Upload __main__.py

__main__.py

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+"""
+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()