// face-api 모델 가중치를 ./models 로 내려받는 스크립트.
// 출처: @vladmandic/face-api 모델 저장소 (오프라인 동작을 위해 앱에 동봉).
//   node scripts/download-models.mjs

import { mkdir, writeFile, access } from 'node:fs/promises'
import { constants } from 'node:fs'
import { join, dirname } from 'node:path'
import { fileURLToPath } from 'node:url'

const __dirname = dirname(fileURLToPath(import.meta.url))
const MODELS_DIR = join(__dirname, '..', 'models')

const BASE = 'https://raw.githubusercontent.com/vladmandic/face-api/master/model'

// 필요한 모델: SSD MobileNet v1, Tiny Face Detector, Landmark68, Recognition
const FILES = [
  'ssd_mobilenetv1_model-weights_manifest.json',
  'ssd_mobilenetv1_model.bin',
  'tiny_face_detector_model-weights_manifest.json',
  'tiny_face_detector_model.bin',
  'face_landmark_68_model-weights_manifest.json',
  'face_landmark_68_model.bin',
  'face_recognition_model-weights_manifest.json',
  'face_recognition_model.bin'
]

async function exists(p) {
  try {
    await access(p, constants.F_OK)
    return true
  } catch {
    return false
  }
}

async function download(file) {
  const dest = join(MODELS_DIR, file)
  if (await exists(dest)) {
    console.log(`  skip  ${file} (이미 존재)`)
    return
  }
  const url = `${BASE}/${file}`
  const res = await fetch(url)
  if (!res.ok) throw new Error(`다운로드 실패 ${res.status}: ${url}`)
  const buf = Buffer.from(await res.arrayBuffer())
  await writeFile(dest, buf)
  console.log(`  ok    ${file} (${(buf.length / 1024).toFixed(0)} KB)`)
}

async function main() {
  await mkdir(MODELS_DIR, { recursive: true })
  console.log(`모델 다운로드 → ${MODELS_DIR}`)
  for (const f of FILES) {
    await download(f)
  }
  console.log('완료. 모델 준비됨.')
}

main().catch((err) => {
  console.error('오류:', err.message)
  process.exit(1)
})