Pillow

Pillow is the ‘friendly’ PIL fork by Alex Clark and Contributors. PIL is the Python Imaging Library by Fredrik Lundh and Contributors.

To start using Pillow, please read the installation instructions.

You can get the source and contribute at https://github.com/python-imaging/Pillow. You can download archives and old versions from PyPI.

Installation

Warning

Pillow >= 2.1.0 no longer supports “import _imaging”. Please use “from PIL.Image import core as _imaging” instead.

Warning

Pillow >= 1.0 no longer supports “import Image”. Please use “from PIL import Image” instead.

Warning

PIL and Pillow currently cannot co-exist in the same environment. If you want to use Pillow, please remove PIL first.

Note

Pillow >= 2.0.0 supports Python versions 2.6, 2.7, 3.2, 3.3, 3.4

Note

Pillow < 2.0.0 supports Python versions 2.4, 2.5, 2.6, 2.7.

Simple installation

Note

The following instructions will install Pillow with support for most formats. See External libraries for the features you would gain by installing the external libraries first. This page probably also include specific instructions for your platform.

You can install Pillow with pip:

$ pip install Pillow

Or easy_install (for installing Python Eggs, as pip does not support them):

$ easy_install Pillow

Or download the compressed archive from PyPI, extract it, and inside it run:

$ python setup.py install

External libraries

Many of Pillow’s features require external libraries:

• libjpeg provides JPEG functionality.
  • Pillow has been tested with libjpeg versions 6b, 8, and 9
• zlib provides access to compressed PNGs
• libtiff provides group4 tiff functionality
  • Pillow has been tested with libtiff versions 3.x and 4.0
• libfreetype provides type related services
• littlecms provides color management
  • Pillow version 2.2.1 and below uses liblcms1, Pillow 2.3.0 and above uses liblcms2. Tested with 1.19 and 2.2.
• libwebp provides the Webp format.
  • Pillow has been tested with version 0.1.3, which does not read transparent webp files. Versions 0.3.0 and 0.4.0 support transparency.
• tcl/tk provides support for tkinter bitmap and photo images.
• openjpeg provides JPEG 2000 functionality.
  • Pillow has been tested with openjpeg 2.0.0.

If the prerequisites are installed in the standard library locations for your machine (e.g. /usr or /usr/local), no additional configuration should be required. If they are installed in a non-standard location, you may need to configure setuptools to use those locations (i.e. by editing setup.py and/or setup.cfg). Once you have installed the prerequisites, run:

$ pip install Pillow

Linux installation

Note

Fedora, Debian/Ubuntu, and ArchLinux include Pillow (instead of PIL) with their distributions. Consider using those instead of installing manually.

Note

You do not need to install all of the external libraries to get Pillow’s basics to work.

We do not provide binaries for Linux. If you didn’t build Python from source, make sure you have Python’s development libraries installed. In Debian or Ubuntu:

$ sudo apt-get install python-dev python-setuptools

Or for Python 3:

$ sudo apt-get install python3-dev python3-setuptools

In Fedora, the command is:

$ sudo yum install python-devel

Prerequisites are installed on Ubuntu 10.04 LTS with:

$ sudo apt-get install libtiff4-dev libjpeg62-dev zlib1g-dev \
    libfreetype6-dev tcl8.5-dev tk8.5-dev python-tk

Prerequisites are installed with on Ubuntu 12.04 LTS or Raspian Wheezy 7.0 with:

$ sudo apt-get install libtiff4-dev libjpeg8-dev zlib1g-dev \
    libfreetype6-dev liblcms2-dev libwebp-dev tcl8.5-dev tk8.5-dev python-tk

Prerequisites are installed on Fedora 20 with:

$ sudo yum install libtiff-devel libjpeg-devel libzip-devel freetype-devel \
    lcms2-devel libwebp-devel tcl-devel tk-devel

Mac OS X installation

Note

You do not need to install all of the external libraries to get Pillow’s basics to work.

We do not provide binaries for OS X, so you’ll need XCode to install Pillow. (XCode 4.2 on 10.6 will work with the Official Python binary distribution. Otherwise, use whatever XCode you used to compile Python.)

The easiest way to install the prerequisites is via Homebrew. After you install Homebrew, run:

$ brew install libtiff libjpeg webp littlecms

If you’ve built your own Python, then you should be able to install Pillow using:

$ pip install Pillow

Windows installation

We provide binaries for Windows in the form of Python Eggs and Python Wheels:

Python Eggs

Note

pip does not support Python Eggs; use easy_install instead.

$ easy_install Pillow

Python Wheels

Note

Experimental. Requires setuptools >=0.8 and pip >=1.4.1

$ pip install --use-wheel Pillow

If the above does not work, it’s likely because we haven’t uploaded a wheel for the latest version of Pillow. In that case, try pinning it to a specific version:

$ pip install --use-wheel Pillow==2.3.0

Platform support

Current platform support for Pillow. Binary distributions are contributed for each release on a volunteer basis, but the source should compile and run everywhere platform support is listed. In general, we aim to support all current versions of Linux, OS X, and Windows.

Note

Contributors please test on your platform, edit this document, and send a pull request.

Operating system	Supported	Tested Python versions	Tested Pillow versions	Tested processors
Mac OS X 10.8 Mountain Lion	Yes	2.6,2.7,3.2,3.3		x86-64
Mac OS X 10.7 Lion	Yes	2.6,2.7,3.2,3.3	2.2.0	x86-64
Redhat Linux 6	Yes	2.6		x86
CentOS 6.3	Yes	2.7,3.3		x86
Fedora 20	Yes	2.7,3.3	2.3.0	x86-64
Ubuntu Linux 10.04 LTS	Yes	2.6	2.3.0	x86,x86-64
Ubuntu Linux 12.04 LTS	Yes	2.6,2.7,3.2,3.3,PyPy2.1 2.7,3.2	2.3.0 2.3.0	x86,x86-64 ppc
Ubuntu Linux 13.10	Yes	2.7,3.2,3.3	2.3.0	x86
Raspian Wheezy	Yes	2.7,3.2	2.3.0	arm
Gentoo Linux	Yes	2.7,3.2	2.1.0	x86-64
Windows 7 Pro	Yes	2.7,3.2,3.3	2.2.1	x86-64
Windows Server 2008 R2 Enterprise	Yes	3.3		x86-64
Windows 8 Pro	Yes	2.6,2.7,3.2,3.3,3.4a3	2.2.0	x86,x86-64
Windows 8.1 Pro	Yes	2.6,2.7,3.2,3.3,3.4	2.3.0, 2.4.0	x86,x86-64

About Pillow

Goals

The fork authors’ goal is to foster active development of PIL through:

• Continuous integration testing via Travis CI
• Publicized development activity on GitHub
• Regular releases to the Python Package Index
• Solicitation for community contributions and involvement on Image-SIG

License

like PIL itself, Pillow is licensed under the MIT-like PIL Software License <http://www.pythonware.com/products/pil/license.htm>:

Software License

The Python Imaging Library (PIL) is

    Copyright © 1997-2011 by Secret Labs AB
    Copyright © 1995-2011 by Fredrik Lundh

By obtaining, using, and/or copying this software and/or its associated documentation, you agree that you have read, understood, and will comply with the following terms and conditions:

Permission to use, copy, modify, and distribute this software and its associated documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appears in all copies, and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of Secret Labs AB or the author not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission.

SECRET LABS AB AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL SECRET LABS AB OR THE AUTHOR BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

Why a fork?

PIL is not setuptools compatible. Please see this Image-SIG post for a more detailed explanation. Also, PIL’s current bi-yearly (or greater) release schedule is too infrequent to accomodate the large number and frequency of issues reported.

What about PIL?

Note

Prior to Pillow 2.0.0, very few image code changes were made. Pillow 2.0.0 added Python 3 support and includes many bug fixes from many contributors.

As more time passes since the last PIL release, the likelyhood of a new PIL release decreases. However, we’ve yet to hear an official “PIL is dead” announcement. So if you still want to support PIL, please report issues here first, then open the corresponding Pillow tickets here.

Please provide a link to the PIL ticket so we can track the issue(s) upstream.

Guides

Overview

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 and other Windows-based toolkits. Many other GUI toolkits come with some kind of PIL support.

For debugging, there’s also a show() method which saves an image to disk, and calls an external display utility.

Image Processing

The library contains 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:

>>> from PIL 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:

>>> from __future__ import print_function
>>> 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 color 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()

Note

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.

Convert files to JPEG

from __future__ import print_function
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:
            Image.open(infile).save(outfile)
        except IOError:
            print("cannot convert", infile)

A second argument can be supplied to the save() method which explicitly specifies a file format. If you use a non-standard extension, you must always specify the format this way:

Create JPEG thumbnails

from __future__ import print_function
import os, sys
from PIL import Image

size = (128, 128)

for infile in sys.argv[1:]:
    outfile = os.path.splitext(infile)[0] + ".thumbnail"
    if infile != outfile:
        try:
            im = Image.open(infile)
            im.thumbnail(size)
            im.save(outfile, "JPEG")
        except IOError:
            print("cannot create thumbnail for", infile)

It is important to note that the library doesn’t decode or load the raster data unless it really has to. When you open a file, the file header is read to determine the file format and extract things like mode, size, and other properties required to decode the file, but the rest of the file is not processed until later.

This means that opening an image file is a fast operation, which is independent of the file size and compression type. Here’s a simple script to quickly identify a set of image files:

Identify Image Files

from __future__ import print_function
import sys
from PIL import Image

for infile in sys.argv[1:]:
    try:
        with Image.open(infile) as im:
            print(infile, im.format, "%dx%d" % im.size, im.mode)
    except IOError:
        pass

Cutting, pasting, and merging images

The Image class contains methods allowing you to manipulate regions within an image. To extract a sub-rectangle from an image, use the crop() method.

Copying a subrectangle from an image

box = (100, 100, 400, 400)
region = im.crop(box)

The region is defined by a 4-tuple, where coordinates are (left, upper, right, lower). The Python Imaging Library uses a coordinate system with (0, 0) in the upper left corner. Also note that coordinates refer to positions between the pixels, so the region in the above example is exactly 300x300 pixels.

The region could now be processed in a certain manner and pasted back.

Processing a subrectangle, and pasting it back

region = region.transpose(Image.ROTATE_180)
im.paste(region, box)

When pasting regions back, the size of the region must match the given region exactly. In addition, the region cannot extend outside the image. However, the modes of the original image and the region do not need to match. If they don’t, the region is automatically converted before being pasted (see the section on Color transforms below for details).

Here’s an additional example:

Rolling an image

def roll(image, delta):
    "Roll an image sideways"

    xsize, ysize = image.size

    delta = delta % xsize
    if delta == 0: return image

    part1 = image.crop((0, 0, delta, ysize))
    part2 = image.crop((delta, 0, xsize, ysize))
    image.paste(part2, (0, 0, xsize-delta, ysize))
    image.paste(part1, (xsize-delta, 0, xsize, ysize))

    return image

For more advanced tricks, the paste method can also take a transparency mask as an optional argument. In this mask, the value 255 indicates that the pasted image is opaque in that position (that is, the pasted image should be used as is). The value 0 means that the pasted image is completely transparent. Values in-between indicate different levels of transparency.

The Python Imaging Library also allows you to work with the individual bands of an multi-band image, such as an RGB image. The split method creates a set of new images, each containing one band from the original multi-band image. The merge function takes a mode and a tuple of images, and combines them into a new image. The following sample swaps the three bands of an RGB image:

Splitting and merging bands

r, g, b = im.split()
im = Image.merge("RGB", (b, g, r))

Note that for a single-band image, split() returns the image itself. To work with individual color bands, you may want to convert the image to “RGB” first.

Geometrical transforms

The PIL.Image.Image class contains methods to resize() and rotate() an image. The former takes a tuple giving the new size, the latter the angle in degrees counter-clockwise.

Simple geometry transforms

out = im.resize((128, 128))
out = im.rotate(45) # degrees counter-clockwise

To rotate the image in 90 degree steps, you can either use the rotate() method or the transpose() method. The latter can also be used to flip an image around its horizontal or vertical axis.

Transposing an image

out = im.transpose(Image.FLIP_LEFT_RIGHT)
out = im.transpose(Image.FLIP_TOP_BOTTOM)
out = im.transpose(Image.ROTATE_90)
out = im.transpose(Image.ROTATE_180)
out = im.transpose(Image.ROTATE_270)

There’s no difference in performance or result between transpose(ROTATE) and corresponding rotate() operations.

A more general form of image transformations can be carried out via the transform() method.

Color transforms

The Python Imaging Library allows you to convert images between different pixel representations using the convert() method.

Converting between modes

im = Image.open("lena.ppm").convert("L")

The library supports transformations between each supported mode and the “L” and “RGB” modes. To convert between other modes, you may have to use an intermediate image (typically an “RGB” image).

Image enhancement

The Python Imaging Library provides a number of methods and modules that can be used to enhance images.

Filters

The ImageFilter module contains a number of pre-defined enhancement filters that can be used with the filter() method.

Applying filters

from PIL import ImageFilter
out = im.filter(ImageFilter.DETAIL)

Point Operations

The point() method can be used to translate the pixel values of an image (e.g. image contrast manipulation). In most cases, a function object expecting one argument can be passed to the this method. Each pixel is processed according to that function:

Applying point transforms

# multiply each pixel by 1.2
out = im.point(lambda i: i * 1.2)

Using the above technique, you can quickly apply any simple expression to an image. You can also combine the point() and paste() methods to selectively modify an image:

Processing individual bands

# 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)

Note the syntax used to create the mask:

imout = im.point(lambda i: expression and 255)

Python only evaluates the portion of a logical expression as is necessary to determine the outcome, and returns the last value examined as the result of the expression. So if the expression above is false (0), Python does not look at the second operand, and thus returns 0. Otherwise, it returns 255.

Enhancement

For more advanced image enhancement, you can use the classes in the ImageEnhance module. Once created from an image, an enhancement object can be used to quickly try out different settings.

You can adjust contrast, brightness, color balance and sharpness in this way.

Enhancing images

from PIL import ImageEnhance

enh = ImageEnhance.Contrast(im)
enh.enhance(1.3).show("30% more contrast")

Image sequences

The Python Imaging Library contains some basic support for image sequences (also called animation formats). Supported sequence formats include FLI/FLC, GIF, and a few experimental formats. TIFF files can also contain more than one frame.

When you open a sequence file, PIL automatically loads the first frame in the sequence. You can use the seek and tell methods to move between different frames:

Reading sequences

from PIL import Image

im = Image.open("animation.gif")
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

As seen in this example, you’ll get an EOFError exception when the sequence ends.

Note that most drivers in the current version of the library only allow you to seek to the next frame (as in the above example). To rewind the file, you may have to reopen it.

The following iterator class lets you to use the for-statement to loop over the sequence:

A sequence iterator class

class ImageSequence:
    def __init__(self, im):
        self.im = im
    def __getitem__(self, ix):
        try:
            if ix:
                self.im.seek(ix)
            return self.im
        except EOFError:
            raise IndexError # end of sequence

for frame in ImageSequence(im):
    # ...do something to frame...

Postscript printing

The Python Imaging Library includes functions to print images, text and graphics on Postscript printers. Here’s a simple example:

Drawing Postscript

from PIL import Image
from PIL import PSDraw

im = Image.open("lena.ppm")
title = "lena"
box = (1*72, 2*72, 7*72, 10*72) # in points

ps = PSDraw.PSDraw() # default is sys.stdout
ps.begin_document(title)

# draw the image (75 dpi)
ps.image(box, im, 75)
ps.rectangle(box)

# draw centered title
ps.setfont("HelveticaNarrow-Bold", 36)
w, h, b = ps.textsize(title)
ps.text((4*72-w/2, 1*72-h), title)

ps.end_document()

More on reading images

As described earlier, the open() function of the Image module is used to open an image file. In most cases, you simply pass it the filename as an argument:

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

If everything goes well, the result is an PIL.Image.Image object. Otherwise, an IOError exception is raised.

You can use a file-like object instead of the filename. The object must implement read(), seek() and tell() methods, and be opened in binary mode.

Reading from an open file

fp = open("lena.ppm", "rb")
im = Image.open(fp)

To read an image from string data, use the StringIO class:

Reading from a string

import StringIO

im = Image.open(StringIO.StringIO(buffer))

Note that the library rewinds the file (using seek(0)) before reading the image header. In addition, seek will also be used when the image data is read (by the load method). If the image file is embedded in a larger file, such as a tar file, you can use the ContainerIO or TarIO modules to access it.

Reading from a tar archive

from PIL import TarIO

fp = TarIO.TarIO("Imaging.tar", "Imaging/test/lena.ppm")
im = Image.open(fp)

Controlling the decoder

Some decoders allow you to manipulate the image while reading it from a file. This can often be used to speed up decoding when creating thumbnails (when speed is usually more important than quality) and printing to a monochrome laser printer (when only a greyscale version of the image is needed).

The draft() method manipulates an opened but not yet loaded image so it as closely as possible matches the given mode and size. This is done by reconfiguring the image decoder.

Reading in draft mode

from __future__ import print_function
im = Image.open(file)
print("original =", im.mode, im.size)

im.draft("L", (100, 100))
print("draft =", im.mode, im.size)

This prints something like:

original = RGB (512, 512)
draft = L (128, 128)

Note that the resulting image may not exactly match the requested mode and size. To make sure that the image is not larger than the given size, use the thumbnail method instead.

Concepts

The Python Imaging Library handles raster images; that is, rectangles of pixel data.

Bands

An image can consist of one or more bands of data. The Python Imaging Library allows you to store several bands in a single image, provided they all have the same dimensions and depth.

To get the number and names of bands in an image, use the getbands() method.

