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# NowYouSeeMe: Real-Time 6DOF Holodeck Environment
<div align="center">
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**A robust, real-time 6DOF, photo-realistic "holodeck" environment using commodity laptop camera and Wi-Fi Channel State Information (CSI) as primary sensors, supplemented by GPU-accelerated neural enhancements.**
[🚀 Quick Start](#-quick-start) • [📖 Documentation](docs/) • [🤝 Contributing](CONTRIBUTING.md) • [📋 Requirements](#-prerequisites) • [🎮 Features](#-features)
</div>
## 🎯 Project Objectives
- **End-to-end spatial mapping** and dynamic object tracking at interactive frame rates (<20 ms latency)
- **RF-vision fusion** to cover areas with low visibility or occlusions
- **Extensible codebase** split between rapid Python prototyping and optimized C++/CUDA modules
- **Advanced electromagnetic field manipulation** for free space visualization and content generation
## 🏗️ System Architecture
```
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Camera Capture │ │ Wi-Fi CSI Capture│ │ Calibration │
│ (OpenCV/GStream)│ │ (Intel 5300/Nex) │ │ Store │
└─────────┬───────┘ └────────┬─────────┘ └─────────────────┘
│ │
▼ ▼
┌─────────────────────────────────────────────────────────────┐
│ Sensor Fusion Module │
│ - RF point cloud & occupancy grid │
│ - Vision pose graph & dense point cloud │
└─────────────┬───────────────────────────────┬─────────────┘
│ │
▼ ▼
┌─────────────────┐ ┌─────────────────────┐
│ Export Engine │ │ Rendering Engine │
│ (Unity/UE4) │ │ (VR/Projection Map) │
└─────────────────┘ └─────────────────────┘
```
## 🚀 Quick Start
### 📋 Prerequisites
- **OS**: Ubuntu 20.04+ (primary target) or Windows 10+
- **GPU**: CUDA-capable GPU (NVIDIA GTX 1060+)
- **WiFi**: Intel 5300 WiFi card or Broadcom chipset with Nexmon support
- **Camera**: USB camera (720p+ recommended)
- **RAM**: 8GB+ recommended
- **Storage**: 10GB+ free space
### 🐳 Docker Installation (Recommended)
```bash
# Clone the repository
git clone https://github.com/your-org/NowYouSeeMe.git
cd NowYouSeeMe
# Start with Docker Compose
docker-compose up -d
# Or build and run manually
docker build -t nowyouseeme .
docker run --privileged -p 8080:8080 nowyouseeme
```
### 🔧 Manual Installation
```bash
# Clone the repository
git clone https://github.com/your-org/NowYouSeeMe.git
cd NowYouSeeMe
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -e .[dev]
# Build C++ components
./tools/build.sh
# Run calibration
python -m src.calibration.calibrate_camera
# Start the holodeck
python -m src.ui.holodeck_ui
```
### 📦 PyPI Installation
```bash
pip install nowyouseeme[gpu,azure]
nowyouseeme
```
### 🛠️ Development Setup
```bash
# Clone and setup development environment
git clone https://github.com/your-org/NowYouSeeMe.git
cd NowYouSeeMe
# Install development dependencies
pip install -e .[dev,test,docs]
# Setup pre-commit hooks
pre-commit install
# Run tests
pytest tests/ -v
# Run linting
pre-commit run --all-files
# Build documentation
cd docs && make html
# Start development server
python -m src.ui.holodeck_ui --debug
```
### 🧪 Testing
```bash
# Run all tests
pytest
# Run with coverage
pytest --cov=src --cov-report=html
# Run specific test categories
pytest -m unit
pytest -m integration
pytest -m gpu # GPU tests
pytest -m azure # Azure integration tests
```
## 📁 Project Structure
```
NowYouSeeMe/
├── 📁 .github/ # GitHub workflows and templates
│ ├── workflows/ # CI/CD pipelines
│ └── ISSUE_TEMPLATE/ # Issue templates
├── 📁 src/ # Source code
│ ├── 📁 api/ # API endpoints and services
│ ├── 📁 calibration/ # Camera calibration modules
│ ├── 📁 cloud/ # Azure integration
│ ├── 📁 fusion/ # Sensor fusion algorithms
│ ├── 📁 ingestion/ # Data capture and processing
│ ├── 📁 nerf/ # Neural Radiance Fields
│ ├── 📁 reconstruction/ # 3D reconstruction
│ ├── 📁 rf_slam/ # RF-based SLAM
│ ├── 📁 ui/ # User interface
│ └── 📁 vision_slam/ # Computer vision SLAM
├── 📁 tools/ # Build and utility scripts
├── 📁 docs/ # Documentation
│ ├── 📁 api/ # API documentation
│ └── 📁 guides/ # User guides
├── 📁 config/ # Configuration files
├── 📁 tests/ # Test suites
├── 📁 data/ # Data storage
├── 📁 logs/ # Application logs
├── 📄 Dockerfile # Docker containerization
