The ImageFilter module contains a number of pre-defined filters such as BLUR, CONTOUR, DETAIL, EDGE_ENHANCE, EMBOSS, SHARPEN, SMOOTH, etc. These filters can be used with the ```Image.filter()``` method. 

An example: 
``` 
from PIL import ImageFilter

im1 = im.filter(ImageFilter.BLUR)

im2 = im.filter(ImageFilter.MinFilter(3))
im3 = im.filter(ImageFilter.MinFilter)
```

Filters

The ```point()``` method can be used to translate the pixel of an image. This method can be combined with ```paste()``` to selectively modify an image. 

```
# split the image into individual bands
source = im.split()

R, G, B = 0, 1, 2

# select regions where red is less than 100
mask = source[R].point(lambda i: i < 100 and 255)

# process the green band
out = source[G].point(lambda i: i * 0.7)

# paste the processed band back, but only where red was < 100
source[G].paste(out, None, mask)

# build a new multiband image
im = Image.merge(im.mode, source)
```

Point Operations

The ImageEnhance module provides its own classes and functions that allows the user to adjust contrast, brightness, color balance, and sharpness. For all four functions, an enhancement factor of 1.0 gives the original image, and a factor of 0.0 gives a black/white/blurred image. 

For instance, to vary the sharpness of an image, use:
```
from PIL import ImageEnhance

enhancer = ImageEnhance.Sharpness(image)

for i in range(8):
    factor = i / 4.0
    enhancer.enhance(factor).show(f"Sharpness {factor:f}")
```

Advanced Enhancement

PIL provides a number of methods and modules that can be used to enhance images using
- Filters
- Point Operations
- Advanced enhancement

University of Michigan - Ann Arbor

The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file support, an efficient internal representation, and fairly powerful image processing capabilities. 

A few possible uses of this library includes
- Image Archives
- Image Display
- Image Processing 

pip can be installed with pip
```
pip install --upgrade pip
pip install -- upgrade Pillow
```

python imaging library (PIL / Pillow)

https://pillow.readthedocs.io/en/stable/index.html

PIL/Pillow documentaion

To create instances of this class, the user could load images from files, process other images, or create images from scratch. 

The most common usage would be to load an image from a file using the ```open()``` function, which returns an Image object. To examine the instance attributes, use functions ```format```, ```size```, and ```mode```.

To display the image just loaded, use ```show()```.

Using the Image class

To identify image files, use the following snippet:
```
import sys
from PIL import Image 

for infile in sys.argv[1:]:
   try:
      with Image.open(infile) as im:
          print (infile, im.format, f"{im.size}x{im.mode}")
   except OSError:
          pass
```

To convert file sto JPEG, use the following snippet: 
```
import os, sys
from PIL import Image

for infile in sys.argv[1:]:
    f, e = os.path.splitext(infile)
    outfile = f + ".jpg"
    if infile != outfile:
        try:
            with Image.open(infile) as im:
                im.save(outfile)
        except OSError:
            print("cannot convert", infile)
```

Reading and writing images

Image enhancement

Animation formats are taken in as image sequences, and supported formats include GIF, FLI/FLC, and TIFF files. PIL contains basic support for image sequences such as reading sequences and iterating through the sequence. 

To read a sequence: 
```
from PIL import Image

with Image.open("animation.gif") as im:
    im.seek(1) # skip to the second frame

    try:
        while 1:
            im.seek(im.tell()+1)
            # do something to im
    except EOFError:
        pass # end of sequence
```

To use the iterator class: 
```
from PIL import ImageSequence
for frame in ImageSequence.Iterator(im):
    # ...do something to frame...
```

Learn Before

Related

Learn After