Face Recognition Attendance System Web App Deploy in AWS

Name: Face Recognition Attendance System Web App Deploy in AWS
Rating: 4.3 (225 reviews)

Build a Comprehensive Attendance System web app using Face Recognition, Machine Learning, Redis, Python, Streamlit

Created byG Sudheer, datascience Anywhere, VedicSkill Academy

Last updated 6/2025

English

What you'll learn

Real Time Live Attendance System
Detect and Idenify person name and person role with Face Recognition
Develop 3 Streamlit Web App
Integrate Face Recognition Model with Redis Database
Learn about Redis with Python
App-1: Real Time Live Attendance System
App-2: Registration Form for new teachers and students
App-3: Reporting

Course content

14 sections • 119 lectures • 12h 40m total length

Introduction9:25
Course Curriculum1:57
Complete Resources0:02
OpenCV with Python0:52

Useful links0:02
Setting up Redis cloud8:22
This lesson explains to setup a free subscription and database in redis cloud
Connect notebook to Redis CLI (Client) using host, port and password3:35
This lesson explain further details about redis cloud database like hostname, port number and security setting like username and password. Also in this lesson we explains how to connect to external notebook like https://rbook.cloud/
Redis Data Structures3:18
This lesson explain the common data structures that we store data in redis and gives brief description about different data structure
Redis: Strings commands ("set", "get")4:52
In this lesson we will do deep dive into string data structure of redis and backend processing of redis. Also we will explain two commands
SET (set a string value of a key)
GET (get a value of a key)
Redis: String - SET part 24:54
In this lesson you learn more details of SET command and different options/flags of the command like NX, XX, EX, PX, EXAT, PXAT, GET etc.
Redis: String - Part 34:33
Redis: String - Part 43:34
Redis: String - part 54:37
Redis: String - part 64:54
Redis String: String (additional commands)4:56
Intro to Redis with Python10:42
Redis List6:07
Redis List part 28:21
Redis List part 311:34
Redis List part 49:00
Redis List part 57:59

Useful Links0:03
Automatic Fast Face Recongnition System Intro5:04
What and Why Insightface1:22
InsightFace Install6:42
Import insightface & how to solve common error import error9:10
Configure Pretrained Models of Insightface in python10:08
Assignment Solution: Configure "bufallo_sc" model2:19
Get Face Analysis results/report from Insightface python4:46
Draw bounding box, Key points, Age, Gender for multiple faces part -17:29
Draw bounding box, Key points, Age, Gender for multiple faces part -211:37
Assignment Solution: bbox, keypoints, score for buffalo_sc model9:07

Introduction to Attendance System and What we are building in this course3:53
Flow Diagram of Attendance System5:34
Get Data & Understand the folder structure of data3:44
Fast Face Recognition: Data Preparation in Python9:53
Fast Face Recognition (FFR): Data Preparation - Clean Text (labels)5:38
FFR: Data Preparation - define path of all images3:45
FFR: Data Preparation - Extract Facial Embeddings from all images9:39
Predicting Person name part 19:12
Machine Learning (ML) Search Algorithm - Euclidean Distance7:47
ML Search Algorithm - Manhattan Distance2:32
ML Search Algorithm - Chebyshev Distance1:49
ML Search Algorithm - Minkowski Distances1:09
ML Search Algorithm - Cosine Similarity6:20
Distance vs Similarity methods4:19
ML Search Algorithm - Distance Method6:08
ML Search Algorithm - Similarity Method4:01
ML Search Algorithm in Python7:05
Analyzing Euclidean , Manhattan and Cosine values for test image10:09
Predicting Person Name with Euclidean Distance5:10
Predicting Person Name with Manhattan Distance2:17
Predicting Person Name with Cosine similarity3:30
Advantages of Cosine similarity over Euclidean and Manhattan Distance.1:55
Identify Multiple Person Name in one image part 14:25
Identify Multiple Person Name in one image part 28:15
Identify Multiple Person Name in one image part 311:44
Identify Multiple Person Name in one image part 44:27
Optimize Collected data (facial embeddings) and save4:31
Optimize Collected data (facial embeddings) and save part 25:25

Streamlit App Intro1:32
Create Home and connect all Pages from Home page6:28
Import face_rec into app and retrive data from Redis9:16
Apply Spinner to face_rec and reduce the time to start the app5:37
Real Time Person name detection using streamlit webrtc8:42
Find time at which person name is detected6:59
Save Logs (person name and time) in Redis database3:04
Save Logs (person name and time) in Redis database part 219:40
Show Logs in Streamlit Report5:44
Show Logs: Add refresh button1:13
Show Logs: Create tabs for Registered users and Logs3:21
Testing logs2:26
Registration Form part 18:26
Registration Form Part 217:28
Registration Form part 35:09
Registration Form part 417:35
Testing Registration form6:00

Requirements

At least beginner to Python
Atleast begineer on Pandas, Numpy and OpenCV libraries

Description

This course is designed to teach you how to create a Complete Attendance System using Face Recognition technology. You will learn the principles of face recognition, image processing, and machine learning algorithms that enable the creation of an accurate and reliable attendance system.

Throughout the course, you will use Python programming language and various libraries, such as OpenCV, Numpy, Pandas, Insightface, Redis to build a comprehensive attendance system. You will start by learning the basics of face detection, feature extraction, and face recognition algorithms. Then, you will integrate these algorithms with the attendance system that you will build from scratch.

By the end of the course, you will have a complete attendance system that is capable of identifying people and marking their attendance based on their facial features. This course is suitable for beginners in programming and machine learning, and no prior knowledge of face recognition is required.

Topics covered in this course include:

Introduction to face recognition and attendance systems
Basic image processing techniques
Feature extraction and dimensionality reduction
Face detection and recognition algorithms
Machine learning for face recognition
Building an attendance system with face recognition
Redis with Python
Integrate Redis and Face Recognition system.
Registration Form (Add new person data)
Streamlit for webapp
Real Time Prediction App
- Registration Form
- Report

By the end of this course, you will have a strong understanding of how to create a complete attendance system using face recognition technology. You will also have the skills to apply this knowledge to other computer vision applications.

See you inside the course.

Who this course is for:

Anyone who like to develop End to End Face Recognition based Attendance System.

Face Recognition Attendance System Web App Deploy in AWS

What you'll learn

Explore related topics

Course content

Introduction4 lectures • 12min

Setting up Environment5 lectures • 22min

Redis as Database Crash Course [Python]: Optional17 lectures • 1hr 41min

Face Recognition with InsightFace API11 lectures • 1hr 8min

Attendance System : Fast Face Recognition28 lectures • 2hr 34min

Attendance System : Registration Form & Integrate to Redis6 lectures • 44min

Attendance System : Real Time Person name detection6 lectures • 40min

WEB APP Installations2 lectures • 10min

Attendance Web App17 lectures • 2hr 9min

Additional Lectures1 lecture • 7min

Requirements

Description

Who this course is for: