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mAniPulAting imAgeS

If you have a digital camera or even if

you just upload photos from your phone

to Facebook, you probably cross paths with

digital image ﬁles all the time. You may know

how to use basic graphics software, such as Microsoft

Paint or Paintbrush, or even more advanced applica-

tions such as Adobe Photoshop. But if you need to

edit a massive number of images, editing them by

hand can be a lengthy, boring job.

Enter Python. Pillow is a third-party Python module for interacting

with image ﬁles. The module has several functions that make it easy to

crop, resize, and edit the content of an image. With the power to manipu-

late images the same way you would with software such as Microsoft Paint

or Adobe Photoshop, Python can automatically edit hundreds or thousands

of images with ease.

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388

Chapter 17

computer image fundamentals

In order to manipulate an image, you need to understand the basics of how

computers deal with colors and coordinates in images and how you can

work with colors and coordinates in Pillow. But before you continue, install

the

pillow

module. See Appendix A for help installing third-party modules.

Colors and RGBA Values

Computer programs often represent a color in an image as an RGBA value.

An RGBA value is a group of numbers that specify the amount of red, green,

blue, and alpha (or transparency) in a color. Each of these component values

is an integer from

(none at all) to

255

(the maximum). These RGBA values

are assigned to individual pixels; a pixel is the smallest dot of a single color

the computer screen can show (as you can imagine, there are millions of

pixels on a screen). A pixel’s RGB setting tells it precisely what shade of

color it should display. Images also have an alpha value to create RGBA

values. If an image is displayed on the screen over a background image

or desktop wallpaper, the alpha value determines how much of the back-

ground you can “see through” the image’s pixel.

In Pillow, RGBA values are represented by a tuple of four integer values.

For example, the color red is represented by

(255, 0, 0, 255)

. This color has

the maximum amount of red, no green or blue, and the maximum alpha

value, meaning it is fully opaque. Green is represented by

(0, 255, 0, 255)

and blue is

(0, 0, 255, 255)

. White, the combination of all colors, is

(255,

255, 255, 255)

, while black, which has no color at all, is

(0, 0, 0, 255)

If a color has an alpha value of

, it is invisible, and it doesn’t really mat-

ter what the RGB values are. After all, invisible red looks the same as invis-

ible black.

Pillow uses the standard color names that HTML uses. Table 17-1 lists a

selection of standard color names and their values.

table 17-1: Standard Color Names and Their RGBA Values

name

rgBA value

name

rgBA value

White

(255, 255, 255, 255)

Red

(255, 0, 0, 255)

Green

(0, 128, 0, 255)

Blue

(0, 0, 255, 255)

Gray

(128, 128, 128, 255)

Yellow

(255, 255, 0, 255)

Black

(0, 0, 0, 255)

Purple

(128, 0, 128, 255)

Pillow offers the

ImageColor.getcolor()

function so you don’t have to

memorize RGBA values for the colors you want to use. This function takes

a color name string as its ﬁrst argument, and the string

'RGBA'

as its second

argument, and it returns an RGBA tuple.

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Manipulating Images

389

To see how this function works, enter the following into the interactive

shell:

u >>> from PIL import ImageColor

v >>> ImageColor.getcolor('red', 'RGBA')

(255, 0, 0, 255)

w >>> ImageColor.getcolor('RED', 'RGBA')

(255, 0, 0, 255)

>>> ImageColor.getcolor('Black', 'RGBA')

(0, 0, 0, 255)

>>> ImageColor.getcolor('chocolate', 'RGBA')

(210, 105, 30, 255)

>>> ImageColor.getcolor('CornflowerBlue', 'RGBA')

(100, 149, 237, 255)

First, you need to import the

ImageColor

module from PIL u (not

from Pillow; you’ll see why in a moment). The color name string you pass

ImageColor.getcolor()

is case insensitive, so passing

'red'

v and passing

'RED'

w give you the same RGBA tuple. You can also pass more unusual

color names, like

'chocolate'

and

'Cornflower Blue'

Pillow supports a huge number of color names, from

'aliceblue'

'whitesmoke'

. You can ﬁnd the full list of more than 100 standard color

names in the resources at http://nostarch.com/automatestuff/.

