OpenAI Text To 3D Models | 2023 
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.
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| A chair that looks | ||
| like an avocado | An airplane that looks | |
| like a banana | A spaceship | |
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| A birthday cupcake | A chair that looks | |
| like a tree | A green boot | |
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| 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_PATHto the path of the Blender executable.
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