Update app.py

app.py

@@ -180,25 +180,9 @@ with tempfile.TemporaryDirectory() as tmpdir:
             [![Github](https://img.shields.io/badge/Github-Repo-orange?logo=github)](https://github.com/sony/genwarp/)  
             [![Models](https://img.shields.io/badge/Models-checkpoints-blue?logo=huggingface)](https://huggingface.co/Sony/genwarp)  
             [![arXiv](https://img.shields.io/badge/arXiv-2405.17251-red?logo=arxiv)](https://arxiv.org/abs/2405.17251)
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+        
             ## Introduction
             This is an official demo for the paper "[GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping](https://genwarp-nvs.github.io/)". Genwarp can generate novel view images from a single input conditioned on camera poses. In this demo, we offer a basic use of inference of the model. For detailed information, please refer to the [paper](https://arxiv.org/abs/2405.17251).
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-            ## How to Use
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-            ### Try examples
-            - Examples are in the bottom section of the page
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-            ### Upload your own images
-            1. Upload a reference image to "Reference Input"
-            2. Move the camera to your desired view in "Unprojected 3DGS" 3D viewer
-            3. Hit "Generate a novel view" button and check the result
-
-            ## Tips
-            - This model is mainly trained for indoor/outdoor scenery. It might not work well for object-centric inputs. For details on training the model, please check our [paper](https://arxiv.org/abs/2405.17251).
-            - Extremely large camera movement from the input view might cause low performance results due to the unexpected deviation from the training distribution, which is not the scope of this model. Instead, you can feed the generation result for the small camera movement repeatedly and progressively move towards a desired view.
-            - 3D viewer might take some time to update especially when trying different images back to back. Wait until it fully updates to the new image.
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             """
         )
         file = gr.File(label='Left', file_types=['image'])