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removed hsv power from amp and saehd
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seranus
parent
bf783a43eb
commit
1e84097d68
4 changed files with 1 additions and 22 deletions
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@ -46,7 +46,6 @@ class AMPModel(ModelBase):
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default_lr_dropout = self.options['lr_dropout'] = self.load_or_def_option('lr_dropout', 'n')
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default_random_warp = self.options['random_warp'] = self.load_or_def_option('random_warp', True)
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default_random_hsv_power = self.options['random_hsv_power'] = self.load_or_def_option('random_hsv_power', 0.0)
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default_random_downsample = self.options['random_downsample'] = self.load_or_def_option('random_downsample', False)
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default_random_noise = self.options['random_noise'] = self.load_or_def_option('random_noise', False)
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default_random_blur = self.options['random_blur'] = self.load_or_def_option('random_blur', False)
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@ -151,9 +150,6 @@ class AMPModel(ModelBase):
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self.options['random_blur'] = io.input_bool("Enable random blur of samples", default_random_blur, help_message="")
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self.options['random_jpeg'] = io.input_bool("Enable random jpeg compression of samples", default_random_jpeg, help_message="")
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#self.options['random_hsv_power'] = np.clip ( io.input_number ("Random hue/saturation/light intensity", default_random_hsv_power, add_info="0.0 .. 0.3", help_message="Random hue/saturation/light intensity applied to the src face set only at the input of the neural network. Stabilizes color perturbations during face swapping. Reduces the quality of the color transfer by selecting the closest one in the src faceset. Thus the src faceset must be diverse enough. Typical fine value is 0.05"), 0.0, 0.3 )
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self.options['gan_power'] = np.clip ( io.input_number ("GAN power", default_gan_power, add_info="0.0 .. 5.0", help_message="Forces the neural network to learn small details of the face. Enable it only when the face is trained enough with random_warp(off), and don't disable. The higher the value, the higher the chances of artifacts. Typical fine value is 0.1"), 0.0, 5.0 )
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@ -206,7 +202,6 @@ class AMPModel(ModelBase):
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morph_factor = self.options['morph_factor']
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gan_power = self.gan_power = self.options['gan_power']
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random_warp = self.options['random_warp']
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#random_hsv_power = self.options['random_hsv_power']
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if 'eyes_mouth_prio' in self.options:
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self.options.pop('eyes_mouth_prio')
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@ -779,7 +774,6 @@ class AMPModel(ModelBase):
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'random_blur': self.options['random_blur'],
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'random_jpeg': self.options['random_jpeg'],
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'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode,
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#'random_hsv_shift_amount' : random_hsv_power,
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'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
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{'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False,
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'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode,
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@ -110,11 +110,6 @@
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"random_warp": {
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"type": "boolean"
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},
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"random_hsv_power": {
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"type": "number",
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"minimum": 0.0,
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"maximum": 0.3
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},
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"random_downsample": {
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"type": "boolean"
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},
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@ -58,7 +58,6 @@ class SAEHDModel(ModelBase):
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default_loss_function = self.options['loss_function'] = self.load_or_def_option('loss_function', 'SSIM')
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default_random_warp = self.options['random_warp'] = self.load_or_def_option('random_warp', True)
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default_random_hsv_power = self.options['random_hsv_power'] = self.load_or_def_option('random_hsv_power', 0.0)
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default_random_downsample = self.options['random_downsample'] = self.load_or_def_option('random_downsample', False)
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default_random_noise = self.options['random_noise'] = self.load_or_def_option('random_noise', False)
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default_random_blur = self.options['random_blur'] = self.load_or_def_option('random_blur', False)
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@ -187,8 +186,6 @@ class SAEHDModel(ModelBase):
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self.options['random_warp'] = io.input_bool ("Enable random warp of samples", default_random_warp, help_message="Random warp is required to generalize facial expressions of both faces. When the face is trained enough, you can disable it to get extra sharpness and reduce subpixel shake for less amount of iterations.")
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#self.options['random_hsv_power'] = np.clip ( io.input_number ("Random hue/saturation/light intensity", default_random_hsv_power, add_info="0.0 .. 0.3", help_message="Random hue/saturation/light intensity applied to the src face set only at the input of the neural network. Stabilizes color perturbations during face swapping. Reduces the quality of the color transfer by selecting the closest one in the src faceset. Thus the src faceset must be diverse enough. Typical fine value is 0.05"), 0.0, 0.3 )
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self.options['random_downsample'] = io.input_bool("Enable random downsample of samples", default_random_downsample, help_message="")
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self.options['random_noise'] = io.input_bool("Enable random noise added to samples", default_random_noise, help_message="")
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self.options['random_blur'] = io.input_bool("Enable random blur of samples", default_random_blur, help_message="")
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@ -278,14 +275,12 @@ class SAEHDModel(ModelBase):
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random_warp = False if self.pretrain else self.options['random_warp']
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random_src_flip = self.random_src_flip if not self.pretrain else True
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random_dst_flip = self.random_dst_flip if not self.pretrain else True
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#random_hsv_power = self.options['random_hsv_power'] if not self.pretrain else 0.0
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blur_out_mask = self.options['blur_out_mask']
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if self.pretrain:
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self.options_show_override['lr_dropout'] = 'n'
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self.options_show_override['random_warp'] = False
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self.options_show_override['gan_power'] = 0.0
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#self.options_show_override['random_hsv_power'] = 0.0
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self.options_show_override['face_style_power'] = 0.0
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self.options_show_override['bg_style_power'] = 0.0
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self.options_show_override['uniform_yaw'] = True
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@ -830,7 +825,7 @@ class SAEHDModel(ModelBase):
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'random_noise': self.options['random_noise'],
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'random_blur': self.options['random_blur'],
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'random_jpeg': self.options['random_jpeg'],
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'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode, #'random_hsv_shift_amount' : random_hsv_power,
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'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode,
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'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
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{'sample_type': SampleProcessor.SampleType.FACE_IMAGE,'warp':False , 'transform':True, 'channel_type' : channel_type, 'ct_mode': ct_mode, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
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{'sample_type': SampleProcessor.SampleType.FACE_MASK, 'warp':False , 'transform':True, 'channel_type' : SampleProcessor.ChannelType.G, 'face_mask_type' : SampleProcessor.FaceMaskType.FULL_FACE, 'face_type':self.face_type, 'data_format':nn.data_format, 'resolution': resolution},
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@ -103,11 +103,6 @@
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"random_warp": {
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"type": "boolean"
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},
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"random_hsv_power": {
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"type": "number",
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"minimum": 0.0,
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"maximum": 0.3
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},
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"random_downsample": {
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"type": "boolean"
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},
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