from PIL import Image
def image_clip(filename, savename, width_scale, height_scale):
    """圖像裁剪
    :param filename: 原圖路徑
    :param savename: 保存圖片路徑
    :param width_scale: 寬的比例
    :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.
    返回此圖像的大小調(diào)整后的副本。
    :param size: The requested size in pixels, as a 2-tuple:
       (width, height).
     param size: 請求的大小(以像素為單位)，是一個二元數(shù)組：(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: 一個可選的重采樣過濾器。
    :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: 可選的4元浮點數(shù)，提供要縮放的源映像區(qū)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: 通過兩個步驟調(diào)整圖像大小來應(yīng)用優(yōu)化。
    :returns: An :py:class:`~PIL.Image.Image` object.
     returns: 返回一個 PIL.Image.Image 對象
    """

from PIL import Image
 
 
image = Image.open('圖片路徑')
 
# 調(diào)整圖片大小，并保持比例不變
# 給定一個基本寬度
base_width = 50
 
# 基本寬度與原圖寬度的比例
w_percent = base_width / float(image.size[0])
 
# 計算比例不變的條件下新圖的長度
h_size = int(float(image.size[1]) * float(w_percent))
 
# 重新設(shè)置大小
# 默認情況下，PIL使用Image.NEAREST過濾器進行大小調(diào)整，從而獲得良好的性能，但質(zhì)量很差。
image = image.resize((base_width, h_size), Image.ANTIALIAS)