Hancy commited on
Commit
706f88d
Β·
1 Parent(s): 2aa6e78
Files changed (2) hide show
  1. app.py +3 -7
  2. app_config.py +10 -4
app.py CHANGED
@@ -6,7 +6,7 @@ import torch
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  import numpy as np
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  from matplotlib.colors import LinearSegmentedColormap
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- from app_config import CSS, TITLE, DESCRIPTION, BIBTEX, DEVICE
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  import sample_cond
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  model = sample_cond.load_model()
@@ -30,7 +30,6 @@ def colorize_depth(depth, log_scale):
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  return rgb
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- @spaces.GPU
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  @torch.no_grad()
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  def generate_lidar(model, cond):
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  img, pcd = sample_cond.sample(model, cond)
@@ -47,10 +46,7 @@ def load_camera(image):
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  with gr.Blocks(css=CSS) as demo:
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- gr.Markdown(TITLE)
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- gr.Markdown(DESCRIPTION)
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- gr.Markdown("### Camera-to-LiDAR Demo")
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- # gr.Markdown("You can slide the output to compare the depth prediction with input image")
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  with gr.Row():
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  input_image = gr.Image(label="Input Image", type='numpy', elem_id='img-display-input')
@@ -76,7 +72,7 @@ with gr.Blocks(css=CSS) as demo:
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  examples = gr.Examples(examples=example_files, inputs=[input_image], outputs=[output_image, raw_file],
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  fn=on_submit, cache_examples=True)
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- gr.Markdown(BIBTEX)
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  if __name__ == '__main__':
 
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  import numpy as np
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  from matplotlib.colors import LinearSegmentedColormap
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+ from app_config import CSS, HEADER, FOOTER, DEVICE
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  import sample_cond
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  model = sample_cond.load_model()
 
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  return rgb
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  @torch.no_grad()
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  def generate_lidar(model, cond):
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  img, pcd = sample_cond.sample(model, cond)
 
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  with gr.Blocks(css=CSS) as demo:
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+ gr.Markdown(HEADER)
 
 
 
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  with gr.Row():
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  input_image = gr.Image(label="Input Image", type='numpy', elem_id='img-display-input')
 
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  examples = gr.Examples(examples=example_files, inputs=[input_image], outputs=[output_image, raw_file],
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  fn=on_submit, cache_examples=True)
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+ gr.Markdown(FOOTER)
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  if __name__ == '__main__':
app_config.py CHANGED
@@ -12,10 +12,16 @@ CSS = """
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  }
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  """
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  DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
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- TITLE = "# LiDAR Diffusion"
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- DESCRIPTION = """Official demo for **LiDAR Diffusion: Towards Realistic Scene Generation with LiDAR Diffusion Models**.
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- Please refer to our [paper](https://arxiv.org/abs/2404.00815), [project page](https://lidar-diffusion.github.io/), or [github](https://github.com/hancyran/LiDAR-Diffusion) for more details."""
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- BIBTEX = r"""
 
 
 
 
 
 
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  ```bibtex
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  @inproceedings{ran2024towards,
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  title={Towards Realistic Scene Generation with LiDAR Diffusion Models},
 
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  }
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  """
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  DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
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+
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+ HEADER = '''
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+ # LiDAR Diffusion
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+ Official demo for **LiDAR Diffusion: Towards Realistic Scene Generation with LiDAR Diffusion Models**.
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+ Please refer to our [paper](https://arxiv.org/abs/2404.00815), [project page](https://lidar-diffusion.github.io/), or [github](https://github.com/hancyran/LiDAR-Diffusion) for more details.
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+
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+ ### Camera-to-LiDAR Demo
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+ '''
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+
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+ FOOTER = r"""
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  ```bibtex
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  @inproceedings{ran2024towards,
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  title={Towards Realistic Scene Generation with LiDAR Diffusion Models},