Displaying images (cv2.imshow, matplotlib) in Computer Vision - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What does this OpenCV code display?

Consider the following Python code using OpenCV to display an image. What will the window show when this code runs?

Computer Vision

import cv2
import numpy as np

img = np.zeros((100, 100, 3), dtype=np.uint8)
img[25:75, 25:75] = [0, 255, 0]  # green square in the center
cv2.imshow('Test Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

A A white window with a red square in the center

B A white window with a green square in the center

C A black window with a red square in the center

D A black window with a green square in the center

💡 Hint

Remember that np.zeros creates a black image and the color is in BGR format.

The image is initialized as black (all zeros). The slice sets a square region to [0, 255, 0], which in BGR is green. So the window shows a black background with a green square.

❓ Predict Output

intermediate

What color does matplotlib show for this image array?

Given this code using matplotlib to display an image, what color will the square appear?

Computer Vision

import matplotlib.pyplot as plt
import numpy as np

img = np.zeros((100, 100, 3), dtype=np.uint8)
img[25:75, 25:75] = [0, 0, 255]  # red square in BGR
plt.imshow(img)
plt.show()

A A black window with a blue square in the center

B A black window with a green square in the center

C A black window with a red square in the center

D A black window with a yellow square in the center

💡 Hint

Matplotlib expects RGB format, but the array is in BGR.

The image array is in BGR format, but matplotlib expects RGB. So [0,0,255] in BGR is red, but matplotlib reads it as blue. The square appears blue on black.

❓ Model Choice

advanced

Choosing the right method to display images in a real-time video feed

You want to display frames from a live webcam feed with minimal delay and allow keyboard interaction to stop the feed. Which method is best?

A Use cv2.imshow with cv2.waitKey inside a loop

B Use print() to output pixel values to the console

C Save each frame as an image file and open it externally

D Use matplotlib.pyplot.imshow inside a loop with plt.show()

💡 Hint

Consider speed and ability to handle keyboard events.

cv2.imshow with cv2.waitKey is designed for fast image display and keyboard input in loops, ideal for real-time video. Matplotlib is slow and blocks execution.

❓ Metrics

advanced

Understanding the effect of cv2.waitKey argument on image display

What happens if you call cv2.waitKey(0) versus cv2.waitKey(1) after cv2.imshow?

A Both wait indefinitely for a key press

B cv2.waitKey(0) waits 0 ms; cv2.waitKey(1) waits indefinitely

C cv2.waitKey(0) waits indefinitely for a key press; cv2.waitKey(1) waits 1 ms and continues

D Both wait 1 ms and then continue

💡 Hint

Think about how waitKey controls the pause duration.

cv2.waitKey(0) pauses the program until a key is pressed. cv2.waitKey(1) pauses for 1 millisecond and then continues, useful for video loops.

🔧 Debug

expert

Why does this matplotlib image display show a distorted color?

You run this code to display an image loaded by OpenCV, but the colors look wrong. What is the cause?

Computer Vision

import cv2
import matplotlib.pyplot as plt

img = cv2.imread('image.jpg')
plt.imshow(img)
plt.show()

A Matplotlib cannot display images loaded from OpenCV

B OpenCV loads images in BGR format but matplotlib expects RGB, causing color distortion

C The image file is corrupted, causing wrong colors

D cv2.imread returns grayscale images by default, causing color issues

💡 Hint

Check the color channel order between OpenCV and matplotlib.

OpenCV loads images in BGR order, but matplotlib expects RGB. Without converting, colors appear distorted.