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Converter: added Apply super resolution? (y/n skip:n) : , Enhance details by applying DCSCN network.

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refactorings
This commit is contained in:
iperov 2019-03-28 21:50:27 +04:00
parent 4683c362ac
commit 85c01e3b4a
12 changed files with 271 additions and 77 deletions
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15
models/Model_SAE/Model.py
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@ -406,13 +406,12 @@ class SAEModel(ModelBase):
return [ ('SAE', np.concatenate (st, axis=0 )), ]
def predictor_func (self, face):
prd = [ x[0] for x in self.AE_convert ( [ face[np.newaxis,:,:,0:3] ] ) ]
if not self.options['learn_mask']:
prd += [ face[...,3:4] ]
return np.concatenate ( prd, -1 )
if self.options['learn_mask']:
bgr, mask = self.AE_convert ([face[np.newaxis,...]])
return bgr[0], mask[0][...,0]
else:
bgr, = self.AE_convert ([face[np.newaxis,...]])
return bgr[0]
#override
def get_converter(self):
@ -428,7 +427,7 @@ class SAEModel(ModelBase):
from converters import ConverterMasked
return ConverterMasked(self.predictor_func,
predictor_input_size=self.options['resolution'],
output_size=self.options['resolution'],
predictor_masked=self.options['learn_mask'],
face_type=face_type,
default_mode = 1 if self.options['face_style_power'] or self.options['bg_style_power'] else 4,
base_erode_mask_modifier=base_erode_mask_modifier,