Quick and Dirty Colour Histogram of a masked image in OpenCV

colourhist.py

import cv2
import numpy as np
import matplotlib.pyplot as plt

im = cv2.imread('IMG_3545S.JPG')

# convert to greyscale for easy thresholding
imgray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)

# get a threshold - basically splits the image into black and white
thresh = cv2.threshold(imgray, 127, 255, cv2.THRESH_BINARY)[1]

# invert it. This is the mask we're gonna be using
invertMask = cv2.bitwise_not(thresh, thresh) 

# calculate histograms!
histB = cv2.calcHist([im[...,0]], [0], invertMask, [256], [0,256])  # im[...,0] is the Blue channel
histG = cv2.calcHist([im[...,1]], [0], invertMask, [256], [0,256])  # im[...,1] is the Green channel
histR = cv2.calcHist([im[...,2]], [0], invertMask, [256], [0,256])  # im[...,2] is the Red channel
hist = cv2.calcHist([im], [0], invertMask, [256], [0,256])  # general histogram

#plot all the things!
fig = plt.figure()
plt.plot(histB, color='b') # plots histogram for the blue channel with a blue line
plt.plot(histG, color='g')
plt.plot(histR, color='r')
plt.plot(hist, color='k') # plots general histogram with a black line

plt.savefig('histogram.png')