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133 lines
4.1 KiB
ReStructuredText
133 lines
4.1 KiB
ReStructuredText
.. py:module:: PIL.ImageMath
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.. py:currentmodule:: PIL.ImageMath
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:py:mod:`~PIL.ImageMath` Module
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===============================
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The :py:mod:`~PIL.ImageMath` module can be used to evaluate “image expressions”. The
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module provides a single :py:meth:`~PIL.ImageMath.eval` function, which takes
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an expression string and one or more images.
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Example: Using the :py:mod:`~PIL.ImageMath` module
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--------------------------------------------------
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.. code-block:: python
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from PIL import Image, ImageMath
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im1 = Image.open("image1.jpg")
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im2 = Image.open("image2.jpg")
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out = ImageMath.eval("convert(min(a, b), 'L')", a=im1, b=im2)
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out.save("result.png")
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.. py:function:: eval(expression, environment)
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Evaluate expression in the given environment.
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In the current version, :py:mod:`~PIL.ImageMath` only supports
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single-layer images. To process multi-band images, use the
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:py:meth:`~PIL.Image.Image.split` method or :py:func:`~PIL.Image.merge`
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function.
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:param expression: A string which uses the standard Python expression
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syntax. In addition to the standard operators, you can
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also use the functions described below.
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:param environment: A dictionary that maps image names to Image instances.
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You can use one or more keyword arguments instead of a
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dictionary, as shown in the above example. Note that
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the names must be valid Python identifiers.
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:return: An image, an integer value, a floating point value,
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or a pixel tuple, depending on the expression.
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Expression syntax
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-----------------
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Expressions are standard Python expressions, but they’re evaluated in a
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non-standard environment. You can use PIL methods as usual, plus the following
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set of operators and functions:
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Standard Operators
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^^^^^^^^^^^^^^^^^^
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You can use standard arithmetical operators for addition (+), subtraction (-),
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multiplication (*), and division (/).
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The module also supports unary minus (-), modulo (%), and power (**) operators.
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Note that all operations are done with 32-bit integers or 32-bit floating
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point values, as necessary. For example, if you add two 8-bit images, the
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result will be a 32-bit integer image. If you add a floating point constant to
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an 8-bit image, the result will be a 32-bit floating point image.
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You can force conversion using the ``convert()``, ``float()``, and ``int()``
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functions described below.
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Bitwise Operators
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^^^^^^^^^^^^^^^^^
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The module also provides operations that operate on individual bits. This
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includes and (&), or (|), and exclusive or (^). You can also invert (~) all
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pixel bits.
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Note that the operands are converted to 32-bit signed integers before the
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bitwise operation is applied. This means that you’ll get negative values if
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you invert an ordinary greyscale image. You can use the and (&) operator to
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mask off unwanted bits.
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Bitwise operators don’t work on floating point images.
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Logical Operators
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^^^^^^^^^^^^^^^^^
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Logical operators like ``and``, ``or``, and ``not`` work
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on entire images, rather than individual pixels.
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An empty image (all pixels zero) is treated as false. All other images are
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treated as true.
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Note that ``and`` and ``or`` return the last evaluated operand,
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while not always returns a boolean value.
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Built-in Functions
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^^^^^^^^^^^^^^^^^^
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These functions are applied to each individual pixel.
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.. py:currentmodule:: None
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.. py:function:: abs(image)
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:noindex:
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Absolute value.
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.. py:function:: convert(image, mode)
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:noindex:
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Convert image to the given mode. The mode must be given as a string
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constant.
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.. py:function:: float(image)
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:noindex:
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Convert image to 32-bit floating point. This is equivalent to
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convert(image, “F”).
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.. py:function:: int(image)
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:noindex:
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Convert image to 32-bit integer. This is equivalent to convert(image, “I”).
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Note that 1-bit and 8-bit images are automatically converted to 32-bit
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integers if necessary to get a correct result.
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.. py:function:: max(image1, image2)
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:noindex:
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Maximum value.
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.. py:function:: min(image1, image2)
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:noindex:
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Minimum value.
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