Update app.py

app.py

@@ -106,21 +106,22 @@ def analyze_expression(image):
     
     # Analyze Action Units
     aus = {
-        'AU01': measurements['inner_brow_raise'] > 0.15,  # Inner Brow Raiser
-        'AU02': measurements['outer_brow_raise'] > 0.15,  # Outer Brow Raiser
-        'AU04': measurements['brow_furrow'] < 0.2,        # Brow Lowerer
-        'AU05': measurements['eye_opening'] > 0.12,       # Upper Lid Raiser
-        'AU12': measurements['smile_width'] > 0.45,       # Lip Corner Puller
-        'AU25': measurements['mouth_opening'] > 0.1,      # Lips Part
-        'AU26': measurements['mouth_opening'] > 0.2       # Jaw Drop
+        'AU01': measurements['inner_brow_raise'] > 0.12,  # Inner Brow Raiser - more sensitive
+        'AU02': measurements['outer_brow_raise'] > 0.12,  # Outer Brow Raiser - more sensitive
+        'AU04': measurements['brow_furrow'] < 0.25,       # Brow Lowerer - more lenient
+        'AU05': measurements['eye_opening'] > 0.1,        # Upper Lid Raiser - more sensitive
+        'AU12': measurements['smile_width'] > 0.4,        # Lip Corner Puller - more sensitive
+        'AU25': measurements['mouth_opening'] > 0.08,     # Lips Part - more sensitive
+        'AU26': measurements['mouth_opening'] > 0.15      # Jaw Drop - more sensitive
     }
     
-    # Emotion classification based on AUs
+    # Emotion classification based on AUs - more lenient conditions
     emotions = {
-        "Happy": (aus['AU12'] and measurements['lip_corner_height'] < 0),
-        "Sad": (not aus['AU12'] and measurements['lip_corner_height'] > 0 and (aus['AU01'] or aus['AU04'])),
-        "Surprised": (aus['AU01'] and aus['AU02'] and (aus['AU25'] or aus['AU26'])),
-        "Neutral": not any([aus['AU01'], aus['AU02'], aus['AU04'], aus['AU12'], aus['AU26']])
+        "Happy": (aus['AU12'] or measurements['lip_corner_height'] < -0.02),
+        "Sad": (measurements['lip_corner_height'] > 0.02 and (aus['AU01'] or aus['AU04'])),
+        "Surprised": ((aus['AU01'] or aus['AU02']) and (aus['AU25'] or aus['AU26'])),
+        "Neutral": not any([aus['AU01'], aus['AU02'], aus['AU04'], aus['AU12'], aus['AU26']]) and 
+                  abs(measurements['lip_corner_height']) < 0.02
     }
     
     # Create visualization
@@ -136,13 +137,15 @@ def analyze_expression(image):
         'jaw': (255, 128, 0)    # Orange
     }
     
-    # Draw landmarks with feature-specific colors
+    # Draw landmarks with feature-specific colors - made more visible
     for feature, points_list in FACIAL_LANDMARKS.items():
         color = colors.get(feature.split('_')[0], (0, 255, 0))
         for point_idx in points_list:
             pos = (int(landmarks.landmark[point_idx].x * w), 
                   int(landmarks.landmark[point_idx].y * h))
-            cv2.circle(viz_image, pos, 2, color, -1)
+            # Larger circles with white outline for visibility
+            cv2.circle(viz_image, pos, 4, (255, 255, 255), -1)  # White background
+            cv2.circle(viz_image, pos, 3, color, -1)  # Colored center
     
     # Add emotion text
     detected_emotions = [emotion for emotion, is_present in emotions.items() if is_present]