Update app.py

app.py

@@ -14,6 +14,13 @@ base_model = keras.applications.Xception(
 
 base_model.trainable = False
 
+
+def img_pros(img):
+  img = tf.keras.preprocessing.image.img_to_array(img)
+  img = tf.image.resize(img, [160,160])
+  img = tf.expand_dims(img, axis = 0)
+  return img
+
 #function for creating model
 #returns model, its inputs, Xception's last conv output, the whole model's outputs
 def create_model_mod():
@@ -95,6 +102,7 @@ weights = "weights.h5"
 # img, y_pred = gen_grad_img_single(weights, img)
 
 def get_grad(img):
+    img = img_pros(img)
     a = gen_grad_img_single(weights, img)
     return a