openai /shap-e

Generate 3D objects conditioned on text or images

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PythonCreated 2023-04-20
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README

Shap-E

This is the official code and model release for Shap-E: Generating Conditional 3D Implicit Functions.

  See Usage for guidance on how to use this repository.
  See 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.


    
        
            
                
            
            
                
            
            
                
            
        
        
            A chair that lookslike an avocado
            An airplane that lookslike a banana
            A spaceship
        
        
            
                
            
            
                
            
            
                
            
        
        
            A birthday cupcake
            A chair that lookslike 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 - sample a 3D model, conditioned on a text prompt.
 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 - 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.

Snapshot: 2026-11-04T14:00:00Z · Data license Apache-2.0 · JSON