Packt
Computer Vision: Face Recognition Quick Starter in Python
Packt

Computer Vision: Face Recognition Quick Starter in Python

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

7 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

7 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Explain the principles of face detection and face recognition technology.

  • Install and configure dependencies and libraries such as dlib, OpenCV, and Pillow.

  • Execute face detection and face recognition tasks using Python.

Details to know

Shareable certificate

Add to your LinkedIn profile

Recently updated!

September 2024

Assessments

9 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 26 modules in this course

In this module, we will introduce the course, providing an overview of the topics to be covered, and discuss the significance of face recognition in various applications. We'll also present the structure and objectives of the course to set clear expectations.

What's included

2 videos1 reading

In this module, we will set up the development environment by installing the Anaconda package. This will prepare our computer for Python coding, ensuring that we have the necessary tools and libraries for face recognition tasks.

What's included

1 video

In this module, we will cover essential Python programming basics, including assignments, flow control, data structures, and functions. This foundational knowledge is crucial for understanding and implementing face recognition algorithms.

What's included

4 videos

In this module, we will install the necessary dependencies and libraries required for face recognition. We will also address common issues with DLib and ensure the environment is correctly configured for our projects.

What's included

3 videos

In this module, we will introduce face detectors, discussing their importance and the different techniques used for detecting faces. This knowledge is fundamental for implementing effective face recognition solutions.

What's included

1 video1 assignment

In this module, we will implement face detection in code using the face_recognition and OpenCV libraries. We will cover practical coding examples and ensure a thorough understanding of face detection implementation.

What's included

2 videos

In this module, we will address the common issue of the cv2.imshow() function not responding while displaying images. We will implement a fix and verify that the display window functions correctly.

What's included

1 video

In this module, we will detect and locate faces from a real-time webcam video feed. We will cover the steps required to implement and optimize real-time face detection for practical applications.

What's included

2 videos1 assignment

In this module, we will detect and locate faces in pre-recorded video files. We will discuss the implementation details and performance considerations for video-based face detection.

What's included

1 video

In this module, we will blur detected faces in real-time video to ensure privacy. We will cover the implementation and testing of face blurring techniques in a real-time context.

What's included

1 video

In this module, we will install the libraries required for real-time facial expression detection. Proper installation and configuration are essential for the subsequent implementation of facial expression detection.

What's included

1 video1 assignment

In this module, we will detect facial expressions from a real-time webcam video feed. We will implement the necessary algorithms and optimize the detection process for accurate and efficient performance.

What's included

2 videos

In this module, we will delve into the techniques for detecting facial expressions in video footage. We will explore methods to identify and analyze emotions based on facial cues, and implement algorithms that enhance the accuracy of facial expression recognition.

What's included

1 video

In this module, we will detect facial expressions in static images. We will discuss the implementation and validation of image-based facial expression detection techniques.

What's included

1 video1 assignment

In this module, we will introduce age and gender detection, discussing their significance and applications. We will provide an overview of the steps involved in implementing real-time age and gender classification.

What's included

1 video

In this module, we will perform real-time age and gender classification on webcam video feed. We will focus on the implementation, optimization, and validation of the detection algorithms.

What's included

1 video

In this module, we will classify the age and gender of faces in static images. We will cover the implementation and validation of image-based detection algorithms.

What's included

1 video1 assignment

In this module, we will introduce face recognition, discussing its applications and underlying principles. We will also address the challenges and solutions involved in face recognition technology.

What's included

1 video

In this module, we will implement face recognition algorithms to detect and recognize faces in images. We will cover the coding and optimization techniques required for an effective face recognition system.

What's included

2 videos

In this module, we will detect and recognize faces from a real-time webcam video feed. We will focus on implementing and optimizing real-time face recognition algorithms.

What's included

2 videos1 assignment

In this module, we will detect and recognize faces in pre-recorded video files. We will discuss the implementation details and performance evaluation of video-based face recognition.

What's included

1 video

In this module, we will calculate the distance between faces for advanced analysis. We will cover the implementation and optimization of face distance algorithms.

What's included

2 videos

In this module, we will learn how to visualize and customize face landmarks in images. We will cover the implementation and testing of face landmark visualization techniques.

What's included

2 videos1 assignment

In this module, we will visualize and customize face landmarks for multiple faces in both real-time and pre-saved videos. We will focus on the implementation, optimization, and testing of multi-face landmark visualization techniques.

What's included

2 videos

In this module, we will demonstrate how to customize face landmarks to apply simple makeup. We will cover the implementation and testing of face makeup techniques using face landmarks.

What's included

1 video

In this module, we will demonstrate face makeup in a real-time video using face landmarks. We will focus on implementing, optimizing, and validating real-time face makeup algorithms.

What's included

1 video2 assignments

Instructor

Packt
Packt
170 Courses2,469 learners

Offered by

Packt

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

New to Data Analysis? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions