refactorings
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@@ -41,19 +41,19 @@ class Model(ModelBase):
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training=True)
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if self.is_training_mode:
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f = SampleProcessor.TypeFlags
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face_type = f.FACE_TYPE_FULL if self.options['face_type'] == 'f' else f.FACE_TYPE_HALF
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t = SampleProcessor.Types
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face_type = t.FACE_TYPE_FULL if self.options['face_type'] == 'f' else t.FACE_TYPE_HALF
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self.set_training_data_generators ([
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SampleGeneratorFace(self.training_data_src_path, debug=self.is_debug(), batch_size=self.batch_size,
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sample_process_options=SampleProcessor.Options(random_flip=True, motion_blur = [25, 1] ),
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output_sample_types=[ [f.WARPED_TRANSFORMED | face_type | f.MODE_BGR_SHUFFLE | f.OPT_APPLY_MOTION_BLUR, self.resolution],
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[f.WARPED_TRANSFORMED | face_type | f.MODE_M | f.FACE_MASK_FULL, self.resolution],
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sample_process_options=SampleProcessor.Options(random_flip=True),
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output_sample_types=[ { 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_BGR_SHUFFLE), 'resolution' : self.resolution, 'motion_blur':(25, 1) },
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{ 'types': (t.IMG_WARPED_TRANSFORMED, face_type, t.MODE_M, t.FACE_MASK_FULL), 'resolution': self.resolution },
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]),
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SampleGeneratorFace(self.training_data_dst_path, debug=self.is_debug(), batch_size=self.batch_size,
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sample_process_options=SampleProcessor.Options(random_flip=True ),
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output_sample_types=[ [f.TRANSFORMED | face_type | f.MODE_BGR_SHUFFLE, self.resolution],
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output_sample_types=[ { 'types': (t.IMG_TRANSFORMED , face_type, t.MODE_BGR_SHUFFLE), 'resolution' : self.resolution},
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])
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])
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