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manual extractor: increased FPS,
sort by final : now you can specify target number of images, converter: fix seamless mask and exception, huge refactoring
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7db469a1da
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30 changed files with 1834 additions and 1718 deletions
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@ -4,14 +4,14 @@ from nnlib import nnlib
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from models import ModelBase
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from facelib import FaceType
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from samples import *
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from utils.console_utils import *
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from interact import interact as io
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class Model(ModelBase):
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#override
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def onInitializeOptions(self, is_first_run, ask_override):
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if is_first_run:
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self.options['lighter_ae'] = input_bool ("Use lightweight autoencoder? (y/n, ?:help skip:n) : ", False, help_message="Lightweight autoencoder is faster, requires less VRAM, sacrificing overall quality. If your GPU VRAM <= 4, you should to choose this option.")
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self.options['lighter_ae'] = io.input_bool ("Use lightweight autoencoder? (y/n, ?:help skip:n) : ", False, help_message="Lightweight autoencoder is faster, requires less VRAM, sacrificing overall quality. If your GPU VRAM <= 4, you should to choose this option.")
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else:
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default_lighter_ae = self.options.get('created_vram_gb', 99) <= 4 #temporally support old models, deprecate in future
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if 'created_vram_gb' in self.options.keys():
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@ -20,12 +20,12 @@ class Model(ModelBase):
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if is_first_run or ask_override:
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def_pixel_loss = self.options.get('pixel_loss', False)
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self.options['pixel_loss'] = input_bool ("Use pixel loss? (y/n, ?:help skip: n/default ) : ", def_pixel_loss, help_message="Default DSSIM loss good for initial understanding structure of faces. Use pixel loss after 20k epochs to enhance fine details and decrease face jitter.")
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self.options['pixel_loss'] = io.input_bool ("Use pixel loss? (y/n, ?:help skip: n/default ) : ", def_pixel_loss, help_message="Default DSSIM loss good for initial understanding structure of faces. Use pixel loss after 20k epochs to enhance fine details and decrease face jitter.")
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else:
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self.options['pixel_loss'] = self.options.get('pixel_loss', False)
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#override
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def onInitialize(self, **in_options):
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def onInitialize(self):
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exec(nnlib.import_all(), locals(), globals())
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self.set_vram_batch_requirements( {2.5:4} )
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@ -125,15 +125,14 @@ class Model(ModelBase):
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return np.concatenate ( (x,mx), -1 )
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#override
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def get_converter(self, **in_options):
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from models import ConverterMasked
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def get_converter(self):
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from converters import ConverterMasked
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return ConverterMasked(self.predictor_func,
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predictor_input_size=128,
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output_size=128,
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face_type=FaceType.HALF,
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base_erode_mask_modifier=100,
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base_blur_mask_modifier=100,
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**in_options)
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base_blur_mask_modifier=100)
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def Build(self, lighter_ae):
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exec(nnlib.code_import_all, locals(), globals())
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