Update app.py

app.py

@@ -44,9 +44,6 @@ def inference(input_image):
     probabilities = torch.nn.functional.softmax(output[0], dim=0)
 
     # Read the categories
-    with open("artist_classes.txt", "r") as f:
-        categories = [s.strip() for s in f.readlines()]
-        
     categories = {
         0:"vanGogh",
         1:"Monet",
@@ -69,7 +66,7 @@ outputs = gr.Label(type="confidences",num_top_classes=5,label='Prediction')
 title = "Artist Classifier"
 description = "The classifier is a demo classifier to predict the painter using fine-tuned EfficientNet. It allows you to identify the creator of a painting among Van Gogh, Claude Monet, Leonardo da Vinci, Rembrandt, Pablo Picasso, and Salvador Dali. Just upload the image to the left blank box and click the Submit button. A list of confidence will be displayed. Following the link below to find a related work that helps to create your own paintings following the style of painters"
 
-article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/breynolds1247/StarryNight_StyleTransfer'>Style Transfer: Create your own stylish paintings </a></p>"
+article = "<p style='text-align: left'><a href='https://huggingface.co/spaces/breynolds1247/StarryNight_StyleTransfer'>Style Transfer: Create your own stylish paintings </a></p>"
 
 #examples = [
 #            ['dog.jpg']