Update README.md

README.md

@@ -58,4 +58,20 @@ with torch.no_grad():
         logits = outputs.logits  # Extract predictions
 
         all_preds.extend(logits.cpu().numpy())  # Store predictions
-        all_actuals.extend(gps_coords.cpu
+        all_actuals.extend(gps_coords.cpu().numpy())  # Store actual values
+
+# Denormalize predictions and actual values
+all_preds = np.array(all_preds)
+all_actuals = np.array(all_actuals)
+
+all_preds_denorm = all_preds * np.array([lat_std, lon_std]) + np.array([lat_mean, lon_mean])
+all_actuals_denorm = all_actuals * np.array([lat_std, lon_std]) + np.array([lat_mean, lon_mean])
+
+# Calculate RMSE using geodesic distances
+squared_errors = []
+for pred, actual in zip(all_preds_denorm, all_actuals_denorm):
+    distance = geodesic((actual[0], actual[1]), (pred[0], pred[1])).meters  
+    squared_errors.append(distance**2)  # Square the distance for RMSE
+
+rmse = np.sqrt(np.mean(squared_errors))
+print(f"RMSE: {rmse:.2f} meters")