          grids = self._constants["warp_lm_grids"]
          slices = self._constants["tgt_slices"]
  
          batch_dst = (batch_dst_points + np.random.normal(size=batch_dst_points.shape,
                                                           scale=2.0)).astype("int32")
  
          face_cores = [cv2.convexHull(np.concatenate([src[17:], dst[17:]], axis=0))
                        for src, dst in zip(batch_src_points, batch_dst)]
  
          batch_src = np.append(batch_src_points, edge_anchors, axis=1)
 
</s> remove                       for src, dst in zip(batch_src_points, batch_dst)]
 </s> add                       for src, dst in zip(batch_src_points.astype("int32"),
                                          batch_dst.astype("int32"))] </s> remove         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()
 </s> add         l_eye = np.array(l_eye_points + l_brow_points).reshape((-1, 2)).astype('int32').flatten()
        r_eye = np.array(r_eye_points + r_brow_points).reshape((-1, 2)).astype('int32').flatten()
 </s> remove         aligned_landmarks_68 = cv2.transform(aligned_landmarks_68,  # pylint: disable=no-member
 </s> add         aligned_landmarks_68 = cv2.transform(aligned_landmarks_68,
 </s> remove         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> add         mouth = mouth.reshape((-1, 2)).astype('int32').flatten()
        l_eye_hull = cv2.convexHull(l_eye.reshape((-1, 2)))
        r_eye_hull = cv2.convexHull(r_eye.reshape((-1, 2)))
        mouth_hull = cv2.convexHull(mouth.reshape((-1, 2)))
 </s> remove                 item = np.concatenate(item)
                hull = cv2.convexHull(item).astype("int32")  # pylint: disable=no-member
 </s> add                 item = np.rint(np.concatenate(item)).astype("int32")
                hull = cv2.convexHull(item)
                                                         scale=2.0))
          grids = self._constants["warp_lm_grids"]
          slices = self._constants["tgt_slices"]
  
          batch_dst = (batch_dst_points + np.random.normal(size=batch_dst_points.shape,
                                                         scale=2.0))
  
          face_cores = [cv2.convexHull(np.concatenate([src[17:], dst[17:]], axis=0))
                        for src, dst in zip(batch_src_points, batch_dst)]
  
          batch_src = np.append(batch_src_points, edge_anchors, axis=1)
keep keep keep keep replace keep keep keep keep keep
 Landmarks stored and used as floating point numbers (#928)

* remove and fix int adjustments
* masking rounding 
lib/training_data.py