Why Displaying images (cv2.imshow, matplotlib) in Computer Vision? - Purpose & Use Cases

The Big Idea

What if you could instantly see and compare hundreds of images without leaving your code?

The Scenario

Imagine you have hundreds of photos from a trip and you want to check each one to find the best shots. Opening each image manually one by one on your computer is tiring and slow.

The Problem

Manually opening images takes a lot of time and effort. You might miss details or make mistakes because it's hard to compare images quickly. Also, you can't easily add notes or see changes side by side.

The Solution

Using tools like cv2.imshow or matplotlib lets you quickly display images right inside your program. You can automate showing many images, compare them easily, and even add titles or annotations to understand them better.

Before vs After

✗ Before

Open each image file manually in a photo viewer.

✓ After

cv2.imshow('Image', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
plt.show()

What It Enables

This lets you instantly see and compare images during your work, making image analysis faster and more interactive.

Real Life Example

A photographer can quickly preview and compare hundreds of photos from a shoot inside a program, choosing the best ones without leaving the coding environment.

Key Takeaways

Manually viewing images is slow and error-prone.

Displaying images in code speeds up review and comparison.

Tools like cv2.imshow and matplotlib make image display easy and interactive.