From c746cac1f7c7715ee2b82b046ad019a6da0cb7b4 Mon Sep 17 00:00:00 2001
From: Nils Lehmann <35272119+nilsleh@users.noreply.github.com>
Date: Sun, 27 Oct 2024 10:19:36 +0100
Subject: [PATCH] Add SpaceNet6 datamodule (#2367)

* spacenet 6 datamodule

* datamodule base class

* mypy

* fix tests

* fix docs

* fix tests again

* uncomment test

* magic comma

* review

* class -> instance

---------

Co-authored-by: Adam J. Stewart <ajstewart426@gmail.com>
---
 docs/api/datamodules.rst                      |   2 +
 tests/conf/spacenet1.yaml                     |   2 +-
 tests/conf/spacenet6.yaml                     |  19 ++
 ...SN1_buildings_train_AOI_1_Rio_3band.tar.gz | Bin 653 -> 0 bytes
 ...SN1_buildings_train_AOI_1_Rio_8band.tar.gz | Bin 643 -> 0 bytes
 ...s_train_AOI_1_Rio_geojson_buildings.tar.gz | Bin 525 -> 0 bytes
 tests/data/spacenet/data.py                   |  92 ----------
 .../test}/3band/3band_AOI_1_RIO_img1.tif      | Bin
 .../test}/3band/3band_AOI_1_RIO_img2.tif      | Bin
 .../test}/3band/3band_AOI_1_RIO_img3.tif      | Bin
 .../test}/3band/3band_AOI_1_RIO_img4.tif      | Bin
 .../test/8band/8band_AOI_1_RIO_img1.tif}      | Bin
 .../test/8band/8band_AOI_1_RIO_img2.tif}      | Bin
 .../test/8band/8band_AOI_1_RIO_img3.tif}      | Bin
 .../test/8band/8band_AOI_1_RIO_img4.tif}      | Bin
 .../SN1_buildings_test_AOI_1_Rio_3band.tar.gz | Bin 0 -> 615 bytes
 .../SN1_buildings_test_AOI_1_Rio_8band.tar.gz | Bin 0 -> 615 bytes
 .../train/3band/3band_AOI_1_RIO_img1.tif      | Bin 0 -> 390 bytes
 .../train/3band/3band_AOI_1_RIO_img2.tif      | Bin 0 -> 390 bytes
 .../train/3band/3band_AOI_1_RIO_img3.tif      | Bin 0 -> 390 bytes
 .../train/3band/3band_AOI_1_RIO_img4.tif      | Bin 0 -> 390 bytes
 .../train/8band/8band_AOI_1_RIO_img1.tif      | Bin 0 -> 456 bytes
 .../train/8band/8band_AOI_1_RIO_img2.tif      | Bin 0 -> 456 bytes
 .../train/8band/8band_AOI_1_RIO_img3.tif      | Bin 0 -> 456 bytes
 .../train/8band/8band_AOI_1_RIO_img4.tif      | Bin 0 -> 456 bytes
 ...SN1_buildings_train_AOI_1_Rio_3band.tar.gz | Bin 0 -> 620 bytes
 ...SN1_buildings_train_AOI_1_Rio_8band.tar.gz | Bin 0 -> 620 bytes
 ...s_train_AOI_1_Rio_geojson_buildings.tar.gz | Bin 0 -> 515 bytes
 .../train/geojson/Geo_AOI_1_RIO_img1.geojson  |   0
 .../train/geojson/Geo_AOI_1_RIO_img2.geojson  |   0
 .../train/geojson/Geo_AOI_1_RIO_img3.geojson  |   0
 .../train/geojson/Geo_AOI_1_RIO_img4.geojson  |   1 +
 tests/data/spacenet/spacenet1/data.py         | 161 +++++++++++++++++
 ...SN6_buildings_AOI_11_Rotterdam_test.tar.gz | Bin 0 -> 714 bytes
 ...y_20190804111224_20190804111453_tile_1.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_2.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_3.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_4.tif | Bin 0 -> 410 bytes
 ...N6_buildings_AOI_11_Rotterdam_train.tar.gz | Bin 0 -> 1665 bytes
 ...N_20190804111224_20190804111453_tile_1.tif | Bin 0 -> 370 bytes
 ...N_20190804111224_20190804111453_tile_2.tif | Bin 0 -> 370 bytes
 ...N_20190804111224_20190804111453_tile_3.tif | Bin 0 -> 370 bytes
 ...N_20190804111224_20190804111453_tile_4.tif | Bin 0 -> 370 bytes
 ...B_20190804111224_20190804111453_tile_1.tif | Bin 0 -> 390 bytes
 ...B_20190804111224_20190804111453_tile_2.tif | Bin 0 -> 390 bytes
 ...B_20190804111224_20190804111453_tile_3.tif | Bin 0 -> 390 bytes
 ...B_20190804111224_20190804111453_tile_4.tif | Bin 0 -> 390 bytes
 ...R_20190804111224_20190804111453_tile_1.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_2.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_3.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_4.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_1.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_2.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_3.tif | Bin 0 -> 410 bytes
 ...R_20190804111224_20190804111453_tile_4.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_1.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_2.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_3.tif | Bin 0 -> 410 bytes
 ...y_20190804111224_20190804111453_tile_4.tif | Bin 0 -> 410 bytes
 ...190804111224_20190804111453_tile_1.geojson |   0
 ...190804111224_20190804111453_tile_2.geojson |   1 +
 ...190804111224_20190804111453_tile_3.geojson |   0
 ...190804111224_20190804111453_tile_4.geojson |   1 +
 tests/data/spacenet/spacenet6/data.py         | 171 ++++++++++++++++++
 tests/datasets/test_spacenet.py               |  64 ++++---
 tests/trainers/test_segmentation.py           |   1 +
 torchgeo/datamodules/__init__.py              |   4 +-
 torchgeo/datamodules/spacenet.py              | 155 ++++++++++++----
 68 files changed, 521 insertions(+), 153 deletions(-)
 create mode 100644 tests/conf/spacenet6.yaml
 delete mode 100644 tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_3band.tar.gz
 delete mode 100644 tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_8band.tar.gz
 delete mode 100644 tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_geojson_buildings.tar.gz
 delete mode 100755 tests/data/spacenet/data.py
 rename tests/data/spacenet/{SN1_buildings/train => spacenet1/SN1_buildings/test}/3band/3band_AOI_1_RIO_img1.tif (100%)
 rename tests/data/spacenet/{SN1_buildings/train => spacenet1/SN1_buildings/test}/3band/3band_AOI_1_RIO_img2.tif (100%)
 rename tests/data/spacenet/{SN1_buildings/train => spacenet1/SN1_buildings/test}/3band/3band_AOI_1_RIO_img3.tif (100%)
 rename tests/data/spacenet/{SN1_buildings/train => spacenet1/SN1_buildings/test}/3band/3band_AOI_1_RIO_img4.tif (100%)
 rename tests/data/spacenet/{SN1_buildings/train/8band/3band_AOI_1_RIO_img1.tif => spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img1.tif} (100%)
 rename tests/data/spacenet/{SN1_buildings/train/8band/3band_AOI_1_RIO_img2.tif => spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img2.tif} (100%)
