我今天用的例子是:

import PIL
import numpy
from PIL import Image

def resize_image(numpy_array_image, new_height):
    # convert nympy array image to PIL.Image
    image = Image.fromarray(numpy.uint8(numpy_array_image))
    old_width = float(image.size[0])
    old_height = float(image.size[1])
    ratio = float( new_height / old_height)
    new_width = int(old_width * ratio)
    image = image.resize((new_width, new_height), PIL.Image.ANTIALIAS)
    # convert PIL.Image into nympy array back again
    return array(image)

我今天用的例子是:

import PIL
import numpy
from PIL import Image

def resize_image(numpy_array_image, new_height):
    # convert nympy array image to PIL.Image
    image = Image.fromarray(numpy.uint8(numpy_array_image))
    old_width = float(image.size[0])
    old_height = float(image.size[1])
    ratio = float( new_height / old_height)
    new_width = int(old_width * ratio)
    image = image.resize((new_width, new_height), PIL.Image.ANTIALIAS)
    # convert PIL.Image into nympy array back again
    return array(image)

你需要将你的图像转换为numpy数组:

import numpy
import PIL

img = PIL.Image.open("foo.jpg").convert("L")
imgarr = numpy.array(img) 

def imshow(img):
    img = img / 2 + 0.5     # unnormalize
    npimg = img.numpy()
    plt.imshow(np.transpose(npimg, (1, 2, 0)))
    plt.show()

您可以将图像转换为numpy 通过压缩特征后将图像解析为numpy()函数(非归一化)

将Numpy转换为PIL图像和PIL转换为Numpy

import numpy as np
from PIL import Image

def pilToNumpy(img):
    return np.array(img)

def NumpyToPil(img):
    return Image.fromarray(img)

将I作为数组打开:

>>> I = numpy.asarray(PIL.Image.open('test.jpg'))

对I做一些操作，然后将它转换回图像:

>>> im = PIL.Image.fromarray(numpy.uint8(I))

来源:使用FFT过滤numpy图像，Python

如果您出于某种原因想显式地执行此操作，在related .zip中的此页上有pil2array()和array2pil()函数使用getdata()。