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#!/usr/bin/env python
# Calculating and displaying 2D Hue-Saturation histogram of a color image
import sys
import cv2.cv as cv
def hs_histogram(src):
# Convert to HSV
hsv = cv.CreateImage(cv.GetSize(src), 8, 3)
cv.CvtColor(src, hsv, cv.CV_BGR2HSV)
# Extract the H and S planes
h_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
s_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
cv.Split(hsv, h_plane, s_plane, None, None)
planes = [h_plane, s_plane]
h_bins = 30
s_bins = 32
hist_size = [h_bins, s_bins]
# hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
h_ranges = [0, 180]
# saturation varies from 0 (black-gray-white) to
# 255 (pure spectrum color)
s_ranges = [0, 255]
ranges = [h_ranges, s_ranges]
scale = 10
hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)
cv.CalcHist([cv.GetImage(i) for i in planes], hist)
(_, max_value, _, _) = cv.GetMinMaxHistValue(hist)
hist_img = cv.CreateImage((h_bins*scale, s_bins*scale), 8, 3)
for h in range(h_bins):
for s in range(s_bins):
bin_val = cv.QueryHistValue_2D(hist, h, s)
intensity = cv.Round(bin_val * 255 / max_value)
cv.Rectangle(hist_img,
(h*scale, s*scale),
((h+1)*scale - 1, (s+1)*scale - 1),
cv.RGB(intensity, intensity, intensity),
cv.CV_FILLED)
return hist_img
if __name__ == '__main__':
src = cv.LoadImageM(sys.argv[1])
cv.NamedWindow("Source", 1)
cv.ShowImage("Source", src)
cv.NamedWindow("H-S Histogram", 1)
cv.ShowImage("H-S Histogram", hs_histogram(src))
cv.WaitKey(0)
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