commit 8a8c10248c61200d8612ec895fe18e7724db9754 Author: g1nation Date: Mon Jun 1 13:36:40 2026 +0900 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) diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..bad572d --- /dev/null +++ b/.gitignore @@ -0,0 +1,13 @@ +node_modules/ +out/ +release/ +dist/ +*.log +.DS_Store +# TypeScript 증분 빌드 정보 (생성물) +*.tsbuildinfo +# ASTRA 도구 로컬 캐시 (프로젝트 산출물 아님) +.astra/ +# 모델 가중치는 용량이 커서 git에 올리지 않음 — npm run models:download 로 받음 +models/*.bin +models/*-weights_manifest.json diff --git a/README.md b/README.md new file mode 100644 index 0000000..67159ee --- /dev/null +++ b/README.md @@ -0,0 +1,67 @@ +# AI Photo Organizer + +얼굴 인식 + 촬영일(EXIF) 기준으로 사진을 **로컬에서** 자동 정리하는 Electron 데스크톱 앱. +클라우드 업로드 없이 내 PC 안에서만 동작한다. + +> 기획·설계 문서: [docs/PRD.md](docs/PRD.md) · [docs/DECISIONS.md](docs/DECISIONS.md) · [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) + +## 동작 방식 + +1. 인물 프로필(최대 3명)과 참조 얼굴 사진을 등록한다. +2. 정리할 폴더(소스)와 결과 폴더(출력)를 고른다. +3. [정리 시작] → 각 사진을 스캔해 + - 얼굴이 매칭되면 `출력/<인물>/YYYY/MM/` 로 **이동**(2·3순위 인물에게는 **복사**) + - 매칭 인물이 없으면 `출력/[미정]/YYYY/MM/` 로 이동 + - EXIF 촬영일이 없으면 파일 수정일로 대체 + +데이터 안전: 이동은 **복사 → 무결성 검증 → 원본 삭제** 순서로 수행하고, 파일명 충돌 시 `_1`, `_2` 로 자동 리네임한다(덮어쓰기 없음). + +## 기술 스택 + +Electron 33 · electron-vite · React 18 + TypeScript · Zustand · Tailwind · +[@vladmandic/face-api](https://github.com/vladmandic/face-api) (WebGL) · exifr · electron-builder + +3개 프로세스로 분리된 구조: +- **Main** (Node): 스캔 / EXIF / 파일 이동·복사 / 오케스트레이션 +- **UI Renderer** (React): 화면 — 무거운 연산 없음 +- **Inference Renderer** (숨김 창): face-api 얼굴 인식 전담 + +## 개발 + +```bash +npm install +npm run models:download # 최초 1회 — 모델 가중치 받기 +npm run dev # 개발 실행 (HMR) +``` + +## 검증 / 빌드 + +```bash +npm run typecheck # 타입체크 (node + web) +npm test # 순수 로직 단위 테스트 (Vitest) +npm run dist:all # Windows(nsis) + macOS(dmg) 인스톨러 빌드 +``` + +> macOS 타깃은 macOS 호스트에서 빌드해야 코드사이닝/공증이 가능하다(미서명 dmg는 어디서나 생성 가능). + +## 트러블슈팅 + +- **`TypeError: Cannot read properties of undefined (reading 'whenReady')`** 로 부팅 즉시 크래시하면, + 환경에 `ELECTRON_RUN_AS_NODE=1` 이 설정된 것이다. 이 변수가 있으면 Electron 바이너리가 일반 Node로 동작해 + `electron.app` 이 `undefined` 가 된다. 실행 전 변수를 해제하라: + - PowerShell: `Remove-Item Env:\ELECTRON_RUN_AS_NODE` + - bash: `unset ELECTRON_RUN_AS_NODE` + +## 폴더 구조 + +``` +src/ + main/ Main 프로세스 (scanner, exif, fileOps, orchestrator, ...) + preload/ contextBridge (UI용 index, 추론창용 inference) + renderer/ React UI + inference/ 숨김 추론 창 (faceEngine, imageLoader) + shared/ 공유 타입/상수 +models/ face-api 가중치 (download 스크립트로 채움) +tests/ Vitest 단위 테스트 +docs/ 기획·설계 문서 +``` diff --git a/docs/ARCHITECTURE.md b/docs/ARCHITECTURE.md new file mode 100644 index 0000000..771a9d8 --- /dev/null +++ b/docs/ARCHITECTURE.md @@ -0,0 +1,303 @@ +# AI Photo Organizer — 시스템 아키텍처 설계 + +> 상태: **확정 (Final)** · 최종 갱신: 2026-06-01 +> 선행 문서: [PRD](./PRD.md) · [DECISIONS.md](./DECISIONS.md) +> 승인 완료 — 본 설계로 스캐폴딩/구현 착수. + +--- + +## 0. 한눈에 보기 (TL;DR) + +- **플랫폼**: Electron 데스크톱 앱 (Windows/macOS). +- **3-프로세스 구조**: `Main`(파일·오케스트레이션) + `UI Renderer`(React 화면) + `Inference Renderer`(숨김 창, 얼굴인식 전담). +- **왜 분리?** face-api.js는 브라우저(WebGL/Canvas) 환경이 필요하고, 파일 I/O는 Node 환경이 필요하다. 둘을 다른 프로세스로 나눠 **UI 프리징 0**, **빌드 안정성**을 동시에 확보한다. +- **데이터 흐름**: 스캔(Main) → 얼굴인식(Inference) → 날짜추출(Main) → 경로생성/이동·복사(Main) → 진행률 이벤트(UI). + +--- + +## 1. 기술 스택 확정 (Tech Stack & Versions) + +| 영역 | 라이브러리 | 버전(기준) | 비고 | +|------|-----------|-----------|------| +| 런타임/셸 | **Electron** | `^33.0.0` | Chromium + Node 번들. WebGL 가속 사용. | +| 빌드 도구 | **electron-vite** | `^2.3.0` | Main/Preload/Renderer 멀티 엔트리를 Vite로 통합 빌드. | +| 번들러 | **Vite** | `^5.4` | electron-vite 내부. | +| UI | **React** | `^18.3` | 함수형 + Hooks. | +| 언어 | **TypeScript** | `^5.5` | 전 프로세스 공통. `strict: true`. | +| 상태관리 | **Zustand** | `^4.5` | 경량 글로벌 스토어 (Redux 과잉 회피). | +| 스타일 | **Tailwind CSS** | `^3.4` | 빠른 UI 구성. (선호 시 교체 가능) | +| **얼굴 인식** | **@vladmandic/face-api** | `^1.7` | 원본 `face-api.js`(유지보수 중단)의 API 호환 포크. **tfjs(WebGL 백엔드)를 내부 번들로 포함** → 별도 tfjs 의존 불필요. Inference Renderer에서만 사용. | +| **EXIF 파싱** | **exifr** | `^7.1` | 빠르고 HEIC/주요 포맷 지원. Main(Node)에서 실행. | +| 파일 작업 | **node:fs/promises** | 내장 | 비동기 I/O. | +| 동시성 제어 | **(자체 구현 세마포어)** | - | 외부 `p-limit` 대신 경량 직접 구현. | +| 패키징 | **electron-builder** | `^25` | 배포용 인스톨러(.exe/.dmg) 생성. | +| 테스트 | **Vitest** | `^2` | 순수 로직(스캐너/EXIF/경로/충돌) 단위 테스트. | + +> Node는 Electron 번들 버전(Electron 33 → Node 20 계열)을 사용하므로 별도 Node 버전 고정 불필요. + +--- + +## 2. 프로세스 아키텍처 (Process Topology) + +``` +┌──────────────────────────────────────────────────────────────────┐ +│ Electron App │ +│ │ +│ ┌─────────────────┐ IPC ┌──────────────────────┐ │ +│ │ UI Renderer │◀──────────────────▶│ Main Process │ │ +│ │ (visible window)│ progress/control │ (orchestrator/Node) │ │ +│ │ React + Zustand │ │ │ │ +│ └─────────────────┘ │ scanner / exif / │ │ +│ ▲ preload(contextBridge) │ fileOps / pathBuilder│ │ +│ │ │ profileStore /reporter│ │ +│ │ └──────────┬───────────┘ │ +│ │ │ IPC (descriptor│ +│ │ │ 요청/응답) │ +│ │ ┌──────────▼───────────┐ │ +│ │ │ Inference Renderer │ │ +│ └─────────(미표시)────────────────▶│ (hidden window) │ │ +│ │ face-api + WebGL │ │ +│ │ faceEngine/imageLoader│ │ +│ └──────────────────────┘ │ +└──────────────────────────────────────────────────────────────────┘ +``` + +### 2.1 각 프로세스 책임 + +| 프로세스 | 환경 | 책임 | +|----------|------|------| +| **Main** | Node | 폴더 스캔, EXIF 추출, 파일 이동/복사(원자성), 프로필 영속화, 작업 오케스트레이션, 리포트/로그, IPC 라우팅. | +| **UI Renderer** | Chromium(보임) | 프로필 등록 UI, 폴더 선택, 실행 제어, 실시간 진행률/파일목록, 결과 리포트 표시. **무거운 연산 없음 → 프리징 없음.** | +| **Inference Renderer** | Chromium(숨김) | face-api 모델 로드, 이미지 디코딩, 얼굴 검출·descriptor 계산, 프로필과 매칭. UI 스레드와 분리되어 연산이 화면을 막지 않음. | + +> **대안 검토**: Inference를 별도 숨김 창 대신 *Web Worker + OffscreenCanvas*로 둘 수도 있으나, face-api는 `document`/`canvas` 의존이 있어 worker 환경 패치가 까다롭다. v1은 **숨김 BrowserWindow**가 가장 안정적. (성능 이슈 시 worker로 이전 검토.) + +--- + +## 3. 모듈 구조 (Module Breakdown) + +### 3.1 Main Process (`src/main/`) + +| 모듈 | 파일 | 역할 | 핵심 인터페이스(개념) | +|------|------|------|----------------------| +| **Scanner** | `scanner.ts` | 소스 폴더 재귀 순회, 확장자 필터, 이미지 경로 스트림 산출. | `async *scan(root): AsyncIterable` | +| **ExifReader** | `exif.ts` | `DateTimeOriginal` 추출, 없으면 `fs.stat().mtime` 폴백 → `{year, month}`. | `getCaptureDate(path): Promise<{year,month}>` | +| **FileOps** | `fileOps.ts` | 이동(복사→검증→삭제)/복사, 충돌 시 자동 리네임, 원자성·오류처리. | `move(src,dest)`, `copy(src,dest)` | +| **PathBuilder** | `pathBuilder.ts` | `/<프로필>/YYYY/MM/` · `[미정]/YYYY/MM/` 경로 생성, 파일명 충돌 해소. | `build(outRoot, who, date, filename)` | +| **ProfileStore** | `profileStore.ts` | 프로필(이름·순서·참조이미지·descriptor) JSON 영속화/로드. | `load()`, `save()`, `upsert()` | +| **Orchestrator** | `orchestrator.ts` | 전체 잡 파이프라인 구동, 동시성 제어, 진행률 이벤트 발행, 중단/취소. | `run(job)`, `cancel()` | +| **InferenceBridge** | `inferenceWindow.ts` | 숨김 Inference 창 생성/관리, descriptor 요청-응답 RPC. | `detect(imagePath): Promise` | +| **Reporter** | `reporter.ts` | 통계 집계(총/성공/실패/소요), 결과 리포트 + 로그파일 출력. | `summarize()`, `writeLog()` | +| **IpcMain** | `ipc.ts` | UI/Inference 채널 핸들러 등록·라우팅. | - | +| **Logger** | `logger.ts` | 구조적 로그(파일+콘솔), 오류 추적. | - | + +### 3.2 Inference Renderer (`src/inference/`) + +| 모듈 | 파일 | 역할 | +|------|------|------| +| **FaceEngine** | `faceEngine.ts` | 모델 1회 로드(SSD MobileNet v1 + Landmark68 + Recognition), 이미지당 얼굴검출+descriptor, `FaceMatcher`로 프로필 매칭(거리 `<0.5`). | +| **ImageLoader** | `imageLoader.ts` | 파일→`HTMLImageElement`/`canvas` 디코딩, 대형 이미지 다운스케일(예: 장변 1024px), 처리 후 canvas/objectURL 해제로 메모리 회수. | +| **bootstrap** | `main.ts` | 모델 로드 완료 시 Main에 ready 통지, descriptor 요청 수신 루프. | + +### 3.3 UI Renderer (`src/renderer/`) + +| 컴포넌트 | 파일 | 역할 | +|----------|------|------| +| App 셸 | `App.tsx` | 단계별 화면 라우팅(프로필→폴더→실행→리포트). | +| ProfileManager | `components/ProfileManager.tsx` | 최대 3인 프로필 등록/수정, 참조 이미지 추가, descriptor 생성 트리거. | +| FolderPicker | `components/FolderPicker.tsx` | 소스 폴더·출력 루트 선택(다이얼로그). | +| RunControl | `components/RunControl.tsx` | 실행/취소, 임계값 등 옵션. | +| ProgressView | `components/ProgressView.tsx` | 진행률 바, 처리 중 파일명, 카운터. | +| FileList | `components/FileList.tsx` | 처리 결과 스트림(파일→대상폴더/판정) 가상 스크롤. | +| ReportView | `components/ReportView.tsx` | 총처리/성공/실패/소요시간 + 로그 열기. | +| Store | `store.ts` | Zustand: 프로필·잡상태·진행률·결과. | + +### 3.4 Preload (`src/preload/`) + +`contextBridge`로 안전한 API만 노출 (`nodeIntegration: false`, `contextIsolation: true`). +```ts +window.api = { + profiles: { list, upsert, remove, addReference }, + dialog: { pickSource, pickOutput }, + job: { run, cancel }, + on: (event, cb) => unsubscribe, // progress / fileProcessed / done / error +} +``` + +### 3.5 Shared (`src/shared/`) +`types.ts`(Profile, Job, MatchResult, ProgressEvent, Report 등), `constants.ts`(확장자, 기본 임계값, IPC 채널명). + +--- + +## 4. 데이터 흐름 (End-to-End Sequence) + +### 4.1 프로필 등록 +``` +UI: 이름 + 참조이미지 선택 + → IPC profiles.addReference(path[]) + → Main: 이미지 경로를 InferenceBridge.detect()로 전달 + → Inference: 참조이미지의 descriptor 계산 → 반환 + → Main ProfileStore: {name, order, refImages, descriptors[]} 저장 (다수 → 평균 descriptor) + → UI: 등록 완료 표시 +``` + +### 4.2 정리 잡 실행 (핵심 파이프라인) +``` +UI: [실행] (source, outputRoot, options) + → IPC job.run + → Main Orchestrator 시작 + 1) Scanner.scan(source) ──▶ 이미지 경로 큐 (스트리밍) + 2) 동시성 N(기본 3)개 워커로 각 경로 처리: + a. InferenceBridge.detect(path) + Inference: 이미지 로드 → 얼굴검출 → descriptor + → FaceMatcher로 프로필 매칭(거리<0.5) + → MatchResult { matched: [{name, order, distance}], faceFound: bool } + b. ExifReader.getCaptureDate(path) → {year, month} (없으면 mtime) + c. 분기: + - matched.length ≥ 1: + 정렬(등록순서 asc) → first=이동, rest=복사 + PathBuilder로 각 대상경로 생성 → FileOps.move/copy + - matched.length == 0 (미검출/실패): + PathBuilder([미정], date) → FileOps.move + d. 진행률/결과 이벤트 발행 → UI 갱신 + 3) 큐 소진 시 Reporter.summarize() → 로그 작성 + → IPC done(report) → UI ReportView +``` + +### 4.3 이동(Move)의 원자성 (데이터 무결성 0 Error) +``` +move(src, dest): + 1. dest 충돌 검사 → 있으면 자동 리네임(dest_1, dest_2 …) + 2. fs.copyFile(src, tmp) # 임시로 복사 + 3. 무결성 검증 (size 일치 + 필요 시 해시) + 4. rename(tmp → dest) # 원자적 노출 + 5. unlink(src) # 원본 삭제 (검증 통과 후에만) + 실패 시: 원본 보존, tmp 정리, 에러 로깅 → 잡 계속 (해당 파일만 실패 처리) +``` +> 동일 볼륨이면 `fs.rename` 최적화 가능하나, 안전성 우선으로 copy-verify-delete를 기본으로 한다. (옵션화 가능) + +--- + +## 5. 프로젝트 폴더 트리 + +``` +PhotoAI/ +├─ docs/ +│ ├─ PRD.md +│ ├─ DECISIONS.md +│ └─ ARCHITECTURE.md ← 본 문서 +├─ models/ # face-api 가중치 (ssd_mobilenetv1, landmark68, recognition) +├─ src/ +│ ├─ main/ # Main 프로세스 +│ │ ├─ index.ts # 앱 진입, 창 생성 +│ │ ├─ orchestrator.ts +│ │ ├─ scanner.ts +│ │ ├─ exif.ts +│ │ ├─ fileOps.ts +│ │ ├─ pathBuilder.ts +│ │ ├─ profileStore.ts +│ │ ├─ reporter.ts +│ │ ├─ inferenceWindow.ts +│ │ ├─ ipc.ts +│ │ └─ logger.ts +│ ├─ preload/ +│ │ └─ index.ts # contextBridge API +│ ├─ renderer/ # UI 창 +│ │ ├─ index.html +│ │ ├─ main.tsx +│ │ ├─ App.tsx +│ │ ├─ store.ts +│ │ ├─ components/ +│ │ │ ├─ ProfileManager.tsx +│ │ │ ├─ FolderPicker.tsx +│ │ │ ├─ RunControl.tsx +│ │ │ ├─ ProgressView.tsx +│ │ │ ├─ FileList.tsx +│ │ │ └─ ReportView.tsx +│ │ └─ styles/index.css +│ ├─ inference/ # 숨김 추론 창 +│ │ ├─ index.html +│ │ ├─ main.ts +│ │ ├─ faceEngine.ts +│ │ └─ imageLoader.ts +│ └─ shared/ +│ ├─ types.ts +│ └─ constants.ts +├─ tests/ # Vitest 단위 테스트 (scanner/exif/pathBuilder/fileOps) +├─ electron.vite.config.ts +├─ electron-builder.yml +├─ tsconfig.json +├─ tailwind.config.js +├─ package.json +└─ README.md +``` + +### 5.1 런타임 데이터 위치 +- **프로필 저장**: `app.getPath('userData')/profiles.json` (OS 표준 사용자 데이터 경로). 내보내기 기능으로 백업 가능. +- **작업 로그**: 출력 루트 하위 `_PhotoAI_logs/run-<타임스탬프>.log` (사용자가 결과와 함께 확인). +- **모델**: 앱 번들 내 `models/` (오프라인 동작, 클라우드 미사용). + +--- + +## 6. IPC 채널 명세 + +| 채널 | 방향 | 페이로드 | 설명 | +|------|------|---------|------| +| `profiles:list` | UI→Main(invoke) | - | 프로필 목록 | +| `profiles:upsert` | UI→Main | `{id?, name, order}` | 등록/수정 | +| `profiles:addReference` | UI→Main | `{id, imagePaths[]}` | 참조이미지+descriptor | +| `profiles:remove` | UI→Main | `{id}` | 삭제 | +| `dialog:pickSource` / `dialog:pickOutput` | UI→Main | - | 폴더 선택 | +| `job:run` | UI→Main | `{source, outputRoot, options}` | 잡 시작 | +| `job:cancel` | UI→Main | - | 취소 | +| `job:progress` | Main→UI(send) | `{done, total, current}` | 진행률 | +| `job:fileProcessed` | Main→UI | `{file, decision, target}` | 파일 결과 | +| `job:done` | Main→UI | `Report` | 완료 | +| `job:error` | Main→UI | `{file, message}` | 파일 단위 오류 | +| `infer:detect` | Main→Inference(invoke) | `{imagePath}` | descriptor/매칭 | +| `infer:ready` | Inference→Main | - | 모델 로드 완료 | + +--- + +## 7. 