Update css
Browse files
app.py
CHANGED
@@ -55,6 +55,7 @@ title = "Interactive demo: Document Layout Analysis with DiT"
|
|
55 |
description = "Demo for Microsoft's DiT, the Document Image Transformer for state-of-the-art document understanding tasks. This particular model is fine-tuned on PubLayNet, a large dataset for document layout analysis. To use it, simply upload an image or use the example image below and click 'Submit'. 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'."
|
56 |
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2203.02378' target='_blank'>DiT: Self-supervised Pre-training for Document Image Transformer</a> | <a href='https://github.com/microsoft/unilm/dit' target='_blank'>Github Repo</a></p>"
|
57 |
examples =[['publaynet_example.jpeg']]
|
|
|
58 |
|
59 |
iface = gr.Interface(fn=analyze_image,
|
60 |
inputs=gr.inputs.Image(type="numpy"),
|
@@ -62,5 +63,6 @@ iface = gr.Interface(fn=analyze_image,
|
|
62 |
title=title,
|
63 |
description=description,
|
64 |
examples=examples,
|
|
|
65 |
enable_queue=True)
|
66 |
iface.launch(debug=True)
|
|
|
55 |
description = "Demo for Microsoft's DiT, the Document Image Transformer for state-of-the-art document understanding tasks. This particular model is fine-tuned on PubLayNet, a large dataset for document layout analysis. To use it, simply upload an image or use the example image below and click 'Submit'. 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'."
|
56 |
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2203.02378' target='_blank'>DiT: Self-supervised Pre-training for Document Image Transformer</a> | <a href='https://github.com/microsoft/unilm/dit' target='_blank'>Github Repo</a></p>"
|
57 |
examples =[['publaynet_example.jpeg']]
|
58 |
+
css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
|
59 |
|
60 |
iface = gr.Interface(fn=analyze_image,
|
61 |
inputs=gr.inputs.Image(type="numpy"),
|
|
|
63 |
title=title,
|
64 |
description=description,
|
65 |
examples=examples,
|
66 |
+
css=css,
|
67 |
enable_queue=True)
|
68 |
iface.launch(debug=True)
|