snapshot...

modules/deeplearning/espcn.py

@@ -240,7 +240,9 @@ class ESPCN:
             nda = np.load(f)
             label_s.append(nda)
 
-        data = np.concatenate(data_s)
+        #data = np.concatenate(data_s)
+        data = np.concatenate(label_s)
+        data = tf.image.resize(data, (32, 32))
         label = np.concatenate(label_s)
 
         label = label[:, label_idx, :, :]
@@ -416,8 +418,8 @@ class ESPCN:
 
         input_2d = self.inputs[0]
         print('input: ', input_2d.shape)
-        conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding='VALID', activation=None)(input_2d)
-        # conv = conv[:, 4:20, 4:20, :]
+        # conv = tf.keras.layers.Conv2D(num_filters, kernel_size=5, strides=1, padding='VALID', activation=None)(input_2d)
+        conv = input_2d
         print('Contracting Branch')
         print('input: ', conv.shape)
         skip = conv