Function main

scripts/python/MvsPointCloud2TSDF.py:319–353

()

def main():
    parser = argparse.ArgumentParser(description="Reconstruct a mesh from a point cloud with normals using TSDF.")
    parser.add_argument("-i", "--input", type=str, required=True, help="Path to input PLY file")
    parser.add_argument("-o", "--output", type=str, default="mesh.ply", help="Path to output PLY file")
    parser.add_argument("-x", "--voxel_size", type=float, default=0.0, help="Voxel size (0 for auto-estimation)")
    parser.add_argument("-t", "--truncation_mult", type=float, default=3.0, help="Truncation multiplier (default: 3.0)")
    parser.add_argument("-c", "--chunk_size", type=int, default=100000, help="Chunk size for vectorized processing (default: 10000)")
    parser.add_argument("--method", type=str, choices=["splatting", "voxel"], default="splatting", help="Method: 'splatting' (sparse, faster) or 'voxel' (dense, KDTree)")

    args = parser.parse_args()

    if not os.path.exists(args.input):
        print(f"Error: {args.input} not found.")
        return

    print(f"Loading {args.input}...")
    try:
        points, normals = load_ply(args.input)
    except Exception as e:
        print(f"Error loading points: {e}")
        return
    print(f"Loaded {len(points)} points.")

    if args.method == "voxel":
        # Check for scipy
        try:
            import scipy
        except ImportError:
            print("Error: 'voxel' method requires 'scipy'. Please install it: pip install scipy")
            return
        sdf_grid, min_bound, vs = compute_tsdf_voxel(points, normals, args.voxel_size, args.truncation_mult, args.chunk_size)
        extract_mesh_dense(sdf_grid, min_bound, vs, args.output)
    else:
        tsdf_vol, min_bound, vs = splat_points_to_tsdf(points, normals, args.voxel_size, args.truncation_mult, args.chunk_size)
        extract_mesh(tsdf_vol, min_bound, vs, args.output)

if __name__ == "__main__":
    main()