 rename tests/data/spacenet/{SN1_buildings/train/8band/3band_AOI_1_RIO_img3.tif => spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img3.tif} (100%)
 rename tests/data/spacenet/{SN1_buildings/train/8band/3band_AOI_1_RIO_img4.tif => spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img4.tif} (100%)
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/test/SN1_buildings_test_AOI_1_Rio_3band.tar.gz
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/test/SN1_buildings_test_AOI_1_Rio_8band.tar.gz
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/3band/3band_AOI_1_RIO_img1.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/3band/3band_AOI_1_RIO_img2.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/3band/3band_AOI_1_RIO_img3.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/3band/3band_AOI_1_RIO_img4.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/8band/8band_AOI_1_RIO_img1.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/8band/8band_AOI_1_RIO_img2.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/8band/8band_AOI_1_RIO_img3.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/8band/8band_AOI_1_RIO_img4.tif
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_3band.tar.gz
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_8band.tar.gz
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_geojson_buildings.tar.gz
 rename tests/data/spacenet/{ => spacenet1}/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img1.geojson (100%)
 rename tests/data/spacenet/{ => spacenet1}/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img2.geojson (100%)
 rename tests/data/spacenet/{ => spacenet1}/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img3.geojson (100%)
 create mode 100644 tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img4.geojson
 create mode 100755 tests/data/spacenet/spacenet1/data.py
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/test/SN6_buildings_AOI_11_Rotterdam_test.tar.gz
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/test/test_public/AOI_11_Rotterdam/SAR-Intensity/SN6_Test_Public_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_1.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/test/test_public/AOI_11_Rotterdam/SAR-Intensity/SN6_Test_Public_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_2.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/test/test_public/AOI_11_Rotterdam/SAR-Intensity/SN6_Test_Public_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_3.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/test/test_public/AOI_11_Rotterdam/SAR-Intensity/SN6_Test_Public_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_4.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/SN6_buildings_AOI_11_Rotterdam_train.tar.gz
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PAN/SN6_Train_AOI_11_Rotterdam_PAN_20190804111224_20190804111453_tile_1.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PAN/SN6_Train_AOI_11_Rotterdam_PAN_20190804111224_20190804111453_tile_2.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PAN/SN6_Train_AOI_11_Rotterdam_PAN_20190804111224_20190804111453_tile_3.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PAN/SN6_Train_AOI_11_Rotterdam_PAN_20190804111224_20190804111453_tile_4.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGB/SN6_Train_AOI_11_Rotterdam_PS-RGB_20190804111224_20190804111453_tile_1.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGB/SN6_Train_AOI_11_Rotterdam_PS-RGB_20190804111224_20190804111453_tile_2.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGB/SN6_Train_AOI_11_Rotterdam_PS-RGB_20190804111224_20190804111453_tile_3.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGB/SN6_Train_AOI_11_Rotterdam_PS-RGB_20190804111224_20190804111453_tile_4.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGBNIR/SN6_Train_AOI_11_Rotterdam_PS-RGBNIR_20190804111224_20190804111453_tile_1.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGBNIR/SN6_Train_AOI_11_Rotterdam_PS-RGBNIR_20190804111224_20190804111453_tile_2.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGBNIR/SN6_Train_AOI_11_Rotterdam_PS-RGBNIR_20190804111224_20190804111453_tile_3.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/PS-RGBNIR/SN6_Train_AOI_11_Rotterdam_PS-RGBNIR_20190804111224_20190804111453_tile_4.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/RGBNIR/SN6_Train_AOI_11_Rotterdam_RGBNIR_20190804111224_20190804111453_tile_1.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/RGBNIR/SN6_Train_AOI_11_Rotterdam_RGBNIR_20190804111224_20190804111453_tile_2.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/RGBNIR/SN6_Train_AOI_11_Rotterdam_RGBNIR_20190804111224_20190804111453_tile_3.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/RGBNIR/SN6_Train_AOI_11_Rotterdam_RGBNIR_20190804111224_20190804111453_tile_4.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/SAR-Intensity/SN6_Train_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_1.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/SAR-Intensity/SN6_Train_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_2.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/SAR-Intensity/SN6_Train_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_3.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/SAR-Intensity/SN6_Train_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_4.tif
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_1.geojson
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_2.geojson
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_3.geojson
 create mode 100644 tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_4.geojson
 create mode 100644 tests/data/spacenet/spacenet6/data.py

diff --git a/docs/api/datamodules.rst b/docs/api/datamodules.rst
index a4afe8c366..abb0c6eaef 100644
--- a/docs/api/datamodules.rst
+++ b/docs/api/datamodules.rst
@@ -193,7 +193,9 @@ So2Sat
 SpaceNet
 ^^^^^^^^
 
+.. autoclass:: SpaceNetBaseDataModule
 .. autoclass:: SpaceNet1DataModule
+.. autoclass:: SpaceNet6DataModule
 
 SSL4EO
 ^^^^^^
diff --git a/tests/conf/spacenet1.yaml b/tests/conf/spacenet1.yaml
index 275e54eee0..6f47d88d35 100644
--- a/tests/conf/spacenet1.yaml
+++ b/tests/conf/spacenet1.yaml
@@ -15,4 +15,4 @@ data:
     val_split_pct: 0.34
     test_split_pct: 0.34
   dict_kwargs:
-    root: 'tests/data/spacenet'
+    root: 'tests/data/spacenet/spacenet1'
diff --git a/tests/conf/spacenet6.yaml b/tests/conf/spacenet6.yaml
new file mode 100644
index 0000000000..c017102d3d
--- /dev/null
+++ b/tests/conf/spacenet6.yaml
@@ -0,0 +1,19 @@
+model:
+  class_path: SemanticSegmentationTask
+  init_args:
+    loss: 'ce'
+    model: 'unet'
+    backbone: 'resnet18'
+    in_channels: 4
+    num_classes: 3
+    num_filters: 1
+    ignore_index: null
+data:
+  class_path: SpaceNet6DataModule
+  init_args:
+    batch_size: 1
+    val_split_pct: 0.34
+    test_split_pct: 0.34
+  dict_kwargs:
+    root: 'tests/data/spacenet/spacenet6'
+    image: 'SAR-Intensity'
diff --git a/tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_3band.tar.gz b/tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_3band.tar.gz
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diff --git a/tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_geojson_buildings.tar.gz b/tests/data/spacenet/SN1_buildings/train/SN1_buildings_train_AOI_1_Rio_geojson_buildings.tar.gz
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diff --git a/tests/data/spacenet/data.py b/tests/data/spacenet/data.py
deleted file mode 100755
index 4d99e415e6..0000000000
--- a/tests/data/spacenet/data.py
+++ /dev/null
@@ -1,92 +0,0 @@
-#!/usr/bin/env python3
-
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License.
-
-import json
-import os
-import shutil
-
-import numpy as np
-import rasterio
-from rasterio.crs import CRS
-from rasterio.transform import Affine
-
-SIZE = 2
-
-dataset_id = 'SN1_buildings'
-
-profile = {
-    'driver': 'GTiff',
-    'dtype': 'uint8',
-    'width': SIZE,
-    'height': SIZE,
-    'crs': CRS.from_epsg(4326),
-    'transform': Affine(
-        4.489235388119662e-06,
-        0.0,
-        -43.7732462563,
-        0.0,
-        -4.486127586210932e-06,
-        -22.9214851954,
-    ),
-}
-
-np.random.seed(0)
-Z = np.random.randint(np.iinfo('uint8').max, size=(SIZE, SIZE), dtype='uint8')
-
-for count in [3, 8]:
-    os.makedirs(os.path.join(dataset_id, 'train', f'{count}band'), exist_ok=True)
-    for i in range(1, 5):
-        path = os.path.join(
-            dataset_id, 'train', f'{count}band', f'3band_AOI_1_RIO_img{i}.tif'
-        )
-        profile['count'] = count
-        with rasterio.open(path, 'w', **profile) as src:
-            for j in range(1, count + 1):
-                src.write(Z, j)
-
-    shutil.make_archive(
-        os.path.join(dataset_id, 'train', f'SN1_buildings_train_AOI_1_Rio_{count}band'),
-        'gztar',
-        os.path.join(dataset_id, 'train'),
-        f'{count}band',
-    )
-
-geojson = {
-    'type': 'FeatureCollection',
-    'crs': {'type': 'name', 'properties': {'name': 'urn:ogc:def:crs:OGC:1.3:CRS84'}},
-    'features': [
-        {
-            'type': 'Feature',
-            'geometry': {
-                'type': 'Polygon',
-                'coordinates': [
-                    [
-                        [-43.7720361, -22.922229499999958, 0.0],
-                        [-43.772064, -22.9222724, 0.0],
-                        [-43.772102399999937, -22.922247399999947, 0.0],
-                        [-43.772074499999974, -22.9222046, 0.0],
-                        [-43.7720361, -22.922229499999958, 0.0],
-                    ]
-                ],
-            },
-        }
-    ],
-}
-
-os.makedirs(os.path.join(dataset_id, 'train', 'geojson'), exist_ok=True)
-for i in range(1, 4):
-    path = os.path.join(dataset_id, 'train', 'geojson', f'Geo_AOI_1_RIO_img{i}.geojson')
-    with open(path, 'w') as src:
-        if i % 2 == 0:
-            json.dump(geojson, src)
-
-shutil.make_archive(
-    os.path.join(
-        dataset_id, 'train', 'SN1_buildings_train_AOI_1_Rio_geojson_buildings'
-    ),
-    'gztar',
-    os.path.join(dataset_id, 'train'),
-    'geojson',
-)
diff --git a/tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img1.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img1.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img1.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img1.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img2.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img2.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img2.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img2.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img3.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img3.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img3.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img3.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img4.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img4.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/3band/3band_AOI_1_RIO_img4.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/3band/3band_AOI_1_RIO_img4.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img1.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img1.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img1.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img1.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img2.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img2.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img2.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img2.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img3.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img3.tif
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img3.tif
rename to tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img3.tif
diff --git a/tests/data/spacenet/SN1_buildings/train/8band/3band_AOI_1_RIO_img4.tif b/tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img4.tif
similarity index 100%
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rename to tests/data/spacenet/spacenet1/SN1_buildings/test/8band/8band_AOI_1_RIO_img4.tif
diff --git a/tests/data/spacenet/spacenet1/SN1_buildings/test/SN1_buildings_test_AOI_1_Rio_3band.tar.gz b/tests/data/spacenet/spacenet1/SN1_buildings/test/SN1_buildings_test_AOI_1_Rio_3band.tar.gz
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diff --git a/tests/data/spacenet/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img1.geojson b/tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img1.geojson
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img1.geojson
rename to tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img1.geojson
diff --git a/tests/data/spacenet/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img2.geojson b/tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img2.geojson
