Update app.py

app.py

@@ -535,7 +535,7 @@ def detect_logos(pil_image):
         'Logo Positions': positions_str}
 
 
-def analyze_face_features(image, confidence_threshold=0.3):
+def analyze_face_features(image):
     #GDPR -- exclude gender and race inference
 
     # BGR format for deepface
@@ -563,15 +563,8 @@ def analyze_face_features(image, confidence_threshold=0.3):
             "surprise": 0,
             "neutral": 0}
 
-    # Filter out low confidence detections
-    filtered_results = []
-    for face in results:
-        # Check for face_confidence key specifically based on your output
-        if 'face_confidence' in face and face['face_confidence'] >= confidence_threshold:
-            filtered_results.append(face)
-
     # If no faces meet confidence threshold, return zeros
-    if not filtered_results:
+    if not results:
         return {
             "angry": 0,
             "disgust": 0,
@@ -593,14 +586,14 @@ def analyze_face_features(image, confidence_threshold=0.3):
     }
 
     # process faces
-    for face in filtered_results:
+    for face in results:
         for emotion, value in face['emotion'].items():
             emotion_lower = emotion.lower()
             if emotion_lower in emotions_sum:
                 emotions_sum[emotion_lower] += value
 
     # average emtions
-    num_faces = len(filtered_results)
+    num_faces = len(results)
     avg_emotions = {emotion: round(value / num_faces, 2) for emotion, value in emotions_sum.items()}
 
     result = {