Why video extends CV to temporal data in Computer Vision - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load a video file using OpenCV.

Computer Vision

import cv2
video = cv2.VideoCapture([1])

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

A'video.mp4'

Bvideo.mp4

Copen('video.mp4')

Dcv2.VideoCapture('video.mp4')

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting quotes around the file name causes errors.

Passing the function call inside itself is incorrect.

We need to pass the video file name as a string to cv2.VideoCapture. So, the correct answer is 'video.mp4' with quotes.

2fill in blank

medium

Complete the code to read a frame from the video.

Computer Vision

ret, frame = video.[1]()

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

Aread_frame

Bget_frame

Ccapture

Dread

Attempts:

3 left

💡 Hint

Common Mistakes

Using non-existent methods like read_frame() or get_frame().

The method to read a frame from a video in OpenCV is read().

3fill in blank

hard

Fix the error in the code to convert a frame to grayscale.

Computer Vision

gray = cv2.cvtColor(frame, [1])

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Acv2.COLOR_RGB2GRAY

Bcv2.COLOR_BGR2GRAY

Ccv2.COLOR_GRAY2BGR

Dcv2.COLOR_BGR2RGB

Attempts:

3 left

💡 Hint

Common Mistakes

Using RGB to GRAY conversion when the image is BGR.

Using conversion codes that change color order instead of to grayscale.

To convert a BGR image to grayscale, use cv2.COLOR_BGR2GRAY.

4fill in blank

hard

Fill the blank to create a dictionary of frame numbers and their grayscale frames for frames where the frame number {{BLANK_1}} 10 and the frame is not None.

Computer Vision

frames_dict = {i: gray_frame for i, gray_frame in enumerate(frames) if i [1] 10 and gray_frame is not None}

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

A<

B>

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using > or == instead of <.

Confusing the condition with frame content checks.

We want frames with frame number less than 10, so the operator is <.

5fill in blank

hard

Fill all three blanks to create a list of frame differences between consecutive grayscale frames.

Computer Vision

diffs = [cv2.absdiff(frames[i], frames[i [1] [2]]) for i in range([3], len(frames))]

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

A-

B+

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using addition instead of subtraction.

Starting range at 0 causing index errors.

Using wrong index offset.

To get differences between consecutive frames, subtract the previous frame (i-1) from the current frame i. The range starts at 1 to avoid index error.