code: def deltaE(color1, color2,
             input_space="sRGB1", uniform_space="CAM02-UCS"):
      
  
      uniform1 = cspace_convert(color1, input_space, uniform_space)
      uniform2 = cspace_convert(color2, input_space, uniform_space)
      return np.sqrt(np.sum((uniform1 - uniform2) ** 2, axis=-1))
docs: Computes the :math:`\Delta E` distance between pairs of colors.
  
      :param input_space: The space the colors start out in. Can be anything
         recognized by :func:`cspace_convert`. Default: "sRGB1"
      :param uniform_space: Which space to perform the distance measurement
         in. This should be a uniform space like CAM02-UCS where
         Euclidean distance approximates similarity judgements, because
         otherwise the results of this function won't be very meaningful, but in
         fact any color space known to :func:`cspace_convert` will be accepted.
  
      By default, computes the euclidean distance in CAM02-UCS :math:`J'a'b'`
      space (thus giving :math:`\Delta E'`); for details, see
      :cite:`CAM02-UCS`. If you want the classic :math:`\Delta E^*_{ab}` defined
      by CIE 1976, use ``uniform_space="CIELab"``. Other good choices include
      ``"CAM02-LCD"`` and ``"CAM02-SCD"``.
  
      This function has no ability to perform :math:`\Delta E` calculations like
      CIEDE2000 that are not based on euclidean distances.
  
      This function is vectorized, i.e., color1, color2 may be arrays with shape
      (..., 3), in which case we compute the distance between corresponding
      pairs of colors.