This repository implements a modern Automatic Number Plate Recognition (ANPR) pipeline as a production-ready application. It ingests images (via HTTP upload or WebSocket stream), runs detection using the `fast-alpr` library (YOLO-based ONNX model), performs OCR with `fast-plate-ocr`, applies post-processing (confusion-pair correction, Turkish plate format parsing, temporal majority voting), optionally tracks vehicles via an IoU-based multi-object tracker, and stores only HMAC-SHA256 hashed plate texts for privacy compliance. The system is exposed through a FastAPI REST API with WebSocket support and a HTMX web UI, plus a Typer CLI for inference and server management. It is containerized with Docker and publishes to PyPI and GHCR. The repository also contains a legacy directory (`legacy/`) with a complete YOLOv5 training pipeline for license plate detection, but that code is explicitly unmaintained and serves as historical reference only. The modern codebase is actively maintained, well-tested, and demonstrates strong software engineering practices including protocol-based abstractions, structured logging, Prometheus metrics, and privacy-by-design persistence.