使用 PIL 在图片比例不变的情况下修改图片大小。
目录
一、介绍
Image.resize
def resize(self, size, resample=BICUBIC, box=None, reducing_gap=None):
"""
Returns a resized copy of this image.
返回此图像的大小调整后的副本。:param size: The requested size in pixels, as a 2-tuple:
(width, height).
param size: 请求的大小(以像素为单位)，是一个二元数组：(width, height)
:param resample: An optional resampling filter. This can be
one of :py:attr:`PIL.Image.NEAREST`, :py:attr:`PIL.Image.BOX`,
:py:attr:`PIL.Image.BILINEAR`, :py:attr:`PIL.Image.HAMMING`,
:py:attr:`PIL.Image.BICUBIC` or :py:attr:`PIL.Image.LANCZOS`.
Default filter is :py:attr:`PIL.Image.BICUBIC`.
If the image has mode "1" or "P", it is
always set to :py:attr:`PIL.Image.NEAREST`.
See: :ref:`concept-filters`.
param resample: 一个可选的重采样过滤器。
: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 box: 可选的4元浮点数，提供要缩放的源映像区域。
: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).
param reducing_gap: 通过两个步骤调整图像大小来应用优化。
:returns: An :py:class:`~PIL.Image.Image` object.
returns: 返回一个 PIL.Image.Image 对象
"""
二、代码
from PIL import Image
image = Image.open('图片路径')
# 调整图片大小，并保持比例不变
# 给定一个基本宽度
base_width = 50
# 基本宽度与原图宽度的比例
w_percent = base_width / float(image.size[0])
# 计算比例不变的条件下新图的长度
h_size = int(float(image.size[1]) * float(w_percent))
# 重新设置大小
# 默认情况下，PIL使用Image.NEAREST过滤器进行大小调整，从而获得良好的性能，但质量很差。
image = image.resize((base_width, h_size), Image.ANTIALIAS)