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SAEHD:

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added new experimental arhi
'liaech' - made by @chervoniy. Based on liae, but produces more src-like face.
This commit is contained in:
Colombo 2020-03-07 16:06:10 +04:00
parent 0bac399841
commit 45270f3fb5
1 changed files with 10 additions and 8 deletions
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18
models/Model_SAEHD/Model.py
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@ -62,7 +62,7 @@ class SAEHDModel(ModelBase):
resolution = np.clip ( (resolution // 16) * 16, 64, 512)
self.options['resolution'] = resolution
self.options['face_type'] = io.input_str ("Face type", default_face_type, ['h','mf','f','wf'], help_message="Half / mid face / full face / whole face. 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, but requires manual merge in Adobe After Effects.").lower()
self.options['archi'] = io.input_str ("AE architecture", default_archi, ['dfhd','liaehd','df','liae'], help_message="'df' keeps faces more natural. 'liae' can fix overly different face shapes. 'hd' is heavyweight version for the best quality.").lower()
self.options['archi'] = io.input_str ("AE architecture", default_archi, ['df','liae','dfhd','liaehd','liaech'], help_message="'df' keeps faces more natural.\n'liae' can fix overly different face shapes.\n'hd' are experimental versions.\n'liaech' - new experimental model by @chervoniy. Based on liae, but produces more src-like face.").lower()
default_d_dims = 48 if self.options['archi'] == 'dfhd' else 64
default_d_dims = self.options['d_dims'] = self.load_or_def_option('d_dims', default_d_dims)
@ -125,8 +125,6 @@ class SAEHDModel(ModelBase):
nn.initialize(data_format=self.model_data_format)
tf = nn.tf
Encoder, Inter, Decoder = nn.get_ae_models()
device_config = nn.getCurrentDeviceConfig()
devices = device_config.devices
@ -163,8 +161,6 @@ class SAEHDModel(ModelBase):
output_ch = 3
bgr_shape = nn.get4Dshape(resolution,resolution,input_ch)
mask_shape = nn.get4Dshape(resolution,resolution,1)
lowest_dense_res = resolution // 16
self.model_filename_list = []
@ -180,12 +176,18 @@ class SAEHDModel(ModelBase):
self.target_dstm_all = tf.placeholder (nn.tf_floatx, mask_shape)
# Initializing model classes
if archi == 'liaech':
lowest_dense_res, Encoder, Inter, Decoder = nn.get_ae_models_chervoniy(resolution)
else:
lowest_dense_res, Encoder, Inter, Decoder = nn.get_ae_models(resolution)
with tf.device (models_opt_device):
if 'df' in archi:
self.encoder = Encoder(in_ch=input_ch, e_ch=e_dims, is_hd=is_hd, name='encoder')
encoder_out_ch = self.encoder.compute_output_channels ( (nn.tf_floatx, bgr_shape))
self.inter = Inter (in_ch=encoder_out_ch, lowest_dense_res=lowest_dense_res, ae_ch=ae_dims, ae_out_ch=ae_dims, is_hd=is_hd, name='inter')
self.inter = Inter (in_ch=encoder_out_ch, ae_ch=ae_dims, ae_out_ch=ae_dims, is_hd=is_hd, name='inter')
inter_out_ch = self.inter.compute_output_channels ( (nn.tf_floatx, (None,encoder_out_ch)))
self.decoder_src = Decoder(in_ch=inter_out_ch, d_ch=d_dims, d_mask_ch=d_mask_dims, is_hd=is_hd, name='decoder_src')
@ -205,8 +207,8 @@ class SAEHDModel(ModelBase):
self.encoder = Encoder(in_ch=input_ch, e_ch=e_dims, is_hd=is_hd, name='encoder')
encoder_out_ch = self.encoder.compute_output_channels ( (nn.tf_floatx, bgr_shape))
self.inter_AB = Inter(in_ch=encoder_out_ch, lowest_dense_res=lowest_dense_res, ae_ch=ae_dims, ae_out_ch=ae_dims*2, is_hd=is_hd, name='inter_AB')
self.inter_B = Inter(in_ch=encoder_out_ch, lowest_dense_res=lowest_dense_res, ae_ch=ae_dims, ae_out_ch=ae_dims*2, is_hd=is_hd, name='inter_B')
self.inter_AB = Inter(in_ch=encoder_out_ch, ae_ch=ae_dims, ae_out_ch=ae_dims*2, is_hd=is_hd, name='inter_AB')
self.inter_B = Inter(in_ch=encoder_out_ch, ae_ch=ae_dims, ae_out_ch=ae_dims*2, is_hd=is_hd, name='inter_B')
inter_AB_out_ch = self.inter_AB.compute_output_channels ( (nn.tf_floatx, (None,encoder_out_ch)))
inter_B_out_ch = self.inter_B.compute_output_channels ( (nn.tf_floatx, (None,encoder_out_ch)))