Average colour of slic superpixel

I want to segment an image using slic superpixels and then replace the original colour of a superpixel with the average colour of said superpixel.

import numpy as np
import matplotlib.pyplot as plt
from skimage import io
from skimage.segmentation import slic, mark_boundaries
from skimage.data import astronaut
from skimage.measure import regionprops

img = astronaut()
segments = slic(img, n_segments=512, compactness=10,
            multichannel=True,
            enforce_connectivity=True,
            convert2lab=True)
regions = regionprops(segments, intensity_image=img)

I get the errorValueError: Label and intensity image must have thesame shape. Segments shape is (512,512) and img shape in (512,512,3). What is the correct use of regionprops in my case?

According to the documentation, regionprops can only quantify a grey-value image, and won't work for color.

A simple solution would be to measure average intensity in each channel separately, and combine the results:

out = np.empty_like(img)
for ii in range(3):
   regions = regionprops(segments, intensity_image=img[:,:,ii])
   # paint, and write to out[:,:,ii]

Using DIPlib this can be done quite simply (disclaimer: I'm an author):

import diplib as dip

segments = segments.astype('uint32')  # 64-bit types not accepted by DIPlib
msr = dip.MeasurementTool.Measure(segments, img, ['Mean'])
out = dip.ObjectToMeasurement(segments, msr['Mean'])
out.Show()