5374eba08f
- New module: modules/ai_upscaler.py - Real-ESRGAN integration for AI-powered upscaling - Designed specifically for low-res game textures/icons - 4x upscale factor with neural network enhancement - Falls back gracefully if model not available - Updated TGA Converter UI: - New "AI Enhanced (Real-ESRGAN)" option in upscale dropdown - Only shown if Real-ESRGAN is installed - AI upscaling happens before canvas placement - Shows progress during AI model loading Real-ESRGAN is much better than basic methods for rendered (non-pixel) icons! To use AI upscaling: 1. pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu 2. pip install realesrgan 3. Download RealESRGAN_x4plus.pth model 4. Select "AI Enhanced" in the UI |
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| core | ||
| docs | ||
| memory | ||
| modules | ||
| test-data | ||
| tests | ||
| ui | ||
| .env.example | ||
| .gitignore | ||
| AGENTS.md | ||
| AI_KNOWLEDGE_BASE.md | ||
| COMPLETE_FEATURE_SUMMARY.md | ||
| DEVELOPMENT_SUMMARY.md | ||
| GAME_MECHANICS.md | ||
| INSPIRATION.md | ||
| MODULE_REQUIREMENTS.md | ||
| OBSIDIAN_WORKFLOW.md | ||
| OCR_IMPLEMENTATION_SUMMARY.md | ||
| OCR_SETUP.md | ||
| PROJECT_INDEX.md | ||
| PROJECT_RESUME.md | ||
| README.md | ||
| RESOURCES.md | ||
| TECHNICAL_SPECS.md | ||
| TESTING_AND_DEBUGGING.md | ||
| UI_CLEANUP_SUMMARY.md | ||
| USER_TEST_GUIDE.md | ||
| VERIFICATION_CHECKLIST.md | ||
| WINDOWS_TESTING_GUIDE.md | ||
| demo_ocr.py | ||
| environment-test.md | ||
| fix_pytorch.bat | ||
| fix_pytorch_python313.bat | ||
| gui_main.py | ||
| install_vision_quick.bat | ||
| main.py | ||
| migrate_db.py | ||
| pytest.ini | ||
| requirements-ocr.txt | ||
| requirements.txt | ||
| run_tests.bat | ||
| test_ocr_system.py | ||
| verify_vision.py | ||
| vision_example.py | ||
README.md
Entropia-Tools Suite Replication Project
Project Overview
This project aims to replicate the full software suite found at Entropia-Tools.com. The suite provides professional-grade analytics, financial tracking, and utility tools for players of the MMORPG Entropia Universe.
Core Philosophy: The Data Principle
All modules must treat user data as "Projects." Every session (a hunt, a mining run, or a crafting batch) must be:
- Stored: Automatically saved to a local database.
- Archivable: Capable of being closed and reopened as a "Previous Project."
- Comparable: Users should be able to compare current live data against historical project data.
Module Summary
- Hunter Tracker: Combat performance and ROI analytics.
- Mining Tracker: Geospatial resource mapping and probe efficiency.
- Crafting Tool: Manufacturing cost/benefit simulation.
- Inventory Manager: Asset valuation and market markup tracking.
Technical Stack Recommendation
- Language: Python (for rapid dev) or C#/.NET (for Windows native performance).
- Database: SQLite or structured JSON for project storage.
- UI: Modern Dark Mode (PyQt6 or Electron).