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New script:

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5.XSeg) data_dst/src mask for XSeg trainer - fetch.bat
Copies faces containing XSeg polygons to aligned_xseg\ dir.
Useful only if you want to collect labeled faces and reuse them in other fakes.

Now you can use trained XSeg mask in the SAEHD training process.
It’s mean default ‘full_face’ mask obtained from landmarks will be replaced with the mask obtained from the trained XSeg model.
use
5.XSeg.optional) trained mask for data_dst/data_src - apply.bat
5.XSeg.optional) trained mask for data_dst/data_src - remove.bat

Normally you don’t need it. You can use it, if you want to use ‘face_style’ and ‘bg_style’ with obstructions.

XSeg trainer : now you can choose type of face
XSeg trainer : now you can restart training in “override settings”
Merger: XSeg-* modes now can be used with all types of faces.

Therefore old MaskEditor, FANSEG models, and FAN-x modes have been removed,
because the new XSeg solution is better, simpler and more convenient, which costs only 1 hour of manual masking for regular deepfake.
This commit is contained in:
Colombo 2020-03-30 14:00:40 +04:00
parent e5bad483ca
commit 6d3607a13d
30 changed files with 279 additions and 1520 deletions
Download patch file Download diff file Expand all files Collapse all files

18
facelib/LandmarksProcessor.py
View file

@ -9,7 +9,6 @@ import numpy.linalg as npla
from core import imagelib
from core import mathlib
from facelib import FaceType
from core.imagelib import IEPolys
from core.mathlib.umeyama import umeyama
landmarks_2D = np.array([
@ -374,7 +373,7 @@ def expand_eyebrows(lmrks, eyebrows_expand_mod=1.0):
def get_image_hull_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0, ie_polys=None ):
def get_image_hull_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0 ):
hull_mask = np.zeros(image_shape[0:2]+(1,),dtype=np.float32)
lmrks = expand_eyebrows(image_landmarks, eyebrows_expand_mod)
@ -393,9 +392,6 @@ def get_image_hull_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0,
merged = np.concatenate(item)
cv2.fillConvexPoly(hull_mask, cv2.convexHull(merged), (1,) )
if ie_polys is not None:
ie_polys.overlay_mask(hull_mask)
return hull_mask
def get_image_eye_mask (image_shape, image_landmarks):
@ -647,13 +643,13 @@ def mirror_landmarks (landmarks, val):
result[:,0] = val - result[:,0] - 1
return result
def get_face_struct_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0, ie_polys=None, color=(1,) ):
def get_face_struct_mask (image_shape, image_landmarks, eyebrows_expand_mod=1.0, color=(1,) ):
mask = np.zeros(image_shape[0:2]+( len(color),),dtype=np.float32)
lmrks = expand_eyebrows(image_landmarks, eyebrows_expand_mod)
draw_landmarks (mask, image_landmarks, color=color, draw_circles=False, thickness=2, ie_polys=ie_polys)
draw_landmarks (mask, image_landmarks, color=color, draw_circles=False, thickness=2)
return mask
def draw_landmarks (image, image_landmarks, color=(0,255,0), draw_circles=True, thickness=1, transparent_mask=False, ie_polys=None):
def draw_landmarks (image, image_landmarks, color=(0,255,0), draw_circles=True, thickness=1, transparent_mask=False):
if len(image_landmarks) != 68:
raise Exception('get_image_eye_mask works only with 68 landmarks')
@ -683,11 +679,11 @@ def draw_landmarks (image, image_landmarks, color=(0,255,0), draw_circles=True,
cv2.circle(image, (x, y), 2, color, lineType=cv2.LINE_AA)
if transparent_mask:
mask = get_image_hull_mask (image.shape, image_landmarks, ie_polys=ie_polys)
mask = get_image_hull_mask (image.shape, image_landmarks)
image[...] = ( image * (1-mask) + image * mask / 2 )[...]
def draw_rect_landmarks (image, rect, image_landmarks, face_type, face_size=256, 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)
def draw_rect_landmarks (image, rect, image_landmarks, face_type, face_size=256, transparent_mask=False, landmarks_color=(0,255,0)):
draw_landmarks(image, image_landmarks, color=landmarks_color, transparent_mask=transparent_mask)
imagelib.draw_rect (image, rect, (255,0,0), 2 )
image_to_face_mat = get_transform_mat (image_landmarks, face_size, face_type)