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H64, H128, DF, LIAEF128: added pixel loss option.

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iperov 2019-02-11 12:05:54 +04:00
commit f8e63970d2
5 changed files with 52 additions and 34 deletions
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14
models/Model_DF/Model.py
View file

@ -4,13 +4,21 @@ from nnlib import nnlib
from models import ModelBase
from facelib import FaceType
from samples import *
from utils.console_utils import *
class Model(ModelBase):
encoderH5 = 'encoder.h5'
decoder_srcH5 = 'decoder_src.h5'
decoder_dstH5 = 'decoder_dst.h5'
#override
def onInitializeOptions(self, is_first_run, ask_override):
if is_first_run or ask_override:
self.options['pixel_loss'] = self.options['pixel_loss'] = input_bool ("Use pixel loss? (y/n, ?:help skip: n/default ) : ", False, help_message="Default DSSIM loss good for initial understanding structure of faces. Use pixel loss after 30-40k epochs to enhance fine details and remove face jitter.")
else:
self.options['pixel_loss'] = self.options.get('pixel_loss', False)
#override
def onInitialize(self, **in_options):
exec(nnlib.import_all(), locals(), globals())
@ -29,8 +37,8 @@ class Model(ModelBase):
self.autoencoder_src = Model([ae_input_layer,mask_layer], self.decoder_src(self.encoder(ae_input_layer)))
self.autoencoder_dst = Model([ae_input_layer,mask_layer], self.decoder_dst(self.encoder(ae_input_layer)))
self.autoencoder_src.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMaskLoss([mask_layer]), 'mse'] )
self.autoencoder_dst.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMaskLoss([mask_layer]), 'mse'] )
self.autoencoder_src.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMSEMaskLoss(mask_layer, is_mse=self.options['pixel_loss']), 'mse'] )
self.autoencoder_dst.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMSEMaskLoss(mask_layer, is_mse=self.options['pixel_loss']), 'mse'] )
if self.is_training_mode:
f = SampleProcessor.TypeFlags

7
models/Model_H128/Model.py
View file

@ -22,6 +22,11 @@ class Model(ModelBase):
self.options.pop ('created_vram_gb')
self.options['lighter_ae'] = self.options.get('lighter_ae', default_lighter_ae)
if is_first_run or ask_override:
self.options['pixel_loss'] = self.options['pixel_loss'] = input_bool ("Use pixel loss? (y/n, ?:help skip: n/default ) : ", False, help_message="Default DSSIM loss good for initial understanding structure of faces. Use pixel loss after 30-40k epochs to enhance fine details and remove face jitter.")
else:
self.options['pixel_loss'] = self.options.get('pixel_loss', False)
#override
def onInitialize(self, **in_options):
exec(nnlib.import_all(), locals(), globals())
@ -44,7 +49,7 @@ class Model(ModelBase):
self.ae = Model([input_src_bgr,input_src_mask,input_dst_bgr,input_dst_mask], [rec_src_bgr, rec_src_mask, rec_dst_bgr, rec_dst_mask] )
self.ae.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999),
loss=[ DSSIMMaskLoss([input_src_mask]), 'mae', DSSIMMaskLoss([input_dst_mask]), 'mae' ] )
loss=[ DSSIMMSEMaskLoss(input_src_mask, is_mse=self.options['pixel_loss']), 'mae', DSSIMMSEMaskLoss(input_dst_mask, is_mse=self.options['pixel_loss']), 'mae' ] )
self.src_view = K.function([input_src_bgr],[rec_src_bgr, rec_src_mask])
self.dst_view = K.function([input_dst_bgr],[rec_dst_bgr, rec_dst_mask])

12
models/Model_H64/Model.py
View file

@ -21,7 +21,12 @@ class Model(ModelBase):
if 'created_vram_gb' in self.options.keys():
self.options.pop ('created_vram_gb')
self.options['lighter_ae'] = self.options.get('lighter_ae', default_lighter_ae)
if is_first_run or ask_override:
self.options['pixel_loss'] = self.options['pixel_loss'] = input_bool ("Use pixel loss? (y/n, ?:help skip: n/default ) : ", False, help_message="Default DSSIM loss good for initial understanding structure of faces. Use pixel loss after 30-40k epochs to enhance fine details and remove face jitter.")
else:
self.options['pixel_loss'] = self.options.get('pixel_loss', False)
#override
def onInitialize(self, **in_options):
exec(nnlib.import_all(), locals(), globals())
@ -44,9 +49,8 @@ class Model(ModelBase):
rec_dst_bgr, rec_dst_mask = self.decoder_dst( self.encoder(input_dst_bgr) )
self.ae = Model([input_src_bgr,input_src_mask,input_dst_bgr,input_dst_mask], [rec_src_bgr, rec_src_mask, rec_dst_bgr, rec_dst_mask] )
self.ae.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999),
loss=[ DSSIMMaskLoss([input_src_mask]), 'mae', DSSIMMaskLoss([input_dst_mask]), 'mae' ] )
self.ae.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[ DSSIMMSEMaskLoss(input_src_mask, is_mse=self.options['pixel_loss']), 'mae', DSSIMMSEMaskLoss(input_dst_mask, is_mse=self.options['pixel_loss']), 'mae' ] )
self.src_view = K.function([input_src_bgr],[rec_src_bgr, rec_src_mask])
self.dst_view = K.function([input_dst_bgr],[rec_dst_bgr, rec_dst_mask])

14
models/Model_LIAEF128/Model.py
View file

@ -4,6 +4,7 @@ from nnlib import nnlib
from models import ModelBase
from facelib import FaceType
from samples import *
from utils.console_utils import *
class Model(ModelBase):
@ -11,7 +12,14 @@ class Model(ModelBase):
decoderH5 = 'decoder.h5'
inter_BH5 = 'inter_B.h5'
inter_ABH5 = 'inter_AB.h5'
#override
def onInitializeOptions(self, is_first_run, ask_override):
if is_first_run or ask_override:
self.options['pixel_loss'] = self.options['pixel_loss'] = input_bool ("Use pixel loss? (y/n, ?:help skip: n/default ) : ", False, help_message="Default DSSIM loss good for initial understanding structure of faces. Use pixel loss after 30-40k epochs to enhance fine details and remove face jitter.")
else:
self.options['pixel_loss'] = self.options.get('pixel_loss', False)
#override
def onInitialize(self, **in_options):
exec(nnlib.import_all(), locals(), globals())
@ -34,8 +42,8 @@ class Model(ModelBase):
self.autoencoder_src = Model([ae_input_layer,mask_layer], self.decoder(Concatenate()([AB, AB])) )
self.autoencoder_dst = Model([ae_input_layer,mask_layer], self.decoder(Concatenate()([B, AB])) )
self.autoencoder_src.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMaskLoss([mask_layer]), 'mse'] )
self.autoencoder_dst.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMaskLoss([mask_layer]), 'mse'] )
self.autoencoder_src.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMSEMaskLoss(mask_layer, is_mse=self.options['pixel_loss']), 'mse'] )
self.autoencoder_dst.compile(optimizer=Adam(lr=5e-5, beta_1=0.5, beta_2=0.999), loss=[DSSIMMSEMaskLoss(mask_layer, is_mse=self.options['pixel_loss']), 'mse'] )
if self.is_training_mode:
f = SampleProcessor.TypeFlags