python PIL resize

https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.resize

Image.resize(size, resample=None, box=None, reducing_gap=None)[source]

Returns a resized copy of this image.

Parameters:

size – The requested size in pixels, as a 2-tuple: (width, height).
resample – An optional resampling filter. This can be one of Resampling.NEAREST, Resampling.BOX, Resampling.BILINEAR, Resampling.HAMMING, Resampling.BICUBIC or Resampling.LANCZOS. If the image has mode “1” or “P”, it is always set to Resampling.NEAREST. If the image mode specifies a number of bits, such as “I;16”, then the default filter is Resampling.NEAREST. Otherwise, the default filter is Resampling.BICUBIC. See: Filters.
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.
reducing_gap – Apply optimization by resizing the image in two steps. First, reducing the image by integer times using 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 Image object.

This resizes the given image from (width, height) to (width/2, height/2):

from PIL import Image

with Image.open("hopper.jpg") as im:

    # Provide the target width and height of the image
    (width, height) = (im.width // 2, im.height // 2)
    im_resized = im.resize((width, height))