Installation

This guide provides three methods to install PyTorch-SVGRender.

Environment Setup

Choose one of the following installation methods that best suits your needs:

Method 1: Standard Installation

For a straightforward installation, run these commands in the project’s root directory:

chmod +x script/install.sh
bash script/install.sh

Method 2: Docker Installation

For a containerized environment, use Docker:

chmod +x script/run_docker.sh
sudo bash script/run_docker.sh

Method 3: Python Installation

For a manual Python setup:

# Create and activate conda environment
conda create -n svgrender python=3.10
conda activate svgrender

# Install the package
python setup.py install

System Requirements

  • Python 3.10 or higher

  • CUDA-capable GPU (optional, for accelerated rendering)

  • Docker (only for Method 2)

  • Git

Troubleshooting

If you encounter any issues during installation:

  1. Ensure all prerequisites are installed

  2. Check your Python version

  3. Verify CUDA installation (if using GPU)

  4. Ensure you have sufficient disk space

For detailed error messages and solutions, please refer to our GitHub Issues.

Additional Notes

  • The Docker installation method is recommended for production environments

  • For development purposes, the Python installation method (Method 3) is preferred

  • Standard installation (Method 1) is best for quick testing and evaluation

Need Help?

If you need assistance:

Note

Make sure to activate the conda environment before running any commands.

Warning

GPU support requires appropriate NVIDIA drivers and CUDA toolkit installation.