Merge two images Python OpenCV

Question

Use cv2.vconcat(),

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

0 to concatenate (combine) images vertically and horizontally with Python, OpenCV.

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

1 means vertical and

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

2 means horizontal.

Table of Contents Show

Concatenate vertically: cv2.vconcat()
Concatenate images of the same width vertically
Repeat the same image vertically
Concatenate images of different widths vertically
Concatenate horizontally: im_v = cv2.vconcat([im1, im1]) cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v) 0
Concatenate images of the same height horizontally
Repeat the same image horizontally
Concatenate images of different heights horizontally
Concatenate vertically and horizontally (like tiles)
Concatenate images of the same size vertically and horizontally
Concatenate same images vertically and horizontally
Concatenate images of different sizes in vertical and horizontal tiles
How to merge two images in OpenCV Python?
How do I put two pictures together in OpenCV?
How to combine 2 images into one Python?
How do I blend images in OpenCV Python?

Pass a list of images (

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

3), an image (

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

3) in which the images in the list are vertically or horizontally concatenated is returned. Images with different sizes need to be resized beforehand. An error is raised if the width or height is not aligned.

This article describes the following contents with sample codes.

Concatenate vertically: cv2.vconcat()

Concatenate horizontally:

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

0

Concatenate vertically and horizontally (like tiles)

Read two images as an example.

import cv2
import numpy as np

im1 = cv2.imread('data/src/lena.jpg')
im2 = cv2.imread('data/src/rocket.jpg')

source:

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

7 is convenient when arranging the same image repeatedly.

NumPy: Arrange ndarray in tiles with np.tile()

For more information on image concatenation using Pillow and scikit-image, see the following articles. For images of the same size, scikit-image is easy to use. You can also add a border between the images.

Concatenate images with Python, Pillow
Create a montage of images with Python, scikit-image (skimage.util.montage)

Concatenate vertically: cv2.vconcat()

Concatenate images of the same width vertically

When concatenating images of the same width vertically, cv2.vconcat() can be used as it is.

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

source:

Repeat the same image vertically

You can use

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

0 as well if you arrange the same image repeatedly.

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

source:

Concatenate images of different widths vertically

It is useful to define a function to combine images of different widths. Here, the bigger one is resized.

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

1 represents height and

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

2 represents width.

Get image size (width, height) with Python, OpenCV, Pillow (PIL)

def vconcat_resize_min(im_list, interpolation=cv2.INTER_CUBIC):
    w_min = min(im.shape[1] for im in im_list)
    im_list_resize = [cv2.resize(im, (w_min, int(im.shape[0] * w_min / im.shape[1])), interpolation=interpolation)
                      for im in im_list]
    return cv2.vconcat(im_list_resize)

im_v_resize = vconcat_resize_min([im1, im2, im1])
cv2.imwrite('data/dst/opencv_vconcat_resize.jpg', im_v_resize)

source:

List comprehensions are used to create a list of resized images.

List comprehensions in Python

Concatenate horizontally: im_v = cv2.vconcat([im1, im1]) cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v) 0

The horizontal case is basically the same concept as the vertical case.

Concatenate images of the same height horizontally

When concatenating images of the same height horizontally,

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

0 can be used as it is.

im_h = cv2.hconcat([im1, im1])
cv2.imwrite('data/dst/opencv_hconcat.jpg', im_h)

source:

Repeat the same image horizontally

You can use

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

0 as well if you arrange the same image repeatedly.

im_h_np = np.tile(im1, (1, 2, 1))
cv2.imwrite('data/dst/opencv_hconcat_np.jpg', im_h_np)

source:

Concatenate images of different heights horizontally

As with vertical concatenation, it is useful to define a function to combine images of different sizes. Here, the bigger one is resized.

def hconcat_resize_min(im_list, interpolation=cv2.INTER_CUBIC):
    h_min = min(im.shape[0] for im in im_list)
    im_list_resize = [cv2.resize(im, (int(im.shape[1] * h_min / im.shape[0]), h_min), interpolation=interpolation)
                      for im in im_list]
    return cv2.hconcat(im_list_resize)

im_h_resize = hconcat_resize_min([im1, im2, im1])
cv2.imwrite('data/dst/opencv_hconcat_resize.jpg', im_h_resize)

source:

Concatenate vertically and horizontally (like tiles)

Concatenate images of the same size vertically and horizontally

Using cv2.vconcat() and

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

0, images can be concatenated vertically and horizontally in tile form.

A function that concatenates images of the same size with a 2D list (array) can be defined as follows:

def concat_tile(im_list_2d):
    return cv2.vconcat([cv2.hconcat(im_list_h) for im_list_h in im_list_2d])

im1_s = cv2.resize(im1, dsize=(0, 0), fx=0.5, fy=0.5)
im_tile = concat_tile([[im1_s, im1_s, im1_s, im1_s],
                       [im1_s, im1_s, im1_s, im1_s],
                       [im1_s, im1_s, im1_s, im1_s]])
cv2.imwrite('data/dst/opencv_concat_tile.jpg', im_tile)

source:

The example uses the same image for simplicity, but it is useful when comparing the results of changing the image processing coefficients.

Concatenate same images vertically and horizontally

When arranging the same image repeatedly,

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

0 can be used as before.

When concatenating color images (3D

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

3), set the second parameter (

def vconcat_resize_min(im_list, interpolation=cv2.INTER_CUBIC):
    w_min = min(im.shape[1] for im in im_list)
    im_list_resize = [cv2.resize(im, (w_min, int(im.shape[0] * w_min / im.shape[1])), interpolation=interpolation)
                      for im in im_list]
    return cv2.vconcat(im_list_resize)

im_v_resize = vconcat_resize_min([im1, im2, im1])
cv2.imwrite('data/dst/opencv_vconcat_resize.jpg', im_v_resize)

0) to

def vconcat_resize_min(im_list, interpolation=cv2.INTER_CUBIC):
    w_min = min(im.shape[1] for im in im_list)
    im_list_resize = [cv2.resize(im, (w_min, int(im.shape[0] * w_min / im.shape[1])), interpolation=interpolation)
                      for im in im_list]
    return cv2.vconcat(im_list_resize)

im_v_resize = vconcat_resize_min([im1, im2, im1])
cv2.imwrite('data/dst/opencv_vconcat_resize.jpg', im_v_resize)

1. For grayscale images (2D

im_v = cv2.vconcat([im1, im1])
cv2.imwrite('data/dst/opencv_vconcat.jpg', im_v)

3), set

def vconcat_resize_min(im_list, interpolation=cv2.INTER_CUBIC):
    w_min = min(im.shape[1] for im in im_list)
    im_list_resize = [cv2.resize(im, (w_min, int(im.shape[0] * w_min / im.shape[1])), interpolation=interpolation)
                      for im in im_list]
    return cv2.vconcat(im_list_resize)

im_v_resize = vconcat_resize_min([im1, im2, im1])
cv2.imwrite('data/dst/opencv_vconcat_resize.jpg', im_v_resize)

0 to

def vconcat_resize_min(im_list, interpolation=cv2.INTER_CUBIC):
    w_min = min(im.shape[1] for im in im_list)
    im_list_resize = [cv2.resize(im, (w_min, int(im.shape[0] * w_min / im.shape[1])), interpolation=interpolation)
                      for im in im_list]
    return cv2.vconcat(im_list_resize)

im_v_resize = vconcat_resize_min([im1, im2, im1])
cv2.imwrite('data/dst/opencv_vconcat_resize.jpg', im_v_resize)

4.

See the following article for more information on

im_v_np = np.tile(im1, (2, 1, 1))
cv2.imwrite('data/dst/opencv_vconcat_np.jpg', im_v_np)

0.

NumPy: Arrange ndarray in tiles with np.tile()

Concatenate images of different sizes in vertical and horizontal tiles

When concatenating images of different sizes in vertical and horizontal tiles, use the resizing and concatenating function defined above.

How to merge two images in OpenCV Python?

To concatenate images vertically and horizontally with Python, cv2 library comes with two functions as:.

hconcat(): It is used as cv2. hconcat() to concatenate images horizontally. Here h means horizontal..

vconcat(): It is used as cv2. vconcat() to concatenate images vertically. Here v means vertical..

How do I put two pictures together in OpenCV?

You can add two images with the OpenCV function, cv. add(), or simply by the numpy operation res = img1 + img2. Both images should be of same depth and type, or the second image can just be a scalar value.

How to combine 2 images into one Python?

Merging two images Create an empty image using the Image. new() function. Paste the images using the paste() function. Save and display the resultant image using the save() and show() functions.

How do I blend images in OpenCV Python?

Like before, we start by importing the cv2 module, followed by reading both images and resizing them to be 400×400. We will then display the second image in a window called “blend“. It will be the one we will use every time we update the weights to display the resulting image.