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