31.7. Read and Display an Image Using Python

Program Objective: Read and display an image using OpenCV.

This chunk provides the objective of the program: to read and display an image using the OpenCV library in Python. OpenCV (Open Source Computer Vision Library) is a powerful tool for image processing and computer vision tasks. The primary goal here is to understand how to import an image file and then display it on the screen.

Imagine you have a photo on your computer, and you want to open and view it. Just like you would use an image viewer application to double-click the file and see your photo, in programming, we can write code that tells the computer how to open and display the image using OpenCV.

Code:

import cv2
# Replace 'image.jpg' with the actual image filename
img = cv2.imread('image.jpg')

In this chunk, we see the actual code needed to read an image. The 'cv2.imread()' function is used to load the image file. The string 'image.jpg' needs to be replaced with the name of your actual image file. This function will read the image from your computer and store it as a variable (in this case, 'img') for further processing.

Think of this as putting a photo into your hands before you can show it to someone. You need to pick it up (read it) from somewhere (your computer), and this code is how you pick it up in programming.

Code:

# Display the image
cv2.imshow('Displayed Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

After reading the image, you need to display it using 'cv2.imshow()'. This function creates a window that shows the image, where 'Displayed Image' is the title of the window. The 'cv2.waitKey(0)' function pauses the execution until a key is pressed, ensuring the image window stays open. Finally, 'cv2.destroyAllWindows()' closes all opened image windows, cleaning up after displaying the image.

Consider this step like opening a photo viewer on your computer. After you load a picture, you want it to be visible for a while until you decide to close it. Just like how you press 'Esc' or 'Close' on the viewer, in the same way, this code manages to show and eventually close the image display.

⚠️ If you're using a Jupyter notebook, use cv2.imshow() with caution. Alternatively, display using matplotlib:

import matplotlib.pyplot as plt
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.axis('off')
plt.show()

For users running code in a Jupyter notebook, using 'cv2.imshow()' might not work as expected, so it's better to use the Matplotlib library to display images. The 'cv2.cvtColor()' function is used to convert the image color format from BGR (which OpenCV uses) to RGB (which Matplotlib uses). The functions 'plt.axis('off')' removes the axis markings for a cleaner look, and 'plt.show()' displays the image. This is useful when you want to visualize your image in a notebook environment.

Think of Jupyter notebooks as a digital scrapbook where you can mix text, images, and code. Using Matplotlib to display images is like creatively placing your photos in the scrapbook without the clutter of tool markings and edges, focusing solely on the images you want to show.

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