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#!/usr/bin/env python
''' This is a sample for histogram plotting for RGB images and grayscale images for better understanding of colour distribution
Benefit : Learn how to draw histogram of images
Get familier with cv.calcHist, cv.equalizeHist,cv.normalize and some drawing functions
Level : Beginner or Intermediate
Functions : 1) hist_curve : returns histogram of an image drawn as curves
2) hist_lines : return histogram of an image drawn as bins ( only for grayscale images )
Usage : python hist.py <image_file>
Abid Rahman 3/14/12 debug Gary Bradski
'''
# Python 2/3 compatibility
from __future__ import print_function
import numpy as np
import cv2 as cv
bins = np.arange(256).reshape(256,1)
def hist_curve(im):
h = np.zeros((300,256,3))
if len(im.shape) == 2:
color = [(255,255,255)]
elif im.shape[2] == 3:
color = [ (255,0,0),(0,255,0),(0,0,255) ]
for ch, col in enumerate(color):
hist_item = cv.calcHist([im],[ch],None,[256],[0,256])
cv.normalize(hist_item,hist_item,0,255,cv.NORM_MINMAX)
hist=np.int32(np.around(hist_item))
pts = np.int32(np.column_stack((bins,hist)))
cv.polylines(h,[pts],False,col)
y=np.flipud(h)
return y
def hist_lines(im):
h = np.zeros((300,256,3))
if len(im.shape)!=2:
print("hist_lines applicable only for grayscale images")
#print("so converting image to grayscale for representation"
im = cv.cvtColor(im,cv.COLOR_BGR2GRAY)
hist_item = cv.calcHist([im],[0],None,[256],[0,256])
cv.normalize(hist_item,hist_item,0,255,cv.NORM_MINMAX)
hist = np.int32(np.around(hist_item))
for x,y in enumerate(hist):
cv.line(h,(x,0),(x,y[0]),(255,255,255))
y = np.flipud(h)
return y
def main():
import sys
if len(sys.argv)>1:
fname = sys.argv[1]
else :
fname = 'lena.jpg'
print("usage : python hist.py <image_file>")
im = cv.imread(cv.samples.findFile(fname))
if im is None:
print('Failed to load image file:', fname)
sys.exit(1)
gray = cv.cvtColor(im,cv.COLOR_BGR2GRAY)
print(''' Histogram plotting \n
Keymap :\n
a - show histogram for color image in curve mode \n
b - show histogram in bin mode \n
c - show equalized histogram (always in bin mode) \n
d - show histogram for gray image in curve mode \n
e - show histogram for a normalized image in curve mode \n
Esc - exit \n
''')
cv.imshow('image',im)
while True:
k = cv.waitKey(0)
if k == ord('a'):
curve = hist_curve(im)
cv.imshow('histogram',curve)
cv.imshow('image',im)
print('a')
elif k == ord('b'):
print('b')
lines = hist_lines(im)
cv.imshow('histogram',lines)
cv.imshow('image',gray)
elif k == ord('c'):
print('c')
equ = cv.equalizeHist(gray)
lines = hist_lines(equ)
cv.imshow('histogram',lines)
cv.imshow('image',equ)
elif k == ord('d'):
print('d')
curve = hist_curve(gray)
cv.imshow('histogram',curve)
cv.imshow('image',gray)
elif k == ord('e'):
print('e')
norm = cv.normalize(gray, gray, alpha = 0,beta = 255,norm_type = cv.NORM_MINMAX)
lines = hist_lines(norm)
cv.imshow('histogram',lines)
cv.imshow('image',norm)
elif k == 27:
print('ESC')
cv.destroyAllWindows()
break
print('Done')
if __name__ == '__main__':
print(__doc__)
main()
cv.destroyAllWindows()
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