How to best create a new image out of existing images in openCV

Question

I have several images which I want to aggregate in a new image 8 image per column, 5 per row side by side with openCV in Python.

Curiously, I did not find an answer which directly addresses this question. From my spare knowledge on openCV, I would now count the width and height of the image to which the existing images should be copied, create a numpy Array with these images and change the values of the corresponding regions of Pinterest to values of each image.

Would this procedure work and more important isn't there an easier solution for this problem which haven't found?

Answer 1

When images are read in OpenCV's Python API, you get Numpy arrays. Numpy has vstack() and hstack() functions, which you can use to stack arrays (images) vertically and horizontally.

Let's open up two images with OpenCV:

import cv2
import numpy as np

knight = cv2.imread('knight.jpg', cv2.IMREAD_GRAYSCALE)

To use stacking in numpy, there are restriction on the image dimensions depending on the stackng axis (vertical/horizontal), so for this image, I will use cv2.resize() to get the right dimensions

queen = cv2.imread('queen.jpg', cv2.IMREAD_GRAYSCALE)
queen = cv2.resize(queen, (525, 700))

Let's make a first column by stacking 2 Knights

col_1 = np.vstack([knight, knight]) # Simply put the images in the list
                                    # I've put 2 knights as example

Now let's make a second column with 2 Queens

col_2 = np.vstack([queen, queen])

Let's put those two columns together, but this time we'll use hstack() for that

collage = np.hstack([col_1, col_2]

Et voila, a collage of 2 x 2 which you can adapt to your needs. Note that the images passed in the stacking do need to be identical or anything, you can pass in any list of images, as long as you respect the dimensions.