Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -38,6 +38,7 @@ def preprocess_images(images: List[Tuple[Image.Image, str]]) -> List[Image.Image
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def pack_state(gs: Gaussian, mesh: MeshExtractResult) -> dict:
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return {
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'gaussian': {
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'_xyz': gs._xyz.cpu().numpy(),
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'_features_dc': gs._features_dc.cpu().numpy(),
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'_scaling': gs._scaling.cpu().numpy(),
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@@ -192,7 +193,8 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
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slat_guidance_strength = gr.Slider(0.0, 10.0, label="Guidance Strength", value=3.0, step=0.1)
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slat_sampling_steps = gr.Slider(1, 50, label="Sampling Steps", value=12, step=1)
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multiimage_algo = gr.Radio(["stochastic", "multidiffusion"], label="Multi-image Algorithm", value="stochastic")
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-
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with gr.Accordion(label="GLB Extraction Settings", open=False):
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mesh_simplify = gr.Slider(0.9, 0.98, label="Simplify", value=0.95, step=0.01)
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def pack_state(gs: Gaussian, mesh: MeshExtractResult) -> dict:
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return {
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'gaussian': {
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**gs.init_params,
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'_xyz': gs._xyz.cpu().numpy(),
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'_features_dc': gs._features_dc.cpu().numpy(),
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'_scaling': gs._scaling.cpu().numpy(),
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slat_guidance_strength = gr.Slider(0.0, 10.0, label="Guidance Strength", value=3.0, step=0.1)
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slat_sampling_steps = gr.Slider(1, 50, label="Sampling Steps", value=12, step=1)
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multiimage_algo = gr.Radio(["stochastic", "multidiffusion"], label="Multi-image Algorithm", value="stochastic")
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+
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generate_btn = gr.Button("Generate")
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with gr.Accordion(label="GLB Extraction Settings", open=False):
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mesh_simplify = gr.Slider(0.9, 0.98, label="Simplify", value=0.95, step=0.01)
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