snapshot...

modules/deeplearning/espcn.py

@@ -67,12 +67,13 @@ x_134_2 = x_134[2:133:2]
 y_134_2 = y_134[2:133:2]
 
 
-def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.leaky_relu, padding='SAME'):
+def build_residual_conv2d_block(conv, num_filters, block_name, activation=tf.nn.leaky_relu, padding='SAME', scale=None):
 
     with tf.name_scope(block_name):
         skip = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding, activation=activation)(conv)
         skip = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, padding=padding, activation=None)(skip)
-
+        if scale is not None:
+            skip = tf.keras.layers.Lambda(lambda x: x * scale)(skip)
         conv = conv + skip
         print(conv.shape)