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fixed error "Failed to get convolution algorithm" on some systems

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fixed error "dll load failed" on some systems
Expanded eyebrows line of face masks. It does not affect mask of FAN-x converter mode.
This commit is contained in:
iperov
2019-08-11 11:17:22 +04:00
parent 582c974851
commit b72d5a3f9a
15 changed files with 367 additions and 222 deletions
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facelib/FaceType.py
+12 -12
View File
@@ -4,10 +4,10 @@ class FaceType(IntEnum):
HALF = 0,
FULL = 1,
HEAD = 2,
AVATAR = 3, #centered nose only
MARK_ONLY = 4, #no align at all, just embedded faceinfo
QTY = 5
FULL_NO_ALIGN = 5,
MARK_ONLY = 10, #no align at all, just embedded faceinfo
@staticmethod
def fromString (s):
r = from_string_dict.get (s.lower())
@@ -17,17 +17,17 @@ class FaceType(IntEnum):
@staticmethod
def toString (face_type):
return to_string_list[face_type]
return to_string_dict[face_type]
from_string_dict = {'half_face': FaceType.HALF,
'full_face': FaceType.FULL,
'head' : FaceType.HEAD,
'avatar' : FaceType.AVATAR,
'mark_only' : FaceType.MARK_ONLY,
'full_face_no_align' : FaceType.FULL_NO_ALIGN,
}
to_string_list = [ 'half_face',
'full_face',
'head',
'avatar',
'mark_only'
]
to_string_dict = { FaceType.HALF : 'half_face',
FaceType.FULL : 'full_face',
FaceType.HEAD : 'head',
FaceType.MARK_ONLY :'mark_only',
FaceType.FULL_NO_ALIGN : 'full_face_no_align'
}
facelib/LandmarksProcessor.py
+67 -55
View File
@@ -109,10 +109,19 @@ landmarks_68_3D = np.array( [
[0.205322 , 31.408738 , -21.903670 ],
[-7.198266 , 30.844876 , -20.328022 ] ], dtype=np.float32)
def transform_points(points, mat, invert=False):
if invert:
mat = cv2.invertAffineTransform (mat)
points = np.expand_dims(points, axis=1)
points = cv2.transform(points, mat, points.shape)
points = np.squeeze(points)
return points
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)
"""
if face_type == FaceType.AVATAR:
centroid = np.mean (image_landmarks, axis=0)
@@ -128,76 +137,79 @@ def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
mat = mat * scale * (output_size / 3)
mat[:,2] += output_size / 2
else:
if face_type == FaceType.HALF:
padding = 0
elif face_type == FaceType.FULL:
padding = (output_size / 64) * 12
elif face_type == FaceType.HEAD:
padding = (output_size / 64) * 24
else:
raise ValueError ('wrong face_type: ', face_type)
"""
remove_align = False
if face_type == FaceType.FULL_NO_ALIGN:
face_type = FaceType.FULL
remove_align = True
if face_type == FaceType.HALF:
padding = 0
elif face_type == FaceType.FULL:
padding = (output_size / 64) * 12
elif face_type == FaceType.HEAD:
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 *= (1 / scale)
mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 )
mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
mat = mat * (output_size - 2 * padding)
mat[:,2] += padding
mat *= (1 / scale)
mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 )
if remove_align:
bbox = transform_points ( [ (0,0), (0,output_size-1), (output_size-1, output_size-1), (output_size-1,0) ], mat, True)
area = mathlib.polygon_area(bbox[:,0], bbox[:,1] )
side = math.sqrt(area) / 2
center = transform_points ( [(output_size/2,output_size/2)], mat, True)
pts1 = np.float32([ center+[-side,-side], center+[side,-side], center+[-side,side] ])
