Update app.py

app.py

@@ -13,6 +13,7 @@ import tempfile
 import json
 from math import radians, cos, sin, asin, sqrt, atan2, degrees
 import time
+import functools
 
 # ============================
 # Configure Logging
@@ -689,10 +690,14 @@ def main():
 
     # Define the Gradio components for classical prediction tab
     classical_tab = gr.Interface(
-        fn=lambda file, model_choice, min_mmsi, max_mmsi: classical_prediction(file, model_choice, min_mmsi, max_mmsi, models, loaded_scalers),
+        fn=functools.partial(classical_prediction, models=models, loaded_scalers=loaded_scalers),
         inputs=[
             gr.File(label="Upload CSV File", type='filepath'),
-            gr.Dropdown(choices=["Auto-Select", "Teacher", "Student_North", "Student_Mid", "Student_South"], value="Auto-Select", label="Choose Model"),
+            gr.Dropdown(
+                choices=["Auto-Select", "Teacher", "Student_North", "Student_Mid", "Student_South"],
+                value="Auto-Select",
+                label="Choose Model"
+            ),
             gr.Number(label="Min MMSI", value=0),
             gr.Number(label="Max MMSI", value=999999999)
         ],
@@ -703,12 +708,15 @@ def main():
             gr.Textbox(label="Error Message", lines=2, visible=False)
         ],
         title="Classical Prediction & Metrics",
-        description="Upload a CSV file and select a model to get classical evaluation metrics such as MAE, MSE, RMSE. The inference time is also provided."
+        description=(
+            "Upload a CSV file and select a model to get classical evaluation metrics such as MAE, MSE, RMSE. "
+            "The inference time is also provided."
+        )
     )
 
     # Define the Gradio components for abnormal behavior detection tab
     abnormal_tab = gr.Interface(
-        fn=lambda prediction_file, alpha, threshold: abnormal_behavior_detection(prediction_file, alpha, threshold),
+        fn=functools.partial(abnormal_behavior_detection),
         inputs=[
             gr.File(label="Upload Predicted Positions CSV", type='filepath'),
             gr.Slider(minimum=0, maximum=1, step=0.1, value=0.5, label="Alpha (α)"),
@@ -725,6 +733,7 @@ def main():
         )
     )
 
+
     # Combine the two tabs using Gradio Tabs component
     with gr.Blocks() as demo:
         gr.Markdown("# Vessel Trajectory Prediction and Abnormal Behavior Detection")
@@ -736,7 +745,7 @@ def main():
 
     # Launch the Gradio interface
     logging.info("Launching Gradio interface...")
-    demo.launch(share=True)
+    demo.launch()
     logging.info("Gradio interface launched successfully.")
 
 # Run the app