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img2.geojson
rename to tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img2.geojson
diff --git a/tests/data/spacenet/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img3.geojson b/tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img3.geojson
similarity index 100%
rename from tests/data/spacenet/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img3.geojson
rename to tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img3.geojson
diff --git a/tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img4.geojson b/tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img4.geojson
new file mode 100644
index 0000000000..dabcc4ce30
--- /dev/null
+++ b/tests/data/spacenet/spacenet1/SN1_buildings/train/geojson/Geo_AOI_1_RIO_img4.geojson
@@ -0,0 +1 @@
+{"type": "FeatureCollection", "crs": {"type": "name", "properties": {"name": "urn:ogc:def:crs:OGC:1.3:CRS84"}}, "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-43.7720361, -22.922229499999958, 0.0], [-43.772064, -22.9222724, 0.0], [-43.77210239999994, -22.922247399999947, 0.0], [-43.772074499999974, -22.9222046, 0.0], [-43.7720361, -22.922229499999958, 0.0]]]}}]}
\ No newline at end of file
diff --git a/tests/data/spacenet/spacenet1/data.py b/tests/data/spacenet/spacenet1/data.py
new file mode 100755
index 0000000000..f8187583cc
--- /dev/null
+++ b/tests/data/spacenet/spacenet1/data.py
@@ -0,0 +1,161 @@
+#!/usr/bin/env python3
+
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import hashlib
+import json
+import os
+import shutil
+from typing import Any
+
+import numpy as np
+import rasterio
+from rasterio.crs import CRS
+from rasterio.transform import Affine
+
+SIZE = 2
+
+NUM_SAMPLES = 4
+
+dataset_id = 'SN1_buildings'
+
+profile = {
+    'driver': 'GTiff',
+    'dtype': 'uint8',
+    'width': SIZE,
+    'height': SIZE,
+    'crs': CRS.from_epsg(4326),
+    'transform': Affine(
+        4.489235388119662e-06,
+        0.0,
+        -43.7732462563,
+        0.0,
+        -4.486127586210932e-06,
+        -22.9214851954,
+    ),
+}
+
+np.random.seed(0)
+Z = np.random.randint(np.iinfo('uint8').max, size=(SIZE, SIZE), dtype='uint8')
+
+
+def create_directories(base_path: str, band_counts: list[int]) -> None:
+    for count in band_counts:
+        os.makedirs(os.path.join(base_path, f'{count}band'), exist_ok=True)
+
+
+def generate_geotiff_files(
+    base_path: str, band_counts: list[int], profile: dict[str, Any], Z: np.ndarray
+) -> None:
+    for count in band_counts:
+        for i in range(1, NUM_SAMPLES + 1):
+            path = os.path.join(
+                base_path, f'{count}band', f'{count}band_AOI_1_RIO_img{i}.tif'
+            )
+            profile['count'] = count
+            with rasterio.open(path, 'w', **profile) as src:
+                for j in range(1, count + 1):
+                    src.write(Z, j)
+
+
+def generate_geojson_files(base_path: str, geojson: dict[str, Any]) -> None:
+    os.makedirs(os.path.join(base_path, 'geojson'), exist_ok=True)
+    for i in range(1, NUM_SAMPLES + 1):
+        path = os.path.join(base_path, 'geojson', f'Geo_AOI_1_RIO_img{i}.geojson')
+        with open(path, 'w') as src:
+            if i % 2 == 0:
+                json.dump(geojson, src)
+
+
+def compute_md5(file_path: str) -> str:
+    hash_md5 = hashlib.md5()
+    with open(file_path, 'rb') as f:
+        for chunk in iter(lambda: f.read(4096), b''):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+
+# Generate dummy GeoJSON files for building footprints
+geojson = {
+    'type': 'FeatureCollection',
+    'crs': {'type': 'name', 'properties': {'name': 'urn:ogc:def:crs:OGC:1.3:CRS84'}},
+    'features': [
+        {
+            'type': 'Feature',
+            'geometry': {
+                'type': 'Polygon',
+                'coordinates': [
+                    [
+                        [-43.7720361, -22.922229499999958, 0.0],
+                        [-43.772064, -22.9222724, 0.0],
+                        [-43.772102399999937, -22.922247399999947, 0.0],
+                        [-43.772074499999974, -22.9222046, 0.0],
+                        [-43.7720361, -22.922229499999958, 0.0],
+                    ]
+                ],
+            },
+        }
+    ],
+}
+
+# Remove existing data if it exists
+if os.path.exists(dataset_id):
+    shutil.rmtree(dataset_id)
+
+train_base_path = os.path.join(dataset_id, 'train')
+test_base_path = os.path.join(dataset_id, 'test')
+
+# Create directories and generate dummy GeoTIFF files for train dataset
+create_directories(train_base_path, [3, 8])
+generate_geotiff_files(train_base_path, [3, 8], profile, Z)
+generate_geojson_files(train_base_path, geojson)
+
+# Create directories and generate dummy GeoTIFF files for test dataset (only 3band and 8band)
+create_directories(test_base_path, [3, 8])
+generate_geotiff_files(test_base_path, [3, 8], profile, Z)
+
+# Create tarballs for train and test datasets
+tarball_specs = {
+    'train': {
+        '3band': 'SN1_buildings_train_AOI_1_Rio_3band',
+        '8band': 'SN1_buildings_train_AOI_1_Rio_8band',
+        'geojson': 'SN1_buildings_train_AOI_1_Rio_geojson_buildings',
+    },
+    'test': {
+        '3band': 'SN1_buildings_test_AOI_1_Rio_3band',
+        '8band': 'SN1_buildings_test_AOI_1_Rio_8band',
+    },
+}
+
+for split, specs in tarball_specs.items():
+    for subdir, tarball_name in specs.items():
+        tarball_path = os.path.join(dataset_id, split, tarball_name)
+        shutil.make_archive(
+            tarball_path,
+            'gztar',
+            root_dir=os.path.join(dataset_id, split),
+            base_dir=subdir,
+        )
+
+# Compute and print MD5 checksums for the generated tarballs
+print('MD5 Checksums for Train Dataset:')
+train_tarballs = [
+    'SN1_buildings_train_AOI_1_Rio_3band.tar.gz',
+    'SN1_buildings_train_AOI_1_Rio_8band.tar.gz',
+    'SN1_buildings_train_AOI_1_Rio_geojson_buildings.tar.gz',
+]
+for tarball in train_tarballs:
+    tarball_path = os.path.join(dataset_id, 'train', tarball)
+    if os.path.exists(tarball_path):
+        print(f'{tarball}: {compute_md5(tarball_path)}')
+
+print('\nMD5 Checksums for Test Dataset:')
+test_tarballs = [
+    'SN1_buildings_test_AOI_1_Rio_3band.tar.gz',
+    'SN1_buildings_test_AOI_1_Rio_8band.tar.gz',
+]
+for tarball in test_tarballs:
+    tarball_path = os.path.join(dataset_id, 'test', tarball)
+    if os.path.exists(tarball_path):
+        print(f'{tarball}: {compute_md5(tarball_path)}')
diff --git a/tests/data/spacenet/spacenet6/SN6_buildings/test/SN6_buildings_AOI_11_Rotterdam_test.tar.gz b/tests/data/spacenet/spacenet6/SN6_buildings/test/SN6_buildings_AOI_11_Rotterdam_test.tar.gz
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diff --git a/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_1.geojson b/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_1.geojson
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_2.geojson b/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_2.geojson
new file mode 100644
index 0000000000..7ae5755f9f
--- /dev/null
