Shap-E

What is Shap-E?

Shap-E is an open-source project by OpenAI that allows you to generate 3D objects based on text prompts or images. It provides code and models for generating conditional 3D implicit functions.

How does Shap-E work?

Shap-E leverages deep learning models to create 3D shapes. It uses text or images as conditions to guide the generation process. This means you can describe the object you want, or provide a reference image, and Shap-E will attempt to create a corresponding 3D model. The core of Shap-E involves generating conditional 3D implicit functions, which are then used to render the 3D object.

Key Features of Shap-E:

• Text-to-3D Generation: Create 3D models by simply providing a text description.
• Image-to-3D Generation: Generate 3D models based on a reference image.
• Open-Source: The code and models are publicly available, allowing for community contributions and further research.

How to use Shap-E?

1. Installation: Install Shap-E using pip: pip install -e .
2. Examples: Use the provided Jupyter notebooks to get started:
   • sample_text_to_3d.ipynb: Generate a 3D model from a text prompt.
   • sample_image_to_3d.ipynb: Generate a 3D model from an image (remove background for best results).
   • encode_model.ipynb: Encode a 3D model, renders, and point clouds into a latent representation.
     • Note: Requires Blender version 3.3.1 or higher, with the BLENDER_PATH environment variable set to the Blender executable path.

Example Usage

To generate a 3D model of an avocado-like chair, you would use the sample_text_to_3d.ipynb notebook and provide the text prompt "A chair that looks like an avocado". Similarly, for creating a 3D model of a banana-like airplane, the prompt would be "An airplane that looks like a banana".

Who is Shap-E for?

Shap-E is ideal for:

• 3D Modelers and Designers: Quickly prototype 3D models based on text or image inputs.
• AI/ML Researchers: Experiment with generative 3D models and contribute to the field.
• Game Developers: Generate 3D assets for games.
• Hobbyists: Explore the world of AI-generated 3D art.

Samples from Shap-E

Shap-E can generate a wide array of 3D objects:

• A chair that looks like an avocado
• An airplane that looks like a banana
• A spaceship
• A birthday cupcake
• A chair that looks like a tree
• A green boot
• A penguin
• Ube ice cream cone
• A bowl of vegetables

Additional Resources

• GitHub Repository: https://github.com/openai/shap-e

Conclusion

Shap-E is a powerful tool for generating 3D objects from text or image prompts. Its open-source nature, combined with its ease of use and impressive results, makes it a valuable resource for researchers, designers, and anyone interested in exploring the intersection of AI and 3D modeling. The ability to quickly prototype 3D models using simple text descriptions opens up new possibilities for creative expression and design exploration. By providing both code and pre-trained models, Shap-E lowers the barrier to entry for those looking to experiment with generative 3D content creation. What is particularly exciting is the potential for further development and refinement of these techniques, leading to even more realistic and controllable 3D generation in the future.