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        LICENSE
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            MIT License
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            Copyright (c) 2025  | 
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            Permission is hereby granted, free of charge, to any person obtaining a copy
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            of this software and associated documentation files (the "Software"), to deal
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            MIT License
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            Copyright (c) 2025 AmieDD
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            Permission is hereby granted, free of charge, to any person obtaining a copy
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            of this software and associated documentation files (the "Software"), to deal
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        README.md
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            ---
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            title:  | 
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            emoji: 🧩
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            colorFrom: blue
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            colorTo: pink
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            app_file: app.py
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            pinned: false
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            license: mit
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            short_description: 3D Mesh Generation | 
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            ---
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            Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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            ---
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            title: 3D PartAlchemy
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            emoji: 🧩
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            colorFrom: blue
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            colorTo: pink
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            app_file: app.py
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            pinned: false
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            license: mit
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            short_description: Image to 3D Mesh Generation
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            ---
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        app.py
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                        margin: 0 auto;
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                        max-width: 1280px;
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                    }
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                    """
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                theme = gr.themes.Ocean()
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                        with gr.Row():
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                            with gr.Column(scale=1):
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                                gr.Markdown(
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                                """ 
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                                • We would like to acknowledge : [@alexandernasa](https://twitter.com/alexandernasa/) for the contribution of the Hugging Face Space. """
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                                )
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                                input_image = gr.Image(type="filepath", label="Input Image", height=256)
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                                num_parts = gr.Slider(1, MAX_NUM_PARTS, value=4, step=1, label="Number of Parts")
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                                run_button = gr.Button("🧩 Generate 3D Parts", variant="primary")
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                                with gr.Accordion("Advanced Settings", open=False):
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                                    seed = gr.Number(value=0, label="Random Seed", precision=0)
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                        margin: 0 auto;
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                        max-width: 1280px;
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                    }
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                    .pink-button {
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                        background: linear-gradient(45deg, #ff69b4, #ff1493) !important;
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                        border: none !important;
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                        color: white !important;
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                    }
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                    .pink-button:hover {
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                        background: linear-gradient(45deg, #ff1493, #dc143c) !important;
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                    }
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                    """
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                theme = gr.themes.Ocean()
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                        with gr.Row():
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                            with gr.Column(scale=1):
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                                gr.Markdown(
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                                )
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                                input_image = gr.Image(type="filepath", label="Input Image", height=256)
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                                num_parts = gr.Slider(1, MAX_NUM_PARTS, value=4, step=1, label="Number of Parts")
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                                run_button = gr.Button("🧩 Generate 3D Parts", variant="primary", elem_classes=["pink-button"])
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                                with gr.Accordion("Advanced Settings", open=False):
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                                    seed = gr.Number(value=0, label="Random Seed", precision=0)
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        datasets/README.md
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            We provide the data preprocessing pipeline for PartCrafter. By following the instructions, you can generate the training data from the raw GLB data. While we are considering releasing the preprocessed dataset, please note that it may take some time before it becomes available. 
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            ## Download Raw Data
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            Our final model uses a subset of [Objaverse](https://huggingface.co/datasets/allenai/objaverse) provided by [LGM](https://github.com/ashawkey/objaverse_filter)  | 
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            ## Data Preprocess
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            We provide several scripts to preprocess the raw GLB files [here](./preprocess/). These scripts are minimal implementations and illustrate the whole preprocessing pipeline on a single 3D object. 
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            ## Download Raw Data
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            Our final model uses a subset of [Objaverse](https://huggingface.co/datasets/allenai/objaverse) provided by [LGM](https://github.com/ashawkey/objaverse_filter) 
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            ## Data Preprocess
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            We provide several scripts to preprocess the raw GLB files [here](./preprocess/). These scripts are minimal implementations and illustrate the whole preprocessing pipeline on a single 3D object. 
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