Awesome

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.

<table> <tbody> <tr> <td align="center"> <img src="samples/a_chair_that_looks_like_an_avocado/2.gif" alt="A chair that looks like an avocado"> </td> <td align="center"> <img src="samples/an_airplane_that_looks_like_a_banana/3.gif" alt="An airplane that looks like a banana"> </td align="center"> <td align="center"> <img src="samples/a_spaceship/0.gif" alt="A spaceship"> </td> </tr> <tr> <td align="center">A chair that looks<br>like an avocado</td> <td align="center">An airplane that looks<br>like a banana</td> <td align="center">A spaceship</td> </tr> <tr> <td align="center"> <img src="samples/a_birthday_cupcake/3.gif" alt="A birthday cupcake"> </td> <td align="center"> <img src="samples/a_chair_that_looks_like_a_tree/2.gif" alt="A chair that looks like a tree"> </td> <td align="center"> <img src="samples/a_green_boot/3.gif" alt="A green boot"> </td> </tr> <tr> <td align="center">A birthday cupcake</td> <td align="center">A chair that looks<br>like a tree</td> <td align="center">A green boot</td> </tr> <tr> <td align="center"> <img src="samples/a_penguin/1.gif" alt="A penguin"> </td> <td align="center"> <img src="samples/ube_ice_cream_cone/3.gif" alt="Ube ice cream cone"> </td> <td align="center"> <img src="samples/a_bowl_of_vegetables/2.gif" alt="A bowl of vegetables"> </td> </tr> <tr> <td align="center">A penguin</td> <td align="center">Ube ice cream cone</td> <td align="center">A bowl of vegetables</td> </tr> </tbody> <table>

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.