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https://github.com/ReshotAI/gaussian-painters
Gaussian Painters using 3D Gaussian Splatting
https://github.com/ReshotAI/gaussian-painters
3d ai art gaussian-splatting machine-learning nerf painting python pytorch
Last synced: 9 days ago
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Gaussian Painters using 3D Gaussian Splatting
- Host: GitHub
- URL: https://github.com/ReshotAI/gaussian-painters
- Owner: ReshotAI
- License: other
- Created: 2023-09-02T16:19:15.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-26T21:16:44.000Z (3 months ago)
- Last Synced: 2024-08-27T00:14:17.516Z (3 months ago)
- Topics: 3d, ai, art, gaussian-splatting, machine-learning, nerf, painting, python, pytorch
- Language: Python
- Homepage: https://www.lingosub.com
- Size: 2.83 MB
- Stars: 366
- Watchers: 10
- Forks: 19
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Gaussian Painters
**Sponsored by 
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**and 
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This is a fork of 3D Gaussian Splatting. Refer to the original repo for instructions on how to run the code.
## How to create a Gaussian Painter dataset
After having installed the 3D Gaussian Splatting code, run the following command:
```bash
python create_dataset.py --img_path /path/to/image --output_dir /path/to/output_dir
```
You can disable the `opacity_reset_interval` argument by setting it to 30_000.
You can also set `sh_degree` to 0 to disable viewdependent effects.
This will create a dataset ready to be trained with the Gaussian Splatting code.
## Experiments
- Orthogonal images (using `create_dataset2.py`)
https://github.com/ReshotAI/gaussian-painters/assets/16474636/4799f0b6-ed29-412e-9875-4a790ecbbaaf
- Steganography (using `create_dataset3.py`)
https://github.com/ReshotAI/gaussian-painters/assets/16474636/9a391361-7d5b-40cc-ab67-97e15e53a913
- Lenticular effect (using `create_dataset5.py`)
This code requires to install [kornia](https://github.com/kornia/kornia) using `pip install kornia`
https://github.com/ReshotAI/gaussian-painters/assets/16474636/356ad0f6-3bcb-46fe-a6f8-421138e54222
## Visualize the "painting" process
Using the SIBR visualizer, you can visualize the "painting" process during the Gaussian Splatting optimization.
https://github.com/ReshotAI/gaussian-painters/assets/16474636/b29731b6-5fcc-43f5-a169-bfed2b109ce0
## How it works?
The `create_dataset` script simply creates a COLMAP output directory with a single camera pointing at a plane. 100 points are sampled from the image and used as initial point cloud for the Gaussian Splatting optimization. A second perpendicular image is also created with a black image as target.
