🎨 Professional AI-powered multi-layer 3D printing optimization tool that converts 2D images into optimized multi-layer 3D models for color printing with advanced transparency mixing.

Version Python PyTorch License

BananaForge uses cutting-edge AI optimization to create multi-color 3D prints with 30% fewer material swaps and professional-quality results:

• 🧠 AI-Powered Optimization: PyTorch-based differentiable optimization with Gumbel softmax sampling
• 🌈 Advanced Transparency Mixing: Create more colors with fewer materials through strategic layer transparency
• 🎯 Intelligent Material Selection: LAB color space optimization for perceptual accuracy
• ⚡ GPU Acceleration: CUDA and MPS support for fast processing
• 📊 Professional Output: STL files, HueForge projects, detailed cost analysis

# Install BananaForge
pip install -e .
# Convert your first image
bananaforge convert photo.jpg --materials materials.csv
# With transparency mixing for fewer material swaps
bananaforge convert photo.jpg --enable-transparency --materials materials.csv --max-materials 6

BananaForge introduces transparency-based color mixing that revolutionizes multi-color 3D printing:

• 33% opacity: Light transparency for subtle color mixing
• 67% opacity: Medium transparency for gradient effects
• 100% opacity: Full color for vibrant base layers

• 30%+ reduction in material swaps
• Intelligent base layer optimization for maximum contrast
• Gradient detection for smooth color transitions
• Cost analysis with detailed savings reports

# Enable transparency features with full options
bananaforge convert image.jpg \
 --enable-transparency \
 --opacity-levels "0.33,0.67,1.0" \
 --optimize-base-layers \
 --enable-gradients \
 --materials materials.csv \
 --max-materials 6 \
 --max-layers 25 \
 --mixed-precision \
 --export-format "stl,instructions,cost_report,transparency_analysis" \
 --output ./transparent_model/

git clone https://github.com/eddieoz/BananaForge.git
cd BananaForge
pip install -e .[dev]

bananaforge version
bananaforge --help

• Enhanced Optimization Engine: Discrete validation, learning rate scheduling, mixed precision
• Advanced Image Processing: LAB color space, saturation enhancement, color-preserving resize
• Intelligent Height Map System: Two-stage K-means clustering, multi-threaded initialization
• Transparency Mixing System: Physics-based alpha compositing, gradient processing
• Professional Output: STL with alpha support, HueForge projects, detailed analytics

• PyTorch: Differentiable optimization with automatic mixed precision
• LAB Color Space: Perceptually uniform color calculations
• Gumbel Softmax: Discrete optimization with gradient flow
• Multi-threading: Parallel processing for complex operations

• Quick Start Guide - Get started in 5 minutes
• Materials Guide - Managing filaments and color matching
• CLI Reference - Complete command reference
• API Reference - Python programming interface
• Configuration - Advanced settings and workflows
• Examples - Real-world usage examples

# Run all tests
pytest tests/ -v
# Run with coverage
pytest tests/ --cov=bananaforge --cov-report=html
# Run specific feature tests
pytest tests/test_feature4_5_transparency_color_mixing.py -v

We welcome contributions! This project follows TDD/BDD development practices.

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Write tests first: Follow our BDD scenarios in tests/
4. Implement features: Make tests pass
5. Submit a pull request

MIT License - see LICENSE for details.

• Built with ❤️ using PyTorch and modern AI techniques
• Inspired by the 3D printing and computer vision communities
• Special thanks to HueForge and Autoforge for pioneering multi-color 3D printing workflows

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