feat: RapidOCR default OCR engine, office-only ocr_engine, drop operator toggle

README.md

@@ -97,8 +97,8 @@ batch mode, DO upload/staged/settings, CSV/Excel export). Data source:
 | `do_manual` | Operator + DO photo scan | yes |
 | `manual` | Operator buttons (legacy) | no |
 
-Office (`:5721`) switches mode / model mode / require_plate (403 on operator
-POST). **DO manual flow:** open `http://<jetson>:5000/operator` on a phone →
+Office (`:5721`) switches mode / model mode / require_plate / ocr_engine (403
+on operator POST). **DO manual flow:** open `http://<jetson>:5000/operator` on a phone →
 Ambil Foto DO → review/edit OCR fields → Mulai Batch → count → Selesai
 (soft-warn if zone busy). Discard only when both sack and box nets are 0.
 ERD: [`ERD.md`](ERD.md).
@@ -117,7 +117,6 @@ archive/              Retired experiments (predict_new.py, rpo_iki/, simple_pred
                       check/merge/test scripts) — history preserved, not imported
 export_model.py       Export .pt → TensorRT .engine (FP16)  |  export_v4.py  variant
 deploy_to_jetson.py   Paramiko sync + service restart
-scripts/              Loose helpers (frame sampling, DB check, guide PDF)
 *.service             systemd units (counter, dashboard, mediamtx)
 zones.json            Calibrated zone geometry
 batch_history_folder/ Per-batch JSON reports