snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -259,18 +259,16 @@ class SRCNN:
         data_norm = []
         for param in data_params:
             idx = params.index(param)
-            # tmp = input_data[:, idx, slc_y_2, slc_x_2]
-            tmp = input_data[:, idx, slc_y, slc_x]
+            tmp = input_data[:, idx, slc_y_2, slc_x_2]
             tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
-            # tmp = resample_2d_linear(x_2, y_2, tmp, t, s)
+            tmp = resample_2d_linear(x_2, y_2, tmp, t, s)
             data_norm.append(tmp)
         # --------------------------
         param = 'refl_0_65um_nom'
         idx = params.index(param)
-        # tmp = input_data[:, idx, slc_y_2, slc_x_2]
-        tmp = input_data[:, idx, slc_y, slc_x]
+        tmp = input_data[:, idx, slc_y_2, slc_x_2]
         tmp = normalize(tmp, param, mean_std_dct, add_noise=add_noise, noise_scale=noise_scale)
-        # tmp = resample_2d_linear(x_2, y_2, tmp, t, s)
+        tmp = resample_2d_linear(x_2, y_2, tmp, t, s)
         data_norm.append(tmp)
         # --------
         tmp = input_data[:, label_idx, slc_y_2, slc_x_2]