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