Mode

The mode of an image defines the type and depth of a pixel in the image. The current release supports the following standard modes:

• 1 (1-bit pixels, black and white, stored with one pixel per byte)
• L (8-bit pixels, black and white)
• P (8-bit pixels, mapped to any other mode using a color palette)
• RGB (3x8-bit pixels, true color)
• RGBA (4x8-bit pixels, true color with transparency mask)
• CMYK (4x8-bit pixels, color separation)
• YCbCr (3x8-bit pixels, color video format)
• I (32-bit signed integer pixels)
• F (32-bit floating point pixels)

PIL also provides limited support for a few special modes, including LA (L with alpha), RGBX (true color with padding) and RGBa (true color with premultiplied alpha). However, PIL doesn’t support user-defined modes; if you to handle band combinations that are not listed above, use a sequence of Image objects.

You can read the mode of an image through the mode attribute. This is a string containing one of the above values.

Size

You can read the image size through the size attribute. This is a 2-tuple, containing the horizontal and vertical size in pixels.

Coordinate System

The Python Imaging Library uses a Cartesian pixel coordinate system, with (0,0) in the upper left corner. Note that the coordinates refer to the implied pixel corners; the centre of a pixel addressed as (0, 0) actually lies at (0.5, 0.5).

Coordinates are usually passed to the library as 2-tuples (x, y). Rectangles are represented as 4-tuples, with the upper left corner given first. For example, a rectangle covering all of an 800x600 pixel image is written as (0, 0, 800, 600).

Palette

The palette mode (P) uses a color palette to define the actual color for each pixel.

Info

You can attach auxiliary information to an image using the info attribute. This is a dictionary object.

How such information is handled when loading and saving image files is up to the file format handler (see the chapter on Image file formats). Most handlers add properties to the info attribute when loading an image, but ignore it when saving images.

Filters

For geometry operations that may map multiple input pixels to a single output pixel, the Python Imaging Library provides four different resampling filters.

NEAREST

Pick the nearest pixel from the input image. Ignore all other input pixels.

BILINEAR

Use linear interpolation over a 2x2 environment in the input image. Note that in the current version of PIL, this filter uses a fixed input environment when downsampling.

BICUBIC

Use cubic interpolation over a 4x4 environment in the input image. Note that in the current version of PIL, this filter uses a fixed input environment when downsampling.

ANTIALIAS

Calculate the output pixel value using a high-quality resampling filter (a truncated sinc) on all pixels that may contribute to the output value. In the current version of PIL, this filter can only be used with the resize and thumbnail methods.

New in version 1.1.3.

Note that in the current version of PIL, the ANTIALIAS filter is the only filter that behaves properly when downsampling (that is, when converting a large image to a small one). The BILINEAR and BICUBIC filters use a fixed input environment, and are best used for scale-preserving geometric transforms and upsamping.

Porting existing PIL-based code to Pillow

Pillow is a functional drop-in replacement for the Python Imaging Library. To run your existing PIL-compatible code with Pillow, it needs to be modified to import the Image module from the PIL namespace instead of the global namespace. Change this:

import Image

to this:

from PIL import Image

The _imaging module has been moved. You can now import it like this:

from PIL.Image import core as _imaging

The image plugin loading mechanism has changed. Pillow no longer automatically imports any file in the Python path with a name ending in ImagePlugin.py. You will need to import your image plugin manually.

Reference

Image Module

The Image module provides a class with the same name which is used to represent a PIL image. The module also provides a number of factory functions, including functions to load images from files, and to create new images.

Examples

The following script loads an image, rotates it 45 degrees, and displays it using an external viewer (usually xv on Unix, and the paint program on Windows).

Open, rotate, and display an image (using the default viewer)

from PIL import Image
im = Image.open("bride.jpg")
im.rotate(45).show()

The following script creates nice 128x128 thumbnails of all JPEG images in the current directory.

Create thumbnails

from PIL import Image
import glob, os

size = 128, 128

for infile in glob.glob("*.jpg"):
    file, ext = os.path.splitext(infile)
    im = Image.open(infile)
    im.thumbnail(size, Image.ANTIALIAS)
    im.save(file + ".thumbnail", "JPEG")

Functions

PIL.Image.open(fp, mode='r')

Opens and identifies the given image file.

This is a lazy operation; this function identifies the file, but the file remains open and the actual image data is not read from the file until you try to process the data (or call the load() method). See new().

Parameters:

• file – A filename (string) or a file object. The file object must implement read(), seek(), and tell() methods, and be opened in binary mode.
• mode – The mode. If given, this argument must be “r”.

Returns:

An Image object.

Raises IOError:

If the file cannot be found, or the image cannot be opened and identified.

Image processing

PIL.Image.alpha_composite(im1, im2)

Alpha composite im2 over im1.

Parameters:

• im1 – The first image.
• im2 – The second image. Must have the same mode and size as the first image.

Returns:

An Image object.

PIL.Image.blend(im1, im2, alpha)

Creates a new image by interpolating between two input images, using a constant alpha.:

out = image1 * (1.0 - alpha) + image2 * alpha

Parameters:

• im1 – The first image.
• im2 – The second image. Must have the same mode and size as the first image.
• alpha – The interpolation alpha factor. If alpha is 0.0, a copy of the first image is returned. If alpha is 1.0, a copy of the second image is returned. There are no restrictions on the alpha value. If necessary, the result is clipped to fit into the allowed output range.

Returns:

An Image object.

PIL.Image.composite(image1, image2, mask)

Create composite image by blending images using a transparency mask.

Parameters:

• image1 – The first image.
• image2 – The second image. Must have the same mode and size as the first image.
• mask – A mask image. This image can can have mode “1”, “L”, or “RGBA”, and must have the same size as the other two images.

PIL.Image.eval(image, *args)

Applies the function (which should take one argument) to each pixel in the given image. If the image has more than one band, the same function is applied to each band. Note that the function is evaluated once for each possible pixel value, so you cannot use random components or other generators.

Parameters:

• image – The input image.
• function – A function object, taking one integer argument.

Returns:

An Image object.

PIL.Image.merge(mode, bands)

Merge a set of single band images into a new multiband image.

Parameters:

• mode – The mode to use for the output image.
• bands – A sequence containing one single-band image for each band in the output image. All bands must have the same size.

Returns:

An Image object.

Constructing images

PIL.Image.new(mode, size, color=0)

Creates a new image with the given mode and size.

Parameters:

• mode – The mode to use for the new image.
• size – A 2-tuple, containing (width, height) in pixels.
• color – What color to use for the image. Default is black. If given, this should be a single integer or floating point value for single-band modes, and a tuple for multi-band modes (one value per band). When creating RGB images, you can also use color strings as supported by the ImageColor module. If the color is None, the image is not initialised.

Returns:

An Image object.

PIL.Image.fromarray(obj, mode=None)

Creates an image memory from an object exporting the array interface (using the buffer protocol).

If obj is not contiguous, then the tobytes method is called and frombuffer() is used.

Parameters:

• obj – Object with array interface
• mode – Mode to use (will be determined from type if None)

Returns:

An image memory.

New in version 1.1.6.

PIL.Image.frombytes(mode, size, data, decoder_name='raw', *args)

Creates a copy of an image memory from pixel data in a buffer.

In its simplest form, this function takes three arguments (mode, size, and unpacked pixel data).

You can also use any pixel decoder supported by PIL. For more information on available decoders, see the section Writing Your Own File Decoder.

Note that this function decodes pixel data only, not entire images. If you have an entire image in a string, wrap it in a BytesIO object, and use open() to load it.

Parameters:

• mode – The image mode.
• size – The image size.
• data – A byte buffer containing raw data for the given mode.
• decoder_name – What decoder to use.
• args – Additional parameters for the given decoder.

Returns:

An Image object.

PIL.Image.fromstring(*args, **kw)

Deprecated alias to frombytes.

Deprecated since version 2.0.

PIL.Image.frombuffer(mode, size, data, decoder_name='raw', *args)

Creates an image memory referencing pixel data in a byte buffer.

This function is similar to frombytes(), but uses data in the byte buffer, where possible. This means that changes to the original buffer object are reflected in this image). Not all modes can share memory; supported modes include “L”, “RGBX”, “RGBA”, and “CMYK”.

Note that this function decodes pixel data only, not entire images. If you have an entire image file in a string, wrap it in a BytesIO object, and use open() to load it.

In the current version, the default parameters used for the “raw” decoder differs from that used for fromstring(). This is a bug, and will probably be fixed in a future release. The current release issues a warning if you do this; to disable the warning, you should provide the full set of parameters. See below for details.

Parameters:

• mode – The image mode.
• size – The image size.
• data – A bytes or other buffer object containing raw data for the given mode.
• decoder_name – What decoder to use.
• args –

  Additional parameters for the given decoder. For the default encoder (“raw”), it’s recommended that you provide the full set of parameters:

  frombuffer(mode, size, data, "raw", mode, 0, 1)
  

Returns:

An Image object.

New in version 1.1.4.

Registering plugins

Note

These functions are for use by plugin authors. Application authors can ignore them.

PIL.Image.register_open(id, factory, accept=None)

Register an image file plugin. This function should not be used in application code.

Parameters:

• id – An image format identifier.
• factory – An image file factory method.
• accept – An optional function that can be used to quickly reject images having another format.

PIL.Image.register_mime(id, mimetype)

Registers an image MIME type. This function should not be used in application code.

Parameters:

• id – An image format identifier.
• mimetype – The image MIME type for this format.

PIL.Image.register_save(id, driver)

Registers an image save function. This function should not be used in application code.

Parameters:

• id – An image format identifier.
• driver – A function to save images in this format.

PIL.Image.register_extension(id, extension)

Registers an image extension. This function should not be used in application code.

Parameters:

• id – An image format identifier.
• extension – An extension used for this format.

The Image Class

class PIL.Image.Image

This class represents an image object. To create Image objects, use the appropriate factory functions. There’s hardly ever any reason to call the Image constructor directly.

• open()
• new()
• frombytes()

An instance of the Image class has the following methods. Unless otherwise stated, all methods return a new instance of the Image class, holding the resulting image.

Image.convert(mode=None, matrix=None, dither=None, palette=0, colors=256)

Returns a converted copy of this image. For the “P” mode, this method translates pixels through the palette. If mode is omitted, a mode is chosen so that all information in the image and the palette can be represented without a palette.

The current version supports all possible conversions between “L”, “RGB” and “CMYK.” The matrix argument only supports “L” and “RGB”.

When translating a color image to black and white (mode “L”), the library uses the ITU-R 601-2 luma transform:

L = R * 299/1000 + G * 587/1000 + B * 114/1000

The default method of converting a greyscale (“L”) or “RGB” image into a bilevel (mode “1”) image uses Floyd-Steinberg dither to approximate the original image luminosity levels. If dither is NONE, all non-zero values are set to 255 (white). To use other thresholds, use the point() method.

Parameters:

• mode – The requested mode.
• matrix – An optional conversion matrix. If given, this should be 4- or 16-tuple containing floating point values.
• dither – Dithering method, used when converting from mode “RGB” to “P” or from “RGB” or “L” to “1”. Available methods are NONE or FLOYDSTEINBERG (default).
• palette – Palette to use when converting from mode “RGB” to “P”. Available palettes are WEB or ADAPTIVE.
• colors – Number of colors to use for the ADAPTIVE palette. Defaults to 256.

Return type:

Image

Returns:

An Image object.

The following example converts an RGB image (linearly calibrated according to ITU-R 709, using the D65 luminant) to the CIE XYZ color space:

rgb2xyz = (
    0.412453, 0.357580, 0.180423, 0,
    0.212671, 0.715160, 0.072169, 0,
    0.019334, 0.119193, 0.950227, 0 )
out = im.convert("RGB", rgb2xyz)

Image.copy()

Copies this image. Use this method if you wish to paste things into an image, but still retain the original.

Return type:Image Returns:An Image object.

Image.crop(box=None)

Returns a rectangular region from this image. The box is a 4-tuple defining the left, upper, right, and lower pixel coordinate.

This is a lazy operation. Changes to the source image may or may not be reflected in the cropped image. To break the connection, call the load() method on the cropped copy.

Parameters:box – The crop rectangle, as a (left, upper, right, lower)-tuple. Return type:Image Returns:An Image object.

Image.draft(mode, size)

NYI

Configures the image file loader so it returns a version of the image that as closely as possible matches the given mode and size. For example, you can use this method to convert a color JPEG to greyscale while loading it, or to extract a 128x192 version from a PCD file.

Note that this method modifies the Image object in place. If the image has already been loaded, this method has no effect.

Parameters:

• mode – The requested mode.
• size – The requested size.

Image.filter(filter)

Filters this image using the given filter. For a list of available filters, see the ImageFilter module.

Parameters:filter – Filter kernel. Returns:An Image object.

Image.getbands()

Returns a tuple containing the name of each band in this image. For example, getbands on an RGB image returns (“R”, “G”, “B”).

Returns:A tuple containing band names. Return type:tuple

Image.getbbox()

Calculates the bounding box of the non-zero regions in the image.

Returns:The bounding box is returned as a 4-tuple defining the left, upper, right, and lower pixel coordinate. If the image is completely empty, this method returns None.

Image.getcolors(maxcolors=256)

Returns a list of colors used in this image.

Parameters:maxcolors – Maximum number of colors. If this number is exceeded, this method returns None. The default limit is 256 colors. Returns:An unsorted list of (count, pixel) values.

Image.getdata(band=None)

Returns the contents of this image as a sequence object containing pixel values. The sequence object is flattened, so that values for line one follow directly after the values of line zero, and so on.

Note that the sequence object returned by this method is an internal PIL data type, which only supports certain sequence operations. To convert it to an ordinary sequence (e.g. for printing), use list(im.getdata()).

Parameters:band – What band to return. The default is to return all bands. To return a single band, pass in the index value (e.g. 0 to get the “R” band from an “RGB” image). Returns:A sequence-like object.

Image.getextrema()

Gets the the minimum and maximum pixel values for each band in the image.

Returns:For a single-band image, a 2-tuple containing the minimum and maximum pixel value. For a multi-band image, a tuple containing one 2-tuple for each band.

Image.getpixel(xy)

Returns the pixel value at a given position.

Parameters:xy – The coordinate, given as (x, y). Returns:The pixel value. If the image is a multi-layer image, this method returns a tuple.

Image.histogram(mask=None, extrema=None)

Returns a histogram for the image. The histogram is returned as a list of pixel counts, one for each pixel value in the source image. If the image has more than one band, the histograms for all bands are concatenated (for example, the histogram for an “RGB” image contains 768 values).

A bilevel image (mode “1”) is treated as a greyscale (“L”) image by this method.

If a mask is provided, the method returns a histogram for those parts of the image where the mask image is non-zero. The mask image must have the same size as the image, and be either a bi-level image (mode “1”) or a greyscale image (“L”).

Parameters:mask – An optional mask. Returns:A list containing pixel counts.

Image.offset(xoffset, yoffset=None)

Deprecated since version 2.0.

Note

New code should use PIL.ImageChops.offset().

Returns a copy of the image where the data has been offset by the given distances. Data wraps around the edges. If yoffset is omitted, it is assumed to be equal to xoffset.

Parameters:

• xoffset – The horizontal distance.
• yoffset – The vertical distance. If omitted, both distances are set to the same value.

Returns:

An Image object.

Image.paste(im, box=None, mask=None)

Pastes another image into this image. The box argument is either a 2-tuple giving the upper left corner, a 4-tuple defining the left, upper, right, and lower pixel coordinate, or None (same as (0, 0)). If a 4-tuple is given, the size of the pasted image must match the size of the region.

If the modes don’t match, the pasted image is converted to the mode of this image (see the convert() method for details).

Instead of an image, the source can be a integer or tuple containing pixel values. The method then fills the region with the given color. When creating RGB images, you can also use color strings as supported by the ImageColor module.

If a mask is given, this method updates only the regions indicated by the mask. You can use either “1”, “L” or “RGBA” images (in the latter case, the alpha band is used as mask). Where the mask is 255, the given image is copied as is. Where the mask is 0, the current value is preserved. Intermediate values can be used for transparency effects.

Note that if you paste an “RGBA” image, the alpha band is ignored. You can work around this by using the same image as both source image and mask.

Parameters:

• im – Source image or pixel value (integer or tuple).
• box –

  An optional 4-tuple giving the region to paste into. If a 2-tuple is used instead, it’s treated as the upper left corner. If omitted or None, the source is pasted into the upper left corner.

  If an image is given as the second argument and there is no third, the box defaults to (0, 0), and the second argument is interpreted as a mask image.

• mask – An optional mask image.

Image.point(lut, mode=None)

Maps this image through a lookup table or function.

Parameters:

• lut – A lookup table, containing 256 (or 65336 if self.mode==”I” and mode == “L”) values per band in the image. A function can be used instead, it should take a single argument. The function is called once for each possible pixel value, and the resulting table is applied to all bands of the image.
• mode – Output mode (default is same as input). In the current version, this can only be used if the source image has mode “L” or “P”, and the output has mode “1” or the source image mode is “I” and the output mode is “L”.

Returns:

An Image object.

Image.putalpha(alpha)

Adds or replaces the alpha layer in this image. If the image does not have an alpha layer, it’s converted to “LA” or “RGBA”. The new layer must be either “L” or “1”.

Parameters:alpha – The new alpha layer. This can either be an “L” or “1” image having the same size as this image, or an integer or other color value.

Image.putdata(data, scale=1.0, offset=0.0)

Copies pixel data to this image. This method copies data from a sequence object into the image, starting at the upper left corner (0, 0), and continuing until either the image or the sequence ends. The scale and offset values are used to adjust the sequence values: pixel = value*scale + offset.

Parameters:

• data – A sequence object.
• scale – An optional scale value. The default is 1.0.
• offset – An optional offset value. The default is 0.0.

