bo-graduation/venv/lib/python3.7/site-packages/PIL/ImageChops.py

#
# 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. At least one of the images must have mode "1".

    .. 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. At least one of the images must have mode "1".

    .. 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. At least one of the images must have mode "1".

    .. 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. At least
    one of the images must have mode "1".

    .. 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. At least one of the
    images must have mode "1".

    .. 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.
    At least one of the images must have mode "1".

    .. 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. At least one of the
    images must have mode "1".

    .. 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. At least one of the images
    must have mode "1".

    .. 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. At least one of the
    images must have mode "1".

    .. 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. At least one of the images must have
    mode "1".

    .. 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. At least one 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. At least one 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:meth:`PIL.Image.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:meth:`PIL.Image.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))