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https://github.com/openai/shap-e
Generate 3D objects conditioned on text or images
https://github.com/openai/shap-e
Last synced: 5 days ago
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Generate 3D objects conditioned on text or images
- Host: GitHub
- URL: https://github.com/openai/shap-e
- Owner: openai
- License: mit
- Created: 2023-04-19T18:54:32.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-22T19:19:14.000Z (7 months ago)
- Last Synced: 2025-01-07T03:42:53.384Z (12 days ago)
- Language: Python
- Size: 11.4 MB
- Stars: 11,744
- Watchers: 234
- Forks: 958
- Open Issues: 96
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Shap-E
This is the official code and model release for [Shap-E: Generating Conditional 3D Implicit Functions](https://arxiv.org/abs/2305.02463).
* See [Usage](#usage) for guidance on how to use this repository.
* See [Samples](#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](samples.md).
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 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](shap_e/examples/sample_text_to_3d.ipynb) - sample a 3D model, conditioned on a text prompt.
* [sample_image_to_3d.ipynb](shap_e/examples/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](shap_e/examples/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.