我附加了一个简单的例程来将npy转换为图像。

from PIL import Image
import matplotlib

img = np.load('flair1_slice75.npy')

matplotlib.image.imsave("G1_flair_75.jpeg", img)

使用cv2.imwrite。

import cv2
assert mat.shape[2] == 1 or mat.shape[2] == 3, 'the third dim should be channel'
cv2.imwrite(path, mat) # note the form of data should be height - width - channel  

python有opencv(文档在这里)。

import cv2
import numpy as np

img = ... # Your image as a numpy array 

cv2.imwrite("filename.png", img)

如果需要进行除保存以外的更多处理，则非常有用。

matplotlib:

import matplotlib.image

matplotlib.image.imsave('name.png', array)

适用于matplotlib 1.3.1，我不知道低版本。从文档字符串:

Arguments:
  *fname*:
    A string containing a path to a filename, or a Python file-like object.
    If *format* is *None* and *fname* is a string, the output
    format is deduced from the extension of the filename.
  *arr*:
    An MxN (luminance), MxNx3 (RGB) or MxNx4 (RGBA) array.

Imageio是一个Python库，它提供了一个简单的接口来读取和写入广泛的图像数据，包括动画图像、视频、体积数据和科学格式。它是跨平台的，运行在Python 2.7和3.4+上，易于安装。

这是一个灰度图像的例子:

import numpy as np
import imageio

# data is numpy array with grayscale value for each pixel.
data = np.array([70,80,82,72,58,58,60,63,54,58,60,48,89,115,121,119])

# 16 pixels can be converted into square of 4x4 or 2x8 or 8x2
data = data.reshape((4, 4)).astype('uint8')

# save image
imageio.imwrite('pic.jpg', data)

您可以使用PyPNG。它是一个纯Python(无依赖)开源PNG编码器/解码器，它支持将NumPy数组写入图像。