  
  landmarks_2D = numpy.stack( [ mean_face_x, mean_face_y ], axis=1 )
  
  def get_align_mat(face, size, should_align_eyes):
      mat_umeyama = umeyama(numpy.array(face.landmarks_as_xy()[17:]), landmarks_2D, True)[0:2]
  
      if should_align_eyes is False:
          return mat_umeyama
  
      mat_umeyama = mat_umeyama * size
 
</s> remove mean_face_x = numpy.array([
0.000213256, 0.0752622, 0.18113, 0.29077, 0.393397, 0.586856, 0.689483, 0.799124,
0.904991, 0.98004, 0.490127, 0.490127, 0.490127, 0.490127, 0.36688, 0.426036,
0.490127, 0.554217, 0.613373, 0.121737, 0.187122, 0.265825, 0.334606, 0.260918,
0.182743, 0.645647, 0.714428, 0.793132, 0.858516, 0.79751, 0.719335, 0.254149,
0.340985, 0.428858, 0.490127, 0.551395, 0.639268, 0.726104, 0.642159, 0.556721,
0.490127, 0.423532, 0.338094, 0.290379, 0.428096, 0.490127, 0.552157, 0.689874,
0.553364, 0.490127, 0.42689 ])

mean_face_y = numpy.array([
0.106454, 0.038915, 0.0187482, 0.0344891, 0.0773906, 0.0773906, 0.0344891,
0.0187482, 0.038915, 0.106454, 0.203352, 0.307009, 0.409805, 0.515625, 0.587326,
0.609345, 0.628106, 0.609345, 0.587326, 0.216423, 0.178758, 0.179852, 0.231733,
0.245099, 0.244077, 0.231733, 0.179852, 0.178758, 0.216423, 0.244077, 0.245099,
0.780233, 0.745405, 0.727388, 0.742578, 0.727388, 0.745405, 0.780233, 0.864805,
0.902192, 0.909281, 0.902192, 0.864805, 0.784792, 0.778746, 0.785343, 0.778746,
0.784792, 0.824182, 0.831803, 0.824182 ])

landmarks_2D = numpy.stack( [ mean_face_x, mean_face_y ], axis=1 )
 </s> add  </s> remove     landmarks = numpy.matrix(face.landmarks_as_xy())
 </s> add     landmarks = np.matrix(face.landmarks_as_xy())
 </s> remove     mat_align_eyes = numpy.matrix(mat_align_eyes)
 </s> add     mat_align_eyes = np.matrix(mat_align_eyes)
 </s> remove     transform_mat = numpy.delete(transform_mat, 2, 0)
 </s> add     transform_mat = np.delete(transform_mat, 2, 0)
 </s> remove     mat_umeyama = numpy.matrix(mat_umeyama)
 </s> add     mat_umeyama = np.matrix(mat_umeyama)

    """ Return the alignment Matrix """
    mat_umeyama = umeyama(np.array(face.landmarks_as_xy()[17:]),
                          LANDMARKS_2D,
                          True)[0:2]

  
  landmarks_2D = numpy.stack( [ mean_face_x, mean_face_y ], axis=1 )
  
  def get_align_mat(face, size, should_align_eyes):
    """ Return the alignment Matrix """
    mat_umeyama = umeyama(np.array(face.landmarks_as_xy()[17:]),
                          LANDMARKS_2D,
                          True)[0:2]
  
      if should_align_eyes is False:
          return mat_umeyama
  
      mat_umeyama = mat_umeyama * size
keep keep keep keep replace keep keep keep keep keep
 Fix convert-adjust (#531)

* Add dimensions to alignments + refactor

* Add frame_dims + funcs to DetectFaces. Add alignments lib

* Convert Adjust working

* Refactor and tidy up 
lib/aligner.py