Upload convert.py

convert.py

@@ -0,0 +1,17 @@
+import segmentation_models_pytorch as smp
+import torch
+
+paths = [
+    "2_Class_CCBY_FTW_Pretrained.ckpt",
+    "2_Class_FULL_FTW_Pretrained.ckpt",
+    "3_Class_CCBY_FTW_Pretrained.ckpt",
+    "3_Class_FULL_FTW_Pretrained.ckpt",
+]
+classes = [2, 2, 3, 3]
+for num_classes, path in zip(classes, paths):
+    state_dict = torch.load(path, weights_only=True, map_location="cpu")["state_dict"]
+    state_dict = {k.replace("model.", ""): v for k, v in state_dict.items()}
+    del state_dict["criterion.weight"]
+    model = smp.Unet(encoder_name="efficientnet-b3", in_channels=8, classes=num_classes, encoder_weights=None)
+    model.load_state_dict(state_dict)
+    torch.save(model.state_dict(), path.replace(".ckpt", ".pth"))