Update app.py

app.py

@@ -64,10 +64,10 @@ def process_image(image):
 
 title = "Interactive demo: LayoutLMv2 with CORD receipts dataset"
 description = "Demo for Microsoft's LayoutLMv2, a Transformer for state-of-the-art document image understanding tasks. This particular model is fine-tuned on CORD, a dataset of manually annotated receipts. It annotates the words appearing in the image in up to 30 classes. To use it, simply upload an image or use the example image below. Results will show up in a few seconds. If you want to make the output bigger, right-click on it and select ‘Open image in new tab’."
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2012.14740'>LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding</a> | <a href='https://github.com/microsoft/unilm'>Github Repo</a> | <a href='https://katanaml.io' target='_blank'>Katana ML</a> | <a href='https://github.com/katanaml/sparrow'>Sparrow Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=abaranovskij_cord' alt='visitor badge'></center>"
-examples =[['test0.jpeg', 'test1.jpeg', 'test2.jpeg']]
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2012.14740' target='_blank'>LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding</a> | <a href='https://github.com/microsoft/unilm' target='_blank'>LayoutLMv2 Github Repo</a> | <a href='https://katanaml.io' target='_blank'>Katana ML</a> | <a href='https://github.com/katanaml/sparrow' target='_blank'>Sparrow Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=abaranovskij_cord' alt='visitor badge'></center>"
+examples =[['test0.jpeg'], ['test1.jpeg'], ['test2.jpeg']]
 
-css = ".output-image, .input-image {height: 40rem !important; width: 100% !important;}"
+css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
 
 iface = gr.Interface(fn=process_image,
                      inputs=gr.inputs.Image(type="pil"),