CODEWITHSUNDEEP
pythonarraysimagenumpydata-visualization
jlswint
jlswint

Reputation: 3883

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

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)

Upvotes: 378

Views: 944118

Answers (11)

Steve Tjoa
Steve Tjoa

Reputation: 61044

Use plt.imshow to create the figure, and plt.show to display it:

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

For Jupyter notebooks, add this line before importing matplotlib:

%matplotlib inline

For interactive plots in Jupyter [demo], install ipyml pip install ipympl, then use:

%matplotlib widget

Upvotes: 446

Peter Hansen
Peter Hansen

Reputation: 22047

Note: both these APIs have been first deprecated, then removed.

Shortest path is to use scipy, like this:

# Note: deprecated in v0.19.0 and removed in v1.3.0
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:

# Note: deprecated in v1.0.0 and removed in v1.8.0
from scipy.misc import imshow
imshow(data)

Upvotes: 53

abbujaansboy
abbujaansboy

Reputation: 99

For example your image is in an array names 'image'

All you do is

plt.imshow(image)
plt.show

This will display an array in the form of an image Also, dont forget to import PLT

Upvotes: 4

Aman Bagrecha
Aman Bagrecha

Reputation: 436

this could be a possible code solution:

from skimage import io
import numpy as np
data=np.random.randn(5,2)
io.imshow(data)

Upvotes: 0

Hrvoje
Hrvoje

Reputation: 15162

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:

enter image description here

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=' ')

Upvotes: 19

Sivasai
Sivasai

Reputation: 99

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

Upvotes: 9

user140536
user140536

Reputation: 164

Supplement for doing so with matplotlib. I found it handy doing computer vision tasks. Let's say you got data with dtype = int32

from matplotlib import pyplot as plot
import numpy as np

fig = plot.figure()
ax = fig.add_subplot(1, 1, 1)
# make sure your data is in H W C, otherwise you can change it by
# data = data.transpose((_, _, _))
data = np.zeros((512,512,3), dtype=np.int32)
data[256,256] = [255,0,0]
ax.imshow(data.astype(np.uint8))

Upvotes: 3

unutbu
unutbu

Reputation: 879561

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()

Upvotes: 359

user3322286
user3322286

Reputation: 119

Using pillow's fromarray, for example:

from PIL import Image
from numpy import *

im = array(Image.open('image.jpg'))
Image.fromarray(im).show()

Upvotes: 9

ars
ars

Reputation: 123508

The Python Imaging Library can display images using Numpy arrays. Take a look at this page for sample code:

EDIT: As the note on the bottom of that page says, you should check the latest release notes which make this much simpler:

http://effbot.org/zone/pil-changes-116.htm

Upvotes: 0

Stefan Kendall
Stefan Kendall

Reputation: 67832

Using pygame, you can open a window, get the surface as an array of pixels, and manipulate as you want from there. You'll need to copy your numpy array into the surface array, however, which will be much slower than doing actual graphics operations on the pygame surfaces themselves.

Upvotes: 7

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