我可以使用"normal"将numpy数组另存为16位图像吗? (想)python吗? [英] Can I save a numpy array as a 16-bit image using "normal" (Enthought) python?

问题描述

是否可以使用任何常用的python软件包将numpy数组另存为16位图像(tif，png)? 这是过去是我上班的唯一方法，但是我需要安装FreeImage软件包，这有点烦人.

Is there any way to save a numpy array as a 16 bit image (tif, png) using any of the commonly available python packages? This is the only way that I could get to work in the past, but I needed to install the FreeImage package, which is a little annoying.

这似乎是一项非常基本的任务，所以我希望它应该被scipy覆盖，但是scipy.misc.imsave仅适用8位.

This seems like a pretty basic task, so I would expect that it should be covered by scipy, but scipy.misc.imsave only does 8-bits.

有什么想法吗?

推荐答案

一种替代方法是使用 pypng .您仍然必须安装另一个软件包，但这是纯Python，因此应该很容易. (在pypng源文件中实际上有一个Cython文件，但是它的使用是可选的.)

One alternative is to use pypng. You'll still have to install another package, but it is pure Python, so that should be easy. (There is actually a Cython file in the pypng source, but its use is optional.)

以下是使用pypng将numpy数组写入PNG的示例:

Here's an example of using pypng to write numpy arrays to PNG:

import png

import numpy as np

# The following import is just for creating an interesting array
# of data.  It is not necessary for writing a PNG file with PyPNG.
from scipy.ndimage import gaussian_filter


# Make an image in a numpy array for this demonstration.
nrows = 240
ncols = 320
np.random.seed(12345)
x = np.random.randn(nrows, ncols, 3)

# y is our floating point demonstration data.
y = gaussian_filter(x, (16, 16, 0))

# Convert y to 16 bit unsigned integers.
z = (65535*((y - y.min())/y.ptp())).astype(np.uint16)

# Use pypng to write z as a color PNG.
with open('foo_color.png', 'wb') as f:
    writer = png.Writer(width=z.shape[1], height=z.shape[0], bitdepth=16)
    # Convert z to the Python list of lists expected by
    # the png writer.
    z2list = z.reshape(-1, z.shape[1]*z.shape[2]).tolist()
    writer.write(f, z2list)

# Here's a grayscale example.
zgray = z[:, :, 0]

# Use pypng to write zgray as a grayscale PNG.
with open('foo_gray.png', 'wb') as f:
    writer = png.Writer(width=z.shape[1], height=z.shape[0], bitdepth=16, greyscale=True)
    zgray2list = zgray.tolist()
    writer.write(f, zgray2list)

这是颜色输出:

这是灰度输出:

更新:我最近为名为 numpngw 提供了将numpy数组写入PNG文件的功能.该存储库具有一个setup.py文件，用于将其作为软件包安装，但是基本代码位于单个文件numpngw.py中，可以将其复制到任何方便的位置. numpngw的唯一依赖项是numpy.

Update: I recently created a github repository for a module called numpngw that provides a function for writing a numpy array to a PNG file. The repository has a setup.py file for installing it as a package, but the essential code is in a single file, numpngw.py, that could be copied to any convenient location. The only dependency of numpngw is numpy.

这是一个脚本，可以生成与上面显示的图像相同的16位图像:

Here's a script that generates the same 16 bit images as those shown above:

import numpy as np
import numpngw

# The following import is just for creating an interesting array
# of data.  It is not necessary for writing a PNG file with PyPNG.
from scipy.ndimage import gaussian_filter


# Make an image in a numpy array for this demonstration.
nrows = 240
ncols = 320
np.random.seed(12345)
x = np.random.randn(nrows, ncols, 3)

# y is our floating point demonstration data.
y = gaussian_filter(x, (16, 16, 0))

# Convert y to 16 bit unsigned integers.
z = (65535*((y - y.min())/y.ptp())).astype(np.uint16)

# Use numpngw to write z as a color PNG.
numpngw.write_png('foo_color.png', z)

# Here's a grayscale example.
zgray = z[:, :, 0]

# Use numpngw to write zgray as a grayscale PNG.
numpngw.write_png('foo_gray.png', zgray)

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