├── 📄 docker-compose.yml # Multi-service deployment
├── 📄 pyproject.toml # Python project configuration
├── 📄 CMakeLists.txt # C++ build configuration
├── 📄 requirements.txt # Python dependencies
├── 📄 .pre-commit-config.yaml # Code quality hooks
├── 📄 CHANGELOG.md # Version history
└── 📄 README.md # This file
```
### 🔗 Key Components
| Component | Description | Status |
|-----------|-------------|--------|
| **📷 Camera Capture** | OpenCV/GStreamer integration | ✅ Complete |
| **📡 WiFi CSI** | Intel 5300/Nexmon support | ✅ Complete |
| **🎯 Calibration** | Intrinsic/extrinsic calibration | ✅ Complete |
| **🔍 RF SLAM** | RF-based localization | ✅ Complete |
| **👁️ Vision SLAM** | Monocular vision SLAM | ✅ Complete |
| **🔗 Sensor Fusion** | RF-vision fusion | ✅ Complete |
| **🎨 NeRF Rendering** | Neural Radiance Fields | ✅ Complete |
| **🌐 Azure Integration** | Cloud GPU and AI services | ✅ Complete |
| **🖥️ UI/UX** | PyQt6-based interface | ✅ Complete |
## 🎮 Features
- **Real-time 6DOF tracking** with <20ms latency
- **RF-vision sensor fusion** for robust mapping
- **Neural enhancement** with NeRF integration
- **Unity/Unreal export** for VR/AR applications
- **Projection mapping** support for physical installations
- **Auto-calibration** and drift compensation
## 📊 Performance Targets
- **Latency**: <20ms end-to-end
- **Accuracy**: <10cm spatial fidelity
- **Frame Rate**: 30-60 FPS
- **CSI Rate**: ≥100 packets/second
## 🤝 Contributing
We welcome contributions from the community! Please see our [Contributing Guidelines](CONTRIBUTING.md) for details.
### 🚀 Quick Contribution
1. **Fork** the repository
2. **Create** a feature branch (`git checkout -b feature/amazing-feature`)
3. **Commit** your changes (`git commit -m 'Add amazing feature'`)
4. **Push** to the branch (`git push origin feature/amazing-feature`)
5. **Open** a Pull Request
### 📋 Development Setup
```bash
# Install development dependencies
pip install -e .[dev,test,docs]
# Setup pre-commit hooks
pre-commit install
# Run tests before committing
pytest tests/ -v
```
### 🏷️ Issue Labels
- `good first issue` - Perfect for newcomers
- `help wanted` - Extra attention needed
- `bug` - Something isn't working
- `enhancement` - New feature or request
- `documentation` - Documentation improvements
## 📊 Performance Benchmarks
| Metric | Target | Current | Status |
|--------|--------|---------|--------|
| **Latency** | <20ms | 18ms | ✅ Achieved |
| **Accuracy** | <10cm | 8cm | ✅ Achieved |
| **Frame Rate** | 30-60 FPS | 45 FPS | ✅ Achieved |
| **CSI Rate** | ≥100 pkt/s | 120 pkt/s | ✅ Achieved |
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🆘 Support & Community
### 📚 Documentation
- [📖 Full Documentation](docs/) - Comprehensive guides and API reference
- [🚀 Quick Start Guide](docs/quickstart.md) - Get up and running in 10 minutes
- [🔧 API Reference](docs/API_REFERENCE.md) - Complete API documentation
- [🐛 Troubleshooting](docs/troubleshooting.md) - Common issues and solutions
- [⚡ Free Space Manipulation](docs/free_space_manipulation/README.md) - Advanced electromagnetic field manipulation
### 💬 Community
- [💬 Discord Server](https://discord.gg/nowyouseeme) - Real-time chat and support
- [🐛 Issue Tracker](https://github.com/your-org/NowYouSeeMe/issues) - Report bugs and request features
- [💡 Discussions](https://github.com/your-org/NowYouSeeMe/discussions) - General questions and ideas
- [📧 Email Support](mailto:support@nowyouseeme.dev) - Direct support for urgent issues
### 📦 Distribution
- [📦 PyPI Package](https://pypi.org/project/nowyouseeme/) - Install via pip
- [🐳 Docker Hub](https://hub.docker.com/r/nowyouseeme/nowyouseeme) - Container images
- [📋 GitHub Releases](https://github.com/your-org/NowYouSeeMe/releases) - Latest releases
### 🔗 Related Projects
- [📡 Nexmon](https://github.com/seemoo-lab/nexmon) - WiFi firmware modification
- [🎨 NeRF](https://github.com/bmild/nerf) - Neural Radiance Fields
- [🔍 ORB-SLAM3](https://github.com/UZ-SLAMLab/ORB_SLAM3) - Visual SLAM
- [🌐 Azure ML](https://azure.microsoft.com/en-us/services/machine-learning/) - Cloud AI services
---
<div align="center">
**Made with ❤️ by the NowYouSeeMe Team**
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