{"id":128171,"date":"2022-09-16T15:45:26","date_gmt":"2022-09-16T15:45:26","guid":{"rendered":"https:\/\/blog.finxter.com\/?p=682461"},"modified":"2022-09-16T15:45:26","modified_gmt":"2022-09-16T15:45:26","slug":"combine-images-using-numpy","status":"publish","type":"post","link":"https:\/\/sickgaming.net\/blog\/2022\/09\/16\/combine-images-using-numpy\/","title":{"rendered":"Combine Images Using Numpy"},"content":{"rendered":"\n
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Rate this post<\/span> <\/div>\n<\/div>\n

Summary: <\/strong>You can combine images represented in the form of Numpy arrays using the concatenate<\/code> function of the Numpy library as np.concatenate((numpydata_1, numpydata_2), axis=1)<\/code>. This combines the images horizontally. Use syntax: np.concatenate((numpydata_1, numpydata_2), axis=0)<\/code> to combine the images vertically.<\/p>\n

Problem Formulation<\/strong><\/h2>\n

Consider you have two images represented as Numpy arrays of pixels. How will you combine the two images represented in the form of Numpy pixel arrays?<\/p>\n

Combining two images that are in the form of Numpy arrays will create a new Numpy array having pixels that will represent a new combined image formed by either concatenating the two images horizontally or vertically. Let’s understand this with the help of an example:<\/p>\n

Given: <\/strong>Let’s say we have two different images as given below (Both images have similar dimensions)<\/em> –<\/p>\n

\n
\"\"
img_1.JPG<\/strong><\/figcaption><\/figure>\n
\"\"
img_2.JPG<\/strong><\/figcaption><\/figure>\n<\/figure>\n

When you convert them to Numpy arrays this is how you can represent the two images: <\/p>\n

\n\n\n\n\n
numpydata_1<\/strong><\/td>\nnumpydata_2<\/strong><\/td>\n<\/tr>\n
[[[184 186 201]
[184 186 201]
[184 187 202]
…
[174 189 218]
[174 189 218]
[173 188 217]]<\/p>\n

[[184 186 201]
[184 186 201]
[184 187 202]
…
[174 189 218]
[173 188 217]
[173 188 217]]<\/p>\n

[[183 186 203]
[183 186 203]
[184 187 204]
…
[173 188 217]
[173 188 217]
[172 187 216]]<\/p>\n

…<\/p>\n

[[ 43 64 55]
[ 45 66 57]
[ 48 69 60]
…
[ 63 84 77]
[ 64 83 77]
[ 64 83 77]]<\/p>\n

[[ 49 70 61]
[ 50 71 62]
[ 53 73 64]
…
[ 58 84 73]
[ 60 83 73]
[ 61 84 74]]<\/p>\n

[[ 53 74 65]
[ 52 73 64]
[ 56 73 65]
…
[ 56 84 72]
[ 57 83 72]
[ 57 83 72]]]<\/td>\n

[[[255 255 255]
[255 255 255]
[255 255 255]
…
[242 245 252]
[240 243 250]
[241 244 251]]<\/p>\n

[[255 255 255]
[255 255 255]
[255 255 255]
…
[242 245 252]
[241 244 251]
[241 244 251]]<\/p>\n

[[255 255 255]
[255 255 255]
[255 255 255]
…
[243 246 253]
[243 246 253]
[241 244 251]]<\/p>\n

…<\/p>\n

[[115 152 144]
[111 151 142]
[ 96 142 131]
…
[ 72 108 106]
[ 73 109 107]
[ 77 113 111]]<\/p>\n

[[ 75 118 108]
[ 79 125 114]
[ 82 132 120]
…
[ 69 104 100]
[ 69 104 100]
[ 71 106 102]]<\/p>\n

[[ 42 90 78]
[ 47 97 85]
[ 64 116 103]
…
[ 65 97 94]
[ 60 92 89]
[ 64 96 93]]]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

Challenge: <\/strong>Combine the two images – (i) horizontally (ii) vertically<\/p>\n

