Update app.py

app.py

@@ -1,10 +1,10 @@
 import spaces
-
 import os
 import imageio
 import numpy as np
 import torch
 import rembg
+
 from PIL import Image
 from torchvision.transforms import v2
 from pytorch_lightning import seed_everything
@@ -244,14 +244,12 @@ def make3d(images):
 
 
 _HEADER_ = '''
-<h2><b>Official 🤗 Gradio Demo</b></h2><h2><a href='https://github.com/TencentARC/InstantMesh' target='_blank'><b>InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models</b></a></h2>
-
 **InstantMesh** is a feed-forward framework for efficient 3D mesh generation from a single image based on the LRM/Instant3D architecture.
 
 Code: <a href='https://github.com/TencentARC/InstantMesh' target='_blank'>GitHub</a>. Techenical report: <a href='https://arxiv.org/abs/2404.07191' target='_blank'>ArXiv</a>.
 
 ❗️❗️❗️**Important Notes:**
-- Our demo can export a .obj mesh with vertex colors or a .glb mesh now. If you prefer to export a .obj mesh with a **texture map**, please refer to our <a href='https://github.com/TencentARC/InstantMesh?tab=readme-ov-file#running-with-command-line' target='_blank'>Github Repo</a>.
+- The demo can export a .obj mesh with vertex colors or a .glb mesh now. If you prefer to export a .obj mesh with a **texture map**, please refer to our <a href='https://github.com/TencentARC/InstantMesh?tab=readme-ov-file#running-with-command-line' target='_blank'>Github Repo</a>.
 - The 3D mesh generation results highly depend on the quality of generated multi-view images. Please try a different **seed value** if the result is unsatisfying (Default: 42).
 '''
 
@@ -276,7 +274,7 @@ Apache-2.0 LICENSE. Please refer to the [LICENSE file](https://huggingface.co/sp
 
 📧 **Contact**
 
-If you have any questions, feel free to open a discussion or contact us at <b>[email protected]</b>.
+If you have any questions, feel free to open a discussion or contact the creators at <b>[email protected]</b>.
 """