Project Overview
Searchy is a lightweight image browsing and searching application built specifically for macOS. Frustrated with the limitations of existing photo management tools on Mac, I decided to create a solution that leverages AI for intelligent image search while keeping everything on-device.
Key Features
- 🧠 AI-Powered Search: Uses CLIP model for intelligent image understanding
- 🔒 Privacy-First: All processing happens on-device, no data leaves your Mac
- ⚡ Lightweight: Fast and efficient, designed for Mac performance
- 🔍 Semantic Search: Find images by describing what's in them
- 📁 Smart Browsing: Intuitive interface for exploring your photo library
Technology Stack
Languages & Frameworks
The Problem
Mac's built-in photo management solutions often fall short for users with large image collections. Finding specific photos becomes a tedious task of scrolling through thousands of images or relying on basic metadata search. Traditional solutions are either too heavy, cloud-dependent, or lack intelligent search capabilities.
The Solution
Searchy addresses these pain points by providing:
- Semantic Understanding: Search for "sunset over mountains" and find relevant images
- On-Device Processing: Your photos never leave your device
- Performance Optimized: Built with Swift for native Mac performance
- Extensible Design: Architecture allows for future AI model integrations
Future Roadmap
- 🗑️ Duplicate image detection and deletion
- 🏷️ Custom AI models for specific image domains
- 📝 User-defined image tagging system
- 🔍 Spotlight-style search widget integration
- 🎨 Enhanced UI with modern design patterns
- ⚡ Performance optimizations for large libraries
Development Journey
This project represents my exploration into the intersection of AI and practical software solutions. Working with CLIP models and Core ML has been an exciting challenge, requiring me to balance machine learning capabilities with user experience design. The Swift/Python hybrid approach allows for leveraging the best of both ecosystems.