"""단독 프로세스로 FaceLandmarker를 실행해 478 랜드마크를 JSON으로 출력한다.
(같은 프로세스에서 ImageSegmenter와 함께 쓰면 세그폴트가 재현되어 분리했다.)

사용: python _run_face_landmarks.py <이미지경로> <출력json경로>
"""
from __future__ import annotations

import json
import sys
from pathlib import Path

import mediapipe as mp
import numpy as np
from mediapipe.tasks import python as mp_python
from mediapipe.tasks.python import vision
from PIL import Image

MODEL_FACE = Path(__file__).resolve().parent / "_models" / "face_landmarker.task"


def main() -> int:
    image_path = Path(sys.argv[1])
    out_path = Path(sys.argv[2])

    base_options = mp_python.BaseOptions(model_asset_path=str(MODEL_FACE))
    options = vision.FaceLandmarkerOptions(
        base_options=base_options, running_mode=vision.RunningMode.IMAGE, num_faces=1
    )
    im = Image.open(image_path).convert("RGB")
    w, h = im.size
    arr = np.array(im)
    mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=arr)
    with vision.FaceLandmarker.create_from_options(options) as landmarker:
        result = landmarker.detect(mp_image)

    if not result.face_landmarks:
        out_path.write_text(json.dumps({"ok": False}), encoding="utf-8")
        print("FACE_LANDMARKS_FAILED")
        return 1

    lm = result.face_landmarks[0]
    pts = [[p.x * w, p.y * h] for p in lm]
    out_path.write_text(json.dumps({"ok": True, "width": w, "height": h, "points": pts}), encoding="utf-8")
    print(f"FACE_LANDMARKS_OK n={len(pts)}")
    return 0


if __name__ == "__main__":
    sys.exit(main())