cf7c72d4372837838896505b1e45a499598b97c8
Two related fixes:
1. Prevention — scanner now normalizes paths before lookup/insert
in get_or_create_source_root and get_or_create_folder. Trailing
slashes, redundant separators, and `.` segments all collapse to
the same row. _normalize_path uses os.path.normpath; symlinks
are intentionally NOT resolved so mount paths stay intact for
cross-machine portability.
2. Cleanup — new app/services/cleanup.py runs on backend startup
(idempotent) and merges any pre-existing duplicates left over
from older scanner versions:
- Groups source_roots by normalized path. Picks the canonical
row (preferring one with a non-empty name and the earliest
added_at), re-points child Folder rows via UPDATE, and
deletes the duplicates.
- Same for folders, with photo_count as the tiebreaker. Photos
get re-pointed to the canonical folder via UPDATE.
- Recomputes folder.photo_count from the actual non-discarded
photo membership so the sidebar count matches reality.
Wired into main.py's lifespan handler. On the dev DB this merged
the empty-name "/host/Pictures/MulitaTest/" duplicate that was
showing up alongside the canonical MulitaTest source root.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Mulita - Self-Hosted Photo Management Application
A self-hosted, Docker-deployed photo management application inspired by Lightroom's workflow. Mulita provides a fast, keyboard-driven interface to browse, organize, tag, and manage your photo library.
Features
- Photo Organization: Browse photos in a timeline view with virtual scrolling for performance
- Thumbnail Generation: Automatic thumbnail generation for all photo formats including RAW
- Metadata Extraction: Full EXIF/XMP metadata extraction and search
- Keyboard Shortcuts: Lightroom-style keyboard navigation and actions
- File Support: JPEG, PNG, RAW formats (CR2, CR3, NEF, ARW, etc.), HEIC/HEIF, and videos
- Heaps: Temporary collections for organizing photos
- Tags & Ratings: Organize with tags, star ratings, and color labels
- Dark Mode: Photography-optimized dark interface
Tech Stack
Backend
- Python 3.12 with FastAPI
- SQLite with SQLAlchemy (async)
- Celery + Redis for background tasks
- pyvips for fast thumbnail generation
- ExifTool for metadata extraction
Frontend
- React 18 with TypeScript
- Vite for fast development
- TanStack Query for data fetching
- TanStack Virtual for virtualized scrolling
- Tailwind CSS for styling
- Zustand for state management
Quick Start
Prerequisites
- Docker and Docker Compose
- Photo directories to mount
Setup
- Clone the repository:
git clone <repository-url>
cd muleimage
- Configure your photo directories in
.env:
# Edit .env file
PHOTO_DIRS=/path/to/your/photos
- Start the application:
docker-compose up -d
- Access the application at
http://localhost:3000
Architecture
The application consists of 5 Docker services:
- frontend: React SPA served by Nginx
- backend: FastAPI REST API
- worker: Celery workers for background tasks
- redis: Message broker for Celery
- db: SQLite database (file-based)
Keyboard Shortcuts
| Key | Action |
|---|---|
← → ↑ ↓ |
Navigate photos |
Space |
Quick preview |
Enter |
Open loupe view |
P |
Pick photo |
X |
Reject photo |
1-5 |
Set star rating |
Tab |
Toggle left sidebar |
I |
Toggle metadata panel |
G |
Grid view |
E |
Loupe view |
Delete |
Move to trash |
Development
Backend Development
cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload
Frontend Development
cd frontend
npm install
npm run dev
Configuration
Edit mulita.yml to configure:
- Source photo directories
- Thumbnail sizes and quality
- Scanner settings
- Performance tuning
Performance
- Handles 100,000+ photos efficiently
- Virtual scrolling for smooth timeline navigation
- Thumbnail generation at 10+ photos/second
- SQLite FTS5 for fast full-text search
Future Features (Phase 2)
- AI-powered scene classification
- Face detection and clustering
- Smart albums
- Duplicate detection
- Export presets
- Multi-user support
License
MIT
Description
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