# STER code

Scripts run against the official 3dSAGER repo (BarGenossar/3dSAGER) checkout.

| file | purpose |
|------|---------|
| `ster_repro.py` | Reproduce official matching pipeline (Bagging F1=0.946 on Hague-small). |
| `ster_diagnostic.py` | Headroom map: few-shot / long-tail / discrepancy strata. |
| `ster_fewshot.py` | Few-shot baseline landscape across 8 classifiers (bar-setting). |
| `crawl_3dbag_multilod.py` | Crawl 3DBAG multi-LoD (LoD1.2/1.3/2.2) via api.3dbag.nl. |
| `ster_crosslod.py` | Cross-LoD matching + zero-shot difficulty (run after crawl). |
| `ster_export_vectors.py` | Compute per-building 25-D vectors (multi-LoD + Hague) -> `data/ster_wm_vectors.npz`. |
| `ster_wm.py` | STER-WM: InfoNCE self-supervised identity encoder + few-shot fine-tune + hybrid (GPU). |
| `ster_fusion.py` | Rank-fusion of WM cosine + raw Bagging across K (GPU). |
| `ster_proto.py` | Few-shot prototype/metric head on WM relation vectors (GPU). |
| `ster_combo.py` | Sample-efficient linear head on [raw-ratio ⊕ WM-relation] + fusion (GPU). |
| `ster_zeroshot.py` | Zero-shot: train only on multi-LoD (0 target labels), transfer to Hague (GPU). |
| `ster_noisy.py` | Cross-LoD hard-negative matching (noisy regime) (GPU). |
| `ster_flow_v2.py` | Flow-Matching zero-shot (scale-invariant direction cosine); confirmed non-transfer (GPU). |
| `clip.py` | Stub so `import clip` succeeds (ViT baseline unused in matching). |

Dependencies: numpy, pandas, scikit-learn, scipy, xgboost, shapely, pyproj, faiss-cpu, torch. Pod (CPU) computes properties; GPU (torch 2.8+cu128) trains WM/Flow.