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fixed training added support for custom masks in training

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sinofis 2020-12-27 16:46:16 +01:00
commit 0c84554b65
2 changed files with 6 additions and 3 deletions
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4
facelib/FaceType.py
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@ -7,6 +7,7 @@ class FaceType(IntEnum):
FULL = 2
FULL_NO_ALIGN = 3
WHOLE_FACE = 4
CUSTOM = 5
HEAD = 10
HEAD_NO_ALIGN = 20
@ -30,7 +31,8 @@ to_string_dict = { FaceType.HALF : 'half_face',
FaceType.WHOLE_FACE : 'whole_face',
FaceType.HEAD : 'head',
FaceType.HEAD_NO_ALIGN : 'head_no_align',
FaceType.CUSTOM : 'mve_custom',
FaceType.MARK_ONLY :'mark_only',
}

5
models/Model_SAEHD/Model.py
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@ -76,7 +76,7 @@ class SAEHDModel(ModelBase):
resolution = io.input_int("Resolution", default_resolution, add_info="64-640", help_message="More resolution requires more VRAM and time to train. Value will be adjusted to multiple of 16 and 32 for -d archi.")
resolution = np.clip ( (resolution // 16) * 16, min_res, max_res)
self.options['resolution'] = resolution
self.options['face_type'] = io.input_str ("Face type", default_face_type, ['h','mf','f','wf','head'], help_message="Half / mid face / full face / whole face / head. Half face has better resolution, but covers less area of cheeks. Mid face is 30% wider than half face. 'Whole face' covers full area of face include forehead. 'head' covers full head, but requires XSeg for src and dst faceset.").lower()
self.options['face_type'] = io.input_str ("Face type", default_face_type, ['h','mf','f','wf','head', 'custom'], help_message="Half / mid face / full face / whole face / head / custom. Half face has better resolution, but covers less area of cheeks. Mid face is 30% wider than half face. 'Whole face' covers full area of face include forehead. 'head' covers full head, but requires XSeg for src and dst faceset.").lower()
while True:
archi = io.input_str ("AE architecture", default_archi, help_message=\
@ -131,7 +131,7 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
self.options['d_mask_dims'] = d_mask_dims + d_mask_dims % 2
if self.is_first_run() or ask_override:
if self.options['face_type'] == 'wf' or self.options['face_type'] == 'head':
if self.options['face_type'] == 'wf' or self.options['face_type'] == 'head' or self.options['face_type'] == 'custom':
self.options['masked_training'] = io.input_bool ("Masked training", default_masked_training, help_message="This option is available only for 'whole_face' or 'head' type. Masked training clips training area to full_face mask or XSeg mask, thus network will train the faces properly.")
self.options['eyes_prio'] = io.input_bool ("Eyes priority", default_eyes_prio, help_message='Helps to fix eye problems during training like "alien eyes" and wrong eyes direction ( especially on HD architectures ) by forcing the neural network to train eyes with higher priority. before/after https://i.imgur.com/YQHOuSR.jpg ')
@ -184,6 +184,7 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
'mf' : FaceType.MID_FULL,
'f' : FaceType.FULL,
'wf' : FaceType.WHOLE_FACE,
'custom' : FaceType.CUSTOM,
'head' : FaceType.HEAD}[ self.options['face_type'] ]
eyes_prio = self.options['eyes_prio']