67 lines
7.4 KiB
Plaintext
67 lines
7.4 KiB
Plaintext
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ß¼jw ã óH — d dl mZ d dlZd dlmZ ddlmZ G d„ d« ZeZy)é )Ú annotationsN)Úcached_propertyé )ÚImagec óÄ — e Zd Z d d
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d„Zedd„« Zedd„« Zedd„« Zedd„« Zedd„« Z edd„« Z
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edd „« Z edd
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„« Z edd „« Z
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y)ÚStatNc ó — t |t j « r|j |« | _ n%t |t « r|| _ n
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d}t |« ‚t t
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t | j « dz « « | _ y)a
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Calculate statistics for the given image. If a mask is included,
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only the regions covered by that mask are included in the
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statistics. You can also pass in a previously calculated histogram.
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:param image: A PIL image, or a precalculated histogram.
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.. note::
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For a PIL image, calculations rely on the
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:py:meth:`~PIL.Image.Image.histogram` method. The pixel counts are
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grouped into 256 bins, even if the image has more than 8 bits per
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channel. So ``I`` and ``F`` mode images have a maximum ``mean``,
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``median`` and ``rms`` of 255, and cannot have an ``extrema`` maximum
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of more than 255.
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:param mask: An optional mask.
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z$first argument must be image or listé N) Ú
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isinstancer Ú histogramÚhÚlistÚ TypeErrorÚrangeÚlenÚbands)ÚselfÚ
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image_or_listÚmaskÚmsgs úP/home/antigravity/intellecton/venv/lib/python3.12/site-packages/PIL/ImageStat.pyÚ__init__z
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Stat.__init__ sb € ô* �m¤U§[¡[Ô 1Ø"×,Ñ,¨TÓ2ˆD�FÜ
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˜
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¤tÔ
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,Ø"ˆD�Fà8ˆCܘC“.Ð Üœ%¤ D§F¡F£ ¨sÑ 2Ó3Ó4ˆ�
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ó c ó– — dd„}t dt | j « d« D �cg c] } || j |d « ‘Œ c}S c c}w )au
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Min/max values for each band in the image.
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.. note::
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This relies on the :py:meth:`~PIL.Image.Image.histogram` method, and
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simply returns the low and high bins used. This is correct for
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images with 8 bits per channel, but fails for other modes such as
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``I`` or ``F``. Instead, use :py:meth:`~PIL.Image.Image.getextrema` to
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return per-band extrema for the image. This is more correct and
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efficient because, for non-8-bit modes, the histogram method uses
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:py:meth:`~PIL.Image.Image.getextrema` to determine the bins used.
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c ó‚ — d\ }}t d« D ] }| | sŒ |} n t ddd« D ] }| | sŒ |} ||fS ||fS )N)éÿ r r
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r éÿÿÿÿ)r )r Úres_minÚres_maxÚis r Úminmaxz Stat.extrema.<locals>.minmaxM so € Ø %Ñ ˆG�Wܘ3“Zò
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�Ø ˜Q“<Ø �GÙð
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ô ˜3 BÓ'ò
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�Ø ˜Q“<Ø �GØؘGÐ#Ð #ð
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ð ˜GÐ#Ð #r r r
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N)r ú list[int]Úreturnztuple[int, int])r r r
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)r r! r s r Úextremaz Stat.extrema> s= € ó
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$ô -2°!´S¸¿¹³[À#Ó,FÖG q‘�t—v‘v˜a˜b�zÕ"ÒGÐGùÒGs § Ac óš — t dt | j « d« D �cg c] }t | j ||dz « ‘Œ c}S c c}w )z2Total number of pixels for each band in the image.r r
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)r r r
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Úsum©r r s r Úcountz
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Stat.count[ s= € ô 38¸¼3¸t¿v¹v»;ÈÓ2LÖM¨Q”�D—F‘F˜1˜q 3™wÐ'Õ(ÒMÐMùÒMs £"Ac óÊ — g }t dt | j « d« D ]= }d}t d« D ] }||| j ||z z z
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}Œ |j |« Œ? |S )z-Sum of all pixels for each band in the image.r r
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ç )r r r
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Úappend)r Úvr Ú layer_sumÚjs r r& zStat.sum` so € ð
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ˆÜ�qœ#˜dŸf™f›+ sÓ+ò ˆA؈Iܘ3“Zò
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/�ؘQ §¡¨¨A©¡ Ñ .Ñ.‘ ð
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/à
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�H‰H�YÕ ð ð
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ˆr c óâ — g }t dt | j « d« D ]I }d}t d« D ]& }||dz t | j ||z « z z
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}Œ( |j |« ŒK |S )z5Squared sum of all pixels for each band in the image.r r
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r* é )r r r
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Úfloatr+ )r r, r Úsum2r. s r r2 z Stat.sum2l sw € ð
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ˆÜ�qœ#˜dŸf™f›+ sÓ+ò ˆA؈Dܘ3“Zò
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