      IMAGE_SIZE = 128, 128
      IMAGE_DEPTH = len('RGB') # good to let ppl know what these are...
      IMAGE_SHAPE = *IMAGE_SIZE, IMAGE_DEPTH
      
      def __init__(self, model_dir, gpus):
          
          if mswindows:  
              from ctypes import cdll    
              mydll = cdll.LoadLibrary("user32.dll")
              mydll.SetProcessDPIAware(True)        
          
 
</s> remove 
    # still playing with dims
    ENCODER_DIM = 2048
        
    IMAGE_SIZE = 128, 128
    IMAGE_DEPTH = len('RGB') # good to let ppl know what these are...
    IMAGE_SHAPE = *IMAGE_SIZE, IMAGE_DEPTH
 </s> add  </s> remove             mydll.SetProcessDPIAware(True)        
 </s> add             mydll.SetProcessDPIAware(True)                               
        
        self._encoder_type = encoder_type </s> remove     def Decoder(self):
        inp = Input(shape=(8, 8, 512))
        x = self.upscale(384)(inp)
        x = self.res_block(384)(x)
        x = self.upscale_sep(192)(x)
        x = self.res_block(192)(x)
        x = self.upscale(128)(x)
        x = self.res_block(128)(x)
        x = self.upscale(64)(x)
        x = self.res_block(64)(x)                    
        
#         rb = Conv2D(64, kernel_size=3, padding="same", dilation_rate=2)(x)
#         rb = LeakyReLU(alpha=0.2)(rb)
#         rb = Conv2D(64, kernel_size=3, padding="same", dilation_rate=2)(rb)
#         x = add([rb, x])
# 
        #x = self.upscale(32)(x)        
                        
        out = Conv2D(3, kernel_size=5, padding='same', activation='sigmoid')(x)
                
        return KerasModel(inp, out)
 </s> add     def Decoder_original(self):       
        decoder_shape = self.IMAGE_SHAPE[0]//8        
        inpt = Input(shape=(decoder_shape, decoder_shape, 512))
        
        x = self.upscale(512, kernel_initializer=RandomNormal(0, 0.02))(inpt)
        x = self.upscale(256, kernel_initializer=RandomNormal(0, 0.02))(x)
        x = self.upscale(self.IMAGE_SHAPE[0], kernel_initializer=RandomNormal(0, 0.02))(x) </s> remove     def Encoder_v2(self):
        """Old algorithm; pretty good but slow"""
        retina = Input(shape=self.IMAGE_SHAPE)
        x = self.conv(128)(retina)         
        x = self.conv(144)(x)              
        x = self.conv_sep(256)(x)
        x = self.conv(448)(x)        
        x = self.conv_sep(512)(x)        
        x = self.conv(768)(x)
        x = self.conv_sep(1024)(x)
 </s> add     def Encoder_shaoanlu(self, **kwargs):
        impt = Input(shape=self.IMAGE_SHAPE)
                
        in_conv_filters = self.IMAGE_SHAPE[0] if self.IMAGE_SHAPE[0] <= 128 else 128 + (self.IMAGE_SHAPE[0]-128)//4
        
        x = Conv2D(in_conv_filters, kernel_size=5, kernel_initializer=conv_init, use_bias=False, padding="same")(impt)
        x = self.conv_sep3(in_conv_filters+32, use_instance_norm=False)(x)
        x = self.conv_sep3(256)(x)        
        x = self.conv_sep3(512)(x)
        x = self.conv_sep3(1024)(x)        
        
        dense_shape = self.IMAGE_SHAPE[0] // 16          </s> remove     def Encoder_v3(self):
        """Lighter on resources encoder with bigger first conv layer"""
        retina = Input(shape=self.IMAGE_SHAPE)
        x = self.conv_sep_v3(192)(retina)         
 </s> add     def Encoder_original(self, **kwargs):
        impt = Input(shape=self.IMAGE_SHAPE)
        
        in_conv_filters = self.IMAGE_SHAPE[0] if self.IMAGE_SHAPE[0] <= 128 else 128 + (self.IMAGE_SHAPE[0]-128)//4
        x = self.conv(in_conv_filters)(impt)
    ENCODER_DIM = 1024 # dense layer size        
    IMAGE_SHAPE = 128, 128 # image shape
    
    assert [n for n in IMAGE_SHAPE if n>=16]
    
    IMAGE_WIDTH = max(IMAGE_SHAPE)
    IMAGE_WIDTH = (IMAGE_WIDTH//16 + (1 if (IMAGE_WIDTH%16)>=8 else 0))*16
    IMAGE_SHAPE = IMAGE_WIDTH, IMAGE_WIDTH, len('BRG') # good to let ppl know what these are...
    
    
    def __init__(self, model_dir, gpus, encoder_type=ENCODER):
                
      IMAGE_SIZE = 128, 128
      IMAGE_DEPTH = len('RGB') # good to let ppl know what these are...
      IMAGE_SHAPE = *IMAGE_SIZE, IMAGE_DEPTH
      
    ENCODER_DIM = 1024 # dense layer size        
    IMAGE_SHAPE = 128, 128 # image shape
    
    assert [n for n in IMAGE_SHAPE if n>=16]
    
    IMAGE_WIDTH = max(IMAGE_SHAPE)
    IMAGE_WIDTH = (IMAGE_WIDTH//16 + (1 if (IMAGE_WIDTH%16)>=8 else 0))*16
    IMAGE_SHAPE = IMAGE_WIDTH, IMAGE_WIDTH, len('BRG') # good to let ppl know what these are...
    
    
    def __init__(self, model_dir, gpus, encoder_type=ENCODER):
                
    ENCODER_DIM = 1024 # dense layer size        
    IMAGE_SHAPE = 128, 128 # image shape
    
    assert [n for n in IMAGE_SHAPE if n>=16]
    
    IMAGE_WIDTH = max(IMAGE_SHAPE)
    IMAGE_WIDTH = (IMAGE_WIDTH//16 + (1 if (IMAGE_WIDTH%16)>=8 else 0))*16
    IMAGE_SHAPE = IMAGE_WIDTH, IMAGE_WIDTH, len('BRG') # good to let ppl know what these are...
    
    
    def __init__(self, model_dir, gpus, encoder_type=ENCODER):
                
          if mswindows:  
              from ctypes import cdll    
              mydll = cdll.LoadLibrary("user32.dll")
              mydll.SetProcessDPIAware(True)        
          
keep keep keep keep replace replace keep keep keep keep keep
 model update (#417)

New, functional Original 128 model 
plugins/Model_OriginalHighRes/Model.py