얼굴 인식 상세 (Accuracy ≥ 98% 전략) + +- **모델 조합**: `SsdMobilenetv1`(검출, 정확도 우선) + `faceLandmark68Net` + `faceRecognitionNet`(128-d descriptor). + - 속도 우선 옵션으로 `TinyFaceDetector` 토글 제공. +- **매칭**: `faceapi.FaceMatcher`, Euclidean distance 임계값 **0.5**(노출형 파라미터). 낮출수록 엄격(오탐↓/미탐↑). +- **정확도 향상**: 인물당 참조이미지 다수 등록 → 라벨별 다중 descriptor 또는 평균값 사용. +- **메모리 관리**: 이미지 장변 다운스케일, 처리 후 `canvas`/`ObjectURL`/텐서 즉시 해제, 동시성 상한으로 피크 메모리 제어. 모델은 1회 로드·앱 생애 유지. + +--- + +## 8. 비기능 요구 매핑 (PRD §5 대응) + +| 요구 | 설계 반영 | +|------|----------| +| Atomic Operation | §4.3 copy-verify-delete, 파일 단위 try/catch, 실패 격리 | +| No Data Loss | 자동 리네임(덮어쓰기 금지), 검증 후에만 원본 삭제 | +| Asynchronous Processing | 모든 fs I/O 비동기 + 스트리밍 스캔 + 별도 추론 프로세스 → UI 프리징 0 | +| Memory Management | 다운스케일·즉시 해제·동시성 상한·모델 1회 로드 | +| Extension Auto-detection | `constants.ts`의 확장자 화이트리스트(`.jpg/.jpeg/.png/.webp`) | + +--- + +## 9. 빌드 · 실행 · 테스트 + +- **개발**: `electron-vite dev` (HMR, 3개 엔트리 동시). +- **배포**: `electron-vite build` → `electron-builder` 인스톨러. +- **테스트**: Vitest로 순수 로직(스캐너/EXIF 폴백/경로생성/충돌 리네임/이동 원자성) 검증. 얼굴인식은 고정 샘플로 통합 스모크. + +--- + +## 10. 열린 결정 — 확정됨 (Resolved) + +| # | 항목 | 확정 | +|---|------|------| +| 1 | 얼굴인식 라이브러리 | **`@vladmandic/face-api`** (원본 face-api.js 유지보수 포크, API 호환) | +| 2 | Inference 격리 방식 | **숨김 BrowserWindow** (v1) | +| 3 | UI 프레임워크 | **React + TypeScript + Vite + Tailwind** | +| 4 | 프로필 저장 위치 | **OS userData** 경로 | +| 5 | 패키징 범위 | **Windows + macOS 동시** (electron-builder: `nsis` + `dmg`) | + +> 전 항목 확정. 본 설계로 구현 착수. +``` diff --git a/docs/DECISIONS.md b/docs/DECISIONS.md new file mode 100644 index 0000000..b1b6a31 --- /dev/null +++ b/docs/DECISIONS.md @@ -0,0 +1,42 @@ +# AI Photo Organizer — 확정 결정 사항 (Decisions Log) + +> PRD([PRD.md] 별도 보관) 기반. 본 문서는 개발 착수 전 확정된 의사결정을 기록한다. +> 최종 갱신: 2026-06-01 + +## 1. 핵심 결정 (사용자 확정) + +| # | 항목 | 결정 | 근거 | +|---|------|------|------| +| 1 | 앱 형태 | **Electron 데스크톱 앱** | face-api.js를 렌더러(브라우저 환경)에서 네이티브 실행 → 빌드 안정. PRD의 실시간 진행률/파일목록 UI 요구 충족. Windows/Mac 크로스플랫폼. | +| 2 | 중복 파일명 정책 | **자동 리네임** (`photo.jpg` → `photo_1.jpg`) | No Data Loss 원칙. 데이터 유실 0. | +| 3 | EXIF 촬영날짜 누락 시 | **파일 수정일(mtime)로 대체**하여 YYYY/MM 추출 | 대부분의 사진을 연/월 구조에 편입 가능. | +| 4 | 다중 인물 사진의 Move 1순위 | **프로필 등록 순서** (1번 인물=이동, 2·3번=복사) | PRD 명세 "첫 번째 프로필 기준 이동 후 복사"와 일치. | + +## 2. 기본 가정 (Claude 기본값, 이의 없으면 채택) + +- **이동(Move) 구현 방식**: `복사 → 무결성 검증 → 원본 삭제` 순서로 수행 (Atomic 보장, 데이터 무결성 0 Error). +- **유사도 임계값**: face-api Euclidean distance `< 0.5`를 매칭으로 간주 (튜닝 가능 파라미터로 노출). +- **Reference 등록**: 인물당 다수 사진 등록 허용 → 평균 descriptor 사용으로 정확도 향상 (KPI ≥98% 대응). +- **미검출/인식 실패 처리**: `[미정]/YYYY/MM/` 으로 이동 (삭제 금지, Scenario 03). +- **대상 확장자**: `.jpg .jpeg .png .webp` 자동 감지. (`.heic`는 향후 확장 검토.) +- **프로필 최대 인원**: 3명 (PRD 명세). + +## 3. 폴더 출력 구조 + +``` +<출력루트>/ + <프로필명>/YYYY/MM/... # 인물 매칭 사진 + [미정]/YYYY/MM/... # 미검출·인식실패 사진 +``` + +## 4. KPI / 비기능 요구 + +- 분류 정확도 ≥ 98% +- 데이터 무결성 0 Error (유실·경로오류 0건) +- 모든 파일 I/O 비동기 처리 (UI 프리징 방지) +- face-api.js 모델 로드/해제 최적화 (메모리 누수 방지) + +## 5. 범위 외 (Out of Scope) + +- 클라우드(Google Photos 등) 실시간 동기화 +- (미래) 모바일/태블릿 확장 — descriptor 표준 저장 구조는 설계 시 고려 diff --git a/docs/PRD.md b/docs/PRD.md new file mode 100644 index 0000000..b5b85c6 --- /dev/null +++ b/docs/PRD.md @@ -0,0 +1,51 @@ +# [PRD] AI Photo Organizer (가칭) + +> 상태: 확정(Final) · 대상: 개발/디자인/QA +> (원문 보관 — 일부 오타는 정리, 내용은 원안 유지) + +## 1. 배경 +사용자는 스마트폰·DSLR·클라우드 등 다양한 경로로 방대한 사진을 보유한다. 날짜·인물 정보가 파편화되어 특정 인물의 추억을 모으거나 연도별 정리에 막대한 수동 작업이 필요하다. 본 프로젝트는 **얼굴 인식**과 **메타데이터 추출**을 결합해 사용자 개입을 최소화한 자동 정리 환경을 구축한다. + +## 2. 목표 +- **Local-first Automation**: 클라우드 업로드 없이 로컬 PC 내에서 보안 유지하며 자동 분류. +- **Intelligent Archiving**: 인물(Profile) + 시간(EXIF)을 결합한 폴더 구조 생성. +- **Zero-Effort Management**: 사용자는 '정리할 폴더'와 '대상 인물'만 지정. + +## 3. 핵심 사용자 시나리오 +- **S01 — 특정 인물 자동 분류**: 'seunghyun' 프로필 등록 후 폴더 지정 → 해당 얼굴 포함 사진만 찾아 `/seunghyun/YYYY/MM/`로 **이동(Move)**. +- **S02 — 다중 프로필 / 복사 로직**: 'yejin'·'seunghyun' 등록. 두 인물 모두 포함된 사진은 첫 프로필(seunghyun)로 **이동**, 두 번째(yejin)로 **복사(Copy)**. 원칙: 첫 번째 프로필 기준 이동 후 나머지는 복사. +- **S03 — 미검출 예외 처리**: 등록 인물이 없거나 인식 실패 사진은 삭제하지 않고 `[미정]/YYYY/MM/`로 이동. + +## 4. 주요 기능 +| 구분 | 기능 | 설명 | +|------|------|------| +| 인물 관리 | 프로필 등록/수정 | 최대 3명 이름 + 얼굴 참조사진 등록 | +| AI 엔진 | Face Recognition | face-api.js로 사진 인물 ↔ 프로필 유사도 측정 | +| 파일 관리 | Metadata Extraction | EXIF로 촬영 년/월 추출 | +| 자동 정리 | Path Auto-Generation | `/프로필/YYYY/MM/` 또는 `[미정]/YYYY/MM/` 생성 및 이동/복사 | +| UI | 작업 현황 모니터링 | 실시간 진행률 + 처리 파일 목록 | +| 리포팅 | 결과 리포트 | 총 처리 수, 성공/실패, 소요시간 로그 | + +## 5. 비기능 요구사항 +**5.1 데이터 안전성·무결성** +- Atomic Operation: 이동 중 오류 시 원본 무손상 예외 처리. +- No Data Loss: 동일 파일명 존재 시 덮어쓰기 전 백업/스킵 정책 정의. + +**5.2 성능·확장성** +- Asynchronous Processing: 대량 스캔 시 UI 프리징 방지 위해 모든 파일 I/O 비동기. +- Memory Management: 고해상도 분석 시 누수 방지 위해 모델 로드/해제 최적화. + +**5.3 확장성** +- Extension Auto-detection: `.jpg/.png/.webp` 등 주요 확장자 자동 감지. + +## 6. KPI +- 분류 정확도 ≥ 98% +- 데이터 무결성 0 Error +- 작업 처리 효율성: 전체 스캔~완료 시간 측정 + +## 7. 미래/비목표 +- **비목표**: 클라우드(Google Photos 등) 실시간 동기화는 범위 외. +- **미래확장**: 모바일/태블릿 확장 대비 descriptor 표준 저장 구조 설계. + +--- +> 개발 단계 확정 결정은 [DECISIONS.md](./DECISIONS.md), 설계는 [ARCHITECTURE.md](./ARCHITECTURE.md) 참조. diff --git a/electron-builder.yml b/electron-builder.yml new file mode 100644 index 0000000..d8e2a02 --- /dev/null +++ b/electron-builder.yml @@ -0,0 +1,30 @@ +appId: com.photoai.organizer +productName: AI Photo Organizer +directories: + output: release/${version} + buildResources: build +files: + - out/**/* + - package.json +# face-api 모델 가중치를 앱 리소스로 동봉 (오프라인 동작) +extraResources: + - from: models + to: models + filter: + - "**/*" +asarUnpack: + - "**/*.node" +win: + target: + - nsis + artifactName: ${productName}-${version}-win-${arch}.${ext} +nsis: + oneClick: false + allowToChangeInstallationDirectory: true +mac: + target: + - dmg + category: public.app-category.photography + artifactName: ${productName}-${version}-mac-${arch}.${ext} +dmg: + artifactName: ${productName}-${version}-mac-${arch}.${ext} diff --git a/electron.vite.config.ts b/electron.vite.config.ts new file mode 100644 index 0000000..5c019d2 --- /dev/null +++ b/electron.vite.config.ts @@ -0,0 +1,47 @@ +import { resolve } from 'node:path' +import { defineConfig, externalizeDepsPlugin } from 'electron-vite' +import react from '@vitejs/plugin-react' + +export default defineConfig({ + main: { + plugins: [externalizeDepsPlugin()], + resolve: { + alias: { '@shared': resolve('src/shared') } + }, + build: { + rollupOptions: { + input: { index: resolve('src/main/index.ts') } + } + } + }, + preload: { + plugins: [externalizeDepsPlugin()], + build: { + rollupOptions: { + input: { + index: resolve('src/preload/index.ts'), + inference: resolve('src/preload/inference.ts') + } + } + } + }, + renderer: { + root: '.', + resolve: { + alias: { + '@shared': resolve('src/shared'), + '@renderer': resolve('src/renderer') + } + }, + plugins: [react()], + build: { + rollupOptions: { + input: { + // UI 창 + 숨김 추론 창, 두 개의 HTML 엔트리 + main_window: resolve('src/renderer/index.html'), + inference_window: resolve('src/inference/index.html') + } + } + } + } +}) diff --git a/models/README.md b/models/README.md new file mode 100644 index 0000000..a704981 --- /dev/null +++ b/models/README.md @@ -0,0 +1,15 @@ +# 모델 가중치 폴더 + +이 폴더에는 face-api 모델 가중치가 들어갑니다 (용량이 커서 git에는 포함하지 않음). + +아래 명령으로 내려받으세요: + +```bash +npm run models:download +``` + +필요 파일: +- `ssd_mobilenetv1_model-*` (정확도 우선 검출) +- `tiny_face_detector_model-*` (속도 우선 검출) +- `face_landmark_68_model-*` (랜드마크) +- `face_recognition_model-*` (128-d descriptor) diff --git a/package-lock.json b/package-lock.json new file mode 100644 index 0000000..938ff02 --- /dev/null +++ b/package-lock.json @@ -0,0 +1,8609 @@ +{ + "name": "ai-photo-organizer", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "ai-photo-organizer", + 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EXIF based auto archiving", + "author": "PhotoAI", + "license": "MIT", + "main": "./out/main/index.js", + "scripts": { + "dev": "electron-vite dev", + "build": "electron-vite build", + "start": "electron-vite preview", + "typecheck:node": "tsc --noEmit -p tsconfig.node.json", + "typecheck:web": "tsc --noEmit -p tsconfig.web.json", + "typecheck": "npm run typecheck:node && npm run typecheck:web", + "test": "vitest run", + "test:watch": "vitest", + "models:download": "node scripts/download-models.mjs", + "pack": "electron-vite build && electron-builder --dir", + "dist": "electron-vite build && electron-builder", + "dist:win": "electron-vite build && electron-builder --win", + "dist:mac": "electron-vite build && electron-builder --mac", + "dist:all": "electron-vite build && electron-builder --win --mac" + }, + "dependencies": { + "@vladmandic/face-api": "^1.7.13", + "exifr": "^7.1.3", + "zustand": "^4.5.5" + }, + "devDependencies": { + "@types/node": "^20.16.0", + "@types/react": "^18.3.5", + "@types/react-dom": "^18.3.0", + "@vitejs/plugin-react": "^4.3.1", + "autoprefixer": "^10.4.20", + "electron": "^33.0.0", + "electron-builder": "^25.1.8", + "electron-vite": "^2.3.0", + "postcss": "^8.4.47", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "tailwindcss": "^3.4.13", + "typescript": "^5.5.4", + "vite": "^5.4.8", + "vitest": "^2.1.1" + } +} diff --git a/postcss.config.mjs b/postcss.config.mjs new file mode 100644 index 0000000..2b75bd8 --- /dev/null +++ b/postcss.config.mjs @@ -0,0 +1,6 @@ +export default { + plugins: { + tailwindcss: {}, + autoprefixer: {} + } +} diff --git a/scripts/download-models.mjs b/scripts/download-models.mjs new file mode 100644 index 0000000..736e709 --- /dev/null +++ b/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) +}) diff --git a/src/inference/faceEngine.ts b/src/inference/faceEngine.ts new file mode 100644 index 0000000..9d2619e --- /dev/null +++ b/src/inference/faceEngine.ts @@ -0,0 +1,106 @@ +import * as faceapi from '@vladmandic/face-api' +import type { Profile, JobOptions, MatchResult, ProfileMatch } from '@shared/types' +import { loadImageToCanvas, releaseCanvas } from './imageLoader' + +/** + * face-api 기반 얼굴 인식 엔진 (숨김 추론 창에서만 동작). + * - 모델 1회 로드 후 앱 생애 유지 + * - 프로필 descriptor로 FaceMatcher 구성 + * - 이미지당 얼굴 검출 + 매칭 + */ +class FaceEngine { + private modelsLoaded = false + private detector: JobOptions['detector'] = 'ssd' + private matcher: faceapi.FaceMatcher | null = null + /** label(=profileId) → {name, order} */ + private labelMeta = new Map() + + async loadModels(baseUrl: string): Promise { + if (this.modelsLoaded) return + // face-api는 브라우저(렌더러) 환경에서 첫 추론 시 WebGL 백엔드를 자동 초기화한다. + // 별도의 setBackend 호출 없이 모델만 로드하면 된다. + await Promise.all([ + faceapi.nets.ssdMobilenetv1.loadFromUri(baseUrl), + faceapi.nets.tinyFaceDetector.loadFromUri(baseUrl), + faceapi.nets.faceLandmark68Net.loadFromUri(baseUrl), + faceapi.nets.faceRecognitionNet.loadFromUri(baseUrl) + ]) + this.modelsLoaded = true + } + + /** 잡 시작 전 호출: 매처 + 옵션 구성 */ + configure(profiles: Profile[], options: JobOptions): void { + this.detector = options.detector + this.labelMeta.clear() + + const labeled: faceapi.LabeledFaceDescriptors[] = [] + for (const p of profiles) { + if (!p.descriptors || p.descriptors.length === 0) continue + this.labelMeta.set(p.id, { name: p.name, order: p.order }) + const descs = p.descriptors.map((d) => new Float32Array(d)) + labeled.push(new faceapi.LabeledFaceDescriptors(p.id, descs)) + } + + this.matcher = labeled.length + ? new faceapi.FaceMatcher(labeled, options.matchThreshold) + : null + } + + private detectorOptions(): faceapi.SsdMobilenetv1Options | faceapi.TinyFaceDetectorOptions { + return