Image.putpalette(data, rawmode='RGB')

Attaches a palette to this image. The image must be a “P” or “L” image, and the palette sequence must contain 768 integer values, where each group of three values represent the red, green, and blue values for the corresponding pixel index. Instead of an integer sequence, you can use an 8-bit string.

Parameters:data – A palette sequence (either a list or a string).

Image.putpixel(xy, value)

Modifies the pixel at the given position. The color is given as a single numerical value for single-band images, and a tuple for multi-band images.

Note that this method is relatively slow. For more extensive changes, use paste() or the ImageDraw module instead.

See:

• paste()
• putdata()
• ImageDraw

Parameters:

• xy – The pixel coordinate, given as (x, y).
• value – The pixel value.

Image.quantize(colors=256, method=None, kmeans=0, palette=None)

Image.resize(size, resample=0)

Returns a resized copy of this image.

Parameters:

• size – The requested size in pixels, as a 2-tuple: (width, height).
• resample – An optional resampling filter. This can be one of PIL.Image.NEAREST (use nearest neighbour), PIL.Image.BILINEAR (linear interpolation in a 2x2 environment), PIL.Image.BICUBIC (cubic spline interpolation in a 4x4 environment), or PIL.Image.ANTIALIAS (a high-quality downsampling filter). If omitted, or if the image has mode “1” or “P”, it is set PIL.Image.NEAREST.

Returns:

An Image object.

Image.rotate(angle, resample=0, expand=0)

Returns a rotated copy of this image. This method returns a copy of this image, rotated the given number of degrees counter clockwise around its centre.

Parameters:

• angle – In degrees counter clockwise.
• filter – An optional resampling filter. This can be one of PIL.Image.NEAREST (use nearest neighbour), PIL.Image.BILINEAR (linear interpolation in a 2x2 environment), or PIL.Image.BICUBIC (cubic spline interpolation in a 4x4 environment). If omitted, or if the image has mode “1” or “P”, it is set PIL.Image.NEAREST.
• expand – Optional expansion flag. If true, expands the output image to make it large enough to hold the entire rotated image. If false or omitted, make the output image the same size as the input image.

Returns:

An Image object.

Image.save(fp, format=None, **params)

Saves this image under the given filename. If no format is specified, the format to use is determined from the filename extension, if possible.

Keyword options can be used to provide additional instructions to the writer. If a writer doesn’t recognise an option, it is silently ignored. The available options are described later in this handbook.

You can use a file object instead of a filename. In this case, you must always specify the format. The file object must implement the seek, tell, and write methods, and be opened in binary mode.

Parameters:

• file – File name or file object.
• format – Optional format override. If omitted, the format to use is determined from the filename extension. If a file object was used instead of a filename, this parameter should always be used.
• options – Extra parameters to the image writer.

Returns:

None

Raises:

• KeyError – If the output format could not be determined from the file name. Use the format option to solve this.
• IOError – If the file could not be written. The file may have been created, and may contain partial data.

Image.seek(frame)

Seeks to the given frame in this sequence file. If you seek beyond the end of the sequence, the method raises an EOFError exception. When a sequence file is opened, the library automatically seeks to frame 0.

Note that in the current version of the library, most sequence formats only allows you to seek to the next frame.

See tell().

Parameters:frame – Frame number, starting at 0. Raises EOFError:  If the call attempts to seek beyond the end of the sequence.

Image.show(title=None, command=None)

Displays this image. This method is mainly intended for debugging purposes.

On Unix platforms, this method saves the image to a temporary PPM file, and calls the xv utility.

On Windows, it saves the image to a temporary BMP file, and uses the standard BMP display utility to show it (usually Paint).

Parameters:

• title – Optional title to use for the image window, where possible.
• command – command used to show the image

Image.split()

Split this image into individual bands. This method returns a tuple of individual image bands from an image. For example, splitting an “RGB” image creates three new images each containing a copy of one of the original bands (red, green, blue).

Returns:A tuple containing bands.

Image.tell()

Returns the current frame number. See seek().

Returns:Frame number, starting with 0.

Image.thumbnail(size, resample=0)

Make this image into a thumbnail. This method modifies the image to contain a thumbnail version of itself, no larger than the given size. This method calculates an appropriate thumbnail size to preserve the aspect of the image, calls the draft() method to configure the file reader (where applicable), and finally resizes the image.

Note that the bilinear and bicubic filters in the current version of PIL are not well-suited for thumbnail generation. You should use PIL.Image.ANTIALIAS unless speed is much more important than quality.

Also note that this function modifies the Image object in place. If you need to use the full resolution image as well, apply this method to a copy() of the original image.

Parameters:

• size – Requested size.
• resample – Optional resampling filter. This can be one of PIL.Image.NEAREST, PIL.Image.BILINEAR, PIL.Image.BICUBIC, or PIL.Image.ANTIALIAS (best quality). If omitted, it defaults to PIL.Image.NEAREST (this will be changed to ANTIALIAS in a future version).

Returns:

None

Image.tobitmap(name='image')

Returns the image converted to an X11 bitmap.

Note

This method only works for mode “1” images.

Parameters:name – The name prefix to use for the bitmap variables. Returns:A string containing an X11 bitmap. Raises ValueError:  If the mode is not “1”

Image.tostring(*args, **kw)

Image.transform(size, method, data=None, resample=0, fill=1)

Transforms this image. This method creates a new image with the given size, and the same mode as the original, and copies data to the new image using the given transform.

Parameters:

• size – The output size.
• method – The transformation method. This is one of PIL.Image.EXTENT (cut out a rectangular subregion), PIL.Image.AFFINE (affine transform), PIL.Image.PERSPECTIVE (perspective transform), PIL.Image.QUAD (map a quadrilateral to a rectangle), or PIL.Image.MESH (map a number of source quadrilaterals in one operation).
• data – Extra data to the transformation method.
• resample – Optional resampling filter. It can be one of PIL.Image.NEAREST (use nearest neighbour), PIL.Image.BILINEAR (linear interpolation in a 2x2 environment), or PIL.Image.BICUBIC (cubic spline interpolation in a 4x4 environment). If omitted, or if the image has mode “1” or “P”, it is set to PIL.Image.NEAREST.

Returns:

An Image object.

Image.transpose(method)

Transpose image (flip or rotate in 90 degree steps)

Parameters:method – One of PIL.Image.FLIP_LEFT_RIGHT, PIL.Image.FLIP_TOP_BOTTOM, PIL.Image.ROTATE_90, PIL.Image.ROTATE_180, or PIL.Image.ROTATE_270. Returns:Returns a flipped or rotated copy of this image.

Image.verify()

Verifies the contents of a file. For data read from a file, this method attempts to determine if the file is broken, without actually decoding the image data. If this method finds any problems, it raises suitable exceptions. If you need to load the image after using this method, you must reopen the image file.

Image.fromstring(*args, **kw)

Deprecated alias to frombytes.

Deprecated since version 2.0.

Image.load()

Allocates storage for the image and loads the pixel data. In normal cases, you don’t need to call this method, since the Image class automatically loads an opened image when it is accessed for the first time. This method will close the file associated with the image.

Returns:An image access object.

Image.close()

Closes the file pointer, if possible.

This operation will destroy the image core and release it’s memory. The image data will be unusable afterward.

This function is only required to close images that have not had their file read and closed by the load() method.

Attributes

Instances of the Image class have the following attributes:

PIL.Image.format

The file format of the source file. For images created by the library itself (via a factory function, or by running a method on an existing image), this attribute is set to None.

Type :string or None

PIL.Image.mode

Image mode. This is a string specifying the pixel format used by the image. Typical values are “1”, “L”, “RGB”, or “CMYK.” See Concepts for a full list.

Type :string

PIL.Image.size

Image size, in pixels. The size is given as a 2-tuple (width, height).

Type :(width, height)

PIL.Image.palette

Colour palette table, if any. If mode is “P”, this should be an instance of the ImagePalette class. Otherwise, it should be set to None.

Type :ImagePalette or None

PIL.Image.info

A dictionary holding data associated with the image. This dictionary is used by file handlers to pass on various non-image information read from the file. See documentation for the various file handlers for details.

Most methods ignore the dictionary when returning new images; since the keys are not standardized, it’s not possible for a method to know if the operation affects the dictionary. If you need the information later on, keep a reference to the info dictionary returned from the open method.

Type :dict

ImageChops (“Channel Operations”) Module

The ImageChops module contains a number of arithmetical image operations, called channel operations (“chops”). These can be used for various purposes, including special effects, image compositions, algorithmic painting, and more.

For more pre-made operations, see ImageOps.

At this time, most channel operations are only implemented for 8-bit images (e.g. “L” and “RGB”).

Functions

Most channel operations take one or two image arguments and returns a new image. Unless otherwise noted, the result of a channel operation is always clipped to the range 0 to MAX (which is 255 for all modes supported by the operations in this module).

PIL.ImageChops.add(image1, image2, scale=1.0, offset=0)

Adds two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0.

out = ((image1 + image2) / scale + offset)

Return type:Image

PIL.ImageChops.add_modulo(image1, image2)

Add two images, without clipping the result.

out = ((image1 + image2) % MAX)

Return type:Image

PIL.ImageChops.blend(image1, image2, alpha)

Blend images using constant transparency weight. Alias for PIL.Image.Image.blend().

Return type:Image

PIL.ImageChops.composite(image1, image2, mask)

Create composite using transparency mask. Alias for PIL.Image.Image.composite().

Return type:Image

PIL.ImageChops.constant(image, value)

Fill a channel with a given grey level.

Return type:Image

PIL.ImageChops.darker(image1, image2)

Compares the two images, pixel by pixel, and returns a new image containing the darker values.

out = min(image1, image2)

Return type:Image

PIL.ImageChops.difference(image1, image2)

Returns the absolute value of the pixel-by-pixel difference between the two images.

out = abs(image1 - image2)

Return type:Image

PIL.ImageChops.duplicate(image)

Copy a channel. Alias for PIL.Image.Image.copy().

Return type:Image

PIL.ImageChops.invert(image)

Invert an image (channel).

out = MAX - image

Return type:Image

PIL.ImageChops.lighter(image1, image2)

Compares the two images, pixel by pixel, and returns a new image containing the lighter values.

out = max(image1, image2)

Return type:Image

PIL.ImageChops.logical_and(image1, image2)

Logical AND between two images.

out = ((image1 and image2) % MAX)

Return type:Image

PIL.ImageChops.logical_or(image1, image2)

Logical OR between two images.

out = ((image1 or image2) % MAX)

Return type:Image

PIL.ImageChops.multiply(image1, image2)

Superimposes two images on top of each other.

If you multiply an image with a solid black image, the result is black. If you multiply with a solid white image, the image is unaffected.

out = image1 * image2 / MAX

Return type:Image

PIL.ImageChops.offset(image, xoffset, yoffset=None)

Returns a copy of the image where data has been offset by the given distances. Data wraps around the edges. If yoffset is omitted, it is assumed to be equal to xoffset.

Parameters:

• xoffset – The horizontal distance.
• yoffset – The vertical distance. If omitted, both distances are set to the same value.

Return type:

Image

PIL.ImageChops.screen(image1, image2)

Superimposes two inverted images on top of each other.

out = MAX - ((MAX - image1) * (MAX - image2) / MAX)

Return type:Image

PIL.ImageChops.subtract(image1, image2, scale=1.0, offset=0)

Subtracts two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0.

out = ((image1 - image2) / scale + offset)

Return type:Image

PIL.ImageChops.subtract_modulo(image1, image2)

Subtract two images, without clipping the result.

out = ((image1 - image2) % MAX)

Return type:Image

ImageColor Module

The ImageColor module contains color tables and converters from CSS3-style color specifiers to RGB tuples. This module is used by PIL.Image.Image.new() and the ImageDraw module, among others.

Color Names

The ImageColor module supports the following string formats:

• Hexadecimal color specifiers, given as #rgb or #rrggbb. For example, #ff0000 specifies pure red.
• RGB functions, given as rgb(red, green, blue) where the color values are integers in the range 0 to 255. Alternatively, the color values can be given as three percentages (0% to 100%). For example, rgb(255,0,0) and rgb(100%,0%,0%) both specify pure red.
• Hue-Saturation-Lightness (HSL) functions, given as hsl(hue, saturation%, lightness%) where hue is the color given as an angle between 0 and 360 (red=0, green=120, blue=240), saturation is a value between 0% and 100% (gray=0%, full color=100%), and lightness is a value between 0% and 100% (black=0%, normal=50%, white=100%). For example, hsl(0,100%,50%) is pure red.
• Common HTML color names. The ImageColor module provides some 140 standard color names, based on the colors supported by the X Window system and most web browsers. color names are case insensitive. For example, red and Red both specify pure red.

Functions

PIL.ImageColor.getrgb(color)

Convert a color string to an RGB tuple. If the string cannot be parsed,

this function raises a ValueError exception.

New in version 1.1.4.

Parameters:color – A color string Returns:(red, green, blue[, alpha])

PIL.ImageColor.getcolor(color, mode)

Same as getrgb(), but converts the RGB value to a greyscale value if the mode is not color or a palette image. If the string cannot be parsed, this function raises a ValueError exception.

New in version 1.1.4.

Parameters:color – A color string Returns:(graylevel [, alpha]) or (red, green, blue[, alpha])

ImageDraw Module

The ImageDraw module provide simple 2D graphics for Image objects. You can use this module to create new images, annotate or retouch existing images, and to generate graphics on the fly for web use.

For a more advanced drawing library for PIL, see the aggdraw module.

Example: Draw a gray cross over an image

from PIL import Image, ImageDraw

im = Image.open("lena.pgm")

draw = ImageDraw.Draw(im)
draw.line((0, 0) + im.size, fill=128)
draw.line((0, im.size[1], im.size[0], 0), fill=128)
del draw

# write to stdout
im.save(sys.stdout, "PNG")

Concepts

Coordinates

The graphics interface uses the same coordinate system as PIL itself, with (0, 0) in the upper left corner.

Colors

To specify colors, you can use numbers or tuples just as you would use with PIL.Image.Image.new() or PIL.Image.Image.putpixel(). For “1”, “L”, and “I” images, use integers. For “RGB” images, use a 3-tuple containing integer values. For “F” images, use integer or floating point values.

For palette images (mode “P”), use integers as color indexes. In 1.1.4 and later, you can also use RGB 3-tuples or color names (see below). The drawing layer will automatically assign color indexes, as long as you don’t draw with more than 256 colors.

Color Names

See Color Names for the color names supported by Pillow.

Fonts

PIL can use bitmap fonts or OpenType/TrueType fonts.

Bitmap fonts are stored in PIL’s own format, where each font typically consists of a two files, one named .pil and the other usually named .pbm. The former contains font metrics, the latter raster data.

To load a bitmap font, use the load functions in the ImageFont module.

To load a OpenType/TrueType font, use the truetype function in the ImageFont module. Note that this function depends on third-party libraries, and may not available in all PIL builds.

Functions

class PIL.ImageDraw.Draw(im, mode=None)

Creates an object that can be used to draw in the given image.

Note that the image will be modified in place.

Methods

PIL.ImageDraw.Draw.arc(xy, start, end, fill=None)

Draws an arc (a portion of a circle outline) between the start and end angles, inside the given bounding box.

Parameters:

• xy – Four points to define the bounding box. Sequence of either [(x0, y0), (x1, y1)] or [x0, y0, x1, y1].
• outline – Color to use for the outline.

PIL.ImageDraw.Draw.bitmap(xy, bitmap, fill=None)

Draws a bitmap (mask) at the given position, using the current fill color for the non-zero portions. The bitmap should be a valid transparency mask (mode “1”) or matte (mode “L” or “RGBA”).

This is equivalent to doing image.paste(xy, color, bitmap).

To paste pixel data into an image, use the paste() method on the image itself.

PIL.ImageDraw.Draw.chord(xy, start, end, fill=None, outline=None)

Same as arc(), but connects the end points with a straight line.

Parameters:

• xy – Four points to define the bounding box. Sequence of either [(x0, y0), (x1, y1)] or [x0, y0, x1, y1].
• outline – Color to use for the outline.
• fill – Color to use for the fill.

PIL.ImageDraw.Draw.ellipse(xy, fill=None, outline=None)

Draws an ellipse inside the given bounding box.

Parameters:

• xy – Four points to define the bounding box. Sequence of either [(x0, y0), (x1, y1)] or [x0, y0, x1, y1].
• outline – Color to use for the outline.
• fill – Color to use for the fill.

PIL.ImageDraw.Draw.line(xy, fill=None, width=0)

Draws a line between the coordinates in the xy list.

Parameters:

• xy – Sequence of either 2-tuples like [(x, y), (x, y), ...] or numeric values like [x, y, x, y, ...].
• fill – Color to use for the line.
• width –

  The line width, in pixels. Note that line joins are not handled well, so wide polylines will not look good.

  New in version 1.1.5.

  Note

  This option was broken until version 1.1.6.

PIL.ImageDraw.Draw.pieslice(xy, start, end, fill=None, outline=None)

Same as arc, but also draws straight lines between the end points and the center of the bounding box.

Parameters:

• xy – Four points to define the bounding box. Sequence of either [(x0, y0), (x1, y1)] or [x0, y0, x1, y1].
• outline – Color to use for the outline.
• fill – Color to use for the fill.

PIL.ImageDraw.Draw.point(xy, fill=None)

Draws points (individual pixels) at the given coordinates.

Parameters:

• xy – Sequence of either 2-tuples like [(x, y), (x, y), ...] or numeric values like [x, y, x, y, ...].
• fill – Color to use for the point.

PIL.ImageDraw.Draw.polygon(xy, fill=None, outline=None)

Draws a polygon.

The polygon outline consists of straight lines between the given coordinates, plus a straight line between the last and the first coordinate.

Parameters:

• xy – Sequence of either 2-tuples like [(x, y), (x, y), ...] or numeric values like [x, y, x, y, ...].
• outline – Color to use for the outline.
• fill – Color to use for the fill.

