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Refer to quantization method docs in Image.quantize()

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All quantization methods are already documented in a dedicated
section. Don't duplicate that information in the documentation
of Image.quantize(). Link to the existing section.
This commit is contained in:
gofr 2021-02-07 17:36:22 +01:00
parent d273d08949
commit 39acc4478f
2 changed files with 6 additions and 5 deletions
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6
docs/reference/Image.rst
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@ -479,6 +479,8 @@ Used to specify the pallete to use for the :meth:`~Image.convert` method.
.. data:: WEB .. data:: WEB
.. data:: ADAPTIVE .. data:: ADAPTIVE
.. _quantization-methods:
Quantization methods Quantization methods
^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^
@ -486,11 +488,11 @@ Used to specify the quantization method to use for the :meth:`~Image.quantize` m
.. data:: MEDIANCUT .. data:: MEDIANCUT
Median cut Median cut. RGBA not supported.
.. data:: MAXCOVERAGE .. data:: MAXCOVERAGE
Maximum coverage Maximum coverage. RGBA not supported.
.. data:: FASTOCTREE .. data:: FASTOCTREE

5
src/PIL/Image.py
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@ -1054,9 +1054,8 @@ class Image:
:param colors: The desired number of colors, <= 256 :param colors: The desired number of colors, <= 256
:param method: :data:`MEDIANCUT` (default), :param method: :data:`MEDIANCUT` (default),
:data:`MAXCOVERAGE`, :data:`FASTOCTREE` (default for "RGBA" mode).
:data:`FASTOCTREE` (default for RGBA images), See :ref:`quantization-methods` for all available methods.
:data:`LIBIMAGEQUANT`.
:param kmeans: Integer :param kmeans: Integer
:param palette: Quantize to the palette of given :param palette: Quantize to the palette of given
:py:class:`PIL.Image.Image`. :py:class:`PIL.Image.Image`.