Rasberry Pi Facial Recognition Door Lock
Created by
Ashraf S.A Almadhoun
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1 Hours
10 Lesson
Created by
0.00 Star (0)
1 Hours
10 Lesson
$51.99
Welcome to the "Raspberry Pi Facial Recognition Door Lock" course! This hands-on course is designed for hobbyists, tech enthusiasts, and students who are eager to dive into the exciting world of Raspberry Pi projects, IoT, and computer vision. In this course, you will learn how to build a functional and secure facial recognition door lock system using a Raspberry Pi.
Throughout the course, you will gain practical experience in setting up your Raspberry Pi, configuring necessary software, and writing Python scripts to capture and recognize facial features. You will also understand how to train a facial recognition model and integrate it with a physical door lock mechanism. Additionally, you will explore how to manage cloud services like Adafruit IO and remotely access your Raspberry Pi for ease of use and monitoring.
By the end of this course, you will have a comprehensive understanding of integrating hardware and software to create a real-world application. Whether you are a tech enthusiast looking to expand your knowledge or a student seeking a practical project, this course will provide you with the skills and confidence to bring your ideas to life.
Join us on this exciting journey and unlock the power of facial recognition with Raspberry Pi!
Basic understanding of programming in Python.
Raspberry Pi (any model supporting camera interface).
Raspberry Pi camera module.
Internet connection for accessing resources and installing libraries.
Basic electronic components (if you wish to connect the door lock system).
A willingness to learn and explore new technologies!
Hobbyists and tinkerers interested in Raspberry Pi projects.
Tech enthusiasts who want to explore facial recognition and IoT.
Students and educators looking for a practical application of computer vision.
Anyone curious about integrating hardware and software for a real-world project.
Introduction to the project and its objectives.
Understanding and setting up the required files and folders.
Creating and managing an Adafruit IO account.
Setting up a Python editor for coding.
Writing and testing a script for capturing face shots using OpenCV.
Training a facial recognition model.
Testing the trained model.
Implementing and testing a face recognition system for a door lock.
Testing the overall face recognition system.
Accessing Raspberry Pi remotely.
Introduction
1 Lessons
0H 3M
3m 22s
Making Everything Ready
2 Lessons
0H 10M
Coding the Open Script OpenCV
2 Lessons
0H 21M
Coding Training Model
2 Lessons
0H 16M
14m 19s
Testing Face Recognition
1 Lessons
0H 4M
4m 57s
Making and Testing Door Lock using Face Recognition
1 Lessons
0H 11M
Resources
1 Lessons
0H 9M
Dragon Zap Instructor
I've always tried to live life presently and to the fullest. Some of the things I love to do in my spare time include football, biking, traveling to new places, watching sports (huge football fan here!), and sharing meals with friends and family. In 2012, I graduated with my Bachelor of Mechatronics Engineering at Azhar University - one of the top schools in the country. While there, I was fortunate to make Embedded Systems project using Arduino, PIC Microcontroller and other modules. After graduating, I worked at My own university as a Teacher Assistant . I followed that stint with a contract at a local College where I discovered how amazing it is to share your knowledge offline, which made me eager and eventually found myself starting my own online learning journey. I helped more than 100k student since then. Most recently. Throughout this time I built my Educational Engineering School Online brand to teach others the skills that I have. Now I only do things I love each day. I want to show you how to be a better Embedded System creator, make money from your skills, and live the life you dreamed of.
$51.99
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Free Exercises File
Watch online or offline
Certificate of Completion
Ashraf S.A Almadhoun
Metla Sudha Sekhar
Ashraf S.A Almadhoun
Sonar Systems
Sonar Systems
