old_contents: # Ulab is a numpy-like module for micropython, meant to simplify and speed up common
  # mathematical operations on arrays. This basic example shows mean/std on an image.
  #
  # NOTE: ndarrays cause the heap to be fragmented easily. If you run out of memory,
  # there's not much that can be done about it, lowering the resolution might help.
  
  import sensor, image, time, ulab as np
  
  sensor.reset()                      # Reset and initialize the sensor.
  sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to RGB565 (or GRAYSCALE)
  sensor.set_framesize(sensor.QQVGA)   # Set frame size to QVGA (320x240)
  clock = time.clock()                # Create a clock object to track the FPS.
  
  while (True):
      img = sensor.snapshot()         # Take a picture and return the image.
      a = np.array(img, dtype=np.uint8)
      print("mean: %d std:%d"%(np.mean(a), np.std(a)))
  
new_contents: # Ulab is a numpy-like module for micropython, meant to simplify and speed up common
  # mathematical operations on arrays. This basic example shows mean/std on an image.
  #
  # NOTE: ndarrays cause the heap to be fragmented easily. If you run out of memory,
  # there's not much that can be done about it, lowering the resolution might help.
  
  import sensor, image, time, ulab as np
  from ulab import numerical
  
  sensor.reset()                          # Reset and initialize the sensor.
  sensor.set_pixformat(sensor.GRAYSCALE)  # Set pixel format to RGB565 (or GRAYSCALE)
  sensor.set_framesize(sensor.QQVGA)      # Set frame size to QVGA (320x240)
  clock = time.clock()                    # Create a clock object to track the FPS.
  
  while (True):
      img = sensor.snapshot()         # Take a picture and return the image.
      a = np.array(img, dtype=np.uint8)
      print("mean: %d std:%d"%(numerical.mean(a), numerical.std(a)))
  
subject: Update ulab example.