chatGPT 告诉我,PIL 的 resize 的默认插值是 BILINEAR
事实真是如此吗?
看一下 PIL 的源码:
PIL/Image.py
def resize(self, size, resample=None, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
:param size: The requested size in pixels, as a 2-tuple:
(width, height).
:param resample: An optional resampling filter. This can be
one of :py:data:`Resampling.NEAREST`, :py:data:`Resampling.BOX`,
:py:data:`Resampling.BILINEAR`, :py:data:`Resampling.HAMMING`,
:py:data:`Resampling.BICUBIC` or :py:data:`Resampling.LANCZOS`.
If the image has mode "1" or "P", it is always set to
:py:data:`Resampling.NEAREST`. If the image mode specifies a number
of bits, such as "I;16", then the default filter is
:py:data:`Resampling.NEAREST`. Otherwise, the default filter is
:py:data:`Resampling.BICUBIC`. See: :ref:`concept-filters`.
:param box: An optional 4-tuple of floats providing
the source image region to be scaled.
The values must be within (0, 0, width, height) rectangle.
If omitted or None, the entire source is used.
:param reducing_gap: Apply optimization by resizing the image
in two steps. First, reducing the image by integer times
using :py:meth:`~PIL.Image.Image.reduce`.
Second, resizing using regular resampling. The last step
changes size no less than by ``reducing_gap`` times.
``reducing_gap`` may be None (no first step is performed)
or should be greater than 1.0. The bigger ``reducing_gap``,
the closer the result to the fair resampling.
The smaller ``reducing_gap``, the faster resizing.
With ``reducing_gap`` greater or equal to 3.0, the result is
indistinguishable from fair resampling in most cases.
The default value is None (no optimization).
:returns: An :py:class:`~PIL.Image.Image` object.
"""
if resample is None:
type_special = ";" in self.mode
resample = Resampling.NEAREST if type_special else Resampling.BICUBIC
elif resample not in (
Resampling.NEAREST,
Resampling.BILINEAR,
Resampling.BICUBIC,
Resampling.LANCZOS,
Resampling.BOX,
Resampling.HAMMING,
):
但没有指定 resample 的时候,并且 mode 不含 ;
的时候, 就是用 BICUBIC, BICUBIC 是 三次样条插值
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