import cv2
import numpy as np

"""
not sure how you're reading images in but this is it

img = cv2.imread(???,0)

"""
imgb,imgg,imgr = cv2.split(img)


histb = np.histogram(imgb.flatten(),256,[0,256])
binsb = np.histogram(imgb.flatten(),256,[0,256])

cdfb = hist.cumsum()
cdfb_normalized = cdfb * histb.max()/ cdfb.max()

cdfb_m = np.ma.masked_equal(cdfb_m,0)
cdfb_m = (cdfb_m - cdfb_m.min())*255/(cdfb_m.max()-cdfb_m.min())
cdfb = np.ma.filled(cdfb_m,0).astype('uint8')

"

histg = np.histogram(imgg.flatten(),256,[0,256])
binsg = np.histogram(imgg.flatten(),256,[0,256])

cdfg = histg.cumsum()
cdfg_normalized = cdfg * histg.max()/ cdfg.max()

cdfg_m = np.ma.masked_equal(cdfg_m,0)
cdfg_m = (cdfg_m - cdfg_m.min())*255/(cdfg_m.max()-cdfg_m.min())
cdfg = np.ma.filled(cdfg_m,0).astype('uint8')

"

histr = np.histogram(imgr.flatten(),256,[0,256])
binsr = np.histogram(imgr.flatten(),256,[0,256])

cdfr = hist.cumsum()
cdfr_normalized = cdfr * histr.max()/ cdfr.max()

cdfr_m = np.ma.masked_equal(cdfr,0)
cdfr_m = (cdf_m - cdf_m.min())*255/(cdfr_m.max()-cdfr_m.min())
cdfr = np.ma.filled(cdfr_m,0).astype('uint8')

imgb = cv2.merge((b,g,r))

img2 = cdf[img]