CPSC120B
Fundamentals of Computer Science

PPM Module

• We’ve already done some image manipulation
• But it was per-pixel so it was possible to read treat the PPM file as a 1-dimensional list
• Today we are going to do more complicated image manipulation that requires pixel operations using neighboring pixels
• This requires a 2D list, or matrix, of pixel data
• You know how to read PPM files and how to create matrices

• But to save you some time, you can use a module I created that does that for you

  import ppm
  
  image = ppm.read_image("glorious_image.ppm")
  pixel = image[0][0]

• The read_image function returns a 2D list of pixels

• Each pixel is represented with a list of three integers, for the red, green, and blue channels

  import ppm
  
  image = ppm.read_image("glorious_image.ppm")
  pixel = image[0][0]
  red = pixel[0]
  green = pixel[1]
  blue = pixel[2]

Modifying Images

• If you want to do something for every pixel in the image, need to use nested loops to iterate over all combinations of row and column values

  import ppm
  
  image = ppm.read_image("glorious_image.ppm")
  for row in ppm:
      for col in ppm:
          pixel = image[row][col][1] = 0
          pixel = image[row][col][2] = 0

Writing Images

• Writing a 2D list of pixels to a PPM file is as easy as reading

  import ppm
  
  ppm.write_image("boring_image.ppm", image)

• Just specify the file name and the 2D list of pixels

• Warning: the ppm module does no imput verification, you must specify a 2D list of lists containing 3 integers, anything else will cause it to fail in unclear ways

Copying Images

• Sometimes you need to create a new image, without modifying the old one

• Be careful, you can not copy a list with an assignment statement due to aliasing

  image = ppm.read_image("glorious_image.ppm")
  image_copy = image # DANGER! This is an alias, not a copy

• To actually copy an image, you need to create a new 2D list

  image = ppm.read_image("glorious_image.ppm")
  num_rows = len(image)
  num_cols = len(image[0])
  new_image = []
  for row in range(num_rows):
      new_row = []
      for col in range(num_cols):
          pixel = image[row][col]
          new_pixel = [pixel[0], pixel[1], pixel[2]]
          new_row.append(new_pixel)
      new_image.append(new_row)

Lab