+++ b/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_2.geojson
@@ -0,0 +1 @@
+{"type": "FeatureCollection", "crs": {"type": "name", "properties": {"name": "urn:ogc:def:crs:OGC:1.3:CRS84"}}, "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[4.47917, 51.9225, 0.0], [4.4792, 51.92255, 0.0], [4.47925, 51.92252, 0.0], [4.47922, 51.92247, 0.0], [4.47917, 51.9225, 0.0]]]}}]}
\ No newline at end of file
diff --git a/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_3.geojson b/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_3.geojson
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_4.geojson b/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_4.geojson
new file mode 100644
index 0000000000..7ae5755f9f
--- /dev/null
+++ b/tests/data/spacenet/spacenet6/SN6_buildings/train/train/AOI_11_Rotterdam/geojson_buildings/SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_4.geojson
@@ -0,0 +1 @@
+{"type": "FeatureCollection", "crs": {"type": "name", "properties": {"name": "urn:ogc:def:crs:OGC:1.3:CRS84"}}, "features": [{"type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[4.47917, 51.9225, 0.0], [4.4792, 51.92255, 0.0], [4.47925, 51.92252, 0.0], [4.47922, 51.92247, 0.0], [4.47917, 51.9225, 0.0]]]}}]}
\ No newline at end of file
diff --git a/tests/data/spacenet/spacenet6/data.py b/tests/data/spacenet/spacenet6/data.py
new file mode 100644
index 0000000000..47f2b59510
--- /dev/null
+++ b/tests/data/spacenet/spacenet6/data.py
@@ -0,0 +1,171 @@
+#!/usr/bin/env python3
+
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import hashlib
+import json
+import os
+import shutil
+from typing import Any
+
+import numpy as np
+import rasterio
+from rasterio.crs import CRS
+from rasterio.transform import Affine
+
+SIZE = 2
+
+NUM_SAMPLES = 4
+
+dataset_id = 'SN6_buildings'
+
+profile = {
+    'driver': 'GTiff',
+    'dtype': 'uint8',
+    'width': SIZE,
+    'height': SIZE,
+    'crs': CRS.from_epsg(4326),
+    'transform': Affine(
+        4.489235388119662e-06, 0.0, 4.47917, 0.0, -4.486127586210932e-06, 51.9225
+    ),
+}
+
+np.random.seed(0)
+Z = np.random.randint(np.iinfo('uint8').max, size=(SIZE, SIZE), dtype='uint8')
+
+# Define the types of imagery for SpaceNet6
+imagery_types = ['PAN', 'PS-RGB', 'PS-RGBNIR', 'RGBNIR', 'SAR-Intensity']
+imagery_channels = {
+    'PAN': 1,
+    'PS-RGB': 3,
+    'PS-RGBNIR': 4,
+    'RGBNIR': 4,
+    'SAR-Intensity': 4,
+}
+
+
+def create_directories(base_path: str, imagery_types: list[str]) -> None:
+    for imagery_type in imagery_types:
+        os.makedirs(os.path.join(base_path, imagery_type), exist_ok=True)
+
+
+def generate_geotiff_files(
+    base_path: str,
+    imagery_types: str,
+    imagery_channels: int,
+    profile: dict[str, Any],
+    Z: np.ndarray,
+    test: bool = False,
+) -> None:
+    for imagery_type in imagery_types:
+        for i in range(1, NUM_SAMPLES + 1):
+            if test and imagery_type == 'SAR-Intensity':
+                path = os.path.join(
+                    base_path,
+                    f'SN6_Test_Public_AOI_11_Rotterdam_SAR-Intensity_20190804111224_20190804111453_tile_{i}.tif',
+                )
+            else:
+                path = os.path.join(
+                    base_path,
+                    imagery_type,
+                    f'SN6_Train_AOI_11_Rotterdam_{imagery_type}_20190804111224_20190804111453_tile_{i}.tif',
+                )
+            profile['count'] = imagery_channels[imagery_type]
+            with rasterio.open(path, 'w', **profile) as src:
+                for j in range(1, profile['count'] + 1):
+                    src.write(Z, j)
+
+
+def generate_geojson_files(base_path: str, geojson: dict[str, Any]) -> None:
+    os.makedirs(os.path.join(base_path, 'geojson_buildings'), exist_ok=True)
+    for i in range(1, NUM_SAMPLES + 1):
+        path = os.path.join(
+            base_path,
+            'geojson_buildings',
+            f'SN6_Train_AOI_11_Rotterdam_Buildings_20190804111224_20190804111453_tile_{i}.geojson',
+        )
+        with open(path, 'w') as src:
+            if i % 2 == 0:
+                json.dump(geojson, src)
+
+
+def compute_md5(file_path: str) -> str:
+    hash_md5 = hashlib.md5()
+    with open(file_path, 'rb') as f:
+        for chunk in iter(lambda: f.read(4096), b''):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+
+# Generate dummy GeoJSON files for building footprints
+geojson = {
+    'type': 'FeatureCollection',
+    'crs': {'type': 'name', 'properties': {'name': 'urn:ogc:def:crs:OGC:1.3:CRS84'}},
+    'features': [
+        {
+            'type': 'Feature',
+            'geometry': {
+                'type': 'Polygon',
+                'coordinates': [
+                    [
+                        [4.47917, 51.9225, 0.0],
+                        [4.47920, 51.92255, 0.0],
+                        [4.47925, 51.92252, 0.0],
+                        [4.47922, 51.92247, 0.0],
+                        [4.47917, 51.9225, 0.0],
+                    ]
+                ],
+            },
+        }
+    ],
+}
+
+# Remove existing data if it exists
+if os.path.exists(dataset_id):
+    shutil.rmtree(dataset_id)
+
+train_base_path = os.path.join(dataset_id, 'train/train/AOI_11_Rotterdam')
+test_base_path = os.path.join(
+    dataset_id, 'test/test_public/AOI_11_Rotterdam/SAR-Intensity'
+)
+
+# Create directories and generate dummy GeoTIFF files for train dataset
+create_directories(train_base_path, imagery_types)
+generate_geotiff_files(train_base_path, imagery_types, imagery_channels, profile, Z)
+generate_geojson_files(train_base_path, geojson)
+
+# Create directories and generate dummy GeoTIFF files for test dataset (only SAR-Intensity)
+os.makedirs(test_base_path, exist_ok=True)
+generate_geotiff_files(
+    test_base_path, ['SAR-Intensity'], imagery_channels, profile, Z, test=True
+)
+
+# Create tarballs for train and test datasets
+shutil.make_archive(
+    os.path.join(dataset_id, 'train', 'SN6_buildings_AOI_11_Rotterdam_train'),
+    'gztar',
+    root_dir=os.path.join(dataset_id, 'train'),
+    base_dir='train',
+)
+shutil.make_archive(
+    os.path.join(dataset_id, 'test', 'SN6_buildings_AOI_11_Rotterdam_test'),
+    'gztar',
+    root_dir=os.path.join(dataset_id, 'test'),
+    base_dir='test_public',
+)
+
+# Compute and print MD5 checksums for the generated tarballs
+print('MD5 Checksums for Train Dataset:')
+train_tarball_path = os.path.join(
+    dataset_id, 'train', 'SN6_buildings_AOI_11_Rotterdam_train.tar.gz'
+)
+if os.path.exists(train_tarball_path):
+    print(f'Train: {compute_md5(train_tarball_path)}')
+
+print('\nMD5 Checksums for Test Dataset:')
+test_tarball_path = os.path.join(
+    dataset_id, 'test', 'SN6_buildings_AOI_11_Rotterdam_test.tar.gz'
+)
+if os.path.exists(test_tarball_path):
+    print(f'Test: {compute_md5(test_tarball_path)}')
diff --git a/tests/datasets/test_spacenet.py b/tests/datasets/test_spacenet.py
index 4385e7eee0..36d0d57c24 100644
--- a/tests/datasets/test_spacenet.py
+++ b/tests/datasets/test_spacenet.py
@@ -9,48 +9,70 @@
 import pytest
 import torch
 import torch.nn as nn
+from _pytest.fixtures import SubRequest
 from pytest import MonkeyPatch
 
