Practice Detect Faces In An Image (21.5.2) - OpenCV - CBSE 10 AI (Artificial Intelleigence)
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Detect Faces in an Image

Practice - Detect Faces in an Image

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What function is used to convert a color image to grayscale in OpenCV?

💡 Hint: Think of the function that changes color formats.

Question 2 Easy

What is the role of the Haar Cascade classifier in face detection?

💡 Hint: It's a model trained to recognize specific objects.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What must you do before detecting faces in an image?

Convert to RGB
Convert to Grayscale
Resize the image

💡 Hint: What does simplifying the image help with?

Question 2

True or False: The Haar Cascade classifier is trained to recognize various objects beyond just faces.

True
False

💡 Hint: Consider the versatility of the model.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Create a Python script that detects and highlights faces in an image and writes a brief report discussing the choices made for parameters.

💡 Hint: Think about how to balance accuracy and speed.

Challenge 2 Hard

Design an algorithm combining face detection with emotion recognition, detailing how you'd implement both techniques in your code.

💡 Hint: What data will you need for emotion recognition?

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.