PEP: 368 Title: Standard image protocol and class Version: $Revision$
Last-Modified: $Date$ Author: Lino Mastrodomenico
<l.mastrodomenico@gmail.com> Status: Deferred Type: Standards Track
Content-Type: text/x-rst Created: 28-Jun-2007 Python-Version: 2.6, 3.0
Post-History:

Abstract

The current situation of image storage and manipulation in the Python
world is extremely fragmented: almost every library that uses image
objects has implemented its own image class, incompatible with everyone
else's and often not very pythonic. A basic RGB image class exists in
the standard library (Tkinter.PhotoImage), but is pretty much unusable,
and unused, for anything except Tkinter programming.

This fragmentation not only takes up valuable space in the developers
minds, but also makes the exchange of images between different libraries
(needed in relatively common use cases) slower and more complex than it
needs to be.

This PEP proposes to improve the situation by defining a simple and
pythonic image protocol/interface that can be hopefully accepted and
implemented by existing image classes inside and outside the standard
library without breaking backward compatibility with their existing user
bases. In practice this is a definition of how a minimal image-like
object should look and act (in a similar way to the read() and write()
methods in file-like objects).

The inclusion in the standard library of a class that provides basic
image manipulation functionality and implements the new protocol is also
proposed, together with a mixin class that helps adding support for the
protocol to existing image classes.

PEP Deferral

Further exploration of the concepts covered in this PEP has been
deferred for lack of a current champion interested in promoting the
goals of the PEP and collecting and incorporating feedback, and with
sufficient available time to do so effectively.

Rationale

A good way to have high quality modules ready for inclusion in the
Python standard library is to simply wait for natural selection among
competing external libraries to provide a clear winner with useful
functionality and a big user base. Then the de facto standard can be
officially sanctioned by including it in the standard library.

Unfortunately this approach hasn't worked well for the creation of a
dominant image class in the Python world: almost every third-party
library that requires an image object creates its own class incompatible
with the ones from other libraries. This is a real problem because it's
entirely reasonable for a program to create and manipulate an image
using, e.g., PIL (the Python Imaging Library) and then display it using
wxPython or pygame. But these libraries have different and incompatible
image classes, and the usual solution is to manually "export" an image
from the source to a (width, height, bytes_string) tuple and "import" it
creating a new instance in the target format. This approach works, but
is both uglier and slower than it needs to be.

Another "solution" that has been sometimes used is the creation of
specific adapters and/or converters from a class to another (e.g. PIL
offers the ImageTk module for converting PIL images to a class
compatible with the Tkinter one). But this approach doesn't scale well
with the number of libraries involved and it's still annoying for the
user: if I have a perfectly good image object why should I convert
before passing it to the next method, why can't it simply accept my
image as-is?

The problem isn't by any stretch limited to the three mentioned
libraries and has probably multiple causes, including two that IMO are
very important to understand before solving it:

-   in today's computing world an image is a basic type not strictly
    tied to a specific domain. This is why there will never be a clear
    winner between the image classes from the three libraries mentioned
    above (PIL, wxPython and pygame): they cover different domains and
    don't really compete with each other;
-   the Python standard library has never provided a good image class
    that can be adopted or imitated by third part modules.
    Tkinter.PhotoImage provides basic RGB functionality, but it's by far
    the slowest and ugliest of the bunch and it can be instantiated only
    after the Tkinter root window has been created.

This PEP tries to improve this situation in four ways:

1.  It defines a simple and pythonic image protocol/interface (both on
    the Python and the C side) that can be hopefully accepted and
    implemented by existing image classes inside and outside the
    standard library without breaking backward compatibility with their
    existing user bases.
2.  It proposes the inclusion in the standard library of three new
    classes:
    -   ImageMixin provides almost everything necessary to implement the
        new protocol; its main purpose is to make as simple as possible
        to support this interface for existing libraries, in some cases
        as simple as adding it to the list of base classes and doing
        minor additions to the constructor.
    -   Image is a subclass of ImageMixin and will add a constructor
        that can resize and/or convert an image between different pixel
        formats. This is intended to provide a fast and efficient
        default implementation of the new protocol.
    -   ImageSize is a minor helper class. See below for details.
3.  Tkinter.PhotoImage will implement the new protocol (mostly through
    the ImageMixin class) and all the Tkinter methods that can receive
    an image will be modified the accept any object that implements the
    interface. As an aside the author of this PEP will collaborate with
    the developers of the most common external libraries to achieve the
    same goal (supporting the protocol in their classes and accepting
    any class that implements it).
4.  New PyImage_* functions will be added to the CPython C API: they
    implement the C side of the protocol and accept as first parameter
    any object that supports it, even if it isn't an instance of the
    Image/ImageMixin classes.

The main effects for the end user will be a simplification of the
interchange of images between different libraries (if everything goes
well, any Python library will accept images from any other library) and
the out-of-the-box availability of the new Image class. The new class is
intended to cover simple but common use cases like cropping and/or
resizing a photograph to the desired size and passing it an appropriate
widget for displaying it on a window, or darkening a texture and passing
it to a 3D library.

The Image class is not intended to replace or compete with PIL,
Pythonmagick or NumPy, even if it provides a (very small) subset of the
functionality of these three libraries. In particular PIL offers very
rich image manipulation features with dozens of classes, filters,
transformations and file formats. The inclusion of PIL (or something
similar) in the standard library may, or may not, be a worthy goal but
it's completely outside the scope of this PEP.

Specification

The imageop module is used as the default location for the new classes
and objects because it has for a long time hosted functions that
provided a somewhat similar functionality, but a new module may be
created if preferred (e.g. a new "image" or "media" module; the latter
may eventually include other multimedia classes).

MODES is a new module level constant: it is a set of the pixel formats
supported by the Image class. Any image object that implements the new
protocol is guaranteed to be formatted in one of these modes, but
libraries that accept images are allowed to support only a subset of
them.

These modes are in turn also available as module level constants (e.g.
imageop.RGB).

The following table is a summary of the modes currently supported and
their properties:

+-------------+-------------+-------------+-------------+-------------+
|   Name      |   Component | Bits per    | Subsampling |   Valid     |
|             |   names     | component   |             |   intervals |
+-------------+-------------+-------------+-------------+-------------+
| ---------   | ---------   | ---------   | ---------   | ---------   |
+-------------+-------------+-------------+-------------+-------------+
| L           | l           | 8           | no          | full range  |
|             | (lowercase  |             |             |             |
|             | L)          |             |             |             |
+-------------+-------------+-------------+-------------+-------------+
| L16         | l           | 16          | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| L32         | l           | 32          | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| LA          | l, a        | 8           | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| LA32        | l, a        | 16          | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| RGB         | r, g, b     | 8           | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| RGB48       | r, g, b     | 16          | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| RGBA        | r, g, b, a  | 8           | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| RGBA64      | r, g, b, a  | 16          | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| YV12        | y, cr, cb   | 8           | 1, 2, 2     | 16-235,     |
|             |             |             |             | 16-240,     |
|             |             |             |             | 16-240      |
+-------------+-------------+-------------+-------------+-------------+
| JPEG_YV12   | y, cr, cb   | 8           | 1, 2, 2     | full range  |
+-------------+-------------+-------------+-------------+-------------+
| CMYK        | c, m, y, k  | 8           | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+
| CMYK64      | c, m, y, k  | 16          | no          | full range  |
+-------------+-------------+-------------+-------------+-------------+

When the name of a mode ends with a number, it represents the average
number of bits per pixel. All the other modes simply use a byte per
component per pixel.

No palette modes or modes with less than 8 bits per component are
supported. Welcome to the 21st century.

Here's a quick description of the modes and the rationale for their
inclusion; there are four groups of modes:

1.  grayscale (L* modes): they are heavily used in scientific computing
    (those people may also need a very high dynamic range and precision,
    hence L32, the only mode with 32 bits per component) and sometimes
    it can be useful to consider a single component of a color image as
    a grayscale image (this is used by the individual planes of the
    planar images, see YV12 below); the name of the component ('l',
    lowercase letter L) stands for luminance, the second optional
    component ('a') is the alpha value and represents the opacity of the
    pixels: alpha = 0 means full transparency, alpha = 255/65535
    represents a fully opaque pixel;

2.  RGB* modes: the garden variety color images. The optional alpha
    component has the same meaning as in grayscale modes;

3.  YCbCr, a.k.a. YUV (*YV12 modes). These modes are planar (i.e. the
    values of all the pixel for each component are stored in a
    consecutive memory area, instead of the usual arrangement where all
    the components of a pixel reside in consecutive bytes) and use a 1,
    2, 2 (a.k.a. 4:2:0) subsampling (i.e. each pixel has its own Y
    value, but the Cb and Cr components are shared between groups of 2x2
    adjacent pixels) because this is the format that's by far the most
    common for YCbCr images. Please note that the V (Cr) plane is stored
    before the U (Cb) plane.

    YV12 is commonly used for MPEG2 (including DVDs), MPEG4 (both
    ASP/DivX and AVC/H.264) and Theora video frames. Valid values for Y
    are in range(16, 236) (excluding 236), and valid values for Cb and
    Cr are in range(16, 241). JPEG_YV12 is similar to YV12, but the
    three components can have the full range of 256 values. It's the
    native format used by almost all JPEG/JFIF files and by MJPEG video
    frames. The "strangeness" of these two wrt all the other supported
    modes derives from the fact that they are widely used that way by a
    lot of existing libraries and applications; this is also the reason
    why they are included (and the fact that they can't losslessly
    converted to RGB because YCbCr is a bigger color space); the funny
    4:2:0 planar arrangement of the pixel values is relatively easy to
    support because in most cases the three planes can be considered
    three separate grayscale images;

4.  CMYK* modes (cyan, magenta, yellow and black) are subtractive color
    modes, used for printing color images on dead trees. Professional
    designers love to pretend that they can't live without them, so here
    they are.

Python API

See the examples below.

In Python 2.x, all the new classes defined here are new-style classes.

Mode Objects

The mode objects offer a number of attributes and methods that can be
used for implementing generic algorithms that work on different types of
images:

components

  The number of components per pixel (e.g. 4 for an RGBA image).

component_names

  A tuple of strings; see the column "Component names" in the above
  table.

bits_per_component

  8, 16 or 32; see "Bits per component" in the above table.

bytes_per_pixel

  components * bits_per_component // 8, only available for non planar
  modes (see below).

planar

  Boolean; True if the image components reside each in a separate plane.
  Currently this happens if and only if the mode uses subsampling.

subsampling

  A tuple that for each component in the mode contains a tuple of two
  integers that represent the amount of downsampling in the horizontal
  and vertical direction, respectively. In practice it's
  ((1, 1), (2, 2), (2, 2)) for YV12 and JPEG_YV12 and
  ((1, 1),) * components for everything else.

x_divisor

  max(x for x, y in subsampling); the width of an image that uses this
  mode must be divisible for this value.

y_divisor

  max(y for x, y in subsampling); the height of an image that uses this
  mode must be divisible for this value.

intervals

  A tuple that for each component in the mode contains a tuple of two
  integers: the minimum and maximum valid value for the component. Its
  value is ((16, 235), (16, 240), (16, 240)) for YV12 and
  ((0, 2 ** bits_per_component - 1),) * components for everything else.

get_length(iterable[integer]) -> int

  The parameter must be an iterable that contains two integers: the
  width and height of an image; it returns the number of bytes needed to
  store an image of these dimensions with this mode.

Implementation detail: the modes are instances of a subclass of str and
have a value equal to their name (e.g. imageop.RGB == 'RGB') except for
L32 that has value 'I'. This is only intended for backward compatibility
with existing PIL users; new code that uses the image protocol proposed
here should not rely on this detail.

Image Protocol

Any object that supports the image protocol must provide the following
methods and attributes:

mode

  The format and the arrangement of the pixels in this image; it's one
  of the constants in the MODES set.

size

  An instance of the ImageSize class; it's a named tuple of two
  integers: the width and the height of the image in pixels; both of
  them must be >= 1 and can also be accessed as the width and height
  attributes of size.

buffer

  A sequence of integers between 0 and 255; they are the actual bytes
  used for storing the image data (i.e. modifying their values affects
  the image pixels and vice versa); the data has a
  row-major/C-contiguous order without padding and without any special
  memory alignment, even when there are more than 8 bits per component.
  The only supported methods are __len__, __getitem__/__setitem__ (with
  both integers and slice indexes) and __iter__; on the C side it
  implements the buffer protocol.

  This is a pretty low level interface to the image and the user is
  responsible for using the correct (native) byte order for modes with
  more than 8 bit per component and the correct value ranges for YV12
  images. A buffer may or may not keep a reference to its image, but
  it's still safe (if useless) to use the buffer even after the
  corresponding image has been destroyed by the garbage collector (this
  will require changes to the image class of wxPython and possibly other
  libraries). Implementation detail: this can be an array('B'), a
  bytes() object or a specialized fixed-length type.

info

  A dict object that can contain arbitrary metadata associated with the
  image (e.g. DPI, gamma, ICC profile, exposure time...); the
  interpretation of this data is beyond the scope of this PEP and
  probably depends on the library used to create and/or to save the
  image; if a method of the image returns a new image, it can copy or
  adapt metadata from its own info attribute (the ImageMixin
  implementation always creates a new image with an empty info
  dictionary).

bits_per_component
bytes_per_pixel
component_names
components
intervals
planar
subsampling

  Shortcuts for the corresponding mode.* attributes.

map(function[, function...]) -> None

  For every pixel in the image, maps each component through the
  corresponding function. If only one function is passed, it is used
  repeatedly for each component. This method modifies the image in place
  and is usually very fast (most of the time the functions are called
  only a small number of times, possibly only once for simple functions
  without branches), but it imposes a number of restrictions on the
  function(s) passed:

  -   it must accept a single integer argument and return a number (map
      will round the result to the nearest integer and clip it to
      range(0, 2 ** bits_per_component), if necessary);
  -   it must not try to intercept any BaseException, Exception or any
      unknown subclass of Exception raised by any operation on the
      argument (implementations may try to optimize the speed by passing
      funny objects, so even a simple "if n == 10:" may raise an
      exception: simply ignore it, map will take care of it); catching
      any other exception is fine;
  -   it should be side-effect free and its result should not depend on
      values (other than the argument) that may change during a single
      invocation of map.

rotate90() -> image
rotate180() -> image
rotate270() -> image

  Return a copy of the image rotated 90, 180 or 270 degrees
  counterclockwise around its center.

clip() -> None

  Saturates invalid component values in YV12 images to the minimum or
  the maximum allowed (see mode.intervals), for other image modes this
  method does nothing, very fast; libraries that save/export YV12 images
  are encouraged to always call this method, since intermediate
  operations (e.g. the map method) may assign to pixels values outside
  the valid intervals.

split() -> tuple[image]

  Returns a tuple of L, L16 or L32 images corresponding to the
  individual components in the image.

Planar images also supports attributes with the same names defined in
component_names: they contain grayscale (mode L) images that offer a
view on the pixel values for the corresponding component; any change to
the subimages is immediately reflected on the parent image and vice
versa (their buffers refer to the same memory location).

Non-planar images offer the following additional methods:

pixels() -> iterator[pixel]

  Returns an iterator that iterates over all the pixels in the image,
  starting from the top line and scanning each line from left to right.
  See below for a description of the pixel objects.

__iter__() -> iterator[line]

  Returns an iterator that iterates over all the lines in the image,
  from top to bottom. See below for a description of the line objects.

__len__() -> int

  Returns the number of lines in the image (size.height).

__getitem__(integer) -> line

  Returns the line at the specified (y) position.

__getitem__(tuple[integer]) -> pixel

  The parameter must be a tuple of two integers; they are interpreted
  respectively as x and y coordinates in the image (0, 0 is the top left
  corner) and a pixel object is returned.

__getitem__(slice | tuple[integer | slice]) -> image

  The parameter must be a slice or a tuple that contains two slices or
  an integer and a slice; the selected area of the image is copied and a
  new image is returned; image[x:y:z] is equivalent to image[:, x:y:z].

__setitem__(tuple[integer], integer | iterable[integer]) -> None

  Modifies the pixel at specified position; image[x, y] = integer is a
  shortcut for image[x, y] = (integer,) for images with a single
  component.

__setitem__(slice | tuple[integer | slice], image) -> None

  Selects an area in the same way as the corresponding form of the
  __getitem__ method and assigns to it a copy of the pixels from the
  image in the second argument, that must have exactly the same mode as
  this image and the same size as the specified area; the alpha
  component, if present, is simply copied and doesn't affect the other
  components of the image (i.e. no alpha compositing is performed).

The mode, size and buffer (including the address in memory of the
buffer) never change after an image is created.

It is expected that, if PEP 3118 is accepted, all the image objects will
support the new buffer protocol, however this is beyond the scope of
this PEP.

Image and ImageMixin Classes

The ImageMixin class implements all the methods and attributes described
above except mode, size, buffer and info. Image is a subclass of
ImageMixin that adds support for these four attributes and offers the
following constructor (please note that the constructor is not part of
the image protocol):

__init__(mode, size, color, source)

  mode must be one of the constants in the MODES set, size is a sequence
  of two integers (width and height of the new image); color is a
  sequence of integers, one for each component of the image, used to
  initialize all the pixels to the same value; source can be a sequence
  of integers of the appropriate size and format that is copied as-is in
  the buffer of the new image or an existing image; in Python 2.x source
  can also be an instance of str and is interpreted as a sequence of
  bytes. color and source are mutually exclusive and if they are both
  omitted the image is initialized to transparent black (all the bytes
  in the buffer have value 16 in the YV12 mode, 255 in the CMYK* modes
  and 0 for everything else). If source is present and is an image, mode
  and/or size can be omitted; if they are specified and are different
  from the source mode and/or size, the source image is converted.

  The exact algorithms used for resizing and doing color space
  conversions may differ between Python versions and implementations,
  but they always give high quality results (e.g.: a cubic spline
  interpolation can be used for upsampling and an antialias filter can
  be used for downsampling images); any combination of mode conversion
  is supported, but the algorithm used for conversions to and from the
  CMYK* modes is pretty naïve: if you have the exact color profiles of
  your devices you may want to use a good color management tool such as
  LittleCMS. The new image has an empty info dict.

Line Objects

The line objects (returned, e.g., when iterating over an image) support
the following attributes and methods:

mode

  The mode of the image from where this line comes.

__iter__() -> iterator[pixel]

  Returns an iterator that iterates over all the pixels in the line,
  from left to right. See below for a description of the pixel objects.

__len__() -> int

  Returns the number of pixels in the line (the image width).

__getitem__(integer) -> pixel

  Returns the pixel at the specified (x) position.

__getitem__(slice) -> image

  The selected part of the line is copied and a new image is returned;
  the new image will always have height 1.

__setitem__(integer, integer | iterable[integer]) -> None

  Modifies the pixel at the specified position; line[x] = integer is a
  shortcut for line[x] = (integer,) for images with a single component.

__setitem__(slice, image) -> None

  Selects a part of the line and assigns to it a copy of the pixels from
  the image in the second argument, that must have height 1, a width
  equal to the specified slice and the same mode as this line; the alpha
  component, if present, is simply copied and doesn't affect the other
  components of the image (i.e. no alpha compositing is performed).

Pixel Objects

The pixel objects (returned, e.g., when iterating over a line) support
the following attributes and methods:

mode

  The mode of the image from where this pixel comes.

value

  A tuple of integers, one for each component. Any iterable of the
  correct length can be assigned to value (it will be automagically
  converted to a tuple), but you can't assign to it an integer, even if
  the mode has only a single component: use, e.g., pixel.l = 123
  instead.

r, g, b, a, l, c, m, y, k

  The integer values of each component; only those applicable for the
  current mode (in mode.component_names) will be available.

__iter__() -> iterator[int]
__len__() -> int
__getitem__(integer | slice) -> int | tuple[int]
__setitem__(integer | slice, integer | iterable[integer]) ->                                                              None

  These four methods emulate a fixed length list of integers, one for
  each pixel component.

ImageSize Class

ImageSize is a named tuple, a class identical to tuple except that:

-   its constructor only accepts two integers, width and height; they
    are converted in the constructor using their __index__() methods, so
    all the ImageSize objects are guaranteed to contain only int (or
    possibly long, in Python 2.x) instances;
-   it has a width and a height property that are equivalent to the
    first and the second number in the tuple, respectively;
-   the string returned by its __repr__ method is
    'imageop.ImageSize(width=%d, height=%d)' % (width, height).

ImageSize is not usually instantiated by end-users, but can be used when
creating a new class that implements the image protocol, since the size
attribute must be an ImageSize instance.

C API

The available image modes are visible at the C level as PyImage_*
constants of type PyObject * (e.g.: PyImage_RGB is imageop.RGB).

The following functions offer a C-friendly interface to mode and image
objects (all the functions return NULL or -1 on failure):

int PyImageMode_Check(PyObject *obj)

  Returns true if the object obj is a valid image mode.

int PyImageMode_GetComponents(PyObject *mode)
PyObject* PyImageMode_GetComponentNames(PyObject *mode)
int PyImageMode_GetBitsPerComponent(PyObject *mode)
int PyImageMode_GetBytesPerPixel(PyObject *mode)
int PyImageMode_GetPlanar(PyObject *mode)
PyObject* PyImageMode_GetSubsampling(PyObject *mode)
int PyImageMode_GetXDivisor(PyObject *mode)
int PyImageMode_GetYDivisor(PyObject *mode)
Py_ssize_t PyImageMode_GetLength(PyObject *mode, Py_ssize_t width,                                     Py_ssize_t height)

  These functions are equivalent to their corresponding Python
  attributes or methods.

int PyImage_Check(PyObject *obj)

  Returns true if the object obj is an Image object or an instance of a
  subtype of the Image type; see also PyObject_CheckImage below.

int PyImage_CheckExact(PyObject *obj)

  Returns true if the object obj is an Image object, but not an instance
  of a subtype of the Image type.

PyObject* PyImage_New(PyObject *mode, Py_ssize_t width,                          Py_ssize_t height)

  Returns a new Image instance, initialized to transparent black (see
  Image.__init__ above for the details).

PyObject* PyImage_FromImage(PyObject *image, PyObject *mode,                                Py_ssize_t width, Py_ssize_t height)

  Returns a new Image instance, initialized with the contents of the
  image object rescaled and converted to the specified mode, if
  necessary.

PyObject* PyImage_FromBuffer(PyObject *buffer, PyObject *mode,                                 Py_ssize_t width,                                 Py_ssize_t height)

  Returns a new Image instance, initialized with the contents of the
  buffer object.

int PyObject_CheckImage(PyObject *obj)

  Returns true if the object obj implements a sufficient subset of the
  image protocol to be accepted by the functions defined below, even if
  its class is not a subclass of ImageMixin and/or Image. Currently it
  simply checks for the existence and correctness of the attributes
  mode, size and buffer.

PyObject* PyImage_GetMode(PyObject *image)
Py_ssize_t PyImage_GetWidth(PyObject *image)
Py_ssize_t PyImage_GetHeight(PyObject *image)
int PyImage_Clip(PyObject *image)
PyObject* PyImage_Split(PyObject *image)
PyObject* PyImage_GetBuffer(PyObject *image)
int PyImage_AsBuffer(PyObject *image, const void **buffer,                         Py_ssize_t *buffer_len)

  These functions are equivalent to their corresponding Python
  attributes or methods; the image memory can be accessed only with the
  GIL and a reference to the image or its buffer held, and extra care
  should be taken for modes with more than 8 bits per component: the
  data is stored in native byte order and it can be not aligned on 2 or
  4 byte boundaries.

Examples

A few examples of common operations with the new Image class and
protocol:

    # create a new black RGB image of 6x9 pixels
    rgb_image = imageop.Image(imageop.RGB, (6, 9))

    # same as above, but initialize the image to bright red
    rgb_image = imageop.Image(imageop.RGB, (6, 9), color=(255, 0, 0))

    # convert the image to YCbCr
    yuv_image = imageop.Image(imageop.JPEG_YV12, source=rgb_image)

    # read the value of a pixel and split it into three ints
    r, g, b = rgb_image[x, y]

    # modify the magenta component of a pixel in a CMYK image
    cmyk_image[x, y].m = 13

    # modify the Y (luma) component of a pixel in a *YV12 image and
    # its corresponding subsampled Cr (red chroma)
    yuv_image.y[x, y] = 42
    yuv_image.cr[x // 2, y // 2] = 54

    # iterate over an image
    for line in rgb_image:
        for pixel in line:
            # swap red and blue, and set green to 0
            pixel.value = pixel.b, 0, pixel.r

    # find the maximum value of the red component in the image
    max_red = max(pixel.r for pixel in rgb_image.pixels())

    # count the number of colors in the image
    num_of_colors = len(set(tuple(pixel) for pixel in image.pixels()))

    # copy a block of 4x2 pixels near the upper right corner of an
    # image and paste it into the lower left corner of the same image
    image[:4, -2:] = image[-6:-2, 1:3]

    # create a copy of the image, except that the new image can have a
    # different (usually empty) info dict
    new_image = image[:]

    # create a mirrored copy of the image, with the left and right
    # sides flipped
    flipped_image = image[::-1, :]

    # downsample an image to half its original size using a fast, low
    # quality operation and a slower, high quality one:
    low_quality_image = image[::2, ::2]
    new_size = image.size.width // 2, image.size.height // 2
    high_quality_image = imageop.Image(size=new_size, source=image)

    # direct buffer access
    rgb_image[0, 0] = r, g, b
    assert tuple(rgb_image.buffer[:3]) == (r, g, b)

Backwards Compatibility

There are three areas touched by this PEP where backwards compatibility
should be considered:

-   Python 2.6: new classes and objects are added to the imageop module
    without touching the existing module contents; new methods and
    attributes will be added to Tkinter.PhotoImage and its __getitem__
    and __setitem__ methods will be modified to accept integers, tuples
    and slices (currently they only accept strings). All the changes
    provide a superset of the existing functionality, so no major
    compatibility issues are expected.
-   Python 3.0: the legacy contents of the imageop module will be
    deleted, according to PEP 3108; everything defined in this proposal
    will work like in Python 2.x with the exception of the usual 2.x/3.0
    differences (e.g. support for long integers and for interpreting str
    instances as sequences of bytes will be dropped).
-   external libraries: the names and the semantics of the standard
    image methods and attributes are carefully chosen to allow some
    external libraries that manipulate images (including at least PIL,
    wxPython and pygame) to implement the new protocol in their image
    classes without breaking compatibility with existing code. The only
    blatant conflicts between the image protocol and NumPy arrays are
    the value of the size attribute and the coordinates order in the
    image[x, y] expression.

Reference Implementation

If this PEP is accepted, the author will provide a reference
implementation of the new classes in pure Python (that can run in
CPython, PyPy, Jython and IronPython) and a second one optimized for
speed in Python and C, suitable for inclusion in the CPython standard
library. The author will also submit the required Tkinter patches. For
all the code will be available a version for Python 2.x and a version
for Python 3.0 (it is expected that the two version will be very similar
and the Python 3.0 one will probably be generated almost completely
automatically).

Acknowledgments

The implementation of this PEP, if accepted, is sponsored by Google
through the Google Summer of Code program.

Copyright

This document has been placed in the public domain.



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