-from torchgeo.datasets import DatasetNotFoundError, SpaceNet1
+from torchgeo.datasets import DatasetNotFoundError, SpaceNet, SpaceNet1, SpaceNet6
 from torchgeo.datasets.utils import Executable
 
 
 class TestSpaceNet:
-    @pytest.fixture
+    @pytest.fixture(params=[SpaceNet1, SpaceNet6])
     def dataset(
-        self, aws: Executable, monkeypatch: MonkeyPatch, tmp_path: Path
-    ) -> SpaceNet1:
+        self,
+        request: SubRequest,
+        aws: Executable,
+        monkeypatch: MonkeyPatch,
+        tmp_path: Path,
+    ) -> SpaceNet:
+        dataset_class: type[SpaceNet] = request.param
         url = os.path.join(
-            'tests', 'data', 'spacenet', '{dataset_id}', 'train', '{tarball}'
+            'tests',
+            'data',
+            'spacenet',
+            dataset_class.__name__.lower(),
+            '{dataset_id}',
+            'train',
+            '{tarball}',
         )
-        monkeypatch.setattr(SpaceNet1, 'url', url)
+        monkeypatch.setattr(dataset_class, 'url', url)
         transforms = nn.Identity()
-        return SpaceNet1(tmp_path, transforms=transforms, download=True)
+        return dataset_class(tmp_path, transforms=transforms, download=True)
 