PIL.ImageDraw.Draw.rectangle(xy, fill=None, outline=None)

Draws a rectangle.

Parameters:

• xy – Four points to define the bounding box. Sequence of either [(x0, y0), (x1, y1)] or [x0, y0, x1, y1]. The second point is just outside the drawn rectangle.
• outline – Color to use for the outline.
• fill – Color to use for the fill.

PIL.ImageDraw.Draw.shape(shape, fill=None, outline=None)

Warning

This method is experimental.

Draw a shape.

PIL.ImageDraw.Draw.text(xy, text, fill=None, font=None, anchor=None)

Draws the string at the given position.

Parameters:

• xy – Top left corner of the text.
• text – Text to be drawn.
• font – An ImageFont instance.
• fill – Color to use for the text.

PIL.ImageDraw.Draw.textsize(text, font=None)

Return the size of the given string, in pixels.

Parameters:

• text – Text to be measured.
• font – An ImageFont instance.

Legacy API

The Draw class contains a constructor and a number of methods which are provided for backwards compatibility only. For this to work properly, you should either use options on the drawing primitives, or these methods. Do not mix the old and new calling conventions.

PIL.ImageDraw.ImageDraw(image)

Return type:Draw

PIL.ImageDraw.Draw.setink(ink)

Deprecated since version 1.1.5.

Sets the color to use for subsequent draw and fill operations.

PIL.ImageDraw.Draw.setfill(fill)

Deprecated since version 1.1.5.

Sets the fill mode.

If the mode is 0, subsequently drawn shapes (like polygons and rectangles) are outlined. If the mode is 1, they are filled.

PIL.ImageDraw.Draw.setfont(font)

Deprecated since version 1.1.5.

Sets the default font to use for the text method.

Parameters:font – An ImageFont instance.

ImageEnhance Module

The ImageEnhance module contains a number of classes that can be used for image enhancement.

Example: Vary the sharpness of an image

from PIL import ImageEnhance

enhancer = ImageEnhance.Sharpness(image)

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

Also see the enhancer.py demo program in the Scripts/ directory.

Classes

All enhancement classes implement a common interface, containing a single method:

class PIL.ImageEnhance._Enhance

enhance(factor)

Returns an enhanced image.

Parameters:factor – A floating point value controlling the enhancement. Factor 1.0 always returns a copy of the original image, lower factors mean less color (brightness, contrast, etc), and higher values more. There are no restrictions on this value. Return type:Image

class PIL.ImageEnhance.Color(image)

Adjust image color balance.

This class can be used to adjust the colour balance of an image, in a manner similar to the controls on a colour TV set. An enhancement factor of 0.0 gives a black and white image. A factor of 1.0 gives the original image.

class PIL.ImageEnhance.Contrast(image)

Adjust image contrast.

This class can be used to control the contrast of an image, similar to the contrast control on a TV set. An enhancement factor of 0.0 gives a solid grey image. A factor of 1.0 gives the original image.

class PIL.ImageEnhance.Brightness(image)

Adjust image brightness.

This class can be used to control the brighntess of an image. An enhancement factor of 0.0 gives a black image. A factor of 1.0 gives the original image.

class PIL.ImageEnhance.Sharpness(image)

Adjust image sharpness.

This class can be used to adjust the sharpness of an image. An enhancement factor of 0.0 gives a blurred image, a factor of 1.0 gives the original image, and a factor of 2.0 gives a sharpened image.

ImageFile Module

The ImageFile module provides support functions for the image open and save functions.

In addition, it provides a Parser class which can be used to decode an image piece by piece (e.g. while receiving it over a network connection). This class implements the same consumer interface as the standard sgmllib and xmllib modules.

Example: Parse an image

from PIL import ImageFile

fp = open("lena.pgm", "rb")

p = ImageFile.Parser()

while 1:
    s = fp.read(1024)
    if not s:
        break
    p.feed(s)

im = p.close()

im.save("copy.jpg")

Parser

class PIL.ImageFile.Parser

Incremental image parser. This class implements the standard feed/close consumer interface.

In Python 2.x, this is an old-style class.

close()

(Consumer) Close the stream.

Returns:An image object. Raises IOError:If the parser failed to parse the image file either because it cannot be identified or cannot be decoded.

feed(data)

(Consumer) Feed data to the parser.

Parameters:data – A string buffer. Raises IOError:If the parser failed to parse the image file.

reset()

(Consumer) Reset the parser. Note that you can only call this method immediately after you’ve created a parser; parser instances cannot be reused.

ImageFilter Module

The ImageFilter module contains definitions for a pre-defined set of filters, which can be be used with the Image.filter() method.

Example: Filter an image

from PIL import ImageFilter

im1 = im.filter(ImageFilter.BLUR)

im2 = im.filter(ImageFilter.MinFilter(3))
im3 = im.filter(ImageFilter.MinFilter)  # same as MinFilter(3)

Filters

The current version of the library provides the following set of predefined image enhancement filters:

• BLUR
• CONTOUR
• DETAIL
• EDGE_ENHANCE
• EDGE_ENHANCE_MORE
• EMBOSS
• FIND_EDGES
• SMOOTH
• SMOOTH_MORE
• SHARPEN

class PIL.ImageFilter.GaussianBlur(radius=2)

Gaussian blur filter.

Parameters:radius – Blur radius.

class PIL.ImageFilter.UnsharpMask(radius=2, percent=150, threshold=3)

Unsharp mask filter.

See Wikipedia’s entry on digital unsharp masking for an explanation of the parameters.

class PIL.ImageFilter.Kernel(size, kernel, scale=None, offset=0)

Create a convolution kernel. The current version only supports 3x3 and 5x5 integer and floating point kernels.

In the current version, kernels can only be applied to “L” and “RGB” images.

Parameters:

• size – Kernel size, given as (width, height). In the current version, this must be (3,3) or (5,5).
• kernel – A sequence containing kernel weights.
• scale – Scale factor. If given, the result for each pixel is divided by this value. the default is the sum of the kernel weights.
• offset – Offset. If given, this value is added to the result, after it has been divided by the scale factor.

class PIL.ImageFilter.RankFilter(size, rank)

Create a rank filter. The rank filter sorts all pixels in a window of the given size, and returns the rank‘th value.

Parameters:

• size – The kernel size, in pixels.
• rank – What pixel value to pick. Use 0 for a min filter, size * size / 2 for a median filter, size * size - 1 for a max filter, etc.

class PIL.ImageFilter.MedianFilter(size=3)

Create a median filter. Picks the median pixel value in a window with the given size.

Parameters:size – The kernel size, in pixels.

class PIL.ImageFilter.MinFilter(size=3)

Create a min filter. Picks the lowest pixel value in a window with the given size.

Parameters:size – The kernel size, in pixels.

class PIL.ImageFilter.MaxFilter(size=3)

Create a max filter. Picks the largest pixel value in a window with the given size.

Parameters:size – The kernel size, in pixels.

class PIL.ImageFilter.ModeFilter(size=3)

Create a mode filter. Picks the most frequent pixel value in a box with the given size. Pixel values that occur only once or twice are ignored; if no pixel value occurs more than twice, the original pixel value is preserved.

Parameters:size – The kernel size, in pixels.

ImageFont Module

The ImageFont module defines a class with the same name. Instances of this class store bitmap fonts, and are used with the PIL.ImageDraw.Draw.text() method.

PIL uses its own font file format to store bitmap fonts. You can use the :command`pilfont` utility to convert BDF and PCF font descriptors (X window font formats) to this format.

Starting with version 1.1.4, PIL can be configured to support TrueType and OpenType fonts (as well as other font formats supported by the FreeType library). For earlier versions, TrueType support is only available as part of the imToolkit package

Example

from PIL import ImageFont, ImageDraw

draw = ImageDraw.Draw(image)

# use a bitmap font
font = ImageFont.load("arial.pil")

draw.text((10, 10), "hello", font=font)

# use a truetype font
font = ImageFont.truetype("arial.ttf", 15)

draw.text((10, 25), "world", font=font)

Functions

PIL.ImageFont.load(filename)

Load a font file. This function loads a font object from the given bitmap font file, and returns the corresponding font object.

Parameters:filename – Name of font file. Returns:A font object. Raises IOError:If the file could not be read.

PIL.ImageFont.load_path(filename)

Load font file. Same as load(), but searches for a bitmap font along the Python path.

Parameters:filename – Name of font file. Returns:A font object. Raises IOError:If the file could not be read.

PIL.ImageFont.truetype(font=None, size=10, index=0, encoding='', filename=None)

Load a TrueType or OpenType font file, and create a font object. This function loads a font object from the given file, and creates a font object for a font of the given size.

This function requires the _imagingft service.

Parameters:

• filename – A truetype font file. Under Windows, if the file is not found in this filename, the loader also looks in Windows fonts/ directory.
• size – The requested size, in points.
• index – Which font face to load (default is first available face).
• encoding – Which font encoding to use (default is Unicode). Common encodings are “unic” (Unicode), “symb” (Microsoft Symbol), “ADOB” (Adobe Standard), “ADBE” (Adobe Expert), and “armn” (Apple Roman). See the FreeType documentation for more information.

Returns:

A font object.

Raises IOError:

If the file could not be read.

PIL.ImageFont.load_default()

Load a “better than nothing” default font.

New in version 1.1.4.

Returns:A font object.

Methods

PIL.ImageFont.ImageFont.getsize(text)

Returns:(width, height)

PIL.ImageFont.ImageFont.getmask(text, mode='')

Create a bitmap for the text.

If the font uses antialiasing, the bitmap should have mode “L” and use a maximum value of 255. Otherwise, it should have mode “1”.

Parameters:

• text – Text to render.
• mode –

  Used by some graphics drivers to indicate what mode the driver prefers; if empty, the renderer may return either mode. Note that the mode is always a string, to simplify C-level implementations.

  New in version 1.1.5.

Returns:

An internal PIL storage memory instance as defined by the PIL.Image.core interface module.

ImageGrab Module (Windows-only)

The ImageGrab module can be used to copy the contents of the screen or the clipboard to a PIL image memory.

Note

The current version works on Windows only.

New in version 1.1.3.

PIL.ImageGrab.grab(bbox=None)

Take a snapshot of the screen. The pixels inside the bounding box are returned as an “RGB” image. If the bounding box is omitted, the entire screen is copied.

New in version 1.1.3.

Parameters:bbox – What region to copy. Default is the entire screen. Returns:An image

PIL.ImageGrab.grabclipboard()

Take a snapshot of the clipboard image, if any.

New in version 1.1.4.

Returns:An image, a list of filenames, or None if the clipboard does not contain image data or filenames. Note that if a list is returned, the filenames may not represent image files.

ImageMath Module

The ImageMath module can be used to evaluate “image expressions”. The module provides a single eval function, which takes an expression string and one or more images.

Example: Using the ImageMath module

import Image, ImageMath

im1 = Image.open("image1.jpg")
im2 = Image.open("image2.jpg")

out = ImageMath.eval("convert(min(a, b), 'L')", a=im1, b=im2)
out.save("result.png")

PIL.ImageMath.eval(expression, environment)

Evaluate expression in the given environment.

In the current version, ImageMath only supports single-layer images. To process multi-band images, use the split() method or merge() function.

Parameters:

• expression – A string which uses the standard Python expression syntax. In addition to the standard operators, you can also use the functions described below.
• environment – A dictionary that maps image names to Image instances. You can use one or more keyword arguments instead of a dictionary, as shown in the above example. Note that the names must be valid Python identifiers.

Returns:

An image, an integer value, a floating point value, or a pixel tuple, depending on the expression.

Expression syntax

Expressions are standard Python expressions, but they’re evaluated in a non-standard environment. You can use PIL methods as usual, plus the following set of operators and functions:

Standard Operators

You can use standard arithmetical operators for addition (+), subtraction (-), multiplication (*), and division (/).

The module also supports unary minus (-), modulo (%), and power (**) operators.

Note that all operations are done with 32-bit integers or 32-bit floating point values, as necessary. For example, if you add two 8-bit images, the result will be a 32-bit integer image. If you add a floating point constant to an 8-bit image, the result will be a 32-bit floating point image.

You can force conversion using the convert(), float(), and int() functions described below.

Bitwise Operators

The module also provides operations that operate on individual bits. This includes and (&), or (|), and exclusive or (^). You can also invert (~) all pixel bits.

Note that the operands are converted to 32-bit signed integers before the bitwise operation is applied. This means that you’ll get negative values if you invert an ordinary greyscale image. You can use the and (&) operator to mask off unwanted bits.

Bitwise operators don’t work on floating point images.

Logical Operators

Logical operators like and, or, and not work on entire images, rather than individual pixels.

An empty image (all pixels zero) is treated as false. All other images are treated as true.

Note that and and or return the last evaluated operand, while not always returns a boolean value.

Built-in Functions

These functions are applied to each individual pixel.

abs(image)

Absolute value.

convert(image, mode)

Convert image to the given mode. The mode must be given as a string constant.

float(image)

Convert image to 32-bit floating point. This is equivalent to convert(image, “F”).

int(image)

Convert image to 32-bit integer. This is equivalent to convert(image, “I”).

Note that 1-bit and 8-bit images are automatically converted to 32-bit integers if necessary to get a correct result.

max(image1, image2)

Maximum value.

min(image1, image2)

Minimum value.

ImageOps Module

The ImageOps module contains a number of ‘ready-made’ image processing operations. This module is somewhat experimental, and most operators only work on L and RGB images.

Only bug fixes have been added since the Pillow fork.

New in version 1.1.3.

PIL.ImageOps.autocontrast(image, cutoff=0, ignore=None)

Maximize (normalize) image contrast. This function calculates a histogram of the input image, removes cutoff percent of the lightest and darkest pixels from the histogram, and remaps the image so that the darkest pixel becomes black (0), and the lightest becomes white (255).

Parameters:

• image – The image to process.
• cutoff – How many percent to cut off from the histogram.
• ignore – The background pixel value (use None for no background).

Returns:

An image.

PIL.ImageOps.colorize(image, black, white)

Colorize grayscale image. The black and white arguments should be RGB tuples; this function calculates a color wedge mapping all black pixels in the source image to the first color, and all white pixels to the second color.

Parameters:

• image – The image to colorize.
• black – The color to use for black input pixels.
• white – The color to use for white input pixels.

Returns:

An image.

PIL.ImageOps.crop(image, border=0)

Remove border from image. The same amount of pixels are removed from all four sides. This function works on all image modes.

See also

crop()

Parameters:

• image – The image to crop.
• border – The number of pixels to remove.

Returns:

An image.

PIL.ImageOps.deform(image, deformer, resample=2)

Deform the image.

Parameters:

• image – The image to deform.
• deformer – A deformer object. Any object that implements a getmesh method can be used.
• resample – What resampling filter to use.

Returns:

An image.

PIL.ImageOps.equalize(image, mask=None)

Equalize the image histogram. This function applies a non-linear mapping to the input image, in order to create a uniform distribution of grayscale values in the output image.

Parameters:

• image – The image to equalize.
• mask – An optional mask. If given, only the pixels selected by the mask are included in the analysis.

Returns:

An image.

PIL.ImageOps.expand(image, border=0, fill=0)

Add border to the image

Parameters:

• image – The image to expand.
• border – Border width, in pixels.
• fill – Pixel fill value (a color value). Default is 0 (black).

Returns:

An image.

PIL.ImageOps.fit(image, size, method=0, bleed=0.0, centering=(0.5, 0.5))

Returns a sized and cropped version of the image, cropped to the requested aspect ratio and size.

This function was contributed by Kevin Cazabon.

Parameters:

• size – The requested output size in pixels, given as a (width, height) tuple.
• method – What resampling method to use. Default is PIL.Image.NEAREST.
• bleed – Remove a border around the outside of the image (from all four edges. The value is a decimal percentage (use 0.01 for one percent). The default value is 0 (no border).
• centering – Control the cropping position. Use (0.5, 0.5) for center cropping (e.g. if cropping the width, take 50% off of the left side, and therefore 50% off the right side). (0.0, 0.0) will crop from the top left corner (i.e. if cropping the width, take all of the crop off of the right side, and if cropping the height, take all of it off the bottom). (1.0, 0.0) will crop from the bottom left corner, etc. (i.e. if cropping the width, take all of the crop off the left side, and if cropping the height take none from the top, and therefore all off the bottom).

Returns:

An image.

PIL.ImageOps.flip(image)

Flip the image vertically (top to bottom).

Parameters:image – The image to flip. Returns:An image.

PIL.ImageOps.grayscale(image)

Convert the image to grayscale.

Parameters:image – The image to convert. Returns:An image.

PIL.ImageOps.invert(image)

Invert (negate) the image.

Parameters:image – The image to invert. Returns:An image.

PIL.ImageOps.mirror(image)

Flip image horizontally (left to right).

Parameters:image – The image to mirror. Returns:An image.

PIL.ImageOps.posterize(image, bits)

Reduce the number of bits for each color channel.

Parameters:

• image – The image to posterize.
• bits – The number of bits to keep for each channel (1-8).

Returns:

An image.

PIL.ImageOps.solarize(image, threshold=128)

Invert all pixel values above a threshold.

Parameters:

• image – The image to posterize.
• threshold – All pixels above this greyscale level are inverted.

Returns:

An image.

ImagePalette Module

The ImagePalette module contains a class of the same name to represent the color palette of palette mapped images.

Note

This module was never well-documented. It hasn’t changed since 2001, though, so it’s probably safe for you to read the source code and puzzle out the internals if you need to.

The ImagePalette class has several methods, but they are all marked as “experimental.” Read that as you will. The [source] link is there for a reason.

class PIL.ImagePalette.ImagePalette(mode='RGB', palette=None, size=0)

Color palette for palette mapped images

getcolor(color)

Given an rgb tuple, allocate palette entry.

