Image Blending OpenCV Python With Source Code
The Image Blending OpenCV Python was developed using Python OpenCV, This Project is Mixing up of two images. In this Article we will learn how image Blending works in OpenCV Python.
There are many designing tools out there, but our goal is to create a beautiful design without using any of those software in this project. After working on this project, you will also have an idea on how to work with the OpenCV package. It is a great skill to have, especially if you like computer vision. You can follow a similar structure when working on similar OpenCV projects.
What is OpenCV?
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.
In this Python OpenCV Project also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.
By the way if you are new to python programming and you don’t know what would be the the Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS that will suit for you. I also have here How to Download and Install Latest Version of Python on Windows.
To start executing Image Blending OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm on your computer.
Image Blending OpenCV Python With Source Code : Steps on how to run the project
Time needed: 5 minutes
These are the steps on how to run Image Blending OpenCV Python With Source Code
- Step 1: Download the given source code below.
First, download the given source code below and unzip the source code.
- Step 2: Import the project to your PyCharm IDE.
Next, import the source code you’ve download to your PyCharm IDE.
- Step 3: Run the project.
last, run the project with the command “py main.py”
Installed Libraries
import cv2 as cv import numpy as np from matplotlib import pyplot as plt
Complete Source Code
import cv2 as cv import numpy as np from matplotlib import pyplot as plt def blend(): ''' Image Blending Using Pyramid 1. Load two images 2. Find Gaussian Pyramids for two images. Upto 6 level 3. From Gaussian Pyramids,find their Laplacian Pyramids. 4. Now Join the images in each levels of laplacian P. 5. Finally from this joint image Pyramids, reconstruct the Original Image. ''' n1 = cv.imread("./img/nature1.jpg") n2 = cv.imread("./img/nature2.png") print(n1.shape) print(n2.shape) # n1_n2 = np.hstack((n1[:, :256], n2[:, 256:])) ''' Generate Gaussian Pyramid for Nature 1 ''' n1_copy = n1.copy() gp_n1 = [n1_copy] for i in range(6): n1_copy = cv.pyrDown(n1_copy) gp_n1.append(n1_copy) ''' Generate Gaussian Pyramid for Nature 2 ''' n2_copy = n2.copy() gp_n2 = [n2_copy] for i in range(6): n2_copy = cv.pyrDown(n2_copy) gp_n2.append(n2_copy) ''' Laplacian Pyramid for Nature 1 ''' n1_copy = gp_n1[5] lp_n1 = [n1_copy] for i in range(5, 0, -1): gp_ex = cv.pyrUp(gp_n1[i]) lap = cv.subtract(gp_n1[i-1], gp_ex) lp_n1.append(lap) ''' Laplacian Pyramid for Nature 2 ''' n2_copy = gp_n2[5] lp_n2 = [n2_copy] for i in range(5, 0, -1): gp_ex = cv.pyrUp(gp_n2[i]) lap = cv.subtract(gp_n2[i-1], gp_ex) lp_n2.append(lap) ''' Join Half the Pyramid ''' n1_n2_pyramid = [] n = 0 for n1_lap, n2_lap in zip(lp_n1, lp_n2): n += 1 cols, rows, ch = n1_lap.shape laplacian = np.hstack( (n1_lap[:, 0:int(cols/2)], n2_lap[:, int(cols/2):])) n1_n2_pyramid.append(laplacian) ''' Reconstruct ''' reconstruct = n1_n2_pyramid[0] for i in range(1, 6): reconstruct = cv.pyrUp(reconstruct) reconstruct = cv.add(n1_n2_pyramid[i], reconstruct) # cv.imshow("Nature 1", n1) # cv.imshow("Nature 2", n2) cv.imshow("N1_N2", reconstruct) cv.waitKey() cv.destroyAllWindows() if __name__ == "__main__": blend()
Output
Download Source Code below
Anyway, if you want to level up your programming knowledge, especially Python OpenCV, try this new article I’ve made for you Best OpenCV Projects With Source Code For Beginners 2021.
Summary
This Python OpenCV Project With Source Code was developed using Python OpenCV, and this Python code for image–blending based on an image mask. Python and the OpenCV library make it very easy to work with visual input such as images or videos
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Inquiries
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