Update app.py

app.py

@@ -128,16 +128,18 @@ for images, labels in train_ds.take(1):
 num_classes = 12
 
 model = Sequential([
-  layers.experimental.preprocessing.Rescaling(1./255, input_shape=(img_height, img_width, 3)),
+  data_augmentation,
+  layers.Rescaling(1./255),
   layers.Conv2D(16, 3, padding='same', activation='relu'),
   layers.MaxPooling2D(),
   layers.Conv2D(32, 3, padding='same', activation='relu'),
   layers.MaxPooling2D(),
   layers.Conv2D(64, 3, padding='same', activation='relu'),
   layers.MaxPooling2D(),
+  layers.Dropout(0.2),
   layers.Flatten(),
   layers.Dense(128, activation='relu'),
-  layers.Dense(num_classes,activation='softmax')
+  layers.Dense(num_classes, name="outputs")
 ])