julian
6933406ae3
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
38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
"""Runtime configuration, from environment (prefix VISION_).
|
|
|
|
Offline-first: every default is local and works with no network. The recognizer is
|
|
chosen by `recognizer` — "stub" (no models, deterministic placeholder) or "fast_alpr"
|
|
(the real MIT YOLOv9+CCT/ONNX stack, installed via the `alpr` extra).
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
from typing import Literal
|
|
|
|
from pydantic_settings import BaseSettings, SettingsConfigDict
|
|
|
|
|
|
class Settings(BaseSettings):
|
|
model_config = SettingsConfigDict(env_prefix="VISION_", env_file=".env", extra="ignore")
|
|
|
|
host: str = "0.0.0.0"
|
|
port: int = 8089
|
|
|
|
# Which recognizer to load. "stub" needs no model weights (boots anywhere, for
|
|
# dev/CI); "fast_alpr" loads the real models (requires the `alpr` extra installed).
|
|
recognizer: Literal["stub", "fast_alpr"] = "stub"
|
|
|
|
# fast-alpr model names (only used when recognizer="fast_alpr"). Defaults match the
|
|
# library defaults; swap the OCR for the 40+country EU model to benchmark Albanian
|
|
# plates. See wiki/entities/opencv-anpr-service.md "Recognizer evaluation".
|
|
detector_model: str = "yolo-v9-t-384-license-plate-end2end"
|
|
ocr_model: str = "cct-xs-v2-global-model"
|
|
|
|
# Below this OCR confidence the read is returned but flagged low_confidence, so the
|
|
# Node side can fall back to the ticket path rather than trust it.
|
|
min_confidence: float = 0.5
|
|
|
|
|
|
def get_settings() -> Settings:
|
|
return Settings()
|