Update app.py

app.py

@@ -1,6 +1,9 @@
 import gradio as gr
 import numpy as np
 import joblib
+import folium
+from folium import Map, Marker
+from io import BytesIO
 
 # Define model paths
 model_paths = {
@@ -54,55 +57,44 @@ def load_model_and_predict(prediction_type, time_interval, input_data):
         prediction = model.predict(processed_data)
         
         if prediction_type == 'Path':
-            return f"Predicted Path after {time_interval}: Latitude: {prediction[0][0]}, Longitude: {prediction[0][1]}"
+            latitude, longitude = prediction[0][0], prediction[0][1]
+            return f"Predicted Path after {time_interval}: Latitude: {latitude}, Longitude: {longitude}", display_map(latitude, longitude)
     except Exception as e:
         return str(e)
 
+def display_map(latitude, longitude):
+    # Create a map centered around the predicted coordinates
+    m = folium.Map(location=[latitude, longitude], zoom_start=6)
+    folium.Marker([latitude, longitude], tooltip="Predicted Location").add_to(m)
+    
+    # Save map as HTML and load in Gradio
+    map_data = BytesIO()
+    m.save(map_data, close_file=False)
+    return map_data
+
 # Gradio interface components
 with gr.Blocks() as cyclone_predictor:
     gr.Markdown("# Cyclone Path Prediction App")
     
-    # Dropdown for Prediction Type
-    prediction_type = gr.Dropdown(
-        choices=['Path'],
-        value='Path',
-        label="Select Prediction Type"
-    )
-    
-    # Dropdown for Time Interval
+    prediction_type = gr.Dropdown(choices=['Path'], value='Path', label="Select Prediction Type")
     time_interval = gr.Dropdown(
         choices=['3 hours', '6 hours', '9 hours', '12 hours', '15 hours', '18 hours', '21 hours', '24 hours', '27 hours', '30 hours', '33 hours', '36 hours'],
         label="Select Time Interval"
     )
     
-    # Input fields for user data
-    previous_lat_lon = gr.Textbox(
-        placeholder="Enter previous 3-hour lat/lon (e.g., 15.54,90.64)",
-        label="Previous 3-hour Latitude/Longitude"
-    )
-    previous_speed = gr.Number(label="Previous 3-hour Speed")  # Removed placeholder
-    previous_timestamp = gr.Textbox(
-        placeholder="Enter previous 3-hour timestamp (e.g., 2024,10,23,0)",
-        label="Previous 3-hour Timestamp (year, month, day, hour)"
-    )
-
-    present_lat_lon = gr.Textbox(
-        placeholder="Enter present 3-hour lat/lon (e.g., 15.71,90.29)",
-        label="Present 3-hour Latitude/Longitude"
-    )
-    present_speed = gr.Number(label="Present 3-hour Speed")  # Removed placeholder
-    present_timestamp = gr.Textbox(
-        placeholder="Enter present 3-hour timestamp (e.g., 2024,10,23,3)",
-        label="Present 3-hour Timestamp (year, month, day, hour)"
-    )
+    previous_lat_lon = gr.Textbox(placeholder="Enter previous 3-hour lat/lon (e.g., 15.54,90.64)", label="Previous 3-hour Latitude/Longitude")
+    previous_speed = gr.Number(label="Previous 3-hour Speed")
+    previous_timestamp = gr.Textbox(placeholder="Enter previous 3-hour timestamp (e.g., 2024,10,23,0)", label="Previous 3-hour Timestamp (year, month, day, hour)")
+    
+    present_lat_lon = gr.Textbox(placeholder="Enter present 3-hour lat/lon (e.g., 15.71,90.29)", label="Present 3-hour Latitude/Longitude")
+    present_speed = gr.Number(label="Present 3-hour Speed")
+    present_timestamp = gr.Textbox(placeholder="Enter present 3-hour timestamp (e.g., 2024,10,23,3)", label="Present 3-hour Timestamp (year, month, day, hour)")
 
-    # Output prediction
     prediction_output = gr.Textbox(label="Prediction Output")
-    
-    # Predict button
+    map_output = gr.HTML(label="Predicted Location Map")
+
     def get_input_data(previous_lat_lon, previous_speed, previous_timestamp, present_lat_lon, present_speed, present_timestamp):
         try:
-            # Parse inputs into required format
             prev_lat, prev_lon = map(float, previous_lat_lon.split(','))
             prev_time = list(map(int, previous_timestamp.split(',')))
             previous_data = [prev_lat, prev_lon, previous_speed] + prev_time
@@ -117,13 +109,12 @@ with gr.Blocks() as cyclone_predictor:
 
     predict_button = gr.Button("Predict Path")
     
-    # Linking function to UI elements
     predict_button.click(
         fn=lambda pt, ti, p_lat_lon, p_speed, p_time, c_lat_lon, c_speed, c_time: load_model_and_predict(
             pt, ti, get_input_data(p_lat_lon, p_speed, p_time, c_lat_lon, c_speed, c_time)
         ),
         inputs=[prediction_type, time_interval, previous_lat_lon, previous_speed, previous_timestamp, present_lat_lon, present_speed, present_timestamp],
-        outputs=prediction_output
+        outputs=[prediction_output, map_output]
     )
 
-cyclone_predictor.launch()
+cyclone_predictor.launch()