diff --git a/deepface/detectors/Yolov8nfaceWrapper.py b/deepface/detectors/Yolov8nfaceWrapper.py
index 9925e08..1ff7909 100644
--- a/deepface/detectors/Yolov8nfaceWrapper.py
+++ b/deepface/detectors/Yolov8nfaceWrapper.py
@@ -1,3 +1,6 @@
+from deepface.detectors import FaceDetector
+
+
 def build_model():
     import gdown
     import os
@@ -19,8 +22,6 @@ def build_model():
 
 def detect_face(face_detector, img, align=False):
     resp = []
-    confidence = -1
-    detected_face = None
 
     results = face_detector.predict(img, verbose=False, show=True, conf=0.25)[0]
 
@@ -30,22 +31,28 @@ def detect_face(face_detector, img, align=False):
         # print(f"Confidence: {confidence}, x: {x}, y: {y}, w: {w}, h: {h}")
 
         # print landmarks
-        landmarks = result.keypoints.tolist()
-        left_eye, right_eye = landmarks[0], landmarks[1]
+
         # print(result.keypoints.tolist())
         # print(f"Left eye: {left_eye}, right eye: {right_eye}")
 
         # add eyes landmarks to img
-        import cv2
+        # import cv2
 
-        img = cv2.circle(img, (int(left_eye[0]), int(left_eye[1])), 2, (0, 0, 255), 2)
-        img = cv2.circle(img, (int(right_eye[0]), int(right_eye[1])), 2, (0, 255, 0), 2)
+        # img = cv2.circle(img, (int(left_eye[0]), int(left_eye[1])), 2, (0, 0, 255), 2)
+        # img = cv2.circle(img, (int(right_eye[0]), int(right_eye[1])), 2, (0, 255, 0), 2)
         # change to top left corner, width, height
         x, y, w, h = int(x - w / 2), int(y - h / 2), int(w), int(h)
         detected_face = img[y : y + h, x : x + w].copy()
 
-        # if align:
-        #     raise NotImplementedError("`align` is not implemented for Yolov8Wrapper")
+        if align:
+            left_eye, right_eye, _, _, _ = result.keypoints.tolist()
+            # Check the landmarks confidence before alignment
+            # print(f"Left eye: {left_eye[2]}, right eye: {right_eye[2]}")
+            if left_eye[2] > 0.5 and right_eye[2] > 0.5:
+                # print("Aligning face")
+                # print(left_eye[:2], right_eye[:2])
+                detected_face = FaceDetector.alignment_procedure(detected_face, left_eye[:2], right_eye[:2])
+
         resp.append((detected_face, [x, y, w, h], confidence))
 
     return resp