# Create a Python environment for SVRaster
conda create -n svraster python=3.9
conda activate svraster
 
# Install Dependencies
pip install torch==2.5.0 torchvision==0.20.0 torchaudio==2.5.0 --index-url https://download.pytorch.org/whl/cu124
conda install -y -c "nvidia/label/cuda-12.4.0" cuda-toolkit
 
git clone https://github.com/NVlabs/svraster.git
cd svraster
 
pip install -r requirements.txt
 
cd cuda
pip install -e .
 
cd ..
pip install viser
 
# Setup 
chmod +x run_colmap.sh
 
mkdir data
cd data
 
# create project under data directory
svraster/
├── run_colmap.sh
├── data/
│   └── bonsai-1/
│       ├── images/              # <-- Place input images here
│       └──                      # database.db and colmap results will be generated here
 
# Run Script
./run_colmap.sh bonsai-1 --matcher exhaustive
 
# Train Model
python train.py --eval --source_path data/bonsai-1 --model_path result/bonsai-1 --lambda_T_inside 0.01 --lambda_normal_dmean 0.001 --lambda_normal_dmed 0.001 --lambda_sparse_depth 0.01
 
# View Model
python viz.py result/bonsai-1