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Updated release notes

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Eric Soroos 2017-09-20 10:54:59 +00:00
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docs/releasenotes/4.3.0.rst
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4.3.0
-----
Get One Channel From Image
==========================
New method :py:meth:`PIL.Image.Image.getchannel` is added.
It returns single channel by index or name. For example,
``image.getchannel("A")`` will return alpha channel as separate image.
``getchannel`` should work up to 6 times faster than ``image.split()[0]``
in previous Pillow versions.
Box Blur
========
New filter :py:class:`PIL.ImageFilter.BoxBlur` is added.
Partial Resampling
==================
Added new argument ``box`` for :py:meth:`PIL.Image.Image.resize`. This
argument defines a source rectangle from within the source image to be
resized. This is very similar to the ``image.crop(box).resize(size)``
sequence except that ``box`` can be specified with subpixel accuracy.
Loading 16-bit TIFF Images
==========================
Pillow now can read 16-bit multichannel TIFF files including files
with alpha transparency. The image data is truncated to 8-bit
precision.
Performance
API Changes
===========
This release contains several performance improvements:
* Many memory bandwidth-bounded operations such as crop, image allocation,
conversion, split into bands and merging from bands are up to 2x faster.
* Upscaling of multichannel images (such as RGB) is accelerated by 5-10%
* JPEG loading is accelerated up to 15% and JPEG saving up to 20% when
using a recent version of libjpeg-turbo.
Deprecations
^^^^^^^^^^^^
Several undocumented functions in ImageOps have been deprecated:
``gaussian_blur``, ``gblur``, ``unsharp_mask``, ``usm`` and
``box_blur``. Use the equivalent operations in ImageFilter
instead. These functions will be removed in a future release.
TIFF Metadata Changes
=====================
^^^^^^^^^^^^^^^^^^^^^
* TIFF tags with unknown type/quantity now default to being bare
values if they are 1 element, where previously they would be a
@ -61,9 +27,8 @@ TIFF Metadata Changes
items, as there can be multiple items, one for UTF-8, and one for
UTF-16.
Core Image API Changes
======================
^^^^^^^^^^^^^^^^^^^^^^
These are internal functions that should not have been used by user
code, but they were accessible from the python layer.
@ -74,3 +39,71 @@ identified the format of the clipboard data.
The ``PIL.Image.core.copy`` and ``PIL.Image.Image.im.copy2`` methods
have been removed.
API Additions
=============
Get One Channel From Image
^^^^^^^^^^^^^^^^^^^^^^^^^^
A new method :py:meth:`PIL.Image.Image.getchannel` has been added to
return a single channel by index or name. For example,
``image.getchannel("A")`` will return alpha channel as separate image.
``getchannel`` should work up to 6 times faster than
``image.split()[0]`` in previous Pillow versions.
Box Blur
^^^^^^^^
A new filter, :py:class:`PIL.ImageFilter.BoxBlur`, has been
added. This is a filter with similar results to a Gaussian blur, but
is much faster.
Partial Resampling
^^^^^^^^^^^^^^^^^^
Added new argument ``box`` for :py:meth:`PIL.Image.Image.resize`. This
argument defines a source rectangle from within the source image to be
resized. This is very similar to the ``image.crop(box).resize(size)``
sequence except that ``box`` can be specified with subpixel accuracy.
New Transpose Operation
^^^^^^^^^^^^^^^^^^^^^^^
The ``Image.TRANSVERSE`` operation has been added to
:py:meth:`PIL.Image.Image.transpose`. This is equvalent to a transpose
operation about the opposite diagonal.
Multiband Filters
^^^^^^^^^^^^^^^^^
There is a new :py:class:`PIL.ImageFilter.MultibandFilter` base class
for image filters that can run on all channels of an image in one
operation. The original :py:class:`PIL.ImageFilter.Filter` class
remains for image filters that can process only single band images, or
require splitting of channels prior to filtering.
Loading 16-bit TIFF Images
==========================
Pillow now can read 16-bit multichannel TIFF files including files
with alpha transparency. The image data is truncated to 8-bit
precision.
Performance
===========
This release contains several performance improvements:
* Many memory bandwidth-bounded operations such as crop, image allocation,
conversion, split into bands and merging from bands are up to 2x faster.
* Upscaling of multichannel images (such as RGB) is accelerated by 5-10%
* JPEG loading is accelerated up to 15% and JPEG saving up to 20% when
using a recent version of libjpeg-turbo.
* ``Image.transpose`` has been accelerated 15% or more by using a cache
friendly algorithm.
* ImageFilters based on Kernel convolution are significantly faster
due to the new MultibandFilter feature.