zoo/unet/unet_c.py
def expand_group(self, x, f, n_filters):
        """ Construct Expanding Group
            x        : input tensor to group
            f        : corresponding feature maps from contracting path
            n_filters: number of filters
        """
        # The Up Convolution (double feature map size)
        x = self.Conv2DTranspose(x, n_filters, (2, 2), strides=2)

        # Concatenate corresponding feature maps from contracting side
        x = Concatenate()([x, f])

        # Dimensionality Expansion
        x = self.Conv2D(x, n_filters*2, (3, 3), strides=1, padding='valid')
        x = self.ReLU(x)
        # Dimensionality Restoration
        x = self.Conv2D(x, n_filters, (3, 3), strides=1, padding='valid')
        x = self.ReLU(x)
        return x
 Construct Expanding Group
            x        : input tensor to group
            f        : corresponding feature maps from contracting path
            n_filters: number of filters
        
Construct Expanding Group
x        : input tensor to group
f        : corresponding feature maps from contracting path
n_filters: number of filters
Construct Expanding Group x : input tensor to group f : corresponding feature maps from contracting path n_filters : number of filters
def expand_group(self, x, f, n_filters):
        x = self.Conv2DTranspose(x, n_filters, (2, 2), strides=2)
        x = Concatenate()([x, f])
        x = self.Conv2D(x, n_filters*2, (3, 3), strides=1, padding='valid')
        x = self.ReLU(x)
        x = self.Conv2D(x, n_filters, (3, 3), strides=1, padding='valid')
        x = self.ReLU(x)
        return x
def expand_group ( self , x , f , n_filters ) : x = self . Conv2DTranspose ( x , n_filters , ( 2 , 2 ) , strides = 2 ) x = Concatenate ( ) ( [ x , f ] ) x = self . Conv2D ( x , n_filters * 2 , ( 3 , 3 ) , strides = 1 , padding = 'valid' ) x = self . ReLU ( x ) x = self . Conv2D ( x , n_filters , ( 3 , 3 ) , strides = 1 , padding = 'valid' ) x = self . ReLU ( x ) return x
Construct Expanding Group
x        : input tensor to group
f        : corresponding feature maps from contracting path
n_filters: number of filters
Construct Expanding Group x : input tensor to group f : corresponding feature maps from contracting path n_filters : number of filters
""" Construct Expanding Group
            x        : input tensor to group
            f        : corresponding feature maps from contracting path
            n_filters: number of filters
        """ # The Up Convolution (double feature map size) # Concatenate corresponding feature maps from contracting side # Dimensionality Expansion # Dimensionality Restoration
self
x
f
n_filters