fashion-inpainting-system

Fashion Inpainting System

🎨 Advanced AI-powered fashion transformation system that preserves body pose and facial identity while generating new clothing styles.

🚀 Key Features

• Pose Preservation: Advanced 25.3% pose coverage system maintains body structure and proportions
• Facial Identity Protection: Preserves original facial features and expressions
• Safety-First Design: Built-in content filtering and safety checks
• Multiple Checkpoint Support: Compatible with various Stable Diffusion checkpoints
• Production Ready: Comprehensive error handling and fallback systems

🎯 What This System Does

Input: Person wearing any outfit
Output: Same person in a completely different outfit while maintaining:

• ✅ Exact facial identity
• ✅ Original body pose and proportions
• ✅ Natural fabric draping and fit
• ✅ Appropriate content generation

🛡️ Safety & Ethical Use

⚠️ IMPORTANT USAGE RESTRICTIONS

This system is designed for creative and artistic purposes only. By using this software, you agree to:

✅ ALLOWED USES:

• Fashion design and visualization
• Creative artwork and artistic expression
• Educational and research purposes
• Personal style exploration
• Commercial fashion applications (with proper licensing)

❌ PROHIBITED USES:

• Creating deceptive or misleading content
• Non-consensual image manipulation
• Identity theft or impersonation
• Harassment or bullying
• Creation of inappropriate content
• Any illegal or harmful activities

🔒 Built-in Safety Features

• Content Filtering: Automatic detection and prevention of inappropriate outputs
• Identity Preservation: System designed to change clothing only, not faces
• Pose Validation: Ensures generated content maintains appropriate poses
• Quality Thresholds: Filters out low-quality or distorted results

🏗️ System Architecture

Core Components

1. Pose Extraction System (25.3% coverage)

   • OpenPose-based pose detection via controlnet_aux
   • 5-channel pose vectors (Body, Hands, Face, Feet, Skeleton)
   • Dilated regions for enhanced coverage

2. Hand Exclusion Logic

   • Prevents generation of extra hands/limbs
   • Conservative mask erosion with exclusion zones
   • Optimized for natural results

3. Safety-Aware Generation

   • Content filtering for appropriate results
   • Coverage analysis for generation scope
   • Adaptive prompting based on input analysis

4. Checkpoint Compatibility

   • Supports custom Stable Diffusion models
   • Automatic parameter optimization
   • Fashion-specific model recommendations

📋 Requirements

Python 3.8+
torch>=1.13.0
diffusers>=0.21.0
transformers>=4.21.0
controlnet_aux>=0.4.0
opencv-python>=4.6.0
pillow>=9.0.0
numpy>=1.21.0

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/mlworks90/fashion-inpainting-system.git
cd fashion-inpainting-system

# Install dependencies
pip install -r requirements.txt

# Optional: Install with CUDA support
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118

Basic Usage

from fashion_safety_checker import create_fashion_safety_pipeline
pipeline = create_fashion_safety_pipeline()

# Transform outfit
result = pipeline.safe_fashion_transformation(
    source_image_path="person_in_casual_wear.jpg",
    checkpoint_path="fashion_checkpoint.safetensors",
    outfit_prompt="elegant red evening dress",
    output_path="person_in_evening_dress.jpg",
    face_scale=0.90  # Manual face to body ratio adjustment
)

if result['success']:
    print("✅ Fashion transformation completed")
else:    
    print(f"Blocking reason: {result['blocking_reason']}")
    print(f"User message: {result['user_message']}")

📊 Performance & Quality

• Pose Preservation: 25.3% coverage ensures accurate body structure
• Face Identity: >95% facial feature preservation
• Generation Speed: ~30-60 seconds per image (depending on hardware)
• Memory Usage: 8-12GB VRAM recommended
• Success Rate: >85% for well-posed input images

🔧 Configuration

Safety Settings

pipeline = create_fashion_safety_pipeline(safety_mode="legacy_strict") 
 # legacy_strict - highest safety restrictions
 # fashion_strict - conservative outfits only
 # fashion_moderate - default level. Suitable for most garment types except some swimwear.
 # fashion_permissive - most permissive mode. Be aware of inappropriate outputs possibility!
            

🧪 Examples

Fashion Transformations

🏢 Commercial Use & Support

Open Source License

This project is licensed under Apache License 2.0, allowing:

• ✅ Commercial use
• ✅ Modification and distribution
• ✅ Private use
• ✅ Patent grant

Professional Services Available

For commercial deployments, we offer:

• Custom model training for specific fashion domains
• API integration and cloud deployment
• Performance optimization for production environments
• Priority support and SLA guarantees
• Custom safety filtering for brand-specific requirements

Contact: [email protected]

📚 Documentation

• Installation Guide
• API Reference
• Safety Guidelines
• Troubleshooting
• Commercial Licensing

🤝 Contributing

We welcome contributions! Please read our Contributing Guidelines and Code of Conduct.

Development Setup

# Clone repository
git clone https://github.com/mlworks90/fashion-inpainting-system.git
cd fashion-inpainting-system

# Install in development mode
pip install -e .

# Run tests
python -m pytest tests/

🙏 Acknowledgments

This system builds upon excellent open-source projects:

• Stable Diffusion by CompVis
• ControlNet by lllyasviel
• Diffusers by Hugging Face
• controlnet_aux for OpenPose processing

📄 License

Licensed under the Apache License, Version 2.0. See LICENSE for details.

⚖️ Legal & Safety Disclaimers

• Users are responsible for ensuring appropriate use and obtaining necessary consents
• This software is provided "as is" without warranty
• Not intended for creating deceptive or harmful content
• Users must comply with applicable laws and regulations
• Commercial users should review terms and consider professional support

📞 Support & Contact

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Commercial Inquiries: [email protected]
• Documentation: Project Wiki

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Made with ❤️ for the AI and Fashion communities