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:
  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()