feat: surgery pipeline API, video inference, voice confirm, and tests

- Add FastAPI routes for surgery start/end, results, pending confirmation (WAV upload), and health checks.
- Implement RTSP/Hikvision capture, consumable classification, session manager, MinIO/Baidu voice resolution, and DB persistence.
- Add documentation (client API, video backends, staging checklist) and sample camera/RTSP config.
- Add pytest suite (API contract, session manager, voice, repositories, pipeline persistence) and httpx dev dependency.
- Replace deprecated HTTP_422_UNPROCESSABLE_ENTITY with HTTP_422_UNPROCESSABLE_CONTENT.
- Fix SurgeryPipeline DB reads to use an explicit transaction with autobegin disabled.

Made-with: Cursor

app/services/video/frame_encode.py

@@ -0,0 +1,13 @@
+from __future__ import annotations
+
+import cv2
+import numpy as np
+
+
+def frame_to_jpeg_bytes(frame: np.ndarray, *, quality: int = 85) -> bytes:
+    """Encode BGR frame to JPEG bytes for model services expecting image bytes."""
+    params = [int(cv2.IMWRITE_JPEG_QUALITY), int(quality)]
+    ok, buf = cv2.imencode(".jpg", frame, params)
+    if not ok or buf is None:
+        raise RuntimeError("cv2.imencode failed for JPEG")
+    return buf.tobytes()