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added experimental face type 'whole_face'

Browse source 
Basic usage instruction: https://i.imgur.com/w7LkId2.jpg

	'whole_face' requires skill in Adobe After Effects.

	For using whole_face you have to extract whole_face's by using
	4) data_src extract whole_face
	and
	5) data_dst extract whole_face
	Images will be extracted in 512 resolution, so they can be used for regular full_face's and half_face's.

	'whole_face' covers whole area of face include forehead in training square,
	but training mask is still 'full_face'
	therefore it requires manual final masking and composing in Adobe After Effects.

added option 'masked_training'
	This option is available only for 'whole_face' type.
	Default is ON.
	Masked training clips training area to full_face mask,
	thus network will train the faces properly.
	When the face is trained enough, disable this option to train all area of the frame.
	Merge with 'raw-rgb' mode, then use Adobe After Effects to manually mask, tune color, and compose whole face include forehead.
This commit is contained in:
Colombo 2020-02-21 16:21:04 +04:00
parent 778fb94246
commit f1d115b63b
10 changed files with 74 additions and 58 deletions
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7
facelib/FaceType.py
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@ -6,8 +6,9 @@ class FaceType(IntEnum):
MID_FULL = 1
FULL = 2
FULL_NO_ALIGN = 3
HEAD = 4
HEAD_NO_ALIGN = 5
WHOLE_FACE = 4
HEAD = 5
HEAD_NO_ALIGN = 6
MARK_ONLY = 10, #no align at all, just embedded faceinfo
@ -25,6 +26,7 @@ class FaceType(IntEnum):
from_string_dict = {'half_face': FaceType.HALF,
'midfull_face': FaceType.MID_FULL,
'full_face': FaceType.FULL,
'whole_face': FaceType.WHOLE_FACE,
'head' : FaceType.HEAD,
'mark_only' : FaceType.MARK_ONLY,
'full_face_no_align' : FaceType.FULL_NO_ALIGN,
@ -33,6 +35,7 @@ from_string_dict = {'half_face': FaceType.HALF,
to_string_dict = { FaceType.HALF : 'half_face',
FaceType.MID_FULL : 'midfull_face',
FaceType.FULL : 'full_face',
FaceType.WHOLE_FACE : 'whole_face',
FaceType.HEAD : 'head',
FaceType.MARK_ONLY :'mark_only',
FaceType.FULL_NO_ALIGN : 'full_face_no_align',