Coordinates and Box Tuples

Image pixels are addressed with x- and y-coordinates, which respectively

specify a pixel’s horizontal and vertical location in an image. The origin is

the pixel at the top-left corner of the image and is speciﬁed with the nota-

tion (0, 0). The ﬁrst zero represents the x-coordinate, which starts at zero

at the origin and increases going from left to right. The second zero repre-

sents the y-coordinate, which starts at zero at the origin and increases going

Cmyk AnD rgB Coloring

In grade school you learned that mixing red, yellow, and blue paints can

form other colors; for example, you can mix blue and yellow to make green

paint‮ This is known as the subtractive color model, and it applies to dyes, inks,

and pigments‮ This is why color printers have CMYK ink cartridges: the Cyan

(blue), Magenta (red), Yellow, and blacK ink can be mixed together to form any

color‮

However, the physics of light uses what’s called an additive color model‮

When combining light (such as the light given off by your computer screen),

red, green, and blue light can be combined to form any other color‮ This is why

RGB values represent color in computer programs‮

390

Chapter 17

down the image. This bears repeating:

y-coordinates increase going downward,

which is the opposite of how you may

remember y-coordinates being used in

math class. Figure 17-1 demonstrates how

this coordinate system works.

Many of Pillow’s functions and

methods take a box tuple argument. This

means Pillow is expecting a tuple of four

integer coordinates that represent a rect-

angular region in an image. The four

integers are, in order, as follows:

• Left: The x-coordinate of the leftmost

edge of the box.

• Top: The y-coordinate of the top edge

of the box.

• Right: The x-coordinate of one pixel

to the right of the rightmost edge of

the box. This integer must be greater

than the left integer.

• Bottom: The y-coordinate of one pixel

lower than the bottom edge of the

box. This integer must be greater

than the top integer.

Note that the box includes the left

and top coordinates and goes up to but

does not include the right and bottom

coordinates. For example, the box tuple

(3, 1, 9, 6)

represents all the pixels in

the black box in Figure 17-2.

manipulating images with Pillow

Now that you know how colors and coordinates work in Pillow, let’s use

Pillow to manipulate an image. Figure 17-3 is the image that will be used

for all the interactive shell examples in this chapter. You can download it

from http://nostarch.com/automatestuff/.

Once you have the image ﬁle Zophie.png in your current working direc-

tory, you’ll be ready to load the image of Zophie into Python, like so:

>>> from PIL import Image

>>> catIm = Image.open('zophie.png')

Figure 17-2: The area represented

by the box tuple (3, 1, 9, 6)

x increases

y increases

(0,0)

(27,26)

Figure 17-1: The x- and y-coordinates

of a 27×26 image of some sort of

ancient data storage device

Manipulating Images

391

Figure 17-3: My cat Zophie. The camera

adds 10 pounds (which is a lot for a cat).

To load the image, you import the

Image

module from Pillow and call

Image.open()

, passing it the image’s ﬁlename. You can then store the loaded

image in a variable like

CatIm

. The module name of Pillow is

PIL

to make it

backward compatible with an older module called Python Imaging Library,

which is why you must run

from PIL import Image

instead of

from Pillow import

Image

. Because of the way Pillow’s creators set up the

pillow

module, you must

use the

from PIL import Image

form of

import

statement, rather than simply

import PIL

If the image ﬁle isn’t in the current working directory, change the

working directory to the folder that contains the image ﬁle by calling the

os.chdir()

function.

>>> import os

>>> os.chdir('C:\\folder_with_image_file')

The

Image.open()

function returns a value of the

Image

object data type,

which is how Pillow represents an image as a Python value. You can load an

Image

object from an image ﬁle (of any format) by passing the

Image.open()

function a string of the ﬁlename. Any changes you make to the

Image

object can be saved to an image ﬁle (also of any format) with the

save()

method. All the rotations, resizing, cropping, drawing, and other image

manipulations will be done through method calls on this

Image

object.

To shorten the examples in this chapter, I’ll assume you’ve imported

Pillow’s

Image

module and that you have the Zophie image stored in a variable

named

catIm

. Be sure that the zophie.png ﬁle is in the current working direc-

tory so that the

Image.open()

function can ﬁnd it. Otherwise, you will also have

to specify the full absolute path in the string argument to

Image.open()

392

Chapter 17

Working with the Image Data Type

Image

object has several useful attributes that give you basic information

about the image ﬁle it was loaded from: its width and height, the ﬁlename,

and the graphics format (such as JPEG, GIF, or PNG).

For example, enter the following into the interactive shell:

>>> from PIL import Image

>>> catIm = Image.open('zophie.png')

>>> catIm.size

u (816, 1088)

v >>> width, height = catIm.size

w >>> width

816

x >>> height

1088

>>> catIm.filename

'zophie.png'

>>> catIm.format

'PNG'

>>> catIm.format_description

'Portable network graphics'

y >>> catIm.save('zophie.jpg')

After making an

Image

object from Zophie.png and storing the

Image

object in

catIm

, we can see that the object’s

size

attribute contains a tuple

of the image’s width and height in pixels u. We can assign the values in the

tuple to

width

and

height

variables v in order to access with width w and

height x individually. The

filename

attribute describes the original ﬁle’s

name. The

format

and

format_description

attributes are strings that describe

the image format of the original ﬁle (with

format_description

being a bit

more verbose).

Finally, calling the

save()

method and passing it

'zophie.jpg'

saves a new

image with the ﬁlename zophie.jpg to your hard drive y. Pillow sees that the

ﬁle extension is .jpg and automatically saves the image using the JPEG image

format. Now you should have two images, zophie.png and zophie.jpg, on your

hard drive. While these ﬁles are based on the same image, they are not iden-

tical because of their different formats.

Pillow also provides the

Image.new()

function, which returns an

Image

object—much like

Image.open()

, except the image represented by

Image.new()

’s

object will be blank. The arguments to

Image.new()

are as follows:

• The string

'RGBA'

, which sets the color mode to RGBA. (There are other

modes that this book doesn’t go into.)

• The size, as a two-integer tuple of the new image’s width and height.

Manipulating Images

393

• The background color that the image should start with, as a four-

integer tuple of an RGBA value. You can use the return value of

the

ImageColor.getcolor()

function for this argument. Alternatively,

Image.new()

also supports just passing the string of the standard

color name.

For example, enter the following into the interactive shell:

>>> from PIL import Image

u >>> im = Image.new('RGBA', (100, 200), 'purple')

>>> im.save('purpleImage.png')

v >>> im2 = Image.new('RGBA', (20, 20))

>>> im2.save('transparentImage.png')

Here we create an

Image

object for an image that’s 100 pixels wide and

200 pixels tall, with a purple background u. This image is then saved to

the ﬁle purpleImage.png. We call

Image.new()

again to create another

Image

object, this time passing (20, 20) for the dimensions and nothing for the

background color v. Invisible black,

(0, 0, 0, 0)

, is the default color used if

no color argument is speciﬁed, so the second image has a transparent back-

ground; we save this 20×20 transparent square in transparentImage.png.

Cropping Images

Cropping an image means selecting a rectangular region inside an image

and removing everything outside the rectangle. The

crop()

method on

Image

objects takes a box tuple and returns an

Image

object representing

the cropped image. The cropping does not happen in place—that is, the

original

Image

object is left untouched, and the

crop()

method returns a

new

Image

object. Remeber that a boxed tuple—in this case, the cropped

section—includes the left column and top row of pixels but only goes up

to and does not include the right column and bottom row of pixels.

Enter the following into the interactive shell:

>>> croppedIm = catIm.crop((335, 345, 565, 560))

>>> croppedIm.save('cropped.png')

This makes a new

Image

object for the cropped image, stores the

object in

croppedIm

, and then calls

save()

croppedIm

to save the cropped

image in cropped.png. The new ﬁle cropped.png will be created from the ori-

ginal image, like in Figure 17-4.

