Update app.py

app.py

@@ -54,14 +54,15 @@ def load_known_faces():
             image_path = os.path.join(folder_path, image_name)
             image = cv2.imread(image_path)
             gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-            # Detect face in the image
-            faces = mtcnn.detect(image)[0]  # Use the correct detect method
+            # Detect face in the image using mtcnn
+            faces, _ = mtcnn.detect(image)  # Use the correct method detect()
 
-            for face in faces:
-                x, y, w, h = face[0], face[1], face[2], face[3]
-                roi_gray = gray[y:y+h, x:x+w]
-                known_faces.append(roi_gray)
-                known_names.append(image_name.split('.')[0])  # Assuming file name is the person's name
+            if faces is not None:
+                for face in faces:
+                    x, y, w, h = face[0], face[1], face[2], face[3]
+                    roi_gray = gray[y:y+h, x:x+w]
+                    known_faces.append(roi_gray)
+                    known_names.append(image_name.split('.')[0])  # Assuming file name is the person's name
 
     # Train the recognizer with the known faces
     face_recognizer.train(known_faces, np.array([i for i in range(len(known_faces))]))
@@ -71,7 +72,7 @@ load_known_faces()
 # Process a single frame
 def process_frame(frame):
     gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    faces = mtcnn.detect(frame)[0]  # Use the correct detect method
+    faces, _ = mtcnn.detect(frame)  # Use the correct detect method
 
     result_text = ""  # Initialize result text