Warning

This method is experimental.

getdata()

Get palette contents in format suitable # for the low-level im.putpalette primitive.

Warning

This method is experimental.

save(fp)

Save palette to text file.

Warning

This method is experimental.

tobytes()

Convert palette to bytes.

Warning

This method is experimental.

tostring()

Convert palette to bytes.

Warning

This method is experimental.

ImagePath Module

The ImagePath module is used to store and manipulate 2-dimensional vector data. Path objects can be passed to the methods on the ImageDraw module.

class PIL.ImagePath.Path

A path object. The coordinate list can be any sequence object containing either 2-tuples [(x, y), …] or numeric values [x, y, …].

You can also create a path object from another path object.

In 1.1.6 and later, you can also pass in any object that implements Python’s buffer API. The buffer should provide read access, and contain C floats in machine byte order.

The path object implements most parts of the Python sequence interface, and behaves like a list of (x, y) pairs. You can use len(), item access, and slicing as usual. However, the current version does not support slice assignment, or item and slice deletion.

Parameters:xy – A sequence. The sequence can contain 2-tuples [(x, y), ...] or a flat list of numbers [x, y, ...].

PIL.ImagePath.Path.compact(distance=2)

Compacts the path, by removing points that are close to each other. This method modifies the path in place, and returns the number of points left in the path.

distance is measured as Manhattan distance and defaults to two pixels.

PIL.ImagePath.Path.getbbox()

Gets the bounding box of the path.

Returns:(x0, y0, x1, y1)

PIL.ImagePath.Path.map(function)

Maps the path through a function.

PIL.ImagePath.Path.tolist(flat=0)

Converts the path to a Python list [(x, y), …].

Parameters:flat – By default, this function returns a list of 2-tuples [(x, y), ...]. If this argument is True, it returns a flat list [x, y, ...] instead. Returns:A list of coordinates. See flat.

PIL.ImagePath.Path.transform(matrix)

Transforms the path in place, using an affine transform. The matrix is a 6-tuple (a, b, c, d, e, f), and each point is mapped as follows:

xOut = xIn * a + yIn * b + c
yOut = xIn * d + yIn * e + f

ImageQt Module

The ImageQt module contains support for creating PyQt4 or PyQt5 QImage objects from PIL images.

New in version 1.1.6.

class ImageQt.ImageQt(image)

Creates an ImageQt object from a PIL Image object. This class is a subclass of QtGui.QImage, which means that you can pass the resulting objects directly to PyQt4/5 API functions and methods.

This operation is currently supported for mode 1, L, P, RGB, and RGBA images. To handle other modes, you need to convert the image first.

ImageSequence Module

The ImageSequence module contains a wrapper class that lets you iterate over the frames of an image sequence.

Extracting frames from an animation

from PIL import Image, ImageSequence

im = Image.open("animation.fli")

index = 1
for frame in ImageSequence.Iterator(im):
    frame.save("frame%d.png" % index)
    index = index + 1

The Iterator class

class PIL.ImageSequence.Iterator(im)

This class implements an iterator object that can be used to loop over an image sequence.

You can use the [] operator to access elements by index. This operator will raise an IndexError if you try to access a nonexistent frame.

Parameters:im – An image object.

ImageStat Module

The ImageStat module calculates global statistics for an image, or for a region of an image.

class PIL.ImageStat.Stat(image_or_list, mask=None)

Calculate statistics for the given image. If a mask is included, only the regions covered by that mask are included in the statistics. You can also pass in a previously calculated histogram.

Parameters:

• image – A PIL image, or a precalculated histogram.
• mask – An optional mask.

extrema

Min/max values for each band in the image.

count

Total number of pixels.

sum

Sum of all pixels.

sum2

Squared sum of all pixels.

pixel

Average pixel level.

median

Median pixel level.

rms

RMS (root-mean-square).

var

Variance.

stddev

Standard deviation.

ImageTk Module

The ImageTk module contains support to create and modify Tkinter BitmapImage and PhotoImage objects from PIL images.

For examples, see the demo programs in the Scripts directory.

class PIL.ImageTk.BitmapImage(image=None, **kw)

A Tkinter-compatible bitmap image. This can be used everywhere Tkinter expects an image object.

The given image must have mode “1”. Pixels having value 0 are treated as transparent. Options, if any, are passed on to Tkinter. The most commonly used option is foreground, which is used to specify the color for the non-transparent parts. See the Tkinter documentation for information on how to specify colours.

Parameters:image – A PIL image.

height()

Get the height of the image.

Returns:The height, in pixels.

width()

Get the width of the image.

Returns:The width, in pixels.

class PIL.ImageTk.PhotoImage(image=None, size=None, **kw)

A Tkinter-compatible photo image. This can be used everywhere Tkinter expects an image object. If the image is an RGBA image, pixels having alpha 0 are treated as transparent.

The constructor takes either a PIL image, or a mode and a size. Alternatively, you can use the file or data options to initialize the photo image object.

Parameters:

• image – Either a PIL image, or a mode string. If a mode string is used, a size must also be given.
• size – If the first argument is a mode string, this defines the size of the image.
• file – A filename to load the image from (using Image.open(file)).
• data – An 8-bit string containing image data (as loaded from an image file).

height()

Get the height of the image.

Returns:The height, in pixels.

paste(im, box=None)

Paste a PIL image into the photo image. Note that this can be very slow if the photo image is displayed.

Parameters:

• im – A PIL image. The size must match the target region. If the mode does not match, the image is converted to the mode of the bitmap image.
• box – A 4-tuple defining the left, upper, right, and lower pixel coordinate. If None is given instead of a tuple, all of the image is assumed.

width()

Get the width of the image.

Returns:The width, in pixels.

ImageWin Module (Windows-only)

The ImageWin module contains support to create and display images on Windows.

ImageWin can be used with PythonWin and other user interface toolkits that provide access to Windows device contexts or window handles. For example, Tkinter makes the window handle available via the winfo_id method:

from PIL import ImageWin

dib = ImageWin.Dib(...)

hwnd = ImageWin.HWND(widget.winfo_id())
dib.draw(hwnd, xy)

class PIL.ImageWin.Dib(image, size=None)

A Windows bitmap with the given mode and size. The mode can be one of “1”, “L”, “P”, or “RGB”.

If the display requires a palette, this constructor creates a suitable palette and associates it with the image. For an “L” image, 128 greylevels are allocated. For an “RGB” image, a 6x6x6 colour cube is used, together with 20 greylevels.

To make sure that palettes work properly under Windows, you must call the palette method upon certain events from Windows.

Parameters:

• image – Either a PIL image, or a mode string. If a mode string is used, a size must also be given. The mode can be one of “1”, “L”, “P”, or “RGB”.
• size – If the first argument is a mode string, this defines the size of the image.

draw(handle, dst, src=None)

Same as expose, but allows you to specify where to draw the image, and what part of it to draw.

The destination and source areas are given as 4-tuple rectangles. If the source is omitted, the entire image is copied. If the source and the destination have different sizes, the image is resized as necessary.

expose(handle)

Copy the bitmap contents to a device context.

Parameters:handle – Device context (HDC), cast to a Python integer, or a HDC or HWND instance. In PythonWin, you can use the CDC.GetHandleAttrib() to get a suitable handle.

frombytes(buffer)

Load display memory contents from byte data.

Parameters:buffer – A buffer containing display data (usually data returned from <b>tobytes</b>)

paste(im, box=None)

Paste a PIL image into the bitmap image.

Parameters:

• im – A PIL image. The size must match the target region. If the mode does not match, the image is converted to the mode of the bitmap image.
• box – A 4-tuple defining the left, upper, right, and lower pixel coordinate. If None is given instead of a tuple, all of the image is assumed.

query_palette(handle)

Installs the palette associated with the image in the given device context.

This method should be called upon QUERYNEWPALETTE and PALETTECHANGED events from Windows. If this method returns a non-zero value, one or more display palette entries were changed, and the image should be redrawn.

Parameters:handle – Device context (HDC), cast to a Python integer, or an HDC or HWND instance. Returns:A true value if one or more entries were changed (this indicates that the image should be redrawn).

tobytes()

Copy display memory contents to bytes object.

Returns:A bytes object containing display data.

class PIL.ImageWin.HDC(dc)

Wraps a HDC integer. The resulting object can be passed to the draw() and expose() methods.

class PIL.ImageWin.HWND(wnd)

Wraps a HWND integer. The resulting object can be passed to the draw() and expose() methods, instead of a DC.

PSDraw Module

The PSDraw module provides simple print support for Postscript printers. You can print text, graphics and images through this module.

class PIL.PSDraw.PSDraw(fp=None)

Sets up printing to the given file. If file is omitted, sys.stdout is assumed.

begin_document(id=None)

Set up printing of a document. (Write Postscript DSC header.)

end_document()

Ends printing. (Write Postscript DSC footer.)

image(box, im, dpi=None)

Draw a PIL image, centered in the given box.

line(xy0, xy1)

Draws a line between the two points. Coordinates are given in Postscript point coordinates (72 points per inch, (0, 0) is the lower left corner of the page).

rectangle(box)

Draws a rectangle.

Parameters:box –

A 4-tuple of integers whose order and function is currently undocumented.

Hint: the tuple is passed into this format string:

%d %d M %d %d 0 Vr

setfont(font, size)

Selects which font to use.

Parameters:

• font – A Postscript font name
• size – Size in points.

setink(ink)

This has been in the PIL API for ages but was never implemented.

text(xy, text)

Draws text at the given position. You must use setfont() before calling this method.

PIL Package (autodoc of remaining modules)

Reference for modules whose documentation has not yet been ported or written can be found here.

BdfFontFile Module

class PIL.BdfFontFile.BdfFontFile(fp)

Bases: PIL.FontFile.FontFile

PIL.BdfFontFile.bdf_char(f)

ContainerIO Module

class PIL.ContainerIO.ContainerIO(file, offset, length)

isatty()

read(n=0)

readline()

readlines()

seek(offset, mode=0)

tell()

ExifTags Module

FontFile Module

class PIL.FontFile.FontFile

bitmap = None

compile()

Create metrics and bitmap

save(filename)

Save font in version 1 format

save1(filename)

Save font in version 1 format

save2(filename)

Save font in version 2 format

PIL.FontFile.puti16(fp, values)

GdImageFile Module

class PIL.GdImageFile.GdImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'GD'

format_description = 'GD uncompressed images'

PIL.GdImageFile.open(fp, mode='r')

GimpGradientFile Module

class PIL.GimpGradientFile.GimpGradientFile(fp)

Bases: PIL.GimpGradientFile.GradientFile

class PIL.GimpGradientFile.GradientFile

getpalette(entries=256)

gradient = None

PIL.GimpGradientFile.curved(middle, pos)

PIL.GimpGradientFile.linear(middle, pos)

PIL.GimpGradientFile.sine(middle, pos)

PIL.GimpGradientFile.sphere_decreasing(middle, pos)

PIL.GimpGradientFile.sphere_increasing(middle, pos)

GimpPaletteFile Module

class PIL.GimpPaletteFile.GimpPaletteFile(fp)

getpalette()

rawmode = 'RGB'

ImageCms Module

class PIL.ImageCms.ImageCmsProfile(profile)

class PIL.ImageCms.ImageCmsTransform(input, output, input_mode, output_mode, intent=0, proof=None, proof_intent=3, flags=0)

Bases: PIL.Image.ImagePointHandler

Transform. This can be used with the procedural API, or with the standard Image.point() method.

apply(im, imOut=None)

apply_in_place(im)

point(im)

exception PIL.ImageCms.PyCMSError

Bases: exceptions.Exception

(pyCMS) Exception class. This is used for all errors in the pyCMS API.

PIL.ImageCms.applyTransform(im, transform, inPlace=0)

(pyCMS) Applies a transform to a given image.

If im.mode != transform.inMode, a PyCMSError is raised.

If inPlace == TRUE and transform.inMode != transform.outMode, a PyCMSError is raised.

If im.mode, transfer.inMode, or transfer.outMode is not supported by pyCMSdll or the profiles you used for the transform, a PyCMSError is raised.

If an error occurs while the transform is being applied, a PyCMSError is raised.

This function applies a pre-calculated transform (from ImageCms.buildTransform() or ImageCms.buildTransformFromOpenProfiles()) to an image. The transform can be used for multiple images, saving considerable calcuation time if doing the same conversion multiple times.

If you want to modify im in-place instead of receiving a new image as the return value, set inPlace to TRUE. This can only be done if transform.inMode and transform.outMode are the same, because we can’t change the mode in-place (the buffer sizes for some modes are different). The default behavior is to return a new Image object of the same dimensions in mode transform.outMode.

Parameters:

• im – A PIL Image object, and im.mode must be the same as the inMode supported by the transform.
• transform – A valid CmsTransform class object
• inPlace – Bool (1 == True, 0 or None == False). If True, im is modified in place and None is returned, if False, a new Image object with the transform applied is returned (and im is not changed). The default is False.

Returns:

Either None, or a new PIL Image object, depending on the value of inPlace

Raises PyCMSError:  

PIL.ImageCms.buildProofTransform(inputProfile, outputProfile, proofProfile, inMode, outMode, renderingIntent=0, proofRenderingIntent=3, flags=16384)

(pyCMS) Builds an ICC transform mapping from the inputProfile to the outputProfile, but tries to simulate the result that would be obtained on the proofProfile device.

If the input, output, or proof profiles specified are not valid filenames, a PyCMSError will be raised.

If an error occurs during creation of the transform, a PyCMSError will be raised.

If inMode or outMode are not a mode supported by the outputProfile (or by pyCMS), a PyCMSError will be raised.

This function builds and returns an ICC transform from the inputProfile to the outputProfile, but tries to simulate the result that would be obtained on the proofProfile device using renderingIntent and proofRenderingIntent to determine what to do with out-of-gamut colors. This is known as “soft-proofing”. It will ONLY work for converting images that are in inMode to images that are in outMode color format (PIL mode, i.e. “RGB”, “RGBA”, “CMYK”, etc.).

Usage of the resulting transform object is exactly the same as with ImageCms.buildTransform().

Proof profiling is generally used when using an output device to get a good idea of what the final printed/displayed image would look like on the proofProfile device when it’s quicker and easier to use the output device for judging color. Generally, this means that the output device is a monitor, or a dye-sub printer (etc.), and the simulated device is something more expensive, complicated, or time consuming (making it difficult to make a real print for color judgement purposes).

Soft-proofing basically functions by adjusting the colors on the output device to match the colors of the device being simulated. However, when the simulated device has a much wider gamut than the output device, you may obtain marginal results.

Parameters:

• inputProfile – String, as a valid filename path to the ICC input profile you wish to use for this transform, or a profile object
• outputProfile – String, as a valid filename path to the ICC output (monitor, usually) profile you wish to use for this transform, or a profile object
• proofProfile – String, as a valid filename path to the ICC proof profile you wish to use for this transform, or a profile object
• inMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• outMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• renderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for the input->proof (simulated) transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• proofRenderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for proof->output transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• flags – Integer (0-...) specifying additional flags

Returns:

A CmsTransform class object.

Raises PyCMSError:  

PIL.ImageCms.buildProofTransformFromOpenProfiles(inputProfile, outputProfile, proofProfile, inMode, outMode, renderingIntent=0, proofRenderingIntent=3, flags=16384)

(pyCMS) Builds an ICC transform mapping from the inputProfile to the outputProfile, but tries to simulate the result that would be obtained on the proofProfile device.

If the input, output, or proof profiles specified are not valid filenames, a PyCMSError will be raised.

If an error occurs during creation of the transform, a PyCMSError will be raised.

If inMode or outMode are not a mode supported by the outputProfile (or by pyCMS), a PyCMSError will be raised.

This function builds and returns an ICC transform from the inputProfile to the outputProfile, but tries to simulate the result that would be obtained on the proofProfile device using renderingIntent and proofRenderingIntent to determine what to do with out-of-gamut colors. This is known as “soft-proofing”. It will ONLY work for converting images that are in inMode to images that are in outMode color format (PIL mode, i.e. “RGB”, “RGBA”, “CMYK”, etc.).

Usage of the resulting transform object is exactly the same as with ImageCms.buildTransform().

Proof profiling is generally used when using an output device to get a good idea of what the final printed/displayed image would look like on the proofProfile device when it’s quicker and easier to use the output device for judging color. Generally, this means that the output device is a monitor, or a dye-sub printer (etc.), and the simulated device is something more expensive, complicated, or time consuming (making it difficult to make a real print for color judgement purposes).

Soft-proofing basically functions by adjusting the colors on the output device to match the colors of the device being simulated. However, when the simulated device has a much wider gamut than the output device, you may obtain marginal results.

Parameters:

• inputProfile – String, as a valid filename path to the ICC input profile you wish to use for this transform, or a profile object
• outputProfile – String, as a valid filename path to the ICC output (monitor, usually) profile you wish to use for this transform, or a profile object
• proofProfile – String, as a valid filename path to the ICC proof profile you wish to use for this transform, or a profile object
• inMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• outMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• renderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for the input->proof (simulated) transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• proofRenderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for proof->output transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• flags – Integer (0-...) specifying additional flags

Returns:

A CmsTransform class object.

Raises PyCMSError:  

PIL.ImageCms.buildTransform(inputProfile, outputProfile, inMode, outMode, renderingIntent=0, flags=0)

(pyCMS) Builds an ICC transform mapping from the inputProfile to the outputProfile. Use applyTransform to apply the transform to a given image.

If the input or output profiles specified are not valid filenames, a PyCMSError will be raised. If an error occurs during creation of the transform, a PyCMSError will be raised.

If inMode or outMode are not a mode supported by the outputProfile (or by pyCMS), a PyCMSError will be raised.

