mirror of
https://github.com/python-pillow/Pillow.git
synced 2025-01-27 17:54:32 +03:00
9e5173846e
Co-authored-by: Hugo van Kemenade <hugovk@users.noreply.github.com>
80 lines
1.9 KiB
ReStructuredText
80 lines
1.9 KiB
ReStructuredText
10.2.0
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------
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Backwards Incompatible Changes
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==============================
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TODO
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^^^^
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TODO
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Deprecations
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============
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TODO
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^^^^
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TODO
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API Changes
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===========
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Zero or negative font size error
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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When creating a :py:class:`~PIL.ImageFont.FreeTypeFont` instance, either directly or
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through :py:func:`~PIL.ImageFont.truetype`, if the font size is zero or less, a
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:py:exc:`ValueError` will now be raised.
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API Additions
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=============
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Added DdsImagePlugin enums
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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:py:class:`~PIL.DdsImagePlugin.DDSD`, :py:class:`~PIL.DdsImagePlugin.DDSCAPS`,
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:py:class:`~PIL.DdsImagePlugin.DDSCAPS2`, :py:class:`~PIL.DdsImagePlugin.DDPF`,
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:py:class:`~PIL.DdsImagePlugin.DXGI_FORMAT` and :py:class:`~PIL.DdsImagePlugin.D3DFMT`
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enums have been added to :py:class:`PIL.DdsImagePlugin`.
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JPEG restart marker interval
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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When saving JPEG files, ``restart_marker_blocks`` and ``restart_marker_rows`` can now
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be used to emit restart markers whenever the specified number of MCU blocks or rows
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have been produced.
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JPEG tables-only streamtype
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^^^^^^^^^^^^^^^^^^^^^^^^^^^
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When saving JPEG files, ``streamtype`` can now be set to 1, for tables-only. This will
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output only the quantization and Huffman tables for the image.
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Security
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========
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TODO
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^^^^
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TODO
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Other Changes
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=============
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Added DDS BC4U and DX10 BC1 and BC4 reading
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Support has been added to read the BC4U format of DDS images.
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Support has also been added to read DX10 BC1 and BC4, whether UNORM or
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TYPELESS.
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Optimized ImageStat.Stat count and extrema
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Calculating the :py:attr:`~PIL.ImageStat.Stat.count` and
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:py:attr:`~PIL.ImageStat.Stat.extrema` statistics is now faster. After the
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histogram is created in ``st = ImageStat.Stat(im)``, ``st.count`` is 3x as fast
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on average and ``st.extrema`` is 12x as fast on average.
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