snapshot...

modules/deeplearning/cloud_opd_srcnn_viirs.py

@@ -253,11 +253,11 @@ class SRCNN:
             idx = params.index(param)
             tmp = input_data[:, idx, :, :]
             tmp = np.where(np.isnan(tmp), 0, tmp)
-            # tmp = tmp[:, self.slc_y_m, self.slc_x_m]
-            # tmp = self.upsample(tmp)
+            tmp = tmp[:, self.slc_y_m, self.slc_x_m]
+            tmp = self.upsample(tmp)
             # ---------------
-            tmp = upsample_nearest(tmp)
-            tmp = tmp[:, self.slc_y, self.slc_x]
+            # tmp = upsample_nearest(tmp)
+            # tmp = tmp[:, self.slc_y, self.slc_x]
             # ---------------
             tmp = normalize(tmp, param, mean_std_dct)
             data_norm.append(tmp)
@@ -284,11 +284,11 @@ class SRCNN:
         # ---------------------------------------------------
         tmp = input_label[:, label_idx_i, :, :]
         tmp = np.where(np.isnan(tmp), 0, tmp)
-        # tmp = tmp[:, self.slc_y_2, self.slc_x_2]
-        # tmp = self.upsample(tmp)
+        tmp = tmp[:, self.slc_y_2, self.slc_x_2]
+        tmp = self.upsample(tmp)
         # ----------------
-        tmp = upsample_nearest(tmp)
-        tmp = tmp[:, self.slc_y, self.slc_x]
+        # tmp = upsample_nearest(tmp)
+        # tmp = tmp[:, self.slc_y, self.slc_x]
         # ----------------
         tmp = normalize(tmp, label_param, mean_std_dct)
         data_norm.append(tmp)