Update app.py

app.py

@@ -459,19 +459,34 @@ def create_sensation_map(width, height, keypoints):
 def create_heatmap(sensation_map, sensation_type):
     plt.figure(figsize=(10, 15))
     sns.heatmap(sensation_map[:, :, sensation_type], cmap='viridis')
-plt.title(f'{["Pain", "Pleasure", "Pressure", "Temperature", "Texture", "EM Field", "Tickle", "Itch", "Quantum", "Neural", "Proprioception", "Synesthesia"][sensation_type]} Sensation Map')
-plt.axis('off')
     
-buf = io.BytesIO()
-plt.savefig(buf, format='png')
-buf.seek(0)
+def create_heatmap(sensation_map, sensation_type):
+    plt.figure(figsize=(10, 15))
+    sns.heatmap(sensation_map[:, :, sensation_type], cmap='viridis')
+    plt.title(f'{["Pain", "Pleasure", "Pressure", "Temperature", "Texture", "EM Field", "Tickle", "Itch", "Quantum", "Neural", "Proprioception", "Synesthesia"][sensation_type]} Sensation Map')
+    plt.axis('off')
+    
+    buf = io.BytesIO()
+    plt.savefig(buf, format='png')
+    buf.seek(0)
     
-data = base64.b64encode(buf.getvalue()).decode('utf-8')
+    data = base64.b64encode(buf.getvalue()).decode('utf-8')
+    
+    plt.close()
+    
+    return f'data:image/png;base64,{data}'
+
+def generate_ai_response(keypoints, sensation_map):
+    num_keypoints = len(keypoints)
+    avg_sensations = np.mean(sensation_map, axis=(0, 1))
     
-plt.close()
+    response = f"I detect {num_keypoints} key points on the humanoid figure. "
+    response += "The average sensations across the body are:\n"
+    for i, sensation in enumerate(["Pain", "Pleasure", "Pressure", "Temperature", "Texture", "EM Field", 
+                                   "Tickle", "Itch", "Quantum", "Neural", "Proprioception", "Synesthesia"]):
+        response += f"{sensation}: {avg_sensations[i]:.2f}\n"
     
-return 
-f'data:image/png;base64,{data}'
+    return response
 
 # Streamlit app
 st.title("NeuraSense AI - Humanoid Touch Point Detection")
@@ -505,22 +520,11 @@ if uploaded_file is not None:
 
     # Generate AI response based on the image and sensations
     if st.button("Generate AI Response"):
-        # You can customize this part to generate more specific responses based on the detected keypoints and sensations
         response = generate_ai_response(keypoints, sensation_map)
         st.write("AI Response:", response)
 
-def generate_ai_response(keypoints, sensation_map):
-    # This is a simple example. You can make this more sophisticated based on your needs.
-    num_keypoints = len(keypoints)
-    avg_sensations = np.mean(sensation_map, axis=(0, 1))
-    
-    response = f"I detect {num_keypoints} key points on the humanoid figure. "
-    response += "The average sensations across the body are:\n"
-    for i, sensation in enumerate(["Pain", "Pleasure", "Pressure", "Temperature", "Texture", "EM Field", 
-                                   "Tickle", "Itch", "Quantum", "Neural", "Proprioception", "Synesthesia"]):
-        response += f"{sensation}: {avg_sensations[i]:.2f}\n"
-    
-    return response
+
+   
 
 
 # Create futuristic human-like avatar