this.detector === 'tiny' + ? new faceapi.TinyFaceDetectorOptions({ inputSize: 512, scoreThreshold: 0.5 }) + : new faceapi.SsdMobilenetv1Options({ minConfidence: 0.5 }) + } + + /** 참조 이미지 1장 → 대표 descriptor (가장 큰 얼굴 1개) */ + async describeImage(imagePath: string): Promise { + const canvas = await loadImageToCanvas(imagePath) + try { + const det = await faceapi + .detectSingleFace(canvas, this.detectorOptions()) + .withFaceLandmarks() + .withFaceDescriptor() + return det ? Array.from(det.descriptor) : null + } finally { + releaseCanvas(canvas) + } + } + + /** 사진 1장 → 얼굴 검출 + 프로필 매칭 결과 */ + async detectImage(imagePath: string): Promise { + const canvas = await loadImageToCanvas(imagePath) + try { + const results = await faceapi + .detectAllFaces(canvas, this.detectorOptions()) + .withFaceLandmarks() + .withFaceDescriptors() + + const faceCount = results.length + if (faceCount === 0 || !this.matcher) { + return { faceFound: faceCount > 0, matched: [], faceCount } + } + + // 프로필별 최소 거리(최적 매칭) 집계 + const best = new Map() + for (const r of results) { + const m = this.matcher.findBestMatch(r.descriptor) + if (m.label === 'unknown') continue + const prev = best.get(m.label) + if (prev === undefined || m.distance < prev) best.set(m.label, m.distance) + } + + const matched: ProfileMatch[] = [] + for (const [profileId, distance] of best) { + const meta = this.labelMeta.get(profileId) + if (!meta) continue + matched.push({ profileId, name: meta.name, order: meta.order, distance }) + } + + return { faceFound: true, matched, faceCount } + } finally { + releaseCanvas(canvas) + } + } +} + +export const faceEngine = new FaceEngine() diff --git a/src/inference/global.d.ts b/src/inference/global.d.ts new file mode 100644 index 0000000..4b48cb2 --- /dev/null +++ b/src/inference/global.d.ts @@ -0,0 +1,9 @@ +import type { InferBridge } from '../preload/inference' + +declare global { + interface Window { + inferBridge: InferBridge + } +} + +export {} diff --git a/src/inference/imageLoader.ts b/src/inference/imageLoader.ts new file mode 100644 index 0000000..f93673e --- /dev/null +++ b/src/inference/imageLoader.ts @@ -0,0 +1,43 @@ +import { pathToFileUrl } from './pathToFileUrl' +import { MAX_IMAGE_DIMENSION } from '@shared/constants' + +/** + * 파일 경로의 이미지를 HTMLCanvasElement로 디코딩한다. + * 장변이 MAX_IMAGE_DIMENSION을 넘으면 비율 유지하며 다운스케일 → 메모리/속도 최적화. + * webSecurity:false 환경이므로 file:// URL을 직접 로드할 수 있다. + */ +export async function loadImageToCanvas(imagePath: string): Promise { + const img = await loadImageElement(pathToFileUrl(imagePath)) + + const { width, height } = img + const longSide = Math.max(width, height) + const scale = longSide > MAX_IMAGE_DIMENSION ? MAX_IMAGE_DIMENSION / longSide : 1 + const w = Math.max(1, Math.round(width * scale)) + const h = Math.max(1, Math.round(height * scale)) + + const canvas = document.createElement('canvas') + canvas.width = w + canvas.height = h + const ctx = canvas.getContext('2d') + if (!ctx) throw new Error('2D 컨텍스트 생성 실패') + ctx.drawImage(img, 0, 0, w, h) + + // 원본 img 참조 해제 (디코딩 버퍼 회수 유도) + img.src = '' + return canvas +} + +function loadImageElement(url: string): Promise { + return new Promise((resolve, reject) => { + const img = new Image() + img.onload = () => resolve(img) + img.onerror = () => reject(new Error(`이미지 로드 실패: ${url}`)) + img.src = url + }) +} + +/** 처리 후 캔버스 크기를 0으로 줄여 메모리 회수를 유도 */ +export function releaseCanvas(canvas: HTMLCanvasElement): void { + canvas.width = 0 + canvas.height = 0 +} diff --git a/src/inference/index.html b/src/inference/index.html new file mode 100644 index 0000000..e431a94 --- /dev/null +++ b/src/inference/index.html @@ -0,0 +1,11 @@ + + + + + PhotoAI Inference Worker + + + + + + diff --git a/src/inference/main.ts b/src/inference/main.ts new file mode 100644 index 0000000..a9d5672 --- /dev/null +++ b/src/inference/main.ts @@ -0,0 +1,52 @@ +import { faceEngine } from './faceEngine' +import type { Profile, JobOptions, DescriptorResult } from '@shared/types' + +/** + * 숨김 추론 창 부트스트랩. + * 1) URL 쿼리에서 모델 경로 읽어 모델 로드 → ready 통지 + * 2) Main의 요청(infer:init/describe/detect) 처리 후 reply + */ +async function bootstrap(): Promise { + const params = new URLSearchParams(location.search) + const modelsUrl = params.get('models') + if (!modelsUrl) throw new Error('models 경로 쿼리가 없습니다.') + + console.log('models loading from:', decodeURIComponent(modelsUrl)) + await faceEngine.loadModels(decodeURIComponent(modelsUrl)) + console.log('models loaded OK') + window.inferBridge.ready() + + window.inferBridge.onRequest(async (channel, payload) => { + const { requestId } = payload + try { + if (channel === 'infer:init') { + const { profiles, options } = payload as unknown as { + profiles: Profile[] + options: JobOptions + } + faceEngine.configure(profiles, options) + window.inferBridge.reply(requestId, true, { ok: true }) + } else if (channel === 'infer:describe') { + const { imagePaths } = payload as unknown as { imagePaths: string[] } + const out: DescriptorResult[] = [] + for (const imagePath of imagePaths) { + const descriptor = await faceEngine.describeImage(imagePath) + out.push({ imagePath, descriptor }) + } + window.inferBridge.reply(requestId, true, out) + } else if (channel === 'infer:detect') { + const { imagePath } = payload as unknown as { imagePath: string } + const result = await faceEngine.detectImage(imagePath) + window.inferBridge.reply(requestId, true, result) + } + } catch (err) { + window.inferBridge.reply(requestId, false, undefined, (err as Error).message) + } + }) +} + +bootstrap().catch((err) => { + // 부트스트랩 실패 시 콘솔에 남김 — Main은 whenReady에서 영구 대기하므로 + // 개발 중 콘솔로 원인 확인 + console.error('[inference] 부트스트랩 실패:', err) +}) diff --git a/src/inference/pathToFileUrl.ts b/src/inference/pathToFileUrl.ts new file mode 100644 index 0000000..6700fba --- /dev/null +++ b/src/inference/pathToFileUrl.ts @@ -0,0 +1,17 @@ +/** + * 렌더러(브라우저)에는 node:url이 없으므로 경로 → file:// URL 변환을 직접 수행. + * Windows(드라이브 문자, 백슬래시)와 POSIX 경로를 모두 처리한다. + */ +export function pathToFileUrl(p: string): string { + let normalized = p.replace(/\\/g, '/') + // Windows 드라이브 경로(C:/...)는 슬래시 3개 + 그대로 + if (/^[a-zA-Z]:\//.test(normalized)) { + normalized = '/' + normalized + } + // 각 세그먼트를 인코딩 (공백/한글/특수문자 대응), 슬래시는 보존 + const encoded = normalized + .split('/') + .map((seg) => encodeURIComponent(seg)) + .join('/') + return 'file://' + encoded +} diff --git a/src/main/concurrency.ts b/src/main/concurrency.ts new file mode 100644 index 0000000..3738b3f --- /dev/null +++ b/src/main/concurrency.ts @@ -0,0 +1,32 @@ +/** + * 경량 동시성 제한 세마포어. 외부 p-limit 대신 직접 구현. + * limit 개수만큼만 동시에 실행되도록 작업을 게이팅한다. + */ +export function createLimiter(limit: number) { + let active = 0 + const queue: Array<() => void> = [] + + const next = () => { + if (active >= limit) return + const run = queue.shift() + if (run) { + active++ + run() + } + } + + return function schedule(task: () => Promise): Promise { + return new Promise((resolve, reject) => { + const run = () => { + task() + .then(resolve, reject) + .finally(() => { + active-- + next() + }) + } + queue.push(run) + next() + }) + } +} diff --git a/src/main/exif.ts b/src/main/exif.ts new file mode 100644 index 0000000..140c930 --- /dev/null +++ b/src/main/exif.ts @@ -0,0 +1,41 @@ +import exifr from 'exifr' +import { stat } from 'node:fs/promises' +import type { CaptureDate } from '@shared/types' + +function toYearMonth(d: Date, source: CaptureDate['source']): CaptureDate { + const year = String(d.getFullYear()) + const month = String(d.getMonth() + 1).padStart(2, '0') + return { year, month, source } +} + +/** + * 촬영 날짜 추출. + * 1) EXIF DateTimeOriginal (없으면 CreateDate/ModifyDate) 시도 + * 2) 실패 시 파일 시스템 mtime 폴백 + * + * 어떤 경우에도 throw 하지 않고 항상 유효한 CaptureDate를 반환한다. + */ +export async function getCaptureDate(path: string): Promise { + // 1) EXIF 시도 + try { + const exif = await exifr.parse(path, { + pick: ['DateTimeOriginal', 'CreateDate', 'ModifyDate'] + }) + const raw: unknown = + exif?.DateTimeOriginal ?? exif?.CreateDate ?? exif?.ModifyDate + if (raw instanceof Date && !Number.isNaN(raw.getTime())) { + return toYearMonth(raw, 'exif') + } + } catch { + // EXIF 파싱 실패 → 폴백으로 진행 + } + + // 2) mtime 폴백 + try { + const s = await stat(path) + return toYearMonth(s.mtime, 'mtime') + } catch { + // stat 마저 실패하면 현재 시각으로 최후 폴백 (파일 분류는 계속되어야 함) + return toYearMonth(new Date(), 'mtime') + } +} diff --git a/src/main/fileOps.ts b/src/main/fileOps.ts new file mode 100644 index 0000000..32bd350 --- /dev/null +++ b/src/main/fileOps.ts @@ -0,0 +1,67 @@ +import { copyFile, mkdir, unlink, stat, access } from 'node:fs/promises' +import { constants as FS } from 'node:fs' +import { dirname } from 'node:path' +import { withCollisionSuffix } from './pathBuilder' + +async function exists(p: string): Promise { + try { + await access(p, FS.F_OK) + return true + } catch { + return false + } +} + +/** + * 대상 경로에 충돌이 없는 최종 경로를 구한다. + * 이미 존재하면 name_1, name_2 ... 로 자동 리네임 (No Data Loss 정책). + */ +export async function resolveCollisionFreePath(target: string): Promise { + if (!(await exists(target))) return target + for (let i = 1; i < 100000; i++) { + const candidate = withCollisionSuffix(target, i) + if (!(await exists(candidate))) return candidate + } + throw new Error(`충돌 회피 경로 생성 실패(시도 초과): ${target}`) +} + +/** + * 안전 복사: 대상 디렉터리 생성 → copyFile → 크기 검증. + * 반환값은 실제로 기록된 (충돌 회피된) 경로. + */ +export async function safeCopy(src: string, target: string): Promise { + const dest = await resolveCollisionFreePath(target) + await mkdir(dirname(dest), { recursive: true }) + await copyFile(src, dest) + + // 무결성 검증: 원본/사본 크기 일치 + const [s, d] = await Promise.all([stat(src), stat(dest)]) + if (s.size !== d.size) { + // 검증 실패 → 깨진 사본 제거 후 오류 + await unlink(dest).catch(() => {}) + throw new Error(`복사 무결성 검증 실패(size ${s.size} != ${d.size}): ${src}`) + } + return dest +} + +/** + * 안전 이동: 복사 → 검증 → 원본 삭제 (Atomic 정책, 데이터 무결성 0 Error). + * 동일 볼륨 여부와 무관하게 copy-verify-delete 로 동작해 부분 손상 방지. + * 검증 통과 후에만 원본을 삭제하므로 어느 단계에서 실패해도 원본은 보존된다. + * + * @returns 실제로 기록된 (충돌 회피된) 대상 경로 + */ +export async function safeMove(src: string, target: string): Promise { + const dest = await safeCopy(src, target) // 복사 + 검증 완료 + try { + await unlink(src) // 검증 통과 후에만 원본 삭제 + } catch (err) { + // 사본은 정상. 원본 삭제만 실패한 경우 → 사본 유지하되 경고로 남김(데이터 유실 없음) + throw new Error( + `이동 완료(사본 생성됨) 후 원본 삭제 실패: ${src} → ${dest} :: ${(err as Error).message}` + ) + } + return dest +} + +export { exists } diff --git a/src/main/index.ts b/src/main/index.ts new file mode 100644 index 0000000..79cfacb --- /dev/null +++ b/src/main/index.ts @@ -0,0 +1,57 @@ +import { app, BrowserWindow, shell } from 'electron' +import { join } from 'node:path' +import { registerIpc } from './ipc' +import { inferenceBridge } from './inferenceBridge' +import { logger } from './logger' + +let mainWindow: BrowserWindow | null = null + +function createMainWindow(): void { + mainWindow = new BrowserWindow({ + width: 1100, + height: 760, + minWidth: 900, + minHeight: 600, + show: false, + title: 'AI Photo Organizer', + webPreferences: { + preload: join(__dirname, '../preload/index.js'), + contextIsolation: true, + nodeIntegration: false, + sandbox: false + } + }) + + mainWindow.on('ready-to-show', () => mainWindow?.show()) + + // 외부 링크는 기본 브라우저로 + mainWindow.webContents.setWindowOpenHandler(({ url }) => { + shell.openExternal(url) + return { action: 'deny' } + }) + + const devUrl = process.env['ELECTRON_RENDERER_URL'] + if (devUrl) { + mainWindow.loadURL(`${devUrl}/src/renderer/index.html`) + } else { + mainWindow.loadFile(join(__dirname, '../renderer/src/renderer/index.html')) + } +} + +app.whenReady().then(() => { + registerIpc() + // 숨김 추론 창을 먼저 띄워 모델 로드를 선행 + inferenceBridge.init() + createMainWindow() + + app.on('activate', () => { + if (BrowserWindow.getAllWindows().length === 0) createMainWindow() + }) + + logger.info('앱 시작 완료') +}) + +app.on('window-all-closed', () => { + inferenceBridge.dispose() + if (process.platform !