Repository navigation
Releases
Releases · shini111/ImageWeaver
ImageWeaver v1.0.0 - Initial Release
🎯 ImageWeaver v1.0.0 - AI-Powered Image Placement
First official release! 🎉
ImageWeaver intelligently restores images to translated HTML files using advanced context analysis and LLM refinement. Perfect for Korean→English translation workflows where images get lost during text-only translation.
🚀 Quick Start for Windows
Option 1: Download Executable (Recommended)
- Download
ImageWeaver-1.0.0-windows.zipfrom assets below - Extract the zip file
- Run
start.batfor one-click setup menu - Or directly run
ImageWeaver.exefor GUI
Option 2: Individual Downloads
ImageWeaver.exe(17.3 MB) - Modern GUI applicationImageWeaver-Console.exe(13.8 MB) - Command line version
No Python installation required! ✨
✨ What's New in v1.0.0
- 🎯 Advanced Context Extraction: Dynamic thresholds (60-100 chars), quality scoring, adaptive windowing
- 🧠 LLM-Powered Refinement: Ollama (local) and OpenAI support for intelligent placement
- 📊 Smart Fallback Strategies: 4-tier placement system ensures images are never lost
- 🖥️ Modern Dark Mode GUI: Professional interface with real-time progress tracking
- 💻 Command Line Support: Batch processing for automation workflows
- 📈 Detailed Analytics: Success rates, strategy breakdowns, performance metrics
🎯 Performance Highlights
- 15-25x faster than brute-force approaches
- 95% cost reduction for OpenAI usage with advanced targeting
- Dynamic adaptation to document characteristics
- Professional Windows batch files for easy setup
🛠️ LLM Support
Ollama (Recommended - Free & Local)
- Install from https://ollama.ai
- Run:
ollama pull llama3.2:1b - Start:
ollama serve
OpenAI (Cloud - Paid)
- Uses
gpt-4o-minifor cost efficiency - Requires API key from https://platform.openai.com
💻 System Requirements
- Windows: 10+ (64-bit)
- RAM: 4GB minimum (8GB recommended for LLM features)
- Storage: 50MB for application
- Optional: Ollama for local LLM processing
🔧 Advanced Features
- Dynamic threshold adaptation based on paragraph length
- Context quality scoring with dialogue/action detection
- Adaptive window sizing based on document structure
- Intelligent context usage (up to 5+5 paragraphs for LLM)
- Repetitive content detection with automatic fallbacks
📁 Usage Example
Original folder: C:\docs\original\ (HTML files with images)
Translated folder: C:\docs\translated\ (HTML files, text only)
Output folder: C:\docs\output\ (HTML files with images restored)
🤝 Perfect For
- Post-translation processing - Restore images after AI translation
- Content migration - Move images between different HTML structures
- Quality assurance - Ensure translated documents maintain visual layout
- Batch operations - Process large sets of files efficiently
📄 What's Included
- ImageWeaver.exe - Main GUI application (Windows)
- ImageWeaver-Console.exe - Command line version (Windows)
- Batch files - One-click setup and launch scripts
- Complete documentation - README, LICENSE, requirements
- Source code - Full Python source for other platforms
🐛 Known Issues
- Very short paragraphs (< 10 characters) may affect context quality scoring
- Large documents (> 1000 paragraphs) may require longer processing times
🔗 Links
- Documentation: See README.md
- Issues: Report bugs in the Issues tab
- Source Code: Available for other platforms
Supports Korean→English workflows with advanced AI-powered context matching