jpg_histogram_calculation.py

import numpy as np
import cv2

src = cv2.imread('cows.jpg')
bgr_planes = cv2.split(src)

histSize = 256
histRange = (0, 256) # the upper boundary is exclusive
accumulate = False
b_hist = cv2.calcHist(bgr_planes, [0], None, [histSize], histRange, accumulate=accumulate)
g_hist = cv2.calcHist(bgr_planes, [1], None, [histSize], histRange, accumulate=accumulate)
r_hist = cv2.calcHist(bgr_planes, [2], None, [histSize], histRange, accumulate=accumulate)

hist_w = 512
hist_h = 400
bin_w = int(round( hist_w/histSize ))
histImage = np.zeros((hist_h, hist_w, 3), dtype=np.uint8)
cv2.normalize(b_hist, b_hist, alpha=0, beta=hist_h, norm_type=cv2.NORM_MINMAX)
cv2.normalize(g_hist, g_hist, alpha=0, beta=hist_h, norm_type=cv2.NORM_MINMAX)
cv2.normalize(r_hist, r_hist, alpha=0, beta=hist_h, norm_type=cv2.NORM_MINMAX)

for i in range(1, histSize):
    cv2.line(histImage, ( bin_w*(i-1), hist_h - int(b_hist[i-1]) ),
            ( bin_w*(i), hist_h - int(b_hist[i]) ),
            ( 255, 0, 0), thickness=2)
    cv2.line(histImage, ( bin_w*(i-1), hist_h - int(g_hist[i-1]) ),
            ( bin_w*(i), hist_h - int(g_hist[i]) ),
            ( 0, 255, 0), thickness=2)
    cv2.line(histImage, ( bin_w*(i-1), hist_h - int(r_hist[i-1]) ),
            ( bin_w*(i), hist_h - int(r_hist[i]) ),
            ( 0, 0, 255), thickness=2)
cv2.imshow('Source', src)
cv2.imshow('calcHist', histImage)

cv2.waitKey(0)
cv2.destroyAllWindows()