
    h
                    2   S SK Jr  SSKJr  SS jrSS jrSS jrSS jrSS jrSS	 jr	SS
 jr
SS jrSS jrSS jrSS jr S         SS jjr S         SS jjrSS jrSS jrSS jrSS jrSS jrSS jr        S S jrS!S"S jjrg)#    )annotations   )Imagec                F    [         R                  " SU R                  U5      $ )zNFill a channel with a given gray level.

:rtype: :py:class:`~PIL.Image.Image`
L)r   newsize)imagevalues     @/var/www/html/env/lib/python3.13/site-packages/PIL/ImageChops.pyconstantr      s     99S%**e,,    c                "    U R                  5       $ )zaCopy a channel. Alias for :py:meth:`PIL.Image.Image.copy`.

:rtype: :py:class:`~PIL.Image.Image`
)copyr
   s    r   	duplicater       s     ::<r   c                t    U R                  5         U R                  U R                  R                  5       5      $ )z\
Invert an image (channel). ::

    out = MAX - image

:rtype: :py:class:`~PIL.Image.Image`
)load_newimchop_invertr   s    r   invertr   )   s)     
JJL::ehh**,--r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )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`
)r   r   r   chop_lighterimage1image2s     r   lighterr   6   s8     KKM
KKM;;vyy--fii899r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )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`
)r   r   r   chop_darkerr   s     r   darkerr!   E   s8     KKM
KKM;;vyy,,VYY788r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )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`
)r   r   r   chop_differencer   s     r   
differencer$   T   s8     KKM
KKM;;vyy00;<<r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )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`
)r   r   r   chop_multiplyr   s     r   multiplyr'   c   s8     KKM
KKM;;vyy..vyy9::r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )z
Superimposes two inverted images on top of each other. ::

    out = MAX - ((MAX - image1) * (MAX - image2) / MAX)

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_screenr   s     r   screenr*   t   s8     KKM
KKM;;vyy,,VYY788r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )zs
Superimposes two images on top of each other using the Soft Light algorithm

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_soft_lightr   s     r   
soft_lightr-      8     KKM
KKM;;vyy00;<<r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )zs
Superimposes two images on top of each other using the Hard Light algorithm

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_hard_lightr   s     r   
hard_lightr1      r.   r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )zp
Superimposes two images on top of each other using the Overlay algorithm

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_overlayr   s     r   overlayr4      s8     KKM
KKM;;vyy--fii899r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  X#5      5      $ )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`
)r   r   r   chop_addr   r   scaleoffsets       r   addr:      s:     KKM
KKM;;vyy))&))UCDDr   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  X#5      5      $ )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`
)r   r   r   chop_subtractr7   s       r   subtractr=      s:     KKM
KKM;;vyy..vyy%HIIr   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )z{Add two images, without clipping the result. ::

    out = ((image1 + image2) % MAX)

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_add_modulor   s     r   
add_modulor@      s8     KKM
KKM;;vyy00;<<r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )zSubtract two images, without clipping the result. ::

    out = ((image1 - image2) % MAX)

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_subtract_modulor   s     r   subtract_modulorC      s8     KKM
KKM;;vyy55fii@AAr   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )aN  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. ::

    out = ((image1 and image2) % MAX)

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_andr   s     r   logical_andrF      s8     KKM
KKM;;vyy))&))455r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )zLogical OR between two images.

Both of the images must have mode "1". ::

    out = ((image1 or image2) % MAX)

:rtype: :py:class:`~PIL.Image.Image`
)r   r   r   chop_orr   s     r   
logical_orrI      s8     KKM
KKM;;vyy((344r   c                    U R                  5         UR                  5         U R                  U R                  R                  UR                  5      5      $ )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`
)r   r   r   chop_xorr   s     r   logical_xorrL     s8     KKM
KKM;;vyy))&))455r   c                0    [         R                  " XU5      $ )z}Blend images using constant transparency weight. Alias for
:py:func:`PIL.Image.blend`.

:rtype: :py:class:`~PIL.Image.Image`
)r   blend)r   r   alphas      r   rN   rN     s     ;;vu--r   c                0    [         R                  " XU5      $ )zzCreate composite using transparency mask. Alias for
:py:func:`PIL.Image.composite`.

:rtype: :py:class:`~PIL.Image.Image`
)r   	composite)r   r   masks      r   rQ   rQ     s     ??6400r   Nc                    Uc  UnU R                  5         U R                  U R                  R                  X5      5      $ )a}  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 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`
)r   r   r   r9   )r
   xoffsetyoffsets      r   r9   r9   (  s3     	JJL::ehhoog788r   )r
   Image.Imager   intreturnrV   )r
   rV   rX   rV   )r   rV   r   rV   rX   rV   )g      ?r   )
r   rV   r   rV   r8   floatr9   rY   rX   rV   )r   rV   r   rV   rO   rY   rX   rV   )r   rV   r   rV   rR   rV   rX   rV   )N)r
   rV   rT   rW   rU   z
int | NonerX   rV   )
__future__r    r   r   r   r   r   r!   r$   r'   r*   r-   r1   r4   r:   r=   r@   rC   rF   rI   rL   rN   rQ   r9    r   r   <module>r]      s  $ # -
.:9=;"9	=	=	: STEE!,E5:EJOEE$ STJJ!,J5:JJOJJ"
=
B6$56.	1	1!,	14?	1	19r   