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update == 04.20.2019 == (#242)

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* superb improved fanseg

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* added FANseg extractor for src and dst faces to use it in training

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* update to 'partial' func

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* trained FANSeg_256_full_face.h5,
new experimental models: AVATAR, RecycleGAN

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* fix for TCC mode cards(tesla), was conflict with plaidML initialization.

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* update manuals

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iperov 2019-04-20 08:23:08 +04:00 • committed by GitHub
parent 7be2fd67f5
commit 046649e6be
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32 changed files with 1152 additions and 329 deletions
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22
nnlib/nnlib.py
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@ -52,7 +52,7 @@ Input = KL.Input
Dense = KL.Dense
Conv2D = nnlib.Conv2D
Conv2DTranspose = KL.Conv2DTranspose
Conv2DTranspose = nnlib.Conv2DTranspose
SeparableConv2D = KL.SeparableConv2D
MaxPooling2D = KL.MaxPooling2D
UpSampling2D = KL.UpSampling2D
@ -695,6 +695,26 @@ NLayerDiscriminator = nnlib.NLayerDiscriminator
x = ReflectionPadding2D( self.pad ) (x)
return self.func(x)
nnlib.Conv2D = Conv2D
class Conv2DTranspose():
def __init__ (self, *args, **kwargs):
self.reflect_pad = False
padding = kwargs.get('padding','')
if padding == 'zero':
kwargs['padding'] = 'same'
if padding == 'reflect':
kernel_size = kwargs['kernel_size']
if (kernel_size % 2) == 1:
self.pad = (kernel_size // 2,)*2
kwargs['padding'] = 'valid'
self.reflect_pad = True
self.func = keras.layers.Conv2DTranspose (*args, **kwargs)
def __call__(self,x):
if self.reflect_pad:
x = ReflectionPadding2D( self.pad ) (x)
return self.func(x)
nnlib.Conv2DTranspose = Conv2DTranspose
@staticmethod
def import_keras_contrib(device_config):