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README.md

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+# SwinGPSModel
+
+## Model Class
+
+```python
+class SwinGPSModel(nn.Module):
+def __init__(self, pretrained=True):
+super(SwinGPSModel, self).__init__()
+# Load the pretrained Swin Transformer
+self.backbone = create_model('swin_base_patch4_window7_224', pretrained=pretrained)
+
+# Get the number of features from the backbone
+num_features = self.backbone.num_features
+self.backbone.head = nn.Identity()
+
+# Define the regression head
+self.regression_head = nn.Sequential(
+nn.AdaptiveAvgPool2d((1, 1)),
+nn.Flatten(),
+nn.Linear(num_features, 256),
+nn.ReLU(),
+nn.Linear(256, 2)
+)
+
+def forward(self, x):
+# Forward pass through the backbone
+features = self.backbone(x)
+features = features.permute(0, 3, 1, 2)
+return self.regression_head(features)
+```
+
+## How to Run
+In the notebook Run_swin_base.ipynb, replace the line:
+```python
+dataset_test = load_dataset("gydou/released_img")
+```
+with the proper location of the testing dataset.
+
+## Training Dataset Statistics
+```python
+lat_std = 0.0006914493505038013
+lon_std = 0.0006539239061573955
+lat_mean = 39.9517411499467
+lon_mean = -75.19143213125122
+```