394

Chapter 17

Figure 17-4: The new image will be just the cropped

section of the original image.

Copying and Pasting Images onto Other Images

The

copy()

method will return a new

Image

object with the same image

as the

Image

object it was called on. This is useful if you need to make

changes to an image but also want to keep an untouched version of the

original. For example, enter the following into the interactive shell:

>>> catIm = Image.open('zophie.png')

>>> catCopyIm = catIm.copy()

The

catIm

and

catCopyIm

variables contain two separate

Image

objects,

which both have the same image on them. Now that you have an

Image

object stored in

catCopyIm

, you can modify

catCopyIm

as you like and save

it to a new ﬁlename, leaving zophie.png untouched. For example, let’s try

modifying

catCopyIm

with the

paste()

method.

The

paste()

method is called on an

Image

object and pastes another image

on top of it. Let’s continue the shell example by pasting a smaller image onto

catCopyIm

>>> faceIm = catIm.crop((335, 345, 565, 560))

>>> faceIm.size

(230, 215)

>>> catCopyIm.paste(faceIm, (0, 0))

>>> catCopyIm.paste(faceIm, (400, 500))

>>> catCopyIm.save('pasted.png')

Manipulating Images

395

First we pass

crop()

a box tuple for the rectangular area in zophie.png

that contains Zophie’s face. This creates an

Image

object representing a

230×215 crop, which we store in

faceIm

. Now we can paste

faceIm

onto

catCopyIm

. The

paste()

method takes two arguments: a “source”

Image

object and a tuple of the x- and y-coordinates where you want to paste

the top-left corner of the source

Image

object onto the main

Image

object.

Here we call

paste()

twice on

catCopyIm

, passing (0, 0) the ﬁrst time and

(400, 500) the second time. This pastes

faceIm

onto

catCopyIm

twice: once

with the top-left corner of

faceIm

at (0, 0) on

catCopyIm

, and once with

the top-left corner of

faceIm

at (400, 500). Finally, we save the modiﬁed

catCopyIm

to pasted.png. The pasted.png image looks like Figure 17-5.

Figure 17-5: Zophie the cat, with her face

pasted twice

note

Despite their names, the

copy()

and

paste()

methods in Pillow do not use your com-

puter’s clipboard.

Note that the

paste()

method modiﬁes its

Image

object in place; it does

not return an

Image

object with the pasted image. If you want to call

paste()

but also keep an untouched version of the original image around, you’ll

need to ﬁrst copy the image and then call

paste()

on that copy.

Say you want to tile Zophie’s head across the entire image, as in

Figure 17-6. You can achieve this effect with just a couple

for

loops.

Continue the interactive shell example by entering the following:

>>> catImWidth, catImHeight = catIm.size

>>> faceImWidth, faceImHeight = faceIm.size

u >>> catCopyTwo = catIm.copy()

396

Chapter 17

v >>> for left in range(0, catImWidth, faceImWidth):

w for top in range(0, catImHeight, faceImHeight):

print(left, top)

catCopyTwo.paste(faceIm, (left, top))

0 0

0 215

0 430

0 645

0 860

0 1075

230 0

230 215

--snip--

690 860

690 1075

>>> catCopyTwo.save('tiled.png')

Here we store the width of height of

catIm

catImWidth

and

catImHeight

. At u we make a copy of

catIm

and store it in

catCopyTwo

. Now

that we have a copy that we can paste onto, we start looping to paste

faceIm

onto

catCopyTwo

. The outer

for

loop’s

left

variable starts at 0 and increases by

faceImWidth(230)

v. The inner

for

loop’s

top

variable start at 0 and increases

faceImHeight(215)

w. These nested

for

loops produce values for

left

and

top

to paste a grid of

faceIm

images over the

catCopyTwo

Image

object, as in

Figure 17-6. To see our nested loops working, we print

left

and

top

. After

the pasting is complete, we save the modiﬁed

catCopyTwo

to tiled.png.

Figure 17-6: Nested for loops used

with paste() to duplicate the cat’s face

(a dupli-cat, if you will).

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