UniqAI/gaussian-splatting
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@ -97,7 +97,7 @@ conda activate <Drive>/<env_path>/gaussian_splatting
#### Colab #### Colab
User [camenduru](https://github.com/camenduru) was kind enough to provide a Colab template that uses pre-built wheels for a quick and easy access to the method. Please check it out [here](https://github.com/camenduru/gaussian-splatting-colab). User [camenduru](https://github.com/camenduru) was kind enough to provide a Colab template that uses pre-built wheels for quick and easy access to the method. Please check it out [here](https://github.com/camenduru/gaussian-splatting-colab).
#### Modifications #### Modifications
@ -125,7 +125,7 @@ python train.py -s <path to COLMAP or NeRF Synthetic dataset>
#### --resolution / -r #### --resolution / -r
Specifies resolution of the loaded images before training. If provided ```1, 2, 4``` or ```8```, uses original, 1/2, 1/4 or 1/8 resolution, respectively. For all other values, rescales the width to the given number while maintaining image aspect. **If not set and input image width exceeds 1.6K pixels, inputs are automatically rescaled to this target.** Specifies resolution of the loaded images before training. If provided ```1, 2, 4``` or ```8```, uses original, 1/2, 1/4 or 1/8 resolution, respectively. For all other values, rescales the width to the given number while maintaining image aspect. **If not set and input image width exceeds 1.6K pixels, inputs are automatically rescaled to this target.**
#### --data_device #### --data_device
Specifies where to put the source image data, ```cuda``` by default, recommended to use ```cpu``` if training on large/high-resolution dataset, will reduce VRAM consumption, but slightly slow down training. Specifies where to put the source image data, ```cuda``` by default, recommended to use ```cpu``` if training on large/high-resolution dataset, will reduce VRAM consumption, but slightly slow down training. Thanks to [HrsPythonix](https://github.com/HrsPythonix).
#### --white_background / -w #### --white_background / -w
Add this flag to use white background instead of black (default), e.g., for evaluation of NeRF Synthetic dataset. Add this flag to use white background instead of black (default), e.g., for evaluation of NeRF Synthetic dataset.
#### --sh_degree #### --sh_degree