new_contents: import cv2
  import numpy as np
  from pyA20.gpio import gpio
  from pyA20.gpio import port
  from time import sleep
  
  # initialize the gpio module
  gpio.init()
  
  # setup the ports
  gpio.setcfg(port.PA11, gpio.OUTPUT)  # DIR1
  gpio.setcfg(port.PA12, gpio.OUTPUT)  # STEP1
  gpio.setcfg(port.PA1, gpio.OUTPUT)   # DIR2
  gpio.setcfg(port.PA6, gpio.OUTPUT)   # STEP2
  
  # gpio
  gpio.output(port.PA11, gpio.LOW)
  gpio.output(port.PA12, gpio.LOW)
  gpio.output(port.PA1, gpio.LOW)
  gpio.output(port.PA6, gpio.LOW)
  
  
  dire = 0
  sleep(0.5)
  step = 0
  time = 0.1
  
  while True:
      # step
      gpio.output(port.PA12, gpio.HIGH)
      gpio.output(port.PA6, gpio.HIGH)
      sleep(0.0008)
      gpio.output(port.PA12, gpio.LOW)
      gpio.output(port.PA6, gpio.LOW)
      sleep(0.0008)
      step = step + 1
      
      # change direction
      if step > 2000:
          step = 0
          if dire:
              gpio.output(port.PA11, gpio.LOW)
              gpio.output(port.PA1, gpio.LOW)
              dire = 0
          else:
              gpio.output(port.PA11, gpio.HIGH)
              gpio.output(port.PA1, gpio.HIGH)
              dire = 1
  
  
  
  # ---------------------------------------------------------------------------------
  # image processing examples
  
  # generating the kernels
  kernel_sharpen_1 = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
   
  # Camera 0 is the integrated web cam on my netbook
  camera_port = 0
   
  #Number of frames to throw away while the camera adjusts to light levels
  ramp_frames = 60
   
  # Now we can initialize the camera capture object with the cv2.VideoCapture class.
  # All it needs is the index to a camera port.
  camera = cv2.VideoCapture(camera_port)
  
  print("Taking image...")
  # Captures a single image from the camera and returns it in PIL format
  def get_image():
   # read is the easiest way to get a full image out of a VideoCapture object.
   retval, im = camera.read()
   return im
   
  # Ramp the camera - these frames will be discarded and are only used to allow v4l2
  # to adjust light levels, if necessary
  for i in xrange(ramp_frames):
   temp = get_image()
  # Take the actual image we want to keep
  camera_capture = get_image()
  
  print("Processing image...")
  # grayscale
  image = cv2.cvtColor(camera_capture, cv2.COLOR_BGR2GRAY)
  # Pixelate
  #image = cv2.resize(image, (100,75))
  
  # applying different kernels to the input image
  output_1 = cv2.filter2D(image, -1, kernel_sharpen_1)
  
  cv2.imshow('Original', cv2.resize(image, (640,480)))
  cv2.imshow('Sharpening', cv2.resize(output_1, (640,480)))
  cv2.waitKey(0)
  
  #file = "/home/orangepi/image.png"
  # A nice feature of the imwrite method is that it will automatically choose the
  # correct format based on the file extension you provide. Convenient!
  #cv2.imwrite(file, camera_capture)
   
  # You'll want to release the camera, otherwise you won't be able to create a new
  # capture object until your script exits
  del(camera)
  
subject: Create plot.py