blocks|key|298340|text|尝试使用灰度色彩映射表？|type|unstyled|depth|inlineStyleRanges|entityRanges|data|298341|例如像这样的|298342|imshow(...,+cmap=pyplot.cm.binary)|code-block|syntax|javascript|298343|有关色彩映射表的列表，请参见http://scipy-cookbook.readthedocs.org/items/Matplotlib_Show_colormaps.html|offset|length|298344|entityMap|0|LINK|mutability|MUTABLE|url|http://scipy-cookbook.readthedocs.org/items/Matplotlib_Show_colormaps.html^0|0|0|0|E|22|0|0^^$0|@$1|2|3|4|5|6|7|U|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|V|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|W|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|X|8|@]|9|@$K|Y|L|Z|1|10]]|A|$]]|$1|M|3|-4|5|6|7|11|8|@]|9|@]|A|$]]]|N|$O|$5|P|Q|R|A|$S|T]]]]

Try to use a grayscale colormap?

E.g. something like

<pre><code>imshow(..., cmap=pyplot.cm.binary)
</code></pre>

For a list of colormaps, see <a href="http://scipy-cookbook.readthedocs.org/items/Matplotlib_Show_colormaps.html" rel="noreferrer">http://scipy-cookbook.readthedocs.org/items/Matplotlib_Show_colormaps.html</a>

blocks|key|296426|text|下面的代码将从文件image.png加载图像，并将其显示为灰度。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|296427|import+numpy+as+np
import+matplotlib.pyplot+as+plt
from+PIL+import+Image

fname+=+'image.png'
image+=+Image.open(fname).convert("L")
arr+=+np.asarray(image)
plt.imshow(arr,+cmap='gray',+vmin=0,+vmax=255)
plt.show()|code-block|syntax|javascript|296428|如果要显示反转灰度，请将cmap切换为cmap='gray_r'。|296429|entityMap^0|9|9|0|0|J|D|0^^$0|@$1|2|3|4|5|6|7|O|8|@$9|P|A|Q|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|R|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@]|E|$]]|$1|M|3|-4|5|6|7|V|8|@]|D|@]|E|$]]]|N|$]]

The following code will load an image from a file <code>image.png</code> and will display it as grayscale.

<pre><code>import numpy as np
import matplotlib.pyplot as plt
from PIL import Image

fname = 'image.png'
image = Image.open(fname).convert("L")
arr = np.asarray(image)
plt.imshow(arr, cmap='gray', vmin=0, vmax=255)
plt.show()
</code></pre>

If you want to display the inverse grayscale, switch the cmap to <code>cmap='gray_r'</code>.

blocks|key|296436|text|试试这个：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|296437|import+pylab
from+scipy+import+misc

pylab.imshow(misc.lena(),cmap=pylab.gray())
pylab.show()|code-block|syntax|javascript|296438|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

try this:

<pre><code>import pylab
from scipy import misc

pylab.imshow(misc.lena(),cmap=pylab.gray())
pylab.show()
</code></pre>

blocks|key|3019792|text|import+matplotlib.pyplot+as+plt|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3019793|您还可以在代码中运行一次|3019794|plt.gray()|code-block|syntax|javascript|3019795|这将默认以灰度显示图像|3019796|im+=+array(Image.open('I_am_batman.jpg').convert('L'))
plt.imshow(im)
plt.show()|3019797|entityMap^0|0|V|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|V|8|@]|D|@]|E|$]]|$1|H|3|I|5|J|7|W|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|X|8|@]|D|@]|E|$]]|$1|O|3|P|5|J|7|Y|8|@]|D|@]|E|$K|L]]|$1|Q|3|-4|5|6|7|Z|8|@]|D|@]|E|$]]]|R|$]]

<code>import matplotlib.pyplot as plt</code>

You can also run once in your code

<pre><code>plt.gray()
</code></pre>

This will show the images in grayscale as default

<pre class="lang-python prettyprint-override"><code>im = array(Image.open('I_am_batman.jpg').convert('L'))
plt.imshow(im)
plt.show()
</code></pre>

blocks|key|3019799|text|我会使用get_cmap方法。示例：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3019800|import+matplotlib.pyplot+as+plt

plt.imshow(matrix,+cmap=plt.get_cmap('gray'))|code-block|syntax|javascript|3019801|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

