BaseModel.py
def DeblurSHCNet(self, input_shape, num_block):
        '''Base SHC net network for deblur.
        '''

        input_x = Input(shape=input_shape)

        # Model
        # trainable flag just for debug
        self.trainable = True
        #self.trainable = False

        self.kernel_size = (25, 25)
        self.padding = "valid"
        layer_25by25 = self._ConvBNRelu(input_x)

        self.kernel_size = (3, 3)
        self.padding = "same"
        shortcut = self._ConvBNRelu(layer_25by25)
        x = self._ConvBNRelu(shortcut)
        for i in xrange(0, num_block):
            x = self._ConvOnly(x)
            x = self._AddShortCut([x, shortcut])

        self.num_filters = 1
        x = self._ConvOnly(x)
        model = Model(inputs=input_x, outputs=x)

        return model
Base SHC net network for deblur.
        
Base SHC net network for deblur.
Base SHC net network for deblur .
def DeblurSHCNet(self, input_shape, num_block):
        input_x = Input(shape=input_shape)
        self.trainable = True
        self.kernel_size = (25, 25)
        self.padding = "valid"
        layer_25by25 = self._ConvBNRelu(input_x)
        self.kernel_size = (3, 3)
        self.padding = "same"
        shortcut = self._ConvBNRelu(layer_25by25)
        x = self._ConvBNRelu(shortcut)
        for i in xrange(0, num_block):
            x = self._ConvOnly(x)
            x = self._AddShortCut([x, shortcut])
        self.num_filters = 1
        x = self._ConvOnly(x)
        model = Model(inputs=input_x, outputs=x)
        return model
def DeblurSHCNet ( self , input_shape , num_block ) : input_x = Input ( shape = input_shape ) self . trainable = True self . kernel_size = ( 25 , 25 ) self . padding = "valid" layer_25by25 = self . _ConvBNRelu ( input_x ) self . kernel_size = ( 3 , 3 ) self . padding = "same" shortcut = self . _ConvBNRelu ( layer_25by25 ) x = self . _ConvBNRelu ( shortcut ) for i in xrange ( 0 , num_block ) : x = self . _ConvOnly ( x ) x = self . _AddShortCut ( [ x , shortcut ] ) self . num_filters = 1 x = self . _ConvOnly ( x ) model = Model ( inputs = input_x , outputs = x ) return model
Base SHC net network for deblur.
Base SHC net network for deblur .
'''Base SHC net network for deblur.
        ''' # Model # trainable flag just for debug #self.trainable = False
self
input_shape
num_block