== 'darwin') app.quit() +}) diff --git a/src/main/inferenceBridge.ts b/src/main/inferenceBridge.ts new file mode 100644 index 0000000..f16104e --- /dev/null +++ b/src/main/inferenceBridge.ts @@ -0,0 +1,129 @@ +import { BrowserWindow, ipcMain, app } from 'electron' +import { join } from 'node:path' +import { pathToFileURL } from 'node:url' +import type { MatchResult, Profile, DescriptorResult, JobOptions } from '@shared/types' +import { logger } from './logger' + +/** 모델 가중치 디렉터리의 file:// URL (dev: 프로젝트 루트, prod: resources) */ +function modelsBaseUrl(): string { + const dir = app.isPackaged + ? join(process.resourcesPath, 'models') + : join(app.getAppPath(), 'models') + // 끝에 슬래시 없이 — 렌더러에서 `${base}/파일명` 형태로 사용 + return pathToFileURL(dir).toString() +} + +interface Pending { + resolve: (v: unknown) => void + reject: (e: Error) => void +} + +/** + * 숨김 BrowserWindow(Inference Renderer)와의 RPC 브릿지. + * - Main → Renderer: webContents.send(channel, {requestId, ...}) + * - Renderer → Main: ipcRenderer.send('infer:reply', {requestId, ok, data, error}) + * requestId 상관관계로 요청/응답을 매칭한다. + */ +class InferenceBridge { + private win: BrowserWindow | null = null + private readyPromise: Promise | null = null + private readyResolve: (() => void) | null = null + private pending = new Map() + private seq = 0 + + /** 숨김 추론 창 생성 및 모델 로드 대기 준비 */ + init(): void { + if (this.win) return + + this.readyPromise = new Promise((res) => { + this.readyResolve = res + }) + + // 추론 창이 ready를 알리면 resolve + ipcMain.on('infer:ready', () => { + logger.info('Inference 창 모델 로드 완료') + this.readyResolve?.() + }) + + // 추론 창의 모든 응답 수신 + ipcMain.on('infer:reply', (_e, payload: { requestId: string; ok: boolean; data?: unknown; error?: string }) => { + const p = this.pending.get(payload.requestId) + if (!p) return + this.pending.delete(payload.requestId) + if (payload.ok) p.resolve(payload.data) + else p.reject(new Error(payload.error ?? '추론 오류')) + }) + + this.win = new BrowserWindow({ + show: false, + webPreferences: { + preload: join(__dirname, '../preload/inference.js'), + contextIsolation: true, + nodeIntegration: false, + // 숨김 창이 백그라운드에서도 연산을 멈추지 않도록 + backgroundThrottling: false, + // 내부 전용 창: 로컬 파일(모델 가중치/사진)을 file://로 fetch 하기 위해 완화. + // 원격 콘텐츠를 절대 로드하지 않으므로 위험은 격리됨. + webSecurity: false + } + }) + + // 추론창 콘솔을 Main 로그로 포워딩 (모델 로드 성공/실패 가시화) + this.win.webContents.on('console-message', (_e, level, message) => { + const tag = level >= 2 ? 'ERROR' : 'INFO' + logger.info(`[inference console:${tag}] ${message}`) + }) + + const models = encodeURIComponent(modelsBaseUrl()) + + // electron-vite: 개발 시 dev 서버, 배포 시 빌드된 html 로드. + // 모델 경로는 쿼리스트링으로 전달 → 렌더러가 즉시 모델 로드 시작. + const devUrl = process.env['ELECTRON_RENDERER_URL'] + if (devUrl) { + this.win.loadURL(`${devUrl}/src/inference/index.html?models=${models}`) + } else { + this.win.loadFile(join(__dirname, '../renderer/src/inference/index.html'), { + search: `models=${models}` + }) + } + } + + /** 모델 로드 완료까지 대기 */ + async whenReady(): Promise { + if (!this.readyPromise) throw new Error('InferenceBridge.init()가 호출되지 않음') + await this.readyPromise + } + + private call(channel: string, payload: Record): Promise { + if (!this.win) throw new Error('Inference 창이 없음') + const requestId = `req_${++this.seq}` + return new Promise((resolve, reject) => { + this.pending.set(requestId, { resolve: resolve as (v: unknown) => void, reject }) + this.win!.webContents.send(channel, { requestId, ...payload }) + }) + } + + /** 잡 시작 전: 프로필 descriptor로 FaceMatcher 구성 + 옵션 적용 */ + async initMatcher(profiles: Profile[], options: JobOptions): Promise { + await this.call('infer:init', { profiles, options }) + } + + /** 참조 이미지들의 descriptor 계산 (프로필 등록용) */ + async describe(imagePaths: string[], detector: JobOptions['detector']): Promise { + return this.call('infer:describe', { imagePaths, detector }) + } + + /** 사진 1장 얼굴 검출 + 프로필 매칭 */ + async detect(imagePath: string): Promise { + return this.call('infer:detect', { imagePath }) + } + + dispose(): void { + this.pending.forEach((p) => p.reject(new Error('브릿지 종료'))) + this.pending.clear() + this.win?.destroy() + this.win = null + } +} + +export const inferenceBridge = new InferenceBridge() diff --git a/src/main/ipc.ts b/src/main/ipc.ts new file mode 100644 index 0000000..0a5e3e1 --- /dev/null +++ b/src/main/ipc.ts @@ -0,0 +1,69 @@ +import { ipcMain, dialog, BrowserWindow } from 'electron' +import type { ProfileInput, JobRequest } from '@shared/types' +import { IPC } from '@shared/constants' +import { profileStore } from './profileStore' +import { inferenceBridge } from './inferenceBridge' +import { orchestrator } from './orchestrator' +import { logger } from './logger' + +/** UI/다이얼로그/잡 관련 IPC 핸들러 등록 */ +export function registerIpc(): void { + // ---- 프로필 ---- + ipcMain.handle(IPC.PROFILES_LIST, () => profileStore.list()) + + ipcMain.handle(IPC.PROFILES_UPSERT, (_e, input: ProfileInput) => + profileStore.upsert(input) + ) + + ipcMain.handle(IPC.PROFILES_REMOVE, (_e, id: string) => profileStore.remove(id)) + + ipcMain.handle( + IPC.PROFILES_ADD_REFERENCE, + async (_e, id: string, imagePaths: string[]) => { + await inferenceBridge.whenReady() + // 참조 이미지 descriptor 계산 (기본 정확도 우선 detector) + const results = await inferenceBridge.describe(imagePaths, 'ssd') + const valid = results.filter((r) => r.descriptor !== null) + const usedPaths = valid.map((r) => r.imagePath) + const descriptors = valid.map((r) => r.descriptor as number[]) + if (descriptors.length === 0) { + throw new Error('선택한 이미지에서 얼굴을 찾지 못했습니다.') + } + return profileStore.addReference(id, usedPaths, descriptors) + } + ) + + // ---- 다이얼로그 ---- + ipcMain.handle(IPC.DIALOG_PICK_SOURCE, async () => { + const r = await dialog.showOpenDialog({ properties: ['openDirectory'] }) + return r.canceled ? null : r.filePaths[0] + }) + + ipcMain.handle(IPC.DIALOG_PICK_OUTPUT, async () => { + const r = await dialog.showOpenDialog({ properties: ['openDirectory', 'createDirectory'] }) + return r.canceled ? null : r.filePaths[0] + }) + + ipcMain.handle(IPC.DIALOG_PICK_IMAGES, async () => { + const r = await dialog.showOpenDialog({ + properties: ['openFile', 'multiSelections'], + filters: [{ name: 'Images', extensions: ['jpg', 'jpeg', 'png', 'webp'] }] + }) + return r.canceled ? [] : r.filePaths + }) + + // ---- 잡 ---- + ipcMain.handle(IPC.JOB_RUN, async (e, req: JobRequest) => { + const win = BrowserWindow.fromWebContents(e.sender) + if (!win) throw new Error('요청 창을 찾을 수 없음') + // 비동기로 실행하되 완료는 이벤트(JOB_DONE)로 통지 → 호출 즉시 반환 + orchestrator.run(req, win).catch((err) => { + logger.error('잡 실행 실패', { message: (err as Error).message }) + if (!win.isDestroyed()) { + win.webContents.send(IPC.JOB_ERROR, { file: '', message: (err as Error).message }) + } + }) + }) + + ipcMain.handle(IPC.JOB_CANCEL, () => orchestrator.cancel()) +} diff --git a/src/main/logger.ts b/src/main/logger.ts new file mode 100644 index 0000000..8e83d93 --- /dev/null +++ b/src/main/logger.ts @@ -0,0 +1,64 @@ +import { appendFile, mkdir } from 'node:fs/promises' +import { dirname } from 'node:path' + +type Level = 'INFO' | 'WARN' | 'ERROR' + +/** + * 구조적 로거. 콘솔 + (옵션) 파일에 기록. + * 잡 실행 시 setLogFile()로 출력 루트 하위 로그 파일 경로를 지정한다. + */ +class Logger { + private logFile: string | null = null + private buffer: string[] = [] + + async setLogFile(path: string): Promise { + this.logFile = path + await mkdir(dirname(path), { recursive: true }) + } + + private async write(level: Level, msg: string, meta?: unknown): Promise { + // new Date() 사용 (Main 프로세스는 일반 Node — 제약 없음) + const ts = new Date().toISOString() + const metaStr = meta === undefined ? '' : ` ${safeJson(meta)}` + const line = `[${ts}] [${level}] ${msg}${metaStr}` + + if (level === 'ERROR') console.error(line) + else if (level === 'WARN') console.warn(line) + else console.log(line) + + this.buffer.push(line) + if (this.logFile) { + try { + await appendFile(this.logFile, line + '\n', 'utf-8') + } catch { + // 로그 파일 기록 실패는 치명적이지 않음 — 콘솔 출력은 이미 됨 + } + } + } + + info(msg: string, meta?: unknown) { + return this.write('INFO', msg, meta) + } + warn(msg: string, meta?: unknown) { + return this.write('WARN', msg, meta) + } + error(msg: string, meta?: unknown) { + return this.write('ERROR', msg, meta) + } + + /** 잡 종료 시 버퍼 비우기 */ + reset(): void { + this.buffer = [] + this.logFile = null + } +} + +function safeJson(v: unknown): string { + try { + return JSON.stringify(v) + } catch { + return String(v) + } +} + +export const logger = new Logger() diff --git a/src/main/orchestrator.ts b/src/main/orchestrator.ts new file mode 100644 index 0000000..069e92a --- /dev/null +++ b/src/main/orchestrator.ts @@ -0,0 +1,167 @@ +import { BrowserWindow } from 'electron' +import type { + JobRequest, + FileProcessed, + ProgressEvent, + Report, + ProfileMatch +} from '@shared/types' +import { IPC } from '@shared/constants' +import { scan, countImages, defaultSkipDirs } from './scanner' +import { getCaptureDate } from './exif' +import { buildTargetPath } from './pathBuilder' +import { safeMove, safeCopy } from './fileOps' +import { profileStore } from './profileStore' +import { inferenceBridge } from './inferenceBridge' +import { Reporter } from './reporter' +import { createLimiter } from './concurrency' +import { logger } from './logger' + +/** + * 정리 잡 파이프라인 오케스트레이터. + * 스캔 → (얼굴인식 + EXIF) → 경로생성 → 이동/복사 → 진행률/리포트. + */ +class Orchestrator { + private cancelled = false + private running = false + + cancel(): void { + if (this.running) { + this.cancelled = true + logger.warn('잡 취소 요청됨') + } + } + + async run(req: JobRequest, sender: BrowserWindow): Promise { + if (this.running) throw new Error('이미 실행 중인 잡이 있습니다.') + this.running = true + this.cancelled = false + + const send = (channel: string, payload: T) => { + if (!sender.isDestroyed()) sender.webContents.send(channel, payload) + } + + const reporter = new Reporter() + const startTs = Date.now() + const logPath = Reporter.logPathFor(req.outputRoot, startTs) + await logger.setLogFile(logPath) + await logger.info('잡 시작', req) + + try { + const profiles = await profileStore.list() // order asc 정렬됨 + // 추론 엔진 준비 + 매처 구성 + await inferenceBridge.whenReady() + await inferenceBridge.initMatcher(profiles, req.options) + + // 출력물 재처리 방지 위해 우리가 만든 폴더는 스캔 제외 + const skip = defaultSkipDirs(profiles.map((p) => p.name)) + + // 진행률 total 산출 + const total = await countImages(req.source, skip) + logger.info('스캔 대상 이미지 수', { total }) + + let done = 0 + const limit = createLimiter(Math.max(1, req.options.concurrency)) + const tasks: Promise[] = [] + + for await (const file of scan(req.source, skip)) { + if (this.cancelled) break + + const task = limit(async () => { + if (this.cancelled) return + const progress: ProgressEvent = { done, total, current: file } + send(IPC.JOB_PROGRESS, progress) + + const result = await this.processFile(req, file, profiles) + reporter.record(result) + done++ + send(IPC.JOB_FILE_PROCESSED, result) + send(IPC.JOB_PROGRESS, { done, total, current: file }) + if (result.kind === 'failed' && result.error) { + send(IPC.JOB_ERROR, { file, message: result.error }) + } + }) + tasks.push(task) + } + + await Promise.all(tasks) + + const report = await reporter.summarize(logPath) + send(IPC.JOB_DONE, report) + return report + } finally { + this.running = false + logger.reset() + } + } + + /** 파일 1건 처리: 인식 → 날짜 → 이동/복사 */ + private async processFile( + req: JobRequest, + file: string, + profilesOrdered: { id: string; name: string; order: number }[] + ): Promise { + void profilesOrdered + try { + // 얼굴 인식 + 날짜 추출 병렬 + const [match, date] = await Promise.all([ + inferenceBridge.detect(file), + getCaptureDate(file) + ]) + + // 매칭 인물 없음 → [미정] + if (!match.matched || match.matched.length === 0) { + const dest = await safeMove(file, buildTargetPath(req.outputRoot, null, date, file)) + return { + file, + kind: 'unmatched', + targets: [dest], + matchedNames: [], + date + } + } + + // 등록 순서(order asc) 정렬 → 1순위 이동, 나머지 복사 + const ordered: ProfileMatch[] = [...match.matched].sort((a, b) => a.order - b.order) + const targets: string[] = [] + + // 1순위: 이동 + const first = ordered[0] + const movedDest = await safeMove( + file, + buildTargetPath(req.outputRoot, first.name, date, file) + ) + targets.push(movedDest) + + // 나머지: 이동된 파일을 소스로 복사 + for (let i = 1; i < ordered.length; i++) { + const copyDest = await safeCopy( + movedDest, + buildTargetPath(req.outputRoot, ordered[i].name, date, file) + ) + targets.push(copyDest) + } + + return { + file, + kind: 'moved', + targets, + matchedNames: ordered.map((m) => m.name), + date + } + } catch (err) { + const message = (err as Error).message + await logger.error('파일 처리 실패', { file, message }) + return { + file, + kind: 'failed', + targets: [], + matchedNames: [], + date: null, + error: message + } + } + } +} + +export const orchestrator = new Orchestrator() diff --git a/src/main/pathBuilder.ts b/src/main/pathBuilder.ts new file mode 100644 index 0000000..8ff23b5 --- /dev/null +++ b/src/main/pathBuilder.ts @@ -0,0 +1,31 @@ +import { join, extname, basename } from 'node:path' +import type { CaptureDate } from '@shared/types' +import { UNMATCHED_FOLDER } from '@shared/constants' + +/** + * 인물/미정 + 연/월 기준의 대상 디렉터리 경로를 생성한다. + * 실제 파일명 충돌 해소는 fileOps에서 수행 (여기서는 디렉터리 + 원본 파일명까지). + * + * @param who 인물 폴더명, 또는 미검출이면 null → [미정] + */ +export function buildTargetPath( + outputRoot: string, + who: string | null, + date: CaptureDate, + sourceFile: string +): string { + const folder = who ?? UNMATCHED_FOLDER + const filename = basename(sourceFile) + return join(outputRoot, folder, date.year, date.month, filename) +} + +/** + * 파일명 충돌 시 사용할 후보 경로를 생성 (name_1.ext, name_2.ext ...). + * @param index 1부터 시작하는 충돌 회피 인덱스 + */ +export function withCollisionSuffix(targetPath: string, index: number): string { + const dir = targetPath.slice(0, targetPath.length - basename(targetPath).length) + const ext = extname(targetPath) + const stem = basename(targetPath, ext) + return join(dir, `${stem}_${index}${ext}`) +} diff --git a/src/main/profileStore.ts b/src/main/profileStore.ts new file mode 100644 index 0000000..a942cfe --- /dev/null +++ b/src/main/profileStore.ts @@ -0,0 +1,102 @@ +import { app } from 'electron' +import { readFile, writeFile, mkdir } from 'node:fs/promises' +import { join } from 'node:path' +import type { Profile, ProfileInput } from '@shared/types' +import { PROFILE_STORE_FILE, MAX_PROFILES } from '@shared/constants' +import { logger } from './logger' + +/** + * 프로필 영속화. OS userData 경로의 profiles.json 에 저장. + * descriptor(Float32Array)는 number[][] 직렬화 형태로 보관 → 모바일 확장 시 표준 구조 호환. + */ +class ProfileStore { + private profiles: Profile[] = [] + private loaded = false + + private filePath(): string { + return join(app.getPath('userData'), PROFILE_STORE_FILE) + } + + async load(): Promise { + if (this.loaded) return this.profiles + try { + const raw = await readFile(this.filePath(), 'utf-8') + const parsed = JSON.parse(raw) as { profiles?: Profile[] } + this.profiles = Array.isArray(parsed.profiles) ? parsed.profiles : [] + } catch { + this.profiles = [] // 최초 실행 등 → 빈 목록 + } + this.loaded = true + return this.profiles + } + + async list(): Promise { + await this.load() + return [...this.profiles].sort((a, b) => a.order - b.order) + } + + private async persist(): Promise { + await mkdir(app.getPath('userData'), { recursive: true }) + await writeFile( + this.filePath(), + JSON.stringify({ profiles: this.profiles }, null, 2), + 'utf-8' + ) + } + + /** 생성/수정. id 없으면 신규(최대 인원 검사). */ + async upsert(input: ProfileInput): Promise { + await this.load() + if (input.id) { + const existing = this.profiles.find((p) => p.id === input.id) + if (!existing) throw new Error(`프로필을 찾을 수 없음: ${input.id}`) + existing.name = input.name + existing.order = input.order + await this.persist() + return existing + } + if (this.profiles.length >= MAX_PROFILES) { + throw new Error(`프로필은 최대 ${MAX_PROFILES}명까지 등록 가능합니다.`) + } + const profile: Profile = { + id: cryptoRandomId(), + name: input.name, + order: input.order, + referenceImages: [], + descriptors: [] + } + this.profiles.push(profile) + await this.persist() + logger.info('프로필 생성', { id: profile.id, name: profile.name }) + return profile + } + + async remove(id: string): Promise { + await this.load() + this.profiles = this.profiles.filter((p) => p.id !== id) + await this.persist() + } + + /** 참조 이미지 + 계산된 descriptor 추가 */ + async addReference( + id: string, + imagePaths: string[], + descriptors: number[][] + ): Promise { + await this.load() + const p = this.profiles.find((x) => x.id === id) + if (!p) throw new Error(`프로필을 찾을 수 없음: ${id}`) + p.referenceImages.push(...imagePaths) + p.descriptors.push(...descriptors) + await this.persist() + logger.info('참조 이미지 추가', { id, added: descriptors.length }) + return p + } +} + +function cryptoRandomId(): string { + // Electron Main(Node)에서 무작위 ID — globalThis.crypto.randomUUID 사용 + return globalThis.crypto.randomUUID() +} + +export const profileStore = new ProfileStore() diff --git a/src/main/reporter.ts b/src/main/reporter.ts new file mode 100644 index 0000000..64cfdae --- /dev/null +++ b/src/main/reporter.ts @@ -0,0 +1,63 @@ +import { join } from 'node:path' +import type { FileProcessed, Report } from '@shared/types' +import { LOG_FOLDER } from '@shared/constants' +import { logger } from './logger' + +/** + * 잡 통계 집계 + 결과 로그 파일 생성. + */ +export class Reporter { + private moved = 0 + private copied = 0 + private unmatched = 0 + private failed = 0 + private total = 0 + private readonly startedAt: number + + constructor() { + this.startedAt = Date.now() + } + + record(result: FileProcessed): void { + this.total++ + switch (result.kind) { + case 'moved': + this.moved++ + // 복사 대상은 targets에서 첫(이동) 제외한 나머지 + this.copied += Math.max(0, result.targets.length - 1) + break + case 'unmatched': + this.unmatched++ + break + case 'failed': + this.failed++ + break + case 'copied': + this.copied++ + break + } + } + + /** 로그 파일 경로 (출력 루트 하위 _PhotoAI_logs/run-.log) */ + static logPathFor(outputRoot: string, ts: number): string { + const stamp = new Date(ts).toISOString().replace(/[:.]/g, '-') + return join(outputRoot, LOG_FOLDER, `run-${stamp}.log`) + } + + async summarize(logPath: string): Promise { + const finishedAt = Date.now() + const report: Report = { + total: this.total, + moved: this.moved, + copied: this.copied, + unmatched: this.unmatched, + failed: this.failed, + elapsedMs: finishedAt - this.startedAt, + logPath, + startedAt: this.startedAt, + finishedAt + } + await logger.info('==== 작업 결과 리포트 ====', report) + return report + } +} diff --git a/src/main/scanner.ts b/src/main/scanner.ts new file mode 100644 index 0000000..173f4f6 --- /dev/null +++ b/src/main/scanner.ts @@ -0,0 +1,60 @@ +import { readdir } from 'node:fs/promises' +import { extname, join } from 'node:path' +import { SUPPORTED_EXTENSIONS, LOG_FOLDER, UNMATCHED_FOLDER } from '@shared/constants' + +const EXT_SET = new Set(SUPPORTED_EXTENSIONS) + +function isSupportedImage(filename: string): boolean { + return EXT_SET.has(extname(filename).toLowerCase()) +} + +/** + * 소스 폴더를 재귀 순회하며 지원 확장자 이미지의 절대 경로를 스트리밍 산출. + * 비동기 제너레이터 → 대량 폴더에서도 메모리에 전체 목록을 적재하지 않음. + * + * @param skipDirs 순회에서 제외할 디렉터리명 (출력 루트가 소스 내부일 때 자기 출력물 재처리 방지) + */ +export async function* scan( + root: string, + skipDirs: ReadonlySet = new Set() +): AsyncGenerator { + let entries + try { + entries = await readdir(root, { withFileTypes: true }) + } catch { + // 읽을 수 없는 디렉터리는 건너뜀 + return + } + + for (const entry of entries) { + const full = join(root, entry.name) + if (entry.isDirectory()) { + // 우리 자신이 만든 폴더(프로필/[미정]/로그)는 재귀 제외 + if (skipDirs.has(entry.name)) continue + yield* scan(full, skipDirs) + } else if (entry.isFile() && isSupportedImage(entry.name)) { + yield full + } + } +} + +/** + * 전체 개수를 먼저 세는 헬퍼 (진행률 total 표시용). + * 스캔을 한 번 더 도는 비용이 있으나, 정확한 진행률을 위해 사용. + */ +export async function countImages( + root: string, + skipDirs: ReadonlySet = new Set() +): Promise { + let count = 0 + for await (const _ of scan(root, skipDirs)) { + void _ + count++ + } + return count +} + +/** 출력물 재처리 방지를 위한 기본 제외 디렉터리 집합 */ +export function defaultSkipDirs(profileNames: string[]): Set { + return new Set([LOG_FOLDER, UNMATCHED_FOLDER, ...profileNames]) +} diff --git a/src/preload/index.ts b/src/preload/index.ts new file mode 100644 index 0000000..7ae2386 --- /dev/null +++ b/src/preload/index.ts @@ -0,0 +1,44 @@ +import { contextBridge, ipcRenderer } from 'electron' +import { IPC } from '../shared/constants' +import type { + ExposedApi, + ProfileInput, + JobRequest, + RendererEventName, + RendererEvents +} from '../shared/types' + +// Main→UI 이벤트 채널 화이트리스트 +const EVENT_CHANNELS: Record = { + 'job:progress': IPC.JOB_PROGRESS, + 'job:fileProcessed': IPC.JOB_FILE_PROCESSED, + 'job:done': IPC.JOB_DONE, + 'job:error': IPC.JOB_ERROR +} + +const api: ExposedApi = { + profiles: { + list: () => ipcRenderer.invoke(IPC.PROFILES_LIST), + upsert: (input: ProfileInput) => ipcRenderer.invoke(IPC.PROFILES_UPSERT, input), + remove: (id: string) => ipcRenderer.invoke(IPC.PROFILES_REMOVE, id), + addReference: (id: string, imagePaths: string[]) => + ipcRenderer.invoke(IPC.PROFILES_ADD_REFERENCE, id, imagePaths) + }, + dialog: { + pickSource: () => ipcRenderer.invoke(IPC.DIALOG_PICK_SOURCE), + pickOutput: () => ipcRenderer.invoke(IPC.DIALOG_PICK_OUTPUT), + pickImages: () => ipcRenderer.invoke(IPC.DIALOG_PICK_IMAGES) + }, + job: { + run: (req: JobRequest) => ipcRenderer.invoke(IPC.JOB_RUN, req), + cancel: () => ipcRenderer.invoke(IPC.JOB_CANCEL) + }, + on(event: E, cb: (payload: RendererEvents[E]) => void) { + const channel = EVENT_CHANNELS[event] + const listener = (_e: unknown, payload: RendererEvents[E]) => cb(payload) + ipcRenderer.on(channel, listener) + return () => ipcRenderer.removeListener(channel, listener) + } +} + +contextBridge.exposeInMainWorld('api', api) diff --git a/src/preload/inference.ts b/src/preload/inference.ts new file mode 100644 index 0000000..ebb0147 --- /dev/null +++ b/src/preload/inference.ts @@ -0,0 +1,33 @@ +import { contextBridge, ipcRenderer } from 'electron' + +// 숨김 추론 창 전용 브릿지. +// Main이 보내는 요청 채널만 수신하고, 응답은 'infer:reply'로만 전송한다. +const REQUEST_CHANNELS = ['infer:init', 'infer:describe', 'infer:detect'] as const +type RequestChannel = (typeof REQUEST_CHANNELS)[number] + +export interface InferBridge { + /** Main의 요청 수신 */ + onRequest( + cb: (channel: RequestChannel, payload: Record & { requestId: string }) => void + ): void + /** 요청 처리 결과 회신 */ + reply(requestId: string, ok: boolean, data?: unknown, error?: string): void + /** 모델 로드 완료 통지 */ + ready(): void +} + +const bridge: InferBridge = { + onRequest(cb) { + for (const channel of REQUEST_CHANNELS) { + ipcRenderer.on(channel, (_e, payload) => cb(channel, payload)) + } + }, + reply(requestId, ok, data, error) { + ipcRenderer.send('infer:reply', { requestId, ok, data, error }) + }, + ready() { + ipcRenderer.send('infer:ready') + } +} + +contextBridge.exposeInMainWorld('inferBridge', bridge) diff --git a/src/renderer/App.tsx b/src/renderer/App.tsx new file mode 100644 index 0000000..ba6c549 --- /dev/null +++ b/src/renderer/App.tsx @@ -0,0 +1,45 @@ +import { useEffect } from 'react' +import { useStore, wireEvents } from './store' +import { ProfileManager } from './components/ProfileManager' +import { FolderPicker } from './components/FolderPicker' +import { RunControl } from './components/RunControl' +import { ProgressView } from './components/ProgressView' +import { FileList } from './components/FileList' +import { ReportView } from './components/ReportView' + +export default function App(): JSX.Element { + const phase = useStore((s) => s.phase) + const refreshProfiles = useStore((s) => s.refreshProfiles) + + useEffect(() => { + const unwire = wireEvents() + void refreshProfiles() + return unwire + }, [refreshProfiles]) + + return ( +
+
+

