This is the official code and model release for Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

Install with pip install -e ..

To get started with examples, see the following notebooks:

• image2pointcloud.ipynb - sample a point cloud, conditioned on some example synthetic view images.
• text2pointcloud.ipynb - use our small, worse quality pure text-to-3D model to produce 3D point clouds directly from text descriptions. This model's capabilities are limited, but it does understand some simple categories and colors.
• pointcloud2mesh.ipynb - try our SDF regression model for producing meshes from point clouds.

For our P-FID and P-IS evaluation scripts, see:

• evaluate_pfid.py
• evaluate_pis.py

For our Blender rendering code, see blender_script.py

You can download the seed images and point clouds corresponding to the paper banner images here.

You can download the seed images used for COCO CLIP R-Precision evaluations here.