Clone the repository locally
git clone https://github.com/lkeab/gaussian-grouping.git
cd gaussian-grouping
Our default, provided install method is based on Conda package and environment management:
conda create -n gaussian_grouping python=3.8 -y
conda activate gaussian_grouping
conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch
pip install plyfile==0.8.1
pip install tqdm scipy wandb opencv-python scikit-learn lpips
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn(Optional) If you want to prepare masks on your own dataset, you will also need to prepare DEVA environment.
cd Tracking-Anything-with-DEVA
pip install -e .
bash scripts/download_models.sh # Download the pretrained models
git clone https://github.com/hkchengrex/Grounded-Segment-Anything.git
cd Grounded-Segment-Anything
export AM_I_DOCKER=False
export BUILD_WITH_CUDA=True
python -m pip install -e segment_anything
python -m pip install -e GroundingDINO
cd ../..(Optional) If you want to inpaint on your own dataset, you will also need to prepare LaMa environment.
cd lama
pip install -r requirements.txt
cd ..