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encoder.py

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+from segmentation_models_pytorch.encoders import encoders
+from segmentation_models_pytorch import Unet
+import torch
+
+# Override pretrained settings for your weights
+encoders["dpn131"]["pretrained_settings"]["imagenet-micronet"] = {
+    "url": "https://huggingface.co/jstuckner/microscopy-dpn131-imagenet-micronet/resolve/main/dpn131_imagenet-micronet_weights.pth",
+    "input_space": "RGB",
+    "input_range": [0, 1],
+    "mean": [0.485, 0.456, 0.406],
+    "std": [0.229, 0.224, 0.225],
+}
+
+# Use as normal
+model = Unet(
+    encoder_name="dpn131",
+    encoder_weights="imagenet-micronet",
+    classes=1,
+    activation=None,
+)
+
+# Test input
+x = torch.randn(1, 3, 256, 256)
+with torch.no_grad():
+    y = model(x)
+print("Output shape:", y.shape)