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https://github.com/python-pillow/Pillow.git
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83ff0b3b31
In py3k, imports are absolute unless using the "from . import" syntax. This commit also solves a recursive import between Image, ImageColor, and ImagePalette by delay-importing ImagePalette in Image. I'm not too keen on this commit because the syntax is ugly. I might go back and prefer the prettier "from PIL import".
303 lines
7.2 KiB
Python
303 lines
7.2 KiB
Python
#
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# The Python Imaging Library.
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# $Id$
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#
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# standard channel operations
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#
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# History:
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# 1996-03-24 fl Created
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# 1996-08-13 fl Added logical operations (for "1" images)
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# 2000-10-12 fl Added offset method (from Image.py)
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#
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# Copyright (c) 1997-2000 by Secret Labs AB
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# Copyright (c) 1996-2000 by Fredrik Lundh
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#
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# See the README file for information on usage and redistribution.
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#
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from . import Image
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##
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# The <b>ImageChops</b> module contains a number of arithmetical image
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# operations, called <i>channel operations</i> ("chops"). These can be
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# used for various purposes, including special effects, image
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# compositions, algorithmic painting, and more.
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# <p>
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# At this time, channel operations are only implemented for 8-bit
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# images (e.g. "L" and "RGB").
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# <p>
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# Most channel operations take one or two image arguments and returns
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# a new image. Unless otherwise noted, the result of a channel
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# operation is always clipped to the range 0 to MAX (which is 255 for
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# all modes supported by the operations in this module).
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##
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##
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# Return an image with the same size as the given image, but filled
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# with the given pixel value.
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#
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# @param image Reference image.
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# @param value Pixel value.
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# @return An image object.
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def constant(image, value):
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"Fill a channel with a given grey level"
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return Image.new("L", image.size, value)
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##
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# Copy image.
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#
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# @param image Source image.
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# @return A copy of the source image.
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def duplicate(image):
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"Create a copy of a channel"
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return image.copy()
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##
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# Inverts an image
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# (MAX - image).
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#
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# @param image Source image.
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# @return An image object.
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def invert(image):
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"Invert a channel"
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image.load()
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return image._new(image.im.chop_invert())
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##
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# Compare images, and return lighter pixel value
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# (max(image1, image2)).
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# <p>
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# Compares the two images, pixel by pixel, and returns a new image
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# containing the lighter values.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def lighter(image1, image2):
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"Select the lighter pixels from each image"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_lighter(image2.im))
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##
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# Compare images, and return darker pixel value
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# (min(image1, image2)).
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# <p>
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# Compares the two images, pixel by pixel, and returns a new image
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# containing the darker values.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def darker(image1, image2):
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"Select the darker pixels from each image"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_darker(image2.im))
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##
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# Calculate absolute difference
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# (abs(image1 - image2)).
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# <p>
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# Returns the absolute value of the difference between the two images.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def difference(image1, image2):
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"Subtract one image from another"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_difference(image2.im))
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##
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# Superimpose positive images
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# (image1 * image2 / MAX).
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# <p>
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# Superimposes two images on top of each other. If you multiply an
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# image with a solid black image, the result is black. If you multiply
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# with a solid white image, the image is unaffected.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def multiply(image1, image2):
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"Superimpose two positive images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_multiply(image2.im))
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##
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# Superimpose negative images
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# (MAX - ((MAX - image1) * (MAX - image2) / MAX)).
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# <p>
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# Superimposes two inverted images on top of each other.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def screen(image1, image2):
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"Superimpose two negative images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_screen(image2.im))
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##
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# Add images
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# ((image1 + image2) / scale + offset).
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# <p>
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# Adds two images, dividing the result by scale and adding the
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# offset. If omitted, scale defaults to 1.0, and offset to 0.0.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def add(image1, image2, scale=1.0, offset=0):
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"Add two images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_add(image2.im, scale, offset))
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##
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# Subtract images
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# ((image1 - image2) / scale + offset).
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# <p>
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# Subtracts two images, dividing the result by scale and adding the
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# offset. If omitted, scale defaults to 1.0, and offset to 0.0.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def subtract(image1, image2, scale=1.0, offset=0):
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"Subtract two images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_subtract(image2.im, scale, offset))
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##
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# Add images without clipping
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# ((image1 + image2) % MAX).
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# <p>
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# Adds two images, without clipping the result.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def add_modulo(image1, image2):
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"Add two images without clipping"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_add_modulo(image2.im))
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##
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# Subtract images without clipping
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# ((image1 - image2) % MAX).
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# <p>
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# Subtracts two images, without clipping the result.
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#
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# @param image1 First image.
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# @param image1 Second image.
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# @return An image object.
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def subtract_modulo(image1, image2):
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"Subtract two images without clipping"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_subtract_modulo(image2.im))
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##
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# Logical AND
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# (image1 and image2).
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def logical_and(image1, image2):
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"Logical and between two images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_and(image2.im))
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##
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# Logical OR
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# (image1 or image2).
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def logical_or(image1, image2):
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"Logical or between two images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_or(image2.im))
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##
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# Logical XOR
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# (image1 xor image2).
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def logical_xor(image1, image2):
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"Logical xor between two images"
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image1.load()
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image2.load()
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return image1._new(image1.im.chop_xor(image2.im))
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##
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# Blend images using constant transparency weight.
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# <p>
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# Same as the <b>blend</b> function in the <b>Image</b> module.
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def blend(image1, image2, alpha):
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"Blend two images using a constant transparency weight"
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return Image.blend(image1, image2, alpha)
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##
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# Create composite using transparency mask.
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# <p>
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# Same as the <b>composite</b> function in the <b>Image</b> module.
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def composite(image1, image2, mask):
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"Create composite image by blending images using a transparency mask"
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return Image.composite(image1, image2, mask)
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##
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# Offset image data.
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# <p>
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# Returns a copy of the image where data has been offset by the given
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# distances. Data wraps around the edges. If yoffset is omitted, it
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# is assumed to be equal to xoffset.
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#
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# @param image Source image.
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# @param xoffset The horizontal distance.
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# @param yoffset The vertical distance. If omitted, both
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# distances are set to the same value.
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# @return An Image object.
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def offset(image, xoffset, yoffset=None):
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"Offset image in horizontal and/or vertical direction"
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if yoffset is None:
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yoffset = xoffset
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image.load()
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return image._new(image.im.offset(xoffset, yoffset))
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