Toolkit: Benchmarking 3D and 4D World Models in the Real World 🌍

Table of Contents

• Overview
• Features
• Installation
• Usage
• Topics
• Contributing
• License
• Contact

Overview

Welcome to the Toolkit repository! This project focuses on benchmarking 3D and 4D world models in real-world scenarios. Our goal is to provide a comprehensive set of tools that enable researchers and developers to evaluate and improve their spatial intelligence models.

To get started, visit our Releases page for the latest updates and downloads.

Features

• 3D Generation: Create realistic 3D models for various applications.
• 4D Generation: Incorporate the time dimension into your models for dynamic simulations.
• AIGC Support: Leverage Artificial Intelligence for Generative Content.
• Lidar Generation: Utilize Lidar data for enhanced spatial awareness.
• Occupancy Generation: Model spaces with occupancy data for better planning.
• Spatial Intelligence: Improve the ability of models to understand and interact with their environments.
• Video Generation: Generate videos that demonstrate the capabilities of your models.

Installation

To install the Toolkit, follow these steps:

1. Download the latest release from our Releases page.
2. Extract the downloaded file.
3. Execute the installation script.

cd toolkit
./install.sh

Usage

After installation, you can start using the Toolkit. Here’s a basic example of how to generate a 3D model:

from toolkit import ModelGenerator

model = ModelGenerator()
model.create_3d_model(parameters)
model.save("output_model.obj")

For 4D models, the usage is similar:

from toolkit import ModelGenerator

model = ModelGenerator()
model.create_4d_model(parameters)
model.save("output_model_4d.obj")

Explore the documentation for more advanced usage and features.

Topics

This repository covers a wide range of topics:

• 3D Generation: Techniques and algorithms for creating 3D models.
• 4D Generation: Expanding 3D models to include time-based elements.
• AIGC: Tools and frameworks for AI-driven content generation.
• AIGC3D: Specialized tools for 3D content generation using AI.
• Embodied AI: Understanding AI in physical spaces.
• Lidar Generation: Methods for creating and utilizing Lidar data.
• Occupancy Generation: Techniques for modeling occupied spaces.
• Spatial Intelligence: Enhancing models to understand their environment.
• Video Generation: Tools for generating videos that showcase model capabilities.
• World Models: Frameworks for creating comprehensive models of real-world environments.

Contributing

We welcome contributions! If you would like to help improve the Toolkit, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push to your branch.
5. Open a pull request.

Please ensure your code adheres to our coding standards and includes tests where applicable.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

For questions or suggestions, feel free to reach out to us through the issues section or directly via email.

For updates and the latest releases, check our Releases page.

---

This README provides a detailed overview of the Toolkit project, its features, and how to get started. For any further information, please explore the repository and its documentation.