https://github.com/openai/shap-e

Generate 3D objects conditioned on text or images
https://github.com/openai/shap-e

Last synced: about 1 hour ago
JSON representation

Generate 3D objects conditioned on text or images

• Host: GitHub
• URL: https://github.com/openai/shap-e
• Owner: openai
• License: mit
• Created: 2023-04-19T18:54:32.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-06-22T19:19:14.000Z (7 months ago)
• Last Synced: 2025-01-28T06:03:46.548Z (about 5 hours ago)
• Language: Python
• Size: 11.4 MB
• Stars: 11,768
• Watchers: 234
• Forks: 966
• Open Issues: 97
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome - openai/shap-e - Generate 3D objects conditioned on text or images (Python)
• ai-game-devtools - Shap-E
• AiTreasureBox - openai/shap-e - 01-19_11761_1](https://img.shields.io/github/stars/openai/shap-e.svg) |Generate 3D objects conditioned on text or images| (Repos)

README

        
# Shap-E

This is the official code and model release for [Shap-E: Generating Conditional 3D Implicit Functions](https://arxiv.org/abs/2305.02463).

 * See [Usage](#usage) for guidance on how to use this repository.

 * See [Samples](#samples) for examples of what our text-conditional model can generate.

# Samples

Here are some highlighted samples from our text-conditional model. For random samples on selected prompts, see [samples.md](samples.md).

    

        

            

                

            

            

                

            

            

                

            

        

        

            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

        

    

# Usage

Install with `pip install -e .`.

To get started with examples, see the following notebooks:

* [sample_text_to_3d.ipynb](shap_e/examples/sample_text_to_3d.ipynb) - sample a 3D model, conditioned on a text prompt.

* [sample_image_to_3d.ipynb](shap_e/examples/sample_image_to_3d.ipynb) - sample a 3D model, conditioned on a synthetic view image. To get the best result, you should remove background from the input image.

* [encode_model.ipynb](shap_e/examples/encode_model.ipynb) - loads a 3D model or a trimesh, creates a batch of multiview renders and a point cloud, encodes them into a latent, and renders it back. For this to work, install Blender version 3.3.1 or higher, and set the environment variable `BLENDER_PATH` to the path of the Blender executable.