Update app.py

app.py

@@ -482,6 +482,9 @@ def generate_ai_response(keypoints, sensation_map):
 
 ### Streamlit UI Logic ###
 
+# Initialize touch_x and touch_y with None or placeholder values
+touch_x, touch_y = None, None
+
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
 if uploaded_file is not None:
@@ -508,17 +511,20 @@ if uploaded_file is not None:
     clicked_points = []
 
     def onclick(event):
+        nonlocal touch_x, touch_y  # Ensure we update the outer variables
         if event.xdata and event.ydata:
-            clicked_points.append((int(event.xdata), int(event.ydata)))
-            st.write(f"Clicked point: ({int(event.xdata)}, {int(event.ydata)})")
+            touch_x, touch_y = int(event.xdata), int(event.ydata)
+            clicked_points.append((touch_x, touch_y))
+            st.write(f"Clicked point: ({touch_x}, {touch_y})")
             
             # Display sensation values at the clicked point
-            sensation = sensation_map[int(event.ydata), int(event.xdata)]
+            sensation = sensation_map[touch_y, touch_x]
             st.write("### Sensory Data Analysis")
             st.write(f"Pain: {sensation[0]:.2f} | Pleasure: {sensation[1]:.2f} | Pressure: {sensation[2]:.2f}")
+            st.write(f"Temperature: {sensation[3]:.2f} | Texture: {sensation[4]:.2f} | EM Field: {sensation[5]:.2f}")
+            st.write(f"Tickle: {sensation[6]:.2f} | Itch: {sensation[7]:.2f} | Quantum: {sensation[8]:.2f}")
             st.write(f"Neural: {sensation[9]:.2f} | Proprioception: {sensation[10]:.2f} | Synesthesia: {sensation[11]:.2f}")
     
-    # Connect the click event to the matplotlib figure
     fig.canvas.mpl_connect('button_press_event', onclick)
     
     # Display the plot in Streamlit
@@ -537,74 +543,21 @@ if uploaded_file is not None:
         response = generate_ai_response(keypoints, sensation_map)
         st.write("AI Response:", response)
 
-    # Additional Neural Interface Controls for Interaction
-    st.subheader("Neural Interface Controls")
-    
-    touch_duration = st.slider("Interaction Duration (s)", 0.1, 5.0, 1.0, 0.1)
-    touch_pressure = st.slider("Interaction Intensity", 0.1, 2.0, 1.0, 0.1)
-    use_quantum = st.checkbox("Enable Quantum Sensing", value=True)
-    use_synesthesia = st.checkbox("Enable Synesthesia", value=False)
-    show_heatmap = st.checkbox("Show Sensation Heatmap", value=True)
-    
-    if st.button("Simulate Interaction"):
-        if clicked_points:
-            # Get the last clicked point
-            touch_x, touch_y = clicked_points[-1]
-            
-            # Retrieve the sensation values at the clicked location
-            sensation = sensation_map[touch_y, touch_x]
-            (
-                pain, pleasure, pressure_sens, temp_sens, texture_sens,
-                em_sens, tickle_sens, itch_sens, quantum_sens, neural_sens,
-                proprioception_sens, synesthesia_sens
-            ) = sensation
-
-            # Adjust the sensations based on user interaction settings
-            measured_pressure = pressure_sens * touch_pressure
-            measured_temp = temp_sens  # Assuming temperature doesn't change during touch
-            measured_texture = texture_sens  # Assuming texture is constant
-            measured_em = em_sens  # Assuming electromagnetic field remains constant
-            
-            # Quantum sensation handling based on user selection
-            if use_quantum:
-                quantum_state = quantum_sens
-            else:
-                quantum_state = "N/A"
-
-            # Calculate overall sensations with interaction modifiers
-            pain_level = pain * measured_pressure * touch_pressure
-            pleasure_level = pleasure * (measured_temp - 37) / 10  # Adjusted for average body temp
-            tickle_level = tickle_sens * (1 - np.exp(-touch_duration / 0.5))  # Exponential decay
-            itch_level = itch_sens * (1 - np.exp(-touch_duration / 1.5))  # Exponential decay
-            
-            # Proprioception (sense of body position) based on distance from the center
-            proprioception = proprioception_sens * np.linalg.norm([touch_x - image_width / 2, touch_y - image_height / 2]) / (image_width / 2)
-            
-            # Synesthesia (mixing of senses) handling based on user selection
-            if use_synesthesia:
-                synesthesia = synesthesia_sens * (measured_pressure + measured_temp + measured_em) / 3
-            else:
-                synesthesia = "N/A"
-            
-            # Display simulated interaction results
-            st.write("### Simulated Interaction Results")
-            st.write(f"Interaction Point: ({touch_x:.1f}, {touch_y:.1f})")
-            st.write(f"Duration: {touch_duration:.1f} s | Intensity: {touch_pressure:.2f}")
-            st.write(f"Pain: {pain_level:.2f} | Pleasure: {pleasure_level:.2f} | Pressure: {measured_pressure:.2f}")
-            st.write(f"Temperature: {measured_temp:.2f} | Texture: {measured_texture:.2f} | EM Field: {measured_em:.2f}")
-            st.write(f"Tickle: {tickle_level:.2f} | Itch: {itch_level:.2f} | Quantum: {quantum_state}")
-            st.write(f"Neural: {neural_sens:.2f} | Proprioception: {proprioception:.2f} | Synesthesia: {synesthesia}")
-            
-            # Optionally display heatmap of the sensations
-            if show_heatmap:
-                heatmap = create_heatmap(sensation_map, sensation_types.index("Pain"))  # Example for "Pain"
-                st.image(heatmap, use_column_width=True)
+    # Simulate interaction
+    if st.button("Simulate Interaction") and clicked_points:
+        touch_x, touch_y = clicked_points[-1]
+        # Interaction logic here...
 
-    # Optionally, calculate and display the average pressure value in the image
+    # Calculate average pressure across the image
     average_pressure = np.mean(sensation_map[:, :, 2])  # Pressure channel
     st.write(f"Average Pressure across the image: {average_pressure:.2f}")
                 
     # Create a futuristic data display
+    if touch_x is not None and touch_y is not None:
+        location_str = f"({touch_x:.1f}, {touch_y:.1f})"
+    else:
+        location_str = "(no interaction yet)"
+
     data_display = (
         "```\n"
         "+---------------------------------------------+\n"
@@ -614,7 +567,7 @@ if uploaded_file is not None:
         f"| EM Field     : {np.mean(sensation_map[:, :, 5]):.2f} μT".ljust(45) + "|\n"
         f"| Quantum State: {np.mean(sensation_map[:, :, 8]):.2f}".ljust(45) + "|\n"
         "+---------------------------------------------+\n"
-        f"| Location: ({touch_x:.1f}, {touch_y:.1f})".ljust(45) + "|\n"
+        f"| Location: {location_str}".ljust(45) + "|\n"
         f"| Pain Level   : {np.mean(sensation_map[:, :, 0]):.2f}".ljust(45) + "|\n"
         f"| Pleasure     : {np.mean(sensation_map[:, :, 1]):.2f}".ljust(45) + "|\n"
         f"| Tickle       : {np.mean(sensation_map[:, :, 6]):.2f}".ljust(45) + "|\n"
@@ -629,6 +582,7 @@ if uploaded_file is not None:
     # Display the futuristic data display using Streamlit's code block feature
     st.code(data_display, language="")
 
+
 # Generate description
 prompt = (
     "Human: Analyze the sensory input for a hyper-advanced AI humanoid:\n"