This function builds and returns an ICC transform from the inputProfile to the outputProfile using the renderingIntent to determine what to do with out-of-gamut colors. It will ONLY work for converting images that are in inMode to images that are in outMode color format (PIL mode, i.e. “RGB”, “RGBA”, “CMYK”, etc.).

Building the transform is a fair part of the overhead in ImageCms.profileToProfile(), so if you’re planning on converting multiple images using the same input/output settings, this can save you time. Once you have a transform object, it can be used with ImageCms.applyProfile() to convert images without the need to re-compute the lookup table for the transform.

The reason pyCMS returns a class object rather than a handle directly to the transform is that it needs to keep track of the PIL input/output modes that the transform is meant for. These attributes are stored in the “inMode” and “outMode” attributes of the object (which can be manually overridden if you really want to, but I don’t know of any time that would be of use, or would even work).

Parameters:

• inputProfile – String, as a valid filename path to the ICC input profile you wish to use for this transform, or a profile object
• outputProfile – String, as a valid filename path to the ICC output profile you wish to use for this transform, or a profile object
• inMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• outMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• renderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for the transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• flags – Integer (0-...) specifying additional flags

Returns:

A CmsTransform class object.

Raises PyCMSError:  

PIL.ImageCms.buildTransformFromOpenProfiles(inputProfile, outputProfile, inMode, outMode, renderingIntent=0, flags=0)

(pyCMS) Builds an ICC transform mapping from the inputProfile to the outputProfile. Use applyTransform to apply the transform to a given image.

If the input or output profiles specified are not valid filenames, a PyCMSError will be raised. If an error occurs during creation of the transform, a PyCMSError will be raised.

If inMode or outMode are not a mode supported by the outputProfile (or by pyCMS), a PyCMSError will be raised.

This function builds and returns an ICC transform from the inputProfile to the outputProfile using the renderingIntent to determine what to do with out-of-gamut colors. It will ONLY work for converting images that are in inMode to images that are in outMode color format (PIL mode, i.e. “RGB”, “RGBA”, “CMYK”, etc.).

Building the transform is a fair part of the overhead in ImageCms.profileToProfile(), so if you’re planning on converting multiple images using the same input/output settings, this can save you time. Once you have a transform object, it can be used with ImageCms.applyProfile() to convert images without the need to re-compute the lookup table for the transform.

The reason pyCMS returns a class object rather than a handle directly to the transform is that it needs to keep track of the PIL input/output modes that the transform is meant for. These attributes are stored in the “inMode” and “outMode” attributes of the object (which can be manually overridden if you really want to, but I don’t know of any time that would be of use, or would even work).

Parameters:

• inputProfile – String, as a valid filename path to the ICC input profile you wish to use for this transform, or a profile object
• outputProfile – String, as a valid filename path to the ICC output profile you wish to use for this transform, or a profile object
• inMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• outMode – String, as a valid PIL mode that the appropriate profile also supports (i.e. “RGB”, “RGBA”, “CMYK”, etc.)
• renderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for the transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• flags – Integer (0-...) specifying additional flags

Returns:

A CmsTransform class object.

Raises PyCMSError:  

PIL.ImageCms.createProfile(colorSpace, colorTemp=-1)

(pyCMS) Creates a profile.

If colorSpace not in [“LAB”, “XYZ”, “sRGB”], a PyCMSError is raised

If using LAB and colorTemp != a positive integer, a PyCMSError is raised.

If an error occurs while creating the profile, a PyCMSError is raised.

Use this function to create common profiles on-the-fly instead of having to supply a profile on disk and knowing the path to it. It returns a normal CmsProfile object that can be passed to ImageCms.buildTransformFromOpenProfiles() to create a transform to apply to images.

Parameters:

• colorSpace – String, the color space of the profile you wish to create. Currently only “LAB”, “XYZ”, and “sRGB” are supported.
• colorTemp – Positive integer for the white point for the profile, in degrees Kelvin (i.e. 5000, 6500, 9600, etc.). The default is for D50 illuminant if omitted (5000k). colorTemp is ONLY applied to LAB profiles, and is ignored for XYZ and sRGB.

Returns:

A CmsProfile class object

Raises PyCMSError:  

PIL.ImageCms.getDefaultIntent(profile)

(pyCMS) Gets the default intent name for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile, a PyCMSError is raised.

If an error occurs while trying to obtain the default intent, a PyCMSError is raised.

Use this function to determine the default (and usually best optomized) rendering intent for this profile. Most profiles support multiple rendering intents, but are intended mostly for one type of conversion. If you wish to use a different intent than returned, use ImageCms.isIntentSupported() to verify it will work first.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:Integer 0-3 specifying the default rendering intent for this profile.

INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

see the pyCMS documentation for details on rendering intents and what they do.

Raises PyCMSError:  

PIL.ImageCms.getOpenProfile(profileFilename)

(pyCMS) Opens an ICC profile file.

The PyCMSProfile object can be passed back into pyCMS for use in creating transforms and such (as in ImageCms.buildTransformFromOpenProfiles()).

If profileFilename is not a vaild filename for an ICC profile, a PyCMSError will be raised.

Parameters:profileFilename – String, as a valid filename path to the ICC profile you wish to open, or a file-like object. Returns:A CmsProfile class object. Raises PyCMSError:  

PIL.ImageCms.getProfileCopyright(profile)

(pyCMS) Gets the copyright for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile, a PyCMSError is raised.

If an error occurs while trying to obtain the copyright tag, a PyCMSError is raised

Use this function to obtain the information stored in the profile’s copyright tag.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:A string containing the internal profile information stored in an ICC tag. Raises PyCMSError:  

PIL.ImageCms.getProfileDescription(profile)

(pyCMS) Gets the description for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile, a PyCMSError is raised.

If an error occurs while trying to obtain the description tag, a PyCMSError is raised

Use this function to obtain the information stored in the profile’s description tag.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:A string containing the internal profile information stored in an ICC tag. Raises PyCMSError:  

PIL.ImageCms.getProfileInfo(profile)

(pyCMS) Gets the internal product information for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile, a PyCMSError is raised.

If an error occurs while trying to obtain the info tag, a PyCMSError is raised

Use this function to obtain the information stored in the profile’s info tag. This often contains details about the profile, and how it was created, as supplied by the creator.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:A string containing the internal profile information stored in an ICC tag. Raises PyCMSError:  

PIL.ImageCms.getProfileManufacturer(profile)

(pyCMS) Gets the manufacturer for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile, a PyCMSError is raised.

If an error occurs while trying to obtain the manufacturer tag, a PyCMSError is raised

Use this function to obtain the information stored in the profile’s manufacturer tag.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:A string containing the internal profile information stored in an ICC tag. Raises PyCMSError:  

PIL.ImageCms.getProfileModel(profile)

(pyCMS) Gets the model for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile, a PyCMSError is raised.

If an error occurs while trying to obtain the model tag, a PyCMSError is raised

Use this function to obtain the information stored in the profile’s model tag.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:A string containing the internal profile information stored in an ICC tag. Raises PyCMSError:  

PIL.ImageCms.getProfileName(profile)

(pyCMS) Gets the internal product name for the given profile.

If profile isn’t a valid CmsProfile object or filename to a profile,

a PyCMSError is raised If an error occurs while trying to obtain the name tag, a PyCMSError is raised.

Use this function to obtain the INTERNAL name of the profile (stored in an ICC tag in the profile itself), usually the one used when the profile was originally created. Sometimes this tag also contains additional information supplied by the creator.

Parameters:profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile. Returns:A string containing the internal name of the profile as stored in an ICC tag. Raises PyCMSError:  

PIL.ImageCms.get_display_profile(handle=None)

(experimental) Fetches the profile for the current display device. :returns: None if the profile is not known.

PIL.ImageCms.isIntentSupported(profile, intent, direction)

(pyCMS) Checks if a given intent is supported.

Use this function to verify that you can use your desired renderingIntent with profile, and that profile can be used for the input/output/proof profile as you desire.

Some profiles are created specifically for one “direction”, can cannot

be used for others. Some profiles can only be used for certain

rendering intents... so it’s best to either verify this before trying to create a transform with them (using this function), or catch the potential PyCMSError that will occur if they don’t support the modes you select.

Parameters:

• profile – EITHER a valid CmsProfile object, OR a string of the filename of an ICC profile.
• intent –

  Integer (0-3) specifying the rendering intent you wish to use with this profile

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• direction –

  Integer specifing if the profile is to be used for input, output, or proof

  INPUT = 0 (or use ImageCms.DIRECTION_INPUT) OUTPUT = 1 (or use ImageCms.DIRECTION_OUTPUT) PROOF = 2 (or use ImageCms.DIRECTION_PROOF)

Returns:

1 if the intent/direction are supported, -1 if they are not.

Raises PyCMSError:  

PIL.ImageCms.profileToProfile(im, inputProfile, outputProfile, renderingIntent=0, outputMode=None, inPlace=0, flags=0)

(pyCMS) Applies an ICC transformation to a given image, mapping from inputProfile to outputProfile.

If the input or output profiles specified are not valid filenames, a PyCMSError will be raised. If inPlace == TRUE and outputMode != im.mode, a PyCMSError will be raised. If an error occurs during application of the profiles, a PyCMSError will be raised. If outputMode is not a mode supported by the outputProfile (or by pyCMS), a PyCMSError will be raised.

This function applies an ICC transformation to im from inputProfile’s color space to outputProfile’s color space using the specified rendering intent to decide how to handle out-of-gamut colors.

OutputMode can be used to specify that a color mode conversion is to be done using these profiles, but the specified profiles must be able to handle that mode. I.e., if converting im from RGB to CMYK using profiles, the input profile must handle RGB data, and the output profile must handle CMYK data.

Parameters:

• im – An open PIL image object (i.e. Image.new(...) or Image.open(...), etc.)
• inputProfile – String, as a valid filename path to the ICC input profile you wish to use for this image, or a profile object
• outputProfile – String, as a valid filename path to the ICC output profile you wish to use for this image, or a profile object
• renderingIntent –

  Integer (0-3) specifying the rendering intent you wish to use for the transform

  INTENT_PERCEPTUAL = 0 (DEFAULT) (ImageCms.INTENT_PERCEPTUAL) INTENT_RELATIVE_COLORIMETRIC = 1 (ImageCms.INTENT_RELATIVE_COLORIMETRIC) INTENT_SATURATION = 2 (ImageCms.INTENT_SATURATION) INTENT_ABSOLUTE_COLORIMETRIC = 3 (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC)

  see the pyCMS documentation for details on rendering intents and what they do.

• outputMode – A valid PIL mode for the output image (i.e. “RGB”, “CMYK”, etc.). Note: if rendering the image “inPlace”, outputMode MUST be the same mode as the input, or omitted completely. If omitted, the outputMode will be the same as the mode of the input image (im.mode)
• inPlace – Boolean (1 = True, None or 0 = False). If True, the original image is modified in-place, and None is returned. If False (default), a new Image object is returned with the transform applied.
• flags – Integer (0-...) specifying additional flags

Returns:

Either None or a new PIL image object, depending on value of inPlace

Raises PyCMSError:  

PIL.ImageCms.versions()

(pyCMS) Fetches versions.

ImageDraw2 Module

class PIL.ImageDraw2.Brush(color, opacity=255)

class PIL.ImageDraw2.Draw(image, size=None, color=None)

arc(xy, start, end, *options)

chord(xy, start, end, *options)

ellipse(xy, *options)

flush()

line(xy, *options)

pieslice(xy, start, end, *options)

polygon(xy, *options)

rectangle(xy, *options)

render(op, xy, pen, brush=None)

settransform(offset)

symbol(xy, symbol, *options)

text(xy, text, font)

textsize(text, font)

class PIL.ImageDraw2.Font(color, file, size=12)

class PIL.ImageDraw2.Pen(color, width=1, opacity=255)

ImageFileIO Module

The ImageFileIO module can be used to read an image from a socket, or any other stream device.

Deprecated. New code should use the PIL.ImageFile.Parser class in the PIL.ImageFile module instead.

See also

modules PIL.ImageFile.Parser

class PIL.ImageFileIO.ImageFileIO(fp)

Bases: _io.BytesIO

ImageShow Module

class PIL.ImageShow.DisplayViewer

Bases: PIL.ImageShow.UnixViewer

get_command_ex(file, **options)

class PIL.ImageShow.UnixViewer

Bases: PIL.ImageShow.Viewer

show_file(file, **options)

class PIL.ImageShow.Viewer

format = None

get_command(file, **options)

get_format(image)

save_image(image)

show(image, **options)

show_file(file, **options)

show_image(image, **options)

class PIL.ImageShow.XVViewer

Bases: PIL.ImageShow.UnixViewer

get_command_ex(file, title=None, **options)

PIL.ImageShow.register(viewer, order=1)

PIL.ImageShow.show(image, title=None, **options)

PIL.ImageShow.which(executable)

ImageTransform Module

class PIL.ImageTransform.AffineTransform(data)

Bases: PIL.ImageTransform.Transform

method = 0

class PIL.ImageTransform.ExtentTransform(data)

Bases: PIL.ImageTransform.Transform

method = 1

class PIL.ImageTransform.MeshTransform(data)

Bases: PIL.ImageTransform.Transform

method = 4

class PIL.ImageTransform.QuadTransform(data)

Bases: PIL.ImageTransform.Transform

method = 3

class PIL.ImageTransform.Transform(data)

Bases: PIL.Image.ImageTransformHandler

getdata()

transform(size, image, **options)

JpegPresets Module

JPEG quality settings equivalent to the Photoshop settings.

More presets can be added to the presets dict if needed.

Can be use when saving JPEG file.

To apply the preset, specify:

quality="preset_name"

To apply only the quantization table:

qtables="preset_name"

To apply only the subsampling setting:

subsampling="preset_name"

Example:

im.save("image_name.jpg", quality="web_high")

Subsampling

Subsampling is the practice of encoding images by implementing less resolution for chroma information than for luma information. (ref.: http://en.wikipedia.org/wiki/Chroma_subsampling)

Possible subsampling values are 0, 1 and 2 that correspond to 4:4:4, 4:2:2 and 4:1:1 (or 4:2:0?).

You can get the subsampling of a JPEG with the JpegImagePlugin.get_subsampling(im) function.

Quantization tables

They are values use by the DCT (Discrete cosine transform) to remove unnecessary information from the image (the lossy part of the compression). (ref.: http://en.wikipedia.org/wiki/Quantization_matrix#Quantization_matrices, http://en.wikipedia.org/wiki/JPEG#Quantization)

You can get the quantization tables of a JPEG with:

im.quantization

This will return a dict with a number of arrays. You can pass this dict directly as the qtables argument when saving a JPEG.

The tables format between im.quantization and quantization in presets differ in 3 ways:

1. The base container of the preset is a list with sublists instead of dict. dict[0] -> list[0], dict[1] -> list[1], ...
2. Each table in a preset is a list instead of an array.
3. The zigzag order is remove in the preset (needed by libjpeg >= 6a).

You can convert the dict format to the preset format with the JpegImagePlugin.convert_dict_qtables(dict_qtables) function.

Libjpeg ref.: http://www.jpegcameras.com/libjpeg/libjpeg-3.html

OleFileIO Module

OleFileIO_PL:

Module to read Microsoft OLE2 files (also called Structured Storage or Microsoft Compound Document File Format), such as Microsoft Office documents, Image Composer and FlashPix files, Outlook messages, ...

version 0.26 2013-07-24 Philippe Lagadec - http://www.decalage.info

Project website: http://www.decalage.info/python/olefileio

Improved version of the OleFileIO module from PIL library v1.1.6 See: http://www.pythonware.com/products/pil/index.htm

The Python Imaging Library (PIL) is

Copyright (c) 1997-2005 by Secret Labs AB Copyright (c) 1995-2005 by Fredrik Lundh

OleFileIO_PL changes are Copyright (c) 2005-2013 by Philippe Lagadec

See source code and LICENSE.txt for information on usage and redistribution.

WARNING: THIS IS (STILL) WORK IN PROGRESS.

class PIL.OleFileIO.OleFileIO(filename=None, raise_defects=40)

OLE container object

This class encapsulates the interface to an OLE 2 structured storage file. Use the {@link listdir} and {@link openstream} methods to access the contents of this file.

