Pillow

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

Documentation Status Travis CI build status (Linux) Travis CI build status (macOS) AppVeyor CI build status (Windows) Latest PyPI version Number of PyPI downloads Code coverage Code health

Installation

Warnings

Warning

Pillow and PIL cannot co-exist in the same environment. Before installing Pillow, please uninstall PIL.

Warning

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

Warning

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

Notes

Note

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

Note

Pillow >= 2.0.0 < 3.5.0 supports Python versions 2.6, 2.7, 3.2, 3.3, 3.4, 3.5

Note

Pillow >= 3.5.0 supports Python versions 2.7, 3.3, 3.4, 3.5, 3.6

Basic Installation

Note

The following instructions will install Pillow with support for most common image formats. See External Libraries for a full list of external libraries supported.

Note

The basic installation works on Windows and macOS using the binaries from PyPI. Other installations require building from source as detailed below.

Install Pillow with pip:

$ pip install Pillow

Or use easy_install for installing Python Eggs as pip does not support them:

$ easy_install Pillow

Windows Installation

We provide Pillow binaries for Windows compiled for the matrix of supported Pythons in both 32 and 64-bit versions in wheel, egg, and executable installers. These binaries have all of the optional libraries included:

> pip install Pillow

or:

> easy_install Pillow

macOS Installation

We provide binaries for macOS for each of the supported Python versions in the wheel format. These include support for all optional libraries except OpenJPEG:

$ pip install Pillow

Linux Installation

We do not provide binaries for Linux. Most major Linux distributions, including Fedora, Debian/Ubuntu and ArchLinux include Pillow in packages that previously contained PIL e.g. python-imaging. Please consider using native operating system packages first to avoid installation problems and/or missing library support later.

FreeBSD Installation

Pillow can be installed on FreeBSD via the official Ports or Packages systems:

Ports:

$ cd /usr/ports/graphics/py-pillow && make install clean

Packages:

$ pkg install py27-pillow

Note

The Pillow FreeBSD port and packages are tested by the ports team with all supported FreeBSD versions and against Python 2.x and 3.x.

Building From Source

Download and extract the compressed archive from PyPI.

External Libraries

Note

You do not need to install all supported external libraries to use Pillow’s basic features. Zlib and libjpeg are required by default.

Note

There are scripts to install the dependencies for some operating systems included in the depends directory.

Many of Pillow’s features require external libraries:

  • libjpeg provides JPEG functionality.
    • Pillow has been tested with libjpeg versions 6b, 8, 9, 9a, and 9b and libjpeg-turbo version 8.
    • Starting with Pillow 3.0.0, libjpeg is required by default, but may be disabled with the --disable-jpeg flag.
  • zlib provides access to compressed PNGs
    • Starting with Pillow 3.0.0, zlib is required by default, but may be disabled with the --disable-zlib flag.
  • libtiff provides compressed 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 2.7.
  • 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 above 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 and 2.1.0.
    • Pillow does not support the earlier 1.5 series which ships with Ubuntu and Debian.
  • libimagequant provides improved color quantization
    • Pillow has been tested with libimagequant 2.6.0
    • Libimagequant is licensed GPLv3, which is more restrictive than the Pillow license, therefore we will not be distributing binaries with libimagequant support enabled.
    • Windows support: Libimagequant requires VS2013/MSVC 18 to compile, so it is unlikely to work with any Python prior to 3.5 on Windows.

Once you have installed the prerequisites, run:

$ pip install Pillow

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 by editing setup.py or setup.cfg, or by adding environment variables on the command line:

$ CFLAGS="-I/usr/pkg/include" pip install pillow

If Pillow has been previously built without the required prerequisites, it may be necessary to manually clear the pip cache or build without cache using the --no-cache-dir option to force a build with newly installed external libraries.

Build Options

  • Environment Variable: MAX_CONCURRENCY=n. By default, Pillow will use multiprocessing to build the extension on all available CPUs, but not more than 4. Setting MAX_CONCURRENCY to 1 will disable parallel building.
  • Build flags: --disable-zlib, --disable-jpeg, --disable-tiff, --disable-freetype, --disable-tcl, --disable-tk, --disable-lcms, --disable-webp, --disable-webpmux, --disable-jpeg2000, --disable-imagequant. Disable building the corresponding feature even if the development libraries are present on the building machine.
  • Build flags: --enable-zlib, --enable-jpeg, --enable-tiff, --enable-freetype, --enable-tcl, --enable-tk, --enable-lcms, --enable-webp, --enable-webpmux, --enable-jpeg2000, --enable-imagequant. Require that the corresponding feature is built. The build will raise an exception if the libraries are not found. Webpmux (WebP metadata) relies on WebP support. Tcl and Tk also must be used together.
  • Build flag: --disable-platform-guessing. Skips all of the platform dependent guessing of include and library directories for automated build systems that configure the proper paths in the environment variables (e.g. Buildroot).
  • Build flag: --debug. Adds a debugging flag to the include and library search process to dump all paths searched for and found to stdout.

Sample Usage:

$ MAX_CONCURRENCY=1 python setup.py build_ext --enable-[feature] install

or using pip:

$ pip install pillow --global-option="build_ext" --global-option="--enable-[feature]"

Building on macOS

The Xcode command line tools are required to compile portions of Pillow. The tools are installed by running xcode-select --install from the command line. The command line tools are required even if you have the full Xcode package installed. It may be necessary to run sudo xcodebuild -license to accept the license prior to using the tools.

The easiest way to install external libraries is via Homebrew. After you install Homebrew, run:

$ brew install libtiff libjpeg webp little-cms2

Install Pillow with:

$ pip install Pillow

or from within the uncompressed source directory:

$ python setup.py install

Building on Windows

We don’t recommend trying to build on Windows. It is a maze of twisty passages, mostly dead ends. There are build scripts and notes for the Windows build in the winbuild directory.

Building on FreeBSD

Note

Only FreeBSD 10 tested

Make sure you have Python’s development libraries installed.:

$ sudo pkg install python2

Or for Python 3:

$ sudo pkg install python3

Prerequisites are installed on FreeBSD 10 with:

$ sudo pkg install jpeg tiff webp lcms2 freetype2

Building on 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 dnf install python-devel redhat-rpm-config

Or for Python 3:

$ sudo dnf install python3-devel redhat-rpm-config

Note

redhat-rpm-config is required on Fedora 23, but not earlier versions.

Prerequisites are installed 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 Ubuntu 14.04 LTS with:

$ sudo apt-get install libtiff5-dev libjpeg8-dev zlib1g-dev \
    libfreetype6-dev liblcms2-dev libwebp-dev tcl8.6-dev tk8.6-dev python-tk

Prerequisites are installed on Fedora 23 with:

$ sudo dnf install libtiff-devel libjpeg-devel zlib-devel freetype-devel \
    lcms2-devel libwebp-devel tcl-devel tk-devel

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, macOS, and Windows.

Note

Contributors please test Pillow on your platform then update this document and send a pull request.

Operating system Supported Tested Python versions Latest tested Pillow version Tested processors
Mac OS X 10.11 El Capitan Yes 2.7,3.3,3.4,3.5 3.4.1 x86-64
Mac OS X 10.10 Yosemite Yes 2.7,3.3,3.4 3.0.0 x86-64
Mac OS X 10.9 Mavericks Yes 2.7,3.2,3.3,3.4 3.0.0 x86-64
Mac OS X 10.8 Mountain Lion Yes 2.6,2.7,3.2,3.3   x86-64
Redhat Linux 6 Yes 2.6   x86
CentOS 6.3 Yes 2.7,3.3   x86
Fedora 23 Yes 2.7,3.4 3.1.0 x86-64
Ubuntu Linux 10.04 LTS Yes 2.6 2.3.0 x86,x86-64
Ubuntu Linux 12.04 LTS Yes

2.6,2.7,3.2,3.3,3.4,3.5 PyPy5.3.1,PyPy3 v2.4.0

2.7,3.2

3.4.1 (CI target)

3.4.1

x86,x86-64

ppc

Ubuntu Linux 14.04 LTS Yes 2.7,3.4 3.1.0 x86-64
Debian 8.2 Jessie Yes 2.7,3.4 3.1.0 x86-64
Raspian Jessie Yes 2.7,3.4 3.1.0 arm
Gentoo Linux Yes 2.7,3.2 2.1.0 x86-64
Arch Linux Yes 2.7,3.5 3.4.1 x86,x86-64
FreeBSD 10.2 Yes 2.7,3.4 3.1.0 x86-64
Windows 7 Pro Yes 2.7,3.2,3.3 3.4.1 x86-64
Windows Server 2008 R2 Enterprise Yes 3.3   x86-64
Windows Server 2012 R2 Yes 2.7,3.3,3.4 3.4.1 (CI target) x86,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 2.4.0 x86,x86-64

Old Versions

You can download old distributions from PyPI. Only the latest major releases for Python 2.x and 3.x are visible, but all releases are available by direct URL access e.g. https://pypi.python.org/pypi/Pillow/1.0.

Handbook

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

    return image

Note that when pasting it back from the crop() operation, load() is called first. This is because cropping is a lazy operation. If load() was not called, then the crop operation would not be performed until the images were used in the paste commands. This would mean that part1 would be cropped from the version of image already modified by the first paste.

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. For example, pasting an RGBA image and also using it as the mask would paste the opaque portion of the image but not its transparent background.

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)

transpose(ROTATE) operations can also be performed identically with rotate() operations, provided the expand flag is true, to provide for the same changes to the image’s size.

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

Using the ImageSequence Iterator class
from PIL import ImageSequence
for frame in ImageSequence.Iterator(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 title
ps.setfont("HelveticaNarrow-Bold", 36)
ps.text((3*72, 4*72), 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

This is only available for JPEG and MPO files.

from PIL import Image
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. For example, a PNG image might have ‘R’, ‘G’, ‘B’, and ‘A’ bands for the red, green, blue, and alpha transparency values. Many operations act on each band separately, e.g., histograms. It is often useful to think of each pixel as having one value per band.

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

Modes

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)
    • Note that this refers to the JPEG, and not the ITU-R BT.2020, standard
  • LAB (3x8-bit pixels, the L*a*b color space)
  • HSV (3x8-bit pixels, Hue, Saturation, Value color space)
  • 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 one nearest pixel from the input image. Ignore all other input pixels.
BOX

Each pixel of source image contributes to one pixel of the destination image with identical weights. For upscaling is equivalent of NEAREST. This filter can only be used with the resize() and thumbnail() methods.

New in version 3.4.0.

BILINEAR
For resize calculate the output pixel value using linear interpolation on all pixels that may contribute to the output value. For other transformations linear interpolation over a 2x2 environment in the input image is used.
HAMMING

Produces more sharp image than BILINEAR, doesn’t have dislocations on local level like with BOX. This filter can only be used with the resize() and thumbnail() methods.

New in version 3.4.0.

BICUBIC
For resize calculate the output pixel value using cubic interpolation on all pixels that may contribute to the output value. For other transformations cubic interpolation over a 4x4 environment in the input image is used.
LANCZOS

Calculate the output pixel value using a high-quality Lanczos filter (a truncated sinc) on all pixels that may contribute to the output value. This filter can only be used with the resize() and thumbnail() methods.

New in version 1.1.3.

Filters comparison table
Filter Downscaling quality Upscaling quality Performance
NEAREST     ⭐⭐⭐⭐⭐
BOX   ⭐⭐⭐⭐
BILINEAR ⭐⭐⭐
HAMMING ⭐⭐   ⭐⭐⭐
BICUBIC ⭐⭐⭐ ⭐⭐⭐ ⭐⭐
LANCZOS ⭐⭐⭐⭐ ⭐⭐⭐⭐

Appendices

Note

Contributors please include appendices as needed or appropriate with your bug fixes, feature additions and tests.

Image file formats

The Python Imaging Library supports a wide variety of raster file formats. Over 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. The EPS driver can read EPS images in L, LAB, RGB and CMYK mode, but Ghostscript may convert the images to RGB mode rather than leaving them in the original color space. The EPS driver can write images in L, RGB and CMYK modes.

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 files in GIF87a by default, unless GIF89a features are used or GIF89a is already in use.

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).
transparency
Transparency color index. This key is omitted if the image is not transparent.
version
Version (either GIF87a or GIF89a).
duration
May not be present. The time to display the current frame of the GIF, in milliseconds.
loop
May not be present. The number of times the GIF should loop.
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.

im.seek() raises an EOFError if you try to seek after the last frame.

Saving

When calling save(), the following options are available:

im.save(out, save_all=True, append_images=[im1, im2, ...])
save_all
If present and true, all frames of the image will be saved. If not, then only the first frame of a multiframe image will be saved.
append_images
A list of images to append as additional frames. Each of the images in the list can be single or multiframe images.
duration
The display duration of each frame of the multiframe gif, in milliseconds. Pass a single integer for a constant duration, or a list or tuple to set the duration for each frame separately.
loop
Integer number of times the GIF should loop.
optimize
If present and true, attempt to compress the palette by eliminating unused colors. This is only useful if the palette can be compressed to the next smaller power of 2 elements.
palette
Use the specified palette for the saved image.
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)]
ICNS

PIL reads and (macOS only) writes macOS .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)).
ICO

ICO is used to store icons on Windows. The largest available icon is read.

The save() method supports the following options:

sizes
A list of sizes including in this ico file; these are a 2-tuple, (width, height); Default to [(16, 16), (24, 24), (32, 32), (48, 48), (64, 64), (128, 128), (255, 255)]. Any sizes bigger than the original size or 255 will be ignored.
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 open() method may set the following info properties if available:

jfif
JFIF application marker found. If the file is not a JFIF file, this key is not present.
jfif_version
A tuple representing the jfif version, (major version, minor version).
jfif_density
A tuple representing the pixel density of the image, in units specified by jfif_unit.
jfif_unit

Units for the jfif_density:

  • 0 - No Units
  • 1 - Pixels per Inch
  • 2 - Pixels per Centimeter
dpi
A tuple representing the reported pixel density in pixels per inch, if the file is a jfif file and the units are in inches.
adobe
Adobe application marker found. If the file is not an Adobe JPEG file, this key is not present.
adobe_transform
Vendor Specific Tag.
progression
Indicates that this is a progressive JPEG file.
icc_profile
The ICC color profile for the image.
exif
Raw EXIF data from the image.

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 and true, indicates that the encoder should make an extra pass over the image in order to select optimal encoder settings.
progressive
If present and true, indicates that this image should be stored as a progressive JPEG file.
dpi
A tuple of integers representing the pixel density, (x,y).
icc_profile

If present and true, the image is stored with the provided ICC profile. If this parameter is not provided, the image will be saved with no profile attached. To preserve the existing profile:

im.save(filename, 'jpeg', icc_profile=im.info.get('icc_profile'))
exif
If present, the image will be stored with the provided raw EXIF data.
subsampling

If present, sets the subsampling for the encoder.

  • keep: Only valid for JPEG files, will retain the original image setting.
  • 4:4:4, 4:2:2, 4:1:1: Specific sampling values
  • -1: equivalent to keep
  • 0: equivalent to 4:4:4
  • 1: equivalent to 4:2:2
  • 2: equivalent to 4:1:1
qtables

If present, sets the qtables for the encoder. This is listed as an advanced option for wizards in the JPEG documentation. Use with caution. qtables can be one of several types of values:

  • a string, naming a preset, e.g. keep, web_low, or web_high
  • a list, tuple, or dictionary (with integer keys = range(len(keys))) of lists of 64 integers. There must be between 2 and 4 tables.

New in version 2.5.0.

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

For P images: Either the palette index for full transparent pixels, or a byte string with alpha values for each palette entry.

For L and RGB images, the color that represents full transparent pixels in this image.

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

Open also sets Image.text to a list of the values of the tEXt, zTXt, and iTXt chunks of the PNG image. Individual compressed chunks are limited to a decompressed size of PngImagePlugin.MAX_TEXT_CHUNK, by default 1MB, to prevent decompression bombs. Additionally, the total size of all of the text chunks is limited to PngImagePlugin.MAX_TEXT_MEMORY, defaulting to 64MB.

The save() method supports the following options:

optimize
If present and true, 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.

For P images, this can be a either the palette index, or a byte string with alpha values for each palette entry.

dpi
A tuple of two numbers corresponding to the desired dpi in each direction.
pnginfo
A PIL.PngImagePlugin.PngInfo instance containing text tags.
compress_level
ZLIB compression level, a number between 0 and 9: 1 gives best speed, 9 gives best compression, 0 gives no compression at all. Default is 6. When optimize option is True compress_level has no effect (it is set to 9 regardless of a value passed).
icc_profile
The ICC Profile to include in the saved file.
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 installation documentation for details.

PPM

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

SGI

Pillow reads and writes uncompressed L, RGB, and RGBA files.

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 homepage 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.

New in version 2.0.0.

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.

resolution

Image resolution as an (xres, yres) tuple, where applicable. This is a measurement in whichever unit is specified by the file.

New in version 1.1.5.

The tag_v2 attribute contains a dictionary of TIFF metadata. The keys are numerical indexes from TAGS_V2. Values are strings or numbers for single items, multiple values are returned in a tuple of values. Rational numbers are returned as a IFDRational object.

New in version 3.0.0.

For compatibility with legacy code, the tag attribute contains a dictionary of decoded TIFF fields as returned prior to version 3.0.0. Values are returned as either strings or tuples of numeric values. Rational numbers are returned as a tuple of (numerator, denominator).

Deprecated since version 3.0.0.

Saving Tiff Images

The save() method can take the following keyword arguments:

save_all

If true, Pillow will save all frames of the image to a multiframe tiff document.

New in version 3.4.0.

tiffinfo

A ImageFileDirectory_v2 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_v2 object and setting the type in tagtype with the appropriate numerical value from TiffTags.TYPES.

New in version 2.3.0.

Metadata values that are of the rational type should be passed in using a IFDRational object.

New in version 3.1.0.

For compatibility with legacy code, a ImageFileDirectory_v1 object may be passed in this field. However, this is deprecated.

New in version 3.0.0.

Note

Only some tags are currently supported when writing using libtiff. The supported list is found in LIBTIFF_CORE.

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, 2 tuple of (numerator, denominator) or a IFDRational. 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 and true, 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).

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.

DDS

DDS is a popular container texture format used in video games and natively supported by DirectX. Currently, DXT1, DXT3, and DXT5 pixel formats are supported and only in RGBA mode.

New in version 3.4.0: DXT3

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.

FTEX

New in version 3.2.0.

The FTEX decoder reads textures used for 3D objects in Independence War 2: Edge Of Chaos. The plugin reads a single texture per file, in the compressed and uncompressed formats.

GBR

The GBR decoder reads GIMP brush files, version 1 and 2.

The open() method sets the following info properties:

comment
The brush name.
spacing
The spacing between the brushes, in pixels. Version 2 only.
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.
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

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.

MPO

Pillow identifies and reads Multi Picture Object (MPO) files, loading the primary image when first opened. The seek() and tell() methods may be used to read other pictures from the file. The pictures are zero-indexed and random access is supported.

PCD

PIL reads PhotoCD files containing RGB data. This only reads the 768x512 resolution image from the file. Higher resolutions are encoded in a proprietary encoding.

PIXAR

PIL provides limited support for PIXAR raster files. The library can identify and read “dumped” RGB files.

The format code is PIXAR.

PSD

PIL identifies and reads PSD files written by Adobe Photoshop 2.5 and 3.0.

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).

When calling save(), if a multiframe image is used, by default, only the first image will be saved. To save all frames, each frame to a separate page of the PDF, the save_all parameter must be present and set to True.

XV Thumbnails

PIL can read XV thumbnail files.

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 playable 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 Image Plugin

The Pillow 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 image plugin manually.

Pillow decodes files in 2 stages:

  1. It loops over the available image plugins in the loaded order, and calls the plugin’s accept function with the first 16 bytes of the file. If the accept function returns true, the plugin’s _open method is called to set up the image metadata and image tiles. The _open method is not for decoding the actual image data.
  2. When the image data is requested, the ImageFile.load method is called, which sets up a decoder for each tile and feeds the data to it.

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.

The raw decoder is useful for uncompressed image formats, but many formats require more control of the decoding context, either with a decoder written in C or by linking in an external library to do the decoding. (Examples of this include PNG, Tiff, and Jpeg support)

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(SpamImageFile.format, SpamImageFile)

Image.register_extension(SpamImageFile.format, ".spam")
Image.register_extension(SpamImageFile.format, ".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, IndexError, EOFError and struct.error 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.frombytes() function, use the following syntax:

image = Image.frombytes(
    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 frombytes function, use the following syntax:

image = frombytes(
    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.

Writing Your Own File Decoder

There are 3 stages in a file decoder’s lifetime:

  1. Setup: Pillow looks for a function named [decodername]_decoder on the internal core image object. That function is called with the args tuple from the tile setup in the _open method.
  2. Decoding: The decoder’s decode function is repeatedly called with chunks of image data.
  3. Cleanup: If the decoder has registered a cleanup function, it will be called at the end of the decoding process, even if there was an exception raised.
Setup

The current conventions are that the decoder setup function is named PyImaging_[Decodername]DecoderNew and defined in decode.c. The python binding for it is named [decodername]_decoder and is setup from within the _imaging.c file in the codecs section of the function array.

The setup function needs to call PyImaging_DecoderNew and at the very least, set the decode function pointer. The fields of interest in this object are:

decode
Function pointer to the decode function, which has access to im, state, and the buffer of data to be added to the image.
cleanup
Function pointer to the cleanup function, has access to state.
im
The target image, will be set by Pillow.
state
An ImagingCodecStateInstance, will be set by Pillow. The context member is an opaque struct that can be used by the decoder to store any format specific state or options.
handles_eof
UNDONE, set if your code handles EOF errors.
pulls_fd

EXPERIMENTALWARNING, interface may change. If set to 1, state->fd will be a pointer to the Python file like object. The decoder may use the functions in codec_fd.c to read directly from the file like object rather than have the data pushed through a buffer. Note that this implementation may be refactored until this warning is removed.

New in version 3.3.0.

Decoding

The decode function is called with the target (core) image, the decoder state structure, and a buffer of data to be decoded.

Experimental – If pulls_fd is set, then the decode function is called once, with an empty buffer. It is the decoder’s responsibility to decode the entire tile in that one call. The rest of this section only applies if pulls_fd is not set.

It is the decoder’s responsibility to pull as much data as possible out of the buffer and return the number of bytes consumed. The next call to the decoder will include the previous unconsumed tail. The decoder function will be called multiple times as the data is read from the file like object.

If an error occurs, set state->errcode and return -1.

Return -1 on success, without setting the errcode.

Cleanup

The cleanup function is called after the decoder returns a negative value, or if there is a read error from the file. This function should free any allocated memory and release any resources from external libraries.

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)
    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:
  • fp – A filename (string), pathlib.Path object 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.

Warning

To protect against potential DOS attacks caused by “decompression bombs” (i.e. malicious files which decompress into a huge amount of data and are designed to crash or cause disruption by using up a lot of memory), Pillow will issue a DecompressionBombWarning if the image is over a certain limit. If desired, the warning can be turned into an error with warnings.simplefilter('error', Image.DecompressionBombWarning) or suppressed entirely with warnings.simplefilter('ignore', Image.DecompressionBombWarning). See also the logging documentation to have warnings output to the logging facility instead of stderr.

Image processing
PIL.Image.alpha_composite(im1, im2)

Alpha composite im2 over im1.

Parameters:
  • im1 – The first image. Must have mode RGBA.
  • im2 – The second image. Must have mode RGBA, and the same 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 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. See: Modes.
  • 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. See: Modes.
  • 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) See: Modes.
Returns:

An image object.

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. See: Modes.
  • 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)
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 frombytes(). 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. See: Modes.
  • 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.

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. See: Modes.
  • matrix – An optional conversion matrix. If given, this should be 4- or 12-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.

Note: Prior to Pillow 3.4.0, this was a lazy operation.

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

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.getpalette()

Returns the image palette as a list.

Returns:A list of color values [r, g, b, ...], or None if the image has no palette.
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)
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 will mix the two images together, including their alpha channels if they have them.

See alpha_composite() if you want to combine images with respect to their alpha channels.

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:

Parameters:
  • xy – The pixel coordinate, given as (x, y).
  • value – The pixel value.
Image.quantize(colors=256, method=None, kmeans=0, palette=None)

Convert the image to ‘P’ mode with the specified number of colors.

Parameters:
  • colors – The desired number of colors, <= 256
  • method – 0 = median cut 1 = maximum coverage 2 = fast octree 3 = libimagequant
  • kmeans – Integer
  • palette – Quantize to the PIL.ImagingPalette palette.
Returns:

A new image

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, PIL.Image.BOX, PIL.Image.BILINEAR, PIL.Image.HAMMING, PIL.Image.BICUBIC or PIL.Image.LANCZOS. If omitted, or if the image has mode “1” or “P”, it is set PIL.Image.NEAREST. See: Filters.
Returns:

An Image object.

Image.rotate(angle, resample=0, expand=0, center=None, translate=None)

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.
  • 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), 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. See Filters.
  • 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. Note that the expand flag assumes rotation around the center and no translation.
  • center – Optional center of rotation (a 2-tuple). Origin is the upper left corner. Default is the center of the image.
  • translate – An optional post-rotate translation (a 2-tuple).
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 in the image format documentation for each writer.

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:
  • fp – A filename (string), pathlib.Path object 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 either the xv utility or the display utility, depending on which one can be found.

On macOS, this method saves the image to a temporary BMP file, and opens it with the native Preview application.

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=3)

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 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.LANCZOS. If omitted, it defaults to PIL.Image.BICUBIC. (was PIL.Image.NEAREST prior to version 2.5.0)
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.tobytes(encoder_name='raw', *args)

Return image as a bytes object.

Warning

This method returns the raw image data from the internal storage. For compressed image data (e.g. PNG, JPEG) use save(), with a BytesIO parameter for in-memory data.

Parameters:
  • encoder_name – What encoder to use. The default is to use the standard “raw” encoder.
  • args – Extra arguments to the encoder.
Return type:

A bytes object.

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, PIL.Image.ROTATE_270 or PIL.Image.TRANSPOSE.
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)
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.
Return type:PixelAccess Class or PIL.PyAccess
Image.close()

Closes the file pointer, if possible.

This operation will destroy the image core and release its 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 Modes 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.width

Image width, in pixels.

Type:int
PIL.Image.height

Image height, in pixels.

Type:int
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.

Unless noted elsewhere, this dictionary does not affect saving files.

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])

ImageCms Module

The ImageCms module provides color profile management support using the LittleCMS2 color management engine, based on Kevin Cazabon’s PyCMS library.

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

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

Will return the output profile in the output.info[‘icc_profile’].

exception PIL.ImageCms.PyCMSError

(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 calculation 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. The profile will be returned in the image’s info[‘icc_profile’].

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 optimized) 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 specifying 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.

CmsProfile

The ICC color profiles are wrapped in an instance of the class CmsProfile. The specification ICC.1:2010 contains more information about the meaning of the values in ICC profiles.

For convenience, all XYZ-values are also given as xyY-values (so they can be easily displayed in a chromaticity diagram, for example).

class PIL.ImageCms.CmsProfile
creation_date

Date and time this profile was first created (see 7.2.1 of ICC.1:2010).

Type:datetime.datetime or None
version

The version number of the ICC standard that this profile follows (e.g. 2.0).

Type:float
icc_version

Same as version, but in encoded format (see 7.2.4 of ICC.1:2010).

device_class

4-character string identifying the profile class. One of scnr, mntr, prtr, link, spac, abst, nmcl (see 7.2.5 of ICC.1:2010 for details).

Type:string
xcolor_space

4-character string (padded with whitespace) identifying the color space, e.g. XYZ␣, RGB␣ or CMYK (see 7.2.6 of ICC.1:2010 for details).

Note that the deprecated attribute color_space contains an interpreted (non-padded) variant of this (but can be empty on unknown input).

Type:string
connection_space

4-character string (padded with whitespace) identifying the color space on the B-side of the transform (see 7.2.7 of ICC.1:2010 for details).

Note that the deprecated attribute pcs contains an interpreted (non-padded) variant of this (but can be empty on unknown input).

Type:string
header_flags

The encoded header flags of the profile (see 7.2.11 of ICC.1:2010 for details).

Type:int
header_manufacturer

4-character string (padded with whitespace) identifying the device manufacturer, which shall match the signature contained in the appropriate section of the ICC signature registry found at www.color.org (see 7.2.12 of ICC.1:2010).

Type:string
header_model

4-character string (padded with whitespace) identifying the device model, which shall match the signature contained in the appropriate section of the ICC signature registry found at www.color.org (see 7.2.13 of ICC.1:2010).

Type:string
attributes

Flags used to identify attributes unique to the particular device setup for which the profile is applicable (see 7.2.14 of ICC.1:2010 for details).

Type:int
rendering_intent

The rendering intent to use when combining this profile with another profile (usually overridden at run-time, but provided here for DeviceLink and embedded source profiles, see 7.2.15 of ICC.1:2010).

One of ImageCms.INTENT_ABSOLUTE_COLORIMETRIC, ImageCms.INTENT_PERCEPTUAL, ImageCms.INTENT_RELATIVE_COLORIMETRIC and ImageCms.INTENT_SATURATION.

Type:int
profile_id

A sequence of 16 bytes identifying the profile (via a specially constructed MD5 sum), or 16 binary zeroes if the profile ID has not been calculated (see 7.2.18 of ICC.1:2010).

Type:bytes
copyright

The text copyright information for the profile (see 9.2.21 of ICC.1:2010).

Type:unicode or None
manufacturer

The (english) display string for the device manufacturer (see 9.2.22 of ICC.1:2010).

Type:unicode or None
model

The (english) display string for the device model of the device for which this profile is created (see 9.2.23 of ICC.1:2010).

Type:unicode or None
profile_description

The (english) display string for the profile description (see 9.2.41 of ICC.1:2010).

Type:unicode or None
target

The name of the registered characterization data set, or the measurement data for a characterization target (see 9.2.14 of ICC.1:2010).

Type:unicode or None
red_colorant

The first column in the matrix used in matrix/TRC transforms (see 9.2.44 of ICC.1:2010).

Type:((X, Y, Z), (x, y, Y)) or None
green_colorant

The second column in the matrix used in matrix/TRC transforms (see 9.2.30 of ICC.1:2010).

Type:((X, Y, Z), (x, y, Y)) or None
blue_colorant

The third column in the matrix used in matrix/TRC transforms (see 9.2.4 of ICC.1:2010).

Type:((X, Y, Z), (x, y, Y)) or None
luminance

The absolute luminance of emissive devices in candelas per square metre as described by the Y channel (see 9.2.32 of ICC.1:2010).

Type:((X, Y, Z), (x, y, Y)) or None
chromaticity

The data of the phosphor/colorant chromaticity set used (red, green and blue channels, see 9.2.16 of ICC.1:2010).

Type:((x, y, Y), (x, y, Y), (x, y, Y)) or None
chromatic_adaption

The chromatic adaption matrix converts a color measured using the actual illumination conditions and relative to the actual adopted white, to an color relative to the PCS adopted white, with complete adaptation from the actual adopted white chromaticity to the PCS adopted white chromaticity (see 9.2.15 of ICC.1:2010).

Two matrices are returned, one in (X, Y, Z) space and one in (x, y, Y) space.

Type:2-tuple of 3-tuple, the first with (X, Y, Z) and the second with (x, y, Y) values
colorant_table

This tag identifies the colorants used in the profile by a unique name and set of PCSXYZ or PCSLAB values (see 9.2.19 of ICC.1:2010).

Type:list of strings
colorant_table_out

This tag identifies the colorants used in the profile by a unique name and set of PCSLAB values (for DeviceLink profiles only, see 9.2.19 of ICC.1:2010).

Type:list of strings
colorimetric_intent

4-character string (padded with whitespace) identifying the image state of PCS colorimetry produced using the colorimetric intent transforms (see 9.2.20 of ICC.1:2010 for details).

Type:string or None
perceptual_rendering_intent_gamut

4-character string (padded with whitespace) identifying the (one) standard reference medium gamut (see 9.2.37 of ICC.1:2010 for details).

Type:string or None
saturation_rendering_intent_gamut

4-character string (padded with whitespace) identifying the (one) standard reference medium gamut (see 9.2.37 of ICC.1:2010 for details).

Type:string or None
technology

4-character string (padded with whitespace) identifying the device technology (see 9.2.47 of ICC.1:2010 for details).

Type:string or None
media_black_point

This tag specifies the media black point and is used for generating absolute colorimetry.

This tag was available in ICC 3.2, but it is removed from version 4.

Type:((X, Y, Z), (x, y, Y)) or None
media_white_point_temperature

Calculates the white point temperature (see the LCMS documentation for more information).

Type:float or None
viewing_condition

The (english) display string for the viewing conditions (see 9.2.48 of ICC.1:2010).

Type:unicode or None
screening_description

The (english) display string for the screening conditions.

This tag was available in ICC 3.2, but it is removed from version 4.

Type:unicode or None
red_primary

The XYZ-transformed of the RGB primary color red (1, 0, 0).

Type:((X, Y, Z), (x, y, Y)) or None
green_primary

The XYZ-transformed of the RGB primary color green (0, 1, 0).

Type:((X, Y, Z), (x, y, Y)) or None
blue_primary

The XYZ-transformed of the RGB primary color blue (0, 0, 1).

Type:((X, Y, Z), (x, y, Y)) or None
is_matrix_shaper

True if this profile is implemented as a matrix shaper (see documentation on LCMS).

Type:bool
clut

Returns a dictionary of all supported intents and directions for the CLUT model.

The dictionary is indexed by intents (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC, ImageCms.INTENT_PERCEPTUAL, ImageCms.INTENT_RELATIVE_COLORIMETRIC and ImageCms.INTENT_SATURATION).

The values are 3-tuples indexed by directions (ImageCms.DIRECTION_INPUT, ImageCms.DIRECTION_OUTPUT, ImageCms.DIRECTION_PROOF).

The elements of the tuple are booleans. If the value is True, that intent is supported for that direction.

Type:dict of boolean 3-tuples
intent_supported

Returns a dictionary of all supported intents and directions.

The dictionary is indexed by intents (ImageCms.INTENT_ABSOLUTE_COLORIMETRIC, ImageCms.INTENT_PERCEPTUAL, ImageCms.INTENT_RELATIVE_COLORIMETRIC and ImageCms.INTENT_SATURATION).

The values are 3-tuples indexed by directions (ImageCms.DIRECTION_INPUT, ImageCms.DIRECTION_OUTPUT, ImageCms.DIRECTION_PROOF).

The elements of the tuple are booleans. If the value is True, that intent is supported for that direction.

Type:dict of boolean 3-tuples
color_space

Deprecated but retained for backwards compatibility. Interpreted value of xcolor_space. May be the empty string if value could not be decoded.

Type:string
pcs

Deprecated but retained for backwards compatibility. Interpreted value of connection_space. May be the empty string if value could not be decoded.

Type:string
product_model

Deprecated but retained for backwards compatibility. ASCII-encoded value of model.

Type:string
product_manufacturer

Deprecated but retained for backwards compatibility. ASCII-encoded value of manufacturer.

Type:string

Deprecated but retained for backwards compatibility. ASCII-encoded value of copyright.

Type:string
product_description

Deprecated but retained for backwards compatibility. ASCII-encoded value of profile_description.

Type:string
product_desc

Deprecated but retained for backwards compatibility. ASCII-encoded value of profile_description.

This alias of product_description used to contain a derived informative string about the profile, depending on the value of the description, copyright, manufacturer and model fields).

Type:string

There is one function defined on the class:

is_intent_supported(intent, direction)

Returns if the intent is supported for the given direction.

Note that you can also get this information for all intents and directions with intent_supported.

Parameters:
  • intent – One of ImageCms.INTENT_ABSOLUTE_COLORIMETRIC, ImageCms.INTENT_PERCEPTUAL, ImageCms.INTENT_RELATIVE_COLORIMETRIC and ImageCms.INTENT_SATURATION.
  • direction – One of ImageCms.DIRECTION_INPUT, ImageCms.DIRECTION_OUTPUT and ImageCms.DIRECTION_PROOF
Returns:

Boolean if the intent and direction is supported.

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.

Example: Draw Partial Opacity Text

from PIL import Image, ImageDraw, ImageFont
# get an image
base = Image.open('Pillow/Tests/images/lena.png').convert('RGBA')

# make a blank image for the text, initialized to transparent text color
txt = Image.new('RGBA', base.size, (255,255,255,0))

# get a font
fnt = ImageFont.truetype('Pillow/Tests/fonts/FreeMono.ttf', 40)
# get a drawing context
d = ImageDraw.Draw(txt)

# draw text, half opacity
d.text((10,10), "Hello", font=fnt, fill=(255,255,255,128))
# draw text, full opacity
d.text((10,60), "World", font=fnt, fill=(255,255,255,255))

out = Image.alpha_composite(base, txt)

out.show()

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.

Parameters:
  • im – The image to draw in.
  • mode – Optional mode to use for color values. For RGB images, this argument can be RGB or RGBA (to blend the drawing into the image). For all other modes, this argument must be the same as the image mode. If omitted, the mode defaults to the mode of the image.

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 [(x0, y0), (x1, y1)] or [x0, y0, x1, y1].
  • start – Starting angle, in degrees. Angles are measured from 3 o’clock, increasing clockwise.
  • end – Ending angle, in degrees.
  • fill – Color to use for the arc.
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 [(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 [(x0, y0), (x1, y1)] or [x0, y0, x1, y1].
  • start – Starting angle, in degrees. Angles are measured from 3 o’clock, increasing clockwise.
  • end – Ending angle, in degrees.
  • fill – Color to use for the fill.
  • outline – Color to use for the outline.
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, spacing=0, align="left")

Draws the string at the given position.

Parameters:
  • xy – Top left corner of the text.
  • text – Text to be drawn. If it contains any newline characters, the text is passed on to multiline_text()
  • fill – Color to use for the text.
  • font – An ImageFont instance.
  • spacing – If the text is passed on to multiline_text(), the number of pixels between lines.
  • align – If the text is passed on to multiline_text(), “left”, “center” or “right”.
PIL.ImageDraw.Draw.multiline_text(xy, text, fill=None, font=None, anchor=None, spacing=0, align="left")

Draws the string at the given position.

Parameters:
  • xy – Top left corner of the text.
  • text – Text to be drawn.
  • fill – Color to use for the text.
  • font – An ImageFont instance.
  • spacing – The number of pixels between lines.
  • align – “left”, “center” or “right”.
PIL.ImageDraw.Draw.textsize(text, font=None, spacing=0)

Return the size of the given string, in pixels.

Parameters:
  • text – Text to be measured. If it contains any newline characters, the text is passed on to multiline_textsize()
  • font – An ImageFont instance.
  • spacing – If the text is passed on to multiline_textsize(), the number of pixels between lines.
PIL.ImageDraw.Draw.multiline_textsize(text, font=None, spacing=0)

Return the size of the given string, in pixels.

Parameters:
  • text – Text to be measured.
  • font – An ImageFont instance.
  • spacing – The number of pixels between lines.

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.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 brightness 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.

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.

Parameters:
  • radius – Blur Radius
  • percent – Unsharp strength, in percent
  • threshold – Threshold controls the minimum brightness change that will be sharpened
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='')

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:
  • font – 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 (macOS and 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 macOS and 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 on Windows or “RGBA” on macOS. If the bounding box is omitted, the entire screen is copied.

New in version 1.1.3: (Windows), 3.0.0 (macOS)

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: (Windows), 3.3.0 (macOS)

Returns:On Windows, 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.

On Mac, an image, or None if the clipboard does not contain image data.

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

from PIL 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.

ImageMorph Module

The ImageMorph module provides morphology operations on images.

class PIL.ImageMorph.LutBuilder(patterns=None, op_name=None)

Bases: object

A class for building a MorphLut from a descriptive language

The input patterns is a list of a strings sequences like these:

4:(...
   .1.
   111)->1

(whitespaces including linebreaks are ignored). The option 4 describes a series of symmetry operations (in this case a 4-rotation), the pattern is described by:

  • . or X - Ignore
  • 1 - Pixel is on
  • 0 - Pixel is off

The result of the operation is described after “->” string.

The default is to return the current pixel value, which is returned if no other match is found.

Operations:

  • 4 - 4 way rotation
  • N - Negate
  • 1 - Dummy op for no other operation (an op must always be given)
  • M - Mirroring

Example:

lb = LutBuilder(patterns = ["4:(... .1. 111)->1"])
lut = lb.build_lut()
add_patterns(patterns)
build_default_lut()
build_lut()

Compile all patterns into a morphology lut.

TBD :Build based on (file) morphlut:modify_lut

get_lut()
class PIL.ImageMorph.MorphOp(lut=None, op_name=None, patterns=None)

Bases: object

A class for binary morphological operators

apply(image)

Run a single morphological operation on an image

Returns a tuple of the number of changed pixels and the morphed image

get_on_pixels(image)

Get a list of all turned on pixels in a binary image

Returns a list of tuples of (x,y) coordinates of all matching pixels.

load_lut(filename)

Load an operator from an mrl file

match(image)

Get a list of coordinates matching the morphological operation on an image.

Returns a list of tuples of (x,y) coordinates of all matching pixels.

save_lut(filename)

Save an operator to an mrl file

set_lut(lut)

Set the lut from an external source

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 – An optional resampling filter. Same values possible as in the PIL.Image.transform function.
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 solarize.
  • 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

Parameters:
  • mode – The mode to use for the Palette. See: Modes. Defaults to “RGB”
  • palette – An optional palette. If given, it must be a bytearray, an array or a list of ints between 0-255 and of length size times the number of colors in mode. The list must be aligned by channel (All R values must be contiguous in the list before G and B values.) Defaults to 0 through 255 per channel.
  • size – An optional palette size. If given, it cannot be equal to or greater than 256. Defaults to 0.
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 += 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 for each band in the image.

sum

Sum of all pixels for each band in the image.

sum2

Squared sum of all pixels for each band in the image.

mean

Average (arithmetic mean) pixel level for each band in the image.

median

Median pixel level for each band in the image.

rms

RMS (root-mean-square) for each band in the image.

var

Variance for each band in the image.

stddev

Standard deviation for each band in the image.

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

class PIL.ImageWin.HWND(wnd)

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

ExifTags Module

The ExifTags module exposes two dictionaries which provide constants and clear-text names for various well-known EXIF tags.

class PIL.ExifTags.TAGS

The TAG dictionary maps 16-bit integer EXIF tag enumerations to descriptive string names. For instance:

>>> from PIL.ExifTags import TAGS
>>> TAGS[0x010e]
'ImageDescription'
class PIL.ExifTags.GPSTAGS

The GPSTAGS dictionary maps 8-bit integer EXIF gps enumerations to descriptive string names. For instance:

>>> from PIL.ExifTags import GPSTAGS
>>> GPSTAGS[20]
'GPSDestLatitude'

TiffTags Module

The TiffTags module exposes many of the standard TIFF metadata tag numbers, names, and type information.

PIL.TiffTags.lookup(tag)
Parameters:tag – Integer tag number
Returns:Taginfo namedtuple, From the TAGS_V2 info if possible, otherwise just populating the value and name from TAGS. If the tag is not recognized, “unknown” is returned for the name

New in version 3.1.0.

class PIL.TiffTags.TagInfo
__init__(self, value=None, name="unknown", type=None, length=0, enum=None)
Parameters:
  • value – Integer Tag Number
  • name – Tag Name
  • type – Integer type from PIL.TiffTags.TYPES
  • length – Array length: 0 == variable, 1 == single value, n = fixed
  • enum – Dict of name:integer value options for an enumeration
cvt_enum(self, value)
Parameters:value – The enumerated value name
Returns:The integer corresponding to the name.

New in version 3.0.0.

PIL.TiffTags.TAGS_V2

The TAGS_V2 dictionary maps 16-bit integer tag numbers to PIL.TagTypes.TagInfo tuples for metadata fields defined in the TIFF spec.

New in version 3.0.0.

PIL.TiffTags.TAGS

The TAGS dictionary maps 16-bit integer TIFF tag number to descriptive string names. For instance:

>>> from PIL.TiffTags import TAGS
>>> TAGS[0x010e]
'ImageDescription'

This dictionary contains a superset of the tags in TAGS_V2, common EXIF tags, and other well known metadata tags.

PIL.TiffTags.TYPES

The TYPES dictionary maps the TIFF type short integer to a human readable type name.

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.
text(xy, text)

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

PixelAccess Class

The PixelAccess class provides read and write access to PIL.Image data at a pixel level.

Note

Accessing individual pixels is fairly slow. If you are looping over all of the pixels in an image, there is likely a faster way using other parts of the Pillow API.

Example

The following script loads an image, accesses one pixel from it, then changes it.

from PIL import Image
im = Image.open('hopper.jpg')
px = im.load()
print (px[4,4])
px[4,4] = (0,0,0)
print (px[4,4])

Results in the following:

(23, 24, 68)
(0, 0, 0)

PixelAccess Class

class PixelAccess
__setitem__(self, xy, color):

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

Parameters:
  • xy – The pixel coordinate, given as (x, y).
  • value – The pixel value.
__getitem__(self, xy):
Returns the pixel at x,y. The pixel is returned as a single

value for single band images or a tuple for multiple band images

param xy:The pixel coordinate, given as (x, y).
returns:a pixel value for single band images, a tuple of pixel values for multiband images.
putpixel(self, xy, color):

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

Parameters:
  • xy – The pixel coordinate, given as (x, y).
  • value – The pixel value.
getpixel(self, xy):
Returns the pixel at x,y. The pixel is returned as a single

value for single band images or a tuple for multiple band images

param xy:The pixel coordinate, given as (x, y).
returns:a pixel value for single band images, a tuple of pixel values for multiband images.

PyAccess Module

The PyAccess module provides a CFFI/Python implementation of the PixelAccess Class. This implementation is far faster on PyPy than the PixelAccess version.

Note

Accessing individual pixels is fairly slow. If you are looping over all of the pixels in an image, there is likely a faster way using other parts of the Pillow API.

Example

The following script loads an image, accesses one pixel from it, then changes it.

from PIL import Image
im = Image.open('hopper.jpg')
px = im.load()
print (px[4,4])
px[4,4] = (0,0,0)
print (px[4,4])

Results in the following:

(23, 24, 68)
(0, 0, 0)

PyAccess Class

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)

Bases: object

isatty()
read(n=0)

Read data.

@def read(bytes=0) :param bytes: Number of bytes to read. If omitted or zero,

read until end of region.
Returns:An 8-bit string.
readline()

Read a line of text.

Returns:An 8-bit string.
readlines()

Read multiple lines of text.

Returns:A list of 8-bit strings.
seek(offset, mode=0)

Move file pointer.

Parameters:
  • offset – Offset in bytes.
  • mode – Starting position. Use 0 for beginning of region, 1 for current offset, and 2 for end of region. You cannot move the pointer outside the defined region.
tell()

Get current file pointer.

Returns:Offset from start of region, in bytes.

FontFile Module

class PIL.FontFile.FontFile

Bases: object

bitmap = None
compile()

Create metrics and bitmap

save(filename)

Save font

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')

Load texture from a GD image file.

Parameters:
  • filename – GD file name, or an opened file handle.
  • mode – Optional mode. In this version, if the mode argument is given, it must be “r”.
Returns:

An image instance.

Raises:

IOError – If the image could not be read.

GimpGradientFile Module

class PIL.GimpGradientFile.GimpGradientFile(fp)

Bases: PIL.GimpGradientFile.GradientFile

class PIL.GimpGradientFile.GradientFile

Bases: object

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)

Bases: object

getpalette()
rawmode = 'RGB'

ImageDraw2 Module

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

Bases: object

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

Bases: object

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)

Bases: object

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

Bases: object

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

Bases: object

Base class for viewers.

format = None
get_command(file, **options)
get_format(image)

Return format name, or None to save as PGM/PPM

save_image(image)

Save to temporary file, and return filename

show(image, **options)
show_file(file, **options)

Display given file

show_image(image, **options)

Display given image

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)

Display a given image.

Parameters:
  • image – An image object.
  • title – Optional title. Not all viewers can display the title.
  • **options – Additional viewer options.
Returns:

True if a suitable viewer was found, false otherwise.

PIL.ImageShow.which(executable)

ImageTransform Module

class PIL.ImageTransform.AffineTransform(data)

Bases: PIL.ImageTransform.Transform

Define an affine image transform.

This function takes a 6-tuple (a, b, c, d, e, f) which contain the first two rows from an affine transform matrix. For each pixel (x, y) in the output image, the new value is taken from a position (a x + b y + c, d x + e y + f) in the input image, rounded to nearest pixel.

This function can be used to scale, translate, rotate, and shear the original image.

See transform()

Parameters:matrix – A 6-tuple (a, b, c, d, e, f) containing the first two rows from an affine transform matrix.
method = 0
class PIL.ImageTransform.ExtentTransform(data)

Bases: PIL.ImageTransform.Transform

Define a transform to extract a subregion from an image.

Maps a rectangle (defined by two corners) from the image to a rectangle of the given size. The resulting image will contain data sampled from between the corners, such that (x0, y0) in the input image will end up at (0,0) in the output image, and (x1, y1) at size.

This method can be used to crop, stretch, shrink, or mirror an arbitrary rectangle in the current image. It is slightly slower than crop, but about as fast as a corresponding resize operation.

See transform()

Parameters:bbox – A 4-tuple (x0, y0, x1, y1) which specifies two points in the input image’s coordinate system.
method = 1
class PIL.ImageTransform.MeshTransform(data)

Bases: PIL.ImageTransform.Transform

Define a mesh image transform. A mesh transform consists of one or more individual quad transforms.

See transform()

Parameters:data – A list of (bbox, quad) tuples.
method = 4
class PIL.ImageTransform.QuadTransform(data)

Bases: PIL.ImageTransform.Transform

Define a quad image transform.

Maps a quadrilateral (a region defined by four corners) from the image to a rectangle of the given size.

See transform()

Parameters:xy – An 8-tuple (x0, y0, x1, y1, x2, y2, y3, y3) which contain the upper left, lower left, lower right, and upper right corner of the source quadrilateral.
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.: https://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.: https://en.wikipedia.org/wiki/Quantization_matrix#Quantization_matrices, https://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://web.archive.org/web/20120328125543/http://www.jpegcameras.com/libjpeg/libjpeg-3.html

PaletteFile Module

class PIL.PaletteFile.PaletteFile(fp)

Bases: object

getpalette()
rawmode = 'RGB'

PcfFontFile Module

class PIL.PcfFontFile.PcfFontFile(fp)

Bases: PIL.FontFile.FontFile

name = 'name'
PIL.PcfFontFile.sz(s, o)

PngImagePlugin.iTXt Class

class PIL.PngImagePlugin.iTXt

Bases: str

Subclass of string to allow iTXt chunks to look like strings while keeping their extra information

__new__(cls, text, lang, tkey)
Parameters:
  • value – value for this key
  • lang – language code
  • tkey – UTF-8 version of the key name

PngImagePlugin.PngInfo Class

class PIL.PngImagePlugin.PngInfo

Bases: object

PNG chunk container (for use with save(pnginfo=))

add(cid, data)

Appends an arbitrary chunk. Use with caution.

Parameters:
  • cid – a byte string, 4 bytes long.
  • data – a byte string of the encoded data
add_itxt(key, value, lang='', tkey='', zip=False)

Appends an iTXt chunk.

Parameters:
  • key – latin-1 encodable text key name
  • value – value for this key
  • lang – language code
  • tkey – UTF-8 version of the key name
  • zip – compression flag
add_text(key, value, zip=0)

Appends a text chunk.

Parameters:
  • key – latin-1 encodable text key name
  • value – value for this key, text or an PIL.PngImagePlugin.iTXt instance
  • zip – compression flag

TarIO Module

class PIL.TarIO.TarIO(tarfile, file)

Bases: PIL.ContainerIO.ContainerIO

WalImageFile Module

PIL.WalImageFile.open(filename)

Load texture from a Quake2 WAL texture file.

By default, a Quake2 standard palette is attached to the texture. To override the palette, use the <b>putpalette</b> method.

Parameters:filename – WAL file name, or an opened file handle.
Returns:An image instance.

_binary Module

PIL._binary.i16be(c, o=0)
PIL._binary.i16le(c, o=0)

Converts a 2-bytes (16 bits) string to an unsigned 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 unsigned 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)
PIL._binary.si16le(c, o=0)

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

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

PIL._binary.si32le(c, o=0)

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

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

Plugin reference

BmpImagePlugin Module

class PIL.BmpImagePlugin.BmpImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

Image plugin for the Windows Bitmap format (BMP)

BITFIELDS = 3
COMPRESSIONS = {'RLE4': 2, 'JPEG': 4, 'BITFIELDS': 3, 'RAW': 0, 'RLE8': 1, 'PNG': 5}
JPEG = 4
PNG = 5
RAW = 0
RLE4 = 2
RLE8 = 1
format = 'BMP'
format_description = 'Windows Bitmap'
class PIL.BmpImagePlugin.DibImageFile(fp=None, filename=None)

Bases: PIL.BmpImagePlugin.BmpImageFile

format = 'DIB'
format_description = 'Windows Bitmap'

BufrStubImagePlugin Module

class PIL.BufrStubImagePlugin.BufrStubImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.StubImageFile

format = 'BUFR'
format_description = 'BUFR'
PIL.BufrStubImagePlugin.register_handler(handler)

Install application-specific BUFR image handler.

Parameters:handler – Handler object.

CurImagePlugin Module

class PIL.CurImagePlugin.CurImageFile(fp=None, filename=None)

Bases: PIL.BmpImagePlugin.BmpImageFile

format = 'CUR'
format_description = 'Windows Cursor'

DcxImagePlugin Module

class PIL.DcxImagePlugin.DcxImageFile(fp=None, filename=None)

Bases: PIL.PcxImagePlugin.PcxImageFile

format = 'DCX'
format_description = 'Intel DCX'
is_animated
n_frames
seek(frame)
tell()

EpsImagePlugin Module

class PIL.EpsImagePlugin.EpsImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

EPS File Parser for the Python Imaging Library

format = 'EPS'
format_description = 'Encapsulated Postscript'
load(scale=1)
load_seek(*args, **kwargs)
mode_map = {1: 'L', 2: 'LAB', 3: 'RGB', 4: 'CMYK'}
PIL.EpsImagePlugin.Ghostscript(tile, size, fp, scale=1)

Render an image using Ghostscript

class PIL.EpsImagePlugin.PSFile(fp)

Bases: object

Wrapper for bytesio object that treats either CR or LF as end of line.

readline()
seek(offset, whence=0)
PIL.EpsImagePlugin.has_ghostscript()

FitsStubImagePlugin Module

class PIL.FitsStubImagePlugin.FITSStubImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.StubImageFile

format = 'FITS'
format_description = 'FITS'
PIL.FitsStubImagePlugin.register_handler(handler)

Install application-specific FITS image handler.

Parameters:handler – Handler object.

FliImagePlugin Module

class PIL.FliImagePlugin.FliImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'FLI'
format_description = 'Autodesk FLI/FLC Animation'
is_animated
n_frames
seek(frame)
tell()

FpxImagePlugin Module

class PIL.FpxImagePlugin.FpxImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'FPX'
format_description = 'FlashPix'
load()

GbrImagePlugin Module

class PIL.GbrImagePlugin.GbrImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'GBR'
format_description = 'GIMP brush file'
load()

GifImagePlugin Module

class PIL.GifImagePlugin.GifImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

data()
format = 'GIF'
format_description = 'Compuserve GIF'
global_palette = None
is_animated
load_end()
n_frames
seek(frame)
tell()
PIL.GifImagePlugin.get_interlace(im)
PIL.GifImagePlugin.getdata(im, offset=(0, 0), **params)

Return a list of strings representing this image. The first string is a local image header, the rest contains encoded image data.

PIL.GifImagePlugin.getheader(im, palette=None, info=None)

Return a list of strings representing a GIF header

GribStubImagePlugin Module

class PIL.GribStubImagePlugin.GribStubImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.StubImageFile

format = 'GRIB'
format_description = 'GRIB'
PIL.GribStubImagePlugin.register_handler(handler)

Install application-specific GRIB image handler.

Parameters:handler – Handler object.

Hdf5StubImagePlugin Module

class PIL.Hdf5StubImagePlugin.HDF5StubImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.StubImageFile

format = 'HDF5'
format_description = 'HDF5'
PIL.Hdf5StubImagePlugin.register_handler(handler)

Install application-specific HDF5 image handler.

Parameters:handler – Handler object.

IcnsImagePlugin Module

class PIL.IcnsImagePlugin.IcnsFile(fobj)

Bases: object

SIZES = {(256, 256, 1): [('ic08', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (128, 128, 2): [('ic13', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (64, 64, 1): [('icp6', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (128, 128, 1): [('ic07', <function read_png_or_jpeg2000 at 0x7fd9122a3410>), ('it32', <function read_32t at 0x7fd9122a32a8>), ('t8mk', <function read_mk at 0x7fd9122a3398>)], (32, 32, 1): [('icp5', <function read_png_or_jpeg2000 at 0x7fd9122a3410>), ('il32', <function read_32 at 0x7fd9122a3320>), ('l8mk', <function read_mk at 0x7fd9122a3398>)], (16, 16, 2): [('ic11', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (512, 512, 2): [('ic10', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (512, 512, 1): [('ic09', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (48, 48, 1): [('ih32', <function read_32 at 0x7fd9122a3320>), ('h8mk', <function read_mk at 0x7fd9122a3398>)], (256, 256, 2): [('ic14', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)], (16, 16, 1): [('icp4', <function read_png_or_jpeg2000 at 0x7fd9122a3410>), ('is32', <function read_32 at 0x7fd9122a3320>), ('s8mk', <function read_mk at 0x7fd9122a3398>)], (32, 32, 2): [('ic12', <function read_png_or_jpeg2000 at 0x7fd9122a3410>)]}
bestsize()
dataforsize(size)

Get an icon resource as {channel: array}. Note that the arrays are bottom-up like windows bitmaps and will likely need to be flipped or transposed in some way.

getimage(size=None)
itersizes()
class PIL.IcnsImagePlugin.IcnsImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

PIL image support for Mac OS .icns files. Chooses the best resolution, but will possibly load a different size image if you mutate the size attribute before calling ‘load’.

The info dictionary has a key ‘sizes’ that is a list of sizes that the icns file has.

format = 'ICNS'
format_description = 'Mac OS icns resource'
load()
PIL.IcnsImagePlugin.nextheader(fobj)
PIL.IcnsImagePlugin.read_32(fobj, start_length, size)

Read a 32bit RGB icon resource. Seems to be either uncompressed or an RLE packbits-like scheme.

PIL.IcnsImagePlugin.read_32t(fobj, start_length, size)
PIL.IcnsImagePlugin.read_mk(fobj, start_length, size)
PIL.IcnsImagePlugin.read_png_or_jpeg2000(fobj, start_length, size)

IcoImagePlugin Module

class PIL.IcoImagePlugin.IcoFile(buf)

Bases: object

frame(idx)

Get an image from frame idx

getimage(size, bpp=False)

Get an image from the icon

sizes()

Get a list of all available icon sizes and color depths.

class PIL.IcoImagePlugin.IcoImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

PIL read-only image support for Microsoft Windows .ico files.

By default the largest resolution image in the file will be loaded. This can be changed by altering the ‘size’ attribute before calling ‘load’.

The info dictionary has a key ‘sizes’ that is a list of the sizes available in the icon file.

Handles classic, XP and Vista icon formats.

This plugin is a refactored version of Win32IconImagePlugin by Bryan Davis <casadebender@gmail.com>. https://code.google.com/archive/p/casadebender/wikis/Win32IconImagePlugin.wiki

format = 'ICO'
format_description = 'Windows Icon'
load()
load_seek()

ImImagePlugin Module

class PIL.ImImagePlugin.ImImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'IM'
format_description = 'IFUNC Image Memory'
is_animated
n_frames
seek(frame)
tell()
PIL.ImImagePlugin.number(s)

ImtImagePlugin Module

class PIL.ImtImagePlugin.ImtImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'IMT'
format_description = 'IM Tools'

IptcImagePlugin Module

class PIL.IptcImagePlugin.IptcImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

field()
format = 'IPTC'
format_description = 'IPTC/NAA'
getint(key)
load()
PIL.IptcImagePlugin.dump(c)
PIL.IptcImagePlugin.getiptcinfo(im)

Get IPTC information from TIFF, JPEG, or IPTC file.

Parameters:im – An image containing IPTC data.
Returns:A dictionary containing IPTC information, or None if no IPTC information block was found.
PIL.IptcImagePlugin.i(c)

JpegImagePlugin Module

PIL.JpegImagePlugin.APP(self, marker)
PIL.JpegImagePlugin.COM(self, marker)
PIL.JpegImagePlugin.DQT(self, marker)
class PIL.JpegImagePlugin.JpegImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

draft(mode, size)
format = 'JPEG'
format_description = 'JPEG (ISO 10918)'
load_djpeg()
PIL.JpegImagePlugin.SOF(self, marker)
PIL.JpegImagePlugin.Skip(self, marker)
PIL.JpegImagePlugin.convert_dict_qtables(qtables)
PIL.JpegImagePlugin.get_sampling(im)
PIL.JpegImagePlugin.jpeg_factory(fp=None, filename=None)

Jpeg2KImagePlugin Module

class PIL.Jpeg2KImagePlugin.Jpeg2KImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'JPEG2000'
format_description = 'JPEG 2000 (ISO 15444)'
load()

McIdasImagePlugin Module

class PIL.McIdasImagePlugin.McIdasImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'MCIDAS'
format_description = 'McIdas area file'

MicImagePlugin Module

class PIL.MicImagePlugin.MicImageFile(fp=None, filename=None)

Bases: PIL.TiffImagePlugin.TiffImageFile

format = 'MIC'
format_description = 'Microsoft Image Composer'
is_animated
n_frames
seek(frame)
tell()

MpegImagePlugin Module

class PIL.MpegImagePlugin.BitStream(fp)

Bases: object

next()
peek(bits)
read(bits)
skip(bits)
class PIL.MpegImagePlugin.MpegImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'MPEG'
format_description = 'MPEG'

MspImagePlugin Module

class PIL.MspImagePlugin.MspImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'MSP'
format_description = 'Windows Paint'

PalmImagePlugin Module

PIL.PalmImagePlugin.build_prototype_image()

PcdImagePlugin Module

class PIL.PcdImagePlugin.PcdImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'PCD'
format_description = 'Kodak PhotoCD'
load_end()

PcxImagePlugin Module

class PIL.PcxImagePlugin.PcxImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'PCX'
format_description = 'Paintbrush'

PdfImagePlugin Module

PixarImagePlugin Module

class PIL.PixarImagePlugin.PixarImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'PIXAR'
format_description = 'PIXAR raster image'

PngImagePlugin Module

PIL.PngImagePlugin.getchunks(im, **params)

Return a list of PNG chunks representing this image.

PIL.PngImagePlugin.is_cid()

match(string[, pos[, endpos]]) –> match object or None. Matches zero or more characters at the beginning of the string

PIL.PngImagePlugin.putchunk(fp, cid, *data)

Write a PNG chunk (including CRC field)

class PIL.PngImagePlugin.ChunkStream(fp)

Bases: object

call(cid, pos, length)

Call the appropriate chunk handler

close()
crc(cid, data)

Read and verify checksum

crc_skip(cid, data)

Read checksum. Used if the C module is not present

push(cid, pos, length)
read()

Fetch a new chunk. Returns header information.

verify(endchunk='IEND')
class PIL.PngImagePlugin.PngImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'PNG'
format_description = 'Portable network graphics'
load_end()

internal: finished reading image data

load_prepare()

internal: prepare to read PNG file

load_read(read_bytes)

internal: read more image data

verify()

Verify PNG file

class PIL.PngImagePlugin.PngStream(fp)

Bases: PIL.PngImagePlugin.ChunkStream

check_text_memory(chunklen)
chunk_IDAT(pos, length)
chunk_IEND(pos, length)
chunk_IHDR(pos, length)
chunk_PLTE(pos, length)
chunk_gAMA(pos, length)
chunk_iCCP(pos, length)
chunk_iTXt(pos, length)
chunk_pHYs(pos, length)
chunk_tEXt(pos, length)
chunk_tRNS(pos, length)
chunk_zTXt(pos, length)

PpmImagePlugin Module

class PIL.PpmImagePlugin.PpmImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'PPM'
format_description = 'Pbmplus image'

PsdImagePlugin Module

class PIL.PsdImagePlugin.PsdImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'PSD'
format_description = 'Adobe Photoshop'
is_animated
load_prepare()
n_frames
seek(layer)
tell()

SgiImagePlugin Module

class PIL.SgiImagePlugin.SgiImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'SGI'
format_description = 'SGI Image File Format'

SpiderImagePlugin Module

class PIL.SpiderImagePlugin.SpiderImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

convert2byte(depth=255)
format = 'SPIDER'
format_description = 'Spider 2D image'
is_animated
n_frames
seek(frame)
tell()
tkPhotoImage()
PIL.SpiderImagePlugin.isInt(f)
PIL.SpiderImagePlugin.isSpiderHeader(t)
PIL.SpiderImagePlugin.isSpiderImage(filename)
PIL.SpiderImagePlugin.loadImageSeries(filelist=None)

create a list of Image.images for use in montage

PIL.SpiderImagePlugin.makeSpiderHeader(im)

SunImagePlugin Module

class PIL.SunImagePlugin.SunImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'SUN'
format_description = 'Sun Raster File'

TgaImagePlugin Module

class PIL.TgaImagePlugin.TgaImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'TGA'
format_description = 'Targa'

TiffImagePlugin Module

class PIL.TiffImagePlugin.AppendingTiffWriter(fn, new=False)
Tags = set([288, 324, 519, 520, 521, 273])
close()
fieldSizes = [0, 1, 1, 2, 4, 8, 1, 1, 2, 4, 8, 4, 8]
finalize()
fixIFD()
fixOffsets(count, isShort=False, isLong=False)
goToEnd()
newFrame()
readLong()
readShort()
rewriteLastLong(value)
rewriteLastShort(value)
rewriteLastShortToLong(value)
seek(offset, whence)
setEndian(endian)
setup()
skipIFDs()
tell()
write(data)
writeLong(value)
writeShort(value)
class PIL.TiffImagePlugin.IFDRational(value, denominator=1)

Bases: numbers.Rational

Implements a rational class where 0/0 is a legal value to match the in the wild use of exif rationals.

e.g., DigitalZoomRatio - 0.00/0.00 indicates that no digital zoom was used

denominator
limit_rational(max_denominator)
Parameters:max_denominator – Integer, the maximum denominator value
Returns:Tuple of (numerator, denominator)
numerator
PIL.TiffImagePlugin.ImageFileDirectory

alias of ImageFileDirectory_v1

class PIL.TiffImagePlugin.ImageFileDirectory_v1(*args, **kwargs)

Bases: PIL.TiffImagePlugin.ImageFileDirectory_v2

This class represents the legacy interface to a TIFF tag directory.

Exposes a dictionary interface of the tags in the directory:

ifd = ImageFileDirectory_v1()
ifd[key] = 'Some Data'
ifd.tagtype[key] = 2
print(ifd[key])
('Some Data',)

Also contains a dictionary of tag types as read from the tiff image file, ~PIL.TiffImagePlugin.ImageFileDirectory_v1.tagtype.

Values are returned as a tuple.

Deprecated since version 3.0.0.

classmethod from_v2(original)

Returns an ImageFileDirectory_v1 instance with the same data as is contained in the original ImageFileDirectory_v2 instance.

Returns:ImageFileDirectory_v1
tagdata
tags
to_v2()

Returns an ImageFileDirectory_v2 instance with the same data as is contained in the original ImageFileDirectory_v1 instance.

Returns:ImageFileDirectory_v2
class PIL.TiffImagePlugin.ImageFileDirectory_v2(ifh='II*x00x00x00x00x00', prefix=None)

Bases: _abcoll.MutableMapping

This class represents a TIFF tag directory. To speed things up, we don’t decode tags unless they’re asked for.

Exposes a dictionary interface of the tags in the directory:

ifd = ImageFileDirectory_v2()
ifd[key] = 'Some Data'
ifd.tagtype[key] = 2
print(ifd[key])
'Some Data'

Individual values are returned as the strings or numbers, sequences are returned as tuples of the values.

The tiff metadata type of each item is stored in a dictionary of tag types in ~PIL.TiffImagePlugin.ImageFileDirectory_v2.tagtype. The types are read from a tiff file, guessed from the type added, or added manually.

Data Structures:

  • self.tagtype = {}
    • Key: numerical tiff tag number
    • Value: integer corresponding to the data type from ~PIL.TiffTags.TYPES

New in version 3.0.0.

as_dict()

Return a dictionary of the image’s tags.

Deprecated since version 3.0.0.

has_key(tag)
legacy_api
load(fp)
load_byte(data, legacy_api=True)
load_double(data, legacy_api=True)
load_float(data, legacy_api=True)
load_long(data, legacy_api=True)
load_rational(data, legacy_api=True)
load_short(data, legacy_api=True)
load_signed_byte(data, legacy_api=True)
load_signed_long(data, legacy_api=True)
load_signed_rational(data, legacy_api=True)
load_signed_short(data, legacy_api=True)
load_string(data, legacy_api=True)
load_undefined(data, legacy_api=True)
named()
Returns:dict of name|key: value

Returns the complete tag dictionary, with named tags where possible.

offset
prefix
reset()
save(fp)
write_byte(data)
write_double(*values)
write_float(*values)
write_long(*values)
write_rational(*values)
write_short(*values)
write_signed_byte(*values)
write_signed_long(*values)
write_signed_rational(*values)
write_signed_short(*values)
write_string(value)
write_undefined(value)
class PIL.TiffImagePlugin.TiffImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'TIFF'
format_description = 'Adobe TIFF'
is_animated
load()
n_frames
seek(frame)

Select a given frame as current image

tell()

Return the current frame number

WebPImagePlugin Module

class PIL.WebPImagePlugin.WebPImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'WEBP'
format_description = 'WebP image'

WmfImagePlugin Module

class PIL.WmfImagePlugin.WmfStubImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.StubImageFile

format = 'WMF'
format_description = 'Windows Metafile'
PIL.WmfImagePlugin.register_handler(handler)

Install application-specific WMF image handler.

Parameters:handler – Handler object.

XVThumbImagePlugin Module

class PIL.XVThumbImagePlugin.XVThumbImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'XVThumb'
format_description = 'XV thumbnail image'

XbmImagePlugin Module

class PIL.XbmImagePlugin.XbmImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'XBM'
format_description = 'X11 Bitmap'

XpmImagePlugin Module

class PIL.XpmImagePlugin.XpmImageFile(fp=None, filename=None)

Bases: PIL.ImageFile.ImageFile

format = 'XPM'
format_description = 'X11 Pixel Map'
load_read(bytes)

Internal Reference Docs

File Handling in Pillow

When opening a file as an image, Pillow requires a filename, pathlib.Path object, or a file-like object. Pillow uses the filename or Path to open a file, so for the rest of this article, they will all be treated as a file-like object.

The first four of these items are equivalent, the last is dangerous and may fail:

from PIL import Image
import io
import pathlib

im = Image.open('test.jpg')

im2 = Image.open(pathlib.Path('test.jpg'))

f = open('test.jpg', 'rb')
im3 = Image.open(f)

with open('test.jpg', 'rb') as f:
    im4 = Image.open(io.BytesIO(f.read()))

# Dangerous FAIL:
with open('test.jpg', 'rb') as f:
    im5 = Image.open(f)
im5.load() # FAILS, closed file

The documentation specifies that the file will be closed after the Image.Image.load() method is called. This is an aspirational specification rather than an accurate reflection of the state of the code.

Pillow cannot in general close and reopen a file, so any access to that file needs to be prior to the close.

Issues

The current open file handling is inconsistent at best:

  • Most of the image plugins do not close the input file.
  • Multi-frame images behave badly when seeking through the file, as it’s legal to seek backward in the file until the last image is read, and then it’s not.
  • Using the file context manager to provide a file-like object to Pillow is dangerous unless the context of the image is limited to the context of the file.
Image Lifecycle
  • Image.open() called. Path-like objects are opened as a file. Metadata is read from the open file. The file is left open for further usage.

  • Image.Image.load() when the pixel data from the image is required, load() is called. The current frame is read into memory. The image can now be used independently of the underlying image file.

  • Image.Image.seek() in the case of multi-frame images (e.g. multipage TIFF and animated GIF) the image file left open so that seek can load the appropriate frame. When the last frame is read, the image file is closed (at least in some image plugins), and no more seeks can occur.

  • Image.Image.close() Closes the file pointer and destroys the core image object. This is used in the Pillow context manager support. e.g.:

    with Image.open('test.jpg') as img:
       ...  # image operations here.
    

The lifecycle of a single frame image is relatively simple. The file must remain open until the load() or close() function is called.

Multi-frame images are more complicated. The load() method is not a terminal method, so it should not close the underlying file. The current behavior of seek() closing the underlying file on accessing the last frame is presumably a heuristic for closing the file after iterating through the entire sequence. In general, Pillow does not know if there are going to be any requests for additional data until the caller has explicitly closed the image.

Complications
  • TiffImagePlugin has some code to pass the underlying file descriptor into libtiff (if working on an actual file). Since libtiff closes the file descriptor internally, it is duplicated prior to passing it into libtiff.

  • decoder.handles_eof This slightly misnamed flag indicates that the decoder wants to be called with a 0 length buffer when reads are done. Despite the comments in ImageFile.load(), the only decoder that actually uses this flag is the Jpeg2K decoder. The use of this flag in Jpeg2K predated the change to the decoder that added the pulls_fd flag, and is therefore not used.

  • I don’t think that there’s any way to make this safe without changing the lazy loading:

    # Dangerous FAIL:
    with open('test.jpg', 'rb') as f:
        im5 = Image.open(f)
    im5.load() # FAILS, closed file
    
Proposed File Handling
  • Image.Image.load() should close the image file, unless there are multiple frames.
  • Image.Image.seek() should never close the image file.
  • Users of the library should call Image.Image.close() on any multi-frame image to ensure that the underlying file is closed.

Limits

This page is documentation to the various fundamental size limits in the Pillow implementation.

Internal Limits
  • Image sizes cannot be negative. These are checked both in Storage.c and Image.py
  • Image sizes may be 0. (At least, prior to 3.4)
  • Maximum pixel dimensions are limited to INT32, or 2^31 by the sizes in the image header.
  • Individual allocations are limited to 2GB in Storage.c
  • The 2GB allocation puts an upper limit to the xsize of the image of either 2^31 for ‘L’ or 2^29 for ‘RGB’
  • Individual memory mapped segments are limited to 2GB in map.c based on the overflow checks. This requires that any memory mapped image is smaller than 2GB, as calculated by y*stride (so 2Gpx for ‘L’ images, and .5Gpx for ‘RGB’
  • Any call to internal python size functions for buffers or strings are currently returned as int32, not py_ssize_t. This limits the maximum buffer to 2GB for operations like frombytes and frombuffer.
  • This also limits the size of buffers converted using a decoder. (decode.c:127)
Format Size Limits

Porting

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.

Pillow will raise an exception if the core extension can’t be loaded for any reason, including a version mismatch between the Python and extension code. Previously PIL allowed Python only code to run if the core extension was not available.

About

Goals

The fork author’s goal is to foster and support active development of PIL through:

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 accommodate 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 likelihood 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 corresponding Pillow tickets here.

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

Release Notes

Note

Contributors please include release notes as needed or appropriate with your bug fixes, feature additions and tests.

4.0.0

Python 2.6 and 3.2 Dropped

Pillow 4.0 no longer supports Python 2.6 and 3.2. We will not be creating binaries, testing, or retaining compatibility with these releases. This release removes some workarounds for those Python releases, so the final working version of Pillow on 2.6 or 3.2 is 3.4.2.

Support added for Python 3.6

Pillow 4.0 supports Python 3.6.

OleFileIO.py

OleFileIO.py has been removed as a vendored file and is now installed from the upstream olefile pypi package. All internal dependencies are redirected to the olefile package. Direct accesses to PIL.OlefileIO raises a deprecation warning, then patches the upstream olefile into sys.modules in its place.

SGI image save

It is now possible to save images in modes L, RGB, and RGBA to the uncompressed SGI image format.

Zero sized images

Pillow 3.4.0 removed support for creating images with (0,0) size. This has been reenabled, restoring pre 3.4 behavior.

Internal handles_eof flag

The handles_eof flag for decoding images has been removed, as there were no internal users of the flag. Anyone maintaining image decoders outside of the Pillow source tree should consider using the cleanup function pointers instead.

Image.core.stretch removed

The stretch function on the core image object has been removed. This used to be for enlarging the image, but has been aliased to resize recently.

3.4.0

New resizing filters

Two new filters available for Image.resize() and Image.thumbnail() functions: BOX and HAMMING. BOX is the high-performance filter with two times shorter window than BILINEAR. It can be used for image reduction 3 and more times and produces a more sharp result than BILINEAR.

HAMMING filter has the same performance as BILINEAR filter while providing the image downscaling quality comparable to BICUBIC. Both new filters don’t show good quality for the image upscaling.

Deprecation Warning when Saving JPEGs

JPEG images cannot contain an alpha channel. Pillow prior to 3.4.0 silently drops the alpha channel. With this release Pillow will now issue a DeprecationWarning when attempting to save a RGBA mode image as a JPEG. This will become an error in Pillow 3.7.

New DDS Decoders

Pillow can now decode DXT3 images, as well as the previously support DXT1 and DXT5 formats. All three formats are now decoded in C code for better performance.

Append images to GIF

Additional frames can now be appended when saving a GIF file, through the append_images argument. The new frames are passed in as a list of images, which may be have multiple frames themselves.

Note that the append_images argument is only used if save_all is also in effect, e.g.:

im.save(out, save_all=True, append_images=[im1, im2, ...])

Save multiple frame TIFF

Multiple frames can now be saved in a TIFF file by using the save_all option. e.g.:

im.save("filename.tiff", format="TIFF", save_all=True)

Image.core.open_ppm removed

The nominally private/debugging function Image.core.open_ppm has been removed. If you were using this function, please use Image.open instead.

3.3.2

Integer overflow in Map.c

Pillow prior to 3.3.2 may experience integer overflow errors in map.c when reading specially crafted image files. This may lead to memory disclosure or corruption.

Specifically, when parameters from the image are passed into Image.core.map_buffer, the size of the image was calculated with xsize``*``ysize``*``bytes_per_pixel. This will overflow if the result is larger than SIZE_MAX. This is possible on a 32-bit system.

Furthermore this size value was added to a potentially attacker provided offset value and compared to the size of the buffer without checking for overflow or negative values.

These values were then used for creating pointers, at which point Pillow could read the memory and include it in other images. The image was marked readonly, so Pillow would not ordinarily write to that memory without duplicating the image first.

This issue was found by Cris Neckar at Divergent Security.

Sign Extension in Storage.c

Pillow prior to 3.3.2 and PIL 1.1.7 (at least) do not check for negative image sizes in ImagingNew in Storage.c. A negative image size can lead to a smaller allocation than expected, leading to arbitrary writes.

This issue was found by Cris Neckar at Divergent Security.

3.3.0

Libimagequant support

There is now support for using libimagequant as a higher quality quantization option in Image.quantize() on Unix-like platforms. This support requires building Pillow from source against libimagequant. We cannot distribute binaries due to licensing differences.

New Setup.py options

There are two new options to control the build_ext task in setup.py:

  • --debug dumps all of the directories and files that are checked when searching for libraries or headers when building the extensions.
  • --disable-platform-guessing removes many of the directories that are checked for libraries and headers for build systems or cross compilers that specify that information in via environment variables.

Resizing

Image resampling for 8-bit per channel images was rewritten using only integer computings. This is faster on most of the platforms and doesn’t introduce precision errors on the wide range of scales. With other performance improvements, this makes resampling 60% faster on average.

Color calculation for images in the LA mode on semitransparent pixels was fixed.

Rotation

Rotation for angles divisible by 90 degrees now always uses transposition. This greatly improve both quality and performance in this cases. Also, the bug with wrong image size calculation when rotating by 90 degrees was fixed.

Image Metadata

The return type for binary data in version 2 Exif and Tiff metadata has been changed from a tuple of integers to bytes. This is a change from the behavior since 3.0.0.

3.2.0

New DDS and FTEX Image Plugins

The DdsImagePlugin reading DXT1 and DXT5 encoded .dds images was added. DXT3 images are not currently supported.

The FtexImagePlugin reads textures used for 3D objects in Independence War 2: Edge Of Chaos. The plugin reads a single texture per file, in the .ftc (compressed) and .ftu (uncompressed) formats.

Updates to the GbrImagePlugin

The GbrImagePlugin (GIMP brush format) has been updated to fix support for version 1 files and add support for version 2 files.

Passthrough Parameters for ImageDraw.text

ImageDraw.multiline_text and ImageDraw.multiline_size take extra spacing parameters above what are used in ImageDraw.text and ImageDraw.size. These parameters can now be passed into ImageDraw.text and ImageDraw.size and they will be passed through to the corresponding multiline functions.

ImageSequence.Iterator changes

ImageSequence.Iterator is now an actual iterator implementing the Iterator protocol. It is also now possible to seek to the first image of the file when using direct indexing.

3.1.2

CVE-2016-3076 – Buffer overflow in Jpeg2KEncode.c

Pillow between 2.5.0 and 3.1.1 may overflow a buffer when writing large Jpeg2000 files, allowing for code execution or other memory corruption.

This occurs specifically in the function j2k_encode_entry, at the line:

state->buffer = malloc (tile_width * tile_height * components * prec / 8);

This vulnerability requires a particular value for height * width such that height * width * components * precision overflows, at which point the malloc will be for a smaller value than expected. The buffer that is allocated will be ((height * width * components * precision) mod (2^31) / 8), where components is 1-4 and precision is either 8 or 16. Common values would be 4 components at precision 8 for a standard RGBA image.

The unpackers then split an image that is laid out:

RGBARGBARGBA....

into:

RRR.
GGG.
BBB.
AAA.

If this buffer is smaller than expected, the jpeg2k unpacker functions will write outside the allocation and onto the heap, corrupting memory.

This issue was found by Alyssa Besseling at Atlassian.

3.1.1

CVE-2016-0740 – Buffer overflow in TiffDecode.c

Pillow 3.1.0 and earlier when linked against libtiff >= 4.0.0 on x64 may overflow a buffer when reading a specially crafted tiff file.

Specifically, libtiff >= 4.0.0 changed the return type of TIFFScanlineSize from int32 to machine dependent int32|64. If the scanline is sized so that it overflows an int32, it may be interpreted as a negative number, which will then pass the size check in TiffDecode.c line 236. To do this, the logical scanline size has to be > 2gb, and for the test file, the allocated buffer size is 64k against a roughly 4gb scan line size. Any image data over 64k is written over the heap, causing a segfault.

This issue was found by security researcher FourOne.

CVE-2016-0775 – Buffer overflow in FliDecode.c

In all versions of Pillow, dating back at least to the last PIL 1.1.7 release, FliDecode.c has a buffer overflow error.

Around line 192:

case 16:
    /* COPY chunk */
    for (y = 0; y < state->ysize; y++) {
        UINT8* buf = (UINT8*) im->image[y];
        memcpy(buf+x, data, state->xsize);
        data += state->xsize;
    }
    break;

The memcpy has error where x is added to the target buffer address. X is used in several internal temporary variable roles, but can take a value up to the width of the image. Im->image[y] is a set of row pointers to segments of memory that are the size of the row. At the max y, this will write the contents of the line off the end of the memory buffer, causing a segfault.

This issue was found by Alyssa Besseling at Atlassian

CVE-2016-2533 – Buffer overflow in PcdDecode.c

In all versions of Pillow, dating back at least to the last PIL 1.1.7 release, PcdDecode.c has a buffer overflow error.

The state.buffer for PcdDecode.c is allocated based on a 3 bytes per pixel sizing, where PcdDecode.c wrote into the buffer assuming 4 bytes per pixel. This writes 768 bytes beyond the end of the buffer into other Python object storage. In some cases, this causes a segfault, in others an internal Python malloc error.

Integer overflow in Resample.c

If a large value was passed into the new size for an image, it is possible to overflow an int32 value passed into malloc.

kk = malloc(xsize * kmax * sizeof(float)); ... xbounds = malloc(xsize * 2 * sizeof(int));

xsize is trusted user input. These multiplications can overflow, leading the malloc’d buffer to be undersized. These allocations are followed by a loop that writes out of bounds. This can lead to corruption on the heap of the Python process with attacker controlled float data.

This issue was found by Ned Williamson.

3.1.0

ImageDraw arc, chord and pieslice can now use floats

There is no longer a need to ensure that the start and end arguments for arc, chord and pieslice are integers.

Note that these numbers are not simply rounded internally, but are actually utilised in the drawing process.

Consistent multiline text spacing

When using the ImageDraw multiline methods, the spacing between lines was inconsistent, based on the combination on ascenders and descenders.

This has now been fixed, so that lines are offset by their baselines, not the absolute height of each line.

There is also now a default spacing of 4px between lines.

Exif, Jpeg and Tiff Metadata

There were major changes in the TIFF ImageFileDirectory support in Pillow 3.0 that led to a number of regressions. Some of them have been fixed in Pillow 3.1, and some of them have been extended to have different behavior.

TiffImagePlugin.IFDRational

Pillow 3.0 changed rational metadata to use a float. In Pillow 3.1, this has changed to allow the expression of 0/0 as a valid piece of rational metadata to reflect usage in the wild.

Rational metadata is now encapsulated in an IFDRational instance. This class extends the Rational class to allow a denominator of 0. It compares as a float or a number, but does allow access to the raw numerator and denominator values through attributes.

When used in a ImageFileDirectory_v1, a 2 item tuple is returned of the numerator and denominator, as was done previously.

This class should be used when adding a rational value to an ImageFileDirectory for saving to image metadata.

JpegImagePlugin._getexif

In Pillow 3.0, the dictionary returned from the private, experimental, but generally widely used _getexif function changed to reflect the ImageFileDirectory_v2 format, without a fallback to the previous format.

In Pillow 3.1, _getexif now returns a dictionary compatible with Pillow 2.9 and earlier, built with ImageFileDirectory_v1 instances. Additionally, any single item tuples have been unwrapped and return a bare element.

The format returned by Pillow 3.0 has been abandoned. A more fully featured interface for EXIF is anticipated in a future release.

Out of Spec Metadata

In Pillow 3.0 and 3.1, images that contain metadata that is internally consistent but not in agreement with the TIFF spec may cause an exception when reading the metadata. This can happen when a tag that is specified to have a single value is stored with an array of values.

It is anticipated that this behavior will change in future releases.

3.0.0

Saving Multipage Images

There is now support for saving multipage images in the GIF and PDF formats. To enable this functionality, pass in save_all=True as a keyword argument to the save:

im.save('test.pdf', save_all=True)

Tiff ImageFileDirectory Rewrite

The Tiff ImageFileDirectory metadata code has been rewritten. Where previously it returned a somewhat arbitrary set of values and tuples, it now returns bare values where appropriate and tuples when the metadata item is a sequence or collection.

The original metadata is still available in the TiffImage.tags, the new values are available in the TiffImage.tags_v2 member. The old structures will be deprecated at some point in the future. When saving Tiff metadata, new code should use the TiffImagePlugin.ImageFileDirectory_v2 class.

Deprecated Methods

Several methods that have been marked as deprecated for many releases have been removed in this release:

Image.tostring()
Image.fromstring()
Image.offset()
ImageDraw.setink()
ImageDraw.setfill()
The ImageFileIO module
The ImageFont.FreeTypeFont and ImageFont.truetype `file` keyword arg
The ImagePalette private _make functions
ImageWin.fromstring()
ImageWin.tostring()

LibJpeg and Zlib are Required by Default

The external dependencies on libjpeg and zlib are now required by default. If the headers or libraries are not found, then installation will abort with an error. This behaviour can be disabled with the --disable-libjpeg and --disable-zlib flags.

2.8.0

Open HTTP response objects with Image.open

HTTP response objects returned from urllib2.urlopen(url) or requests.get(url, stream=True).raw are ‘file-like’ but do not support .seek() operations. As a result PIL was unable to open them as images, requiring a wrap in cStringIO or BytesIO.

Now new functionality has been added to Image.open() by way of an .seek(0) check and catch on exception AttributeError or io.UnsupportedOperation. If this is caught we attempt to wrap the object using io.BytesIO (which will only work on buffer-file-like objects).

This allows opening of files using both urllib2 and requests, e.g.:

Image.open(urllib2.urlopen(url))
Image.open(requests.get(url, stream=True).raw)

If the response uses content-encoding (compression, either gzip or deflate) then this will fail as both the urllib2 and requests raw file object will produce compressed data in that case. Using Content-Encoding on images is rather non-sensical as most images are already compressed, but it can still happen.

For requests the work-around is to set the decode_content attribute on the raw object to True:

response = requests.get(url, stream=True)
response.raw.decode_content = True
image = Image.open(response.raw)

2.7.0

Sane Plugin

The Sane plugin has now been split into its own repo: https://github.com/python-pillow/Sane .

Png text chunk size limits

To prevent potential denial of service attacks using compressed text chunks, there are now limits to the decompressed size of text chunks decoded from PNG images. If the limits are exceeded when opening a PNG image a ValueError will be raised.

Individual text chunks are limited to PIL.PngImagePlugin.MAX_TEXT_CHUNK, set to 1MB by default. The total decompressed size of all text chunks is limited to PIL.PngImagePlugin.MAX_TEXT_MEMORY, which defaults to 64MB. These values can be changed prior to opening PNG images if you know that there are large text blocks that are desired.

Image resizing filters

Image resizing methods resize() and thumbnail() take a resample argument, which tells which filter should be used for resampling. Possible values are: PIL.Image.NEAREST, PIL.Image.BILINEAR, PIL.Image.BICUBIC and PIL.Image.ANTIALIAS. Almost all of them were changed in this version.

Bicubic and bilinear downscaling

From the beginning BILINEAR and BICUBIC filters were based on affine transformations and used a fixed number of pixels from the source image for every destination pixel (2x2 pixels for BILINEAR and 4x4 for BICUBIC). This gave an unsatisfactory result for downscaling. At the same time, a high quality convolutions-based algorithm with flexible kernel was used for ANTIALIAS filter.

Starting from Pillow 2.7.0, a high quality convolutions-based algorithm is used for all of these three filters.

If you have previously used any tricks to maintain quality when downscaling with BILINEAR and BICUBIC filters (for example, reducing within several steps), they are unnecessary now.

Antialias renamed to Lanczos

A new PIL.Image.LANCZOS constant was added instead of ANTIALIAS.

When ANTIALIAS was initially added, it was the only high-quality filter based on convolutions. It’s name was supposed to reflect this. Starting from Pillow 2.7.0 all resize method are based on convolutions. All of them are antialias from now on. And the real name of the ANTIALIAS filter is Lanczos filter.

The ANTIALIAS constant is left for backward compatibility and is an alias for LANCZOS.

Lanczos upscaling quality

The image upscaling quality with LANCZOS filter was almost the same as BILINEAR due to bug. This has been fixed.

Bicubic upscaling quality

The BICUBIC filter for affine transformations produced sharp, slightly pixelated image for upscaling. Bicubic for convolutions is more soft.

Resize performance

In most cases, convolution is more a expensive algorithm for downscaling because it takes into account all the pixels of source image. Therefore BILINEAR and BICUBIC filters’ performance can be lower than before. On the other hand the quality of BILINEAR and BICUBIC was close to NEAREST. So if such quality is suitable for your tasks you can switch to NEAREST filter for downscaling, which will give a huge improvement in performance.

At the same time performance of convolution resampling for downscaling has been improved by around a factor of two compared to the previous version. The upscaling performance of the LANCZOS filter has remained the same. For BILINEAR filter it has improved by 1.5 times and for BICUBIC by four times.

Default filter for thumbnails

In Pillow 2.5 the default filter for thumbnail() was changed from NEAREST to ANTIALIAS. Antialias was chosen because all the other filters gave poor quality for reduction. Starting from Pillow 2.7.0, ANTIALIAS has been replaced with BICUBIC, because it’s faster and ANTIALIAS doesn’t give any advantages after downscaling with libjpeg, which uses supersampling internally, not convolutions.

Image transposition

A new method PIL.Image.TRANSPOSE has been added for the transpose() operation in addition to FLIP_LEFT_RIGHT, FLIP_TOP_BOTTOM, ROTATE_90, ROTATE_180, ROTATE_270. TRANSPOSE is an algebra transpose, with an image reflected across its main diagonal.

The speed of ROTATE_90, ROTATE_270 and TRANSPOSE has been significantly improved for large images which don’t fit in the processor cache.

Gaussian blur and unsharp mask

The GaussianBlur() implementation has been replaced with a sequential application of box filters. The new implementation is based on “Theoretical foundations of Gaussian convolution by extended box filtering” from the Mathematical Image Analysis Group. As UnsharpMask() implementations use Gaussian blur internally, all changes from this chapter are also applicable to it.

Blur radius

There was an error in the previous version of Pillow, where blur radius (the standard deviation of Gaussian) actually meant blur diameter. For example, to blur an image with actual radius 5 you were forced to use value 10. This has been fixed. Now the meaning of the radius is the same as in other software.

If you used a Gaussian blur with some radius value, you need to divide this value by two.

Blur performance

Box filter computation time is constant relative to the radius and depends on source image size only. Because the new Gaussian blur implementation is based on box filter, its computation time also doesn’t depends on the blur radius.

For example, previously, if the execution time for a given test image was 1 second for radius 1, 3.6 seconds for radius 10 and 17 seconds for 50, now blur with any radius on same image is executed for 0.2 seconds.

Blur quality

The previous implementation takes into account only source pixels within 2 * standard deviation radius for every destination pixel. This was not enough, so the quality was worse compared to other Gaussian blur software.

The new implementation does not have this drawback.

TIFF Parameter Changes

Several kwarg parameters for saving TIFF images were previously specified as strings with included spaces (e.g. ‘x resolution’). This was difficult to use as kwargs without constructing and passing a dictionary. These parameters now use the underscore character instead of space. (e.g. ‘x_resolution’)

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Indices and tables