New script:

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.

DFLIMG/DFLJPG.py

@@ -7,7 +7,7 @@ import numpy as np
 from core.interact import interact as io
 from core.structex import *
 from facelib import FaceType
-
+from core.imagelib import SegIEPolys
 
 class DFLJPG(object):
     def __init__(self, filename):
@@ -151,17 +151,6 @@ class DFLJPG(object):
             print (e)
             return None
 
-    @staticmethod
-    def embed_dfldict(filename, dfl_dict):
-        inst = DFLJPG.load_raw (filename)
-        inst.set_dict (dfl_dict)
-
-        try:
-            with open(filename, "wb") as f:
-                f.write ( inst.dump() )
-        except:
-            raise Exception( 'cannot save %s' % (filename) )
-
     def has_data(self):
         return len(self.dfl_dict.keys()) != 0
 
@@ -176,8 +165,10 @@ class DFLJPG(object):
         data = b""
 
         dict_data = self.dfl_dict
+        
+        # Remove None keys
         for key in list(dict_data.keys()):
-            if dict_data[key] is None:
+            if dict_data[key] is None:                
                 dict_data.pop(key)
 
         for chunk in self.chunks:
@@ -251,18 +242,50 @@ class DFLJPG(object):
         return None
     def set_image_to_face_mat(self, image_to_face_mat):   self.dfl_dict['image_to_face_mat'] = image_to_face_mat
 
-    def get_ie_polys(self):             return self.dfl_dict.get('ie_polys',None)
-    def set_ie_polys(self, ie_polys):
-        if ie_polys is not None and \
-           not isinstance(ie_polys, list):
-            ie_polys = ie_polys.dump()
-
-        self.dfl_dict['ie_polys'] = ie_polys
-
-    def get_seg_ie_polys(self): return self.dfl_dict.get('seg_ie_polys',None)
+    def get_seg_ie_polys(self): 
+        d = self.dfl_dict.get('seg_ie_polys',None)
+        if d is not None:
+            d = SegIEPolys.load(d)
+        else:
+            d = SegIEPolys()
+            
+        return d
+        
     def set_seg_ie_polys(self, seg_ie_polys):
+        if seg_ie_polys is not None:        
+            if not isinstance(seg_ie_polys, SegIEPolys):
+                raise ValueError('seg_ie_polys should be instance of SegIEPolys')
+            
+            if seg_ie_polys.has_polys():
+                seg_ie_polys = seg_ie_polys.dump()
+            else:
+                seg_ie_polys = None
+        
         self.dfl_dict['seg_ie_polys'] = seg_ie_polys
 
+    def get_xseg_mask(self): 
+        mask_buf = self.dfl_dict.get('xseg_mask',None)
+        if mask_buf is None:
+            return None
+            
+        img = cv2.imdecode(mask_buf, cv2.IMREAD_UNCHANGED)
+        if len(img.shape) == 2:
+            img = img[...,None]
+            
+        
+        return img.astype(np.float32) / 255.0
+        
+        
+    def set_xseg_mask(self, mask_a):
+        if mask_a is None:
+            self.dfl_dict['xseg_mask'] = None
+            return
+            
+        ret, buf = cv2.imencode( '.png', np.clip( mask_a*255, 0, 255 ).astype(np.uint8) )
+        if not ret:
+            raise Exception("unable to generate PNG data for set_xseg_mask")
+        
+        self.dfl_dict['xseg_mask'] = buf