
gaussian-painters
Gaussian Painters using 3D Gaussian Splatting
Stars: 358

This tool is a fork of the 3D Gaussian Splatting code. It allows users to create a dataset ready to be trained with the Gaussian Splatting code. The dataset can be used for various experiments, such as creating orthogonal images, steganography, and lenticular effects. The tool also includes a visualizer that allows users to visualize the "painting" process during the Gaussian Splatting optimization.
README:
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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.
After having installed the 3D Gaussian Splatting code, run the following command:
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.
- 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 using pip install kornia
https://github.com/ReshotAI/gaussian-painters/assets/16474636/356ad0f6-3bcb-46fe-a6f8-421138e54222
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
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.
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