AI Photo Organizer

+

+ 얼굴 인식 + 촬영일 기준 자동 사진 정리 · 로컬 전용 +

+
+ +
+ {/* 좌측: 설정 패널 */} +
+ + + +
+ + {/* 우측: 진행/결과 */} +
+ {phase === 'done' ? : } + +
+
+
+ ) +} diff --git a/src/renderer/components/FileList.tsx b/src/renderer/components/FileList.tsx new file mode 100644 index 0000000..114d237 --- /dev/null +++ b/src/renderer/components/FileList.tsx @@ -0,0 +1,59 @@ +import { useStore } from '../store' +import type { FileDecisionKind } from '@shared/types' + +const KIND_STYLE: Record = { + moved: { label: '이동', cls: 'bg-emerald-100 text-emerald-700' }, + copied: { label: '복사', cls: 'bg-sky-100 text-sky-700' }, + unmatched: { label: '미정', cls: 'bg-slate-200 text-slate-600' }, + failed: { label: '실패', cls: 'bg-red-100 text-red-700' } +} + +function baseName(p: string): string { + const idx = Math.max(p.lastIndexOf('/'), p.lastIndexOf('\\')) + return idx >= 0 ? p.slice(idx + 1) : p +} + +/** 처리 결과 스트림 (최근 건 상단) */ +export function FileList(): JSX.Element { + const processed = useStore((s) => s.processed) + + return ( +
+
+

처리 내역

+ 최근 {processed.length}건 +
+ +
+ {processed.length === 0 ? ( +

아직 처리된 파일이 없습니다.

