          logger.trace("aligned_landmarks_68: %s, size: %s, padding: %s, dilation: %s",
                       aligned_landmarks_68, size, padding, dilation)
          scale = size - 2 * padding
          translation = padding
          pad_mat = np.matrix([[scale, 0.0, translation],
                               [0.0, scale, translation]])
          aligned_landmarks_68 = np.expand_dims(aligned_landmarks_68, axis=1)
          aligned_landmarks_68 = cv2.transform(aligned_landmarks_68,
                                               pad_mat,
                                               aligned_landmarks_68.shape)
          aligned_landmarks_68 = np.squeeze(aligned_landmarks_68)
 
</s> remove         aligned_landmarks_68 = cv2.transform(aligned_landmarks_68,
 </s> add         aligned_landmarks_68 = cv2.transform(aligned_landmarks_68,  # pylint: disable=no-member
 </s> remove         # pylint: disable=no-member
 </s> add  </s> remove     def get_feature_mask(aligned_landmarks_68, size,
                         padding=0, dilation=30):
 </s> add     def get_feature_mask(aligned_landmarks_68, size, padding=0, dilation=30):
 </s> remove 
        (l_start, l_end) = FACIAL_LANDMARKS_IDXS["left_eye"]
        (r_start, r_end) = FACIAL_LANDMARKS_IDXS["right_eye"]
        (m_start, m_end) = FACIAL_LANDMARKS_IDXS["mouth"]
        (n_start, n_end) = FACIAL_LANDMARKS_IDXS["nose"]
        (lb_start, lb_end) = FACIAL_LANDMARKS_IDXS["left_eyebrow"]
        (rb_start, rb_end) = FACIAL_LANDMARKS_IDXS["right_eyebrow"]
        (c_start, c_end) = FACIAL_LANDMARKS_IDXS["chin"]

        l_eye_points = aligned_landmarks_68[l_start:l_end].tolist()
        l_brow_points = aligned_landmarks_68[lb_start:lb_end].tolist()
        r_eye_points = aligned_landmarks_68[r_start:r_end].tolist()
        r_brow_points = aligned_landmarks_68[rb_start:rb_end].tolist()
        nose_points = aligned_landmarks_68[n_start:n_end].tolist()
        chin_points = aligned_landmarks_68[c_start:c_end].tolist()
        mouth_points = aligned_landmarks_68[m_start:m_end].tolist()
        l_eye_points = l_eye_points + l_brow_points
        r_eye_points = r_eye_points + r_brow_points
        mouth_points = mouth_points + nose_points + chin_points

        l_eye_hull = cv2.convexHull(np.array(l_eye_points).reshape(
            (-1, 2)).astype(int)).flatten().reshape((-1, 2))
        r_eye_hull = cv2.convexHull(np.array(r_eye_points).reshape(
            (-1, 2)).astype(int)).flatten().reshape((-1, 2))
        mouth_hull = cv2.convexHull(np.array(mouth_points).reshape(
            (-1, 2)).astype(int)).flatten().reshape((-1, 2))
 </s> add         l_eye_points = aligned_landmarks_68[42:48].tolist()
        l_brow_points = aligned_landmarks_68[22:27].tolist()
        r_eye_points = aligned_landmarks_68[36:42].tolist()
        r_brow_points = aligned_landmarks_68[17:22].tolist()
        nose_points = aligned_landmarks_68[27:36].tolist()
        chin_points = aligned_landmarks_68[8:11].tolist()
        mouth_points = aligned_landmarks_68[48:68].tolist()
        # TODO remove excessive reshapes and flattens

        l_eye = np.array(l_eye_points + l_brow_points).reshape((-1, 2)).astype(int).flatten()
        r_eye = np.array(r_eye_points + r_brow_points).reshape((-1, 2)).astype(int).flatten()
        mouth = np.array(mouth_points + nose_points + chin_points)
        mouth = mouth.reshape((-1, 2)).astype(int).flatten()
        l_eye_hull = cv2.convexHull(l_eye.reshape((-1, 2)))  # pylint: disable=no-member
        r_eye_hull = cv2.convexHull(r_eye.reshape((-1, 2)))  # pylint: disable=no-member
        mouth_hull = cv2.convexHull(mouth.reshape((-1, 2)))  # pylint: disable=no-member
 </s> remove             logger.trace("Loading aligned face: (size: %s, align_eyes: %s, dtype: %s)",
                         size, align_eyes, dtype)
 </s> add             logger.trace("Loading aligned face: (size: %s, dtype: %s)", size, dtype)
        pad_mat = np.matrix([[scale, 0.0, translation], [0.0, scale, translation]])

          logger.trace("aligned_landmarks_68: %s, size: %s, padding: %s, dilation: %s",
                       aligned_landmarks_68, size, padding, dilation)
          scale = size - 2 * padding
          translation = padding
        pad_mat = np.matrix([[scale, 0.0, translation], [0.0, scale, translation]])
        pad_mat = np.matrix([[scale, 0.0, translation], [0.0, scale, translation]])
          aligned_landmarks_68 = np.expand_dims(aligned_landmarks_68, axis=1)
          aligned_landmarks_68 = cv2.transform(aligned_landmarks_68,
                                               pad_mat,
                                               aligned_landmarks_68.shape)
          aligned_landmarks_68 = np.squeeze(aligned_landmarks_68)
keep keep keep keep replace replace keep keep keep keep keep
 Align eyes deprecation (#851)

* align eyes removal

* add align_eyes tool 
lib/aligner.py