LTT commited on
Commit
9330b46
1 Parent(s): 8bdf0a6

Update app.py

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Files changed (1) hide show
  1. app.py +37 -36
app.py CHANGED
@@ -321,37 +321,37 @@ def make3d(images):
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  # get triplane
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  planes = model.forward_planes(images, input_cameras)
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- # get video
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- chunk_size = 20 if IS_FLEXICUBES else 1
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- render_size = 512
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- frames = []
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- frames, albedos, pbr_spec_lights, pbr_diffuse_lights, normals, alphas = render_frames(
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- model,
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- planes,
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- render_cameras=all_mvp,
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- camera_pos=all_campos,
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- env=ENV,
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- materials=materials,
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- render_size=render_size,
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- chunk_size=chunk_size,
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- is_flexicubes=IS_FLEXICUBES,
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- )
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- normals = (torch.nn.functional.normalize(normals) + 1) / 2
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- normals = normals * alphas + (1-alphas)
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- all_frames = torch.cat([frames, albedos, pbr_spec_lights, pbr_diffuse_lights, normals], dim=3)
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- images_to_video(
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- all_frames,
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- video_fpath,
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- fps=30,
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- )
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- print(f"Video saved to {video_fpath}")
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  mesh_fpath, mesh_glb_fpath = make_mesh(mesh_fpath, planes)
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-
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- return video_fpath, mesh_fpath, mesh_glb_fpath
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  import gradio as gr
@@ -361,7 +361,7 @@ _HEADER_ = '''
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  **PRM** is a feed-forward framework for high-quality 3D mesh generation with fine-grained local details from a single image.
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- Code: <a href='https://github.com/g3956/PRM' target='_blank'>GitHub</a>.
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  '''
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  _CITE_ = r"""
@@ -450,14 +450,14 @@ with gr.Blocks() as demo:
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  interactive=False
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  )
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- with gr.Column():
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- with gr.Column():
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- output_video = gr.Video(
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- label="video", format="mp4",
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- width=768,
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- autoplay=True,
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- interactive=False
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- )
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  with gr.Row():
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  with gr.Tab("OBJ"):
@@ -492,7 +492,8 @@ with gr.Blocks() as demo:
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  ).success(
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  fn=make3d,
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  inputs=[mv_images],
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- outputs=[output_video, output_model_obj, output_model_glb]
 
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  )
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  # demo.queue(max_size=10)
 
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  # get triplane
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  planes = model.forward_planes(images, input_cameras)
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+ # # get video
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+ # chunk_size = 20 if IS_FLEXICUBES else 1
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+ # render_size = 512
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+ # frames = []
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+ # frames, albedos, pbr_spec_lights, pbr_diffuse_lights, normals, alphas = render_frames(
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+ # model,
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+ # planes,
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+ # render_cameras=all_mvp,
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+ # camera_pos=all_campos,
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+ # env=ENV,
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+ # materials=materials,
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+ # render_size=render_size,
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+ # chunk_size=chunk_size,
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+ # is_flexicubes=IS_FLEXICUBES,
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+ # )
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+ # normals = (torch.nn.functional.normalize(normals) + 1) / 2
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+ # normals = normals * alphas + (1-alphas)
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+ # all_frames = torch.cat([frames, albedos, pbr_spec_lights, pbr_diffuse_lights, normals], dim=3)
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+ # images_to_video(
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+ # all_frames,
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+ # video_fpath,
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+ # fps=30,
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+ # )
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+ # print(f"Video saved to {video_fpath}")
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  mesh_fpath, mesh_glb_fpath = make_mesh(mesh_fpath, planes)
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+ return mesh_fpath, mesh_glb_fpath
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+ # return video_fpath, mesh_fpath, mesh_glb_fpath
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  import gradio as gr
 
361
 
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  **PRM** is a feed-forward framework for high-quality 3D mesh generation with fine-grained local details from a single image.
363
 
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+ Code: <a href='https://github.com/g3956/PRM' target='_blank'>GitHub</a>. Techenical report: <a href='https://arxiv.org/abs/2404.07191' target='_blank'>ArXiv</a>.
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  '''
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  _CITE_ = r"""
 
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  interactive=False
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  )
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+ # with gr.Column():
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+ # with gr.Column():
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+ # output_video = gr.Video(
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+ # label="video", format="mp4",
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+ # width=768,
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+ # autoplay=True,
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+ # interactive=False
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+ # )
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  with gr.Row():
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  with gr.Tab("OBJ"):
 
492
  ).success(
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  fn=make3d,
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  inputs=[mv_images],
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+ outputs=[output_model_obj, output_model_glb]
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+ # outputs=[output_video, output_model_obj, output_model_glb]
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  )
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  # demo.queue(max_size=10)