""" CLI entry point for LightweightMR reconstruction. Usage: python -m lightweightmr --input path/to/pointcloud.ply --output path/to/mesh.ply """ import argparse import os import sys from .optimize import Runner def main(): parser = argparse.ArgumentParser(description="LightweightMR — pure-Python mesh reconstruction") parser.add_argument("--input", "-i", required=True, help="Input point cloud (.ply, .pcd, .xyz)") parser.add_argument("--output", "-o", required=True, help="Output mesh file (.ply or .obj)") parser.add_argument("--device", default="cpu", help="torch device: cpu or cuda") parser.add_argument("--out-dir", default="./output", help="Intermediate outputs directory") parser.add_argument("--sdf-iters", type=int, default=20_000, help="SDF training iterations") parser.add_argument("--vg-iters", type=int, default=8_000, help="Vertex generation iterations") parser.add_argument("--sdf-lr", type=float, default=1e-3, help="SDF learning rate") parser.add_argument("--vg-lr", type=float, default=1e-3, help="VG learning rate") parser.add_argument("--sdf-batch", type=int, default=5_000, help="SDF batch size") parser.add_argument("--vertices", type=int, default=3_400, help="Target number of vertices") parser.add_argument("--update-size", type=int, default=5, help="Curriculum update steps") parser.add_argument("--update-ratio", type=float, default=1.2, help="Curriculum growth ratio") parser.add_argument("--k-samples", type=int, default=21, help="Tetrahedron interior samples") parser.add_argument("--multires", type=int, default=8, help="Positional encoding frequencies") parser.add_argument("--queries-size", type=int, default=1_000_000, help="SDF query sample count") parser.add_argument("--surface-queries", type=int, default=200_000, help="Surface query count") parser.add_argument("--project-sdf-level", type=float, default=0.0, help="SDD projection level") parser.add_argument("--save-freq", type=int, default=2_000, help="Checkpoint save frequency") parser.add_argument("--resume-sdf", default=None, help="Resume from SDF checkpoint .pth") args = parser.parse_args() if not os.path.exists(args.input): print(f"ERROR: input file not found: {args.input}") sys.exit(1) runner = Runner( pointcloud_path=args.input, out_dir=args.out_dir, device=args.device, sdf_iters=args.sdf_iters, vg_iters=args.vg_iters, sdf_lr=args.sdf_lr, vg_lr=args.vg_lr, sdf_batch=args.sdf_batch, vertices_size=args.vertices, update_size=args.update_size, update_ratio=args.update_ratio, k_samples=args.k_samples, multires=args.multires, queries_size=args.queries_size, surface_queries=args.surface_queries, project_sdf_level=args.project_sdf_level, save_freq=args.save_freq, ) if args.resume_sdf: print(f"Loading SDF checkpoint: {args.resume_sdf}") runner.load_sdf_checkpoint(args.resume_sdf) v, f = runner.run(mesh_path=args.output) print(f"\nDone! Mesh: {len(v)} vertices, {len(f)} faces") if __name__ == "__main__": main()