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README.md
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license: mit
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library_name: torchgeo
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license: mit
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library_name: torchgeo
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---
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Model Weights extracted below:
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```python
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import os
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import hashlib
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import torch
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import segmentation_models_pytorch as smp
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url = "https://github.com/microsoft/ai4g-flood/raw/refs/heads/main/models/ai4g_sar_model.ckpt"
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state_dict = torch.hub.load_state_dict_from_url(url, weights_only=False, map_location="cpu")["state_dict"]
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state_dict = {k.replace("model.model.", ""): v for k, v in state_dict.items() if "model.model." in k}
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model = smp.Unet(
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encoder_name="mobilenet_v2",
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encoder_weights=None,
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in_channels=2,
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classes=2,
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)
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model.load_state_dict(state_dict, strict=True)
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filename = "unet_mobilenetv2_sentinel1_ai4g_flood.pth"
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torch.save(model.state_dict(), filename)
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md5 = hashlib.md5(open(filename, "rb").read()).hexdigest()[:8]
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os.rename(filename, filename.replace(".pth", f"-{md5}.pth"))
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```
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