Installation

TorchGeo is simple and easy to install. We support installation using the pip, conda, and spack package managers.

pip

Since TorchGeo is written in pure-Python, the easiest way to install it is using pip:

$ pip install torchgeo

If you want to install a development version, you can use a VCS project URL:

$ pip install git+https://github.com/microsoft/torchgeo.git

or a local git checkout:

$ git clone https://github.com/microsoft/torchgeo.git
$ cd torchgeo
$ pip install .

By default, only required dependencies are installed. TorchGeo has a number of optional dependencies for specific datasets or development. These can be installed with a comma-separated list:

$ pip install torchgeo[datasets]
$ pip install torchgeo[style,tests]
$ pip install torchgeo[all]

See the pyproject.toml for a complete list of options. See the pip documentation for more details.

conda

First, you’ll want to configure conda to only use the conda-forge channel:

$ conda config --add channels conda-forge
$ conda config --set channel_priority strict

Now, you can install the latest stable release using:

$ conda install torchgeo

Note

The installation of TorchGeo in this manner is not supported on Windows since PyTorch from the conda-forge channel currently does not support Windows. Users are recommended to use pip instead.

Conda does not support development versions or optional dependencies. If you install from conda-forge, only stable releases and required dependencies will be installed. Development versions or optional dependencies can be installed afterwards using pip.

See the conda-forge documentation for more details.

spack

If you are working in an HPC environment or want to install your software from source, the easiest way is with spack:

$ spack install py-torchgeo
$ spack load py-torchgeo

Our spack package has a main version that can be used to install the latest commit:

$ spack install py-torchgeo@main
$ spack load py-torchgeo

Optional dependencies can be installed by enabling build variants:

$ spack install py-torchgeo+datasets
$ spack install py-torchgeo+style+tests

Run spack info py-torchgeo for a complete list of variants. See the spack documentation for more details.