I would use the get_cmap method. Ex.:

<pre><code>import matplotlib.pyplot as plt

plt.imshow(matrix, cmap=plt.get_cmap('gray'))
</code></pre>

blocks|key|293307|text|@unutbu的答案非常接近正确答案。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|293308|默认情况下，plt.imshow()会尝试将(MxN)数组数据缩放到0.0~1.0。然后映射到0~255。对于大多数自然拍摄的图像，这是很好的，你不会看到不同的。但是如果像素值图像的范围很窄，那么最小像素是156，最大像素是234。灰色图像将看起来完全错误。用灰色显示图像的正确方法是|293309|from+matplotlib.colors+import+NoNorm
...
plt.imshow(img,cmap='gray',norm=NoNorm())
...|code-block|syntax|javascript|293310|让我们看一个例子：|293311|这是原始图像：original|offset|length|293312|这是使用默认的规范设置，它是None：wrong+pic|293313|这是使用NoNorm设置，即NoNorm()：right+pic|293314|entityMap|0|LINK|mutability|MUTABLE|url|https://i.stack.imgur.com/pcXpB.jpg|1|https://i.stack.imgur.com/YOKgA.png|2|https://i.stack.imgur.com/MWM2a.png^0|0|0|0|0|7|8|0|0|J|9|1|0|N|9|2|0^^$0|@$1|2|3|4|5|6|7|14|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|15|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|16|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|17|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|18|8|@]|9|@$M|19|N|1A|1|1B]]|A|$]]|$1|O|3|P|5|6|7|1C|8|@]|9|@$M|1D|N|1E|1|1F]]|A|$]]|$1|Q|3|R|5|6|7|1G|8|@]|9|@$M|1H|N|1I|1|1J]]|A|$]]|$1|S|3|-4|5|6|7|1K|8|@]|9|@]|A|$]]]|T|$U|$5|V|W|X|A|$Y|Z]]|10|$5|V|W|X|A|$Y|11]]|12|$5|V|W|X|A|$Y|13]]]]

@unutbu's answer is quite close to the right answer.

By default, plt.imshow() will try to scale your (MxN) array data to 0.0~1.0. And then map to 0~255. For most natural taken images, this is fine, you won't see a different. But if you have narrow range of pixel value image, say the min pixel is 156 and the max pixel is 234. The gray image will looks totally wrong.
The right way to show an image in gray is 

<pre><code>from matplotlib.colors import NoNorm
...
plt.imshow(img,cmap='gray',norm=NoNorm())
...
</code></pre>

Let's see an example: 

this is the origianl image:
<a href="https://i.stack.imgur.com/pcXpB.jpg" rel="noreferrer">original</a>

this is using defaul norm setting,which is None:
<a href="https://i.stack.imgur.com/YOKgA.png" rel="noreferrer">wrong pic</a>

this is using NoNorm setting,which is NoNorm():
<a href="https://i.stack.imgur.com/MWM2a.png" rel="noreferrer">right pic</a>

blocks|key|293316|text|不使用插值并设置为灰色。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|293317|import+matplotlib.pyplot+as+plt
plt.imshow(img[:,:,1],+cmap='gray',interpolation='none')|code-block|syntax|javascript|293318|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Use no interpolation and set to gray.

<pre class="lang-py prettyprint-override"><code>import matplotlib.pyplot as plt
plt.imshow(img[:,:,1], cmap='gray',interpolation='none')
</code></pre>

blocks|key|298414|text|当图像为紫色和黄色时。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|298415|更改保存图像的方式：|298416|plt.imsave(....,+cmap='gray')|offset|length|style|CODE|298417|entityMap^0|0|0|0|T|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|N|8|@$F|O|G|P|H|I]]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|K|$]]

