Update app.py

app.py

@@ -340,17 +340,29 @@ AVATAR_WIDTH = 600
 AVATAR_HEIGHT = 800
 
 
-# Create heatmap function
+
+def create_heatmap(sensation_map):
+    # Calculate the overall sensitivity by taking the mean across all sensations
     overall_sensitivity = np.mean(sensation_map, axis=2)
+    
+    # Create a figure and axis
     fig, ax = plt.subplots(figsize=(10, 15))
+    
+    # Generate the heatmap
     sns.heatmap(overall_sensitivity, cmap='YlOrRd', alpha=0.7, cbar=False, ax=ax)
+    
+    # Remove axes and labels
     ax.set_axis_off()
+    
+    # Convert the plot to an image
     buf = BytesIO()
     plt.savefig(buf, format='png', bbox_inches='tight', pad_inches=0)
     buf.seek(0)
     heatmap_img = Image.open(buf)
+    
     plt.close(fig)
-
+    
+    return heatmap_img
 # Your Streamlit app code goes here
 st.title("NeuraSense AI - Cyberpunk Edition")
 
@@ -507,7 +519,14 @@ def create_avatar_with_heatmap():
     avatar_img = create_avatar()
     heatmap_img = create_heatmap(avatar_sensation_map)
     heatmap_img = heatmap_img.resize((AVATAR_WIDTH, AVATAR_HEIGHT))
-    combined_img = Image.alpha_composite(avatar_img.convert('RGBA'), heatmap_img.convert('RGBA'))
+    heatmap_img = heatmap_img.convert('RGBA')
+    
+    # Adjust alpha channel of heatmap
+    data = np.array(heatmap_img)
+    data[:, :, 3] = data[:, :, 3] * 0.5  # Reduce opacity to 50%
+    heatmap_img = Image.fromarray(data)
+    
+    combined_img = Image.alpha_composite(avatar_img.convert('RGBA'), heatmap_img)
     return combined_img
 
 # Create the avatar with heatmap