#!/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()