refactor

app.py

@@ -1,12 +1,12 @@
+from PIL import Image
+
 import gradio as gr
 import torch
-from model import *
-
-from PIL import Image
 import torchvision.transforms as transforms
 
+from model import *
 
-title = "Fashion Image Recognition"
+title = "Garment Classifier"
 description = "Trained on the Fashion MNIST dataset (28x28 pixels). The model expects images containing only one garment article as in the examples."
 inputs = gr.components.Image()
 outputs = gr.components.Label()
@@ -14,7 +14,7 @@ examples = "examples"
 
 model = torch.load("model/fashion.mnist.base.pt", map_location=torch.device("cpu"))
 
-# Images need to be transformed to an approximated `fashion MNIST` dataset format
+# Images need to be transformed to the `Fashion MNIST` dataset format
 # see https://arxiv.org/abs/1708.07747
 transform = transforms.Compose(
     [