Expected Output:<\/strong><\/p>\n

\n\n\n\n\n
Horizontal Combination<\/strong><\/td>\nVertical Combination<\/strong><\/td>\n<\/tr>\n
[[[184 186 201]
[184 186 201]
[184 187 202]
\u2026
[242 245 252]
[240 243 250]
[241 244 251]]
[[184 186 201]
[184 186 201]
[184 187 202]
\u2026
[242 245 252]
[241 244 251]
[241 244 251]]
[[183 186 203]
[183 186 203]
[184 187 204]
\u2026
[243 246 253]
[243 246 253]
[241 244 251]]
\u2026
[[ 43 64 55]
[ 45 66 57]
[ 48 69 60]
\u2026
[ 72 108 106]
[ 73 109 107]
[ 77 113 111]]
[[ 49 70 61]
[ 50 71 62]
[ 53 73 64]
\u2026
[ 69 104 100]
[ 69 104 100]
[ 71 106 102]]
[[ 53 74 65]
[ 52 73 64]
[ 56 73 65]
\u2026
[ 65 97 94]
[ 60 92 89]
[ 64 96 93]]]<\/td>\n		[[[184 186 201]
[184 186 201]
[184 187 202]
\u2026
[174 189 218]
[174 189 218]
[173 188 217]]
[[184 186 201]
[184 186 201]
[184 187 202]
\u2026
[174 189 218]
[173 188 217]
[173 188 217]]
[[183 186 203]
[183 186 203]
[184 187 204]
\u2026
[173 188 217]
[173 188 217]
[172 187 216]]
\u2026
[[115 152 144]
[111 151 142]
[ 96 142 131]
\u2026
[ 72 108 106]
[ 73 109 107]
[ 77 113 111]]
[[ 75 118 108]
[ 79 125 114]
[ 82 132 120]
\u2026
[ 69 104 100]
[ 69 104 100]
[ 71 106 102]]
[[ 42 90 78]
[ 47 97 85]
[ 64 116 103]
\u2026
[ 65 97 94]
[ 60 92 89]
[ 64 96 93]]]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

So, are you up for the challenge? Well! If it looks daunting – don’t worry. This tutorial will guide you through the techniques to solve the programming challenge. So, without further delay let us dive into the solution.<\/p>\n

Prerequisite:<\/strong> To understand how the solutions to follow work it is essential to understand – “How to concatenate two Numpy arrays in Python.”<\/p>\n

NumPy\u2019s\u00a0concatenate()<\/a><\/code>\u00a0method joins a sequence of arrays along an existing axis. The first couple of comma-separated array arguments are joined. If you use the axis argument, you can specify along which axis the arrays should be joined. For example,\u00a0np.concatenate(a, b, axis=0)<\/code>\u00a0joins arrays along the first axis and\u00a0np.concatenate(a, b, axis=None)<\/code>\u00a0joins the flattened arrays. <\/p>\n

To learn more about concatenating arrays in Python, here’s a wonderful tutorial that will guide you through numerous methods of doing so: How to Concatenate Two NumPy Arrays?<\/a><\/strong><\/p>\n

Combine Images “Horizontally” with Numpy<\/h2>\n

Approach: <\/strong>The concatenate()<\/code> method of the Numpy library allows you combine matrices of different images along different axes. To combine the two image arrays horizontally, you must specify the axis=1<\/strong>. <\/p>\n

Code:<\/strong> Please go through the comments mentioned in the script in order to understand how each line of code works.<\/p>\n

