Displaying images (cv2.imshow, matplotlib) in Computer Vision - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does cv2.imshow() do in image processing?

cv2.imshow() opens a window to display an image using OpenCV. It shows the image until a key is pressed.

beginner

How do you display an image using matplotlib?

Use plt.imshow() to show the image and plt.show() to display the window with the image.

intermediate

Why might images look different when displayed with cv2.imshow() vs matplotlib.pyplot.imshow()?

OpenCV uses BGR color order, while matplotlib uses RGB. Without converting colors, images may look strange in matplotlib.

beginner

What function is used to wait for a key press in OpenCV after showing an image?

cv2.waitKey() pauses the program and waits for a key press. It is needed to keep the image window open.

beginner

How do you close all OpenCV image windows programmatically?

Use cv2.destroyAllWindows() to close all windows opened by OpenCV.

Which function displays an image in a window using OpenCV?

A plt.showimage()

B plt.imshow()

C cv2.showimage()

D cv2.imshow()

cv2.imshow() is the correct OpenCV function to display images.

What must you call after cv2.imshow() to keep the window open until a key is pressed?

A cv2.waitKey()

B plt.show()

C cv2.destroyAllWindows()

D cv2.close()

cv2.waitKey() waits for a key press and keeps the window open.

Why do images sometimes appear with wrong colors in matplotlib after loading with OpenCV?

A OpenCV loads images in BGR format, matplotlib expects RGB

B Matplotlib cannot display color images

C OpenCV images are grayscale only

D Matplotlib requires images in grayscale

OpenCV uses BGR color order, so colors look wrong in matplotlib unless converted to RGB.

Which matplotlib function actually shows the image window?

A cv2.imshow()

B plt.show()

C plt.imshow()

D plt.display()

plt.show() displays the image window after plt.imshow() sets the image.

How do you close all OpenCV windows after displaying images?

A cv2.closeAll()

B plt.close()

C cv2.destroyAllWindows()

D cv2.closeWindows()

cv2.destroyAllWindows() closes all OpenCV image windows.

Explain how to display an image using OpenCV and keep the window open until a key is pressed.

Think about the functions needed to show and pause the image window.

Describe the difference in color formats between OpenCV and matplotlib and how to fix color issues when displaying images.

Consider how OpenCV loads colors and what matplotlib expects.

Practice

1. What is the main purpose of using cv2.imshow in computer vision?

easy

A. To resize an image

B. To save an image to disk

C. To convert an image from BGR to RGB

D. To open a window that displays an image

Solution

1. Step 1: Understand the function of cv2.imshow

   cv2.imshow is used to open a new window that shows the image you provide.

2. Step 2: Differentiate from other functions

   Saving images uses cv2.imwrite, color conversion uses cv2.cvtColor, and resizing uses cv2.resize.

3. Final Answer:

   To open a window that displays an image -> Option D

4. Quick Check:

   cv2.imshow shows images in a window [OK]

Hint: cv2.imshow always opens a window to show images [OK]

Common Mistakes:

• Confusing cv2.imshow with saving or converting images
• Forgetting that cv2.imshow opens a separate window
• Thinking cv2.imshow changes image data

2. Which of the following is the correct sequence to display an image using OpenCV in Python?

easy

A. cv2.imshow(), cv2.waitKey(), cv2.destroyAllWindows()

B. cv2.waitKey(), cv2.imshow(), cv2.destroyAllWindows()

C. cv2.destroyAllWindows(), cv2.imshow(), cv2.waitKey()

D. cv2.imshow(), cv2.destroyAllWindows(), cv2.waitKey()

Solution

1. Step 1: Recall the correct order of OpenCV display functions

   First, cv2.imshow() opens the image window, then cv2.waitKey() waits for a key press, and finally cv2.destroyAllWindows() closes the window.

2. Step 2: Check the options order

   Only cv2.imshow(), cv2.waitKey(), cv2.destroyAllWindows() follows this correct sequence.