+ ) : ( +
    + {processed.map((f, i) => { + const style = KIND_STYLE[f.kind] + return ( +
  • + + {style.label} + + + {baseName(f.file)} + + + {f.matchedNames.length > 0 + ? f.matchedNames.join(', ') + : f.error + ? f.error.slice(0, 40) + : '—'} + +
    • + ) + })} +
+ )} +
+
+ ) +} diff --git a/src/renderer/components/FolderPicker.tsx b/src/renderer/components/FolderPicker.tsx new file mode 100644 index 0000000..3b7e61c --- /dev/null +++ b/src/renderer/components/FolderPicker.tsx @@ -0,0 +1,50 @@ +import { useStore } from '../store' + +/** 소스 폴더 + 출력 루트 선택 */ +export function FolderPicker(): JSX.Element { + const source = useStore((s) => s.source) + const outputRoot = useStore((s) => s.outputRoot) + const setSource = useStore((s) => s.setSource) + const setOutput = useStore((s) => s.setOutput) + + const pickSource = async () => { + const p = await window.api.dialog.pickSource() + if (p) setSource(p) + } + const pickOutput = async () => { + const p = await window.api.dialog.pickOutput() + if (p) setOutput(p) + } + + return ( +
+

2. 폴더 선택

+ + + +
+ ) +} + +function Row(props: { + label: string + value: string | null + onPick: () => void +}): JSX.Element { + return ( +
+
{props.label}
+
+
+ {props.value ?? '미선택'} +
+ +
+
+ ) +} diff --git a/src/renderer/components/ProfileManager.tsx b/src/renderer/components/ProfileManager.tsx new file mode 100644 index 0000000..4371910 --- /dev/null +++ b/src/renderer/components/ProfileManager.tsx @@ -0,0 +1,114 @@ +import { useState } from 'react' +import { useStore } from '../store' +import { MAX_PROFILES } from '@shared/constants' + +/** 최대 3인 프로필 등록/수정 + 참조 이미지 추가 */ +export function ProfileManager(): JSX.Element { + const profiles = useStore((s) => s.profiles) + const refreshProfiles = useStore((s) => s.refreshProfiles) + const [name, setName] = useState('') + const [busy, setBusy] = useState(null) + const [error, setError] = useState(null) + + const addProfile = async () => { + const trimmed = name.trim() + if (!trimmed) return + setError(null) + try { + // 등록 순서 = 현재 인원 수 (뒤에 추가) + await window.api.profiles.upsert({ name: trimmed, order: profiles.length }) + setName('') + await refreshProfiles() + } catch (e) { + setError((e as Error).message) + } + } + + const addReference = async (id: string) => { + const paths = await window.api.dialog.pickImages() + if (paths.length === 0) return + setBusy(id) + setError(null) + try { + await window.api.profiles.addReference(id, paths) + await refreshProfiles() + } catch (e) { + setError((e as Error).message) + } finally { + setBusy(null) + } + } + + const remove = async (id: string) => { + await window.api.profiles.remove(id) + await refreshProfiles() + } + + return ( +
+
+

1. 인물 프로필

+ + {profiles.length}/{MAX_PROFILES}명 · 순서 = 이동 우선순위 + +
+ +
+ setName(e.target.value)} + onKeyDown={(e) => e.key === 'Enter' && addProfile()} + disabled={profiles.length >= MAX_PROFILES} + /> + +
+ + {error &&

{error}

} + +
    + {profiles.map((p, i) => ( +
  • +
    + #{i + 1} + {p.name} + + 참조 {p.descriptors.length}장 + +
    +
    + + +
    +
    • + ))} + {profiles.length === 0 && ( +
  • + 등록된 프로필이 없습니다. 이름을 추가하고 참조 얼굴 사진을 등록하세요. +
    • + )} +
+
+ ) +} diff --git a/src/renderer/components/ProgressView.tsx b/src/renderer/components/ProgressView.tsx new file mode 100644 index 0000000..bf49643 --- /dev/null +++ b/src/renderer/components/ProgressView.tsx @@ -0,0 +1,35 @@ +import { useStore } from '../store' + +/** 실시간 진행률 바 + 현재 처리 파일 */ +export function ProgressView(): JSX.Element { + const phase = useStore((s) => s.phase) + const progress = useStore((s) => s.progress) + + const total = progress?.total ?? 0 + const done = progress?.done ?? 0 + const pct = total > 0 ? Math.round((done / total) * 100) : 0 + + return ( +
+
+

진행 상황

+ + {phase === 'running' ? `${done} / ${total}` : '대기 중'} + +
+ +
+
+
+
+ + {progress?.current ?? (phase === 'running' ? '스캔 중…' : '실행 대기')} + + {pct}% +
+
+ ) +} diff --git a/src/renderer/components/ReportView.tsx b/src/renderer/components/ReportView.tsx new file mode 100644 index 0000000..a6fe143 --- /dev/null +++ b/src/renderer/components/ReportView.tsx @@ -0,0 +1,60 @@ +import { useStore } from '../store' + +function fmtDuration(ms: number): string { + const s = Math.round(ms / 1000) + const m = Math.floor(s / 60) + const rem = s % 60 + return m > 0 ? `${m}분 ${rem}초` : `${rem}초` +} + +/** 잡 완료 후 결과 리포트 */ +export function ReportView(): JSX.Element { + const report = useStore((s) => s.report) + const errors = useStore((s) => s.errors) + if (!report) return <> + + const stats = [ + { label: '총 처리', value: report.total, cls: 'text-slate-700' }, + { label: '이동', value: report.moved, cls: 'text-emerald-600' }, + { label: '복사', value: report.copied, cls: 'text-sky-600' }, + { label: '미정', value: report.unmatched, cls: 'text-slate-500' }, + { label: '실패', value: report.failed, cls: 'text-red-600' } + ] + + return ( +
+
+

✅ 작업 완료

+ 소요 {fmtDuration(report.elapsedMs)} +
+ +
+ {stats.map((s) => ( +
+
{s.value}
+
{s.label}
+
+ ))} +
+ +
+ 로그: {report.logPath} +
+ + {errors.length > 0 && ( +
+ + 오류 {errors.length}건 보기 + +
    + {errors.map((e, i) => ( +
  • + {e.file}: {e.message} +
    • + ))} +
+
+ )} +
+ ) +} diff --git a/src/renderer/components/RunControl.tsx b/src/renderer/components/RunControl.tsx new file mode 100644 index 0000000..98250b8 --- /dev/null +++ b/src/renderer/components/RunControl.tsx @@ -0,0 +1,107 @@ +import { useStore } from '../store' + +/** 실행/취소 + 옵션(임계값, 동시성, 검출기) */ +export function RunControl(): JSX.Element { + const { source, outputRoot, profiles, options, phase } = useStore((s) => ({ + source: s.source, + outputRoot: s.outputRoot, + profiles: s.profiles, + options: s.options, + phase: s.phase + })) + const setOptions = useStore((s) => s.setOptions) + const startJob = useStore((s) => s.startJob) + const cancelJob = useStore((s) => s.cancelJob) + const resetJob = useStore((s) => s.resetJob) + + const hasDescriptors = profiles.some((p) => p.descriptors.length > 0) + const canRun = !!source && !!outputRoot && phase !== 'running' + const running = phase === 'running' + + return ( +
+

