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more stable and precise version of face transformation matrix

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Colombo 2019-12-19 15:25:06 +04:00
parent c04740eac1
commit 853a056769
1 changed files with 28 additions and 46 deletions
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74
facelib/LandmarksProcessor.py
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@ -183,6 +183,15 @@ landmarks_68_3D = np.array( [
[0.205322 , 31.408738 , -21.903670 ],
[-7.198266 , 30.844876 , -20.328022 ] ], dtype=np.float32)
FaceType_to_padding_remove_align = {
FaceType.HALF: (0.0, False),
FaceType.MID_FULL: (0.06, False),
FaceType.FULL: (0.1875, False),
FaceType.FULL_NO_ALIGN: (0.1875, True),
FaceType.HEAD: (0.328125, False),
FaceType.HEAD_NO_ALIGN: (0.328125, True),
}
def convert_98_to_68(lmrks):
#jaw
result = [ lmrks[0] ]
@ -244,62 +253,35 @@ 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)
padding, remove_align = FaceType_to_padding_remove_align.get(face_type, 0.0)
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]
mat = mat * scale * (output_size / 3)
mat[:,2] += output_size / 2
else:
"""
remove_align = False
if face_type == FaceType.FULL_NO_ALIGN:
face_type = FaceType.FULL
remove_align = True
elif face_type == FaceType.HEAD_NO_ALIGN:
face_type = FaceType.HEAD
remove_align = True
if face_type == FaceType.HALF:
padding = 0
elif face_type == FaceType.MID_FULL:
padding = int(output_size * 0.06)
elif face_type == FaceType.FULL:
padding = (output_size / 64) * 12
elif face_type == FaceType.HEAD:
padding = (output_size / 64) * 21
else:
raise ValueError ('wrong face_type: ', face_type)
#mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
mat = umeyama( np.concatenate ( [ image_landmarks[17:49] , image_landmarks[54:55] ] ) , landmarks_2D_new, True)[0:2]
mat = mat * (output_size - 2 * padding)
mat[:,2] += padding
mat *= (1 / scale)
mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 )
l_p = transform_points ( np.float32([(0,0),(1,0),(1,1),(0,1),(0.5,0.5)]) , mat, True)
tb_diag_vec = (l_p[2]-l_p[0]).astype(np.float32)
tb_diag_vec /= npla.norm(tb_diag_vec)
bt_diag_vec = (l_p[1]-l_p[3]).astype(np.float32)
bt_diag_vec /= npla.norm(bt_diag_vec)
mod = (1.0 / scale)* ( output_size*padding*np.sqrt(2.0) + npla.norm(l_p[0]-l_p[4]) )
l_c = l_p[4]
l_0 = np.round( l_c - tb_diag_vec*mod )
l_1 = np.round( l_c + bt_diag_vec*mod )
l_2 = np.round( l_c + tb_diag_vec*mod )
pts1 = np.float32(( l_0, l_1, l_2 ))
pts2 = np.float32(( (0,0),(output_size,0),(output_size,output_size) ))
mat = cv2.getAffineTransform(pts1,pts2)
if remove_align:
bbox = transform_points ( [ (0,0), (0,output_size-1), (output_size-1, output_size-1), (output_size-1,0) ], mat, True)
bbox = transform_points ( [ (0,0), (0,output_size), (output_size, output_size), (output_size,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]])
pts1 = np.float32(( center+[-side,-side], center+[side,-side], center+[-side,side] ))
pts2 = np.float32(((0,0),(output_size,0),(0,output_size)))
mat = cv2.getAffineTransform(pts1,pts2)
return mat
def expand_eyebrows(lmrks, eyebrows_expand_mod=1.0):
if len(lmrks) != 68:
raise Exception('works only with 68 landmarks')
@ -627,7 +609,7 @@ def draw_rect_landmarks (image, rect, image_landmarks, face_size, face_type, tra
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)
imagelib.draw_polygon (image, points, (0,0,255), 2)
points = transform_points ( [ ( int(face_size*0.05), 0), ( int(face_size*0.1), int(face_size*0.1) ), ( 0, int(face_size*0.1) ) ], image_to_face_mat, True)
imagelib.draw_polygon (image, points, (0,0,255), 2)