IMAGE PROCESSING LIBRARY
(PIL)
This is a package that you can import into python and it has
quite a few methods that you can process image files with.
There are loaders for the majority of the popular file formats
The following import is required
from PIL import Image
The above works already in Anaconda. If you are building
your own world using IDLE then you would need to download
PIL and install in your environment.
Auto generates x values here!
EXAMPLE COMMANDS IN PIL
The Image module is quite useful. Here are some examples
from PIL import Image
im = Image.open("bride.jpg") #Read in the image
im.rotate(45) #Returns a rotated image, 45 degrees
im.crop(box) # Returns a copy of a rect. sub-region
im.filter(filter) #Returns a copy of an image filtered by the given
#filter. For a list of available filters, see the ImageFilter module.
im.load() #Returns a high speed pixel access object.
im.resize() # Returns the image resized.
im.save(“Name”) #Save the image into file “Name”
STRUCTURE OF A 24 BIT IMAGE
Location=(col,row)
(14,14)
Contents=(R,G,B) tuple i.e. (255,34,128)
cols,rows=im.size
rows=18 and cols=35
LOOKING AT EVERY PIXEL
In order to process each pixel in the image we need to use a double
loop. Here is a simple example.
00
01
for c in range(3): #col values
0 2 col 0
for r in range(5): #row values
03
print c,r
04
10
11
1 2 col 1
13
14
20
21
2 2 col 2
23
24
ANTIALISING
This is a process that is used in image production that
smooths out hard edges with a visual trick. Here is an
example.
antialiased
no antialising
PAINT.NET ANTIALISING
Every image processing program has a button or icon to click to turn on/off
antialising. The above is paint.nets method. Note you must be in one of the
drawing tools, ie pen to see the control. Turn it off or on BEFORE you draw.
I CREATED THIS IMAGE
WITHOUT ANTIALISING
Lets turn this red to grey
CONVERT RED PIXELS TO GRAY BY
LOOPING THRU EVERY PIXEL
import matplotlib.pyplot as plt
from PIL import Image
im = Image.open('thingsnoanti.png') # read in image
pix = im.load() #allows fast access for pixel access
cols,rows=im.size #get dimensions from size tuple
#look at every single pixel and if red turn it to gray. Capice?!
for r in range(rows):
for c in range(cols):
if (pix[c,r] == (255,0,0)): #if pixel is red
pix[c,r]=(220,220,220) #set it gray
plt.imshow(im)
plt.show()
Note that you can do anything you want to every pixel using the above
method. Just change the blue lines.
USING FILTERS
The filter operations (BLUR, SMOOTH, SHARPEN etc) will
loop thru the entire image for you.
Here is the result of blur
as applied to our original
image.
AND HERE IS THE CODE
import matplotlib.pyplot as plt
from PIL import Image
from PIL import ImageFilter
im = Image.open('thingsnoanti.png')
plt.figure(1)
#work on figure 1
plt.imshow(im) #show original image
plt.show()
im1 = im.filter(ImageFilter.BLUR) #lets blur it
plt.figure(2) #Work on figure 2
plt.imshow(im1) #show new image
plt.show()
From ImageFilter module
BLUR
CONTOUR
DETAIL
EDGE_ENHANCE
EDGE_ENHANCE_MORE
EMBOSS
FIND_EDGES
SMOOTH
SMOOTH_MORE
SHARPEN
PLOT A HISTOGRAM OF A
GRAY-SCALE IMAGE
import matplotlib.pyplot as plt
from PIL import Image
im = Image.open('sea.gif')
plt.figure(1)
plt.imshow(im) #show original image
plt.show()
hist = im.histogram()
#note that the hist here is a list not an image
plt.figure(2)
plt.plot(hist) #So we must plot the list NOT imshow()
plt.show()
HERE IS AN EXAMPLE