update

app.py

@@ -241,6 +241,27 @@ def main(args):
         image = resize_to_224(image)
         return image
 
+    _CITE_ = r"""
+    If LN3Diff is helpful, please help to ⭐ the 
+    <a href='https://github.com/NIRVANALAN/LN3Diff/' target='_blank'>Github Repo</a>. Thanks! [![GitHub Stars](https://img.shields.io/github/stars/NIRVANALAN/LN3Diff?style=social)](https://github.com/NIRVANALAN/LN3Diff/)
+    ---
+    📝 **Citation**
+    If you find our work useful for your research or applications, please cite using this bibtex:
+    ```bibtex
+    @inproceedings{lan2024ln3diff,
+    title={LN3Diff: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation}, 
+    author={Yushi Lan and Fangzhou Hong and Shuai Yang and Shangchen Zhou and Xuyi Meng and Bo Dai and Xingang Pan and Chen Change Loy},
+    year={2024},
+    booktitle={ECCV},
+}
+    ```
+    📋 **License**
+    S-Lab 1.0 LICENSE. Please refer to the [LICENSE file](https://github.com/NIRVANALAN/LN3Diff/blob/main/LICENSE) for details.
+    📧 **Contact**
+    If you have any questions, feel free to open a discussion or contact us at <b>lanyushi15@gmail.com</b>.
+    """
+
+
 
     with gr.Blocks(css=css) as demo:
         gr.Markdown(

nsr/train_util_diffusion.py

@@ -31,6 +31,9 @@ from guided_diffusion.train_util import (TrainLoop, calc_average_loss,
                                          log_rec3d_loss_dict,
                                          parse_resume_step_from_filename)
 
+
+import mcubes
+import trimesh
 import dnnlib
 from safetensors.torch import load_file
 from huggingface_hub import hf_hub_download
@@ -196,8 +199,6 @@ class TrainLoopDiffusionWithRec(TrainLoop):
             # if True:
             mesh_size = 192 # avoid OOM on V100
             mesh_thres = 10  # TODO, requires tuning
-            import mcubes
-            import trimesh
             dump_path = f'{logger.get_dir()}/mesh/'
 
             os.makedirs(dump_path, exist_ok=True)

requirements.txt

@@ -30,3 +30,5 @@ rembg
 safetensors
 matplotlib
 git+https://github.com/nupurkmr9/vision-aided-gan
+PyMCubes
+trimesh