     @pytest.mark.parametrize('index', [0, 1])
-    def test_getitem(self, dataset: SpaceNet1, index: int) -> None:
+    def test_getitem(self, dataset: SpaceNet, index: int) -> None:
         x = dataset[index]
         assert isinstance(x, dict)
         assert isinstance(x['image'], torch.Tensor)
         assert isinstance(x['mask'], torch.Tensor)
 
-    def test_len(self, dataset: SpaceNet1) -> None:
-        assert len(dataset) == 3
+    def test_len(self, dataset: SpaceNet) -> None:
+        assert len(dataset) == 4
 
-    def test_already_extracted(self, dataset: SpaceNet1) -> None:
-        SpaceNet1(root=dataset.root)
+    def test_already_extracted(self, dataset: SpaceNet) -> None:
+        dataset.__class__(root=dataset.root)
 
-    def test_already_downloaded(self, dataset: SpaceNet1) -> None:
-        for product in ['3band', '8band', 'geojson']:
-            dir = os.path.join(dataset.root, dataset.dataset_id, dataset.split, product)
+    def test_already_downloaded(self, dataset: SpaceNet) -> None:
+        if dataset.dataset_id == 'SN1_buildings':
+            base_dir = os.path.join(dataset.root, dataset.dataset_id, dataset.split)
+        elif dataset.dataset_id == 'SN6_buildings':
+            base_dir = os.path.join(
+                dataset.root,
+                dataset.dataset_id,
+                dataset.split,
+                dataset.split,
+                'AOI_11_Rotterdam',
+            )
+        for product in dataset.valid_images['train'] + list(dataset.valid_masks):
+            dir = os.path.join(base_dir, product)
             shutil.rmtree(dir)
-        SpaceNet1(root=dataset.root)
+        dataset.__class__(root=dataset.root)
 
-    def test_not_downloaded(self, tmp_path: Path) -> None:
+    def test_not_downloaded(self, tmp_path: Path, dataset: SpaceNet) -> None:
         with pytest.raises(DatasetNotFoundError, match='Dataset not found'):
-            SpaceNet1(tmp_path)
+            dataset.__class__(root=os.path.join(tmp_path, 'dummy'))
 
-    def test_plot(self, dataset: SpaceNet1) -> None:
+    def test_plot(self, dataset: SpaceNet) -> None:
         x = dataset[0]
         dataset.plot(x, show_titles=False)
         plt.close()
@@ -58,12 +80,12 @@ def test_plot(self, dataset: SpaceNet1) -> None:
         dataset.plot(x, suptitle='Test')
         plt.close()
 
-    def test_image_id(self, monkeypatch: MonkeyPatch, dataset: SpaceNet1) -> None:
+    def test_image_id(self, monkeypatch: MonkeyPatch, dataset: SpaceNet) -> None:
         file_regex = r'global_monthly_(\d+.*\d+)'
         monkeypatch.setattr(dataset, 'file_regex', file_regex)
         dataset._image_id('global_monthly_2018_01_mosaic_L15-0331E-1257N_1327_3160.tif')
 
-    def test_list_files(self, monkeypatch: MonkeyPatch, dataset: SpaceNet1) -> None:
+    def test_list_files(self, monkeypatch: MonkeyPatch, dataset: SpaceNet) -> None:
         directory_glob = os.path.join('**', 'AOI_{aoi}_*', '{product}')
         monkeypatch.setattr(dataset, 'directory_glob', directory_glob)
         dataset._list_files(aoi=1)
diff --git a/tests/trainers/test_segmentation.py b/tests/trainers/test_segmentation.py
index 8c33fa702f..4bdd966a1b 100644
--- a/tests/trainers/test_segmentation.py
+++ b/tests/trainers/test_segmentation.py
@@ -77,6 +77,7 @@ class TestSemanticSegmentationTask:
             'sentinel2_south_america_soybean',
             'southafricacroptype',
             'spacenet1',
+            'spacenet6',
             'ssl4eo_l_benchmark_cdl',
             'ssl4eo_l_benchmark_nlcd',
             'vaihingen2d',
diff --git a/torchgeo/datamodules/__init__.py b/torchgeo/datamodules/__init__.py
index 3bbb5153b4..ae4f029c93 100644
--- a/torchgeo/datamodules/__init__.py
+++ b/torchgeo/datamodules/__init__.py
@@ -43,7 +43,7 @@
 from .skippd import SKIPPDDataModule
 from .so2sat import So2SatDataModule
 from .southafricacroptype import SouthAfricaCropTypeDataModule
-from .spacenet import SpaceNet1DataModule
+from .spacenet import SpaceNet1DataModule, SpaceNet6DataModule, SpaceNetBaseDataModule
 from .ssl4eo import SSL4EOLDataModule, SSL4EOS12DataModule
 from .ssl4eo_benchmark import SSL4EOLBenchmarkDataModule
 from .sustainbench_crop_yield import SustainBenchCropYieldDataModule
@@ -99,7 +99,9 @@
     'SEN12MSDataModule',
     'SKIPPDDataModule',
     'So2SatDataModule',
+    'SpaceNetBaseDataModule',
     'SpaceNet1DataModule',
+    'SpaceNet6DataModule',
     'SSL4EOLBenchmarkDataModule',
     'SSL4EOLDataModule',
     'SSL4EOS12DataModule',
diff --git a/torchgeo/datamodules/spacenet.py b/torchgeo/datamodules/spacenet.py
index dad903bd71..e6b0b32582 100644
--- a/torchgeo/datamodules/spacenet.py
+++ b/torchgeo/datamodules/spacenet.py
@@ -10,57 +10,44 @@
 from torch import Tensor
 from torch.utils.data import random_split
 
-from ..datasets import SpaceNet1
+from ..datasets import SpaceNet, SpaceNet1, SpaceNet6
 from ..transforms import AugmentationSequential
 from .geo import NonGeoDataModule
 
 
-class SpaceNet1DataModule(NonGeoDataModule):
-    """LightningDataModule implementation for the SpaceNet1 dataset.
+class SpaceNetBaseDataModule(NonGeoDataModule):
+    """LightningDataModule implementation for the SpaceNet datasets.
 
-    Randomly splits into train/val/test.
+    Randomly splits the train split into train/val/test. The test split does not have labels,
+    and is only used for prediction.
 
-    .. versionadded:: 0.4
+    .. versionadded:: 0.7
     """
 
     def __init__(
         self,
+        spacenet_ds_class: type[SpaceNet],
         batch_size: int = 64,
         num_workers: int = 0,
         val_split_pct: float = 0.1,
         test_split_pct: float = 0.2,
         **kwargs: Any,
     ) -> None:
-        """Initialize a new SpaceNet1DataModule instance.
+        """Initialize a new SpaceNetBaseDataModule instance.
 
