Source code for PIL.ImageChops

#
# The Python Imaging Library.
# $Id$
#
# standard channel operations
#
# History:
# 1996-03-24 fl   Created
# 1996-08-13 fl   Added logical operations (for "1" images)
# 2000-10-12 fl   Added offset method (from Image.py)
#
# Copyright (c) 1997-2000 by Secret Labs AB
# Copyright (c) 1996-2000 by Fredrik Lundh
#
# See the README file for information on usage and redistribution.
#

from . import Image


[docs]def constant(image, value): """Fill a channel with a given grey level. :rtype: :py:class:`~PIL.Image.Image` """ return Image.new("L", image.size, value)
[docs]def duplicate(image): """Copy a channel. Alias for :py:meth:`PIL.Image.Image.copy`. :rtype: :py:class:`~PIL.Image.Image` """ return image.copy()
[docs]def invert(image): """ Invert an image (channel). .. code-block:: python out = MAX - image :rtype: :py:class:`~PIL.Image.Image` """ image.load() return image._new(image.im.chop_invert())
[docs]def lighter(image1, image2): """ Compares the two images, pixel by pixel, and returns a new image containing the lighter values. .. code-block:: python out = max(image1, image2) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_lighter(image2.im))
[docs]def darker(image1, image2): """ Compares the two images, pixel by pixel, and returns a new image containing the darker values. .. code-block:: python out = min(image1, image2) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_darker(image2.im))
[docs]def difference(image1, image2): """ Returns the absolute value of the pixel-by-pixel difference between the two images. .. code-block:: python out = abs(image1 - image2) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_difference(image2.im))
[docs]def 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. .. code-block:: python out = image1 * image2 / MAX :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_multiply(image2.im))
[docs]def screen(image1, image2): """ Superimposes two inverted images on top of each other. .. code-block:: python out = MAX - ((MAX - image1) * (MAX - image2) / MAX) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_screen(image2.im))
[docs]def soft_light(image1, image2): """ Superimposes two images on top of each other using the Soft Light algorithm :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_soft_light(image2.im))
[docs]def hard_light(image1, image2): """ Superimposes two images on top of each other using the Hard Light algorithm :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_hard_light(image2.im))
[docs]def overlay(image1, image2): """ Superimposes two images on top of each other using the Overlay algorithm :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_overlay(image2.im))
[docs]def 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. .. code-block:: python out = ((image1 + image2) / scale + offset) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_add(image2.im, scale, offset))
[docs]def 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. .. code-block:: python out = ((image1 - image2) / scale + offset) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_subtract(image2.im, scale, offset))
[docs]def add_modulo(image1, image2): """Add two images, without clipping the result. .. code-block:: python out = ((image1 + image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_add_modulo(image2.im))
[docs]def subtract_modulo(image1, image2): """Subtract two images, without clipping the result. .. code-block:: python out = ((image1 - image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_subtract_modulo(image2.im))
[docs]def logical_and(image1, image2): """Logical AND between two images. Both of the images must have mode "1". If you would like to perform a logical AND on an image with a mode other than "1", try :py:meth:`~PIL.ImageChops.multiply` instead, using a black-and-white mask as the second image. .. code-block:: python out = ((image1 and image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_and(image2.im))
[docs]def logical_or(image1, image2): """Logical OR between two images. Both of the images must have mode "1". .. code-block:: python out = ((image1 or image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_or(image2.im))
[docs]def logical_xor(image1, image2): """Logical XOR between two images. Both of the images must have mode "1". .. code-block:: python out = ((bool(image1) != bool(image2)) % MAX) :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_xor(image2.im))
[docs]def blend(image1, image2, alpha): """Blend images using constant transparency weight. Alias for :py:func:`PIL.Image.blend`. :rtype: :py:class:`~PIL.Image.Image` """ return Image.blend(image1, image2, alpha)
[docs]def composite(image1, image2, mask): """Create composite using transparency mask. Alias for :py:func:`PIL.Image.composite`. :rtype: :py:class:`~PIL.Image.Image` """ return Image.composite(image1, image2, mask)
[docs]def 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``. :param xoffset: The horizontal distance. :param yoffset: The vertical distance. If omitted, both distances are set to the same value. :rtype: :py:class:`~PIL.Image.Image` """ if yoffset is None: yoffset = xoffset image.load() return image._new(image.im.offset(xoffset, yoffset))