update

README.md

@@ -1,13 +1,13 @@
 ---
 title: PolyFormer
-emoji: 🖌️🎨
+emoji: 💠
 colorFrom: pink
 colorTo: purple
 sdk: gradio
 sdk_version: 3.14.0
 app_file: app.py
 pinned: false
-license: afl-3.0
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -23,25 +23,28 @@ import base64
 import re
 from demo import visual_grounding
 
-title = "PolyFormer-Visual_Grounding"
-description = "Gradio Demo for PolyFormer-Visual_Grounding. Upload your own image or click any one of the examples, " \
-              "and write a description about a certain object.  " \
-              "Then click \"Submit\" and wait for the result of grounding. For help or to provide feedback, please contact: Hui Ding (@huidin)"
-article = "<p style='text-align: center'><a href='https://arxiv.org/pdf/2302.07387.pdf' target='_blank'>PolyFormer CVPR2023" \
-          "</a></p> "
-# examples = [['A bear astronaut in the space.jpeg', 'a bear astronaut in the space'],
-#             ['A unicorn doing computer vision research.jpeg', 'a unicorn doing computer vision research'],
-#             ['pig.jpeg', 'a pig robot preparing a delicious meal'],
-#             ['otta.png', 'a gentleman otter in a 19th century portrait'],
-#             ['pikachu.jpeg', 'a pikachu fine-dining  with  a view  to  the  Eiffel Tower'],
-#             ['A small cabin on top of a snowy mountain in the style of Disney artstation.jpeg', 'a small cabin on top of a snowy mountain in the style of Disney artstation'],
-#
-#             ]
-examples = []
+title = "PolyFormer"
+
+description = """<p style='text-align: center'> <a href='https://polyformer.github.io/' target='_blank'>Project Page</a> | <a href='https://arxiv.org/pdf/2302.07387.pdf' target='_blank'>Paper</a> | <a href='https://github.com/amazon-science/polygon-transformer' target='_blank'>Github Repo</a></p>
+                 <p style='text-align: center'> Demo of PolyFormer for referring image segmentation and referring expression comprehension. Upload your own image or click any one of the examples, and write a description about a certain object. Then click \"Submit\" and wait for the result of grounding.</p>
+<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings.
+<br/>
+<a href="https://huggingface.co/spaces/koajoel/PolyFormer?duplicate=true">
+<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
+</p>
+"""
+
+examples = [['demo/bear.jpeg', 'a bear astronaut in the space'],
+            ['demo/unicorn.jpeg', 'a unicorn doing computer vision research'],
+            ['demo/pig.jpeg', 'a pig robot preparing a delicious meal'],
+            ['demo/otta.png', 'a gentleman otter in a 19th century portrait'],
+            ['demo/pikachu.jpeg', 'a pikachu fine-dining  with  a view  to  the  Eiffel Tower'],
+            ['demo/cabin.jpeg', 'a small cabin on top of a snowy mountain in the style of Disney art station']
+            ]
 io = gr.Interface(fn=visual_grounding, inputs=[gr.inputs.Image(type='pil'), "textbox"],
                   outputs=[gr.outputs.Image(label="output", type='numpy'), gr.outputs.Image(label="predicted mask", type='numpy')],
                   title=title, description=description, article=article, examples=examples,
                   allow_flagging=False, allow_screenshot=False)
-# io.launch(cache_examples=True)
-io.launch()
+io.launch(cache_examples=True)
+# io.launch()