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Python Imaging Library Overview

PIL 1.1.3 | March 12, 2002 | Fredrik Lundh, Matthew Ellis

Introduction

The Python Imaging Library adds image processing capabilities to your Python

interpreter.

This library provides extensive file format support, an efficient internal representation,

and fairly powerful image processing capabilities.

The core image library is designed for fast access to data stored in a few basic pixel

formats. It should provide a solid foundation for a general image processing tool.

Let's look at a few possible uses of this library:

Image Archives

The Python Imaging Library is ideal for for image archival and batch processing

applications. You can use the library to create thumbnails, convert between file formats,

print images, etc.

The current version identifies and reads a large number of formats. Write support is

intentionally restricted to the most commonly used interchange and presentation formats.

Image Display

The current release includes Tk PhotoImage and BitmapImage interfaces, as well as a

Windows DIB interface that can be used with PythonWin. For X and Mac displays, you can

use Jack Jansen's img library.

For debugging, there's also a show method in the Unix version which calls xv to display the

image.

Image Processing

The library contains some basic image processing functionality, including point operations,

filtering with a set of built-in convolution kernels, and colour space conversions.

The library also supports image resizing, rotation and arbitrary affine transforms.

There's a histogram method allowing you to pull some statistics out of an image. This can

be used for automatic contrast enhancement, and for global statistical analysis.

Tutorial

Using the Image Class

The most important class in the Python Imaging Library is the Image class, defined in the

module with the same name. You can create instances of this class in several ways; either

by loading images from files, processing other images, or creating images from scratch.

To load an image from a file, use the open function in the Image module.

>>> import Image

>>> im = Image.open("lena.ppm")

If successful, this function returns an Image object. You can now use instance attributes

to examine the file contents.

>>> print im.format, im.size, im.mode

PPM (512, 512) RGB

The format attribute identifies the source of an image. If the image was not read from a

file, it is set to None. The size attribute is a 2-tuple containing width and height (in

pixels). The mode attribute defines the number and names of the bands in the image, and

also the pixel type and depth. Common modes are "L" (luminance) for greyscale images,

"RGB" for true colour images, and "CMYK" for pre-press images.

If the file cannot be opened, an IOError exception is raised.

Once you have an instance of the Image class, you can use the methods defined by this

class to process and manipulate the image. For example, let's display the image we just

loaded:

>>> im.show()

(The standard version of show is not very efficient, since it saves the image to a

temporary file and calls the xv utility to display the image. If you don't have xv installed,

it won't even work. When it does work though, it is very handy for debugging and tests.)

The following sections provide an overview of the different functions provided in this

library.

Reading and Writing Images

The Python Imaging Library supports a wide variety of image file formats. To read files

from disk, use the open function in the Image module. You don't have to know the file

format to open a file. The library automatically determines the format based on the

contents of the file.

To save a file, use the save method of the Image class. When saving files, the name

becomes important. Unless you specify the format, the library uses the filename extension

to discover which file storage format to use.

Example: Convert files to JPEG

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