Update app.py

app.py

@@ -111,85 +111,4 @@ def predict_and_plot(velocity, temperature, precipitation, humidity):
         cleaning_times = calculate_cleaning_time(time_intervals, simulated_contamination_levels)
 
         # Lidar names
-        lidar_names = ['F/L', 'F/R', 'Left', 'Right', 'Roof', 'Rear']
-
-        # Plot the graph
-        plt.figure(figsize=(12, 8))
-
-        for i in range(simulated_contamination_levels.shape[1]):
-            plt.plot(time_intervals, simulated_contamination_levels[:, i], label=f'{lidar_names[i]}')
-            plt.axhline(y=0.4, color='r', linestyle='--', label='Contamination Threshold' if i == 0 else "")
-            if i < len(cleaning_times):
-                plt.scatter(cleaning_times[i], 0.4, color='k')  # Mark the cleaning time point
-
-        plt.title('Contamination Levels Over Time for Each Lidar')
-        plt.xlabel('Time (seconds)')
-        plt.ylabel('Contamination Level')
-        plt.legend()
-        plt.grid(True)
-        
-        # Return the plot and predictions
-        return plt, [f"{val * 100:.2f}%" for val in contamination_levels[0]], [f"{val:.2f}" for val in cleaning_times]
-
-    except Exception as e:
-        print(f"Error in Gradio interface: {e}")
-        return plt.figure(), ["Error"] * 6, ["Error"] * 6
-
-inputs = [
-    gr.Slider(minimum=0, maximum=100, value=50, step=0.05, label="Velocity (mph)"),
-    gr.Slider(minimum=-2, maximum=30, value=0, step=0.5, label="Temperature (°C)"),
-    gr.Slider(minimum=0, maximum=1, value=0, step=0.01, label="Precipitation (inch)"),
-    gr.Slider(minimum=0, maximum=100, value=50, label="Humidity (%)")
-]
-
-contamination_outputs = [
-    gr.Textbox(label="Front Left Contamination"),
-    gr.Textbox(label="Front Right Contamination"),
-    gr.Textbox(label="Left Contamination"),
-    gr.Textbox(label="Right Contamination"),
-    gr.Textbox(label="Roof Contamination"),
-    gr.Textbox(label="Rear Contamination")
-]
-
-cleaning_time_outputs = [
-    gr.Textbox(label="Front Left Cleaning Time"),
-    gr.Textbox(label="Front Right Cleaning Time"),
-    gr.Textbox(label="Left Cleaning Time"),
-    gr.Textbox(label="Right Cleaning Time"),
-    gr.Textbox(label="Roof Cleaning Time"),
-    gr.Textbox(label="Rear Cleaning Time")
-]
-
-with gr.Blocks() as demo:
-    gr.Markdown("<h1 style='text-align: center;'>Environmental Factor-Based Contamination & Cleaning Time Prediction</h1>")
-    gr.Markdown("This application predicts the contamination levels, corresponding gradients, and cleaning times for different parts of a car's LiDAR system based on environmental factors such as velocity, temperature, precipitation, and humidity.")
-    
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("### Input Parameters")
-            for inp in inputs:
-                inp.render()
-
-            # Centered image display
-            with gr.Row():
-                with gr.Column(scale=1, min_width=0):
-                    gr.Image(image_path)  # Ensure the image is centered
-            
-            gr.Button(value="Submit", variant="primary").click(
-                fn=predict_and_plot, 
-                inputs=inputs, 
-                outputs=[gr.Plot(label="Contamination Levels Over Time")] + contamination_outputs + cleaning_time_outputs
-            )
-            gr.Button(value="Clear").click(fn=lambda: None)
-            
-        with gr.Column():
-            gr.Markdown("### Contamination Predictions")
-            for out in contamination_outputs:
-                out.render()
-                
-        with gr.Column():
-            gr.Markdown("### Cleaning Time Predictions")
-            for out in cleaning_time_outputs:
-                out.render()
-
-demo.launch()
+        lidar_names = ['F/L', 'F/R', 'Left', '