import cv2import numpy as npbins = 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 ydef 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 yif __name__ == '__main__': import sys if len(sys.argv)>1: im = cv2.imread(sys.argv[1]) else : im = cv2.imread('../cpp/lena.jpg') print "usage : python hist.py <image_file>" 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() 
