Display multiple images in one IPython Notebook cell?

Question

If I have multiple images (loaded as NumPy arrays) how can I display the in one IPython Notebook cell?

I know that I can use plt.imshow(ima) to display

Answer 1

This is easier and works:

from IPython.display import Image
from IPython.display import display
x = Image(filename='1.png') 
y = Image(filename='2.png') 
display(x, y)

Answer 2

Somehow related to this question (and since I was directed to this answer when I was trying to solve it), I was able to solve a similar problem by simply typing the full file-path when calling Image(). In my case, I had to choose a random image from different folder paths stored in a list your_folder and display them.

import random, os 
for i in range(len(your_folder)):
   ra1 = "../"+your_folder[i]+"/"+random.choice(os.listdir(your_folder[i]))
   image = Image(ra1)
   display(image)

Answer 3

from matplotlib.pyplot import figure, imshow, axis
from matplotlib.image import imread

mypath='.'
hSize = 5
wSize = 5
col = 4

def showImagesMatrix(list_of_files, col=10):
    fig = figure( figsize=(wSize, hSize))
    number_of_files = len(list_of_files)
    row = number_of_files/col
    if (number_of_files%col != 0):
        row += 1
    for i in range(number_of_files):
        a=fig.add_subplot(row,col,i+1)
        image = imread(mypath+'/'+list_of_files[i])
        imshow(image,cmap='Greys_r')
        axis('off')

showImagesMatrix(listOfImages,col)

based on @Michael answer

Answer 4

The answers in this thread helped me: Combine several images horizontally with Python

The problem of using matplotlib was the displayed images' definition was really bad. I adapted one of the answers there to my needs:

The following code displays the images concatenated horizontaly in a jupyter notebook. Notice the commented line with the code to save the image if you'd like that.

import numpy as np
import PIL
from IPython.display import display

list_im = ['Test1.jpg', 'Test2.jpg', 'Test3.jpg']
imgs    = [ PIL.Image.open(i) for i in list_im ]
# pick the image which is the smallest, and resize the others to match it (can be arbitrary image shape here)
min_shape = sorted( [(np.sum(i.size), i.size ) for i in imgs])[0][1]
imgs_comb = np.hstack( (np.asarray( i.resize(min_shape) ) for i in imgs ) )

# save that beautiful picture
imgs_comb = PIL.Image.fromarray( imgs_comb)
#imgs_comb.save( 'combo.jpg' )    

display(imgs_comb)