mirror of
https://github.com/opencv/opencv.git
synced 2024-12-28 11:58:13 +08:00
117 lines
3.5 KiB
Python
Executable File
117 lines
3.5 KiB
Python
Executable File
#!/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 cv2.calcHist, cv2.equalizeHist,cv2.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
|
|
'''
|
|
|
|
import cv2
|
|
import numpy as np
|
|
|
|
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 = cv2.calcHist([im],[ch],None,[256],[0,256])
|
|
cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
|
|
hist=np.int32(np.around(hist_item))
|
|
pts = np.int32(np.column_stack((bins,hist)))
|
|
cv2.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 = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
|
|
hist_item = cv2.calcHist([im],[0],None,[256],[0,256])
|
|
cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
|
|
hist=np.int32(np.around(hist_item))
|
|
for x,y in enumerate(hist):
|
|
cv2.line(h,(x,0),(x,y),(255,255,255))
|
|
y = np.flipud(h)
|
|
return y
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
|
import sys
|
|
|
|
if len(sys.argv)>1:
|
|
fname = sys.argv[1]
|
|
else :
|
|
fname = '../cpp/lena.jpg'
|
|
print "usage : python hist.py <image_file>"
|
|
|
|
im = cv2.imread(fname)
|
|
|
|
if im is None:
|
|
print 'Failed to load image file:', fname
|
|
sys.exit(1)
|
|
|
|
gray = cv2.cvtColor(im,cv2.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 color image in curve mode \n
|
|
e - show histogram for a normalized image in curve mode \n
|
|
Esc - exit \n
|
|
'''
|
|
|
|
cv2.imshow('image',im)
|
|
while True:
|
|
k = cv2.waitKey(0)&0xFF
|
|
if k == ord('a'):
|
|
curve = hist_curve(im)
|
|
cv2.imshow('histogram',curve)
|
|
cv2.imshow('image',im)
|
|
print 'a'
|
|
elif k == ord('b'):
|
|
print 'b'
|
|
lines = hist_lines(im)
|
|
cv2.imshow('histogram',lines)
|
|
cv2.imshow('image',gray)
|
|
elif k == ord('c'):
|
|
print 'c'
|
|
equ = cv2.equalizeHist(gray)
|
|
lines = hist_lines(equ)
|
|
cv2.imshow('histogram',lines)
|
|
cv2.imshow('image',equ)
|
|
elif k == ord('d'):
|
|
print 'd'
|
|
curve = hist_curve(gray)
|
|
cv2.imshow('histogram',curve)
|
|
cv2.imshow('image',gray)
|
|
elif k == ord('e'):
|
|
print 'e'
|
|
norm = cv2.normalize(gray,alpha = 0,beta = 255,norm_type = cv2.NORM_MINMAX)
|
|
lines = hist_lines(norm)
|
|
cv2.imshow('histogram',lines)
|
|
cv2.imshow('image',norm)
|
|
elif k == 27:
|
|
print 'ESC'
|
|
cv2.destroyAllWindows()
|
|
break
|
|
cv2.destroyAllWindows()
|