Real-time processing patterns in Computer Vision - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to capture video frames in real-time using OpenCV.

Computer Vision

import cv2

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.[1]()
    if not ret:
        break
    cv2.imshow('Frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

Drag options to blanks, or click blank then click option'

Acapture

Bread

Cget

Dgrab

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'grab()' which only grabs the frame but does not decode it.

Using 'get()' which retrieves properties, not frames.

The method 'read()' captures a frame from the video stream and returns a success flag and the frame itself.

2fill in blank

medium

Complete the code to convert a captured frame to grayscale for faster processing.

Computer Vision

import cv2

frame = cv2.imread('image.jpg')
gray = cv2.[1](frame, cv2.COLOR_BGR2GRAY)

Drag options to blanks, or click blank then click option'

AconvertColor

BtransformColor

CchangeColor

DcvtColor

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'convertColor' which is not a valid OpenCV function.

Using 'changeColor' or 'transformColor' which do not exist.

The correct OpenCV function to convert color spaces is 'cvtColor'.

3fill in blank

hard

Fix the error in the code to apply a Gaussian blur to the frame.

Computer Vision

import cv2

frame = cv2.imread('image.jpg')
blurred = cv2.GaussianBlur(frame, ([1], 5), 0)

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A7

B3

C5

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 or even numbers which cause errors.

Using mismatched kernel sizes.

The kernel size must be a tuple of odd numbers. (5,5) is valid; here the first value is missing and should be 5.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps frame indices to their grayscale versions.

Computer Vision

frames_gray = {i: cv2.[1](frame, cv2.COLOR_BGR2GRAY) for i, frame in enumerate(frames) if i [2] 5}

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AcvtColor

B<

C>

DconvertColor

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'convertColor' which is invalid.

Using '>' which selects frames after index 5.

Use 'cvtColor' to convert frames to grayscale and '<' to select frames with index less than 5.

5fill in blank

hard

Fill all three blanks to create a dictionary of frame indices and their blurred grayscale frames for frames with index greater than 2.

Computer Vision

blurred_frames = {i: cv2.GaussianBlur(cv2.[1](frame, cv2.COLOR_BGR2GRAY), ([2], [3]), 0) for i, frame in enumerate(frames) if i > 2}

Drag options to blanks, or click blank then click option'

AcvtColor

B3

DconvertColor

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'convertColor' which is invalid.

Using even kernel sizes or zeros.

Use 'cvtColor' to convert to grayscale and (3,3) as the kernel size for Gaussian blur.