Making single channel image from multichannel images (RGB in this example).

flatim.py

import numpy as np
from PIL import Image

# Open a multichannel image
# In this example, an RGB image

fname = r"C:\Users\Conor\Downloads\PXL_20240304_174814563.MP.jpg"
im = Image.open(fname)
arr = np.array(im,dtype=np.uint8)

# Some different ways to flatten the image to greyscale

r,g,b = np.squeeze(np.dsplit(arr,arr.shape[2]),arr.shape[-1])
meanarr = np.array(np.round(np.mean(arr,axis=2)),dtype=np.uint8)
medianarr=np.array(np.median(arr,axis=2),dtype=np.uint8)
maxarr = np.max(arr,axis=2)
minarr = np.min(arr,axis=2)

im.save("splitA_original.tif")
Image.fromarray(r).save("splitB_R.tif")
Image.fromarray(g).save("splitC_B.tif")
Image.fromarray(b).save("splitD_B.tif")
Image.fromarray(meanarr).save("splitE_Mean.tif")
Image.fromarray(medianarr).save("splitF_Median.tif")
Image.fromarray(maxarr).save("splitG_Max.tif")
Image.fromarray(minarr).save("splitH_Min.tif")