3. Final Answer:

   cv2.imshow(), cv2.waitKey(), cv2.destroyAllWindows() -> Option A

4. Quick Check:

   Display, wait, then close windows [OK]

Hint: Always call waitKey after imshow before destroying windows [OK]

Common Mistakes:

• Calling destroyAllWindows before waitKey
• Not calling waitKey causing window to close immediately
• Mixing order of functions

3. What will be the output of this code snippet?

import cv2
import matplotlib.pyplot as plt
img = cv2.imread('image.jpg')
plt.imshow(img)
plt.show()

medium

A. The image displays with correct colors

B. The image displays but colors look incorrect (blue and red swapped)

C. The code throws an error because plt.imshow cannot display images

D. The image window opens but closes immediately

Solution

1. Step 1: Understand color format difference

   OpenCV loads images in BGR format, but matplotlib expects RGB format.

2. Step 2: Effect on plt.imshow

   Displaying BGR image directly with plt.imshow causes colors to appear swapped, especially red and blue.

3. Final Answer:

   The image displays but colors look incorrect (blue and red swapped) -> Option B

4. Quick Check:

   OpenCV BGR images show wrong colors in matplotlib [OK]

Hint: Convert BGR to RGB before plt.imshow to fix colors [OK]

Common Mistakes:

• Assuming plt.imshow shows correct colors without conversion
• Confusing BGR and RGB formats
• Expecting plt.imshow to throw error on BGR images

4. You wrote this code to display an image but the window closes immediately. What is the error?

import cv2
img = cv2.imread('photo.png')
cv2.imshow('Photo', img)
cv2.destroyAllWindows()

medium

A. Missing cv2.waitKey() call after cv2.imshow()

B. cv2.destroyAllWindows() should be before cv2.imshow()

C. cv2.imread() cannot read PNG files

D. Window name 'Photo' is invalid

Solution

1. Step 1: Identify missing waitKey()

   Without cv2.waitKey(), the window opens and closes immediately because the program does not wait for a key press.

2. Step 2: Confirm other options are incorrect

   Destroying windows before showing is wrong, cv2.imread supports PNG, and window names can be any string.

3. Final Answer:

   Missing cv2.waitKey() call after cv2.imshow() -> Option A

4. Quick Check:

   Always call waitKey to pause window [OK]

Hint: Always add cv2.waitKey() after imshow to keep window open [OK]

Common Mistakes:

• Forgetting waitKey causes window to close instantly
• Thinking destroyAllWindows controls window display timing
• Assuming cv2.imread can't read PNG images

5. You want to display an image inside a Jupyter notebook using matplotlib with correct colors. Which code snippet is correct?

hard

A. import cv2
import matplotlib.pyplot as plt
img = cv2.imread('img.jpg')
plt.imshow(img)
plt.show()

B. import matplotlib.pyplot as plt
img = cv2.imread('img.jpg')
plt.imshow(img)
plt.show()

C. import cv2
import matplotlib.pyplot as plt
img = cv2.imread('img.jpg')
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
plt.imshow(img_rgb)
plt.show()

D. import cv2
img = cv2.imread('img.jpg')
cv2.imshow('Image', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

Solution

1. Step 1: Understand color format for matplotlib display

   OpenCV loads images in BGR format, but matplotlib expects RGB, so conversion is needed.

2. Step 2: Check each option

   import cv2 import matplotlib.pyplot as plt img = cv2.imread('img.jpg') plt.imshow(img) plt.show() misses color conversion, so colors will be wrong. import cv2 import matplotlib.pyplot as plt img = cv2.imread('img.jpg') img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) plt.imshow(img_rgb) plt.show() converts BGR to RGB correctly before display. import matplotlib.pyplot as plt img = cv2.imread('img.jpg') plt.imshow(img) plt.show() misses cv2 import (NameError) and color conversion. import cv2 img = cv2.imread('img.jpg') cv2.imshow('Image', img) cv2.waitKey(0) cv2.destroyAllWindows() uses cv2.imshow which opens a separate window, not inside notebook.

3. Final Answer:

   correctly converts BGR to RGB and displays image inside notebook -> Option C

4. Quick Check:

   Convert BGR to RGB before matplotlib display [OK]

Hint: Convert BGR to RGB before plt.imshow for correct colors [OK]

Common Mistakes:

• Skipping color conversion causing wrong colors
• Using cv2.imshow inside notebooks expecting inline display
• Assuming plt.imread always works for all image types