Class 32 — Monday April 19

Chrestomatics and patterning

I need a haiku — I can't think of one I like — Will you please help me

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Look both ways

• Back or ahead

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Agenda

• Problem solving

• Image manipulation

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Downloads

• Module manip.py

• Module blue.py

• Module negative.py

• Module bw.py

• Module mirror.py

• Module flip.py

• Module grey.py

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Some possible image transformations

		Duplicate
		Bluing
		Monotone
		Mirror
		Flip
		Sepia
		Grayscale
		Clockwise rotation
		Palette reduction
		Shrinking
		Pixelate

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Strategy — produce the new image from left to right and top to bottom

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Basic photo-manipulation problem-solving pattern

• Create a new image by making a copy that tweaks the original image

# get dimensions of the original

ow, oh = ...

 

# set dimensions of the new image

nw, nh = ...

 

# get a new appropriately sized image

new_image = Image.new( 'RGB', ( nw, nh ) )

 

# fill in every pixel of the new image

for nx in range( 0, nw ) : # consider every x value for the new image

  for ny in range( 0, nh ) : # in tandem with every y value for the image

 

  # set the spot to be filled in the new image

  nspot = (nx ,ny )

 

  # determine the corresponding spot of interest in the original

  ospot = ...

 

  # get the pixel at the ospot

  opixel = ...

 

  # determine the pixel for the new image

  npixel = ...

 

  # set the nspot in the new image

  ...

 

# return the filled in new image

return new_image

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Basic photo-manipulation problem-solving Python function

def manip( original, size, color, where ) :

  ''' Provide a pattern for image manipulation

  function size(): determines size of new image based on the original

  function color(): determines color of new image pixel based on an

  original pixel

  function where(): determines where on original to determine

  correspondent pixel for new image

  '''

  # set dimensions of the new image

  nw, nh = size( original )

  # get a new appropriately sized image

  new_image = Image.new( 'RGB', ( nw, nh ) )

  # fill in every pixel of the new image

  for nx in range( 0, nw ) : # consider every x value for the new image

  for ny in range( 0, nh ) : # in tandem with every y value for the image

  # set the spot to be filled in the new image

  nspot = ( nx, ny )

  # determine the corresponding spot of interest in the original

  ospot = where( nspot, nw, nh )

  # get the pixel at the ospot

  opixel = original.getpixel( ospot )

  # determine the pixel for the new image

  npixel = color( opixel )

  # set the nspot in the new image

  new_image.putpixel( nspot, npixel )

  # return the filled in new image

  return new_image

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Actual photo-manipulation problem-solving Python function

def same_size( image ) :

  return image.size

def same_color( pixel ) :

  return pixel

def same_where( spot, w, h ) :

  return spot

def manip( original, size=same_size, color=same_color, where=same_where ) :

  ...

 

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🦆 © 2022 Jim Cohoon

Resources from previous semesters are available.