"""PP-OCRv5 Latin inference using preloaded local model directories only."""

from __future__ import annotations

import argparse
import json
import os
from pathlib import Path


ROOT = Path(os.environ.get("OCR_MODEL_HOME", Path(__file__).resolve().parents[1] / ".cache")).expanduser().resolve()
MODELS = ROOT / "official_models"


def main() -> None:
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("image", type=Path)
    parser.add_argument("output", type=Path)
    parser.add_argument("--fine-text", action="store_true")
    args = parser.parse_args()
    image, output = args.image, args.output
    detector = MODELS / "PP-OCRv5_mobile_det"
    recognizer = MODELS / "latin_PP-OCRv5_mobile_rec"
    if not (detector / "inference.pdiparams").is_file() or not (recognizer / "inference.pdiparams").is_file():
        raise SystemExit(3)
    from paddleocr import PaddleOCR

    engine = PaddleOCR(
        text_detection_model_name="PP-OCRv5_mobile_det",
        text_detection_model_dir=str(detector),
        text_recognition_model_name="latin_PP-OCRv5_mobile_rec",
        text_recognition_model_dir=str(recognizer),
        use_doc_orientation_classify=False,
        use_doc_unwarping=False,
        use_textline_orientation=False,
        text_det_limit_side_len=2048 if args.fine_text else 960,
        text_det_limit_type="max",
        device="cpu",
    )
    results = list(engine.predict(str(image)))
    if len(results) != 1:
        raise RuntimeError("expected_one_page")
    raw = results[0].json["res"]
    lines = []
    for text, polygon in zip(raw["rec_texts"], raw["rec_polys"]):
        points = [[int(x), int(y)] for x, y in polygon]
        xs, ys = zip(*points)
        lines.append({"text": str(text), "bbox": [min(xs), min(ys), max(xs), max(ys)]})
    output.write_text(json.dumps({"lines": lines}, ensure_ascii=False))


if __name__ == "__main__":
    main()