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Docs: reorganize tutorial hierarchy (#2439)
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* Docs: redesign tutorial organization

* Typo fixes

* Try .ipynb links

* Add input range

* ruff

* more fix

* Fix filename
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adamjstewart authored Dec 8, 2024
1 parent e743e6d commit ac0723e
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26 changes: 9 additions & 17 deletions docs/index.rst
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Expand Up @@ -12,6 +12,15 @@ torchgeo
user/glossary
user/alternatives

.. toctree::
:maxdepth: 2
:caption: Tutorials

tutorials/getting_started
tutorials/basic_usage
tutorials/case_studies
tutorials/customization

.. toctree::
:maxdepth: 2
:caption: Package Reference
Expand All @@ -24,23 +33,6 @@ torchgeo
api/trainers
api/transforms

.. toctree::
:maxdepth: 1
:caption: Tutorials

tutorials/getting_started
tutorials/pytorch
tutorials/geospatial
tutorials/torchgeo
tutorials/contribute_non_geo_dataset
tutorials/custom_raster_dataset
tutorials/contribute_datamodule
tutorials/transforms
tutorials/indices
tutorials/trainers
tutorials/pretrained_weights
tutorials/earth_surface_water

.. toctree::
:maxdepth: 1
:caption: PyTorch Libraries
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18 changes: 18 additions & 0 deletions docs/tutorials/basic_usage.rst
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@@ -0,0 +1,18 @@
Basic Usage
===========

The following tutorials introduce the basic concepts and components of TorchGeo:

* `Transforms <transforms.ipynb>`_: Preprocessing and data augmentation transforms for geospatial data
* `Indices <indices.ipynb>`_: Spectral indices
* `Pretrained Weights <pretrained_weights.ipynb>`_: Models and pretrained weights
* `Lightning Trainers <trainers.ipynb>`_: PyTorch Lightning data modules and trainers

.. toctree::
:hidden:
:maxdepth: 1

transforms
indices
pretrained_weights
trainers
14 changes: 14 additions & 0 deletions docs/tutorials/case_studies.rst
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Case Studies
============

The following case studies present end-to-end workflows for common use cases of geospatial machine learning:

* `Earth Surface Water <earth_surface_water.ipynb>`_: A workflow for mapping surface water, including lakes and rivers

Do you have a use case that is missing from this list? Please open a pull request to add tutorials for your own use cases.

.. toctree::
:hidden:
:maxdepth: 1

earth_surface_water
6 changes: 5 additions & 1 deletion docs/tutorials/contribute_non_geo_dataset.ipynb
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Expand Up @@ -259,7 +259,11 @@
"# Create dummy data for all splits and filenames\n",
"for split in splits:\n",
" for filename in image_file_names:\n",
" create_input_image(split, filename)\n",
" create_input_image(\n",
" os.path.join(root_dir, 'image', split, filename),\n",
" (IMG_SIZE, IMG_SIZE),\n",
" range(2**16),\n",
" )\n",
" create_target_images(split, filename.replace('_', '_target_'))\n",
"\n",
"# Zip directory\n",
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20 changes: 20 additions & 0 deletions docs/tutorials/customization.rst
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Customization
=============

Is TorchGeo missing a dataset or model you need? Would you like to modify the default augmentations for a data module or extend a builtin trainer?

The following tutorials will teach you how to customize TorchGeo to meet your needs:

* `Custom Non-Geospatial Datasets <contribute_non_geo_dataset.ipynb>`_: How to create and contribute a new NonGeoDataset
* `Custom Raster Datasets <custom_raster_dataset.ipynb>`_: How to create a new RasterDataset
* `Custom Data Module <contribute_datamodule.ipynb>`_: How to create and contribute a new DataModule

TorchGeo is a community-driven open source library. If there is a feature missing that you would like to add, please open a pull request to add it. See the ref:`contributing` guidelines to get started.

.. toctree::
:hidden:
:maxdepth: 1

contribute_non_geo_dataset
custom_raster_dataset
contribute_datamodule
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