Update app.py

app.py

@@ -10,8 +10,9 @@ model = tf.saved_model.load("best_saved_model") #Loading the saved model
 
 def process_img(img): 
     img = img.resize((640,640)) # resize the image as reqired for the model input
+    img = np.array(img)
     copy_img = img.copy()
-    img = np.array(img)/255                    # Normalizing the picel value 
+    img = img/255                    # Normalizing the picel value 
     img = img.astype("float32")      # Convert the format double to format float
     img = np.expand_dims(img,axis=0) # exapanding dimension to add batch
     return img,copy_img