When the image has purple &amp; yellow color.
change way of saving image: 
<code>plt.imsave(...., cmap='gray')</code>

blocks|key|298425|text|plt.imshow(img[:,:,0],+cmap='gray')

plt.imshow(img[:,:,1],+cmap='gray')

plt.imshow(img[:,:,2],+cmap='gray')|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|298426|应该行得通。但是，这种方法的问题是它不是真正的灰色。它只会将其中一个RGB通道更改为灰色。|unstyled|298427|请看下面。|298428|from+sklearn.datasets+import+load_sample_image
flower+=+load_sample_image("flower.jpg")

plt.subplot(1,4,1)
plt.imshow(flower)
plt.axis("off")
plt.title("Original")

#+R+level+to+gray
plt.subplot(1,4,2)
plt.imshow(flower[:,:,0],+cmap='gray')
plt.axis("off")
plt.title("R+to+gray")


#+G+leval+to+gray
plt.subplot(1,4,3)
plt.imshow(flower[:,:,1],+cmap='gray')
plt.axis("off")
plt.title("R+to+gray")

#+B+leval+to+gray
plt.subplot(1,4,4)
plt.imshow(flower[:,:,2],+cmap='gray')
plt.axis("off")
plt.title("R+to+gray")

plt.show()|298429|[Result+images]|offset|length|298430|entityMap|0|LINK|mutability|MUTABLE|url|https://i.stack.imgur.com/Z54w9.png^0|0|0|0|0|0|F|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|X|8|@]|9|@]|A|$]]|$1|G|3|H|5|F|7|Y|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|Z|8|@]|9|@]|A|$B|C]]|$1|K|3|L|5|F|7|10|8|@]|9|@$M|11|N|12|1|13]]|A|$]]|$1|O|3|-4|5|F|7|14|8|@]|9|@]|A|$]]]|P|$Q|$5|R|S|T|A|$U|V]]]]

<pre><code>plt.imshow(img[:,:,0], cmap='gray')

plt.imshow(img[:,:,1], cmap='gray')

plt.imshow(img[:,:,2], cmap='gray')
</code></pre>
should work. But, the issue with this approach is that it is not true gray. It only changes one of RGB channel to gray.
look below.
<pre><code>from sklearn.datasets import load_sample_image
flower = load_sample_image(&quot;flower.jpg&quot;)

plt.subplot(1,4,1)
plt.imshow(flower)
plt.axis(&quot;off&quot;)
plt.title(&quot;Original&quot;)

# R level to gray
plt.subplot(1,4,2)
plt.imshow(flower[:,:,0], cmap='gray')
plt.axis(&quot;off&quot;)
plt.title(&quot;R to gray&quot;)


# G leval to gray
plt.subplot(1,4,3)
plt.imshow(flower[:,:,1], cmap='gray')
plt.axis(&quot;off&quot;)
plt.title(&quot;R to gray&quot;)

# B leval to gray
plt.subplot(1,4,4)
plt.imshow(flower[:,:,2], cmap='gray')
plt.axis(&quot;off&quot;)
plt.title(&quot;R to gray&quot;)

plt.show()
</code></pre>
<a href="https://i.stack.imgur.com/Z54w9.png" rel="nofollow noreferrer">[Result images]</a>

I'm trying to display a grayscale image using matplotlib.pyplot.imshow(). My problem is that the grayscale image is displayed as a colormap. I need the grayscale because I want to draw on top of the image with color.

I read in the image and convert to grayscale using PIL's Image.open().convert("L") 

<pre><code>image = Image.open(file).convert("L")</code></pre>

Then I convert the image to a matrix so that I can easily do some image processing using 

<pre><code>matrix = scipy.misc.fromimage(image, 0)</code></pre>

However, when I do 

<pre><code>figure() 
matplotlib.pyplot.imshow(matrix) 
show()</code></pre> 

it displays the image using a colormap (i.e. it's not grayscale).

What am I doing wrong here?

Display image as grayscale using matplotlib

我正在尝试使用matplotlib.pyplot.imshow().显示灰度图像我的问题是灰度图像显示为色彩映射表。我需要灰度，因为我想在图像上绘制颜色。我读取了图像并使用PIL的Image.open().convert("L")转换为灰度image = Image.open(file).convert("L")然后将...

问使用matplotlib将图像显示为灰度
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