o svXj[@sddlmZddZddZddZdd Zd d Zd d ZddZddZ ddZ ddZ ddZ d/ddZ d/ddZddZd d!Zd"d#Zd$d%Zd&d'Zd(d)Zd*d+Zd0d-d.Zd,S)1)ImagecCstd|j|S)zVFill a channel with a given grey level. :rtype: :py:class:`~PIL.Image.Image` L)rnewsize)imagevaluerK/var/www/html/myproject/venv/lib/python3.10/site-packages/PIL/ImageChops.pyconstantsr cCs|S)ziCopy a channel. Alias for :py:meth:`PIL.Image.Image.copy`. :rtype: :py:class:`~PIL.Image.Image` )copyrrrr duplicatesr cCs|||jS)zl Invert an image (channel). :: out = MAX - image :rtype: :py:class:`~PIL.Image.Image` )load_newim chop_invertr rrr invert's rcC$||||j|jS)z Compares the two images, pixel by pixel, and returns a new image containing the lighter values. :: out = max(image1, image2) :rtype: :py:class:`~PIL.Image.Image` )rrr chop_lighterimage1image2rrr lighter4 rcCr)z Compares the two images, pixel by pixel, and returns a new image containing the darker values. :: out = min(image1, image2) :rtype: :py:class:`~PIL.Image.Image` )rrr chop_darkerrrrr darkerCrrcCr)z Returns the absolute value of the pixel-by-pixel difference between the two images. :: out = abs(image1 - image2) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_differencerrrr differenceRrrcCr)a 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. :: out = image1 * image2 / MAX :rtype: :py:class:`~PIL.Image.Image` )rrr chop_multiplyrrrr multiplyas rcCr)z Superimposes two inverted images on top of each other. :: out = MAX - ((MAX - image1) * (MAX - image2) / MAX) :rtype: :py:class:`~PIL.Image.Image` )rrr chop_screenrrrr screenrs r!cCr)z Superimposes two images on top of each other using the Soft Light algorithm :rtype: :py:class:`~PIL.Image.Image` )rrrchop_soft_lightrrrr soft_lightr#cCr)z Superimposes two images on top of each other using the Hard Light algorithm :rtype: :py:class:`~PIL.Image.Image` )rrrchop_hard_lightrrrr hard_lightr$r&cCr)z| Superimposes two images on top of each other using the Overlay algorithm :rtype: :py:class:`~PIL.Image.Image` )rrr chop_overlayrrrr overlayr$r(?cC(||||j|j||S)z Adds two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0. :: out = ((image1 + image2) / scale + offset) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_addrrscaleoffsetrrr add r0cCr+)z Subtracts two images, dividing the result by scale and adding the offset. If omitted, scale defaults to 1.0, and offset to 0.0. :: out = ((image1 - image2) / scale + offset) :rtype: :py:class:`~PIL.Image.Image` )rrr chop_subtractr-rrr subtractr1r3cCr)zAdd two images, without clipping the result. :: out = ((image1 + image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_add_modulorrrr add_modulor5cCr)zSubtract two images, without clipping the result. :: out = ((image1 - image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_subtract_modulorrrr subtract_modulor6r8cCr)ajLogical 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. :: out = ((image1 and image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_andrrrr logical_ands r:cCr)zLogical OR between two images. Both of the images must have mode "1". :: out = ((image1 or image2) % MAX) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_orrrrr logical_orrr<cCr)zLogical XOR between two images. Both of the images must have mode "1". :: out = ((bool(image1) != bool(image2)) % MAX) :rtype: :py:class:`~PIL.Image.Image` )rrrchop_xorrrrr logical_xorrr>cCt|||S)zBlend images using constant transparency weight. Alias for :py:func:`PIL.Image.blend`. :rtype: :py:class:`~PIL.Image.Image` )rblend)rralpharrr r@ r@cCr?)zCreate composite using transparency mask. Alias for :py:func:`PIL.Image.composite`. :rtype: :py:class:`~PIL.Image.Image` )r composite)rrmaskrrr rCrBrCNcCs(|dur|}|||j||S)aReturns 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 image: Input image. :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` N)rrrr/)rxoffsetyoffsetrrr r/ s r/)r)r*)N)rr r rrrrrr!r#r&r(r0r3r5r8r:r<r>r@rCr/rrrr s,