Computer Vision: Face Recognition Quick Starter in Python

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Course Features

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Duration

4.15 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4.15 hours

Course Description

This course offers a comprehensive introduction to face recognition using Python without requiring a deep understanding of mathematics or complex deep learning concepts. The course covers various topics, including face detection technology, face recognition technology, and the installation of the necessary software dependencies.

Throughout the course, you will learn how to extract and detect faces from images and real-time video captured by a webcam. You will also have the opportunity to customize the face detection program to blur faces detected in the video stream. The course utilizes a pre-trained deep-learning model to recognize facial expressions and predict age and gender.

Additionally, you will learn how to write Python code for face recognition, allowing you to identify faces that have been detected. The course also delves into face distance and modifying landmark points for more accurate face detection.

This course is designed for beginners and individuals interested in learning Python-based face recognition techniques. By completing this course, you will gain practical skills that can be applied in real-world scenarios.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Use Python to detect and recognize faces from images and real-time webcam video

Become well-versed with emotion detection

Get up to speed with predicting age and gender from images and real-time webcam video

Target Students

This course is designed for beginners or anyone who wants to get started with Python-based face recognition

Course Instructors

Abhilash Nelson

Instructor

Abhilash Nelson is the instructor for this course
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