python - 图像的RGB矩阵

python - RGB matrix of an image

提问by Ojas

Taking an image as input, how can I get the rgb matrix corresponding to it? I checked out the numpy.asarray function. Does that give me the rgb matrix or some other matrix?

以图像作为输入，如何得到与之对应的rgb矩阵？我检查了 numpy.asarray 函数。这是否给了我 rgb 矩阵或其他一些矩阵？

采纳答案by abarnert

Note that this answer is outdated as of 2018; scipyhas deprecated imread, and you should switch to imageio.imread. See this transition docabout differences between the two. The code below should work with no changes if you just import the new library in place of the old, but I haven't tested it.

请注意，此答案截至 2018 年已过时；scipy已弃用imread，您应该切换到imageio.imread. 有关两者之间的差异，请参阅此转换文档。如果您只是导入新库代替旧库，则下面的代码应该无需更改，但我尚未对其进行测试。

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The simplest answer is to use the NumPy and SciPy wrappers around PIL. There's a great tutorial, but the basic idea is:

最简单的答案是使用围绕 PIL 的 NumPy 和 SciPy 包装器。有一个很棒的教程，但基本思想是：

from scipy import misc
arr = misc.imread('lena.png') # 640x480x3 array
arr[20, 30] # 3-vector for a pixel
arr[20, 30, 1] # green value for a pixel

For a 640x480 RGB image, this will give you a 640x480x3 array of uint8.

对于 640x480 RGB 图像，这将为您提供 640x480x3 的uint8.

Or you can just open the file with PIL (or, rather, Pillow; if you're still using PIL, this may not work, or may be very slow) and pass it straight to NumPy:

或者，您可以使用 PIL（或者，更确切地说，Pillow；如果您仍在使用 PIL，这可能不起作用，或者可能很慢）并直接将其传递给 NumPy：

import numpy as np
from PIL import Image
img = Image.open('lena.png')
arr = np.array(img) # 640x480x4 array
arr[20, 30] # 4-vector, just like above

This will give you a 640x480x4 array of type uint8(the 4th is alpha; PIL always loads PNG files as RGBA, even if they have no transparency; see img.getbands()if you're every unsure).

这将为您提供一个 640x480x4 类型的数组uint8（第 4 个是 alpha；PIL 始终将 PNG 文件加载为 RGBA，即使它们没有透明度；看看img.getbands()您是否都不确定）。

If you don't want to use NumPy at all, PIL's own PixelArraytype is a more limited array:

如果你根本不想使用 NumPy，PIL 自己的PixelArray类型是一个更有限的数组：

arr = img.load()
arr[20, 30] # tuple of 4 ints

This gives you a 640x480 PixelAccessarray?of RGBA 4-tuples.

这为您提供了一个 640x480PixelAccess的 RGBA 4 元组数组。

Or you can just call getpixelon the image:

或者你可以只调用getpixel图像：

img.getpixel(20, 30) # tuple of 4 ints

回答by Bemmu

I have a feeling I'm not doing exactly what you wanted here, so please specify if this is totally off. You could open the image like this and get an array of pixels:

我有一种感觉，我在这里没有完全按照您的意愿行事，因此请说明这是否完全关闭。你可以像这样打开图像并获得一个像素数组：

import Image
im = Image.open('Lenna.png')
pixels = list(im.getdata())

This will get you a flat list of RGB data that looks like

这将为您提供一个平面的 RGB 数据列表，看起来像

[(226, 137, 125), (226, 137, 125), (223, 137, 133), (223, 136, 128), 
 (226, 138, 120), (226, 129, 116), (228, 138, 123), (227, 134, 124), 
 (227, 140, 127), (225, 136, 119), (228, 135, 126), (225, 134, 121),...

Now this will be all pixels in a flat array, if you want a two dimensional array then some additional code would be needed for that. Not sure if there is a direct function for it in PIL.

现在这将是平面阵列中的所有像素，如果您想要二维阵列，则需要一些额外的代码。不确定 PIL 中是否有直接的函数。

回答by mike

Also to add, if you or anyone else is using opencv.

另外要补充的是，如果您或其他任何人正在使用 opencv。

 imgc=cv2.imread(file)

or to read in as grayscale

或读入灰度

 imgc=cv2.imread(file,0)

If you will be doing some comparison between the images you may want to think about turning the array of pixels into histograms to normalise the data.

如果您将在图像之间进行一些比较，您可能需要考虑将像素阵列转换为直方图以对数据进行标准化。

   hist = np.histogram(img.flatten(),256,[0,256])[0]

The above line firstly flattens your img array so you do lose the dimensionality of your image. It then produces bins from 0 to 256 (for the grayscale image) and adds the counts from the img to these bins and returns them as hist which can then be plotted. For example, if the 100 bin has a value of 20 it means that 20 pixels in your image had a value of 100.

上面的行首先展平了您的 img 数组，因此您确实会丢失图像的维度。然后它生成从 0 到 256（对于灰度图像）的 bin，并将来自 img 的计数添加到这些 bin 并将它们作为 hist 返回，然后可以绘制。例如，如果 100 bin 的值为 20，则表示图像中 20 个像素的值为 100。

Hope this adds another possiblity to think about or to anyone looking to get started in opencv.

希望这为任何希望开始使用 opencv 的人增加了另一种思考的可能性。

回答by Denziloe

I tried imageio.imreadand it worked great, but a minute later stumbled upon a function in matplotlibwhich worked exactly the same, getting a numpyn by m by 3 array:

我试过了imageio.imread，效果很好，但一分钟后偶然发现了一个功能matplotlib完全相同的函数，得到一个numpyn x m x 3 数组：

from matplotlib import pyplot as plot
image = plt.imread(path)

回答by TitouanT

You can do that with Pillow, the getdatamethod gives you a flat array of the pixels, you can then build a matrix from that using the sizeof the image.

您可以使用Pillow，该getdata方法为您提供一个平面的像素阵列，然后您可以使用size图像的构建一个矩阵。

from PIL import Image

def getPixels(filename):
    img = Image.open(filename, 'r')
    w, h = img.size
    pix = list(img.getdata())
    return [pix[n:n+w] for n in range(0, w*h, w)]

回答by Prabhat Soni

Thanks abarenet! Please use imageioinstead of scipyas scipyis not being continued anymore. Simplifying abarnet's answer:

谢谢阿巴雷特！请使用imageio而不是scipy因为scipy不再继续。简化 abarnet 的回答：

1. Install imageio

   pip3 install imageio

2. python3 code:

   If the image is of dimensions 260X340, then rgb_matrix is an array of dimensions 260X340X3

   from imageio import imread rgb_matrix = imread('image13.png') print(rgb_matrix[15][23])

1. 安装 imageio

   pip3 install imageio

2. python3代码：

   如果图像具有维度260X340，则 rgb_matrix 是维度数组260X340X3

   from imageio import imread rgb_matrix = imread('image13.png') print(rgb_matrix[15][23])