          return block 
          
      def conv_sep3(self, filters, kernel_size=3, strides=2, use_instance_norm=True, **kwargs):
          def block(x):
              x = SeparableConv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=RandomNormal(0, 0.02), padding='same', **kwargs)(x)        
              if use_instance_norm:
                  x = inst_norm()(x)
              x = Activation("relu")(x)
              return x    
          return block
 
</s> remove     def conv_sep3(self, filters, kernel_size=3, strides=2, use_instance_norm=True, **kwargs):
 </s> add     def conv_inst_norm(self, filters, kernel_size=3, strides=2, use_instance_norm=True, **kwargs): </s> remove             x = SeparableConv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=RandomNormal(0, 0.02), padding='same', **kwargs)(x)
 </s> add             x = SeparableConv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=_kern_init, padding='same', **kwargs)(x) </s> remove             x = Conv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=RandomNormal(0, 0.02), padding='same', **kwargs)(x)         
 </s> add             x = Conv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=_kern_init, padding='same', **kwargs)(x)          </s> remove     def upscale_sep3(self, filters, use_instance_norm=True, **kwargs):
 </s> add     def upscale_inst_norm(self, filters, use_instance_norm=True, **kwargs): </s> remove                        kernel_initializer=RandomNormal(0, 0.02), padding='same', **kwargs)(x)
 </s> add                        kernel_initializer=_kern_init, padding='same', **kwargs)(x)
            x = SeparableConv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=_kern_init, padding='same', **kwargs)(x)        
          return block 
          
      def conv_sep3(self, filters, kernel_size=3, strides=2, use_instance_norm=True, **kwargs):
          def block(x):
            x = SeparableConv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=_kern_init, padding='same', **kwargs)(x)        
              if use_instance_norm:
                  x = inst_norm()(x)
              x = Activation("relu")(x)
              return x    
          return block
keep keep keep keep replace keep keep keep keep keep
 Merge staging to Master (#470)

* DLib scaling amends (#461)

* Scaling area fix and rework of frames and bounding boxes

* Update DLib scaling and initialization

* Extract - Detector reinitialization bugfix

* Slight OriginaHightRes Model re-factoring (#464)

* Model re-factoring, might fix red screen of death on multi-gpu configurations

* Limited trainer support for various INPUT_SIZE

* Auto Extraction multiprocess bugfix

* Sort tool bugfixes and linting 
plugins/Model_OriginalHighRes/Model.py