Question

I'm having trouble creating a histogram using openCV (color segmentation)

Answer 1

Code:

from __future__ import print_function
from __future__ import division
import cv2 as cv
import numpy as np

## [Load image]
src = cv.imread(cv.samples.findFile('img.jpg'))
if src is None:
    print('Could not open or find the image')
    exit(0)

## [Separate the image in 3 places ( B, G and R )]
bgr_planes = cv.split(src)

## [Establish the number of bins]
histSize = 256

## [Set the ranges ( for B,G,R) )]
histRange = (0, 256) # the upper boundary is exclusive

## [Compute the histograms]
b_hist = cv.calcHist(bgr_planes, [0], None, [histSize], histRange, accumulate=False)
g_hist = cv.calcHist(bgr_planes, [1], None, [histSize], histRange, accumulate=False)
r_hist = cv.calcHist(bgr_planes, [2], None, [histSize], histRange, accumulate=False)

## [Draw the histograms for B, G and R]
hist_w = 512
hist_h = 400
bin_w = int(round( hist_w/histSize ))

histImage = np.zeros((hist_h, hist_w, 3), dtype=np.uint8)
## [Draw the histograms for B, G and R]

## [Normalize the result to ( 0, histImage.rows )]
cv.normalize(b_hist, b_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
cv.normalize(g_hist, g_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)
cv.normalize(r_hist, r_hist, alpha=0, beta=hist_h, norm_type=cv.NORM_MINMAX)

    
## [Draw for each channel]
for i in range(1, histSize):
    cv.line(histImage, ( bin_w*(i-1), hist_h - round(int(b_hist[i-1])) ),
            ( bin_w*(i), hist_h - round(int(b_hist[i])) ),
            ( 255, 0, 0), thickness=2)
    cv.line(histImage, ( bin_w*(i-1), hist_h - round(int(g_hist[i-1])) ),
            ( bin_w*(i), hist_h - round(int(g_hist[i])) ),
            ( 0, 255, 0), thickness=2)
    cv.line(histImage, ( bin_w*(i-1), hist_h - round(int(r_hist[i-1])) ),
            ( bin_w*(i), hist_h - round(int(r_hist[i])) ),
            ( 0, 0, 255), thickness=2)

## [Display]
cv.imshow("Source image", src );
cv.imshow('calcHist Demo', histImage)
cv.waitKey()

Code Snippet:

Original Image:

Histogram: