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Resize performance
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homm 2014-11-30 20:31:33 +03:00
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docs/releasenotes/2.7.rst
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@ -47,8 +47,8 @@ and is an alias for :py:attr:`~PIL.Image.LANCZOS`.
Lanczos upscaling quality
^^^^^^^^^^^^^^^^^^^^^^^^^
Image upscaling quality with :py:attr:`PIL.Image.LANCZOS` filter was almost
the same as :py:attr:`PIL.Image.BILINEAR` due to bug. This was fixed.
Image upscaling quality with :py:attr:`~PIL.Image.LANCZOS` filter was almost
the same as :py:attr:`~PIL.Image.BILINEAR` due to bug. This was fixed.
Bicubic upscaling quality
^^^^^^^^^^^^^^^^^^^^^^^^^
@ -60,6 +60,21 @@ more soft.
Resize performance
^^^^^^^^^^^^^^^^^^
In most cases convolution is more expensive algorithm for downscaling because
it tekes in account all pixels of source image. Therefore
:py:attr:`~PIL.Image.BILINEAR` and :py:attr:`~PIL.Image.BICUBIC` filters
performance can be lower than before. On the other hand quality of
:py:attr:`~PIL.Image.BILINEAR` and :py:attr:`~PIL.Image.BICUBIC` was close to
:py:attr:`~PIL.Image.NEAREST`. So if such quality is suitable for your task
you can switch to :py:attr:`~PIL.Image.NEAREST` filter for downscaling,
that will give huge win in performance.
At the same time performance of convolution resampling for downscaling was
improved in about two times compared to previous version.
Upscaling performance of :py:attr:`~PIL.Image.LANCZOS` filter remained the same.
For :py:attr:`~PIL.Image.BILINEAR` filter it grew in 1.5 times and
for :py:attr:`~PIL.Image.BICUBIC` in 4 times.
Default filter for thumbnails
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@ -67,7 +82,7 @@ In Pillow 2.5 default filter for :py:meth:`~PIL.Image.Image.thumbnail` was
changed from :py:attr:`~PIL.Image.NEAREST` to :py:attr:`~PIL.Image.ANTIALIAS`.
Antialias was chosen because all other filters gave poor quality for reduction.
Starting from Pillow 2.7 :py:attr:`~PIL.Image.ANTIALIAS` replaced with
:py:attr:`~PIL.Image.BICUBIC`, because bicubic is faster and
:py:attr:`~PIL.Image.BICUBIC`, because it faster and
:py:attr:`~PIL.Image.ANTIALIAS` doesn't give any advantages after
downscaling with libJPEG, which uses supersampling internaly, not convolutions.