net.viz

Modern neural network visualization for the AI era. Explore, analyze, and understand your ONNX models with an intuitive graph-based interface.

Features • Installation • Usage • Development • Contribute

✨ Features

• 🎯 Interactive Graph Visualization

  • Intuitive node-based visualization
  • Pan, zoom, and interactive exploration
  • Smart layout algorithms for complex models
  • Custom node grouping and collapsing

• 🔍 Model Analysis

  • Detailed layer inspection
  • Parameter visualization
  • Memory usage analysis (upcoming)
  • Performance profiling (upcoming)

• 🎨 Modern UI/UX

  • Dark/Light theme support
  • Responsive design
  • Command palette (⌘K)
  • Keyboard shortcuts

• 🛠 Developer Tools

  • Model comparison
  • Export capabilities
  • Custom scripting support
  • Extensive API

🚀 Quick Start

Prerequisites

• Python 3.8+
• Node.js 16+
• npm/yarn

Backend Setup

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
cd backend
pip install -r requirements.txt

# Start the server
uvicorn app.main:app --reload

Frontend Setup

# Install dependencies
cd frontend
npm install

# Start development server
npm start

The application will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API Documentation: http://localhost:8000/docs

🏗 Project Structure

onnx-visualizer/
├── backend/                 # FastAPI backend
│   ├── app/
│   │   ├── api/            # API routes
│   │   ├── core/           # Business logic
│   │   ├── models/         # Data models
│   │   └── utils/          # Utilities
│   └── requirements.txt    # Python dependencies
│
├── frontend/               # React + TypeScript
│   ├── src/
│   │   ├── components/     # React components
│   │   ├── services/       # API services
│   │   ├── types/         # TypeScript types
│   │   └── utils/         # Utilities
│   └── package.json       # Frontend dependencies

🧪 Development

Running Tests

# Backend tests
cd backend
pytest

# Frontend tests
cd frontend
npm test

Code Style

• Backend: Black + isort
• Frontend: ESLint + Prettier

📚 Documentation

• API Documentation
• Architecture Overview
• Contributing Guide

🤝 Contributing

Contributions are welcome! Please read our Contributing Guide for details on our code of conduct and the process for submitting pull requests.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• ONNX for the model format
• React Flow for graph visualization
• shadcn/ui for UI components
• All our contributors

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