         Args:
+            spacenet_ds_class: The SpaceNet dataset class to use.
             batch_size: Size of each mini-batch.
-            num_workers: Number of workers for parallel data loading.
             val_split_pct: Percentage of the dataset to use as a validation set.
             test_split_pct: Percentage of the dataset to use as a test set.
-            **kwargs: Additional keyword arguments passed to
-                :class:`~torchgeo.datasets.SpaceNet1`.
+            num_workers: Number of workers for parallel data loading.
+            **kwargs: Additional keyword arguments passed to the SpaceNet dataset.
         """
-        super().__init__(SpaceNet1, batch_size, num_workers, **kwargs)
+        super().__init__(spacenet_ds_class, batch_size, num_workers, **kwargs)
 
         self.val_split_pct = val_split_pct
         self.test_split_pct = test_split_pct
-
-        self.train_aug = AugmentationSequential(
-            K.Normalize(mean=self.mean, std=self.std),
-            K.PadTo((448, 448)),
-            K.RandomRotation(p=0.5, degrees=90),
-            K.RandomHorizontalFlip(p=0.5),
-            K.RandomVerticalFlip(p=0.5),
-            K.RandomSharpness(p=0.5),
-            K.ColorJitter(p=0.5, brightness=0.1, contrast=0.1, saturation=0.1, hue=0.1),
-            data_keys=['image', 'mask'],
-        )
-        self.aug = AugmentationSequential(
-            K.Normalize(mean=self.mean, std=self.std),
-            K.PadTo((448, 448)),
-            data_keys=['image', 'mask'],
-        )
+        self.spacenet_ds_class = spacenet_ds_class
 
     def setup(self, stage: str) -> None:
         """Set up datasets.
@@ -68,17 +55,22 @@ def setup(self, stage: str) -> None:
         Args:
             stage: Either 'fit', 'validate', 'test', or 'predict'.
         """
-        self.dataset = SpaceNet1(**self.kwargs)
-        generator = torch.Generator().manual_seed(0)
-        self.train_dataset, self.val_dataset, self.test_dataset = random_split(
-            self.dataset,
-            [
-                1 - self.val_split_pct - self.test_split_pct,
-                self.val_split_pct,
-                self.test_split_pct,
-            ],
-            generator,
-        )
+        if stage in ['fit', 'validate', 'test']:
+            self.dataset = self.spacenet_ds_class(split='train', **self.kwargs)
+            generator = torch.Generator().manual_seed(0)
+            self.train_dataset, self.val_dataset, self.test_dataset = random_split(
+                self.dataset,
+                [
+                    1 - self.val_split_pct - self.test_split_pct,
+                    self.val_split_pct,
+                    self.test_split_pct,
+                ],
+                generator,
+            )
+
+        # test split in SpaceNet does not have labels
+        if stage in ['predict']:
+            self.predict_dataset = self.spacenet_ds_class(split='test', **self.kwargs)
 
     def on_after_batch_transfer(
         self, batch: dict[str, Tensor], dataloader_idx: int
@@ -95,6 +87,93 @@ def on_after_batch_transfer(
         # We add 1 to the mask to map the current {background, building} labels to
         # the values {1, 2}. This is necessary because we add 0 padding to the
         # mask that we want to ignore in the loss function.
-        batch['mask'] += 1
+        if 'mask' in batch:
+            batch['mask'] += 1
 
         return super().on_after_batch_transfer(batch, dataloader_idx)
+
+
+class SpaceNet1DataModule(SpaceNetBaseDataModule):
+    """LightningDataModule implementation for the SpaceNet1 dataset.
+
+    Randomly splits the train split into train/val/test. The test split does not have labels,
+    and is only used for prediction.
+
+    .. versionadded:: 0.4
+    """
+
+    def __init__(
+        self,
+        batch_size: int = 64,
+        num_workers: int = 0,
+        val_split_pct: float = 0.1,
+        test_split_pct: float = 0.2,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a new SpaceNet1DataModule instance.
+
+        Args:
+            batch_size: Size of each mini-batch.
+            num_workers: Number of workers for parallel data loading.
+            val_split_pct: Percentage of the dataset to use as a validation set.
+            test_split_pct: Percentage of the dataset to use as a test set.
+            **kwargs: Additional keyword arguments passed to
+                :class:`~torchgeo.datasets.SpaceNet1`.
+        """
+        super().__init__(
+            SpaceNet1, batch_size, num_workers, val_split_pct, test_split_pct, **kwargs
+        )
+
+        self.train_aug = AugmentationSequential(
+            K.Normalize(mean=self.mean, std=self.std),
+            K.PadTo((448, 448)),
+            K.RandomRotation(p=0.5, degrees=90),
+            K.RandomHorizontalFlip(p=0.5),
+            K.RandomVerticalFlip(p=0.5),
+            K.RandomSharpness(p=0.5),
+            K.ColorJitter(p=0.5, brightness=0.1, contrast=0.1, saturation=0.1, hue=0.1),
+            data_keys=['image', 'mask'],
+        )
+        self.aug = AugmentationSequential(
+            K.Normalize(mean=self.mean, std=self.std),
+            K.PadTo((448, 448)),
+            data_keys=['image', 'mask'],
+        )
+
+        self.predict_aug = AugmentationSequential(
+            K.Normalize(mean=self.mean, std=self.std),
+            K.PadTo((448, 448)),
+            data_keys=['image'],
+        )
+
+
+class SpaceNet6DataModule(SpaceNetBaseDataModule):
+    """LightningDataModule implementation for the SpaceNet6 dataset.
+
+    Randomly splits the train split into train/val/test. The test split does not have labels,
+    and is only used for prediction.
+
+    .. versionadded:: 0.7
+    """
+
+    def __init__(
+        self,
+        batch_size: int = 64,
+        num_workers: int = 0,
+        val_split_pct: float = 0.1,
+        test_split_pct: float = 0.2,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize a new SpaceNet6DataModule instance.
+
+        Args:
+            batch_size: Size of each mini-batch.
+            num_workers: Number of workers for parallel data loading.
+            val_split_pct: Percentage of the dataset to use as a validation set.
+            test_split_pct: Percentage of the dataset to use as a test set.
+            **kwargs: Additional keyword arguments passed to
+                :class:`~torchgeo.datasets.SpaceNet6`.
+        """
+        super().__init__(
+            SpaceNet6, batch_size, num_workers, val_split_pct, test_split_pct, **kwargs
+        )