3. 실행 옵션

+ +
+ + + + + +
+ + {!hasDescriptors && ( +

+ ⚠️ 등록된 얼굴이 없습니다. 매칭 인물 없이 모두 [미정]으로 분류됩니다. +

+ )} + +
+ {!running ? ( + + ) : ( + + )} + {phase === 'done' && ( + + )} +
+
+ ) +} diff --git a/src/renderer/global.d.ts b/src/renderer/global.d.ts new file mode 100644 index 0000000..473f853 --- /dev/null +++ b/src/renderer/global.d.ts @@ -0,0 +1,9 @@ +import type { ExposedApi } from '@shared/types' + +declare global { + interface Window { + api: ExposedApi + } +} + +export {} diff --git a/src/renderer/index.html b/src/renderer/index.html new file mode 100644 index 0000000..fa76ead --- /dev/null +++ b/src/renderer/index.html @@ -0,0 +1,16 @@ + + + + + + + AI Photo Organizer + + +
+ + + diff --git a/src/renderer/main.tsx b/src/renderer/main.tsx new file mode 100644 index 0000000..701cfe4 --- /dev/null +++ b/src/renderer/main.tsx @@ -0,0 +1,13 @@ +import React from 'react' +import { createRoot } from 'react-dom/client' +import App from './App' +import './styles/index.css' + +const container = document.getElementById('root') +if (!container) throw new Error('#root 요소를 찾을 수 없음') + +createRoot(container).render( + + + +) diff --git a/src/renderer/store.ts b/src/renderer/store.ts new file mode 100644 index 0000000..1b5da23 --- /dev/null +++ b/src/renderer/store.ts @@ -0,0 +1,97 @@ +import { create } from 'zustand' +import type { + Profile, + JobOptions, + FileProcessed, + ProgressEvent, + Report +} from '@shared/types' +import { DEFAULT_JOB_OPTIONS } from '@shared/constants' + +export type JobPhase = 'idle' | 'running' | 'done' + +interface AppState { + // 프로필 + profiles: Profile[] + setProfiles: (p: Profile[]) => void + refreshProfiles: () => Promise + + // 폴더/옵션 + source: string | null + outputRoot: string | null + options: JobOptions + setSource: (s: string | null) => void + setOutput: (s: string | null) => void + setOptions: (o: Partial) => void + + // 잡 상태 + phase: JobPhase + progress: ProgressEvent | null + processed: FileProcessed[] + report: Report | null + errors: { file: string; message: string }[] + + startJob: () => Promise + cancelJob: () => Promise + resetJob: () => void + + // 이벤트 핸들러(내부) + _onProgress: (p: ProgressEvent) => void + _onFile: (f: FileProcessed) => void + _onDone: (r: Report) => void + _onError: (e: { file: string; message: string }) => void +} + +export const useStore = create((set, get) => ({ + profiles: [], + setProfiles: (profiles) => set({ profiles }), + refreshProfiles: async () => { + const profiles = await window.api.profiles.list() + set({ profiles }) + }, + + source: null, + outputRoot: null, + options: { ...DEFAULT_JOB_OPTIONS }, + setSource: (source) => set({ source }), + setOutput: (outputRoot) => set({ outputRoot }), + setOptions: (o) => set({ options: { ...get().options, ...o } }), + + phase: 'idle', + progress: null, + processed: [], + report: null, + errors: [], + + startJob: async () => { + const { source, outputRoot, options } = get() + if (!source || !outputRoot) return + set({ phase: 'running', progress: null, processed: [], report: null, errors: [] }) + await window.api.job.run({ source, outputRoot, options }) + }, + cancelJob: async () => { + await window.api.job.cancel() + }, + resetJob: () => set({ phase: 'idle', progress: null, processed: [], report: null, errors: [] }), + + _onProgress: (progress) => set({ progress }), + _onFile: (f) => + set((s) => ({ + // 메모리 보호: 최근 500건만 UI에 유지 (리포트는 Main이 집계) + processed: [f, ...s.processed].slice(0, 500) + })), + _onDone: (report) => set({ report, phase: 'done' }), + _onError: (e) => set((s) => ({ errors: [e, ...s.errors].slice(0, 200) })) +})) + +/** 앱 시작 시 1회: Main→UI 이벤트 구독 */ +export function wireEvents(): () => void { + const s = useStore.getState() + const offs = [ + window.api.on('job:progress', s._onProgress), + window.api.on('job:fileProcessed', s._onFile), + window.api.on('job:done', s._onDone), + window.api.on('job:error', s._onError) + ] + return () => offs.forEach((off) => off()) +} diff --git a/src/renderer/styles/index.css b/src/renderer/styles/index.css new file mode 100644 index 0000000..a85b515 --- /dev/null +++ b/src/renderer/styles/index.css @@ -0,0 +1,19 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; + +:root { + color-scheme: light; +} + +body { + margin: 0; + font-family: 'Segoe UI', system-ui, -apple-system, sans-serif; + background: #f5f6fa; + color: #1f2330; +} + +/* 파일 목록 가독성용 모노 폰트 */ +.mono { + font-family: 'Cascadia Code', 'Consolas', monospace; +} diff --git a/src/shared/constants.ts b/src/shared/constants.ts new file mode 100644 index 0000000..4465b01 --- /dev/null +++ b/src/shared/constants.ts @@ -0,0 +1,50 @@ +// 전 프로세스 공유 상수 + +/** 처리 대상 이미지 확장자 (소문자, 점 포함) */ +export const SUPPORTED_EXTENSIONS = ['.jpg', '.jpeg', '.png', '.webp'] as const + +/** 미검출/인식실패 사진이 들어가는 폴더명 */ +export const UNMATCHED_FOLDER = '[미정]' + +/** 로그 폴더명 (출력 루트 하위) */ +export const LOG_FOLDER = '_PhotoAI_logs' + +/** 프로필 영속화 파일명 (userData 하위) */ +export const PROFILE_STORE_FILE = 'profiles.json' + +/** 최대 프로필 인원 (PRD) */ +export const MAX_PROFILES = 3 + +/** 기본 잡 옵션 */ +export const DEFAULT_JOB_OPTIONS = { + matchThreshold: 0.5, + concurrency: 3, + detector: 'ssd' as const +} + +/** 추론 시 이미지 장변 최대 픽셀 (다운스케일 기준) */ +export const MAX_IMAGE_DIMENSION = 1024 + +/** IPC 채널명 */ +export const IPC = { + // UI → Main (invoke) + PROFILES_LIST: 'profiles:list', + PROFILES_UPSERT: 'profiles:upsert', + PROFILES_REMOVE: 'profiles:remove', + PROFILES_ADD_REFERENCE: 'profiles:addReference', + DIALOG_PICK_SOURCE: 'dialog:pickSource', + DIALOG_PICK_OUTPUT: 'dialog:pickOutput', + DIALOG_PICK_IMAGES: 'dialog:pickImages', + JOB_RUN: 'job:run', + JOB_CANCEL: 'job:cancel', + // Main → UI (send) + JOB_PROGRESS: 'job:progress', + JOB_FILE_PROCESSED: 'job:fileProcessed', + JOB_DONE: 'job:done', + JOB_ERROR: 'job:error', + // Main ↔ Inference + INFER_READY: 'infer:ready', + INFER_DETECT: 'infer:detect', + INFER_DESCRIBE: 'infer:describe', + INFER_INIT: 'infer:init' +} as const diff --git a/src/shared/types.ts b/src/shared/types.ts new file mode 100644 index 0000000..2942c09 --- /dev/null +++ b/src/shared/types.ts @@ -0,0 +1,144 @@ +// 전 프로세스(Main/Preload/Renderer/Inference)가 공유하는 타입 정의 + +/** 등록된 인물 프로필 */ +export interface Profile { + id: string + /** 폴더명으로 사용되는 인물 이름 (예: "seunghyun") */ + name: string + /** 이동/복사 우선순위. 작을수록 1순위(=이동 대상). PRD: 첫 프로필 기준 이동 */ + order: number + /** 참조 이미지 절대 경로 목록 */ + referenceImages: string[] + /** 참조 이미지로부터 계산된 128-d descriptor 들 (number[] 직렬화 형태) */ + descriptors: number[][] +} + +/** 프로필 등록/수정 입력 */ +export interface ProfileInput { + id?: string + name: string + order: number +} + +/** 한 사진에 대한 단일 인물 매칭 결과 */ +export interface ProfileMatch { + profileId: string + name: string + order: number + /** Euclidean distance (작을수록 유사) */ + distance: number +} + +/** Inference 창이 반환하는 사진 1장 분석 결과 */ +export interface MatchResult { + /** 얼굴이 하나라도 검출되었는지 */ + faceFound: boolean + /** 등록 프로필과 매칭된 결과 (없으면 빈 배열) */ + matched: ProfileMatch[] + /** 검출된 총 얼굴 수 (디버깅/리포트용) */ + faceCount: number +} + +/** 참조 이미지 1장에 대한 descriptor 계산 결과 */ +export interface DescriptorResult { + imagePath: string + /** 얼굴 미검출 시 null */ + descriptor: number[] | null +} + +/** 촬영 날짜 (EXIF 또는 mtime 폴백) */ +export interface CaptureDate { + year: string // "2024" + month: string // "03" + /** EXIF에서 왔는지 mtime 폴백인지 */ + source: 'exif' | 'mtime' +} + +/** 정리 잡 실행 옵션 */ +export interface JobOptions { + /** 얼굴 매칭 거리 임계값 (기본 0.5) */ + matchThreshold: number + /** 동시 처리 워커 수 (기본 3) */ + concurrency: number + /** 정확도 우선(ssd) vs 속도 우선(tiny) */ + detector: 'ssd' | 'tiny' +} + +/** 정리 잡 정의 */ +export interface JobRequest { + source: string + outputRoot: string + options: JobOptions +} + +/** 파일 1건 처리 후 결정 종류 */ +export type FileDecisionKind = 'moved' | 'copied' | 'unmatched' | 'failed' + +/** 파일 1건 처리 결과 (UI 스트림 + 리포트용) */ +export interface FileProcessed { + file: string + /** 주된 결정 (이동/미정/실패) */ + kind: FileDecisionKind + /** 실제 기록된 대상 경로들 (이동 1 + 복사 N) */ + targets: string[] + /** 매칭된 인물 이름들 */ + matchedNames: string[] + date: CaptureDate | null + error?: string +} + +/** 진행률 이벤트 */ +export interface ProgressEvent { + done: number + total: number + /** 현재 처리 중인 파일 경로 */ + current: string +} + +/** 잡 완료 리포트 */ +export interface Report { + total: number + moved: number + copied: number + unmatched: number + failed: number + /** 소요 시간(ms) */ + elapsedMs: number + /** 작성된 로그 파일 경로 */ + logPath: string + startedAt: number + finishedAt: number +} + +/** IPC 이벤트(Main→UI) 페이로드 매핑 */ +export interface RendererEvents { + 'job:progress': ProgressEvent + 'job:fileProcessed': FileProcessed + 'job:done': Report + 'job:error': { file: string; message: string } +} + +export type RendererEventName = keyof RendererEvents + +/** preload가 노출하는 window.api 형태 */ +export interface ExposedApi { + profiles: { + list(): Promise + upsert(input: ProfileInput): Promise + remove(id: string): Promise + addReference(id: string, imagePaths: string[]): Promise + } + dialog: { + pickSource(): Promise + pickOutput(): Promise + pickImages(): Promise + } + job: { + run(req: JobRequest): Promise + cancel(): Promise + } + on( + event: E, + cb: (payload: RendererEvents[E]) => void + ): () => void +} diff --git a/tailwind.config.mjs b/tailwind.config.mjs new file mode 100644 index 0000000..96b424d --- /dev/null +++ b/tailwind.config.mjs @@ -0,0 +1,15 @@ +/** @type {import('tailwindcss').Config} */ +export default { + content: ['./src/renderer/**/*.{html,ts,tsx}'], + theme: { + extend: { + colors: { + brand: { + DEFAULT: '#5b7cfa', + dark: '#3f5ad6' + } + } + } + }, + plugins: [] +} diff --git a/tests/concurrency.test.ts b/tests/concurrency.test.ts new file mode 100644 index 0000000..87006a8 --- /dev/null +++ b/tests/concurrency.test.ts @@ -0,0 +1,29 @@ +import { describe, it, expect } from 'vitest' +import { createLimiter } from '../src/main/concurrency' + +describe('createLimiter', () => { + it('동시 실행 수가 limit을 넘지 않는다', async () => { + const limit = createLimiter(2) + let active = 0 + let maxActive = 0 + + const task = () => + limit(async () => { + active++ + maxActive = Math.max(maxActive, active) + await new Promise((r) => setTimeout(r, 10)) + active-- + }) + + await Promise.all(Array.from({ length: 10 }, task)) + expect(maxActive).toBeLessThanOrEqual(2) + }) + + it('모든 작업의 결과를 반환한다', async () => { + const limit = createLimiter(3) + const results = await Promise.all( + Array.from({ length: 5 }, (_, i) => limit(async () => i * 2)) + ) + expect(results).toEqual([0, 2, 4, 6, 8]) + }) +}) diff --git a/tests/fileOps.test.ts b/tests/fileOps.test.ts new file mode 100644 index 0000000..bb7c4b6 --- /dev/null +++ b/tests/fileOps.test.ts @@ -0,0 +1,59 @@ +import { describe, it, expect, beforeEach, afterEach } from 'vitest' +import { mkdtemp, writeFile, readFile, rm, mkdir, access } from 'node:fs/promises' +import { constants } from 'node:fs' +import { tmpdir } from 'node:os' +import { join } from 'node:path' +import { safeMove, safeCopy, resolveCollisionFreePath } from '../src/main/fileOps' + +let dir: string + +beforeEach(async () => { + dir = await mkdtemp(join(tmpdir(), 'photoai-')) +}) +afterEach(async () => { + await rm(dir, { recursive: true, force: true }) +}) + +async function exists(p: string): Promise { + try { + await access(p, constants.F_OK) + return true + } catch { + return false + } +} + +describe('safeMove', () => { + it('복사 후 원본을 삭제하고 내용이 보존된다', async () => { + const src = join(dir, 'a.txt') + await writeFile(src, 'hello') + const target = join(dir, 'out', 'a.txt') + + const dest = await safeMove(src, target) + expect(await exists(src)).toBe(false) // 원본 삭제됨 + expect(await readFile(dest, 'utf-8')).toBe('hello') + }) +}) + +describe('safeCopy + 충돌 자동 리네임', () => { + it('대상이 존재하면 _1, _2 로 리네임한다 (덮어쓰기 금지)', async () => { + const target = join(dir, 'out', 'a.txt') + await mkdir(join(dir, 'out'), { recursive: true }) + await writeFile(target, 'existing') + + const src = join(dir, 'src.txt') + await writeFile(src, 'new') + + const dest = await safeCopy(src, target) + expect(dest.endsWith('a_1.txt')).toBe(true) + expect(await readFile(target, 'utf-8')).toBe('existing') // 원본 보존 + expect(await readFile(dest, 'utf-8')).toBe('new') + }) +}) + +describe('resolveCollisionFreePath', () => { + it('충돌 없으면 그대로 반환한다', async () => { + const target = join(dir, 'fresh.txt') + expect(await resolveCollisionFreePath(target)).toBe(target) + }) +}) diff --git a/tests/pathBuilder.test.ts b/tests/pathBuilder.test.ts new file mode 100644 index 0000000..fc22344 --- /dev/null +++ b/tests/pathBuilder.test.ts @@ -0,0 +1,24 @@ +import { describe, it, expect } from 'vitest' +import { buildTargetPath, withCollisionSuffix } from '../src/main/pathBuilder' +import type { CaptureDate } from '../src/shared/types' + +const date: CaptureDate = { year: '2024', month: '03', source: 'exif' } + +describe('buildTargetPath', () => { + it('인물 매칭 시 /프로필/YYYY/MM/파일명 경로를 만든다', () => { + const p = buildTargetPath('/out', 'seunghyun', date, '/src/a/photo.jpg') + expect(p.replace(/\\/g, '/')).toBe('/out/seunghyun/2024/03/photo.jpg') + }) + + it('미검출(who=null) 시 [미정] 폴더로 보낸다', () => { + const p = buildTargetPath('/out', null, date, '/src/photo.png') + expect(p.replace(/\\/g, '/')).toBe('/out/[미정]/2024/03/photo.png') + }) +}) + +describe('withCollisionSuffix', () => { + it('확장자 앞에 _N을 붙인다', () => { + const p = withCollisionSuffix('/out/x/photo.jpg', 2) + expect(p.replace(/\\/g, '/')).toBe('/out/x/photo_2.jpg') + }) +}) diff --git a/tsconfig.json b/tsconfig.json new file mode 100644 index 0000000..155ebaa --- /dev/null +++ b/tsconfig.json @@ -0,0 +1,7 @@ +{ + "files": [], + "references": [ + { "path": "./tsconfig.node.json" }, + { "path": "./tsconfig.web.json" } + ] +} diff --git a/tsconfig.node.json b/tsconfig.node.json new file mode 100644 index 0000000..0e5a9ab --- /dev/null +++ b/tsconfig.node.json @@ -0,0 +1,27 @@ +{ + "compilerOptions": { + "composite": true, + "target": "ES2022", + "module": "ESNext", + "moduleResolution": "Bundler", + "lib": ["ES2022"], + "strict": true, + "noUnusedLocals": true, + "noUnusedParameters": true, + "esModuleInterop": true, + "skipLibCheck": true, + "resolveJsonModule": true, + "types": ["node"], + "baseUrl": ".", + "paths": { + "@shared/*": ["src/shared/*"] + } + }, + "include": [ + "src/main/**/*.ts", + "src/preload/**/*.ts", + "src/shared/**/*.ts", + "scripts/**/*.mjs", + "electron.vite.config.ts" + ] +} diff --git a/tsconfig.web.json b/tsconfig.web.json new file mode 100644 index 0000000..5f745f1 --- /dev/null +++ b/tsconfig.web.json @@ -0,0 +1,28 @@ +{ + "compilerOptions": { + "composite": true, + "target": "ES2022", + "module": "ESNext", + "moduleResolution": "Bundler", + "lib": ["ES2022", "DOM", "DOM.Iterable"], + "jsx": "react-jsx", + "strict": true, + "noUnusedLocals": true, + "noUnusedParameters": true, + "esModuleInterop": true, + "skipLibCheck": true, + "resolveJsonModule": true, + "allowSyntheticDefaultImports": true, + "baseUrl": ".", + "paths": { + "@shared/*": ["src/shared/*"], + "@renderer/*": ["src/renderer/*"] + } + }, + "include": [ + "src/renderer/**/*.ts", + "src/renderer/**/*.tsx", + "src/inference/**/*.ts", + "src/shared/**/*.ts" + ] +} diff --git a/vitest.config.ts b/vitest.config.ts new file mode 100644 index 0000000..5fef398 --- /dev/null +++ b/vitest.config.ts @@ -0,0 +1,12 @@ +import { resolve } from 'node:path' +import { defineConfig } from 'vitest/config' + +export default defineConfig({ + resolve: { + alias: { '@shared': resolve(__dirname, 'src/shared') } + }, + test: { + environment: 'node', + include: ['tests/**/*.test.ts'] + } +})