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fix Util.py, SAE: lowest ae dims now can be 32 (for testing)
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2 changed files with 11 additions and 2 deletions
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@ -29,7 +29,16 @@ def convert_png_to_jpg_file (filepath):
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img = cv2.imread (str(filepath))
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new_filepath = str(filepath.parent / (filepath.stem + '.jpg'))
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cv2.imwrite ( new_filepath, img, [int(cv2.IMWRITE_JPEG_QUALITY), 85])
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DFLJPG.embed_data( new_filepath, **dfl_dict )
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DFLJPG.embed_data( new_filepath,
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face_type=dfl_dict.get('face_type', None),
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landmarks=dfl_dict.get('landmarks', None),
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yaw_value=dfl_dict.get('yaw_value', None),
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pitch_value=dfl_dict.get('pitch_value', None),
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source_filename=dfl_dict.get('source_filename', None),
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source_rect=dfl_dict.get('source_rect', None),
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source_landmarks=dfl_dict.get('source_landmarks', None) )
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filepath.unlink()
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@ -60,7 +60,7 @@ class SAEModel(ModelBase):
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default_ae_dims = 256 if self.options['archi'] == 'liae' else 512
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default_ed_ch_dims = 42
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if is_first_run:
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self.options['ae_dims'] = np.clip ( input_int("AutoEncoder dims (128-1024 ?:help skip:%d) : " % (default_ae_dims) , default_ae_dims, help_message="More dims are better, but requires more VRAM. You can fine-tune model size to fit your GPU." ), 128, 1024 )
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self.options['ae_dims'] = np.clip ( input_int("AutoEncoder dims (32-1024 ?:help skip:%d) : " % (default_ae_dims) , default_ae_dims, help_message="More dims are better, but requires more VRAM. You can fine-tune model size to fit your GPU." ), 32, 1024 )
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self.options['ed_ch_dims'] = np.clip ( input_int("Encoder/Decoder dims per channel (21-85 ?:help skip:%d) : " % (default_ed_ch_dims) , default_ed_ch_dims, help_message="More dims are better, but requires more VRAM. You can fine-tune model size to fit your GPU." ), 21, 85 )
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self.options['face_type'] = input_str ("Half or Full face? (h/f, ?:help skip:f) : ", default_face_type, ['h','f'], help_message="Half face has better resolution, but covers less area of cheeks.").lower()
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else:
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