Object names are given as a list of strings, one for each subentry level. The root entry should be omitted. For example, the following code extracts all image streams from a Microsoft Image Composer file:

ole = OleFileIO("fan.mic")

for entry in ole.listdir():
    if entry[1:2] == "Image":
        fin = ole.openstream(entry)
        fout = open(entry[0:1], "wb")
        while True:
            s = fin.read(8192)
            if not s:
                break
            fout.write(s)

You can use the viewer application provided with the Python Imaging Library to view the resulting files (which happens to be standard TIFF files).

close()

close the OLE file, to release the file object

dumpdirectory()

Dump directory (for debugging only)

dumpfat(fat, firstindex=0)

Displays a part of FAT in human-readable form for debugging purpose

dumpsect(sector, firstindex=0)

Displays a sector in a human-readable form, for debugging purpose.

exists(filename)

Test if given filename exists as a stream or a storage in the OLE container.

filename: path of stream in storage tree. (see openstream for syntax) return: True if object exist, else False.

get_metadata()

Parse standard properties streams, return an OleMetadata object containing all the available metadata. (also stored in the metadata attribute of the OleFileIO object)

new in version 0.25

get_rootentry_name()

Return root entry name. Should usually be ‘Root Entry’ or ‘R’ in most implementations.

get_size(filename)

Return size of a stream in the OLE container, in bytes.

filename: path of stream in storage tree (see openstream for syntax) return: size in bytes (long integer) raise: IOError if file not found, TypeError if this is not a stream.

get_type(filename)

Test if given filename exists as a stream or a storage in the OLE container, and return its type.

filename: path of stream in storage tree. (see openstream for syntax) return: False if object does not exist, its entry type (>0) otherwise:

• STGTY_STREAM: a stream
• STGTY_STORAGE: a storage
• STGTY_ROOT: the root entry

getctime(filename)

Return creation time of a stream/storage.

filename: path of stream/storage in storage tree. (see openstream for syntax) return: None if creation time is null, a python datetime object otherwise (UTC timezone)

new in version 0.26

getmtime(filename)

Return modification time of a stream/storage.

filename: path of stream/storage in storage tree. (see openstream for syntax) return: None if modification time is null, a python datetime object otherwise (UTC timezone)

new in version 0.26

getproperties(filename, convert_time=False, no_conversion=None)

Return properties described in substream.

filename: path of stream in storage tree (see openstream for syntax) convert_time: bool, if True timestamps will be converted to Python datetime no_conversion: None or list of int, timestamps not to be converted

(for example total editing time is not a real timestamp)

return: a dictionary of values indexed by id (integer)

getsect(sect)

Read given sector from file on disk. sect: sector index returns a string containing the sector data.

listdir(streams=True, storages=False)

Return a list of streams stored in this file

streams: bool, include streams if True (True by default) - new in v0.26 storages: bool, include storages if True (False by default) - new in v0.26 (note: the root storage is never included)

loaddirectory(sect)

Load the directory. sect: sector index of directory stream.

loadfat(header)

Load the FAT table.

loadfat_sect(sect)

Adds the indexes of the given sector to the FAT sect: string containing the first FAT sector, or array of long integers return: index of last FAT sector.

loadminifat()

Load the MiniFAT table.

open(filename)

Open an OLE2 file. Reads the header, FAT and directory.

filename: string-like or file-like object

openstream(filename)

Open a stream as a read-only file object (BytesIO).

filename: path of stream in storage tree (except root entry), either:

• a string using Unix path syntax, for example: ‘storage_1/storage_1.2/stream’
• a list of storage filenames, path to the desired stream/storage. Example: [‘storage_1’, ‘storage_1.2’, ‘stream’]

return: file object (read-only) raise IOError if filename not found, or if this is not a stream.

sect2array(sect)

convert a sector to an array of 32 bits unsigned integers, swapping bytes on big endian CPUs such as PowerPC (old Macs)

PIL.OleFileIO.isOleFile(filename)

Test if file is an OLE container (according to its header). filename: file name or path (str, unicode) return: True if OLE, False otherwise.

PaletteFile Module

class PIL.PaletteFile.PaletteFile(fp)

getpalette()

rawmode = 'RGB'

PcfFontFile Module

class PIL.PcfFontFile.PcfFontFile(fp)

Bases: PIL.FontFile.FontFile

name = 'name'

PIL.PcfFontFile.sz(s, o)

TarIO Module

class PIL.TarIO.TarIO(tarfile, file)

Bases: PIL.ContainerIO.ContainerIO

TiffTags Module

WalImageFile Module

PIL.WalImageFile.open(filename)

_binary Module

PIL._binary.i16be(c, o=0)

PIL._binary.i16le(c, o=0)

Converts a 2-bytes (16 bits) string to an integer.

c: string containing bytes to convert o: offset of bytes to convert in string

PIL._binary.i32be(c, o=0)

PIL._binary.i32le(c, o=0)

Converts a 4-bytes (32 bits) string to an integer.

c: string containing bytes to convert o: offset of bytes to convert in string

PIL._binary.i8(c)

PIL._binary.o16be(i)

PIL._binary.o16le(i)

PIL._binary.o32be(i)

PIL._binary.o32le(i)

PIL._binary.o8(i)

Appendices

Image file formats

The Python Imaging Library supports a wide variety of raster file formats. Nearly 30 different file formats can be identified and read by the library. Write support is less extensive, but most common interchange and presentation formats are supported.

The open() function identifies files from their contents, not their names, but the save() method looks at the name to determine which format to use, unless the format is given explicitly.

Fully supported formats

BMP

PIL reads and writes Windows and OS/2 BMP files containing 1, L, P, or RGB data. 16-colour images are read as P images. Run-length encoding is not supported.

The open() method sets the following info properties:

compression

Set to bmp_rle if the file is run-length encoded.

EPS

PIL identifies EPS files containing image data, and can read files that contain embedded raster images (ImageData descriptors). If Ghostscript is available, other EPS files can be read as well. The EPS driver can also write EPS images.

If Ghostscript is available, you can call the load() method with the following parameter to affect how Ghostscript renders the EPS

scale

Affects the scale of the resultant rasterized image. If the EPS suggests that the image be rendered at 100px x 100px, setting this parameter to 2 will make the Ghostscript render a 200px x 200px image instead. The relative position of the bounding box is maintained:

im = Image.open(...)
im.size #(100,100)
im.load(scale=2)
im.size #(200,200)

GIF

PIL reads GIF87a and GIF89a versions of the GIF file format. The library writes run-length encoded GIF87a files. Note that GIF files are always read as grayscale (L) or palette mode (P) images.

The open() method sets the following info properties:

background

Default background color (a palette color index).

duration

Time between frames in an animation (in milliseconds).

transparency

Transparency color index. This key is omitted if the image is not transparent.

version

Version (either GIF87a or GIF89a).

Reading sequences

The GIF loader supports the seek() and tell() methods. You can seek to the next frame (im.seek(im.tell() + 1), or rewind the file by seeking to the first frame. Random access is not supported.

Reading local images

The GIF loader creates an image memory the same size as the GIF file’s logical screen size, and pastes the actual pixel data (the local image) into this image. If you only want the actual pixel rectangle, you can manipulate the size and tile attributes before loading the file:

im = Image.open(...)

if im.tile[0][0] == "gif":
    # only read the first "local image" from this GIF file
    tag, (x0, y0, x1, y1), offset, extra = im.tile[0]
    im.size = (x1 - x0, y1 - y0)
    im.tile = [(tag, (0, 0) + im.size, offset, extra)]

IM

IM is a format used by LabEye and other applications based on the IFUNC image processing library. The library reads and writes most uncompressed interchange versions of this format.

IM is the only format that can store all internal PIL formats.

JPEG

PIL reads JPEG, JFIF, and Adobe JPEG files containing L, RGB, or CMYK data. It writes standard and progressive JFIF files.

Using the draft() method, you can speed things up by converting RGB images to L, and resize images to 1/2, 1/4 or 1/8 of their original size while loading them. The draft() method also configures the JPEG decoder to trade some quality for speed.

The open() method sets the following info properties:

jfif

JFIF application marker found. If the file is not a JFIF file, this key is not present.

adobe

Adobe application marker found. If the file is not an Adobe JPEG file, this key is not present.

progression

Indicates that this is a progressive JPEG file.

The save() method supports the following options:

quality

The image quality, on a scale from 1 (worst) to 95 (best). The default is 75. Values above 95 should be avoided; 100 disables portions of the JPEG compression algorithm, and results in large files with hardly any gain in = image quality.

optimize

If present, indicates that the encoder should make an extra pass over the image in order to select optimal encoder settings.

progressive

If present, indicates that this image should be stored as a progressive JPEG file.

Note

To enable JPEG support, you need to build and install the IJG JPEG library before building the Python Imaging Library. See the distribution README for details.

JPEG 2000

New in version 2.4.0.

PIL reads and writes JPEG 2000 files containing L, LA, RGB or RGBA data. It can also read files containing YCbCr data, which it converts on read into RGB or RGBA depending on whether or not there is an alpha channel. PIL supports JPEG 2000 raw codestreams (.j2k files), as well as boxed JPEG 2000 files (.j2p or .jpx files). PIL does not support files whose components have different sampling frequencies.

When loading, if you set the mode on the image prior to the load() method being invoked, you can ask PIL to convert the image to either RGB or RGBA rather than choosing for itself. It is also possible to set reduce to the number of resolutions to discard (each one reduces the size of the resulting image by a factor of 2), and layers to specify the number of quality layers to load.

The save() method supports the following options:

offset

The image offset, as a tuple of integers, e.g. (16, 16)

tile_offset

The tile offset, again as a 2-tuple of integers.

tile_size

The tile size as a 2-tuple. If not specified, or if set to None, the image will be saved without tiling.

quality_mode

Either “rates” or “dB” depending on the units you want to use to specify image quality.

quality_layers

A sequence of numbers, each of which represents either an approximate size reduction (if quality mode is “rates”) or a signal to noise ratio value in decibels. If not specified, defaults to a single layer of full quality.

num_resolutions

The number of different image resolutions to be stored (which corresponds to the number of Discrete Wavelet Transform decompositions plus one).

codeblock_size

The code-block size as a 2-tuple. Minimum size is 4 x 4, maximum is 1024 x 1024, with the additional restriction that no code-block may have more than 4096 coefficients (i.e. the product of the two numbers must be no greater than 4096).

precinct_size

The precinct size as a 2-tuple. Must be a power of two along both axes, and must be greater than the code-block size.

irreversible

If True, use the lossy Irreversible Color Transformation followed by DWT 9-7. Defaults to False, which means to use the Reversible Color Transformation with DWT 5-3.

progression

Controls the progression order; must be one of "LRCP", "RLCP", "RPCL", "PCRL", "CPRL". The letters stand for Component, Position, Resolution and Layer respectively and control the order of encoding, the idea being that e.g. an image encoded using LRCP mode can have its quality layers decoded as they arrive at the decoder, while one encoded using RLCP mode will have increasing resolutions decoded as they arrive, and so on.

cinema_mode

Set the encoder to produce output compliant with the digital cinema specifications. The options here are "no" (the default), "cinema2k-24" for 24fps 2K, "cinema2k-48" for 48fps 2K, and "cinema4k-24" for 24fps 4K. Note that for compliant 2K files, at least one of your image dimensions must match 2048 x 1080, while for compliant 4K files, at least one of the dimensions must match 4096 x 2160.

Note

To enable JPEG 2000 support, you need to build and install the OpenJPEG library, version 2.0.0 or higher, before building the Python Imaging Library.

Windows users can install the OpenJPEG binaries available on the OpenJPEG website, but must add them to their PATH in order to use PIL (if you fail to do this, you will get errors about not being able to load the _imaging DLL).

MSP

PIL identifies and reads MSP files from Windows 1 and 2. The library writes uncompressed (Windows 1) versions of this format.

PCX

PIL reads and writes PCX files containing 1, L, P, or RGB data.

PNG

PIL identifies, reads, and writes PNG files containing 1, L, P, RGB, or RGBA data. Interlaced files are supported as of v1.1.7.

The open() method sets the following info properties, when appropriate:

gamma

Gamma, given as a floating point number.

transparency

Transparency color index. This key is omitted if the image is not a transparent palette image.

The save() method supports the following options:

optimize

If present, instructs the PNG writer to make the output file as small as possible. This includes extra processing in order to find optimal encoder settings.

transparency

For P, L, and RGB images, this option controls what color image to mark as transparent.

bits (experimental)

For P images, this option controls how many bits to store. If omitted, the PNG writer uses 8 bits (256 colors).

dictionary (experimental)

Set the ZLIB encoder dictionary.

Note

To enable PNG support, you need to build and install the ZLIB compression library before building the Python Imaging Library. See the distribution README for details.

PPM

PIL reads and writes PBM, PGM and PPM files containing 1, L or RGB data.

SPIDER

PIL reads and writes SPIDER image files of 32-bit floating point data (“F;32F”).

PIL also reads SPIDER stack files containing sequences of SPIDER images. The seek() and tell() methods are supported, and random access is allowed.

The open() method sets the following attributes:

format

Set to SPIDER

istack

Set to 1 if the file is an image stack, else 0.

nimages

Set to the number of images in the stack.

A convenience method, convert2byte(), is provided for converting floating point data to byte data (mode L):

im = Image.open('image001.spi').convert2byte()

Writing files in SPIDER format

The extension of SPIDER files may be any 3 alphanumeric characters. Therefore the output format must be specified explicitly:

im.save('newimage.spi', format='SPIDER')

For more information about the SPIDER image processing package, see the SPIDER home page at Wadsworth Center.

TIFF

PIL reads and writes TIFF files. It can read both striped and tiled images, pixel and plane interleaved multi-band images, and either uncompressed, or Packbits, LZW, or JPEG compressed images.

If you have libtiff and its headers installed, PIL can read and write many more kinds of compressed TIFF files. If not, PIL will always write uncompressed files.

The open() method sets the following info properties:

compression

Compression mode.

dpi

Image resolution as an (xdpi, ydpi) tuple, where applicable. You can use the tag attribute to get more detailed information about the image resolution.

New in version 1.1.5.

In addition, the tag attribute contains a dictionary of decoded TIFF fields. Values are stored as either strings or tuples. Note that only short, long and ASCII tags are correctly unpacked by this release.

Saving Tiff Images

The save() method can take the following keyword arguments:

tiffinfo

A ImageFileDirectory object or dict object containing tiff tags and values. The TIFF field type is autodetected for Numeric and string values, any other types require using an ImageFileDirectory object and setting the type in tagtype with the appropriate numerical value from TiffTags.TYPES.

New in version 2.3.0.

compression

A string containing the desired compression method for the

file. (valid only with libtiff installed) Valid compression methods are: [None, "tiff_ccitt", "group3", "group4", "tiff_jpeg", "tiff_adobe_deflate", "tiff_thunderscan", "tiff_deflate", "tiff_sgilog", "tiff_sgilog24", "tiff_raw_16"]

These arguments to set the tiff header fields are an alternative to using the general tags available through tiffinfo.

description

software

date time

artist

copyright

Strings

resolution unit

A string of “inch”, “centimeter” or “cm”

resolution

x resolution

y resolution

dpi

Either a Float, Integer, or 2 tuple of (numerator, denominator). Resolution implies an equal x and y resolution, dpi also implies a unit of inches.

WebP

PIL reads and writes WebP files. The specifics of PIL’s capabilities with this format are currently undocumented.

The save() method supports the following options:

lossless

If present, instructs the WEBP writer to use lossless compression.

quality

Integer, 1-100, Defaults to 80. Sets the quality level for lossy compression.

icc_procfile

The ICC Profile to include in the saved file. Only supported if the system webp library was built with webpmux support.

exif

The exif data to include in the saved file. Only supported if the system webp library was built with webpmux support.

XBM

PIL reads and writes X bitmap files (mode 1).

XV Thumbnails

PIL can read XV thumbnail files.

Read-only formats

CUR

CUR is used to store cursors on Windows. The CUR decoder reads the largest available cursor. Animated cursors are not supported.

DCX

DCX is a container file format for PCX files, defined by Intel. The DCX format is commonly used in fax applications. The DCX decoder can read files containing 1, L, P, or RGB data.

When the file is opened, only the first image is read. You can use seek() or ImageSequence to read other images.

FLI, FLC

PIL reads Autodesk FLI and FLC animations.

The open() method sets the following info properties:

duration

The delay (in milliseconds) between each frame.

FPX

PIL reads Kodak FlashPix files. In the current version, only the highest resolution image is read from the file, and the viewing transform is not taken into account.

Note

To enable full FlashPix support, you need to build and install the IJG JPEG library before building the Python Imaging Library. See the distribution README for details.

GBR

The GBR decoder reads GIMP brush files.

The open() method sets the following info properties:

description

The brush name.

GD

PIL reads uncompressed GD files. Note that this file format cannot be automatically identified, so you must use PIL.GdImageFile.open() to read such a file.

The open() method sets the following info properties:

transparency

Transparency color index. This key is omitted if the image is not transparent.

ICO

ICO is used to store icons on Windows. The largest available icon is read.

ICNS

PIL reads Mac OS X .icns files. By default, the largest available icon is read, though you can override this by setting the size property before calling load(). The open() method sets the following info property:

sizes

A list of supported sizes found in this icon file; these are a 3-tuple, (width, height, scale), where scale is 2 for a retina icon and 1 for a standard icon. You are permitted to use this 3-tuple format for the size property if you set it before calling load(); after loading, the size will be reset to a 2-tuple containing pixel dimensions (so, e.g. if you ask for (512, 512, 2), the final value of size will be (1024, 1024)).

IMT

PIL reads Image Tools images containing L data.

IPTC/NAA

PIL provides limited read support for IPTC/NAA newsphoto files.

MCIDAS

PIL identifies and reads 8-bit McIdas area files.

MIC (read only)

PIL identifies and reads Microsoft Image Composer (MIC) files. When opened, the first sprite in the file is loaded. You can use seek() and tell() to read other sprites from the file.

PCD

PIL reads PhotoCD files containing RGB data. By default, the 768x512 resolution is read. You can use the draft() method to read the lower resolution versions instead, thus effectively resizing the image to 384x256 or 192x128. Higher resolutions cannot be read by the Python Imaging Library.

PSD

PIL identifies and reads PSD files written by Adobe Photoshop 2.5 and 3.0.

SGI

PIL reads uncompressed L, RGB, and RGBA files.

TGA

PIL reads 24- and 32-bit uncompressed and run-length encoded TGA files.

WAL

New in version 1.1.4.

PIL reads Quake2 WAL texture files.

Note that this file format cannot be automatically identified, so you must use the open function in the WalImageFile module to read files in this format.

By default, a Quake2 standard palette is attached to the texture. To override the palette, use the putpalette method.

XPM

PIL reads X pixmap files (mode P) with 256 colors or less.

The open() method sets the following info properties:

transparency

Transparency color index. This key is omitted if the image is not transparent.

Write-only formats

PALM

PIL provides write-only support for PALM pixmap files.

The format code is Palm, the extension is .palm.

PDF

PIL can write PDF (Acrobat) images. Such images are written as binary PDF 1.1 files, using either JPEG or HEX encoding depending on the image mode (and whether JPEG support is available or not).

PIXAR (read only)

PIL provides limited support for PIXAR raster files. The library can identify and read “dumped” RGB files.

The format code is PIXAR.

Identify-only formats

BUFR

New in version 1.1.3.

PIL provides a stub driver for BUFR files.

To add read or write support to your application, use PIL.BufrStubImagePlugin.register_handler().

FITS

New in version 1.1.5.

PIL provides a stub driver for FITS files.

To add read or write support to your application, use PIL.FitsStubImagePlugin.register_handler().

GRIB

New in version 1.1.5.

PIL provides a stub driver for GRIB files.

The driver requires the file to start with a GRIB header. If you have files with embedded GRIB data, or files with multiple GRIB fields, your application has to seek to the header before passing the file handle to PIL.

To add read or write support to your application, use PIL.GribStubImagePlugin.register_handler().

HDF5

New in version 1.1.5.

PIL provides a stub driver for HDF5 files.

To add read or write support to your application, use PIL.Hdf5StubImagePlugin.register_handler().

MPEG

PIL identifies MPEG files.

WMF

PIL can identify placable WMF files.

In PIL 1.1.4 and earlier, the WMF driver provides some limited rendering support, but not enough to be useful for any real application.

In PIL 1.1.5 and later, the WMF driver is a stub driver. To add WMF read or write support to your application, use PIL.WmfImagePlugin.register_handler() to register a WMF handler.

from PIL import Image
from PIL import WmfImagePlugin

class WmfHandler:
    def open(self, im):
        ...
    def load(self, im):
        ...
        return image
    def save(self, im, fp, filename):
        ...

wmf_handler = WmfHandler()

WmfImagePlugin.register_handler(wmf_handler)

im = Image.open("sample.wmf")

Writing your own file decoder

The Python Imaging Library uses a plug-in model which allows you to add your own decoders to the library, without any changes to the library itself. Such plug-ins usually have names like XxxImagePlugin.py, where Xxx is a unique format name (usually an abbreviation).

Warning

Pillow >= 2.1.0 no longer automatically imports any file in the Python path with a name ending in ImagePlugin.py. You will need to import your decoder manually.

A decoder plug-in should contain a decoder class, based on the PIL.ImageFile.ImageFile base class. This class should provide an _open() method, which reads the file header and sets up at least the mode and size attributes. To be able to load the file, the method must also create a list of tile descriptors. The class must be explicitly registered, via a call to the Image module.

For performance reasons, it is important that the _open() method quickly rejects files that do not have the appropriate contents.

Example

The following plug-in supports a simple format, which has a 128-byte header consisting of the words “SPAM” followed by the width, height, and pixel size in bits. The header fields are separated by spaces. The image data follows directly after the header, and can be either bi-level, greyscale, or 24-bit true color.

SpamImagePlugin.py:

from PIL import Image, ImageFile
import string

class SpamImageFile(ImageFile.ImageFile):

    format = "SPAM"
    format_description = "Spam raster image"

    def _open(self):

        # check header
        header = self.fp.read(128)
        if header[:4] != "SPAM":
            raise SyntaxError, "not a SPAM file"

        header = string.split(header)

        # size in pixels (width, height)
        self.size = int(header[1]), int(header[2])

        # mode setting
        bits = int(header[3])
        if bits == 1:
            self.mode = "1"
        elif bits == 8:
            self.mode = "L"
        elif bits == 24:
            self.mode = "RGB"
        else:
            raise SyntaxError, "unknown number of bits"

        # data descriptor
        self.tile = [
            ("raw", (0, 0) + self.size, 128, (self.mode, 0, 1))
        ]

Image.register_open("SPAM", SpamImageFile)

Image.register_extension("SPAM", ".spam")
Image.register_extension("SPAM", ".spa") # dos version

The format handler must always set the size and mode attributes. If these are not set, the file cannot be opened. To simplify the decoder, the calling code considers exceptions like SyntaxError, KeyError, and IndexError, as a failure to identify the file.

Note that the decoder must be explicitly registered using PIL.Image.register_open(). Although not required, it is also a good idea to register any extensions used by this format.

The tile attribute

To be able to read the file as well as just identifying it, the tile attribute must also be set. This attribute consists of a list of tile descriptors, where each descriptor specifies how data should be loaded to a given region in the image. In most cases, only a single descriptor is used, covering the full image.

The tile descriptor is a 4-tuple with the following contents:

(decoder, region, offset, parameters)

The fields are used as follows:

decoder

Specifies which decoder to use. The raw decoder used here supports uncompressed data, in a variety of pixel formats. For more information on this decoder, see the description below.

region

A 4-tuple specifying where to store data in the image.

offset

Byte offset from the beginning of the file to image data.

parameters

Parameters to the decoder. The contents of this field depends on the decoder specified by the first field in the tile descriptor tuple. If the decoder doesn’t need any parameters, use None for this field.

Note that the tile attribute contains a list of tile descriptors, not just a single descriptor.

The raw decoder

The raw decoder is used to read uncompressed data from an image file. It can be used with most uncompressed file formats, such as PPM, BMP, uncompressed TIFF, and many others. To use the raw decoder with the PIL.Image.fromstring() function, use the following syntax:

image = Image.fromstring(
    mode, size, data, "raw",
    raw mode, stride, orientation
    )

When used in a tile descriptor, the parameter field should look like:

(raw mode, stride, orientation)

The fields are used as follows:

raw mode

The pixel layout used in the file, and is used to properly convert data to PIL’s internal layout. For a summary of the available formats, see the table below.

stride

The distance in bytes between two consecutive lines in the image. If 0, the image is assumed to be packed (no padding between lines). If omitted, the stride defaults to 0.

orientation

Whether the first line in the image is the top line on the screen (1), or the bottom line (-1). If omitted, the orientation defaults to 1.

The raw mode field is used to determine how the data should be unpacked to match PIL’s internal pixel layout. PIL supports a large set of raw modes; for a complete list, see the table in the Unpack.c module. The following table describes some commonly used raw modes:

mode	description
1	1-bit bilevel, stored with the leftmost pixel in the most significant bit. 0 means black, 1 means white.
1;I	1-bit inverted bilevel, stored with the leftmost pixel in the most significant bit. 0 means white, 1 means black.
1;R	1-bit reversed bilevel, stored with the leftmost pixel in the least significant bit. 0 means black, 1 means white.
L	8-bit greyscale. 0 means black, 255 means white.
L;I	8-bit inverted greyscale. 0 means white, 255 means black.
P	8-bit palette-mapped image.
RGB	24-bit true colour, stored as (red, green, blue).
BGR	24-bit true colour, stored as (blue, green, red).
RGBX	24-bit true colour, stored as (blue, green, red, pad).
RGB;L	24-bit true colour, line interleaved (first all red pixels, the all green pixels, finally all blue pixels).

Note that for the most common cases, the raw mode is simply the same as the mode.

The Python Imaging Library supports many other decoders, including JPEG, PNG, and PackBits. For details, see the decode.c source file, and the standard plug-in implementations provided with the library.

Decoding floating point data

PIL provides some special mechanisms to allow you to load a wide variety of formats into a mode F (floating point) image memory.

You can use the raw decoder to read images where data is packed in any standard machine data type, using one of the following raw modes:

mode	description
F	32-bit native floating point.
F;8	8-bit unsigned integer.
F;8S	8-bit signed integer.
F;16	16-bit little endian unsigned integer.
F;16S	16-bit little endian signed integer.
F;16B	16-bit big endian unsigned integer.
F;16BS	16-bit big endian signed integer.
F;16N	16-bit native unsigned integer.
F;16NS	16-bit native signed integer.
F;32	32-bit little endian unsigned integer.
F;32S	32-bit little endian signed integer.
F;32B	32-bit big endian unsigned integer.
F;32BS	32-bit big endian signed integer.
F;32N	32-bit native unsigned integer.
F;32NS	32-bit native signed integer.
F;32F	32-bit little endian floating point.
F;32BF	32-bit big endian floating point.
F;32NF	32-bit native floating point.
F;64F	64-bit little endian floating point.
F;64BF	64-bit big endian floating point.
F;64NF	64-bit native floating point.

The bit decoder

If the raw decoder cannot handle your format, PIL also provides a special “bit” decoder that can be used to read various packed formats into a floating point image memory.

To use the bit decoder with the fromstring function, use the following syntax:

image = fromstring(
    mode, size, data, "bit",
    bits, pad, fill, sign, orientation
    )

When used in a tile descriptor, the parameter field should look like:

(bits, pad, fill, sign, orientation)

The fields are used as follows:

bits

Number of bits per pixel (2-32). No default.

pad

Padding between lines, in bits. This is either 0 if there is no padding, or 8 if lines are padded to full bytes. If omitted, the pad value defaults to 8.

fill

Controls how data are added to, and stored from, the decoder bit buffer.

fill=0

Add bytes to the LSB end of the decoder buffer; store pixels from the MSB end.

fill=1

Add bytes to the MSB end of the decoder buffer; store pixels from the MSB end.

fill=2

Add bytes to the LSB end of the decoder buffer; store pixels from the LSB end.

fill=3

Add bytes to the MSB end of the decoder buffer; store pixels from the LSB end.

If omitted, the fill order defaults to 0.

sign

If non-zero, bit fields are sign extended. If zero or omitted, bit fields are unsigned.

orientation

Whether the first line in the image is the top line on the screen (1), or the bottom line (-1). If omitted, the orientation defaults to 1.

Original PIL README

What follows is the original PIL 1.1.7 README file contents.

The Python Imaging Library
$Id$

Release 1.1.7 (November 15, 2009)

====================================================================
The Python Imaging Library 1.1.7
====================================================================

Contents
--------

+ Introduction
+ Support Options
  - Commercial support
  - Free support
+ Software License
+ Build instructions (all platforms)
  - Additional notes for Mac OS X
  - Additional notes for Windows

--------------------------------------------------------------------
Introduction
--------------------------------------------------------------------

The Python Imaging Library (PIL) adds image processing capabilities
to your Python environment.  This library provides extensive file
format support, an efficient internal representation, and powerful
image processing capabilities.

This source kit has been built and tested with Python 2.0 and newer,
on Windows, Mac OS X, and major Unix platforms.  Large parts of the
library also work on 1.5.2 and 1.6.

The main distribution site for this software is:

        http://www.pythonware.com/products/pil/

That site also contains information about free and commercial support
options, PIL add-ons, answers to frequently asked questions, and more.


Development versions (alphas, betas) are available here:

        http://effbot.org/downloads/


The PIL handbook is not included in this distribution; to get the
latest version, check:

        http://www.pythonware.com/library/
        http://effbot.org/books/imagingbook/ (drafts)


For installation and licensing details, see below.


--------------------------------------------------------------------
Support Options
--------------------------------------------------------------------

+ Commercial Support

Secret Labs (PythonWare) offers support contracts for companies using
the Python Imaging Library in commercial applications, and in mission-
critical environments.  The support contract includes technical support,
bug fixes, extensions to the PIL library, sample applications, and more.

For the full story, check:

        http://www.pythonware.com/products/pil/support.htm


+ Free Support

For support and general questions on the Python Imaging Library, send
e-mail to the Image SIG mailing list:

        image-sig@python.org

You can join the Image SIG by sending a mail to:

        image-sig-request@python.org

Put "subscribe" in the message body to automatically subscribe to the
list, or "help" to get additional information.  Alternatively, you can
send your questions to the Python mailing list, python-list@python.org,
or post them to the newsgroup comp.lang.python.  DO NOT SEND SUPPORT
QUESTIONS TO PYTHONWARE ADDRESSES.


--------------------------------------------------------------------
Software License
--------------------------------------------------------------------

The Python Imaging Library is

Copyright (c) 1997-2009 by Secret Labs AB
Copyright (c) 1995-2009 by Fredrik Lundh

By obtaining, using, and/or copying this software and/or its
associated documentation, you agree that you have read, understood,
and will comply with the following terms and conditions:

Permission to use, copy, modify, and distribute this software and its
associated documentation for any purpose and without fee is hereby
granted, provided that the above copyright notice appears in all
copies, and that both that copyright notice and this permission notice
appear in supporting documentation, and that the name of Secret Labs
AB or the author not be used in advertising or publicity pertaining to
distribution of the software without specific, written prior
permission.

SECRET LABS AB AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO
THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS.  IN NO EVENT SHALL SECRET LABS AB OR THE AUTHOR BE LIABLE FOR
ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.


--------------------------------------------------------------------
Build instructions (all platforms)
--------------------------------------------------------------------

For a list of changes in this release, see the CHANGES document.

0. If you're in a hurry, try this:

        $ tar xvfz Imaging-1.1.7.tar.gz
        $ cd Imaging-1.1.7
        $ python setup.py install

   If you prefer to know what you're doing, read on.


1. Prerequisites.

   If you need any of the features described below, make sure you
   have the necessary libraries before building PIL.

   feature              library
   -----------------------------------------------------------------
   JPEG support         libjpeg (6a or 6b)

                        http://www.ijg.org
                        http://www.ijg.org/files/jpegsrc.v6b.tar.gz
                        ftp://ftp.uu.net/graphics/jpeg/

   PNG support          zlib (1.2.3 or later is recommended)

                        http://www.gzip.org/zlib/

   OpenType/TrueType    freetype2 (2.3.9 or later is recommended)
   support
                        http://www.freetype.org
                        http://freetype.sourceforge.net

   CMS support          littleCMS (1.1.5 or later is recommended)
   support
                        http://www.littlecms.com/

   If you have a recent Linux version, the libraries provided with the
   operating system usually work just fine.  If some library is
   missing, installing a prebuilt version (jpeg-devel, zlib-devel,
   etc) is usually easier than building from source.  For example, for
   Ubuntu 9.10 (karmic), you can install the following libraries:

       sudo apt-get install libjpeg62-dev
       sudo apt-get install zlib1g-dev
       sudo apt-get install libfreetype6-dev
       sudo apt-get install liblcms1-dev

   If you're using Mac OS X, you can use the 'fink' tool to install
   missing libraries (also see the Mac OS X section below).

   Similar tools are available for many other platforms.


2. To build under Python 1.5.2, you need to install the stand-alone
   version of the distutils library:

       http://www.python.org/sigs/distutils-sig/download.html

   You can fetch distutils 1.0.2 from the Python source repository:

       svn export http://svn.python.org/projects/python/tags/Distutils-1_0_2/Lib/distutils/

   For newer releases, the distutils library is included in the
   Python standard library.

   NOTE: Version 1.1.7 is not fully compatible with 1.5.2.  Some
   more recent additions to the library may not work, but the core
   functionality is available.


3. If you didn't build Python from sources, make sure you have
   Python's build support files on your machine.  If you've down-
   loaded a prebuilt package (e.g. a Linux RPM), you probably
   need additional developer packages.  Look for packages named
   "python-dev", "python-devel", or similar.  For example, for
   Ubuntu 9.10 (karmic), use the following command:

       sudo apt-get install python-dev


4. When you have everything you need, unpack the PIL distribution
   (the file Imaging-1.1.7.tar.gz) in a suitable work directory:

        $ cd MyExtensions # example
        $ gunzip Imaging-1.1.7.tar.gz
        $ tar xvf Imaging-1.1.7.tar


5. Build the library.  We recommend that you do an in-place build,
   and run the self test before installing.

        $ cd Imaging-1.1.7
        $ python setup.py build_ext -i
        $ python selftest.py

   During the build process, the setup.py will display a summary
   report that lists what external components it found.  The self-
   test will display a similar report, with what external components
   the tests found in the actual build files:

        ----------------------------------------------------------------
        PIL 1.1.7 SETUP SUMMARY
        ----------------------------------------------------------------
        *** TKINTER support not available (Tcl/Tk 8.5 libraries needed)
        --- JPEG support available
        --- ZLIB (PNG/ZIP) support available
        --- FREETYPE support available
        ----------------------------------------------------------------

   Make sure that the optional components you need are included.

   If the build script won't find a given component, you can edit the
   setup.py file and set the appropriate ROOT variable.  For details,
   see instructions in the file.

   If the build script finds the component, but the tests cannot
   identify it, try rebuilding *all* modules:

        $ python setup.py clean
        $ python setup.py build_ext -i


6. If the setup.py and selftest.py commands finish without any
   errors, you're ready to install the library:

        $ python setup.py install

   (depending on how Python has been installed on your machine,
   you might have to log in as a superuser to run the 'install'
   command, or use the 'sudo' command to run 'install'.)


--------------------------------------------------------------------
Additional notes for Mac OS X
--------------------------------------------------------------------

On Mac OS X you will usually install additional software such as
libjpeg or freetype with the "fink" tool, and then it ends up in
"/sw".  If you have installed the libraries elsewhere, you may have
to tweak the "setup.py" file before building.


--------------------------------------------------------------------
Additional notes for Windows
--------------------------------------------------------------------

On Windows, you need to tweak the ROOT settings in the "setup.py"
file, to make it find the external libraries.  See comments in the
file for details.

Make sure to build PIL and the external libraries with the same
runtime linking options as was used for the Python interpreter
(usually /MD, under Visual Studio).


Note that most Python distributions for Windows include libraries
compiled for Microsoft Visual Studio.  You can get the free Express
edition of Visual Studio from:

    http://www.microsoft.com/Express/

To build extensions using other tool chains, see the "Using
non-Microsoft compilers on Windows" section in the distutils handbook:

    http://www.python.org/doc/current/inst/non-ms-compilers.html

For additional information on how to build extensions using the
popular MinGW compiler, see:

    http://mingw.org (compiler)
    http://sebsauvage.net/python/mingw.html (build instructions)
    http://sourceforge.net/projects/gnuwin32 (prebuilt libraries)

Support Pillow!

PIL needs you! Please help us maintain the Python Imaging Library here:

• GitHub
• Freenode
• Image-SIG

Financial

Pillow is a volunteer effort led by Alex Clark. If you can’t help with development please consider helping us financially. Your assistance would be very much appreciated!

Note

Contributors please add your name and donation preference here.

Developer	Preference
Alex Clark (fork author)	http://gittip.com/aclark4life

Indices and tables

• Index
• Module Index
• Search Page