Update app.py

app.py

@@ -244,28 +244,8 @@ def make3d(images):
 
 
 _HEADER_ = '''
-**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:**
-- 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).
-'''
-
-_CITE_ = r"""
-If InstantMesh is helpful, please help to ⭐ the <a href='https://github.com/TencentARC/InstantMesh' target='_blank'>Github Repo</a>. Thanks! [![GitHub Stars](https://img.shields.io/github/stars/TencentARC/InstantMesh?style=social)](https://github.com/TencentARC/InstantMesh)
----
-📝 **Citation**
-
-If you find the work useful for your research or applications, please cite using this bibtex:
-```bibtex
-@article{xu2024instantmesh,
-  title={InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models},
-  author={Xu, Jiale and Cheng, Weihao and Gao, Yiming and Wang, Xintao and Gao, Shenghua and Shan, Ying},
-  journal={arXiv preprint arXiv:2404.07191},
-  year={2024}
-}
+**Hepzeka.com** InstantMesh, Resimden 3 boyutlu Obj oluşturma.
+
 ```
 
 📋 **License**