Published 2/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 949.85 MB | Duration: 1h 15m
Learn Complete Face Recognition Using SQL Database Project From Scratch
What you’ll learn
Understand the fundamentals of face recognition technology and its applications.
Learn how to design and create a SQL database schema for storing facial features.
Dive into the process of extracting facial features from images using OpenCV.
Establish connections between the face recognition algorithms and the SQL database.
Requirements
Basic knowledge of SQL and database management.
Familiarity with Python programming and OpenCV library (helpful but not required).
Description
Course Title: Complete Face Recognition Using SQL Database Project From ScratchCourse Description:Welcome to the “Complete Face Recognition Using SQL Database Project From Scratch” course! In this comprehensive project-based course, you will embark on an exciting journey to create a robust face recognition system using SQL databases. From setting up the project environment to implementing advanced recognition algorithms, this course will equip you with the skills needed to build an efficient and secure face recognition application from the ground up.What You Will Learn:Introduction to Face Recognition:Understand the fundamentals of face recognition technology and its applications.Learn about the importance of databases in storing and managing facial data.Setting Up the Project Environment:Explore how to set up a SQL database environment on your local machine or server.Install necessary tools and libraries for face recognition integration with SQL.Creating the Facial Database:Learn how to design and create a SQL database schema for storing facial features.Understand the structure of the database tables and relationships.Facial Feature Extraction and Encoding:Dive into the process of extracting facial features from images using OpenCV.Explore how to encode and store these features in the SQL database for comparison.Face Detection and Recognition Algorithms:Implement face detection algorithms to locate faces within images or video streams.Learn about various recognition algorithms such as Eigenfaces, Fisherfaces, and LBPH.Integration with SQL Database:Establish connections between the face recognition algorithms and the SQL database.Store and retrieve facial features and recognition results efficiently.Why Enroll:Hands-On Project Development: Engage in a complete project, from database design to user interface development.Practical Skills Application: Apply face recognition algorithms in a real-world scenario using SQL databases.Career Enhancement: Gain valuable experience in a cutting-edge technology field with practical project work.Embark on this exciting journey to create a comprehensive face recognition system using SQL databases. By the end of this course, you’ll have a fully functional project to showcase your skills in face recognition technology and SQL database integration. Enroll now and bring your face recognition project to life!
Overview
Section 1: Introduction To Complete Face Recognition Using SQL Database Project
Lecture 1 Introduction To Complete Face Recognition Using SQL Database Project
Lecture 2 FACE RECOGNITION PROJECT INTRO
Section 2: DATASET CREATER MODULE COURSE – FACE RECOGNITION PROJECT
Lecture 3 DATASET CREATER CLASS 1 – IMPORT PACKAGES
Lecture 4 DATASET CREATER CLASS 2 – SQL DATABASE CONNECTION
Lecture 5 DATASET CREATER CLASS 3 – OUTPUT AND EXPLANATION
Section 3: TRAINING MODULE COURSE – FACE RECOGNITION PROJECT
Lecture 6 TRAINING CLASS 1 – IMPORT PACKAGES
Lecture 7 TRAINING CLASS 2 – LBPH FACE RECOGNIZER AND OPENCV
Lecture 8 TRAINING CLASS 3 – OUTPUT AND EXPLANATION
Section 4: FACE RECOGNITION MODULE COURSE – FACE RECOGNITION PROJECT
Lecture 9 FACE RECOGNITION CLASS 1 – IMPORT PACKAGES
Lecture 10 FACE RECOGNITION CLASS 2 – FACE DETECT AND SQL DATABASE
Lecture 11 FACE RECOGNITION CLASS 3 – OUTPUT AND EXPLANATION
Students and professionals in computer vision, security systems, and biometrics.,Developers interested in learning face recognition technology and its integration with SQL databases.
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