
    :h[0                        d Z ddlmZ dg dg dgddg dg dgddg d	g d
gddg dg dgddg dg dgddg dg dgddg dg dgddg dg dgddg dg dgdd	Zy)u  
JPEG quality settings equivalent to the Photoshop settings.
Can be used when saving JPEG files.

The following presets are available by default:
``web_low``, ``web_medium``, ``web_high``, ``web_very_high``, ``web_maximum``,
``low``, ``medium``, ``high``, ``maximum``.
More presets can be added to the :py:data:`presets` dict if needed.

To apply the preset, specify::

  quality="preset_name"

To apply only the quantization table::

  qtables="preset_name"

To apply only the subsampling setting::

  subsampling="preset_name"

Example::

  im.save("image_name.jpg", quality="web_high")

Subsampling
-----------

Subsampling is the practice of encoding images by implementing less resolution
for chroma information than for luma information.
(ref.: https://en.wikipedia.org/wiki/Chroma_subsampling)

Possible subsampling values are 0, 1 and 2 that correspond to 4:4:4, 4:2:2 and
4:2:0.

You can get the subsampling of a JPEG with the
:func:`.JpegImagePlugin.get_sampling` function.

In JPEG compressed data a JPEG marker is used instead of an EXIF tag.
(ref.: https://exiv2.org/tags.html)


Quantization tables
-------------------

They are values use by the DCT (Discrete cosine transform) to remove
*unnecessary* information from the image (the lossy part of the compression).
(ref.: https://en.wikipedia.org/wiki/Quantization_matrix#Quantization_matrices,
https://en.wikipedia.org/wiki/JPEG#Quantization)

You can get the quantization tables of a JPEG with::

  im.quantization

This will return a dict with a number of lists. You can pass this dict
directly as the qtables argument when saving a JPEG.

The quantization table format in presets is a list with sublists. These formats
are interchangeable.

Libjpeg ref.:
https://web.archive.org/web/20120328125543/http://www.jpegcameras.com/libjpeg/libjpeg-3.html

    )annotations   )@         '   2   .   >   D   r         &   r   5   A   r   r   r      r   r   r   r   r   r   r   r   r   r   r   r   r   r	   r   r   r   r   r   r   r   r
   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   )@   r       r   6   r   r   r   r         r   r   r   r   r   r   r   r   +   B   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   )subsamplingquantization)@r      r   r   r      r      r      r      r   r   r   r   r   r      r   r      #   /   r   r    r   r   r"   %   r$   @   r   r   r   r"   r   3   r&   r&   r   r   r"   r%   r'   r&   r&   r&   r   r   r#   r$   r&   r&   r&   r&   r   r   r$   r&   r&   r&   r&   r&   )@   r    r(   r   r   r"   r   0   r       r   r(   r   r"   r#   r   r(   r   r      r"   r   r
   r   r   r(   r+   r   r   r   r   r&   r   r   r"   r   r   r)   r&   r&   r"   r"   r   r   r)   ?   r&   r&   r   r#   r
   r   r&   r&   r&   r&   r)   r   r   r&   r&   r&   r&   r&   )@      r.   r-   	   r   r   r   r.      r0   r-      
   r   r   r.   r0   r0   r-   r2   r      r*   r-   r-   r-   r   r   r    r*   r   r/   r1   r2   r   r   r   r   r   r   r2   r   r    r   r   r   r   r   r   r3   r*   r   r   r   r   r   r   r*   r   r   r   r   r   )@   r4   r!   r   r"   r   r   r   r4   r   r   r   r   r   r   r   r!   r   r(   r   r   r   r   r   r   r   r   r   r   r   r   r   r"   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   )@r   r   r   r      r.   r0   r-   r   r   r   r   r5   r.   r0   r-   r   r   r   r   r.   r0   r4   r/   r   r   r   r.   r0   r4   r/   r   r5   r5   r.   r0   r1   r2   r   r   r.   r.   r0   r4   r2   r   r   r   r0   r0   r4   r/   r   r   r   r   r-   r-   r/   r   r   r   r   r   )@r5   r5   r0   r/   r!   r    r    r    r5   r.   r-   r   r3   r   r   r   r0   r-   r/   r3   r   r   r   r   r/   r   r3   r   r   r   r   r   r!   r3   r   r   r   r   r   r   r    r   r   r   r   r   r   r   r    r   r   r   r   r   r   r   r    r   r   r   r   r   r   r   )@   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r6   r   r6   r6   r6   r6   r6   r6   r   r   r6   r6   r6   r6   r6   r   r   r5   r6   r6   r6   r6   r   r   r5   r5   r6   r6   r6   r   r   r5   r5   r5   r6   r6   r   r   r5   r5   r5   r5   )@r6   r6   r6   r   r   r5   r5   r5   r6   r6   r6   r   r5   r5   r5   r5   r6   r6   r6   r5   r5   r5   r5   r5   r   r   r5   r5   r5   r5   r5   r5   r   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   r5   )@r   r3   r3   r   r   r#   "   r(   r3   r   r   r*   r"   r   r   r   r3   r   r(   r   r   r   r   r   r   r*   r   r   r   r   r   r   r   r"   r   r   r   r   r   r   r#   r   r   r   r   r   r   r   r7   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   )@r   r*   r+   r   r   r   r(   r(   r*   r   r   r3   r3   r   r   r   r+   r   r3   r3   r   r   r   r   r   r3   r3   r   r   r   r   r   r   r3   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   )@r   r1   r1   r   r(   r   r   r(   r1   r/   r/   r   r    r*   r   r   r1   r/   r2   r   r*   r   r   r   r   r   r   r   r   r   r   r   r(   r    r*   r   r   r   r   r   r   r*   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   )@r!   r   r!   r   r   r   r(   r(   r   r3   r3   r3   r3   r   r   r   r!   r3   r3   r3   r   r   r   r   r   r3   r3   r   r   r   r   r   r   r3   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   )@r-   r.   r.   r-   r/   r   r   r   r.   r0   r0   r-   r1   r2   r   r   r.   r0   r0   r-   r2   r   r   r   r-   r-   r-   r   r   r   r   r   r/   r1   r2   r   r   r   r   r   r   r2   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   )@r4   r4   r!   r   r   r   r(   r(   r4   r   r   r3   r3   r   r   r   r!   r   r3   r3   r   r   r   r   r   r3   r3   r   r   r   r   r   r   r3   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   r(   r   r   r   r   r   r   r   )@r5   r5   r0   r/   r!   r    r    r    r5   r.   r-   r2   r3   r   r   r   r0   r-   r/   r3   r   r   r   r   r/   r2   r3   r   r   r   r   r   r!   r3   r   r   r   r   r   r   r    r   r   r   r   r   r   r   r    r   r   r   r   r   r   r   r    r   r   r   r   r   r   r   )	web_low
web_mediumweb_highweb_very_highweb_maximumlowmediumhighmaximumN)__doc__
__future__r   presets     M/var/www/urcfiles/bundle/venv/lib/python3.12/site-packages/PIL/JpegPresets.py<module>rG      s  ?B # ./ @ @. !& ./ @ @. & ./ @ @. & /0 @ @/ !& ./!@!@. & ./ @ @. & ./ @ @. & ./ @ @. & ./ @ @. slrE   