Update app.py

app.py

@@ -11,11 +11,6 @@ total_variation_weight = 1e-6
 style_weight = 1e-6
 content_weight = 2.5e-8
 
-# Dimensions of the generated picture.
-width, height = keras.preprocessing.image.load_img(base_image_path).size
-img_nrows = 400
-img_ncols = int(width * img_nrows / height)
-
 # Build a VGG19 model loaded with pre-trained ImageNet weights
 model = from_pretrained_keras("rushic24/keras-VGG19")
 
@@ -37,7 +32,6 @@ style_layer_names = [
 # The layer to use for the content loss.
 content_layer_name = "block5_conv2"
 
-
 def preprocess_image(image_path):
     # Util function to open, resize and format pictures into appropriate tensors
     img = keras.preprocessing.image.load_img(