This course will help you delve into face recognition using Python without having to deal with all the complexities and mathematics associated with the deep learning process.
You will start with an introduction to face detection and face recognition technology. After this, you’ll get the system ready by installing the Anaconda package and other dependencies and libraries. You’ll then write Python code to detect faces from a given image and extract the faces as separate images. Next, you’ll focus on face detection by streaming a real-time video from the webcam.
Customize the face detection program to blur the detected faces dynamically from the webcam video stream. You’ll also learn facial expression recognition and age and gender prediction using a pre-trained deep learning model.
Later, you’ll progress to writing Python code for face recognition, which will help identify the faces that are already detected. Then you’ll explore the concept of face distance and tweak the face landmark points used for face detection.
By the end of this course, you’ll be well-versed with face recognition and detection and be able to apply your skills in the real world.
Become well-versed with face detection and face recognition technology
Understand how to install the Anaconda package
Install dependencies and libraries such as dlib, OpenCV, and Pillow
Learn how to perform face detection and face recognition
Use the face distance parameter to calculate the magnitude of faces
Create custom face make-up for an image with face landmark points