snapshot...

modules/deeplearning/icing_fcn.py

@@ -548,7 +548,7 @@ class IcingIntensityFCN:
         activation = tf.nn.leaky_relu
         momentum = 0.99
 
-        num_filters = len(self.train_params) * 4
+        num_filters = len(self.train_params) * 10
 
         input_2d = self.inputs[0]
         conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding=padding, activation=None)(input_2d)
@@ -637,6 +637,10 @@ class IcingIntensityFCN:
 
         conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_3', padding=padding)
 
+        conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_4', padding=padding)
+
+        conv = build_residual_block_1x1(conv, num_filters, activation, 'Residual_Block_5', padding=padding)
+
         print(conv.shape)
 
         if NumClasses == 2: