329 lines
7.1 KiB
Python
329 lines
7.1 KiB
Python
|
#
|
||
|
# 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
|
||
|
|
||
|
|
||
|
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)
|
||
|
|
||
|
|
||
|
def duplicate(image):
|
||
|
"""Copy a channel. Alias for :py:meth:`PIL.Image.Image.copy`.
|
||
|
|
||
|
:rtype: :py:class:`~PIL.Image.Image`
|
||
|
"""
|
||
|
|
||
|
return image.copy()
|
||
|
|
||
|
|
||
|
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())
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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))
|
||
|
|
||
|
|
||
|
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)
|
||
|
|
||
|
|
||
|
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)
|
||
|
|
||
|
|
||
|
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))
|