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dylanebert
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Running on Zero

dylanebert HF staff commited on
Commit
d122969
·
verified ·
1 Parent(s): 97c2903

remove external mesh conversion

Browse files
Files changed (1) hide show
  1. app.py +5 -26
app.py CHANGED
@@ -33,8 +33,8 @@ splat_pipeline = DiffusionPipeline.from_pretrained(
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  ).to("cuda")
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- @spaces.GPU(duration=420)
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- def run(input_image, convert):
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  input_image = input_image.astype("float32") / 255.0
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  images = image_pipeline(
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  "", input_image, guidance_scale=5, num_inference_steps=30, elevation=0
@@ -42,18 +42,7 @@ def run(input_image, convert):
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  gaussians = splat_pipeline(images)
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  output_ply_path = os.path.join(TMP_DIR, "output.ply")
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  splat_pipeline.save_ply(gaussians, output_ply_path)
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- if convert:
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- output_mesh_path = convert_to_mesh(output_ply_path)
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- return output_mesh_path
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- else:
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- return output_ply_path
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-
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-
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- def convert_to_mesh(input_ply):
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- client = Client("https://dylanebert-splat-to-mesh.hf.space/")
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- output_mesh_path = client.predict(file(input_ply), api_name="/run")
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- client.close()
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- return output_mesh_path
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  _TITLE = """LGM Mini"""
@@ -61,6 +50,8 @@ _TITLE = """LGM Mini"""
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  _DESCRIPTION = """
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  <div>
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  A lightweight version of <a href="https://huggingface.co/spaces/ashawkey/LGM">LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation</a>.
 
 
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  </div>
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  """
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@@ -86,19 +77,7 @@ with block:
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  with gr.Row(variant="panel"):
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  with gr.Column(scale=1):
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-
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- def update_warning(checked):
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- if checked:
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- return '<span style="color: #ff0000;">Warning: Mesh conversion takes several minutes and might not work. Visit https://huggingface.co/spaces/dylanebert/splat-to-mesh to convert yourself.</span>'
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- else:
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- return ""
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-
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  input_image = gr.Image(label="image", type="numpy")
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- convert_checkbox = gr.Checkbox(label="Convert to Mesh")
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- warning = gr.HTML()
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- convert_checkbox.change(
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- fn=update_warning, inputs=[convert_checkbox], outputs=[warning]
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- )
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  button_gen = gr.Button("Generate")
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  with gr.Column(scale=1):
 
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  ).to("cuda")
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+ @spaces.GPU
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+ def run(input_image):
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  input_image = input_image.astype("float32") / 255.0
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  images = image_pipeline(
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  "", input_image, guidance_scale=5, num_inference_steps=30, elevation=0
 
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  gaussians = splat_pipeline(images)
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  output_ply_path = os.path.join(TMP_DIR, "output.ply")
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  splat_pipeline.save_ply(gaussians, output_ply_path)
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+ return output_ply_path
 
 
 
 
 
 
 
 
 
 
 
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  _TITLE = """LGM Mini"""
 
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  _DESCRIPTION = """
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  <div>
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  A lightweight version of <a href="https://huggingface.co/spaces/ashawkey/LGM">LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation</a>.
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+
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+ To convert to mesh, download the output splat and visit [splat-to-mesh](https://huggingface.co/spaces/dylanebert/splat-to-mesh).
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  </div>
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  """
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  with gr.Row(variant="panel"):
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  with gr.Column(scale=1):
 
 
 
 
 
 
 
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  input_image = gr.Image(label="image", type="numpy")
 
 
 
 
 
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  button_gen = gr.Button("Generate")
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  with gr.Column(scale=1):