computeMinMax(pixel_val,  min,  max);  //  先算图像的最大和最小值 
for  (i  =  0;  i  <  nNumPixels;  i++) 
  disp_pixel_val[i]  =  (pixel_val[i]  -  min)*255.0/(double)(max-min);   

def matrix2uint8(matrix):
  ''' 
matrix must be a numpy array NXN
Returns uint8 version
  '''
  m_min= np.min(matrix)
  m_max= np.max(matrix)
  matrix = matrix-m_min
  return(np.array(np.rint( (matrix-m_min)/float(m_max-m_min) * 255.0),dtype=np.uint8))
  #np.rint, Round elements of the array to the nearest integer.

def preprocess(img, crop=True, resize=True, dsize=(224, 224)):
  if img.dtype == np.uint8:
    img = img / 255.0

  if crop:
    short_edge = min(img.shape[:2])
    yy = int((img.shape[0] - short_edge) / 2)
    xx = int((img.shape[1] - short_edge) / 2)
    crop_img = img[yy: yy + short_edge, xx: xx + short_edge]
  else:
    crop_img = img

  if resize:
    norm_img = imresize(crop_img, dsize, preserve_range=True)
  else:
    norm_img = crop_img

  return (norm_img).astype(np.float32)
def deprocess(img):
  return np.clip(img * 255, 0, 255).astype(np.uint8)