https://colab.research.google.com/drive/1CGJo16v_LburYrgcj9JCsC4hkUiz29Jl?usp=sharing#scrollTo=RNpaNpz84lxU
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:
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.