Initial commit: AI Photo Organizer (Electron + face-api)

Local-first photo organizer that auto-sorts images by face recognition
and EXIF capture date.

- Electron app with 3-process split: Main (Node) / UI Renderer (React) /
  hidden Inference Renderer (face-api + WebGL)
- Core pipeline: scan -> face match + EXIF -> path build -> atomic move/copy
- Move = copy -> verify -> delete; auto-rename on filename collision
- 1st-registered profile = move, others = copy; unmatched -> [미정]/YYYY/MM
- EXIF date with mtime fallback
- Vitest unit tests (pathBuilder / fileOps / concurrency) all green
- electron-builder config for Windows (nsis) + macOS (dmg)
- Docs: PRD / DECISIONS / ARCHITECTURE

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

scripts/download-models.mjs

@@ -0,0 +1,62 @@
+// 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)
+})