Update README.md

README.md

@@ -92,6 +92,42 @@ for batch in dataloader:
     break
 ```
 
+We provide some additional code for wrapping `albumentations` transform functions.
+We recommend albumentations because parameters are shared between all image modalities (e.g., same random crop). 
+However, it requires some wrapping to bring the data into the expected shape.  
+```python
+import albumentations as A
+from albumentations.pytorch import ToTensorV2
+from terramesh import build_terramesh_dataset, Transpose, MultimodalTransforms
+
+# Define all image modalities
+modalities = ["S2L2A", "S1GRD", "S1RTC", "DEM"]
+
+# Define multimodal transform function that converts the data into the expected shape from albumentations 
+val_transform = MultimodalTransforms(
+    transforms=A.Compose([  # We use albumentations because of the shared transform between image modalities
+        Transpose([1, 2, 0]),  # Convert data to channel last (expected shape from albumentations)
+        A.CenterCrop(224, 224),  # Use center crop in val split
+        # A.RandomCrop(224, 224),  # Use random crop in train split
+        # A.D4(),  # Optionally, use random flipping and rotation for the train split
+        ToTensorV2(),  # Convert to tensor and back to channel first
+    ],
+        is_check_shapes=False,  # Not needed because of aligned data in TerraMesh
+        additional_targets={m: "image" for m in modalities}  
+    ),
+    non_image_modalities=["__key__", "__url__"],  # Additional non-image keys
+)
+
+dataset = build_terramesh_dataset(
+    path="https://huggingface.co/datasets/ibm-esa-geospatial/TerraMesh/resolve/main/",  # Streaming or local path
+    modalities=modalities,
+    split='val',
+    transform=val_transform,
+    batch_size=8,
+)
+```
+
+
 If you have any issues with data loading, please create a discussion in the community tab and tag `@blumenstiel`.
 
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