зеркало из https://github.com/microsoft/torchgeo.git
104 строки
3.1 KiB
ReStructuredText
104 строки
3.1 KiB
ReStructuredText
Installation
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============
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TorchGeo is simple and easy to install. We support installation using the `pip <https://pip.pypa.io/>`_, `conda <https://docs.conda.io/>`_, and `spack <https://spack.io/>`_ package managers.
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pip
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---
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Since TorchGeo is written in pure-Python, the easiest way to install it is using pip:
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.. code-block:: console
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$ pip install torchgeo
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If you want to install a development version, you can use a VCS project URL:
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.. code-block:: console
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$ pip install git+https://github.com/microsoft/torchgeo.git
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or a local git checkout:
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.. code-block:: console
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$ git clone https://github.com/microsoft/torchgeo.git
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$ cd torchgeo
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$ pip install .
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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:
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.. code-block:: console
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$ pip install torchgeo[datasets]
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$ pip install torchgeo[style,tests]
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See the ``setup.cfg`` for a complete list of options. See the `pip documentation <https://pip.pypa.io/>`_ for more details.
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conda
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-----
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If you need to install non-Python dependencies like PyTorch, it's better to use a package manager like conda. First, you'll want to configure conda to only use the conda-forge channel:
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.. code-block:: console
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$ conda config --add channels conda-forge
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$ conda config --set channel_priority strict
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Now, you can install the latest stable release using:
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.. code-block:: console
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$ conda install torchgeo
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Conda does not directly support installing development versions, but you can use conda to install our dependencies, then use pip to install TorchGeo itself.
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.. code-block:: console
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$ git clone https://github.com/microsoft/torchgeo.git
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$ cd torchgeo
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$ conda env create --file environment.yml
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$ conda activate torchgeo
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$ pip install .
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.. note:: The above method will not work on Windows. Windows users are recommended to create a conda environment and install dependencies via pip.
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Conda does not directly support optional dependencies. If you install from conda-forge, only required dependencies will be installed by default. Optional dependencies can be installed afterwards using pip. If you install using the ``environment.yml`` file, all optional dependencies are installed by default.
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See the `conda-forge documentation <https://conda-forge.org/>`_ for more details.
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spack
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-----
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If you are working in an HPC environment or want to install your software from source, the easiest way is with spack:
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.. code-block:: console
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$ spack install py-torchgeo
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$ spack load py-torchgeo
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Our Spack package has a ``main`` version that can be used to install the latest commit:
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.. code-block:: console
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$ spack install py-torchgeo@main
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$ spack load py-torchgeo
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Optional dependencies can be installed by enabling build variants:
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.. code-block:: console
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$ spack install py-torchgeo+datasets
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$ spack install py-torchgeo+style+tests
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Run ``spack info py-torchgeo`` for a complete list of variants.
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See the `spack documentation <https://spack.readthedocs.io/>`_ for more details.
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