snapshot...

modules/deeplearning/icing_cnn.py

@@ -318,18 +318,18 @@ class IcingIntensityNN:
             else:
                 self.in_mem_data_cache_test[key] = (data, data_alt, label)
 
-        if is_training and DO_AUGMENT:
-            data_ud = np.flip(data, axis=1)
-            data_alt_ud = np.copy(data_alt)
-            label_ud = np.copy(label)
-
-            data_lr = np.flip(data, axis=2)
-            data_alt_lr = np.copy(data_alt)
-            label_lr = np.copy(label)
-
-            data = np.concatenate([data, data_ud, data_lr])
-            data_alt = np.concatenate([data_alt, data_alt_ud, data_alt_lr])
-            label = np.concatenate([label, label_ud, label_lr])
+        # if is_training and DO_AUGMENT:
+        #     data_ud = np.flip(data, axis=1)
+        #     data_alt_ud = np.copy(data_alt)
+        #     label_ud = np.copy(label)
+        #
+        #     data_lr = np.flip(data, axis=2)
+        #     data_alt_lr = np.copy(data_alt)
+        #     label_lr = np.copy(label)
+        #
+        #     data = np.concatenate([data, data_ud, data_lr])
+        #     data_alt = np.concatenate([data_alt, data_alt_ud, data_alt_lr])
+        #     label = np.concatenate([label, label_ud, label_lr])
 
         return data, data_alt, label