How do I convert a numpy array to (and display) an image?

Question

I have created an array thusly:

import numpy as np
data = np.zeros( (512,512,3), dtype=np.uint8)
data[256,256] = [255,0,0]

What I want this to do is display a single red dot in the center of a 512x512 image. (At least to begin with... I think I can figure out the rest from there)

Solution 1

You could use PIL to create (and display) an image:

from PIL import Image
import numpy as np

w, h = 512, 512
data = np.zeros((h, w, 3), dtype=np.uint8)
data[0:256, 0:256] = [255, 0, 0] # red patch in upper left
img = Image.fromarray(data, 'RGB')
img.save('my.png')
img.show()

Solution 2

The following should work:

from matplotlib import pyplot as plt
plt.imshow(data, interpolation='nearest')
plt.show()

If you are using Jupyter notebook/lab, use this inline command before importing matplotlib:

%matplotlib inline 

A more featureful way is to install ipyml pip install ipympl and use

%matplotlib widget 

see an example.

Solution 3

Shortest path is to use scipy, like this:

from scipy.misc import toimage
toimage(data).show()

This requires PIL or Pillow to be installed as well.

A similar approach also requiring PIL or Pillow but which may invoke a different viewer is:

from scipy.misc import imshow
imshow(data)

Solution 4

How to show images stored in numpy array with example (works in Jupyter notebook)

I know there are simpler answers but this one will give you understanding of how images are actually drawn from a numpy array.

Load example

from sklearn.datasets import load_digits
digits = load_digits()
digits.images.shape   #this will give you (1797, 8, 8). 1797 images, each 8 x 8 in size

Display array of one image

digits.images[0]
array([[ 0.,  0.,  5., 13.,  9.,  1.,  0.,  0.],
       [ 0.,  0., 13., 15., 10., 15.,  5.,  0.],
       [ 0.,  3., 15.,  2.,  0., 11.,  8.,  0.],
       [ 0.,  4., 12.,  0.,  0.,  8.,  8.,  0.],
       [ 0.,  5.,  8.,  0.,  0.,  9.,  8.,  0.],
       [ 0.,  4., 11.,  0.,  1., 12.,  7.,  0.],
       [ 0.,  2., 14.,  5., 10., 12.,  0.,  0.],
       [ 0.,  0.,  6., 13., 10.,  0.,  0.,  0.]])

Create empty 10 x 10 subplots for visualizing 100 images

import matplotlib.pyplot as plt
fig, axes = plt.subplots(10,10, figsize=(8,8))

Plotting 100 images

for i,ax in enumerate(axes.flat):
    ax.imshow(digits.images[i])

Result:

What does axes.flat do? It creates a numpy enumerator so you can iterate over axis in order to draw objects on them. Example:

import numpy as np
x = np.arange(6).reshape(2,3)
x.flat
for item in (x.flat):
    print (item, end=' ')

Solution 5

import numpy as np
from keras.preprocessing.image import array_to_img
img = np.zeros([525,525,3], np.uint8)
b=array_to_img(img)
b

View more solutions

Comments

[GaryO]

This is more accurate than PIL. PIL rescales/normalizes the array values, whereas pyplot uses the actual RGB values as they are.

[fdermishin]

It seems that there is a bug. You create array with size (w,h,3), but it should be (h,w,3), because indexing in PIL differs from indexing in numpy. There is related question: stackoverflow.com/questions/33725237/…

[unutbu]

@user502144: Thanks for pointing out my error. I should have created an array of shape (h,w,3). (It's now fixed, above.) The length of the first axis can be thought of as the number of rows in the array, and the length of the second axis, the number of columns. So (h, w) corresponds to an array of "height" h and "width" w. Image.fromarray converts this array into an image of height h and width w.

[Chris]

So this method is incompatible with python 3.5...?

[Peter Hansen]

@bordeo, why would it be incompatible with 3.5? It just an import and a couple of function calls.

[Chris]

PIL is incompatible with 3.5 (won't install)

[dtk]

Ftr: you can shorten this further by directly using scipy.misc.imshow(data).

[Cerno]

Maybe good to know: If you want to display grayscale images, it is advisable to call plt.gray() once in your code to switch all following graphs to grayscale. Not what the OP wants but good to know nevertheless.

[john ktejik]

this doesn't answer the question

[user334639]

How to save it?

[Mona Jalal]

File "<ipython-input-29-29c784f62838>", line 39 plt.show() ^ SyntaxError: invalid syntax

[mrgloom]

img.show() don't work in ipython notebook.img_pil = Image.fromarray(img, 'RGB') display(img_pil.resize((256,256), PIL.Image.LANCZOS))

[Sid]

toimage was deprecated in scipy-1.0.0 and removed in 1.2.0, in favor of Pillow’s Image.fromarray.

[Josiah Yoder]

@Cerno Also, grayscale images should have shape(h, w) rather than (h, w, 1). You can use squeeze() to eliminate the third dimension: plt.imshow(data.squeeze())

[Ludovico Verniani]

@unutbu this method seems to distort images ... stackoverflow.com/questions/62293077/…

[raphinesse]

Having Image.fromarray(...) as the last expression of a cell sufficed to display the image for me in Google Colab. No need to write to a file or call .show().

[kbridge4096]

scipy.misc.imshow() is deprecated. Use matplotlib.pyplot.imshow(data) instead. Also, in IPython, you need to run matplotlib.pyplot.show() to show the image display window.