PythonPIL图片如何按比例裁剪

from PIL import Image
def image_clip(filename, savename, width_scale, height_scale):
    """图像裁剪
    :param filename: 原图路径
    :param savename: 保存图片路径
    :param width_scale: 宽的比例
    :param height_scale: 高的比例
    """
    image = Image.open(filename)
    (width, height), (_width, _height) = image.size, image.size
    _height = width / width_scale * height_scale
    if _height > height:
        _height = height
        _width = width_scale * height / height_scale
    image.crop((0, 0, _width, _height)).save(savename)  # 左上角
    # image.crop((0, height - _height, _width, height)).save(savename)  # 左下角
    # image.crop((width - _width, 0, width, _height)).save(savename)  # 右上角
    # image.crop((width - _width, height - _height, width, height)).save(savename)  # 右下角
if __name__ == '__main__':
    filename = '1.jpg'
    savename = 'result.jpg'
    image_clip(filename, savename, width_scale=4, height_scale=3)
    # image_clip(filename, savename, width_scale=3, height_scale=4)

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
    """

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)