pts2 = np.float32([[0,0],[output_size-1,0],[0,output_size-1]])
mat = cv2.getAffineTransform(pts1,pts2)
return mat
def transform_points(points, mat, invert=False):
if invert:
mat = cv2.invertAffineTransform (mat)
points = np.expand_dims(points, axis=1)
points = cv2.transform(points, mat, points.shape)
points = np.squeeze(points)
return points
def get_image_hull_mask (image_shape, image_landmarks, ie_polys=None):
if len(image_landmarks) != 68:
raise Exception('get_image_hull_mask works only with 68 landmarks')
int_lmrks = np.array(image_landmarks, dtype=np.int)
int_lmrks = np.array(image_landmarks.copy(), dtype=np.int)
hull_mask = np.zeros(image_shape[0:2]+(1,),dtype=np.float32)
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[0:9],
int_lmrks[17:18]))) , (1,) )
# #nose
ml_pnt = (int_lmrks[36] + int_lmrks[0]) // 2
mr_pnt = (int_lmrks[16] + int_lmrks[45]) // 2
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[8:17],
int_lmrks[26:27]))) , (1,) )
# mid points between the mid points and eye
ql_pnt = (int_lmrks[36] + ml_pnt) // 2
qr_pnt = (int_lmrks[45] + mr_pnt) // 2
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[17:20],
int_lmrks[8:9]))) , (1,) )
# Top of the eye arrays
bot_l = np.array((ql_pnt, int_lmrks[36], int_lmrks[37], int_lmrks[38], int_lmrks[39]))
bot_r = np.array((int_lmrks[42], int_lmrks[43], int_lmrks[44], int_lmrks[45], qr_pnt))
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[24:27],
int_lmrks[8:9]))) , (1,) )
# Eyebrow arrays
top_l = int_lmrks[17:22]
top_r = int_lmrks[22:27]
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[19:25],
int_lmrks[8:9],
))) , (1,) )
# Adjust eyebrow arrays
int_lmrks[17:22] = top_l + ((top_l - bot_l) // 2)
int_lmrks[22:27] = top_r + ((top_r - bot_r) // 2)
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[17:22],
int_lmrks[27:28],
int_lmrks[31:36],
int_lmrks[8:9]
))) , (1,) )
r_jaw = (int_lmrks[0:9], int_lmrks[17:18])
l_jaw = (int_lmrks[8:17], int_lmrks[26:27])
r_cheek = (int_lmrks[17:20], int_lmrks[8:9])
l_cheek = (int_lmrks[24:27], int_lmrks[8:9])
nose_ridge = (int_lmrks[19:25], int_lmrks[8:9],)
r_eye = (int_lmrks[17:22], int_lmrks[27:28], int_lmrks[31:36], int_lmrks[8:9])
l_eye = (int_lmrks[22:27], int_lmrks[27:28], int_lmrks[31:36], int_lmrks[8:9])
nose = (int_lmrks[27:31], int_lmrks[31:36])
parts = [r_jaw, l_jaw, r_cheek, l_cheek, nose_ridge, r_eye, l_eye, nose]
cv2.fillConvexPoly( hull_mask, cv2.convexHull(
np.concatenate ( (int_lmrks[22:27],
int_lmrks[27:28],
int_lmrks[31:36],
int_lmrks[8:9]
))) , (1,) )
#nose
cv2.fillConvexPoly( hull_mask, cv2.convexHull(int_lmrks[27:36]), (1,) )
for item in parts:
merged = np.concatenate(item)
cv2.fillConvexPoly(hull_mask, cv2.convexHull(merged), 1)
if ie_polys is not None:
ie_polys.overlay_mask(hull_mask)
@@ -309,7 +321,7 @@ def draw_landmarks (image, image_landmarks, color=(0,255,0), transparent_mask=Fa
mask = get_image_hull_mask (image.shape, image_landmarks, ie_polys)
image[...] = ( image * (1-mask) + image * mask / 2 )[...]
def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, transparent_mask=False, ie_polys=None, landmarks_color=(0,255,0) ):
def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, transparent_mask=False, ie_polys=None, landmarks_color=(0,255,0)):
draw_landmarks(image, image_landmarks, color=landmarks_color, transparent_mask=transparent_mask, ie_polys=ie_polys)
imagelib.draw_rect (image, rect, (255,0,0), 2 )