code: def _from_p(self, mode):
          
          self._check_modes(("P", "PA"))
  
          if not self.palette:
              raise RuntimeError("Can't convert palettized image, missing palette.")
          pal = np.array(self.palette)
          pal = da.from_array(pal, chunks=pal.shape)
  
          if pal.shape[1] == 4:
              # colormap's alpha overrides data alpha
              mode = "RGBA"
              alpha = None
          elif self.mode.endswith("A"):
              # add a new/fake 'bands' dimension to the end
              alpha = self.data.sel(bands="A").data[..., None]
              mode = mode + "A" if not mode.endswith("A") else mode
          else:
              alpha = None
  
          flat_indexes = self.data.sel(bands='P').data.ravel().astype('int64')
          dim_sizes = ((key, val) for key, val in self.data.sizes.items() if key != 'bands')
          dims, new_shape = zip(*dim_sizes)
          dims = dims + ('bands',)
          new_shape = new_shape + (pal.shape[1],)
          new_data = pal[flat_indexes].reshape(new_shape)
          coords = dict(self.data.coords)
          coords["bands"] = list(mode)
  
          if alpha is not None:
              new_arr = da.concatenate((new_data, alpha), axis=-1)
              data = xr.DataArray(new_arr, coords=coords, attrs=self.data.attrs, dims=dims)
          else:
              data = xr.DataArray(new_data, coords=coords, attrs=self.data.attrs, dims=dims)
  
          return data
docs: Convert the image from P or PA to RGB or RGBA.