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--- |
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language: en |
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license: mit |
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tags: [3d-reconstruction, foot-scanning, 3dgs, colmap, sugar] |
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library_name: other |
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pipeline_tag: other |
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--- |
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# AMADEUS – 3D Foot Reconstruction Pipeline |
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AMADEUS (AI‑based Morphological Analysis & Design Engine for Unique Shoes) reconstructs a personalized 3D foot model from smartphone video and produces a ready-to-print shoe last. It combines YOLO11n-seg + SAM for segmentation, COLMAP for camera pose estimation, 3D Gaussian Splatting (3DGS) for point cloud optimisation, and SuGaR for mesh generation【528303309685221†L80-L94】. |
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## Pipeline |
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1. **Pre‑processing:** Segment the foot and scale marker from each frame and save masked images【717972134425363†screenshot】. |
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2. **3D Reconstruction:** Use COLMAP to build a sparse point cloud【894071447112061†screenshot】. |
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3. **Undistortion & Alignment:** Remove lens distortion and align the sparse model【894071447112061†screenshot】. |
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4. **3DGS Training:** Optimise a Gaussian point cloud to produce a dense representation【35837800387949†screenshot】. |
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5. **Meshing & Healing:** Convert the Gaussian field to a watertight mesh and remove noise【756719135168637†screenshot】. |
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6. **Scaling:** Convert to real-world dimensions using a checkerboard marker. |
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7. **3D Printing:** Slice and print the mesh. |
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8. **Troubleshooting:** Fix segmentation resolution mismatches and ensure adequate data【756719135168637†screenshot】. |
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## Installation and Usage |
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### Docker |
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``` |
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docker build -t amadeus . |
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docker run --gpus all -it --rm \ |
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-v $(pwd)/data:/app/data \ |
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-v $(pwd)/output:/app/output \ |
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amadeus |
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chmod +x run_pipeline.sh |
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xvfb-run -a ./run_pipeline.sh |
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``` |
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### Manual Setup |
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Clone submodules (`gaussian-splatting` and `SuGaR`), install dependencies from `requirements.txt`, install COLMAP, and run the commands in `run_pipeline.sh` manually. |
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## Citation |
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If you use this project, please cite: |
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``` |
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@report{amadeus2025, |
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title = {AI‑based Morphological Analysis & Design Engine for Unique Shoes}, |
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author = {Kim Taeryang and Park Hyundong and Park Chanwoo and Bang Hojun}, |
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year = {2025}, |
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note = {P–Practical Project third semester (AI) team 3 report} |
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} |
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``` |
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## License |
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MIT License. |
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