Face, Age, Gender, Emotion Recognition Using Facenet Model

Name: Face, Age, Gender, Emotion Recognition Using Facenet Model
Rating: 4.2 (47 reviews)

Complete Face Recognition, Age, Gender, Emotion System Using DeepFace Model

Created byARUNNACHALAM SHANMUGARAAJAN

Last updated 1/2025

English

English [Auto],

What you'll learn

Understand the basics of facial recognition technology and its applications.
Extract age, gender, and emotional data from images and video streams.
Process and analyze real-time data using DeepFace for practical applications.
Test and deploy the system in real-world scenarios.

Course content

1 section • 6 lectures • 1h 0m total length

INTRODUCTION TO COURSE0:39
Explore a complete facial recognition project with age, gender, and emotion detection using a deep face model, including data set creation, training, and recognition across three modules.
CLASS 1 : IMPORT PACKAGES FOR PROJECT3:50
Learn to set up a PyCharm or VSCode project, install OpenCV and OpenCV contrib, and import OS, cv2, numpy, and deep face to enable facial recognition.
CLASS 2 : CREATE FACE DATASET USING OPENCV13:22
Create a dataset by making a data set directory and per-person folders, then capture and save facial images with OpenCV, grayscale conversion, and haar cascade bounding box detection.
CLASS 3 : TRAIN FACE DATASET USING DEEP FACE MODEL6:11
Train the dataset using the deep face model to extract facial features as embeddings with the facenet model; loop through images to build and store embeddings.
CLASS 4 : RECOGNIZE DATASET USING DEEP FACE MODEL22:47
Recognize facial images with gender, age, and emotion using the deep face model and FaceNet embeddings in real time via a webcam.
CLASS 5 : FACIAL RECOGNITION PROJECT OUTPUT13:33
Learn to build a facial recognition project with age, gender, and emotion detection using deep face, including creating, training, and recognizing datasets with embeddings.
FACIAL RECOGNITION ASSIGNEMENT

Requirements

Basic Python & Deep Learning Concepts Required

Description

Unlock the power of Artificial Intelligence (AI) and revolutionize your understanding of facial recognition systems with our comprehensive course, "Face, Age, Gender, Emotion Recognition Using Facenet Model" This course is meticulously designed for beginners and professionals aiming to build cutting-edge AI applications using Python and the popular DeepFace library.

With facial recognition technology being pivotal in security, healthcare, marketing, and entertainment, this course provides you with the expertise to design and implement systems capable of recognizing faces, predicting age, identifying gender, and detecting emotions—all in one solution.

Why Enroll in This Course?

Whether you're a developer, data scientist, student, or AI enthusiast, this course takes you from the basics to an advanced level, ensuring you have the confidence to apply these technologies in real-world scenarios.

Key Features of the Course:

Learn Facial Recognition Basics:
- Understand the science behind facial recognition.
- Explore key concepts like feature extraction and face matching.
Master the DeepFace Library:
- Set up and use the DeepFace library, a leading tool for facial analysis.
- Implement robust models for facial recognition and emotion detection.
Build an All-in-One System:
- Develop a system that detects age, gender, and emotions with high precision.
- Work with real-time data for practical applications.
Hands-On Projects and Implementation:
- Get hands-on coding experience in Python.
- Analyze images, video streams, and live feeds.
Deploy Your Solution:
- Learn best practices for deploying your system.
- Make your project ready for professional or academic use.

Don’t miss this chance to become an expert in facial recognition and AI-driven applications. Join the course now and gain lifetime access to practical knowledge, coding demonstrations, and valuable tips to excel in your AI career.

Who this course is for:

This course is designed for developers, students, and professionals