diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 72ad40aa3066e34a346c2980ca58797c473797e5..71a56352d1a37ec3ef4882be295d4e743894a2ba 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -272,7 +272,7 @@ class SRCNN:
         tmp = input_data[:, label_idx, :, :]
         tmp = tmp.copy()
         tmp = np.where(np.isnan(tmp), 0, tmp)
-        tmp = smooth_2d(tmp, sigma=1.0)
+        # tmp = smooth_2d(tmp, sigma=1.0)
         tmp = tmp[:, slc_y_2, slc_x_2]
         tmp = resample_2d_linear(x_2, y_2, tmp, t, s)
         tmp = tmp[:, y_k, x_k]
@@ -472,7 +472,7 @@ class SRCNN:
         activation = tf.nn.relu
         momentum = 0.99
 
-        num_filters = 32
+        num_filters = 48
 
         input_2d = self.inputs[0]
         print('input: ', input_2d.shape)
@@ -493,7 +493,7 @@ class SRCNN:
 
         conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_4', kernel_size=KERNEL_SIZE, scale=scale)
 
-        #conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_5', kernel_size=KERNEL_SIZE, scale=scale)
+        conv_b = build_residual_conv2d_block(conv_b, num_filters, 'Residual_Block_5', kernel_size=KERNEL_SIZE, scale=scale)
 
         conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, strides=1, activation=activation, kernel_initializer='he_uniform', padding=padding)(conv_b)
 
@@ -837,7 +837,7 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     grd_c = np.where(np.isnan(grd_c), 0, grd_c)
     grd_c = grd_c.copy()
-    grd_c = smooth_2d_single(grd_c, sigma=1.0)
+    # grd_c = smooth_2d_single(grd_c, sigma=1.0)
     grd_c = grd_c[slc_y_2, slc_x_2]
     grd_c = resample_2d_linear_one(x_2, y_2, grd_c, t, s)
     grd_c = grd_c[y_k, x_k]