Adding datamodule

tests/conf/so2sat_all.yaml

@@ -13,4 +13,5 @@ datamodule:
   root: "tests/data/so2sat"
   batch_size: 1
   num_workers: 0
+  version: "2"
   band_set: "all"

tests/conf/so2sat_rgb.yaml

@@ -0,0 +1,17 @@
+module:
+  _target_: torchgeo.trainers.ClassificationTask
+  loss: "ce"
+  model: "resnet18"
+  learning_rate: 1e-3
+  learning_rate_schedule_patience: 6
+  weights: null
+  in_channels: 3
+  num_classes: 17
+
+datamodule:
+  _target_: torchgeo.datamodules.So2SatDataModule
+  root: "tests/data/so2sat"
+  batch_size: 1
+  num_workers: 0
+  version: "3_random"
+  band_set: "rgb"

tests/conf/so2sat_s1.yaml

@@ -13,4 +13,5 @@ datamodule:
   root: "tests/data/so2sat"
   batch_size: 1
   num_workers: 0
+  version: "2"
   band_set: "s1"

tests/conf/so2sat_s2.yaml

@@ -13,4 +13,5 @@ datamodule:
   root: "tests/data/so2sat"
   batch_size: 1
   num_workers: 0
+  version: "2"
   band_set: "s2"

tests/trainers/test_classification.py

@@ -77,6 +77,7 @@ class TestClassificationTask:
             "so2sat_all",
             "so2sat_s1",
             "so2sat_s2",
+            "so2sat_rgb",
             "ucmerced",
         ],
     )

torchgeo/datamodules/so2sat.py

@@ -44,8 +44,50 @@ class So2SatDataModule(NonGeoDataModule):
                 0.10905050699570,
             ]
         ),
-        "3_random": torch.tensor([]),
-        "3_block": torch.tensor([]),
+        "3_random": torch.tensor(
+            [
+                -0.00005541164581,
+                -0.00001363245448,
+                0.00004558943283,
+                0.00002990907940,
+                0.04451951629749,
+                0.25862310103671,
+                0.00032720731137,
+                0.00123416595462,
+                0.12428656593186,
+                0.11001677362564,
+                0.10230652367417,
+                0.11532195526186,
+                0.15989486018315,
+                0.18204406482475,
+                0.17513562590622,
+                0.19565546643221,
+                0.15648722649020,
+                0.11122536338577,
+            ]
+        ),
+        "3_block": torch.tensor(
+            [
+                -0.00004632368791,
+                0.00001260869365,
+                0.00005305557337,
+                0.00003471369557,
+                0.04449937686171,
+                0.26046026815721,
+                0.00087815394475,
+                0.00086889627435,
+                0.12381869777901,
+                0.10944155483024,
+                0.10176911573221,
+                0.11465267892206,
+                0.15870528223797,
+                0.18053964470203,
+                0.17366821871719,
+                0.19390983961551,
+                0.15536490486611,
+                0.11057334452833,
+            ]
+        ),
         "3_culture_10": torch.tensor(  # note: this is the same as "2"
             [
                 -0.00003591224260,
@@ -93,8 +135,50 @@ class So2SatDataModule(NonGeoDataModule):
                 0.08780632,
             ]
         ),
-        "3_random": torch.tensor([]),
-        "3_block": torch.tensor([]),
+        "3_random": torch.tensor(
+            [
+                0.1756914,
+                0.1761190,
+                0.4600589,
+                0.4563601,
+                2.2492179,
+                7.9056503,
+                2.1917633,
+                1.3148480,
+                0.0392269,
+                0.0470917,
+                0.0653264,
+                0.0624057,
+                0.0758367,
+                0.0891717,
+                0.0905092,
+                0.0996856,
+                0.0990188,
+                0.0873386,
+            ]
+        ),
+        "3_block": torch.tensor(
+            [
+                0.1751797,
+                0.1754073,
+                0.4610124,
+                0.4572122,
+                0.8294254,
+                7.1771026,
+                0.9642598,
+                0.8770835,
+                0.0388311,
+                0.0464986,
+                0.0643833,
+                0.0616141,
+                0.0753004,
+                0.0886178,
+                0.0899500,
+                0.0991759,
+                0.0983276,
+                0.0865943,
+            ]
+        ),
         "3_culture_10": torch.tensor(  # note: this is the same as "2"
             [
                 0.17555201,

torchgeo/datasets/so2sat.py

@@ -107,7 +107,10 @@ class So2Sat(NonGeoDataset):
             "train": "94e2e2e667b406c2adf61e113b42204e",
             "test": "1e15c425585ce816342d1cd779d453d8",
         },
-        "3_block": {"train": "", "test": ""},
+        "3_block": {
+            "train": "a91d6150e8b059dac86105853f377a11",
+            "test": "6414af1ec33ace417e879f9c88066d47"
+        },
         "3_culture_10": {
             "train": "702bc6a9368ebff4542d791e53469244",
             "test": "58335ce34ca3a18424e19da84f2832fc",