/shap-e

Generate 3D objects conditioned on text or images

Primary LanguagePythonMIT LicenseMIT

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 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 - 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.