More-detailed dataset docs

docs/conf.py

@@ -33,7 +33,12 @@ release = torchgeo.__version__
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
-extensions = ["sphinx.ext.autodoc", "sphinx.ext.intersphinx", "sphinx.ext.napoleon"]
+extensions = [
+    "sphinx.ext.autodoc",
+    "sphinx.ext.autosectionlabel",
+    "sphinx.ext.intersphinx",
+    "sphinx.ext.napoleon",
+]
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.

docs/datasets.rst

@@ -1,4 +1,73 @@
 torchgeo.datasets
 =================
 
-.. automodule:: torchgeo.datasets
+.. module:: torchgeo.datasets
+
+In :mod:`torchgeo`, we define two types of datasets: :ref:`Geospatial Datasets` and :ref:`Non-geospatial Datasets`. These abstract base classes are documented in more detail in :ref:`Base Classes`.
+
+Geospatial Datasets
+-------------------
+
+:class:`GeoDataset` is designed for datasets that contain geospatial information, like latitude, longitude, coordinate system, and projection. Datasets containing this kind of information can be combined using :class:`ZipDataset`.
+
+Smallholder Cashew Plantations in Benin
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: BeninSmallHolderCashews
+
+CV4A Kenya Crop Type Competition
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: CV4AKenyaCropType
+
+SEN12MS
+^^^^^^^
+
+.. autoclass:: SEN12MS
+
+Non-geospatial Datasets
+-----------------------
+
+:class:`VisionDataset` is designed for datasets that lack geospatial information. These datasets can still be combined using :class:`ConcatDataset <torch.utils.data.ConcatDataset>`.
+
+Cars Overhead With Context (COWC)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: COWC
+.. autoclass:: COWCCounting
+.. autoclass:: COWCDetection
+
+Tropical Cyclone Wind Estimation Competition
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: TropicalCycloneWindEstimation
+
+LandCover.ai (Land Cover from Aerial Imagery)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autoclass:: LandCoverAI
+
+NWPU VHR-10
+^^^^^^^^^^^
+
+.. autoclass:: VHR10
+
+Base Classes
+------------
+
+If you want to write your own custom dataset, you can extend one of these abstract base classes.
+
+GeoDataset
+^^^^^^^^^^
+
+.. autoclass:: GeoDataset
+
+VisionDataset
+^^^^^^^^^^^^^
+
+.. autoclass:: VisionDataset
+
+ZipDataset
+^^^^^^^^^^
+
+.. autoclass:: ZipDataset