feat(vision): scaffold apps/vision ANPR microservice (FastAPI, stub recognizer)

Skeleton of the host-side vision service per the packaging decision: a Python/FastAPI
app at apps/vision/, uv-managed, wired into the Turbo graph via a thin package.json
shim (dev/lint/test/build → uv/uvicorn/ruff/pytest). A per-package turbo.json sets
build outputs [] so the no-op build is warning-free.

Endpoints: GET /health (readiness + model version) and POST /analyze (raw
octet-stream body, so Node POSTs Snapshot.bytes directly; empty→400, oversize→413,
recognizer-not-ready→503). The recognizer is a Protocol with a StubRecognizer (no
models, boots/tests offline — the dev/CI default) and a FastAlprRecognizer (the real
MIT YOLOv9+CCT/ONNX stack, lazily imported; missing models ⇒ ready=False, not a crash)
— the device-adapter pattern applied to the model. fast-alpr + onnxruntime are an
optional `alpr` extra, so `uv sync` needs no model download.

Verified: turbo run lint|test|build includes @parking/vision and stays green; uv run
mypy strict-clean; uvicorn boots and serves /health + /analyze live; pnpm workspace
6→7. Not built yet: the Node VisionClient adapter, a Dockerfile + model fetch, and
Job 2 (vehicle verification). Updates the packaging decision (As-scaffolded) + log.

Claude-Session: https://claude.ai/code/session_01Xcm6ikLgGoCxxHrxtjkk5V

apps/vision/vision_service/schemas.py

@@ -0,0 +1,56 @@
+"""The /analyze response contract — the shape the Node VisionClient adapter consumes.
+
+Mirrors the first-cut API in wiki/entities/opencv-anpr-service.md:
+  { plate: {text, confidence, bbox}|null, vehicle: {...}|null, modelVersion, tookMs }
+Job 2 (vehicle attributes) is scaffolded as an optional field, not yet populated —
+fast-alpr is plate-only; the vehicle stage is built later on the same ONNX runtime.
+"""
+
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class BBox(BaseModel):
+    """Plate bounding box in pixels (top-left origin)."""
+
+    x1: int
+    y1: int
+    x2: int
+    y2: int
+
+
+class PlateResult(BaseModel):
+    text: str
+    confidence: float = Field(ge=0.0, le=1.0)
+    bbox: BBox | None = None
+
+
+class VehicleResult(BaseModel):
+    """Job 2 — vehicle attributes / fingerprint (anti-spoofing). Not yet produced."""
+
+    colour: str | None = None
+    body_type: str | None = None
+    make: str | None = None
+    model: str | None = None
+
+
+class AnalyzeResponse(BaseModel):
+    # The single best plate, or null when none was found.
+    plate: PlateResult | None = None
+    # All plates found (a frame may contain several vehicles).
+    plates: list[PlateResult] = Field(default_factory=list)
+    vehicle: VehicleResult | None = None
+    # True when the best plate is below the confidence floor — Node should treat the
+    # read as advisory only and prefer the ticket path. See fail-state-safety.
+    low_confidence: bool = False
+    model_version: str
+    took_ms: float
+
+
+class HealthResponse(BaseModel):
+    status: str
+    recognizer: str
+    ready: bool
+    model_version: str
+    detail: str | None = None