Update README.md

README.md

@@ -1,3 +1,26 @@
----
-license: mit
----
+---
+license: mit
+---
+
+Instructions to load the pre-trained model weights
+
+```python
+import torch
+from monai.networks.nets import SegResNetDS
+
+weights = torch.load("pretrained_segresnet.torch")
+
+model = SegResNetDS(
+    blocks_down=(1, 2, 2, 4, 4)
+)
+
+model.load_state_dict(weights, strict=False) # Set strict to False as we load only the encoder
+
+# Dummy forward pass
+tensor = torch.randn((2, 1, 32, 32, 32))
+
+# Note that the input data needs to be in "SPL" format (OR z,y,x default numpy/torch format), 
+# you can use Orientation transform in MONAI set with value "SPL". 
+# Note: All subsequent transforms must be applied in (z,y,x) format. Eg patch size of [16, 32, 32] corresponds to 16 in z-axis
+out = model(tensor)
+```