DeepFaceLab/samplelib
Colombo 01d81674fd added new XSegEditor !
here new whole_face + XSeg workflow:

with XSeg model you can train your own mask segmentator for dst(and/or src) faces
that will be used by the merger for whole_face.

Instead of using a pretrained segmentator model (which does not exist),
you control which part of faces should be masked.

new scripts:
	5.XSeg) data_dst edit masks.bat
	5.XSeg) data_src edit masks.bat
	5.XSeg) train.bat

Usage:
	unpack dst faceset if packed

	run 5.XSeg) data_dst edit masks.bat

	Read tooltips on the buttons (en/ru/zn languages are supported)

	mask the face using include or exclude polygon mode.

	repeat for 50/100 faces,
		!!! you don't need to mask every frame of dst
		only frames where the face is different significantly,
		for example:
			closed eyes
			changed head direction
			changed light
		the more various faces you mask, the more quality you will get

		Start masking from the upper left area and follow the clockwise direction.
		Keep the same logic of masking for all frames, for example:
			the same approximated jaw line of the side faces, where the jaw is not visible
			the same hair line
		Mask the obstructions using exclude polygon mode.

	run XSeg) train.bat
		train the model

		Check the faces of 'XSeg dst faces' preview.

		if some faces have wrong or glitchy mask, then repeat steps:
			run edit
			find these glitchy faces and mask them
			train further or restart training from scratch

Restart training of XSeg model is only possible by deleting all 'model\XSeg_*' files.

If you want to get the mask of the predicted face (XSeg-prd mode) in merger,
you should repeat the same steps for src faceset.

New mask modes available in merger for whole_face:

XSeg-prd	  - XSeg mask of predicted face	-> faces from src faceset should be labeled
XSeg-dst	  - XSeg mask of dst face        	-> faces from dst faceset should be labeled
XSeg-prd*XSeg-dst - the smallest area of both

if workspace\model folder contains trained XSeg model, then merger will use it,
otherwise you will get transparent mask by using XSeg-* modes.

Some screenshots:
XSegEditor: https://i.imgur.com/7Bk4RRV.jpg
trainer   : https://i.imgur.com/NM1Kn3s.jpg
merger    : https://i.imgur.com/glUzFQ8.jpg

example of the fake using 13 segmented dst faces
          : https://i.imgur.com/wmvyizU.gifv
2020-03-24 12:15:31 +04:00
..
__init__.py added XSeg model. 2020-03-15 15:12:44 +04:00
PackedFaceset.py optimized face sample generator, CPU load is significantly reduced 2020-01-28 12:24:45 +04:00
Sample.py added new XSegEditor ! 2020-03-24 12:15:31 +04:00
SampleGeneratorBase.py refactoring 2020-03-08 23:19:04 +04:00
SampleGeneratorFace.py global refactoring and fixes, 2020-03-13 08:09:00 +04:00
SampleGeneratorFaceCelebAMaskHQ.py global refactoring and fixes, 2020-03-13 08:09:00 +04:00
SampleGeneratorFacePerson.py refactoring 2020-03-08 23:19:04 +04:00
SampleGeneratorFaceTemporal.py refactoring 2020-03-08 23:19:04 +04:00
SampleGeneratorFaceXSeg.py added new XSegEditor ! 2020-03-24 12:15:31 +04:00
SampleGeneratorImage.py added XSeg model 2020-03-09 13:09:46 +04:00
SampleGeneratorImageTemporal.py refactoring 2020-03-08 23:19:04 +04:00
SampleLoader.py DFLIMG refactoring 2020-03-21 01:18:15 +04:00
SampleProcessor.py DFLIMG refactoring 2020-03-21 01:18:15 +04:00