Class 34 — Wednesday, April 13

Chrestomatics and patterning

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

Look both ways

Back or ahead

Agenda

Problem solving

Image manipulation

Downloads

gradient.py

groovy.py

wahoo.py

Module manip.py

Module blue.py

Module bw.py

Module upleft.py

Module mirror.py

Image Dimension Reminders

Drawing comparisons to Pointillism

Image manipulation with nested loops: gradient.py

This program imports Image from pillow, and all random module functions.

Next, we define a 510 by 255 canvas.

Then, for every position closer to the right-hand side of the image, we set the pixel color to get progressively darker and darker until we get to black.

How we would change the code to have the color get progressively darker and darker from top to bottom, with the bottom edge of the image being black.

Brainstorm how we could create a gradient that transitions from one color to some color other than black.

Some possible image transformations

		Duplicate
		Bluing
		Two tone
		Upper left
		Mirror

Our photo manipulation strategy

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

Produce the new image by going left to right from top to bottom, starting with the top-left corner (0,0)

Determining a pixel for a new image will be a local decision (ie, not dependent on color values of nextdoor neighbor pixels)

Note: not all image manipulations can be carried out this way

Basic photo-manipulation problem-solving pattern

# 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
# consider every x value for the new image between x=0 and x=width-1
for nx in range( 0, nw ) :
# in tandem with every y value for the image between y=0 and y=height-1
for ny in range( 0, nh ) :

# select the new spot to be filled in the new image
nspot = (nx ,ny )

# determine the corresponding old spot of interest in the original
ospot = ...

# get the pixel value -- that is, the color-- that is, the rgb value-- at the ospot
opixel = ...

# determine the pixel value-- that is, the rgb color value-- for the new image
npixel = ...

# set the nspot in the new image
...

# return the filled in new image
return new_image

Basic photo-manipulation problem-solving Python function

def manip( original, size, color, at ) :
''' Provide a pattern for image manipulation
function size(): determines new image size based on the original
function color(): determines new pixel's color based on the original pixel's color
function at(): determines new pixel location relative to original
'''

# 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 = at( 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

Actual photo-manipulation problem-solving Python function

def same_size( image ) :
return image.size

def same_color( pixel ) :
return pixel

def same_at( spot, w, h ) :
return spot

def manip( original, size=same_size, color=same_color, at=same_at ) :
...