new_contents: import cv2 as cv
  import numpy as np
  from matplotlib import pyplot as plt
  from scipy import misc
  
  img = cv.imread('data/ocr-gray.jpg',cv.IMREAD_GRAYSCALE)
  img = cv.medianBlur(img,7)
  ret,th1 = cv.threshold(img,127,255,cv.THRESH_BINARY)
  th2 = cv.adaptiveThreshold(img,255,cv.ADAPTIVE_THRESH_MEAN_C,\
              cv.THRESH_BINARY,15,8)
  th3 = cv.adaptiveThreshold(img,255,cv.ADAPTIVE_THRESH_GAUSSIAN_C,\
              cv.THRESH_BINARY,11,4)
  titles = ['Original Image', 'Global Thresholding (v = 127)',
              'Adaptive Mean Thresholding', 'Adaptive Gaussian Thresholding']
  images = [img, th1, th2, th3]
  
  
  print type(th2)
  
  
  #th2 = array(th2).convert('L')
  #th2 = 1 * (th2 > 128)
  #th2 = 0 * (th2 < 128)
  th2 = th2.astype(np.uint8)
  print th2.shape, th2.dtype
  
  cv.imwrite('data/ocr-bin.jpg', th2, [int(cv.IMWRITE_JPEG_QUALITY), 20])
  misc.imsave('data/misc-bin.jpg', th2)
  print th2.shape, th2.dtype
  
  for i in xrange(4):
      plt.subplot(2,2,i+1),plt.imshow(images[i],'gray')
      plt.title(titles[i])
      plt.xticks([]),plt.yticks([])
  plt.show()
subject: test opencv binarization.