Getting Started With 3D Gaussian Splatting for Windows
References
https://www.youtube.com/watch?v=UXtuigy_wYc
https://github.com/jonstephens85/gaussian-splatting-Windows
1. Install Dependencies/Requirements
- CUDA 11.8
- Visual Studio 2019
- 3DGS has an issue with Visual Studio 2022 !
- Install VS 2019
- https://learn.microsoft.com/en-us/visualstudio/releases/2019/history#release-dates-and-build-numbers
- COLMAP
- ImageMagik(not necessary. It's to convert a video to images)
- FFMEG(not necessary. It's to convert a video to images)
2. Run anaconda3 prompt
3. Cloning the repository
# SSH
git clone git@github.com:graphdeco-inria/gaussian-splatting.git --recursive
# HTTPS
git clone <https://github.com/graphdeco-inria/gaussian-splatting> --recursive
4. Setting up the optimizer
1. go into the cloned repo
cd gaussian-splatting
2. type the followings
SET DISTUTILS_USE_SDK=1 # Windows only
conda env create --file environment.yml
conda activate gaussian_splatting
if failed to create conda env, follow the steps below "Conda env create error"
5. Preparing images for the optimizer
Convert a video to images(FFMEPG installed)
cd (root폴더)\data\tube\input
ffmpeg -i (root폴더)\data\tube\tube_input.mp4 -qscale:v 1 -qmin 1 -vf fps=10 %04d.jpg
- Create data folder in the repo.
- Create input folder and put images into it.(playroom/input, in my case)
- Run the following command at gaussian-splatting
(gaussian_splatting) C:\\Users\\ghdth\\gaussian-splatting> python convert.py -s data/playroom
Results are like below
6. Run the optimizer
python train.py -s <path to COLMAP or NeRF Synthetic dataset>
For example,
python train.py -s data/playroom
Errors
Conda env create error
...
× Encountered error while trying to install package.
╰─> simple_knn
...
Follow the steps below
# init conda environment
conda create --name gaussian_splatting -y python=3.8
conda activate gaussian_splatting
pip install --upgrade pip
# or it would be like this C:\Users\ghdth\miniconda3\envs\gaussian_splatting\python.exe -m pip install --upgrade pip
# install PyTorch and cuda-toolkit
pip install torch==2.1.2+cu118 torchvision==0.16.2+cu118 --extra-index-url <https://download.pytorch.org/whl/cu118>
conda install -c "nvidia/label/cuda-11.8.0" cuda-toolkit
conda install -c conda-forge vs2019_win-64
# clone the source
git clone <https://github.com/graphdeco-inria/gaussian-splatting> --recursive
cd gaussian-splatting
# install dependencies
pip install plyfile tqdm ninja
# install submodules
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
No module named ‘cv2’
pip install opencv-python
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