Update app.py

app.py

@@ -69,13 +69,20 @@ def extract_features(audio_data, sample_rate, max_pad_len=174):
 
 # Initialize model and label encoder
 device = torch.device('cpu')  # Use CPU for deployment
+
+# FIXED: Use all 26 users that the model was trained on (from your training log)
+all_users = [
+    'user1', 'user2', 'user3', 'user4', 'user5', 'user6', 'user7', 'user8', 'user9', 'user10',
+    'user11', 'user12', 'user13', 'user14', 'user15', 'user16', 'user17', 'user19', 'user20',
+    'user21', 'user22', 'user23', 'user24', 'user25', 'user26', 'user27'
+]
+
+# Define which users are authorized for access (you can customize this)
 authorized_users = ['user1', 'user2', 'user3', 'user4', 'user5', 'user6', 'user7']
 
-# Initialize label encoder with known classes
+# Initialize label encoder with ALL classes the model was trained on
 label_encoder = LabelEncoder()
-# You'll need to update this with your actual user classes
-all_users = ['user1', 'user2', 'user3', 'user4', 'user5', 'user6', 'user7']  # Add all your users here
-label_encoder.fit(all_users)
+label_encoder.fit(sorted(all_users))  # Sort to ensure consistent ordering
 
 # Load model
 model = None
@@ -141,7 +148,7 @@ def predict_voice(audio_file, confidence_threshold=0.7):
                     f"❌ Access Denied - Unauthorized User",
                     predicted_user,
                     confidence_score,
-                    f"User '{predicted_user}' not in authorized list"
+                    f"User '{predicted_user}' recognized but not in authorized list"
                 )
             
             return (
@@ -163,7 +170,11 @@ def create_interface():
             
             This system uses advanced voice recognition to control access. Upload an audio file to test the system.
             
+            **Model Training:** Trained on 26 users (user1-user27, excluding user18)
+            
             **Authorized Users:** user1, user2, user3, user4, user5, user6, user7
+            
+            **Note:** The system can recognize all 26 users but only grants access to authorized ones.
             """
         )
         
@@ -217,7 +228,10 @@ def create_interface():
             3. **Set Threshold**: Adjust the confidence threshold (higher = more strict)
             4. **Analyze**: Click 'Analyze Voice' to process the audio
             
-            The system will determine if the speaker is authorized and grant/deny access accordingly.
+            The system will:
+            - Recognize the speaker among 26 trained users
+            - Check if they're in the authorized list
+            - Grant/deny access based on confidence and authorization
             """
         )