diff --git a/modules/deeplearning/srcnn_l1b_l2.py b/modules/deeplearning/srcnn_l1b_l2.py
index 114ec36d4bb6b9816b2ec919b99123af32b968f1..af5fe63fcfcdfc784ea8080815c90a3a0ae7beb9 100644
--- a/modules/deeplearning/srcnn_l1b_l2.py
+++ b/modules/deeplearning/srcnn_l1b_l2.py
@@ -217,12 +217,12 @@ class SRCNN:
             idx = params.index(param)
             tmp = input_data[:, idx, 3:131:2, 3:131:2]
             # tmp = resample(y_64, x_64, tmp, s, t)
-            tmp = resample_2d_linear(y_64, x_64, tmp, s, t)
+            tmp = resample_2d_linear(x_64, y_64, tmp, t, s)
             tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
             data_norm.append(tmp)
         # --------
         tmp = input_data[:, 2, 3:131:2, 3:131:2]
-        tmp = resample_2d_linear(y_64, x_64, tmp, s, t)
+        tmp = resample_2d_linear(x_64, y_64, tmp, t, s)
         #tmp = normalize(tmp, 'temp_11_0um_nom', mean_std_dct)
         data_norm.append(tmp)
         # ---------
@@ -678,10 +678,10 @@ def run_evaluate_static_new(in_file, out_file, ckpt_dir):
     x_up = np.arange(0, lenx, 0.5)
     y_up = np.arange(0, leny, 0.5)
 
-    grd_a = resample_2d_linear_one(y, x, grd_a, y_up, x_up)
+    grd_a = resample_2d_linear_one(x, y, grd_a, x_up, y_up)
     grd_a = normalize(grd_a, data_params[0], mean_std_dct)
 
-    grd_b = resample_2d_linear_one(y, x, grd_b, y_up, x_up)
+    grd_b = resample_2d_linear_one(x, y, grd_b, x_up, y_up)
 
     data = np.stack([grd_a, grd_b], axis=2)
     data = np.expand_dims(data, axis=0)