mirror of
https://github.com/opencv/opencv.git
synced 2024-12-25 18:18:04 +08:00
126 lines
3.6 KiB
Python
Executable File
126 lines
3.6 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 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),(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 color 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()
|