SEAM Studio

Unified RF–visual scene authoring, RF material assignment, and Sionna RT digital-twin simulation — in one local workbench.

SEAM Studio pairs a FastAPI backend with a bundled React/three.js frontend: author a 3D scene, bind ITU/custom RF materials to its surfaces (by hand, by rules, or with a local-LLM agent), then ray-trace paths, radio maps, UE/UAV trajectories, Doppler, beamforming and handover — all persisted as reproducible result sets.

Install

pip install seam-studio

This installs the real ray-tracing engine (sionna-rt, Dr.Jit/Mitsuba) by default — no GPU required (an LLVM CPU backend is used when CUDA is absent), and the app falls back to its deterministic Mock engine if the import fails.

Quickstart

seam-studio            # starts on http://127.0.0.1:8000 and opens the browser

The first run creates a Sample Demo project (toy urban scene with a rooftop TX, street RX, car and pedestrian actors) under ~/.seam/projects, so you can press Simulate paths immediately.

seam-studio --port 9000            # different port
seam-studio --project-root D:\twins  # keep projects elsewhere
seam-studio --no-browser

Highlights

• Scene → RF binding: import Mitsuba XML / scene bundles / OpenStreetMap extrusions; assign RF materials per surface with validation and provenance.
• Simulation: paths, planar & mesh radio maps, multi-TX SINR/RSRP/RSRQ, MIMO beamforming, UE/UAV trajectories with per-step handover (3GPP A3), Doppler spectrograms, ML ground-truth dataset export (NPZ).
• AI assist: local LLM/VLM material suggestion agent (Ollama / LM Studio), natural-language assignment rules, validation explains.
• Reproducibility: every run persisted with config snapshots + content hashes; measurement import and calibration against real logs.

Links

• Repository & docs: https://github.com/jaewoo4200/SEAM
• Website: https://jaewoo4200.github.io/SEAM/

Apache-2.0 © Jaewoo Lee