openai / shap-e

Generate 3D objects conditioned on text or images
MIT License
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Shap-E

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

Samples

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

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