (image.shape, image_landmarks)
|
||||
image[...] = ( image * (1-mask) + image * mask / 2 )[...]
|
||||
|
|
@ -314,24 +314,24 @@ def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, tra
|
|||
draw_landmarks(image, image_landmarks, color=landmarks_color, transparent_mask=transparent_mask)
|
||||
image_utils.draw_rect (image, rect, (255,0,0), 2 )
|
||||
|
||||
image_to_face_mat = get_transform_mat (image_landmarks, face_size, face_type)
|
||||
image_to_face_mat = get_transform_mat (image_landmarks, face_size, face_type)
|
||||
points = transform_points ( [ (0,0), (0,face_size-1), (face_size-1, face_size-1), (face_size-1,0) ], image_to_face_mat, True)
|
||||
image_utils.draw_polygon (image, points, (0,0,255), 2)
|
||||
|
||||
image_utils.draw_polygon (image, points, (0,0,255), 2)
|
||||
|
||||
def calc_face_pitch(landmarks):
|
||||
if not isinstance(landmarks, np.ndarray):
|
||||
landmarks = np.array (landmarks)
|
||||
t = ( (landmarks[6][1]-landmarks[8][1]) + (landmarks[10][1]-landmarks[8][1]) ) / 2.0
|
||||
t = ( (landmarks[6][1]-landmarks[8][1]) + (landmarks[10][1]-landmarks[8][1]) ) / 2.0
|
||||
b = landmarks[8][1]
|
||||
return float(b-t)
|
||||
|
||||
|
||||
def calc_face_yaw(landmarks):
|
||||
if not isinstance(landmarks, np.ndarray):
|
||||
landmarks = np.array (landmarks)
|
||||
l = ( (landmarks[27][0]-landmarks[0][0]) + (landmarks[28][0]-landmarks[1][0]) + (landmarks[29][0]-landmarks[2][0]) ) / 3.0
|
||||
l = ( (landmarks[27][0]-landmarks[0][0]) + (landmarks[28][0]-landmarks[1][0]) + (landmarks[29][0]-landmarks[2][0]) ) / 3.0
|
||||
r = ( (landmarks[16][0]-landmarks[27][0]) + (landmarks[15][0]-landmarks[28][0]) + (landmarks[14][0]-landmarks[29][0]) ) / 3.0
|
||||
return float(r-l)
|
||||
|
||||
|
||||
#returns pitch,yaw [-1...+1]
|
||||
def estimate_pitch_yaw(aligned_256px_landmarks):
|
||||
shape = (256,256)
|
||||
|
|
@ -347,8 +347,8 @@ def estimate_pitch_yaw(aligned_256px_landmarks):
|
|||
aligned_256px_landmarks.astype(np.float32),
|
||||
camera_matrix,
|
||||
np.zeros((4, 1)) )
|
||||
|
||||
|
||||
pitch, yaw, _ = mathlib.rotationMatrixToEulerAngles( cv2.Rodrigues(rotation_vector)[0] )
|
||||
pitch = np.clip ( pitch*1.25, -1.0, 1.0 )
|
||||
yaw = np.clip ( yaw*1.25, -1.0, 1.0 )
|
||||
return pitch, yaw
|
||||
return pitch, yaw
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue