Pillow/docs/reference/ImageMath.rst

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.. py:module:: PIL.ImageMath
.. py:currentmodule:: PIL.ImageMath
:py:mod:`ImageMath` Module
==========================
The :py:mod:`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 :py:mod:`~PIL.ImageMath` module
--------------------------------------------------
.. code-block:: python
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")
.. py:function:: eval(expression, environment)
Evaluate expression in the given environment.
In the current version, :py:mod:`~PIL.ImageMath` only supports
single-layer images. To process multi-band images, use the
:py:meth:`~PIL.Image.Image.split` method or :py:func:`~PIL.Image.merge`
function.
:param expression: A string which uses the standard Python expression
syntax. In addition to the standard operators, you can
also use the functions described below.
:param 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.
:return: 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 theyre 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 :py:func:`~PIL.ImageMath.convert`,
:py:func:`~PIL.ImageMath.float`, and :py:func:`~PIL.ImageMath.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 youll get negative values if
you invert an ordinary greyscale image. You can use the and (&) operator to
mask off unwanted bits.
Bitwise operators dont 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.
.. py:currentmodule:: None
.. py:function:: abs(image)
Absolute value.
.. py:function:: convert(image, mode)
Convert image to the given mode. The mode must be given as a string
constant.
.. py:function:: float(image)
Convert image to 32-bit floating point. This is equivalent to
convert(image, “F”).
.. py:function:: 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.
.. py:function:: max(image1, image2)
Maximum value.
.. py:function:: min(image1, image2)
Minimum value.