Installation#

Dependencies#

Before installing DiGeo, ensure you have a compatible Python version. The necessary libraries will be installed automatically via pip.

  • Python: >= 3.10

  • Libraries: Pytorch, NumPy, tqdm, SciPy, Trimesh, Robust Laplacian

Standard Installation (via pip)#

The easiest way to install the latest stable release is through PyPI. The wheels are precompiled using Pytorch 2.10 and CUDA 12.8.

pip install torch==2.10 --index-url https://download.pytorch.org/whl/cu128
pip install digeo

Important

Compatibility Note: If you are using another version of PyTorch or CUDA, you will need to build from source to ensure binary compatibility.

Platform & Hardware Support#

DiGeo utilizes custom CUDA kernels. Please note the following hardware limitations for the pip installation:

  • Linux (x86_64) and Windows (ARM64): Includes pre-compiled CUDA kernels.

  • Linux (ARM64) and macOS: pip will default to a CPU-only version. For GPU support, you will need to build the package from source.

  • Other platforms or architectures: You must build the package from source.

Install from Source#

Requirements: A working C++ compiler and the NVIDIA CUDA Toolkit.

To install version X.Y.Z of DiGeo from source:

pip install "digeo @ git+ssh://git@github.com/circle-group/DiGeo.git@vX.Y.Z" --no-build-isolation

For example, to install version 1.2.3:

pip install "digeo @ git+ssh://git@github.com/circle-group/DiGeo.git@v1.2.3" --no-build-isolation