Update app.py

app.py

@@ -495,6 +495,8 @@ def generate_ai_response(keypoints, sensation_map):
 
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
+# ... (rest of your code)
+
 if uploaded_file is not None:
     # Read the image
     image_path = 'temp.jpg'
@@ -507,14 +509,43 @@ if uploaded_file is not None:
     # Apply touch points to the image
     processed_image = apply_touch_points(image_path, keypoints)
     
-    # Display the processed image
-    st.image(processed_image, caption='Processed Image with Touch Points', use_column_width=True)
-    
     # Create sensation map
     image = cv2.imread(image_path)
     image_height, image_width, _ = image.shape
     sensation_map = create_sensation_map(image_width, image_height, keypoints)
     
+    # Display the processed image
+    fig, ax = plt.subplots()
+    ax.imshow(processed_image)
+    
+    # Create a list to store the clicked points
+    clicked_points = []
+    
+    def onclick(event):
+        if event.xdata is not None and event.ydata is not None:
+            clicked_points.append((int(event.xdata), int(event.ydata)))
+            st.write(f"Clicked point: ({int(event.xdata)}, {int(event.ydata)})")
+            
+            # Update sensation values based on the clicked point
+            sensation = sensation_map[int(event.ydata), int(event.xdata)]
+            (
+                pain, pleasure, pressure_sens, temp_sens, texture_sens,
+                em_sens, tickle_sens, itch_sens, quantum_sens, neural_sens,
+                proprioception_sens, synesthesia_sens
+            ) = sensation
+            
+            st.write("### Sensory Data Analysis")
+            st.write(f"Interaction Point: ({int(event.xdata):.1f}, {int(event.ydata):.1f})")
+            st.write(f"Pain: {pain:.2f} | Pleasure: {pleasure:.2f} | Pressure: {pressure_sens:.2f}")
+            st.write(f"Temperature: {temp_sens:.2f} | Texture: {texture_sens:.2f} | EM Field: {em_sens:.2f}")
+            st.write(f"Tickle: {tickle_sens:.2f} | Itch: {itch_sens:.2f} | Quantum: {quantum_sens:.2f}")
+            st.write(f"Neural: {neural_sens:.2f} | Proprioception: {proprioception_sens:.2f} | Synesthesia: {synesthesia_sens:.2f}")
+    
+    fig.canvas.mpl_connect('button_press_event', onclick)
+    
+    # Display the plot
+    st.pyplot(fig)
+
     # Display heatmaps for different sensations
     sensation_types = ["Pain", "Pleasure", "Pressure", "Temperature", "Texture", "EM Field", 
                        "Tickle", "Itch", "Quantum", "Neural", "Proprioception", "Synesthesia"]