Image MetaHub

This project was renamed from local-image-browser-for-invokeai to Image MetaHub. All links and references have been updated.

A desktop application for browsing, searching, and organizing AI-generated images locally. Designed for performance with large collections, focusing on powerful metadata filtering and complete privacy.

All processing is performed locally on your machine. No data is sent to external services, and no internet connection is required after installation.

For detailed changes and updates, see the Releases page.

Releases & Updates

This project uses automated release management to ensure consistent, informative release notes:

• Cross-platform builds for Windows, macOS, and Linux
• Rich release notes generated from CHANGELOG.md
• Auto-updates available in the desktop application
• Release guide available in RELEASE-GUIDE.md

For maintainers: See RELEASE-GUIDE.md for the automated release workflow.

Key Features

Advanced Search & Filtering

• Deep Metadata Search: Full-text search across all PNG and JPEG metadata including prompts, models, and generation parameters
• Precise Filtering: Filter by Models, LoRAs, Schedulers, image dimensions, generation steps, CFG Scale, and date ranges
• Multi-Format Support: Works with InvokeAI, Automatic1111, and ComfyUI generated images (PNG and JPEG)

Enhanced User Experience

• Multiple Directories: Add and manage multiple image directories simultaneously
• Configurable Settings: Control cache location and automatic update preferences
• Resizable Grid: Adjust thumbnail sizes for optimal viewing on any display
• Command-Line Support: Launch with a specified directory for automation workflows
• Developer Mode: Access development server from local network devices
• Configurable Directory Scanning: Choose whether to scan subfolders recursively or limit to selected folder only
• Multi-Selection: Use Ctrl+Click to select multiple images for bulk operations

Performance & Large Collections

• Optimized for Scale: Efficiently handles 18,000+ images without performance issues
• Smart Caching: Subsequent folder loads take seconds instead of minutes by processing only new files
• Memory Efficient: Lazy loading and background processing ensure responsive performance

File Management

• Direct File Operations: Rename and delete files within the application (Desktop version)
• Metadata Export: Export complete image metadata to JSON or readable TXT files
• Fullscreen Viewer: Distraction-free image viewing with keyboard navigation

Installation

Desktop Application (Recommended)

1. Go to Releases
2. Download the installer for your system (.exe for Windows, .dmg for macOS, .AppImage for Linux)
3. Run the installer and launch the application

Run from Source

git clone https://github.com/LuqP2/image-metahub.git
cd image-metahub
npm install

# Option 1: Run in browser only
npm run dev

# Option 2: Run Electron app with optional directory
npm run dev:app
npm run dev:app -- --dir "/path/to/images"

Command-Line Usage

Desktop Application (Production)

# Windows
ImageMetaHub.exe --dir "C:\path\to\images"

# macOS/Linux
./ImageMetaHub --dir "/path/to/images"

Development Mode

# Start Vite dev server only (browser access)
npm run dev

# Start Electron app with Vite dev server
npm run dev:app

# Start with initial directory
npm run dev:app -- --dir "/path/to/images"

The dev server automatically binds to 0.0.0.0, making it accessible from other devices on your local network. Check the console output for the network URL.

Quick Start

1. Launch the application and click "Change Folder" to select your AI-generated images directory
2. Choose whether to scan subfolders recursively or limit to the selected folder only
3. Wait for initial indexing (may take a few minutes for large collections)
4. Use the sidebar to search and filter your images by metadata, models, or generation parameters
5. Click any image to view detailed metadata and management options
6. Use "Update" button to quickly index new images without re-processing the entire collection

Technical Details

• Frontend: React 18 with TypeScript
• Desktop: Electron with integrated auto-updater
• Storage: IndexedDB for persistent local caching
• File Access: File System Access API (browser) / Node.js filesystem (desktop)
• Metadata Support: InvokeAI, Automatic1111, and ComfyUI PNG/JPEG metadata formats
• Directory Scanning: Configurable recursive subfolder scanning with user preference persistence

For comprehensive technical information, see ARCHITECTURE.md.

Privacy & Security

This application operates entirely offline:

• All processing happens on your local machine
• No accounts, telemetry, or network requests (except auto-updater)
• File system access requires explicit user permission
• All data remains on your device

Contributing

Contributions are welcome! Please open an issue for major changes to discuss the approach first.

Roadmap

Short-Term

• Advanced range filters for Steps and CFG Scale
• Virtual scrolling for extremely large collections
• Configurable subfolder scanning

Medium-Term

• ComfyUI metadata support (partial implementation complete)
• Custom tagging system
• Image comparison view

Long-Term

• Plugin architecture for extensibility
• Image similarity search
• Optional cloud sync for settings

License

Licensed under the MIT License.

This is an independent project and is not affiliated with Invoke AI, Inc.