from PIL import Image\nimport numpy as np\n# Reading the given images img_1 = Image.open('img_1.JPG')\nimg_2 = Image.open('img_2.JPG')\n# Converting the two images into Numpy Arrays\nnumpydata_1 = np.asarray(img_1)\nnumpydata_2 = np.asarray(img_2)\n# Combining the two images horizontally\nhorizontal = np.concatenate((numpydata_1, numpydata_2), axis=1)\n# Display the horizontally combined image as a Numpy Array\nprint(horizontal)\n# converting the combined image in the Numpy Array form to an image format\ndata = Image.fromarray(horizontal)\n# Saving the combined image\ndata.save('combined_pic.png')<\/pre>\n
Output:<\/strong><\/p>\n
[[[184 186 201] [184 186 201] [184 187 202] ... [242 245 252] [240 243 250] [241 244 251]] [[184 186 201] [184 186 201] [184 187 202] ... [242 245 252] [241 244 251] [241 244 251]] [[183 186 203] [183 186 203] [184 187 204] ... [243 246 253] [243 246 253] [241 244 251]] ... [[ 43 64 55] [ 45 66 57] [ 48 69 60] ... [ 72 108 106] [ 73 109 107] [ 77 113 111]] [[ 49 70 61] [ 50 71 62] [ 53 73 64] ... [ 69 104 100] [ 69 104 100] [ 71 106 102]] [[ 53 74 65] [ 52 73 64] [ 56 73 65] ... [ 65 97 94] [ 60 92 89] [ 64 96 93]]]<\/pre>\n
Here’s how the horizontally combined image looks like when saved to a file:<\/p>\n
\"\"<\/figure>\n
Wonderful! Isn’t it?<\/p>\n
Combine Images “Vertically” with Numpy<\/strong><\/h2>\n
In the previous solution, we combined the images horizontally. In this soution you will learn how to combine two images represented in the form of Numpy arrays vertically. <\/p>\n
Approach: <\/strong>The idea is quite similar to the previous solution with the only difference in the axis<\/em> parameter of the concatenate()<\/code> method. To combine the two image arrays vertically, you must specify the axis=0<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
from PIL import Image\nimport numpy as np\n# Reading the given images\nimg_1 = Image.open('img_1.JPG')\nimg_2 = Image.open('img_2.JPG')\n# Converting the two images into Numpy Arrays\nnumpydata_1 = np.asarray(img_1)\nnumpydata_2 = np.asarray(img_2)\n# Combining the two images horizontally\nvertical = np.concatenate((numpydata_1, numpydata_2), axis=0)\n# Display the vertically combined image as a Numpy Array\nprint(vertical)\n# converting the combined image in the Numpy Array form to an image format\ndata = Image.fromarray(vertical)\n# Saving the combined image\ndata.save('combined_pic.png')<\/pre>\n
Output:<\/strong><\/p>\n
\n[[[184 186 201] [184 186 201] [184 187 202] ... [174 189 218] [174 189 218] [173 188 217]] [[184 186 201] [184 186 201] [184 187 202] ... [174 189 218] [173 188 217] [173 188 217]] [[183 186 203] [183 186 203] [184 187 204] ... [173 188 217] [173 188 217] [172 187 216]] ... [[115 152 144] [111 151 142] [ 96 142 131] ... [ 72 108 106] [ 73 109 107] [ 77 113 111]] [[ 75 118 108] [ 79 125 114] [ 82 132 120] ... [ 69 104 100] [ 69 104 100] [ 71 106 102]] [[ 42 90 78] [ 47 97 85] [ 64 116 103] ... [ 65 97 94] [ 60 92 89] [ 64 96 93]]]<\/pre>\n
Here’s how the horizontally combined image looks like when saved to a file:<\/p>\n
\"\"<\/figure>\n
Hurrah! We have successfully combined the two images vertically.<\/p>\n
Exercises<\/strong><\/h2>\n
Before we wrap this tutorial, here’s a set of challenges to further enhance your knowledge.<\/p>\n
Challenge 1: <\/strong>Consider that you have been given an image. How will you convert this image to a Numpy array?<\/p>\n
Given Image<\/strong><\/strong><\/p>\n
\"\"<\/figure>\n
Solution:<\/strong><\/p>\n
from PIL import Image\nfrom numpy import asarray\nimg = Image.open('img.png')\nimg_to_array = asarray(img)\nprint(img_to_array)<\/pre>\n
Challenge 2: <\/strong>Consider that you have two images of different dimensions. How will you combine the two images horizontally using OpenCV?<\/p>\n
Given Images:<\/p>\n
\"\"
Image_1.png<\/figcaption><\/figure>\n
\"\"
Image_2.png<\/figcaption><\/figure>\n
Solution:<\/strong><\/p>\n
import cv2\nimport numpy as np\nimg_1 = cv2.imread('Imgage_1.png')\nimg_2 = cv2.imread('Image_2.png')\nh1, w1 = img_1.shape[:2]\nh2, w2 = img_2.shape[:2]\nimg_3 = np.zeros((max(h1, h2), w1 + w2, 3), dtype=np.uint8)\nimg_3[:, :] = (255, 255, 255)\nimg_3[:h1, :w1, :3] = img_1\nimg_3[:h2, w1:w1 + w2, :3] = img_2\ncv2.imwrite('Img_3.png', img_3)<\/pre>\n
Output:<\/strong><\/p>\n
\"\"
Img_3.png<\/figcaption><\/figure>\n
Want to learn about OpenCV? Here’s an amazing tutorial to get you started with OpenCV – Python OpenCV Image Processing<\/a><\/strong>.<\/p>\n
Conclusion<\/strong><\/h2>\n
Phew! That was some coding challenge! I hope you can now successfully combine images given as Numpy arrays in both dimensions – horizontally as well as vertically. With that we come to the end of this tutorial. Please subscribe and stay tuned for more interesting tutorials and solutions in the future. <\/p>\n
Happy coding! \"\ud83d\ude42\"<\/p>\n
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Rate this post Summary: You can combine images represented in the form of Numpy arrays using the concatenate function of the Numpy library as np.concatenate((numpydata_1, numpydata_2), axis=1). This combines the images horizontally. Use syntax: np.concatenate((numpydata_1, numpydata_2), axis=0) to combine the images vertically. Problem Formulation Consider you have two images represented as Numpy arrays of pixels. […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[857],"tags":[73,468,528],"class_list":["post-128171","post","type-post","status-publish","format-standard","hentry","category-python-tut","tag-programming","tag-python","tag-tutorial"],"_links":{"self":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts\/128171","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/comments?post=128171"}],"version-history":[{"count":0,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/posts\/128171\/revisions"}],"wp:attachment":[{"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/media?parent=128171"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/categories?post=128171"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sickgaming.net\/blog\/wp-json\/wp\/v2\/tags?post=128171"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}