Spaces:
Running
on
Zero
Running
on
Zero
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Browse files
app.py
CHANGED
@@ -257,26 +257,16 @@ def split_image(image: Image.Image) -> List[Image.Image]:
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with gr.Blocks(delete_cache=(600, 600)) as demo:
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gr.Markdown("""
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## Image to 3D Asset
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* Upload an image and click "Generate" to create a 3D asset.
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* If you find the generated 3D asset satisfactory, click "Extract GLB" to extract the GLB file and download it.
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✨New: 1) Experimental multi-image support. 2) Gaussian file extraction.
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""")
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with gr.Row():
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with gr.Column():
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with gr.Tabs() as input_tabs:
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with gr.Tab(label="Single Image", id=0) as single_image_input_tab:
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image_prompt = gr.Image(label="Image Prompt", format="png", image_mode="RGBA", type="pil", height=300)
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with gr.Tab(label="Multiple Images", id=1) as multiimage_input_tab:
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multiimage_prompt = gr.Gallery(label="Image Prompt", format="png", type="pil", height=300, columns=3)
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gr.Markdown("""
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Input different views of the object in separate images.
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*NOTE: this is an experimental algorithm without training a specialized model. It may not produce the best results for all images, especially those having different poses or inconsistent details.*
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""")
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with gr.Accordion(label="Generation Settings", open=False):
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seed = gr.Slider(0, MAX_SEED, label="Seed", value=0, step=1)
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randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
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with gr.Blocks(delete_cache=(600, 600)) as demo:
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gr.Markdown("""
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## Image to 3D Asset Generator
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* Upload an image and click "Generate" to create a 3D asset.
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* If you find the generated 3D asset satisfactory, click "Extract GLB" to extract the GLB file and download it.
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""")
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with gr.Row():
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with gr.Column():
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with gr.Tabs() as input_tabs:
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with gr.Tab(label="Single Image", id=0) as single_image_input_tab:
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image_prompt = gr.Image(label="Image Prompt", format="png", image_mode="RGBA", type="pil", height=300)
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with gr.Accordion(label="Generation Settings", open=False):
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seed = gr.Slider(0, MAX_SEED, label="Seed", value=0, step=1)
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randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
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